",isbn:"978-1-80356-963-5",printIsbn:"978-1-80356-962-8",pdfIsbn:"978-1-80356-964-2",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,isSalesforceBook:!1,isNomenclature:!1,hash:"8eeb7ab232fa8d5c723b61e0da251857",bookSignature:"Dr. Soumen Dhara and Dr. Gorachand Dutta",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11513.jpg",keywords:"Fabrication Technologies, Applications, Characterizations, Case Studies, Various Gas Sensors, Improvement of Lifestyle, Societal Benefit, Bio-Sensors, Bioreceptor Molecules, Integration, Packaging, Lab-on-Chip",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"April 8th 2022",dateEndSecondStepPublish:"June 17th 2022",dateEndThirdStepPublish:"August 16th 2022",dateEndFourthStepPublish:"November 4th 2022",dateEndFifthStepPublish:"January 3rd 2023",dateConfirmationOfParticipation:null,remainingDaysToSecondStep:"23 days",secondStepPassed:!1,areRegistrationsClosed:!1,currentStepOfPublishingProcess:2,editedByType:null,kuFlag:!1,biosketch:"A pioneering researcher in nanowire heterostructures and laser spectroscopy, recipient of JSPS (Govt. of Japan) and NPDF (Govt. of India) fellowships, and member of MRS(USA), MRS(India), IPA(India).",coeditorOneBiosketch:"Assistant Professor with the School of Medical Science and Technology, Indian Institute of Technology Kharagpur with research interests that include the design and characterization of portable biosensors, biodevices, and sensor interfaces for miniaturized systems and biomedical applications for point-of-care testing.",coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"196334",title:"Dr.",name:"Soumen",middleName:null,surname:"Dhara",slug:"soumen-dhara",fullName:"Soumen Dhara",profilePictureURL:"https://mts.intechopen.com/storage/users/196334/images/system/196334.jpeg",biography:"Dr. Dhara received his Ph. D in Physics in 2012 from Indian Institute of Technology Guwahati, India. Presently, he is associated with the Faculty of Science, Sri Sri University, India as an Assistant Professor in Physics. Prior to joining the current\naffiliation, he was a postdoctoral fellow at different renowned institutions, Kobe University Japan, S. N. Bose National Centre for Basic Sciences, India and Cardiff University, United Kingdom. He was awarded prestigious JSPS postdoctoral fellowship based on his research contribution on semiconducting nanowires. He has published more than 32 research articles including 1 review article in high profile international journals and 3 book chapters to his credit. His research trust areas of interests are semiconductor nanostructures, optoelectronics, solid state lighting and light sensors, spectroscopy of nanomaterials, thin-film transistors (TFTs) etc.",institutionString:"Sri Sri University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"2",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Sri Sri University",institutionURL:null,country:{name:"India"}}}],coeditorOne:{id:"442408",title:"Dr.",name:"Gorachand",middleName:null,surname:"Dutta",slug:"gorachand-dutta",fullName:"Gorachand Dutta",profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:"Dr. Gorachand Dutta, PhD is an Assistant Professor with the School of MedicalScience and Technology, Indian Institute of Technology Kharagpur. His research interests include the design and characterization of portable\r\nbiosensors, biodevices and sensor interfaces for miniaturized systems and biomedical applications for point-of-care testing. He received his Ph.D in Biosensor and Electrochemistry from Pusan National University, South Korea,\r\nwhere he developed different class of electrochemical sensors and studied the electrochemical properties of gold, platinum, and palladium based metal electrodes. He completed his Post-doctoral fellowships in the Department of\r\nMechanical Engineering, Michigan State University, USA and Department of Electronic and Electrical Engineering at University of Bath, UK. He has expertise on label-free multichannel electrochemical biosensors, electronically\r\naddressable biosensor arrays, aptamer- and DNA-based sensors and surface bio-functionalization.",institutionString:"Indian Institute of Technology Kharagpur",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Indian Institute of Technology Kharagpur",institutionURL:null,country:{name:"India"}}},coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"11",title:"Engineering",slug:"engineering"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"429341",firstName:"Paula",lastName:"Gavran",middleName:null,title:"Ms.",imageUrl:"//cdnintech.com/web/frontend/www/assets/author.svg",email:"paula@intechopen.com",biography:null}},relatedBooks:[{type:"book",id:"10198",title:"Response Surface Methodology in Engineering Science",subtitle:null,isOpenForSubmission:!1,hash:"1942bec30d40572f519327ca7a6d7aae",slug:"response-surface-methodology-in-engineering-science",bookSignature:"Palanikumar Kayaroganam",coverURL:"https://cdn.intechopen.com/books/images_new/10198.jpg",editedByType:"Edited by",editors:[{id:"321730",title:"Prof.",name:"Palanikumar",surname:"Kayaroganam",slug:"palanikumar-kayaroganam",fullName:"Palanikumar Kayaroganam"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"1591",title:"Infrared Spectroscopy",subtitle:"Materials Science, Engineering and Technology",isOpenForSubmission:!1,hash:"99b4b7b71a8caeb693ed762b40b017f4",slug:"infrared-spectroscopy-materials-science-engineering-and-technology",bookSignature:"Theophile Theophanides",coverURL:"https://cdn.intechopen.com/books/images_new/1591.jpg",editedByType:"Edited by",editors:[{id:"37194",title:"Dr.",name:"Theophile",surname:"Theophanides",slug:"theophile-theophanides",fullName:"Theophile Theophanides"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3161",title:"Frontiers in Guided Wave Optics and Optoelectronics",subtitle:null,isOpenForSubmission:!1,hash:"deb44e9c99f82bbce1083abea743146c",slug:"frontiers-in-guided-wave-optics-and-optoelectronics",bookSignature:"Bishnu Pal",coverURL:"https://cdn.intechopen.com/books/images_new/3161.jpg",editedByType:"Edited by",editors:[{id:"4782",title:"Prof.",name:"Bishnu",surname:"Pal",slug:"bishnu-pal",fullName:"Bishnu Pal"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"371",title:"Abiotic Stress in Plants",subtitle:"Mechanisms and Adaptations",isOpenForSubmission:!1,hash:"588466f487e307619849d72389178a74",slug:"abiotic-stress-in-plants-mechanisms-and-adaptations",bookSignature:"Arun Shanker and B. 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\n
1. Introduction
\n
Influenza virus infections can affect all age groups, and older individuals are particularly at risk for influenza since, despite having no higher attack rate than younger adults, most influenza-related deaths and severe complications occur in this age group. Although influenza vaccination remains the mainstay in prevention, nonetheless, uncertainties regarding the effectiveness of the influenza vaccines in elderly adults are persistent [1, 2].
\n
The higher rate of flu complications and the reduced vaccine efficacy are generally attributed to both concomitant comorbidities and immunosenescence, i.e., the age-related weakening of the immune system [3, 4].
\n
As reported by Lambert et al. [5], the measurement of vaccine efficacy against influenza illness is a difficult task especially in older adults. Although influenza vaccine effectiveness depends not only on vaccine-induced immune response but also on annual variations in influenza incidence, circulating strain virulence, and the quality of the vaccine-to-circulating strain match [6], previous studies have established that a high serum antibody level can prevent infection at least in children and young adults [7–9], and serological studies based on the evaluation of influenza-specific antibody titers have been widely accepted and used as a surrogate marker for protection against influenza and vaccine efficacy.
\n
Chronic underlying diseases, particularly cardiac and respiratory diseases, were shown to negatively influence the immune response after influenza vaccination in old people [10].
\n
Three previous reviews on serological responses to inactivated seasonal vaccines in elderly people did not consider the possible role of chronic underlying illnesses, because there was not the possibility of controlling for the presence of serious illnesses [11] or because the elderly population was carefully selected to exclude any chronic diseases so that the results would reflect the effect of ageing on comparison with young people [12, 13].
\n
In comparison with community-dwelling elderly people, residents of nursing homes are considered to be at a higher risk of serious influenza-related complications, because they are generally older, more debilitated, and more exposed to influenza infection once the virus is introduced because of the close environment in which they live [14]. However, evaluating vaccine immunogenicity, results reported in the review of Goodwin et al. [12] and results previously obtained in our laboratory [15] suggested that institutionalized elderly responded better when compared with community-dwelling elderly.
\n
The aim of this chapter of the book is to examine the phenomenon of the decreased immunogenicity and efficacy of influenza vaccines in older persons from available data. We examined the data obtained by our research group in 27 winter seasons, from 1988–1989 to 2014–2015, of vaccine immunogenicity in a considerable number (4461) of elderly people (≥60 years of age), most of them with underlying medical conditions, vaccinated with commercially available seasonal trivalent inactivated influenza vaccines. Although some of the results obtained in the different winters were previously published, in the present report the results we obtained are cumulatively examined for the first time.
\n
\n
\n
2. Materials and methods
\n
\n
2.1. Study design and vaccination
\n
The volunteers initially enrolled in the prospective study of antibody response to influenza vaccination, conducted over a period of 27 consecutive winters, were 4461 elderly people, aged ≥60 years (mean age 80.5 year, range 60–106 years). Eighty-six percent of them were living in nursing homes in Central Italy.
\n
After providing informed consent, all the subjects received one dose of trivalent inactivated influenza vaccine intramuscularly, in the deltoid, or intradermally. The vaccines used were commercially available inactivated trivalent vaccines for the winters from 1988–1989 to 2014–2015 produced by propagation of the virus in embryonated hens’ eggs. Each dose of vaccine consisted of 10 μg (from 1988–1989 to 1991–1992) or 15 μg of hemagglutinin (HA) in a 0.5 ml dose (for vaccines administered intramuscularly) or in a 0.1 ml dose (for vaccines administered intradermally) for each of the three influenza strain antigens (A/H3N2, A/H1N1, and B influenza viruses). At the time of recruitment of this study, demographic data, health status, and history of influenza vaccination over the preceding year were obtained from each subject. Serum samples were obtained from the same subject before and 1 month after vaccination. Subjects were included in this study if they did not have a history of immediate hypersensitivity to eggs components. Subjects suffering from specific illnesses or chronic condition were not excluded. The study was conducted according to the Declaration of Helsinki and Good Clinical Practices. Since vaccines were assigned by local health authorities within the annual influenza campaign and sera were leftover sera from samples collected for clinical routine controls, the study did not need to be registered as a formal trial.
\n
\n
\n
2.2. Determination of hemagglutination-inhibiting (HI) antibody titers and measurement results
\n
HI antibody titers were determined using a standard microtiter method [16] with 0.5% chicken (from 1988–1989 to 1996–1997) or turkey erythrocytes (after 1996–1997). Antigens were prepared from the allantoic fluids of embryonated hens’ eggs inoculated 3 days earlier with influenza virus. All sera were heat-inactivated at 56°C for 30 min and treated with potassium periodate and trypsin (from 1988 to 1994) or with receptor-destroying enzyme (RDE) of Vibrio cholerae (after 1994) to remove nonspecific inhibitors. The first dilution for antibody titration was 1:10. Pre- and postvaccination sera from each of the vaccines were frozen at −30°C until used and tested simultaneously for HI antibody titers using the same antigens as those in the vaccine. To eliminate any subjective bias, HI titers determinations were carried on in a blind fashion, i.e., with the tester unaware of which treatment the donor had received.
\n
\n
\n
2.3. Criteria used for evaluating vaccines immunogenicity
\n
HI antibody titers obtained by following the procedure indicated in the previous section were reported as protection rate (percentage of volunteers showing HI titers ≥40, considered to be associated with protection from influenza infection) [9], geometric mean titers (GMT; any HI antibody titer <10 was considered equal to 5 for GMT calculation), ratio of postvaccination to prevaccination GMT values (GMTR), and seroconversion rate (percentage of subjects with a fourfold or greater increase in titer and with a postvaccination titer at least equal to 40 in seronegative volunteers). The antibody titers measured 1 month after vaccination were also evaluated according to the criteria of the Committee for Medicinal Products for Human Use (CHMP) for approval of influenza vaccines, which require that for individuals aged ≥60 years at least one of the following values must be met: seroprotection rate ≥60%, GMTR ≥2, or seroconversion rate ≥30% [17].
\n
\n
\n
2.4. Statistical analyses
\n
Statistical analyses and subanalyses considered in this work were applied to populations with a relatively large number of people, as a consequence both GMT and rate statistics were well approximated by a log normal and normal distributions, respectively. Moreover, since rates values were not close to 0 or 100%, thus significant differences between mean values of the groups were analyzed by Student’s t-test. Both estimated mean values with their corresponding 95% confidence intervals (CI) the p-value of the t-statistic have been reported in the paper. In particular, p-values <0.01 were considered highly statistically significant, whereas p-values <0.05 were regarded as marginally statistically significant. Values of postvaccination GMT observed against different antigens and in different years were examined as such and also corrected for prevaccination status according to Beyer et al. [18] in order to verify that significant differences in the postvaccination status were independent on the prevaccination HI titers. Vaccine response was evaluated also according to the dosage of vaccine antigens (30 and 45 μg), gender, and age (≤75 and >75). For each antigen, significant differences between subpopulations means were evaluated and the corresponding statistical significance was indicated.
\n
A multiple comparison test between groups of vaccine type and between antigens was executed by using one-way analysis of variance (ANOVA). Paired comparison values were presented only when one-way ANOVA comparison identified potentially significant differences. All statistical analyses were carried out using MATLAB® of MathWorks Inc. release 2014b.
\n
\n
\n
\n
3. Results
\n
\n
3.1. Study population and demographic characteristics
\n
Table 1 reports the baseline characteristics of the 4461 elderly volunteers, aged ≥60 years (range 60–106) vaccinated with commercially available seasonal trivalent inactivated influenza vaccines for each year of the 27 consecutive winters (from 1988–1989 to 2014–2015) studied. The number of volunteers examined each year varied from 64 to 372. The mean age was lower in the first years studied (from 1988–1989 to 1998–1999) when a mixed population of community-dwelling and institutionalized elderly was examined (60–80 years) than in the other seasons when volunteers were totally recruited from nursing homes (82–86 years). The majority of elderly subjects has been previously vaccinated (61–100%). Although not reported in Table 1, percentage of volunteers, ≥80%, presented underlying diseases or risk factors for influenza and as a consequence used chronic drugs. The most frequent chronic diseases were cardiovascular, respiratory diseases, and diabetes. The most frequent drugs used were antihypertensive/inotropic drugs and benzodiazepines.
\n
\n
\n
\n
\n
\n
\n
\n
\n
\n
\n
\n
\n\n
\n
\n
\n
\n
\n
\n
Type of seasonal vaccine useda
\n
\n
\n
\n
\n
Season
\n
No. of subjects
\n
Mean age (range)
\n
Living situationb
\n
Vaccination status prior to studyc
\n
Whole
\n
Sub-u
\n
Split
\n
MF59
\n
ID
\n
Vaccine dosage
\n
\n\n\n
\n
1988–1989
\n
282
\n
73 (61–93)
\n
M
\n
na
\n
232
\n
50
\n
–
\n
–
\n
–
\n
30 μg
\n
\n
\n
1989–1990
\n
82
\n
69 (60–83)
\n
M
\n
88%
\n
–
\n
59
\n
23
\n
–
\n
–
\n
30 μg
\n
\n
\n
1990–1991
\n
372
\n
66 (60–87)
\n
M
\n
69%
\n
159
\n
213
\n
–
\n
–
\n
–
\n
30 μg
\n
\n
\n
1991–1992
\n
124
\n
69 (60–93)
\n
M
\n
61%
\n
108
\n
–
\n
16
\n
–
\n
–
\n
30 μg
\n
\n
\n
1992–1993
\n
270
\n
nd (>60)
\n
M
\n
96%
\n
245
\n
8
\n
17
\n
–
\n
–
\n
45 μg
\n
\n
\n
1993–1994
\n
298
\n
76 (60–99)
\n
M
\n
na
\n
51
\n
–
\n
247
\n
–
\n
–
\n
45 μg
\n
\n
\n
1994–1995
\n
235
\n
78 (60–100)
\n
M
\n
90%
\n
32
\n
–
\n
203
\n
–
\n
–
\n
45 μg
\n
\n
\n
1995–1996
\n
213
\n
77 (60–100)
\n
M
\n
90%
\n
–
\n
213
\n
–
\n
–
\n
–
\n
45 μg
\n
\n
\n
1996–1997
\n
173
\n
80 (60–99)
\n
M
\n
96%
\n
–
\n
173
\n
–
\n
–
\n
–
\n
45 μg
\n
\n
\n
1997–1998
\n
176
\n
na (>60)
\n
M
\n
85%
\n
36
\n
140
\n
–
\n
–
\n
–
\n
45 μg
\n
\n
\n
1998–1999
\n
116
\n
74 (60–102)
\n
M
\n
94%
\n
–
\n
110
\n
6
\n
–
\n
–
\n
45 μg
\n
\n
\n
1999–2000
\n
139
\n
83 (60–103)
\n
I
\n
96%
\n
–
\n
46
\n
78
\n
15
\n
–
\n
45 μg
\n
\n
\n
2000–2001
\n
128
\n
83 (60–103)
\n
I
\n
100%
\n
–
\n
82
\n
46
\n
–
\n
–
\n
45 μg
\n
\n
\n
2001–2002
\n
96
\n
82 (60–104)
\n
I
\n
98%
\n
–
\n
–
\n
96
\n
–
\n
–
\n
45 μg
\n
\n
\n
2002–2003
\n
107
\n
82 (60–105)
\n
I
\n
100%
\n
–
\n
–
\n
107
\n
–
\n
–
\n
45 μg
\n
\n
\n
2003–2004
\n
125
\n
83 (60–101)
\n
I
\n
100%
\n
–
\n
–
\n
33
\n
92
\n
–
\n
45 μg
\n
\n
\n
2004–2005
\n
158
\n
82 (60–99)
\n
I
\n
98%
\n
–
\n
–
\n
36
\n
122
\n
–
\n
45 μg
\n
\n
\n
2005–2006
\n
105
\n
83 (60–99)
\n
I
\n
100%
\n
–
\n
–
\n
40
\n
65
\n
–
\n
45 μg
\n
\n
\n
2006–2007
\n
88
\n
83 (60–98)
\n
I
\n
98%
\n
–
\n
–
\n
21
\n
67
\n
–
\n
45 μg
\n
\n
\n
2007–2008
\n
66
\n
84 (61–102)
\n
I
\n
100%
\n
–
\n
–
\n
–
\n
66
\n
–
\n
45 μg
\n
\n
\n
2008–2009
\n
114
\n
83 (60–103)
\n
I
\n
98%
\n
–
\n
–
\n
–
\n
114
\n
–
\n
45 μg
\n
\n
\n
2009–2010
\n
64
\n
83 (65–98)
\n
I
\n
100%
\n
–
\n
–
\n
–
\n
64
\n
–
\n
45 μg
\n
\n
\n
2010–2011
\n
112
\n
85 (64–101)
\n
I
\n
100%
\n
–
\n
–
\n
–
\n
112
\n
–
\n
45 μg
\n
\n
\n
2011–2012
\n
151
\n
84 (65–102)
\n
I
\n
98%
\n
–
\n
–
\n
–
\n
103
\n
48
\n
45 μg
\n
\n
\n
2012–2013
\n
252
\n
85 (60–103)
\n
I
\n
100%
\n
–
\n
–
\n
26
\n
137
\n
89
\n
45 μg
\n
\n
\n
2013–2014
\n
204
\n
86 (60–106)
\n
I
\n
100%
\n
–
\n
–
\n
–
\n
183
\n
21
\n
45 μg
\n
\n
\n
2014–2015
\n
211
\n
84 (60–104)
\n
I
\n
100%
\n
–
\n
–
\n
1
\n
203
\n
7
\n
45 μg
\n
\n
\n
Total
\n
4461
\n
85 (60–106)
\n
\n
\n
863
\n
1094
\n
996
\n
1343
\n
165
\n
\n
\n\n
Table 1.
Characteristics of studied population and type of influenza vaccines in the 27 winter seasons studied (from 1988/1989 to 2014/2015).
bI: Institutionalized elderly; M: mixed, both institutionalized and community living elderly.
cPercent of elderly having received influenza vaccination in the previous year.
na: not available
\n
\n
\n
3.2. Vaccines
\n
As reported in Table 1, different formulations such as whole, split (composed by viruses disrupted, by a detergent, and containing the internal and external component of the virus), and subunit (composed of just the purified surface glycoproteins of the virus, i.e., hemagglutinin (HA) and neuraminidase) of trivalent inactivated vaccines were used in the different years or in the same year. In the first four studied years (from 1988–1989 to 1991–1992), the HA concentration for each strain was lower (10 μg for each antigen) as compared with the concentration (15 μg for each antigen) of the vaccines used in all the years after the winter season 1991–1992. Whole and subunit formulations were administered respectively to 863 and 1094 volunteers in the first 13 years of the study (from 1988–1989 to 2001–2002). Nine hundred ninety-six elderly people were vaccinated with split vaccine in many years studied and, starting from the 1999–2000 season, 1343 volunteers received a subunit vaccine potentiated with MF59 adjuvant. In the last period of the study, a limited number of elderly people was vaccinated with vaccine administered intradermally (165 volunteers from 2011–2012 to 2014–2015). The percentages of previously influenza-vaccinated people were high and ranged from 88 to 100%, not considering 3 years (1990–1991, 69%; 1991–1992, 61%, and 1993–1994, data not available).
\n
The antigenic composition of the vaccines used is reported in Figure 1 and each year was formulated according to the recommendations of both “Ministero della Salute (Italy)” and WHO (Northern Hemisphere) for the corresponding studied winter. During the 27-year period covered by our study (1988–2014), the WHO recommended 15 A/H3N2, 7 A/H1N1, and 12 B new influenza strains for inclusion in seasonal vaccines.
\n
\n
\n
3.3. Overall response to influenza vaccination
\n
The ability of licensed influenza vaccines to elicit an antibody response against vaccine antigens was examined comparing HI antibody titers in blood samples collected from the 4461 volunteers before and 1 month after vaccination with commercially available seasonal trivalent inactivated influenza vaccines in 27 consecutive winters (from 1988–1989 to 2014–2015).
\n
Figure 1.
Recommended viruses for influenza vaccines by World Health Organization between 1988 and 2014.
\n
\n
\n
\n
\n
\n
\n
\n
\n\n
\n
Vaccine component (N = 4461)
\n
Seroprotection rate (95% CI)
\n
Seroconversion rate (95% CI)
\n
GMT (95% CI)
\n
Number of reached CHMP criteria/3
\n
\n
\n
\n
Prevacc.
\n
Postvacc.
\n
\n
Prevacc.
\n
Postvacc. [GMTR]
\n
\n
\n\n\n
\n
A/H3N2
\n
35.1 A,B
\n
65.7** A,B
\n
30.0** A,B
\n
20.9 A,B
\n
54.6** A,B [2.6]
\n
3/3
\n
\n
\n
(33.7–36.5)
\n
(64.3–67.1)
\n
(28.5–31.2)
\n
(20.2–21.6)
\n
(52.5–56.8)
\n
\n
\n
\n
A/H1N1
\n
23.5
\n
52.6**
\n
25.1
\n
14.2
\n
35.3 ** [2.5]
\n
1/3
\n
\n
\n
(22.2–24.7)
\n
(51.1–54.1)
\n
(23.8–26.0)
\n
(13.7–14.6)
\n
(34.0–36.7)
\n
\n
\n
\n
B
\n
23.3
\n
54.5**
\n
25.6
\n
14.5
\n
35.7 ** [2.5]
\n
1/3
\n
\n
\n
(22.1–24.5)
\n
(53.0–55.9)
\n
(24.3–27.1)
\n
(14.1–14.9)
\n
(34.5–37.0)
\n
\n
\n\n
Table 2.
Mean values of the HI antibody responses observed in the 27-years study of the total population to the three influenza vaccine antigens and reachment CHMP criteria.
**: p-value < 0.01 comparing pre- and postvaccination values.
A: p-value <0.01 comparing A/H3N2 and A/H1N1 antigens.
B: p-value <0.01 comparing A/H3N2 and B antigens.
\n
The HI antibody response after one dose of influenza vaccine was evaluated for each antigen (A/H1N1, A/H3N2, and B) and data obtained were processed in order to calculate, for each population considered in the paper, pre- and postvaccination seroprotection rate, seroconversion rate, pre- and postvaccination GMT, and GMTR together to their corresponding 95% confidence intervals. For each antigen, the values of these parameters referred to the overall population are reported in Table 2. One month after vaccination, statistically significant increases were found in the percentage of seroprotected volunteers and in the values of their corresponding GMT against all the three different vaccine antigens. The three CHMP requirements were satisfied 1 month after vaccination against the A/H3N2 vaccine component, whereas only the requested value of GMTR was reached against the A/H1N1 and B antigens.
\n
\nTable 3 reports the results obtained examining the reachment of the CHMP criteria for each studied year against the three vaccine antigens. The seroprotection rate (HI titer ≥40) was higher than the requested 60% in 20 years against A/H3N2 (74%), 16 years against A/H1N1 (59%), and 14 years against B antigen (52%) of the 27 years studied. Values of GMTR satisfying the requested value ≥2 were found in 22 (81%), 25 (93%), and 21 (78%) years against A/H3N2, A/H1N1, and B vaccine components, respectively. The lower positive results were found for seroconversion requested to be ≥30%. This value was reached in 13 years against A/H3N2 (48%), 10 years against A/H1N1 (37%), and 8 years against B virus (30%). In some years none of the three CHMP criteria was satisfied, i.e., in 3 years against A/H3N2 (11%), 2 years against A/H1N1 (7%), and in 7 years against the B antigen (26%). Years with responses satisfying all the three CHMP criteria ranged between 22% (B antigen) and 48% (A/H3N2 antigen). Because the use of a vaccine featuring a novel antigen might affect the antibody response, considering data reported about vaccine antigenic composition in Figure 1, we identified the presence or absence of a novel vaccine component in each year studied, but we could not evidence any obvious association between vaccine HI antibody response and the presence of a new vaccine component.
\n
\n
\n
\n
\n
\n
\n\n
\n
Vaccine component
\n
N. of years (%) [95% CI]
\n
\n
\n
\n
Seroprotection ≥60%
\n
Seroconversion ≥30%
\n
GMTR ≥2
\n
Reachment of three CHMP criteria
\n
\n\n\n
\n
A/H3N2
\n
20 (74%) [55–93]
\n
13 (48%) [29–67]
\n
22 (81%) [67–96]
\n
13 (48%)
\n
\n
\n
A/H1N1
\n
16 (59%) [41–78]
\n
10 (37%) [18–56]
\n
25 (93%) [78–107]
\n
8 (30%)
\n
\n
\n
B
\n
14 (52%) [33–71]
\n
8 (30%) [11–48]
\n
21 (78%) [64–92]
\n
6 (22%)
\n
\n\n
Table 3.
Reachment of the CHMP criteria in the total population in the 27 years examined.
\n
The data reported in Table 2 evidenced differences in the values of the HI antibody titers against the three different vaccine antigens. HI antibody values against A/H3N2 antigen were in most instances significantly higher before and after vaccination as compared with those found both against A/H1N1 and B vaccine components.
\n
Since the baseline serological status is considered to be important in evaluating immunogenicity of influenza vaccines and is regarded as capable of affecting the serological outcomes, in order to reduce the heterogeneity among the responses found against the three vaccine antigens, we examined the GMT values of the overall population correcting the postvaccination titers for the prevaccination status according to Beyer (Figure 2) [18].
\n
Figure 2.
Postvaccination GMT values of: (a) the overall population corrected for the average prevaccination status according to Beyer; and (b) subjects unprotected before vaccination. Comparison of antigens is also shown when differences are significant. The bars indicate the ranges of the 95% confidence limits.
\n
For comparison purposes, also the postvaccination GMT values of the prevaccination unprotected volunteers (HI < 40) are shown in Figure 2 as indicated by the corresponding labels. The data reported confirmed that the responses against the A/H3N2 antigen were higher as compared with those against A/H1N1 and B antigens.
\n
\n
\n
3.4. Factors associated with vaccine response
\n
Since different factors may have an impact on vaccine response, we controlled for a number of variables for which we could obtain data. We did not consider the health status of the study participants, previous vaccination histories, and living situation, since a high percentage of the subjects had chronic underlying disease, was previously vaccinated, and was living in a nursing home.
\n
\n
3.4.1. Subanalysis according to different influenza vaccine dosages
\n
In Italy, as in most European countries, seasonal trivalent influenza vaccines containing 10 μg HA for each antigen (30 μg) has been used until 1991. From 1992 onwards European influenza vaccines contain 15 μg HA per strain (45 μg), according to the European Harmonization of Requirements for Influenza Vaccines [17]. As a consequence, in the first 4 years of the 27-year period examined in our study, we used 30 μg and, after the winter 1991–1992, 45 μg vaccines.
\n
Since previous observations suggested that increase in influenza vaccine dosage might be associated with an increase in antibody titers, at least against some of the vaccine strains [19, 20], we compared HI immune response following vaccination with 30 or 45 μg vaccines. As reported in Table 1, 860 (19%) and 3601 (81%) of the 4461 elderly subjects received respectively a 30 or a 45 μg trivalent influenza vaccine. Table 4 reports the results obtained studying the induced HI antibody response. Significant increases were observed against all the three vaccine antigens comparing pre- and postvaccination data against all the three different vaccine antigens examining the percentages of seroprotected people and GMT values both after 30 and 45 μg vaccine administration.
\n
\n
\n
\n
\n
\n
\n
\n
\n
\n\n
\n
Vaccine component
\n
Vaccine dose (N)
\n
Seroprotection rate
\n
Seroconversion rate (95% CI)
\n
GMT (95% CI)
\n
\n
\n
\n
\n
Prevacc.
\n
Postvacc.
\n
(95% CI)
\n
Prevacc.
\n
Postvacc. [GMTR]
\n
CHMP criteria satisfied
\n
\n\n\n
\n
A/H3N2
\n
30 μg
\n
14.1 A
\n
39.3**A
\n
16.9 A
\n
13.2 A
\n
26.3**A [2.0]
\n
1/3
\n
\n
\n
\n
(860)
\n
(11.7–16.4)
\n
(36.0–42.6)
\n
(14.5–19.4)
\n
(12.4–14.0)
\n
(24.6–28.0)
\n
\n
\n
\n
\n
45 μg
\n
40.1
\n
72.0**
\n
32.9
\n
23.3
\n
65.1** [2.8]
\n
3/3
\n
\n
\n
\n
(3601)
\n
(38.5–41.7)
\n
(70.5–73.5)
\n
(31.4–34.4)
\n
(22.4–24.3)
\n
(62.3–68.0)
\n
\n
\n
\n
A/H1N1
\n
30 μg
\n
10.2
\n
35.7**A
\n
20.8 A
\n
9.5 A
\n
22.5**A [2.4]
\n
1/3
\n
\n
\n
\n
(860)
\n
(8.2–12.3)
\n
(32.5–38.9)
\n
(18.1–23.5)
\n
(8.9–10.0)
\n
(21.0–24.2)
\n
\n
\n
\n
\n
45 μg
\n
26.7
\n
56.6**
\n
26.1
\n
15.6
\n
39.4** [2.5]
\n
1/3
\n
\n
\n
\n
(3601)
\n
(25.2–28.1)
\n
(55.0–58.3)
\n
(24.6–27.6)
\n
(15.0–16.2)
\n
(37.7–41.1)
\n
\n
\n
\n
B
\n
30 μg
\n
5.1
\n
30.0**A
\n
21.2 A
\n
8.1 A
\n
19.9**A [2.5]
\n
1/3
\n
\n
\n
\n
(860)
\n
(3.6–6.6)
\n
(26.7–33.1)
\n
(18.4–24.1)
\n
(7.7–8.5)
\n
(18.5–21.3)
\n
\n
\n
\n
\n
45 μg
\n
27.6
\n
60.3**
\n
26.6
\n
16.6
\n
41.1** [2.5]
\n
2/3
\n
\n
\n
\n
(3601)
\n
(26.2–29.1)
\n
(58.7–61.9)
\n
(25.2–28.0)
\n
(16.1–17.2)
\n
(39.6–42.7)
\n
\n
\n\n
Table 4.
HI antibody response in volunteers divided according to the vaccine dosage (30 or 45 μg).
**: p-value <0.01 comparing pre- and postvaccination values.
A: p-value <0.01 comparing response between vaccine dosages (30 and 45 μg).
\n
At least one of the three CHMP requirements, i.e., the value of GMTR (≥2), was always reached using vaccine containing 30 μg of antigen but following 45 μg vaccine administration all the three parameters were satisfied against A/H3N2 antigen and two of them against the B antigen.
\n
Postvaccination results observed after 45 μg vaccine administration were always significantly higher as compared with those after 30 μg vaccine.
\n
However, comparing values found in the two groups of people before vaccination, we observed that the two groups were poorly comparable since there were differences in the prevaccination status. Volunteers vaccinated with 45 μg vaccine showed prevaccination HI titers in most instances significantly higher as compared with the 30 μg volunteers. In order to have more homogeneous and comparable data, we examined vaccine immunogenicity both correcting the titers for prevaccination status of overall population [17], and considering only prevaccination unprotected volunteers (HI titers < 40). As shown in Figure 3, GMT corrected for prevaccination status confirmed that the increasing of the antigen dosage increments the response to the vaccine antigens. Postvaccination values found considering only people nonseroprotected before vaccination again evidenced a statistically significant higher response induced by 45 μg vaccine as compared with 30 μg.
\n
Figure 3.
Postvaccination GMT values of populations divided according to the vaccine dosage (30 or 45 μg)), as indicated by legend labels. Postvaccination GMT values calculated on the overall population have been corrected for the average prevaccination status according to Beyer. For comparison purposes, post-GMT values of subjects unprotected before vaccination are also shown. The bars indicate the ranges of the 95% confidence limits.
\n
\n
\n
3.4.2. Subanalysis of immunogenicity within the elderly groups, i.e., younger elderly (≤75 years) and very elderly (>75 years)
\n
In a recent meta-analysis about the effect of age on the influenza vaccine–induced immune response based on studies from the past 20 years, Goodwin at al. [12] concluded that aged individual (>65 years) had a significantly reduced antibody response to vaccination. The studied elderly were categorized into two age groups, above or below 75 years. Antibody responses among the very elderly (≥75 years of age) were especially impaired with seroconversion levels at 32%, 46%, and 29% to A/H1N1, A/H3N2, and influenza B, respectively, compared with 42%, 51%, and 35% observed in people aged <75 to >65 years of age [12].
\n
In order to have additive information we considered the immune responses found in volunteers of our study aged ≤75 or >75 years. The exact age was available for only 2712 people (61%) of the 4461 participants and 658 (24%) were aged ≤75 years and 2054 (76%) were >75 years. The results obtained are reported in Table 5 and show that in both groups the vaccine administration induced significant increases in HI titers evaluated as percentage of seroprotected people (HI ≥ 40) and as GMT values. CHMP criteria were always satisfied for GMTR parameter (≥2) against all the three vaccine antigens. All the three requested values were reached in both groups against A/H3N2 antigen and only in >75 year group against A/H1N1 antigen. Against the B antigen, the requested value for seroconversion (≥30%) was not reached in both groups and the value for seroprotection (≥60%) was satisfied only in >75-year group.
\n
\n
\n
\n
\n
\n
\n
\n
\n
\n\n
\n
Vaccine component
\n
Group (N)
\n
Seroprotection rate (95% CI)
\n
Seroconversion rate (95% CI)
\n
GMT (95% CI)
\n
\n
\n
\n
\n
Prevacc.
\n
Postvacc.
\n
\n
Prevacc.
\n
Postvacc. [GMTR]
\n
CHMP criteria satisfied
\n
\n\n\n
\n
A/H3N2
\n
≤75
\n
28.5 A
\n
60.7 **A
\n
31.8
\n
16.5 A
\n
46.9 **A [2.8]
\n
3/3
\n
\n
\n
\n
(658)
\n
(24.1–30.9)
\n
(28.2–35.4)
\n
(56.9–64.4)
\n
(15.1–17.9)
\n
(42.5–51.7)
\n
\n
\n
\n
\n
Age >75
\n
40.1
\n
71.4 **
\n
34.4
\n
23.5
\n
66.7 ** [2.8]
\n
3/3
\n
\n
\n
\n
(2054)
\n
(37.9–42.2)
\n
(69.4–73.3)
\n
(32.4–36.4)
\n
(22.3–24.8)
\n
(62.7–70.9)
\n
\n
\n
\n
A/H1N1
\n
≤75
\n
24.6
\n
52.6 **A
\n
24.5 A
\n
14.2 a
\n
35.6 **A [2.5]
\n
1/3
\n
\n
\n
\n
(658)
\n
(21.3–27.9)
\n
(48.7–56.4)
\n
(21.2–27.8)
\n
(13.0–15.4)
\n
(32.3–39.3)
\n
\n
\n
\n
\n
Age >75
\n
26.9
\n
60.3 **
\n
29.8
\n
15.7
\n
42.5 ** [2.7]
\n
3/3
\n
\n
\n
\n
(2054)
\n
(25.0–28.8)
\n
(58.2–62.4)
\n
(27.8–31.8)
\n
(15.0–16.5)
\n
(40.1–44.9)
\n
\n
\n
\n
B
\n
≤75
\n
254.6A
\n
54.3 **A
\n
26.7
\n
14.3 A
\n
36.8 **A [2.6]
\n
1/3
\n
\n
\n
\n
(658)
\n
(21.3–27.9)
\n
(50.4–58.0)
\n
(23.4–30.0)
\n
(13.2–15.5)
\n
(33.4–40.5)
\n
\n
\n
\n
\n
Age >75
\n
30.6
\n
62.8 **
\n
26.4
\n
18.0
\n
42.6 ** [2.4]
\n
2/3
\n
\n
\n
\n
(2054)
\n
(28.6–32.6)
\n
(60.7–64.9)
\n
(24.5–28.3)
\n
(17.2–18.8)
\n
(40.5–44.9)
\n
\n
\n\n
Table 5.
HI antibody response of populations divided according to the age (younger elderly, ≤75 years, and very elderly, >75 years).
**: p-value <0.01 comparing pre- and post-vaccination values.
A: p-value <0.01 comparing response between age groups.
a: p-value <0.05 comparing response between age groups.
\n
Comparing results obtained in the two groups, the responses observed in the oldest group (>75) were in most instances higher than those observed in the younger elderly (≤75). However, since the prevaccination status of these two groups were not fully comparable, we evaluated the values of GMT corrected for prevaccination status and GMT in people unprotected (HI < 40) before vaccination. Again the values were higher in the very elderly as compared with the younger against A/H1N1 for GMT corrected and against A/H1N1 and B for the GMT unprotected people (Figure 4).
\n
Figure 4.
Postvaccination GMT values of populations divided according to the age class (younger elderly, ≤75 years, and very elderly, >75 years), as indicated in legend labels. Postvaccination GMT values calculated on the overall population have been corrected for the average prevaccination status according to Beyer. For comparison purposes, post-GMT values of subjects unprotected before vaccination are also shown. The bars indicate the ranges of the 95% confidence limits.
\n
\n
\n
3.4.3. Subanalysis according to responses found in females and males
\n
Previous data indicated that receipt of trivalent inactivated influenza vaccines results in significantly higher HI antibody titers among females than males, both in adults and elderly people [21].
\n
In our study, sex data were available for about all the people studied (4457/4461) and the volunteers were prevalently females (70%). We examined the vaccine immunogenicity in females and males and the results are reported in Table 6. Postvaccination increases found against all the three vaccine antigens were statistically significant in both groups. All the three CHMP criteria were satisfied against A/H3N2 antigen in female subjects, whereas only the GMTR requirement was satisfied in males against A/H3N2 and both in males and females against A/H1N1 and B antigens. Comparison of postvaccination values evidenced statistically higher values in the female compared with male group. However, since differences were found also in the prevaccination values we compared the GMT corrected for the prevaccination status and examined the GMT found considering only volunteers not seroprotected before vaccination. The female responses were again higher than those of male against all the three vaccine antigens (Figure 5).
\n
\n
\n
\n
\n
\n
\n
\n
\n
\n\n
\n
Vaccine components
\n
Group (N)
\n
Seroprotection rate (95% CI)
\n
Seroconversion rate (95% CI)
\n
GMT (95% CI)
\n
EMA criteria satisfied
\n
\n
\n
\n
\n
Prevacc.
\n
Postvacc.
\n
\n
Prevacc.
\n
Postvacc. [GMTR]
\n
\n
\n\n\n
\n
A/H3N2
\n
F
\n
36.9 A
\n
68.7 **A
\n
32.7 A
\n
21.7 A
\n
60.0 **A [2.8]
\n
3/3
\n
\n
\n
\n
(3142)
\n
(35.2–38.5)
\n
(67.1–70.3)
\n
(31.0–34.4)
\n
(20.8–22.6)
\n
(57.3–62.9)
\n
\n
\n
\n
\n
M
\n
30.9
\n
58.6 **
\n
23.1
\n
19.1
\n
43.8 ** [2.3]
\n
1/3
\n
\n
\n
\n
(1315)
\n
(28.4–33.4)
\n
(55.9–61.3)
\n
(20.8–25.4)
\n
(17.9–20.4)
\n
(40.9–46.9)
\n
\n
\n
\n
A/H1N1
\n
F
\n
24.1
\n
55.3 **A
\n
27.7 A
\n
14.4
\n
38.0 **A [2.6]
\n
1/3
\n
\n
\n
\n
(3142)
\n
(22.6–25.6)
\n
(53.6–57.1)
\n
(26.2–29.2)
\n
(13.9–15.0)
\n
(36.3–39.8)
\n
\n
\n
\n
\n
M
\n
22.1
\n
46.2 **
\n
18.7
\n
13.6
\n
29.8 ** [2.2]
\n
1/3
\n
\n
\n
\n
(1315)
\n
(19.8–24.3)
\n
(43.5–48.9)
\n
(16.5–20.9)
\n
(12.8–14.4)
\n
(27.8–31.8)
\n
\n
\n
\n
B
\n
F
\n
24.9 A
\n
56.9 **A
\n
26.7 A
\n
15.2 A
\n
38.2 **A [2.5]
\n
1/3
\n
\n
\n
\n
(3142)
\n
(23.4–26.5)
\n
(55.2–58.6)
\n
(25.2–28.2)
\n
(14.6–15.7)
\n
(36.6–39.9)
\n
\n
\n
\n
\n
M
\n
19.3
\n
48.6 **
\n
22.7
\n
13.0
\n
30.5 ** [2.4]
\n
1/3
\n
\n
\n
\n
(1315)
\n
(17.2–21.5)
\n
(45.8–51.3)
\n
(20.5–25.4)
\n
(12.3–13.7)
\n
(28.7–32.4)
\n
\n
\n\n
Table 6.
HI antibody response of populations divided according to gender (male: M; female: F).
**: p-value <0.01 comparing pre- and post-vaccination values.
A: p-value <0.01 comparing response between M and F.
\n
Figure 5.
Postvaccination GMT values of populations divided according to gender (male: M and female: F) as indicated in legend labels. Postvaccination GMT values calculated on the overall population have been corrected for the average prevaccination status according to Beyer. For comparison purposes, post-GMT values of subjects unprotected before vaccination are also shown. The bars indicate the ranges of the 95% confidence limits.
\n
\n
\n
3.4.4. Evaluation of vaccine immunogenicity in “strong responder”
\n
Examining the antibody response after influenza vaccination, McElhaney et al. [22] considered as a vaccination efficiency-related parameter the HI antibody titer ratio between day 30 and day 0 and identified as weak/nonresponder people with a ratio 1– < 4 and as strong responders those with a ratio ≥4, i.e., people who seroconverted after vaccination. Using the same parameter we decided to evaluate in the groups identified as strong responders the induction of HI antibody response evaluated as GMT values against the three vaccine antigens.
\n
The data obtained comparing results found in people who seroconverted after vaccination are reported in Table 7, and in most instances confirmed the results obtained examining the overall population of subgroups vaccinated with vaccine containing different dosages of antigens or subdivided in male and female. The responses induced by a 45 μg vaccine or in female were in most instances statistically higher than those induced by a 30 μg vaccine or in male volunteers, respectively. Moreover, the immune responses evaluated in volunteers with an age ≤ or >75 years were similar against A/H1N1 and B antigens and higher against the A/H3N2 antigen in people aged >75 years as compared with response in those ≤75 years.
\n
\n
\n
\n
\n
\n
\n
\n
\n
\n
\n
\n\n
\n
Group
\n
A/H3N2
\n
A/H1N1
\n
B
\n
\n
\n
\n
\nN (total)
\n
GMT post [GMTR] (95% CI)
\n
Corrected GMT (95% CI)
\n
\nN (total)
\n
GMT post [GMTR] (95% CI)
\n
Corrected GMT (95% CI)
\n
\nN (total)
\n
GMT post [GMTR] (95% CI)
\n
Corrected GMT (95% CI)
\n
\n
\n\n\n
\n
30 μg
\n
146
\n
84.0 A [7.6]
\n
82.9 A
\n
179
\n
76.8 A [10.0]
\n
86.81A
\n
182
\n
83.8 A [9.7]
\n
94.1 A
\n
\n
\n
(860)
\n
(77.2–91.5)
\n
(74.9–91.86)
\n
(860)
\n
(71.4–82.7)
\n
(80.3–93.85)
\n
(860)
\n
(77.9–90.1)
\n
(86.9–101.9)
\n
\n
\n
45 μg
\n
1185
\n
164.7 [9.0]
\n
133.6
\n
940
\n
127.4 [9.8]
\n
126.1
\n
959
\n
110.2 [8.4]
\n
118.9
\n
\n
\n
\n
(3601)
\n
(155.3–174.6)
\n
(125.–142.7)
\n
(3601)
\n
(120.0–135.3)
\n
(118.5–134.1)
\n
(3601)
\n
(104.3–116.4)
\n
(112.1–126.3)
\n
\n
\n
≤75
\n
209
\n
127.7 A [9.2]
\n
112.9 A
\n
161
\n
123.0 [10.0]
\n
121.6
\n
176
\n
113.4 [9.1]
\n
122.7
\n
\n
\n
(658)
\n
(111.4–146.4)
\n
(99.3–128.3)
\n
(658)
\n
(106.1–142.6)
\n
(104.7–141.2)
\n
(658)
\n
(98.6–130.4)
\n
(105.3–143.1)
\n
\n
\n
>75
\n
707
\n
183.3 [9.2]
\n
146.2
\n
612
\n
127.6 [9.7]
\n
128.35
\n
543
\n
112.8 [8.1]
\n
117.3
\n
\n
\n
(2054)
\n
(169.6–198.1)
\n
(133.5–159.9)
\n
(2054)
\n
(118.7–137.2)
\n
(119.3–138.2)
\n
(2054)
\n
(104.9–121.2)
\n
(108.6–126.7)
\n
\n
\n
F
\n
1027
\n
162.1 A [8.9]
\n
130.3 a
\n
872
\n
120.3 [9.9]
\n
121.6 A
\n
842
\n
113 a [8.9]
\n
120.9 A
\n
\n
\n
(3142)
\n
(152.2–172.5)
\n
(121.7–139.6)
\n
(3142)
\n
(113.3–127.8)
\n
(114.4–129.3)
\n
(3142)
\n
(106.7–119.6)
\n
(113.8–128.4)
\n
\n
\n
M
\n
304
\n
125.9 [8.4]
\n
109.4
\n
246
\n
108.4 [9.3]
\n
100.1
\n
299
\n
86.9 [7.8]
\n
93.9
\n
\n
\n
(1315)
\n
(113.4–139.7)
\n
(97.1–123.1)
\n
(1315)
\n
(96.9–121.3)
\n
(90.6–110.4)
\n
(1315)
\n
(79.9–94.4)
\n
(86.3–102.2)
\n
\n\n
Table 7.
HI antibody response of strong responder population divided according to the vaccine dosage (30 or 45 μg), age class (younger elderly, μ75 years, and very elderly, >75 years), and gender (male: M; female: F).
**: p-value <0.01 comparing pre- and postvaccination values.
A: p-value <0.01; a: p-value <0.05 comparing response between different groups.
\n
\n
\n
3.4.5. Subanalysis according to the different types of vaccine used
\n
Finally, since different vaccine formulations (whole, subunit, split, MF59-adjuvanted, and intradermally administered) were used in the 27 years studied, we compared the results obtained after administration of the different types of vaccine. Chi-square and one-way analysis of variance (ANOVA) were used for evaluating multiple comparisons among groups vaccinated with the different vaccine types. Estimates and comparison intervals are shown in Figure 6. Paired comparison p-values resulting from the multicomparison test are reported in Tables 8 only when one-way ANOVA comparison identified potentially significant differences.
\n
Figure 6.
Values of CHMP parameters against the three vaccine antigens following vaccination with whole (N = 863), split (N = 996), subunit (N = 1094), MF-59 adjuvanted (N = 1343), and intradermally administered (N = 165) influenza vaccines. The black-dashed bold line in each figure represents the CHMP threshold value for the corresponding parameter. The bars indicate the ranges of the 95% confidence limits.
\n
All vaccines used induced HI antibody responses satisfying at least one (prevalently GMTR value ≥2) of the three CHMP criteria. The antibody response induced by whole vaccine was in most instances lower as compared with responses induced by the others vaccines (Table 8). However, as reported in Table 1, many of the volunteers vaccinated with whole vaccine in the first years of the study received a vaccine with a low dose of antigen (30 μg). The responses induced by split and subunit vaccines against A/H3N2 and B antigens were similar; on the contrary against A/H1N1 antigen, the response induced by split vaccine was significantly lower as compared with subunit.
\n
The two enhanced vaccines, MF59-adjuvanted and intradermal, induced similar and higher responses compared with conventional vaccines against A/H3N2 antigen.
\n
Against A/H1N1, the response induced by MF59-adjuvanted vaccine was in most instances higher than conventional and intradermal vaccines.
\n
Against B antigen, intradermal vaccine induced higher HI response than that induced by conventional and MF59-adjuvanted vaccines. In some cases the differences were statistically significant.
\n
\n
\n
\n
\n
\n
\n
\n
\n
\n
\n
\n
\n\n
\n
\n
\np-Values (when <0.05)
\n
\n
\n
Parameter
\n
Whole /sub-u
\n
Whole /split
\n
Whole /MF59
\n
Whole /ID
\n
Split /sub-u
\n
Split /MF59
\n
Split /ID
\n
Sub-u /MF59
\n
Sub-u /ID
\n
MF59 /ID
\n
\n\n\n
\n
A/H3N2 antigen
\n
\n
\n
Protection
\n
<0.01
\n
<0.01
\n
<0.01
\n
<0.01
\n
–
\n
<0.01
\n
<0.01
\n
<0.01
\n
<0.01
\n
–
\n
\n
\n
Conversion
\n
–
\n
–
\n
<0.01
\n
<0.01
\n
–
\n
<0.01
\n
<0.01
\n
<0.01
\n
<0.01
\n
–
\n
\n
\n
GMTR
\n
<0.01
\n
–
\n
<0.01
\n
<0.01
\n
–
\n
<0.01
\n
<0.05
\n
<0.01
\n
<0.01
\n
–
\n
\n
\n
A/H1N1 antigen
\n
\n
\n
Protection
\n
<0.01
\n
<0.01
\n
<0.01
\n
–
\n
<0.01
\n
<0.01
\n
–
\n
<0.05
\n
<0.01
\n
<0.01
\n
\n
\n
Conversion
\n
–
\n
<0.01
\n
<0.01
\n
–
\n
<0.01
\n
<0.01
\n
–
\n
–
\n
–
\n
–
\n
\n
\n
GMTR
\n
–
\n
<0.01
\n
<0.01
\n
–
\n
<0.01
\n
<0.01
\n
–
\n
–
\n
–
\n
–
\n
\n
\n
B antigen
\n
\n
\n
Protection
\n
<0.01
\n
<0.01
\n
<0.01
\n
<0.01
\n
<0.01
\n
–
\n
–
\n
<0.01
\n
<0.01
\n
–
\n
\n
\n
Conversion
\n
<0.01
\n
<0.01
\n
–
\n
<0.01
\n
–
\n
–
\n
<0.05
\n
–
\n
–
\n
<0.01
\n
\n
\n
GMTR
\n
–
\n
–
\n
–
\n
–
\n
–
\n
–
\n
–
\n
<0.01
\n
–
\n
<0.01
\n
\n\n
Table 8.
Paired comparison of results obtained in volunteers divided in groups according to the type of vaccine used for immunization. p-values resulting from the multicomparison test are reported only when one-way ANOVA comparison identified potentially significant differences.
This study describes the humoral antibody response of 4461 elderly frail institutionalized volunteers prevalently vaccinated in the previous year after vaccination with influenza inactivated trivalent vaccines commercially available for the different years studied during a 27-year period (from winter season 1988–1989 to 2014–2015).
\n
The first data were obtained by examining the results found in the 27-year period studied as crude mean responses and evidenced the ability of influenza vaccine administration to elicit antibody response in elderly volunteers (Table 2). One month after vaccination, significant increases were found against all the three vaccine antigens; however, vaccination induced significantly higher HI antibody titers against A/H3N2 antigen as compared with A/H1N1 and B strains. The higher responses against A/H3N2 strain were substantially confirmed considering the number of years in the 27-year period examined in which the CHMP criteria were fulfilled (Table 3) or comparing GMT values after correction for baseline titers or considering responses in prevaccination unprotected people (Figure 2).
\n
In accordance with our results, higher titers after vaccination against A/H3N2 strain were previously found by Sasaki et al. [23] and Ohmit et al. [24], but it was not possible to discriminate between the possibility that A/H3N2 antigen is more immunogenic than A/H1N1 and B antigens or the possibility that the higher GMT and protection rate values might depend from earlier contact with the A/H3N2 virus due to vaccination or natural infection. Since all the volunteers were previously vaccinated, the possibility of the influence of a different circulation of A/H3N2 strains is more acceptable. The A/H3N2 viruses have the highest rate of evolution among the three influenza subtypes currently circulating, with antigenically distinct strains emerging on average 2–5 years and capable of a better diffusion among the population [25].
\n
Further considerations about the results obtained derive from post hoc analyses conducted to determine whether vaccine dose, age, sex, and type of vaccine might influence the vaccine-induced humoral immune response.
\n
Although the issue of increase in the antibody titers following increase in influenza vaccine dosage is not completely clarified [19, 20, 26], our data found using vaccines with 30 or 45 μg of antigens for vaccine dose, suggested that the increase in influenza vaccine dosage is generally associated with an increase in the induction of antibody titers. Significant antibody titers increases were observed both administering vaccines with 30 or 45 μg of antigens for vaccine dose against all the three vaccine antigens. However, postvaccination values following vaccination with 45 μg vaccine were in most instances statistically higher as compared with 30 μg both considering mean values for the overall population (Table 4) or GMT corrected for prevaccination status or calculated in prevaccination unprotected volunteers (Figure 3). In accordance with these observations, recently (December 2009) in the United States, a high-dose (60 μg HA per strain) trivalent inactivated influenza vaccine was licensed for people 65 years of age or older. The high dose vaccine was found to improve in people aged ≥65 years both antibody response and protection against laboratory-confirmed influenza illness [27, 28].
\n
Considering vaccine immunogenicity in younger elderly (≤75 years) or in very elderly (>75 years), vaccine administration induced statistically significant increases in both groups. Comparing the two groups, the values were in many instances slightly higher in the very elderly as compared with younger elderly, and in some instances the differences were statistically significant. However, the differences persisted against A/H1N1 antigen both after correction for prevaccination status or calculation in unprotected volunteers before vaccination, and against B antigen only considering responses in unprotected people (Figure 4). The highest response of very elderly people as compared with younger elderly volunteers might be due to the fact that they probably represent a more selected group of elderly people capable of longer surviving and with a possible lower degree of age-associated alteration of the immune system [29].
\n
However, since the differences were particularly evident against the A/H1N1 strain and are in accordance with previous data found in our laboratory showing in two different winter seasons a higher ability to give HI antibody response against A/H1N1 strains of people born between 1903 and 1919 as compared with volunteers born between 1920 and 1957, we cannot exclude the possibility that the differences might be due to cross-reactivity generated from exposure to the 1918 A/H1N1 virus or related A/H1N1 strains [30].
\n
As far as sex could influence the immune response against influenza vaccines, our results confirmed previous data indicating that receipt of trivalent inactivated influenza vaccines results in significantly higher HI titers among females than males, both in adults and elderly people [21]. Significant rises in antibody titers were found after vaccination both in males and females, but the values observed in females were significantly higher as compared with males (Table 6) and the differences persisted also considering only GMT of volunteers unprotected before vaccination or GMT corrected for prevaccination status (Figure 5).
\n
Sex hormones have been considered to be the most important mediators of sex differences and males with high level of testosterone have been found to have low antibody responses after influenza vaccination [31, 32].
\n
However, since our data were obtained in elderly people, i.e., after the reproductive senescence, they support the hypothesis that the sex hormones are not the only mediator of sex differences in humoral response to influenza vaccination and there is the possibility that genetic differences also might underlie sex-based differences in adaptive immune response to viral vaccines [21, 33].
\n
These results (vaccine dose, age, and sex) were, at least in part, confirmed also considering responses evaluated in strong responder, i.e., in volunteers showing a positive response after vaccination (Table 7).
\n
Comparison of the different type of vaccines used in the 27-year period evidenced higher immunogenicity of the new “enhanced vaccines” specially licensed for elderly individuals, i.e., adjuvanted and intradermally administered vaccines, as compared with traditional whole, subunit, and split vaccines (Table 7, Figure 6) supporting previously published data [34, 35].
\n
Our study had several limitations. The most important are that our observations may apply only to frail seniors living in care facilities and that the subanalysis groups were not fully comparable. However, since institutionalized people represent a significant target group for influenza vaccination, it is important to analyze their response to influenza vaccines. An additional limitation is the lack of data demonstrating clinical efficacy against influenza infection and illness. Although there is substantial evidence that HI antibody titers represent a good correlate of protection from severe illness in young adults, the predictive value of these measurements in older adults might be variable. Although the number of volunteers and of winter seasons we examined was considerable and comparable to the data reported in a review, differently from a review on influenza vaccine immunogenicity, the results obtained in each year were considered cumulatively not taking into account of the different characteristics of the vaccines used through the 27-year period. Indeed, the antigenic composition of influenza vaccines differ, even considerably, from one year to another, since it is updated each year to match the strains circulating in the community and inactivated influenza vaccines are available in different formulations (whole, split, and subunit with or without adjuvants), which are administered intramuscularly or intradermally. Moreover, a further aspect that should be carefully considered as compared with those of a review on HI antibody titers after influenza vaccine administration is the HI assay itself. HI test is not standardized across laboratory and was found to be highly variable and sensitive to factors such as reagents, erythrocyte source, and virus passage history. The results reported in the present report were all obtained in the same laboratory, although in different years and although, some changes were introduced in the HI test used during the 27-year period as reported in Section 2.
\n
In conclusion, our data evidenced that the use of influenza vaccination appears to be an appropriate strategy to address the challenge of influenza infections of the elderly. However, they underline the need of studies for new improved influenza vaccines, since, as previously found, the vaccine-induced HI antibody responses against the three vaccine antigens were different and resulted not satisfactory against A/H1N1 and B antigen, since the postvaccination values of seroprotected volunteers were lower than the requested 60% (Table 3).
\n
Moreover, they underline the necessity to expand researches and approaches to understand immunosenescence and its relationship to vaccine-induced immunity in order to have more valid vaccines. The vaccine-induced stimulation of HI antibody response following vaccination was found not only to be higher against one vaccine component as compared with the other two, but also to be influenced by different factors as vaccine dose, age, sex, and type of vaccine. It is therefore important, as suggested by Lambert et al. [5], both to understand the mechanisms that result in these differences and to use such information to devise more immunogenic influenza vaccine candidates.
\n
\n\n',keywords:"influenza vaccination, vaccine immunogenicity, HI antibody titers, CHMP criteria, elderly institutionalized people",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/51708.pdf",chapterXML:"https://mts.intechopen.com/source/xml/51708.xml",downloadPdfUrl:"/chapter/pdf-download/51708",previewPdfUrl:"/chapter/pdf-preview/51708",totalDownloads:1440,totalViews:211,totalCrossrefCites:3,totalDimensionsCites:3,totalAltmetricsMentions:0,impactScore:2,impactScorePercentile:78,impactScoreQuartile:4,hasAltmetrics:0,dateSubmitted:"November 27th 2015",dateReviewed:"May 30th 2016",datePrePublished:null,datePublished:"October 26th 2016",dateFinished:"July 15th 2016",readingETA:"0",abstract:"Elderly people are more likely than younger people to get flu complications and respond suboptimally to influenza vaccination because of the presence of comorbidities and immunosenescence. In order to collect information about this issue, we evaluated data obtained in 27 winters of study, from 1988–1989 to 2014–2015, in frail elderly institutionalized people (≥60 years) vaccinated with commercially available seasonal trivalent inactivated influenza vaccines. The antibody response was examined comparing hemagglutination inhibition antibody titers in sera collected from 4461 volunteers before and 30 days after vaccination. Examining the results as crude mean responses, we evidenced the ability of influenza vaccines to induce significant increases in antibody titers against all the three vaccine antigens satisfying at least one of the three criteria of the Committee for Medical Products for Human Use (CHMP). Higher responses were found against A/H3N2 vaccine components and, examining different subgroups, in volunteers receiving 45 μg vaccine as compared with 30 μg and in female as compared with male subjects. Very elderly people (>75 years) gave better responses than younger elderly (≤75 years) at least against A/H1N1 strain and the last licensed potentiated vaccines (MF59-adjuvanted and intradermal) were more immunogenic than traditional vaccines (whole, subunit, and split).",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/51708",risUrl:"/chapter/ris/51708",book:{id:"5294",slug:"steps-forwards-in-diagnosing-and-controlling-influenza"},signatures:"Barbara Camilloni, Emilia Nunzi, Michela Basileo and Anna Maria\nIorio",authors:[{id:"183195",title:"Prof.",name:"Anna Maria",middleName:null,surname:"Iorio",fullName:"Anna Maria Iorio",slug:"anna-maria-iorio",email:"annaiorio42@gmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"University of Perugia",institutionURL:null,country:{name:"Italy"}}},{id:"187968",title:"Dr.",name:"Barbara",middleName:null,surname:"Camilloni",fullName:"Barbara Camilloni",slug:"barbara-camilloni",email:"barbara.camilloni@unipg.it",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"187969",title:"Dr.",name:"Emilia",middleName:null,surname:"Nunzi",fullName:"Emilia Nunzi",slug:"emilia-nunzi",email:"emilia.nunzi@unipg.it",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"187970",title:"Dr.",name:"Michela",middleName:null,surname:"Basileo",fullName:"Michela Basileo",slug:"michela-basileo",email:"michela.basileo@virgilio.it",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Materials and methods",level:"1"},{id:"sec_2_2",title:"2.1. Study design and vaccination",level:"2"},{id:"sec_3_2",title:"2.2. Determination of hemagglutination-inhibiting (HI) antibody titers and measurement results",level:"2"},{id:"sec_4_2",title:"2.3. Criteria used for evaluating vaccines immunogenicity",level:"2"},{id:"sec_5_2",title:"2.4. Statistical analyses",level:"2"},{id:"sec_7",title:"3. Results",level:"1"},{id:"sec_7_2",title:"3.1. Study population and demographic characteristics",level:"2"},{id:"sec_8_2",title:"3.2. Vaccines",level:"2"},{id:"sec_9_2",title:"3.3. Overall response to influenza vaccination",level:"2"},{id:"sec_10_2",title:"3.4. Factors associated with vaccine response",level:"2"},{id:"sec_10_3",title:"Table 4.",level:"3"},{id:"sec_11_3",title:"Table 5.",level:"3"},{id:"sec_12_3",title:"Table 6.",level:"3"},{id:"sec_13_3",title:"Table 7.",level:"3"},{id:"sec_14_3",title:"Table 8.",level:"3"},{id:"sec_17",title:"4. Discussion",level:"1"}],chapterReferences:[{id:"B1",body:'\nThompson WW, Shay DK, Weintraub E, Brammer L, Cox N, et al. Mortality associated with influenza and respiratory syncytial virus in the United States. JAMA. 2003;289(2):179–186. DOI: 10.1001/jama.289.2.179\n'},{id:"B2",body:'\nMullooly JP, Bridges CB, William W, Thompson WW, Chenb J, Weintraub E, et al. Influenza- and RSV-associated hospitalizations among adults. Vaccine. 2007;25(5):846–855. DOI: 10.1016/j.vaccine.2006.09.041\n'},{id:"B3",body:'\nTargonski PV, Jacobson RM, Poland GA. Immunosenescence: role and measurement in influenza vaccine response among elderly. Vaccine. 2007;25(16):3066–3069.\n'},{id:"B4",body:'\nChen WH, Kozlovsky BF, Effros RB, Grubeck-Loebenstein B, Edelman R, et al. Vaccination in the elderly: an immunological perspective. Trends Immunol. 2009;30(7):351–359. DOI: 10.1007/978-3-0346-0219-8\n'},{id:"B5",body:'\nLambert ND, Ovsyannikova IG, Pankratz VS, Jacobson RM, Poland GA. Understanding the immune response to seasonal influenza vaccination in older adults: a systems biology approach. Expert Rev Vaccines. 2012;11(8):985–994. DOI: 10.1586/erv.12.61\n'},{id:"B6",body:'\nNichol KL. Challenger in evaluating influenza vaccine effectiveness and the mortality benefits controversy. Vaccine. 2009;27:6305–6311. DOI: 10.1016/j.vaccine.2009.07.006\n'},{id:"B7",body:'\nHobson D, Curry RL, Beare AS, Ward-Gardner A. The role of serum haemagglutination-inhibiting antibody in protection against challenge infection with influenza A2 and B viruses. J Hyg (Lond). 1972;70(4):767–777.\n'},{id:"B8",body:'\nPotter CW. Determinants of immunity to influenza infection in man. Br Med Bull. Oxford JS. 1979;35(1):69–75.\n'},{id:"B9",body:'\nKatz JM, Hancock K, Xu X. Serologic assay for influenza surveillance, diagnosis and vaccine evaluation. Expert Rev Anti Infect Ther. 2011;9(6):669–683. DOI: 10.1586/eri.11.51\n'},{id:"B10",body:'\nMcElhaney JE, Zhou X, Talbot HK, Soerhout E, Bleackley RC, et al. The unmet need in the elderly: how immunosenescence, CMV infection, co-morbidities and frailty are a challenge for the development of more effective influenza vaccines. Vaccine. 2012;30:2060–2067. DOI: 10.1016/j.vaccine.2012.01.015\n'},{id:"B11",body:'\nBeyer WE, Palache AM, Baljet M, Masurel N. Antibody induction by influenza vaccines in the elderly: a review of the literature. Vaccine. 1989;7(5):385–394. DOI: 10.1016/0264-410X(89)90150-3\n'},{id:"B12",body:'\nGoodwin K, Viboud C, Simonses L. Antibody response to influenza vaccination in the elderly: a quantitative review. Vaccine. 2006;24(8):1159–1169. DOI: 10.1016/j.vaccine.2005.08.105\n'},{id:"B13",body:'\nSeidman JC, Richard SA, Viboud C, Miller AM. Quantitative review of antibody response to inactivated seasonal influenza vaccines. Influenza Other Respirat Viruses. 2012;6(1):52–62. DOI: 10.1111/j.1750-2659.2011.00268.x\n'},{id:"B14",body:'\nMonto AS, Hornbuckle K, Ohmit SE. Influenza vaccine effectiveness among elderly nursing home residents: a cohort study. Am J Epidemiol. 2001;154:155–160. DOI: 10.1093/aje/154.2.155\n'},{id:"B15",body:'\nIorio AM, Alatri A, Camilloni B, Neri M, Baglio G, et al. Antibody response to 1995–1996 influenza vaccine in institutionalized and non-institutionalized elderly women. Gerontology. 1999;45(1):31–38 . DOI: 10.1159/000022052\n'},{id:"B16",body:'\nHarmon MW, editor. Influenza viruses. Lennette EH (Ed.): Laboratory Diagnosis of Viral Infections. Second ed. New York: Marcel Dekker; 1992. pp. 515–534.\n'},{id:"B17",body:'\nCommission of the European Communities. Ad hoc working party on Biotechnology/Pharmacy. Harmonization of requirements for influenza vaccines. Biologicals. Document 111/3188/91-EN, Brussels; 1991.\n'},{id:"B18",body:'\nBeyer WE, Palache AM, Lüchters G, Nauta J, Osterhaus ADME. Seroprotection rate, mean fold increase, seroconversion rate: which parameter adequately expresses seroresponse to influenza vaccination?. Virus Res. 2004;103:125–132. DOI: 10.1016/j.virusres.2004.02.024\n'},{id:"B19",body:'\nSullivan KM, Monto AS, Foster DA. Antibody response to inactivated influenza vaccines of various antigenic concentration. J Infect Dis. 1990;161(2):333–335. DOI: 10.1093/infdis/161.2.333\n'},{id:"B20",body:'\nPalache AM, Beyer WEP, Sprenger MJW, Masurel N, De Jonge S, et al. Antibody response after immunization with various vaccine doses: a double-blind, placebo-controlled, multi-centre, dose-response study in elderly nursing-home residents and young volunteers. Vaccine. 1993;11:3–7.\n'},{id:"B21",body:'\nKlein SL, Pekosz A. Sex-based biology and the rational design of influenza vaccination strategies. J Infect Dis. 2014;209(S3):S114–S119.\n'},{id:"B22",body:'\nMcElhaney JE, Garmeau H, Camous X, Dupuis G, Pawelec G, et al. Predictors of the antibody response to influenza vaccination in older adults with type 2 diabetes. BMJ Open Diabetes Res Care. 2015;3(e000140). DOI: 10.1136/bmjdrc-2015-000140\n'},{id:"B23",body:'\nSasaki S, He XS, Holmes TH, Dekker CL, Kemble GW, et al. Influence of prior influenza vaccination on antibody and B-cell responses. PLoS One. 2008;3(8). DOI: 10.1371/journal.pone.0002975\n'},{id:"B24",body:'\nOhmit SE, Victor JV, Rotthoff JR, Teich ER, Truscon RK, et al. Prevention of antigenically drifted influenza by inactivated and live attenuated vaccines. N Engl J Med. 2006;355:2513–2522.\n'},{id:"B25",body:'\nWebster RG, Bean WJ, Gorman OT, Chambers TM, Kawaoka Y. Evolution and ecology of influenza A viruses. Microbiol Rev. 1992;56(1):152–179.\n'},{id:"B26",body:'\nPalache AM, Beyer WEP, Osterhaus ADME. Letter to the Editor Influenza vaccine dosages. Vaccine. 2008;26:2305–2306.\n'},{id:"B27",body:'\nSullivan SJ, Jacobson R, Poland AG. Advances in the vaccination of the elderly against influenza: role of a high-dose vaccine. Expert Rev Vaccines. 2010;9(10):1127–1133. DOI: 10.1586/erv.10.117\n'},{id:"B28",body:'\nDiazGranados CA, Dunning AJ, Kimmel M, Kirby D, Treanor J, et al. Efficacy of high-dose versus standard-dose influenza vaccine in older adults. N Engl J Med. 2014;371:635–645. DOI: 10.1056/NEJMoa1315727\n'},{id:"B29",body:'\nTrzonkowski P, Mysliwska J, Pawelec G, Mysliwski A. From bench to bedside and back: the SENIEUR protocol and the efficacy of influenza vaccination in the elderly. Biogerontology. 2009;10:83–94. DOI: 10.1007/s10522-008-9155-5\n'},{id:"B30",body:'\nIorio AM, Camilloni B, Lepri E, Neri M, Basileo M, Azzi A. Induction of cross-reactive antibodies to 2009 pandemic H1N1 influenza virus (pH1N1) after seasonal vaccination (Winters 2003/04 and 2007/08). Procedia Vaccinol. 2011;29:50–58. DOI: 10.1016/j.provac.2011.07.008\n'},{id:"B31",body:'\nCook IF, Barr I, Hartel G, Pond D, Hampson AW. Reactogenicity and immunogenicity of an inactivated influenza vaccine administered by intramuscular or subcutaneous injection in elderly adults. Vaccine. 2006;24:2395–2402. DOI: 10.1016/j.vaccine.2005.11.057\n'},{id:"B32",body:'\nFurman D, Hejblum BP, Simon N, Jojic V, Dekker CL, et al. Systems analysis of sex differences reveals an immunosuppressive role for testosterone in the response to influenza vaccination. PNAS. 2013;111:869–874. DOI: 10.1073/pnas.1321060111\n'},{id:"B33",body:'\nKlein SL, Jedlicka A, Pekosz A. The Xs and Y of immune responses to viral vaccines. Lancet Infect Dis. 2015;5:338–349. DOI: 10.1016/S1473-3099(10)70049-9\n'},{id:"B34",body:'\nBasileo M, Iorio AM, Bartolini G, Bianchini C, Menculini G, et al. Comparative study of immunogenicity of split, intradermal and MF59-adjuvanted influenza vaccines in elderly institutionalized subjects. Procedia Vaccinol. 2014;8:18–23. DOI: 10.1016/j.provac.2014.07.004\n'},{id:"B35",body:'\nCamilloni B, Basileo M, Di Martino A, Donatelli I, Iorio AM. Antibody responses to intradermal or intramuscular MF59-adjuvanted influenza vaccines as evaluated in elderly institutionalized volunteers during a season of partial mismatching between vaccine and circulating A(H3N2) strains. Immunity Ageing. 2014; 11:10. DOI: 10.1186/1742-4933-11-10\n'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Barbara Camilloni",address:"barbara.camilloni@unipg.it",affiliation:'
Department of Experimental Medicine, University of Perugia, Perugia, Italy
Department of Experimental Medicine, University of Perugia, Perugia, Italy
'},{corresp:null,contributorFullName:"Anna Maria Iorio",address:null,affiliation:'
Department of Experimental Medicine, University of Perugia, Perugia, Italy
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1. Introduction
The initial concept of “pancake bonding” was constructed by Mulliken and Person as to characterize the overall shape and bonding mechanisms of donor-acceptor π systems [1]. More recently the term “pancake bonding” has primarily been used to describe the formation of stabilizing parallel π–π interactions between two or more open-shell free radicals, those of which are typically planar and/or consist of light-atoms [2, 3, 4]. Such interactions have received a considerable amount of interest as they allow one to synthesize novel radical-based materials, via electron or hole through-space delocalization, that exhibit unique magnetic [5], optical [6], and electronic properties (i.e. conductive polymers, organic conductors) [7].
Generally, free radical species are short lived and exist in low concentration as two radicals will typically react to form a single covalently bonded dimer, or σ-dimer. However, when radicals are sterically hindered against approaching within a covalent bonding distance, they can exist as a stable, spin-paired, open shell species. Unlike general non-covalent interactions between closed-shell species (i.e. van der Waals), the open-shell radicals have been said to undergo stabilization with each other via through-space π-stacking 2e/mc distributed interactions (i.e. pancake bonding). This 2e/mc bonding (i.e. pancake bonding) is a result of overlapping antibonding (π∗) singly occupied molecular orbitals (SOMO) of the two monomer radicals with highly delocalized π-electrons [8]. It is noted that magnetic experimental analysis has found the spin pairing of pancake bonded dimers to be diamagnetic with an overall spin density of zero (i.e. singlet electronic state) [9]. The overlapping of antibonding (π∗) SOMOs is the basis of pancake bonds as this interaction leads to the following distinctive features [4]: i) contact bond distances that are beyond the usual C(sp3)–C(sp3) bond length (1.54 Å) but are also much shorter than the bonds of closed shell dimers that are held together by vdW forces (sum of vdW radii = 3.40 Å) (ii) due to direct atom-to-atom overlap, SOMO-SOMO overlapping strongly favors configurations that yield maximum overlap orientations which lower the energy of the two radical SOMOs iii) low lying singlet (singlet-singlet) and triplet (singlet-triplet) electronic excited states, iv) negative singlet-triplet splitting energies (i.e., ΔEST = E(singlet) – E(triplet)) for stable open shell singlet pancake bonded complexes [10] and v) interaction energies larger than those of vdW interactions. Bond dissociation energies (BDE) of pancake bonded system have been estimated to be smaller than those of a normal covalent system but larger than dimers subject to typical π-stacking where this type of π-stacking is observed for DNA base pairs [11] (vdW π stacking interactions and pancake bonds are different). Several works analyzed the related binding energies (BE), splitted into two contributions, a destabilizing stabilizing vdW part, EvdW, and a stabilizing energy, ESOMO, associated with the bonding overlap of the singly occupied SOMO [12]. ESOMO yields a reasonable description of the SOMO-SOMO overlap contribution to BE and it has been suggested that ESOMO can be estimated from the difference between E(singlet) – E*(triplet), where E*(triplet) is the triplet energy evaluated for the singlet geometry [12].
BE, ESOMO and SOMO-SOMO overlap have been utilized as to further explain the nature of these systems [8, 13]. It was argued that the dimerization of such radicals exhibit covalent bonding character as the spin-pairing of the electrons in the SOMO leads to a filled highest occupied molecular orbital (HOMO) and a corresponding empty antibonding LUMO [14]. In this situation, the interaction occurs at rigid rotational geometries, due to SOMO-SOMO overlapping, which is different from π-stacking in which various rotational orientations are possible [15]. On the other hand, dispersion and/or van der Waals interactions have been suggested to play important roles in the overall stabilization of these dimers [14]. Thus, the nature of pancake bonds between 1,2-chalcogen-3,5-diazol radicals and phenalenyl-based radicals remains in debate to the present day.
A CSD database survey based upon 35 cis-cofacial dimers composed of HCNSSN radicals, with C–C contact distances ranging between 2.75 to 3.50 Å, showed that S⋯S contact bond distances ranged from 2.93 to 3.30 Å [8]. These S⋯S contact bond are much shorter than the vdW distance between two sulfur atoms (4.06 Å) [16], in the case of two spherical sulfur atoms the vdW distance has been computed to be 3.60 Å. A CSD database survey based on 12 cis-cofacial 1,2-diselena-3,5-diazolyl dimers, with C⋯C contact distances between 2.80 and 3.50 Å, found the average Se⋯Se contact distance to be 3.26 (s = 0.05) [8]. This average Se⋯Se contact distance is slightly smaller than the vdW distance between spherical Se atoms (3.32 Å). Previously computed dissociation energies have suggested that dimers of R-CNSeSeN radicals dimers are more binding than dimers of R-CNSSN radicals; relative binding energy values were also observed to be analogous to vdW interactions [8].
1,2-chalcogen-3,5-diazole dimers: Within the past two decades di-chalcogen-diazole radicals, such as 1,2-dithia-3,5-diazolyl (i.e. HCNSSN) and 1,2-diselena-3,5-diazolyl (i.e. HCNSeSeN) radicals, and their derivatives have been a subject of many investigations [17]. The rings of HCNSSN and HCNSeSeN are rich in π-electrons and have π∗ singly occupied molecular orbitals (SOMO). The 1,2-dithia-3,5-diazolyl and 1,2-diselena-3,5-diazolyl radicals have been experimentally observed to result in stable dimerizations in the solid state where, in most cases, the neutral radicals prefer to be oriented with their faces parallel to one another (cis-cofacial) in order to achieve a configuration that supports maximum π∗-π∗ (SOMO-SOMO) overlapping observed as two electron/eight-center (2e/8c) π-stacking (i.e. pancake bonding) interactions. A notable feature of HCNSSN and HCNSeSeN dimers are their four long chalcogen-chalcogen bonds (i.e. contacts) ranging between 2.2 and 4.0 Å. HCNSSN and HCNSeSeN dimers have been suggested to stabilize via a combination of π and σ aromaticity [13].
Phenalenyl-based dimers: In solution, phenalenyl radicals maintain chemical equilibrium via the formation of a σ-bonded dimer [18]. Due to the very high symmetry of the radical phenalenyl monomer, a unpaired electron is delocalized across all α-positions of the phenalenyl framework excluding the central carbon atom of the monomers [19]. As noted in the work of Kubo [19], the thermodynamic stability of such carbon-centered radical species increases as the delocalization of unpaired electrons across a system increases [19]. Another interesting feature of phenalenyl dimers and their derivatives (i.e. carbon-centered hydrocarbon radicals) is due to the formation of unique two-electron/twelve-center (2e/12c) π-stacking interactions between these spin-delocalized hydrocarbon radicals [20] as verified by NMR [21]. The hexagonal arrangement of the SOMO of the phenalenyl radicals enables perfect π-π overlap in both eclipsed and staggered stacking configurations, the staggered stacking configuration is favored over the eclipsed configuration due to shorter π-π contacts as a result of less atom-atom repulsion [19]. It is mentioned, that various phenalenyl derivatives, which demonstrate π-π stacking (i.e. pancake bonding), have been experimentally identified via single crystal X-ray diffraction (XRD) [22]. The formation of σ-bonded phenalenyl radical dimer can be inhibited by substituting the carbon atoms of the phenalenyl rings, at the 2,5,8-positions, with tert-butyl groups as a π-bonded dimer results from the sterically hindered phenalenyl radicals [19]. Moreover, X-ray studies have revealed that the application of sterically hindered substituents (i.e. tert-butyl groups) on phenalenyl radicals prevent σ-dimerization and results in a π-bonded dimer with a face-to-face stacking distance, twice that of the σ-bonded dimer, at a length of of 3.2 Å [23]. This π-π contact (face-to-face) stacking distance is characteristic to pancake bonding as this length is shorter than that of a vdW complex and is beyond the length of a coventional covalent bond. Bond dissociation energy (BDE) for systems containing carbon radicals such as phenalenyl have been estimated to be around 10 kcal/mol [11]. Because σ-bonded and π-bonded phenalenyl-based dimers are close in energy the existence of the pancake bonded dimer as a fluxional molecule has been reviewed [12].
Although many experimental and computational have been conducted for the dimerizations of 1,2-chalcogen-3,5-diazol and phenalenyl-based radicals, the intrinsic strength of these interactions remains unclear. While popular BDE and its decomposition [24] provides valuable information about the stabilizing forces involved in bond formation (in the case of pancake bond in particular in the formation of 2e/mc interactions), BDE does not adequately describe the intrinsic strength of a bond [25, 26, 27]. Because BDE measures the overall effect of bond breakage it contains the electronic reorganization and geometrical relaxation of the fragments upon dissociation. Therefore, we introduced in this work an intrinsic bond strength measure based on vibrational spectroscopy. Unlike BDE, the local stretching force constant (ka), derived from local vibrational modes [25], conserves the geometry and electronic structure of all bonds/interactions. ka provides a direct description of intrinsic bond strength and has been applied successfully applied to assess the intrinsic bond strengths for a variety of covalent interactions including ultra long C–C bonds, carbon-halogen bonds and non-covalent interactions such as hydrogen, tetrel, pnicogen, chalcogen and halogen bonds; see Ref. [25] and citations therein.
In this study, we applied the local mode analysis [25] complemented with the RING puckering analysis of Cremer and Pople [28] and Bader’s quantum theory of atoms in molecules (QTAIM) analysis of the electron density [29] to quantify the strength of the pancake bonds in six spin-paired, open-shell singlet state dimers 1–6 (shown in Figure 1) and and to learn more about their nature. Species 1–3 are 1,2-chalcogen-3,5-diazole dimers which contain sulfur (1), selenium (2), and tellurium atoms (3); it is noted that 3 is a prototypal (i.e. theoretical) species. Species 4–6 are phenalenyl-based dimers in which the bulkiness of substituents increase as follows: phenalenyl dimer (4) < 2,5,8-trimethylphenalenyl dimer (5) < 2,5,8–tert-butylphenalenyl (6). The aromatic character of the dimer species (4–6) was also explored, in particular the role of the aromaticity for the stabilization of phenalenyl-based dimers. In summary, special focus was on: i) to assess the intrinsic bond strengths of the 2e/mc interactions for selected species, ii) to quantify the ring strengths of the selected species, iii) to determine if the pancake bonds of these species are covalent in nature, iv) to elucidate on the effect of substituents on the aromaticity of phenalenyl-based species, v) to determine, for phenalenyl-based dimers, the effect of dimerization on the aromaticity for phenalenyl-based species, and vi) to determine what bond property, of the phenalenyl-based species investigated, predominately governs changes in aromaticity.
Figure 1.
Species investigated in this work. 1) 1,2-dithia-3,5-diazolyl (HCNSSN) dimer 2) 1,2-diselena-3,5-diazolyl (HCNSeSeN) dimer. 3) 1,2-tellura-3,5-diazolyl (HCNTeTeN) dimer 4) phenalenyl dimer. 5) 2,5,8-tri-methylphenalenyl dimer. 6) 2,5,8-tri-t-butylphenalenyl dimer. Detected pancake bonds (2e/mc) (i.e. targeted contact bonds and interdimer CC bonds) are denoted in red.
2. Computational methods
Local mode theory: Since the underlying theory behind the derivation of local vibrational modes is elaborated on in Ref. [25] the following text briefly covers the fundamental aspects. Every vibrational mode, being associated with potential and kinetic energy contributions, is subject to two mode-to-mode coupling mechanisms, electronic coupling and kinematic (mass) coupling [30]. As a result the normal modes remain perpetually delocalized over a molecule and cannot be directly used to assess chemical bond strength [25]. Solution of the vibrational secular equation (i.e. the Wilson equation) eliminates the electronic coupling as a result of force constant matrix diagonalization. The kinematic coupling which remains is eliminated in the local mode theory via a modified version of the Wilson equation that uses mass-decoupled Euler–Lagrange Equations [25]. This leads to local vibrational modes, associated with local mode frequencies ωa and local mode force constants ka that can serve as a quantitative bond strength measure [25] which we applied to assess the strength all 2e/mc interactions (i.e. pancake bonds) of species 1–6 (see Figure 1). Stretching force constants ka can be transformed into relative bond strength orders (BSO) n which are more convenient for comparison, via a generalized Badger rule [31], leading to the following power relationship between these two quantities: BSO n = A (ka)B. Constants A and B can be determined from two reference molecules with known ka and BSO n values and the requirement that for a zero ka value the BSO n is also zero.
In our study we used the CC single bond of ethane with BSO n = 1 and the CC double bond of ethene with BSO n = 2 as references [32]. In addition to BSO n values for the C⋯C contacts, BSO n values for N⋯N, S⋯S, Se⋯Se, and Te⋯Te bonds of the dichalcodiazolyl species 1–3 were derived using the same power relationship. For dimers 4–6, aside from deriving the BSO n values for the central C–C bonds, we also computed the BSO n values for the outer C⋯C contacts which are established between six carbon atoms of each monomer (see Figure 1).
Aromaticity index based on local modes: π delocalization in species 4–6 was determined via an aromatic delocalization index (AI) derived from local force constants following the procedure of Kraka, Cremer and co-workers [33, 34]. In contrast to the HOMA index [35] which is based upon optimal bond lengths, which sometimes tend to fail for this purpose [33], the AI is based on local stretching force constants and bond strength orders (BSO n). As a reference, we used benzene with an AI value of 1.00 and assigned BSO n value of 1.451 [33].
BDEs for 1–6 were derived via potential energy curves by varying the interdimer distance from 2.5 to 8.0 Å, using increments of 0.1 Å around and 1.0 Å further away from the equilibrium geometry, followed by a constrained optimization. By calculating BDEs via potential energy curves any basis set superposition errors can be avoided, such errors have been reported to as large as 16 kcal/mol in these complexes when the BDE is calculated from the differences between dimer and monomer energies [14]. The covalent character of the pancake bonds was assessed with the Cremer-Kraka criterion [36, 37] of covalent bonding within the framework of Bader’s QTAIM [29]. The Cremer-Kraka criterion is composed of two conditions; (i) existence of a bond path and bond critical point rb = b between the two atoms under consideration; (ii) sufficient condition: the energy density Hrb = Hb is smaller than zero. Hr is defined as Hr = Gr + Vr, where Gr is the kinetic energy density and Vr is the potential energy density. A negative Vr corresponds to a stabilizing accumulation of density whereas the positive Gr corresponds to depletion of electron density [36]. As a result, the sign of Hb indicates which term is dominant [37]. If Hb<0, the interaction is considered covalent in nature, whereas Hb>0 is indicative of electrostatic interactions.
Model chemistry used: To describe the spin-paired open shell singlet states, we applied a single determinant broken-symmetry (BS) unrestricted ansatz, which works well for systems with small singlet-triplet gaps [38, 39], combined with a density functional theory (DFT) approach. We refrained from a multi-reference description, such as CASSCF, which has been mostly applied to unsubstituted species 4 with a relatively small active space and basis sets [40]. We also refrained from post-SCF methods, such as Møller-Plesset perturbation theory of second order, which has shown to over-bind in the case of dimer complexes with pancake bonds and may results in an unrealistic C⋯C contact distance of 2.8 Å [14].
A reliable description of pancake bonding requires a careful choice of DFT functional. The popular B3LYP functional [41, 42] does not describe dispersion well whereas the dispersion corrected ωB97X-D [43] functional sometimes leads to inconsistent results [44]. It was reported that the M06-2X functional [45] yields generally shorter C⋯C contact distances [46] whereas the C⋯C contact distances based off the M05-2X functional [47] agree well for complexes for 4–6 with experimental values [48]. On the other hand, the M06 functional has shown to be well parameterized for describing chalcogens (i.e. sulfur, selenium and tellurium atoms) [45]. Another important part of the model chemistry is the basis set. We tested both, Pople’s augmented 6–31++G(d,p) double zeta [49, 50] and 6-311G(d,p) triple zeta basis sets [51]. For the Te atom we applied the SDD basis set [52] which uses the Stuttgart-Dresden pseudopotentials [53] to account for relativistic effects. Guided by our test calculations, we decided to use for our study the BS-UM06/6-311G(d,p) model chemistry for 1–2, BS-UM06/SDD for 3, and BS-UM05-2X/6–31++G(d,p) for 4–6.
Software used: All DFT geometry optimizations and frequency calculations were carried out using the Gaussian program package [54]. The following local mode analysis and the aromaticity delocalization index (AI) study was carried out with the LModeA software [55]. The QTAIM analysis was performed with the AIMALL program [56] For the rings of the di-chalcodiazoyl dimers (1–3), which do not contain a central atom, we used the ring puckering program [57] followed by LMA, as to obtain the local mode properties of the rings.
3. Results and discussion
It is noted that in regard to the text which follows, the terms contact bonds, π-π stacking interactions, and face-to-face interactions loosely refer to pancake bonds while interdimer/central C-C bonds refer to the C-C bond established in the center of two monomers. Table 1 summarizes the calculated bond distances (Rcalc), experimental bond distances (Rexp), calculated bond dissociation energies (BDEcalc), experimental bond dissociation energies (BDEexp), local stretching force constants (ka), local mode vibrational frequencies (ωa), bond strength orders (BSO n), electron densities (ρb), and energy densities (Hb) for the targeted CC bonds of of targeted contacts bonds of dimers 1–6 and rings of 1–3. Table 2 summarizes symmetry, singlet and triplet C⋯C contact distance (R(CC)), energy values of SOMOs (ESOMO), and triplet/singlet (ΔEST) for all species investigated in this work (1–6). Figure 2 shows the equilibrium geometries for the HCNTeTeN 3 dimer (C2) in singlet and triplet states. Figure 3 shows the various conformations of the phenalenyl dimer in the triplet state where the red lines indicate detected C⋯C contacts. Figure 4 show the generated Morse potential curves of dimers 1–6. Figure 5 shows the correlation between BSO n values and the local stretching force constants ka of 1–6. Figure 6 showcases the BSO n(CC) values, corresponding CC bond lengths, AI values, bond weakening/strengthening parameters (WS), and bond alteration parameters (ALT) for the carbon ring structures and the outer ring structures of phenalenyl, 2,5,8-trimethylphenalenyl, and 2,5,8-tri-t-butylphenalenyl monomer radicals and dimers.
No.
Species
Rcalc
Rexp
BDEcalc
BDEexp
ka
ωa
BSO n
ρb
Hb
1
HCNSSN
Ring
3.071
−5.8
−5.3 [8]
0.657
147
0.214
0.016
0.005
C–C
3.036
3.18
0.208
243
0.083
0.041
0.007
N-N
3.034
0.128
176
0.056
0.052
0.004
S-S
3.125
0.192
143
0.078
0.104
−0.000
2
HCNSeSeN
Ring
3.210
−4.7
N/R
0.302
72
0.113
0.015
0.004
C–C
3.119
3.31
0.080
151
0.038
0.034
0.006
N-N
3.152
0.074
134
0.036
0.042
0.003
Se-Se
3.313
0.151
80
0.064
0.098
−0.000
3
HCNTeTeN, C2v
Ring
3.514
−6.0
N/A
0.049
23
0.021
0.013
0.001
C–C
3.219
N/A
0.029
83
0.014
0.036
0.006
N-N
3.333
0.032
29
0.016
0.039
0.006
Te-Te
3.840
0.045
123
0.022
0.073
0.002
4
HCNTeTeN, C2
Ring
3.413
−8.4
N/A
0.162
43
0.062
0.018
0.002
N-N
3.342
0.112
165
0.045
0.046
0.009
Te-Te
3.820
0.038
65
0.018
0.086
0.003
N-Te
3.510
0.045
78
0.021
0.069
0.007
5
Phenalenyl
Peripheral C–C
3.110
N/A
−11.0
N/A
0.366
123
0.136
0.072
0.005
Central C–C
3.152
N/A
0.293
288
0.113
0.063
0.006
6
tMP
Peripheral C–C
2.997
3.053
−14.8
N/R
0.172
64
0.074
0.090
0.006
Central C–C
3.093
3.145
0.167
217
0.072
0.070
0.007
7
tTBP
Peripheral C–C
3.391
3.306
−12.4
−9.5 [59]
0.194
68
0.081
0.047
0.003
Central C–C
3.287
3.201
0.147
204
0.065
0.050
0.005
Table 1.
Summary of calculated bond distances (Rcalc) in Å, experimental bond distances (Rexp) in Å, bond dissociation energies (BDEcalc) in kcal/Mol, experimental bond dissociation energies (BDEexp) in kcal/Mol, vibrational spectroscopy data, electron densities (ρb) in e/Å3, and energy densities (Hb) in h/Å3 of the targeted contacts bonds and rings of dimers 1–6 (see Figure 1).
The UM06/6-311G(d,p) methodology used for 1 and 2, UM06/SDD for 3, and UM05-2X/6–31++G(d,p) for 4, 5 and 6. N/A, not applicable; N/R, not reported.
No.
Species
Dimer
Monomer
Singlet
Triplet
ESOMO
ΔEST
Symmetry
Symmetry
R(CC)
R(CC)
1
HCNSSN
C2v
C2v
3.036
3.452
−15.61
−2.17
2
HCNSeSeN
C2v
C2v
3.119
3.208
−13.90
−2.09
3
HCNTeTeN
C2v
C2v
3.165
3.362
−13.26
0.96
3
HCNTeTeN
C2
C2
3.563
3.104
−8.46
−1.35
4
Phenalenyl
D3d
C3H
3.152
3.622
−12.97
−5.98
5
tMP
D3d
C3H
3.093
3.744
−19.26
−5.44
6
tTBP
S6
C3H
3.281
3.855
−6.11
−3.13
Table 2.
Symmetry of dimer and monomer, singlet and triplet face-to-face distances (R(CC)) in Å, energy values of SOMOs (ESOMO) in kcal/Mol and triplet/singlet splitting (ΔEST) in kcal/Mol for comlexes 1–6 (see Figure 1) calculated at corresponding levels of theory.
Figure 2.
Equilibrium geometries for HCNTeTeN (3) dimers in C2 symmetry. a) Singlet. b) Triplet.
Figure 3.
Conformations of the phenalenyl dimer in the triplet state. a) Staggered. b) Eclipsed. c) Intermediate geometry. The red lines indicate detected π-π contacts. Bond distances for the central CC bond between the two monomers are given.
Figure 4.
Dissociation curves for dimers 1 and 2 (UM06/6-311G(d,p), 3 (C2v) (UM06/SDD), and 4–6 (UM05-2X/6–31++G(d,p)).
Figure 5.
The relationship between BSO n and force constants of dimers 1–6 calculated with UM06/6-311G(d,p) (1 and 2), UM06/SDD (3), and UM05-2X/6–31++G(d,p) (4–6). BSO n(ring) values for 1–6 were computed via in accordance to the level of theory used.
Figure 6.
Bond strength orders (BSO) and bond lengths (in parentheses, Å) for the phenalenyl, 2,5,8-trimethylphenalenyl and 2,5,8-tri-t-butylphenalenyl radical monomers and dimers (4 through 6). The aromaticity delocalization index (AI), bond weakening (strengthening) parameters (WS) and alteration parameters (ALT) for the FULL carbon ring structures (FULL) and the OUTER ring structure (OUTER) are indicated in boxes. The term FULL accounts for all CC bonds while the term OUTER accounts only for outer CC bonds and does not account for the inner most CC bonds.
3.1 Energetics
Identifying pancake bond interactions: As shown in Table 2, the ESOMO values for dimers 1–6 range between −6.11 and −19.26 kcal/mol where 5 acquires the largest ESOMO value. We note that the ESOMO value of 6 is in good agreement with the ST-splitting of −6.64 kcal/mol derived from ESR experiments [21]. As shown in Table 2 the ΔE(ST) is small and negative for dimers 1–6 with 3 in C2 symmetry. These results are in line with the notion that the formation of pancake bonded dimers requires the spin-paired singlet state to be energetically favored over the triplet state.
From singlet to the triplet state, the central C–C bond distances in dimers 1 and 2 increase from 3.04 Å and 3.12 Å to 3.45 Å and 3.21 Å, respectively. No alterations in the rotational alignments amongst these two species were observed. Unlike for dimers of 1 and 2, we observe that, in the singlet state of the HCNTeTeN dimer (3) one monomer rotates about the CC central axis by 88.5∘, resulting in a C2v symmetry for the dimer. Moreover, the triplet state of the HCNTeTeN dimer (3) involves the rotation of a monomer, about the central C-C axis, by 99.2∘ and results in a C2 symmetry for the dimer (see Figure 2).
The ΔEST values of 1–3, where 3 is in C2 symmetry, indicate stable arrangements (see Table 2). In the case of 3, which is common in symmetry to dimers 1 and 2 (C2v), the triplet state is lower than the singlet state (ΔE(ST) = 0.96 kcal/mol) reflecting an unstable dimer structure as no pancake bonding is formed. We note that for the lower energy structure of 3 (C2) BCP’s were detected for Te⋯Te, Te⋯N, and N⋯N contacts, being consistent with the observations of Gleiter and Haberhauer [58], in which the reorientations of dithiatriazine molecules favored the formation of S⋯N and S⋯C interactions over the the formation of a C⋯C contacts. Notably, unlike the other di-chalcodiazoyl dimers, the central C–C distance of the 3 (C2) dimer, from the singlet to the triplet state, decreases from 3.56 Å to 3.10 Å. Going from a C2v symmetry to C2 symmetry the ESOMO value of 3 changes from −13.26 kcal/mol to −8.46 kcal/mol. These results indicate that there are attractive interactions between the monomers of 3 (C2) that are unrelated to SOMO-SOMO overlap. Overall, the results based on 3 in C2v and symmetry C2, suggest that chalcogen⋯chalcogen bonds and the electrostatic attraction between a chalcogen and a less electronegative atom play significant roles in the stabilization of such dimers.
For the phenalenyl dimer (4), the triplet geometry exhibits two local minima and one global minima (see Figure 3). The staggered configuration of 4 is −1.7 kcal/mol lower in energy than the eclipsed conformer. The central C⋯C distance of both the staggered and eclipsed conformer of 4 are longer than the sum of the van der Waals radii where the central C⋯C bond of the staggered configuration is shorter than that of the eclipsed configuration by 0.27 Å (see Figure 4). The most stable arrangement of 4 is represented by an intermediate structure with a rotational dihedral of 40.9∘ which, in contrast to the staggered and eclipsed geometries, has a shorter central C⋯C distance (3.42 Å) and is −0.4 kcal/mol lower in energy than the staggered configuration. These results suggest that the triplet state of 4 is a π-complex.
Though the interatomic distances of 5 and 6, when going from a singlet to triplet state, increase from values of 3.09 Å and 3.28 Å to values of 3.74 Å and 3.86 Å, we observe no change in the rotational alignment between the monomers of the two species. These results suggest that any change in the orientations of 5 and 6 monomers are hindered by their substituent groups. We also note that the ΔEST values of 4 to 6 steadily decline as substituent size increases (see Table 2).
Dissociation energies: From the Morse potential curves of the dichalcodiazoyl dimers 1–3 (C2) bond dissociation energy (BDEcalc) values of −5.8, −4.7 and −6.0 kcal/mol are obtained, these values being more analogous to the BDE values of electrostatic interactions. The calculated BDE of 1 is in good proximity to the experimental value reported by Beneberu et al. (see Table 1). The bond dissociation energy of species 3, in C2 symmetry, in comparison to 3 in C2v symmetry, is more negative by −2.4 kcal/mol.
The computed bond dissociation energy values for species 4 through 6 are −11.0, −14.8 and −12.4 kcal/mol, respectively. The computed dissociation energy value of 6 is in good agreement with the previously reported experimental enthalpy change (ΔHD) of −9.5 kcal/mol [59]. We observe the BDEcalc of the 2,5,8-trimethylphenalenyl dimer (5) to be larger than that of both 4 and 6 by values of 3.8 and 2.4 and kcal/mol suggesting that the addition of three methyl groups to each monomer of the phenalenyl dimer (5) yields a more stable dimer as dispersion contributions are enhanced (see Tables 1 and 2). In contrast to 5, the addition of three tert-butyl groups (C4H9) to each monomer of the phenalenyl dimer (6) results in a decreased stabilization due to increased steric repulsion between the bulky C4H9 substituents. Moreover, we observe 2,5,8-tri-t-butylphenalenyl dimer (6) to be more stable than the phenalenyl dimer (4) by 1.4 kcal/mol, indicating that, within 6, there is a trade-off amongst the steric repulsion of the tert-butyl groups and stabilizing dispersion (see Table 1 and Figure 4).
3.2 Bond parameters and derived bond strength orders n
Di-chalcodiazoyl dimers: As the chalcogen atoms (S, Se, and Te) of the di-chalcodiazoyl dimers (1–3) increase in atomic radius (see Figure 5), the BSO n values of the C⋯C contacts of 1–3 decrease (see Table 1). It is noted that C⋯C contact distances of 1 and 2 are in excellent agreement with experiment (see Table 1). The chalcogen⋯chalcogen contacts within the 1,2,3,5-ditelluradiazolyl dimer (3), in C2v symmetry, acquire a ka value that is smaller than that of the chalcogen⋯chalcogen interactions of dimers 1 and 2 by 0.147 and 0.109 mdyn/Å, respectively. In the case of the 3, in C2 symmetry, N⋯Te, rather than C⋯C contacts as observed in 3 (C2v), are seen to coexist alongside Te⋯Te contacts. Moreover, we find that the BSO n value for the hetero-chalcogen (N⋯Te) bond of 3 (C2) is larger than that of the Te⋯Te contact (see Table 1).
In regard to individual aromatic rings of 1–3 (i.e. HCNSSN, HCNSeSeN, and HCNTeTeN) we observe the overall bond strength order of each ring (i.e. BSO n(ring)) to decrease as the strength of the chalcogen⋯chalcogen interactions between corresponding rings decrease in the following order: S⋯S > Se⋯Se > Te⋯Te [BSO n(ring) = 0.214 (1), 0.113 (2), 0.021 (3, C2v), 0.062 (3, C2)]. Moreover, as depicted in Figure 5, the dimer 1,2,3,5-dithiadiazolyl (1) is more stable than the 1,2,3,5-diselenadiazolyl dimer (2) by 0.355 mdyn/Å (see Figure 1); this result indicates that a greater extent of π-stacking is present within 1 which results in the C⋯C, N⋯N, and chalcogen⋯chalcogen contacts of 1 being shorter than those of 2 (see Table 1). Furthermore, the ka values for the chalcogen⋯chalcogen contacts (i.e. S⋯S, Se⋯Se, and Te⋯Te) reveal that S⋯S and Se⋯Se interactions contribute large amounts of π-delocalization primarily towards the rings, where the overall rings strength of 2 is stronger than that of 3 due to a greater amount of π-delocalization from the corresponding chalcogen⋯chalcogen interactions (Se⋯Se) (see Table 1). From Figure 5, in addition to the individual ka values of the NN, TeTe, NTe, and CC contacts of 3 in C2 and C2v symmetry, we can see that the C2 configuration of 3 results in a greater amount of stabilizing π-delocalization, dominantly due to the N⋯N contacts, towards the rings (see Table 1). Alongside a decrease in ring strength from 1 to 3 the overall bond length of the aromatic rings, which, in the case of 1 is equivalent to the summation of all R(C-N), R(S-S), and (N-S) bond lengths of a HCNSSN ring, decreases from 1 to 3 (see Table 1).
The energy density (Hb) values at the chalcogen⋯chalcogen (i.e. S⋯S, Se⋯Se, and Te⋯Te) bond critical points rb of 1–3 are negative for 1 and 2 and positive for 3 (see Table 1). The negative energy density Hb values at the bond critical points rb of the chalcogen⋯chalcogen contacts within 1 and 2 (i.e. S⋯S, Se⋯Se) indicate the presence of chalcogen⋯chalcogen covalent bonding [60]. Positive Hb values of the Te⋯Te interactions for 3, in both C2v and C2 symmetries, indicate that the Te⋯Te contacts are much weaker than the S⋯S and Se⋯Se contacts of 1 and 2 which are of an electrostatic nature. We note that in all cases (1–3), the Hb values of C⋯C and N⋯N contacts are positive. The non-detection of a bond critical point for the C⋯C contacts of 3, in C2 symmetry, reveal that such interactions disappear when the C⋯C bond distance stretches slightly beyond that for the equilibrium geometry of 3 (C2v) (see Table 1).
From our results we observe that the stabilization of molecules 1 and 2 is primarily due to the large magnitude of π-delocalization from their corresponding chalcogen interactions (i.e. S⋯S and Se⋯Se) where the extent of π-delocalization is seen to correlate in parallel with the strength of the C⋯C contacts and the overall strength of an aromatic rings (see Table 1). In contrast to dimers 1 and 2, 3 (C2v) acquires a much weaker C⋯C contact strengths and an overall weaker aromatic ring strength due to a lesser extent of π-delocalization from the Te⋯Te interactions as revealed from the much smaller ka(chalcogen⋯chalcogen) values (see Table 1). Our results show that the chalcogen bonding does play a stabilizing role in the dimers such as 1 and 2 as suggested by Gleiter and Haberhauer [13, 58, 61], which observe that as pancake bonded species (dimer) are drawn apart the monomers tip outward in such a way that the chalcogen atoms, on each monomer, undergo separation at a slower rate in contrast to their carbon and nitrogen atoms.
Phenalenyl-based dimers: Unlike dimers 1–3, the phenalenyl dimers (4–6) contain central (interdimer) C–C bonds (see Figure 1). As mentioned earlier, in addition to the central C–C bonds of 4–6, we also analyze all peripheral C⋯C bonds which are established between six carbon atoms of each monomer that comprise the corresponding phenalenyl-based dimers (see Figure 1). We observe that the central C–C bonds of 4–6 decrease in strength from 4 to 6 due to a lesser extent of π-delocalization from peripheral C⋯C as observed from corresponding ka(C⋯C) values (see Table 1). The relative BSO n values of the peripheral C⋯C interactions for all phenalenyl-based dimers (4–6) are stronger than the corresponding central C–C bonds (see Table 1). The ka values of the central C–C bonds within 4–6 are within a range 0.16 and 0.70 mdyn/Å; these bonds are weaker than the C–C single bond in ethane, a classical C–C bond prototype (ka(C–C) = 4.3 mdyn/Å).
Moreover, the peripheral C⋯C bonds of the phenalenyl dimer (4) and of the tri-methylphenalenyl dimer (5) are shorter than their central C–C bonds (see Table 1). For the tri-tert-butylphenalenyl dimer (6), the interdimer C–C bond is distance is smaller than that of the peripheral C⋯C bonds (see Table 1) due to the steric repulsion between the bulky tert-butyl groups of the monomers as this repulsion “locks” the dimer into a staggered configuration. The steric repulsion between the tert-butyl groups groups of 6 results in a concave pyramidalization of the central CC bonds of the monomers [40], causing the central interatomic C–C bond to be shorter than the outer CC interactions (see Table 1). Moreover, the electron density values (ρb) of the peripheral C⋯C bonds of 4 and 5 are less than those for the corresponding central C–C bonds and an opposite trend is observed for that 6 (see Table 1). We observe both the C⋯C contacts and interdimer C–C interactions of 4–6 to have positive energy density values Hb indicating that both interactions acquire an electrostatic nature, rather than a covalent character (see Table 1).
3.3 Aromaticity and ring strength of phenalenyl-based monomers and dimers
In order to assess the effect of substitution and dimerization on the monomers and dimers of 4–6 we conduct aromaticity delocalization index (AI) analysis. Two AI were determined for each monomer and dimer of 4–6, one AI value considers all CC bonds while the second AI value considers only the outer most CC bonds which trace the species (the inner/central most CC bonds are not considered). In addition to AI values, Figure 6 lists corresponding WS and ALT parameters, WS gives the weakening/strengthening parameter of the bonds in and ALT reflects the magnitude of bond strength alteration. Overall, the WS and ALT parameters reflect the loss of aromaticity which is attributed to increased structure irregularity. Therefore, the more symmetrical an aromatic perimeter, the greater the aromaticity (i.e. AI) of the system. For example, in the case of benzene, which is planar and very symmetrical as all CC sides (bonds) are identical, the parameters are as follows: WS = 0, ALT = 0, and AI = 1. In general, the smaller the AI the weaker the aromatic character of a species.
Phenalenyl-based monomers: We observe the six outer most CC bonds of the phenalenyl monomer (BSO n(CC) = 1.412) to be identical in strength to those of benzene (BSO n(CC) = 1.451). The addition of methyl substituents to the phenalenyl monomer, in the form of 2,5,8-trimethylphenalenyl, favors a skewed arrangement which places one H atom of every CH3 group in plane with the phenalenyl rings and the other two H atoms of every CH3 group above and below the plane of the rings (see Figure 6). From the BSO n values and bond distances of the six outermost CC bonds of the 2,5,8-trimethylphenalenyl monomer we observe the outer bonds to be dissimilar (see Figure 6). For the CC outer bonds, that are on the same side of the coplaner hydrogen atom of the CH3 group, CC bond distances and BSO n values increase by 0.002 Å and decrease by 0.032 while that for the CC outer bonds, that are on the same side of the two CH3 hydrogen atoms above and below the ring, increase by 0.008 Å and decrease by 0.065 in contrast to that of the phenalenyl monomer. A similar trend is observed for the substitution of phenalenyl with t-butyl substituents in the form of 2,5,8-tri-t-butylphenalenyl, where the six outer CC bonds become slightly longer and weaker in contrast to 2,5,8-trimethylphenalenyl (see Figure 6). In comparison to the phenalenyl monomer the CC outer bonds of 2,5,8-tri-t-butylphenalenyl, which are on the same side of the coplaner methyl group, become longer by 0.003 Å and weaker by 0.037 BSO n units while that for the outer CC bonds, that are on the same side of the methyl groups above and below the ring, stretch by 0.011 Å and decrease in strength by 0.053 units. For the outer CC bonds, not affiliated with the point of substituent attachment (periphery CC bonds), the effect of substitution is too a lesser extent with bond lengths ranging between 1.412 to 1.415 Å and the BSO n(CC) values ranging from 1.283 to 1.312. We note that 6 acquires the weakest outer and periphery CC bonds. Conversely, the three bonds which radiate from the central C (i.e. inner CC bonds) increase in strength from 4 to 5 and from 5 to 6 (see Figure 6). This indicates that electron density lost by the deformation of the outer CC bonds, occurring from monomer of 4 to 6, redistributes to the inner bonds.
The AI (full/outer) values of the phenalenyl monomer are both 0.915. From monomers 4 to 6 we observe the AI, based upon the outer CC bonds, to decrease steadily while the AI, based upon all CC bonds, fluctuates. From the AI outer/full values of the phenalenyl (AI (full, outer) = 0.915), 2,5,8-trimethylphenalenyl (AI (full, outer) = 0.918, 0.911) and 2,5,8-tri-t-butylphenalenyl monomers (AI (full, outer) = 0.901, 0.885) we observe that the outer rings have a larger degree of π-delocalization than the full ring. From WS and ALT parameters we can see that the decrease in the aromatic character of the outer CC bonds from monomer 4 (WS, ALT = 0.062, 0.023), to 5 (WS, ALT = 0.077, 0.012), to 6 (WS, ALT = 0.108, 0.008) is predominantly due to bond weakening (as indicated by WS). Overall we observe that as the 4 monomer is substituted with CH3 (5) and tert-butyl groups (6) the outer aromaticity decreases steadily and is predominately governed by bond weakening effects which are attributed to smaller magnitudes of π-delocalization as additional π-delocalization (i.e. electron density) is pushed away from the points of substitution and adjacent (periphery) CC bonds towards the inner most CC bonds as reflected from the increasing inner CC bond strength from 4 to 6.
Phenalenyl-based dimers: We note that the trend in BSO n values observed amongst the CC bonds of the monomers discussed in the previous section is similarly observed for the CC bonds of their dimers (4–6). It is worth mentioning that the AI (outer/full) values for the dimers are greater than that of their monomer components (see Figure 6). The phenalenyl dimer 4, in contrast to its monomer counterpart, has larger outer, peripheral, and central CC bond strength orders (BSO n(CC)) of 1.441, in very close proximity to that of benzene (1.451). We observe that the the bigger aromaticity of dimer 4 is predominately attributed to bond strengthening as revealed from a comparison between the WS parameters of the phenalenyl monomer (WS (full/outer) = 0.066, 0.062) and dimer (4) (WS (full/outer) = 0.043, 0.035).
From Figure 6 it is shown that dimers 5 and 6 favor configurations which position the six methyl or tert-butyl groups amongst the dimers in an alternating manner yielding a symmetrical arrangement and in turn a stable species. We note that the methyl groups within the lowest energy rotational isomer of dimer 5 do not have the same orientation as those within its monomer as six hydrogen atoms of the CH3 groups are rotated inward, towards the center of the molecule (see Figure 6). From WS and ALT parameters we see that the dimer of 2,5,8-trimethylphenalenyl (5) has a greater outer CC aromaticity (AI (outer) = 0.911 (monomer), 0.914 (dimer)) than its monomer due to bond strengthening (WS (full, outer) = 0.077 (monomer), 0.075 (dimer)). We note that this result is consistent with the BSO n values of the peripheral and central CC bonds of dimer 5, which are greater than those of the monomer by 0.012 to 0.026 units (see Figure 6). In contrast to the phenalenyl dimer (4), 5 has much larger WS (full/outer) and smaller ALT (full/outer) parameters, where the WS parameters are more altered than the ALT parameters (see Figure 6). These results reveal that the aromaticity of the 2,5,8-trimethylphenalenyl dimer (5) (AI (full/outer) = 0.918, 0.914) is less than that of the phenanlenyl dimer (AI (full/outer) = 0.934, 0.938) primarily due to bond weakening (indicated by WS, see Figure 6). The outer/full AI values of the 2,5,8-tri-t-butylphenalenyl dimer (6) are both bigger than its monomer counterpart being primarily due to bond strengthening as observed from the smaller WS (outer/ full) parameters of the dimer in contrast to that of it monomer (see Figure 6). It is also notable that changes in AI (outer/full), when comparing monomer to monomer, monomer to dimer, or dimer to dimer, do not correspond directly to changes in CC bond lengths, in some instances these lengths stay the same or do not drastically change unlike BSO n (CC) orders (see Figure 6).
From our results, it is clear that substituents not only prevent σ-dimer formation but reduce the overall aromaticity of both phenalenyl-based monomers and the dimers. As noted, the dimeric systems display a higher AI than the monomeric systems indicating that the dimerization of phenalenyl-based species enhances the aromaticity of the species. Our observation is in line with the nucleus-independent chemical shift (NICS) NMR analysis of Suzuki et al. [21], which suggets that SOMO-SOMO overlap in the dimerized system, overall, supports and stabilizes the aromaticity of the molecules. Furthermore, our work supports the suggestions of Gleiter and Haberhauer who propose that dimers which are pancake bonded undergo stabilization via electron combination as to create a Hückel-allowed [62] (4n + 2 electron) 3-dimensional aromatic system as we observe that, despite the fact that the dimers, unlike their monomers, are not planar (which reduces orbital overlap), the dimers exhibit higher aromaticity. Ultimately, from AI, WS, ALT, and BSO n parameters, we discover that the dimerization of phenalenyl-based monomers increases the aromaticity of the phenalenyl rings predominantly through CC bond strengthening while the substitution of the phenalenyl dimer, alongside inhibiting σ-dimerization, reduces the overall aromaticity of the system predominantly through CC bond weakening.
4. Conclusions
In this work, we conducted local mode analysis, electron density analysis, and aromaticity delocalization index (AI) calculations (based upon vibrational frequencies) for a set of six neutral pancake-bonded systems, di-chalcodiazoyl dimers (1–3) and phenalenyl-based dimers (4–6), as to elucidate on the strength of pancake bond interactions within dimers, the ring strength of their monomers, the nature of the pancake bond interactions, the effect of substituents on the aromaticity of phenalenyl-based species, and the effect of dimerization on the aromaticity for phenalenyl-based species. The local stretching force constants, being suitable descriptors of bond strength and π-delocalization, are used to describe the pancake bond interactions of 1–6 and the degree of π-delocalization amongst these bonds and their corresponding dimer species. Directly from computed local stretching force constants we derived bond strength orders. We use measures of AI, and corresponding WS and ALT parameters, to determine what bond property, of the phenalenyl-based species investigated, predominately governs changes in aromaticity. From the results of our work we draw the following: [1] We find that dimer species 1 (1,2,3,5-dithiadiazolyl) and 2 (1,2,3,5-diselenadiazolyl) are significantly stabilized by their chalcogen⋯chalcogen contacts. Unlike 1 and 2, which have C2v symmtery, the 1,2,3,5-ditelluradiazolyl (3) dimer is found to be stable in C2 symmetry as the singlet state is energetically favored over the triplet state, revealed from a negative ΔEST. [2] In regard to the phenalenyl-based dimers, as the substituent size increased from 4 to 6 the stability of the system steadily declined as the steric repulsion between the substituent groups hindered the monomers of these dimers from changing into a orientation of lower energy. [3] As the radius of the chalcogen atoms di-chalcodiazoyl dimers 1–3 increase (Te < Se < S) the strength of the C⋯C contacts decreases. As the strength of the chalcogen⋯chalcogen interactions (i.e. contacts) decrease from 1 to 3 the overall ring strength decreases and the strength of the central (i.e. interdimer) C–C bond decreases [4]. For all phenalenyl-based dimers (4–6) we observed that the BSO n values of peripheral C⋯C are stronger that of their corresponding central C–C bonds. Revealing that pancake bonding interactions contribute largely to the stability of these species [5]. From energy density analysis Hb, following the Cremer-Kraka criteria, we observe the chalcogen⋯chalcogen pancake bonding interactions of the 1,2-dithia-3,5-diazolyl dimer (1) and 1,2-diselena-3,5-diazolyl dimer (2) are covalent in nature as they have negative (stabilizing) Hb values at their bond critical point rb. [6] Unlike the other 1,2-chalcogen-3,5-diazole dimers (1 and 2) the chalcogen⋯chalcogen contacts (i.e. Te⋯Te) of 3 are much weaker in strength and have a positive (destabilizing) energy density value Hb at the Te⋯Te bond critical point rb revealing that the Te⋯Te do not have a typical pancake bond nature as we observed 1 and 2. [7] All pancake bonding interactions within the phenalenyl dimer (4), 2,5,8-trimethylphenalenyldimer (5), and the 2,5,8-tri-t-butylphenalenyl dimer (6) were observed to have postive (destabilizing) Hb values revealing that their pancake interactions are electrostatic in nature. [8] From BSO n(CC) values, the calculated AI, and related WS and ALT parameters we found that the dimerization of phenalenyl-based monomers leads to an increased aromaticity primarily due to CC bond strengthening. [9] From the same parameters mentioned above we observed that the substitution of the phenalenyl dimer, which is necessary for inhibiting σ-dimerization, results in an overall reduction of system aromaticity predominantly through CC bond weakening.
Acknowledgments
In memoriam of Dr. Dieter Cremer (1944-2017) who laid the foundation for this project. This work was financially supported by the National Science Foundation, Grant CHE 1464906. We thank SMU for providing computational resources.
\n',keywords:"local stretching force constant, dimerization, pancake bonding, aromaticity, 2e/mc bonding",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/78532.pdf",chapterXML:"https://mts.intechopen.com/source/xml/78532.xml",downloadPdfUrl:"/chapter/pdf-download/78532",previewPdfUrl:"/chapter/pdf-preview/78532",totalDownloads:102,totalViews:0,totalCrossrefCites:1,dateSubmitted:null,dateReviewed:"July 31st 2021",datePrePublished:"October 8th 2021",datePublished:"May 18th 2022",dateFinished:"September 10th 2021",readingETA:"0",abstract:"From local mode stretching force constants and topological electron density analysis, computed at either the UM06/6-311G(d,p), UM06/SDD, or UM05-2X/6–31++G(d,p) level of theory, we elucidate on the nature/strength of the parallel π-stacking interactions (i.e. pancake bonding) of the 1,2-dithia-3,5-diazolyl dimer, 1,2-diselena-3,5-diazolyl dimer, 1,2-tellura-3,5-diazolyl dimer, phenalenyl dimer, 2,5,8-tri-methylphenalenyl dimer, and the 2,5,8-tri-t-butylphenalenyl dimer. We use local mode stretching force constants to derive an aromaticity delocalization index (AI) for the phenalenyl-based dimers and their monomers as to determine the effect of substitution and dimerization on aromaticity, as well as determining what bond property governs alterations in aromaticity. Our results reveal the strength of the C⋯C contacts and of the rings of the di-chalcodiazoyl dimers investigated decrease in parallel with decreasing chalcogen⋯chalcogen bond strength. Energy density values Hb suggest the S⋯S and Se⋯Se pancake bonds of 1,2-dithia-3,5-diazolyl dimer and the 1,2-diselena-3,5-diazolyl dimer are covalent in nature. We observe the pancake bonds, of all phenalenyl-based dimers investigated, to be electrostatic in nature. In contrast to their monomer counterparts, phenalenyl-based dimers increase in aromaticity primarily due to CC bond strengthening. For phenalenyl-based dimers we observed that the addition of bulky substituents steadily decreased the system aromaticity predominately due to CC bond weakening.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/78532",risUrl:"/chapter/ris/78532",signatures:"Alexis Antoinette Ann Delgado, Alan Humason and Elfi Kraka",book:{id:"11001",type:"book",title:"Density Functional Theory",subtitle:"Recent Advances, New Perspectives and Applications",fullTitle:"Density Functional Theory - Recent Advances, New Perspectives and Applications",slug:"density-functional-theory-recent-advances-new-perspectives-and-applications",publishedDate:"May 18th 2022",bookSignature:"Daniel Glossman-Mitnik",coverURL:"https://cdn.intechopen.com/books/images_new/11001.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",isbn:"978-1-83969-846-0",printIsbn:"978-1-83969-845-3",pdfIsbn:"978-1-83969-847-7",isAvailableForWebshopOrdering:!0,editors:[{id:"198499",title:"Dr.",name:"Daniel",middleName:null,surname:"Glossman-Mitnik",slug:"daniel-glossman-mitnik",fullName:"Daniel Glossman-Mitnik"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"418191",title:"Prof.",name:"Elfi",middleName:null,surname:"Kraka",fullName:"Elfi Kraka",slug:"elfi-kraka",email:"ekraka@smu.edu",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"419169",title:"Mrs.",name:"Alexis",middleName:null,surname:"Antoinette Ann Delgado",fullName:"Alexis Antoinette Ann Delgado",slug:"alexis-antoinette-ann-delgado",email:"alexisdelgado81096@gmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"Southern Methodist University",institutionURL:null,country:{name:"United States of America"}}},{id:"427809",title:"Dr.",name:"Alan",middleName:null,surname:"Humason",fullName:"Alan Humason",slug:"alan-humason",email:"ahumason@smu.edu",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"Southern Methodist University",institutionURL:null,country:{name:"United States of America"}}}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Computational methods",level:"1"},{id:"sec_3",title:"3. Results and discussion",level:"1"},{id:"sec_3_2",title:"3.1 Energetics",level:"2"},{id:"sec_4_2",title:"3.2 Bond parameters and derived bond strength orders n",level:"2"},{id:"sec_5_2",title:"3.3 Aromaticity and ring strength of phenalenyl-based monomers and dimers",level:"2"},{id:"sec_7",title:"4. Conclusions",level:"1"},{id:"sec_8",title:"Acknowledgments",level:"1"}],chapterReferences:[{id:"B1",body:'Mulliken RS, Person WB. Molecular Complexes: Chapter 16 – Inner and Outer Complexes with π-Acceptors. Hoboken, NJ: Wiley-Interscience; 1969.'},{id:"B2",body:'Gleiter R, Haberhauer G. Chapter 3: Aromaticity and Other Conjugation Effects. VCH, Weinheim: Wiley; 2012.'},{id:"B3",body:'Boeré RT. Experimental and computational evidence for “double pancake bonds”: The role of dispersion-corrected DFT methods in strongly dimerized 5-aryl-1λ2,3λ2-dithia-2,4,6-triazines. 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We conclude this chapter by expressing personal perspective on the probable challenges and developments of the controllable synthesis of CeO2 nanomaterials for various applications.",book:{id:"5510",slug:"functionalized-nanomaterials",title:"Functionalized Nanomaterials",fullTitle:"Functionalized Nanomaterials"},signatures:"Adnan Younis, Dewei Chu and Sean Li",authors:[{id:"191574",title:"Dr.",name:"Adnan",middleName:null,surname:"Younis",slug:"adnan-younis",fullName:"Adnan Younis"}]},{id:"9725",doi:"10.5772/8508",title:"Biosynthesis and Application of Silver and Gold Nanoparticles",slug:"biosynthesis-and-application-of-silver-and-gold-nanoparticles",totalDownloads:27930,totalCrossrefCites:23,totalDimensionsCites:58,abstract:null,book:{id:"3621",slug:"silver-nanoparticles",title:"Silver Nanoparticles",fullTitle:"Silver Nanoparticles"},signatures:"Zygmunt Sadowski",authors:null},{id:"17194",doi:"10.5772/21694",title:"Properties of Nanofillers in Polymer",slug:"properties-of-nanofillers-in-polymer",totalDownloads:20390,totalCrossrefCites:9,totalDimensionsCites:56,abstract:null,book:{id:"1045",slug:"nanocomposites-and-polymers-with-analytical-methods",title:"Nanocomposites and Polymers with Analytical Methods",fullTitle:"Nanocomposites and Polymers with Analytical Methods"},signatures:"Damien M. 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Nanotechnology is widely considered to constitute the basis of the next technological revolution, following on from the first Industrial Revolution, which began around 1750 with the introduction of the steam engine and steelmaking. Nanotechnology is defined as the design, characterization, production, and application of materials, devices and systems by controlling shape and size of the nanoscale. The nanoscale itself is at present considered to cover the range from 1 to 100 nm. All samples prepared in thin film forms and the characterization revealed their nanostructure. The major exploitation of thin films has been in microelectronics, there are numerous and growing applications in communications, optical electronics, coatings of all kinds, and in energy generation. A great many sophisticated analytical instruments and techniques, largely developed to characterize thin films, have already become indispensable in virtually every scientific endeavor irrespective of discipline. Among all these techniques, electrodeposition is the most suitable technique for nanostructured thin films from aqueous solution served as samples under investigation. The electrodeposition of metallic layers from aqueous solution is based on the discharge of metal ions present in the electrolyte at a cathodic surface (the substrate or component.) The metal ions accept an electron from the electrically conducting material at the solid- electrolyte interface and then deposit as metal atoms onto the surface. The electrons necessary for this to occur are either supplied from an externally applied potential source or are surrendered by a reducing agent present in solution (electroless reduction). The metal ions themselves derive either from metal salts added to solution, or by the anodic dissolution of the so-called sacrificial anodes, made of the same metal that is to be deposited at the cathode.",book:{id:"4718",slug:"electroplating-of-nanostructures",title:"Electroplating of Nanostructures",fullTitle:"Electroplating of Nanostructures"},signatures:"Souad A. M. Al-Bat’hi",authors:[{id:"174793",title:"Dr.",name:"Mohamad",middleName:null,surname:"Souad",slug:"mohamad-souad",fullName:"Mohamad Souad"}]},{id:"54226",title:"Localized Surface Plasmon Resonance for Optical Fiber-Sensing Applications",slug:"localized-surface-plasmon-resonance-for-optical-fiber-sensing-applications",totalDownloads:2270,totalCrossrefCites:2,totalDimensionsCites:5,abstract:"It is well known that optical fiber sensors have attracted the attention of scientific community due to its intrinsic advantages, such as lightweight, small size, portability, remote sensing, immunity to electromagnetic interferences and the possibility of multiplexing several signals. This field has shown a dramatic growth thanks to the creation of sensitive thin films onto diverse optical fiber configurations. In this sense, a wide range of optical fiber devices have been successfully fabricated for monitoring biological, chemical, medical or physical parameters. In addition, the use of nanoparticles into the sensitive thin films has resulted in an enhancement in the response time, robustness or sensitivity in the optical devices, which is associated to the inherent properties of nanoparticles (high surface area ratio or porosity). Among all of them, the metallic nanoparticles are of great interest for sensing applications due to the presence of strong absorption bands in the visible and near-infrared regions, due to their localized surface plasmon resonances (LSPR). These optical resonances are due to the coupling of certain modes of the incident light to the collective oscillation of the conduction electrons of the metallic nanoparticles. The LSPR extinction bands are very useful for sensing applications as far as they can be affected by refractive index variations of the surrounding medium of the nanoparticles, and therefore, it is possible to create optical sensors with outstanding properties such as high sensitivity and optical self-reference. In this chapter, the attractive optical properties of metal nanostructures and their implementation into different optical fiber configuration for sensing or biosensing applications will be studied.",book:{id:"5721",slug:"nanoplasmonics-fundamentals-and-applications",title:"Nanoplasmonics",fullTitle:"Nanoplasmonics - Fundamentals and Applications"},signatures:"Pedro J. Rivero, Javier Goicoechea and Francisco J. Arregui",authors:[{id:"69816",title:"Dr.",name:"Javier",middleName:null,surname:"Goicoechea",slug:"javier-goicoechea",fullName:"Javier Goicoechea"},{id:"188796",title:"Dr.",name:"Pedro J.",middleName:null,surname:"Rivero",slug:"pedro-j.-rivero",fullName:"Pedro J. 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Piezoelectric materials are capable of transforming mechanical strain and vibration energy into electrical energy. This property allows opportunities for implementing renewable and sustainable energy through power harvesting and self-sustained smart sensing in buildings. As the most common construction material, plain cement paste lacks satisfactory piezoelectricity and is not efficient at harvesting the electrical energy from the ambient vibrations of a building system. In recent years, many techniques have been proposed and applied to improve the piezoelectric capacity of cement-based composite, namely admixture incorporation and physical. The successful application of piezoelectric materials for sustainable building development not only relies on understanding the mechanism of the piezoelectric properties of various building components, but also the latest developments and implementations in the building industry. Therefore, this review systematically illustrates research efforts to develop new construction materials with high piezoelectricity and energy storage capacity. In addition, this article discusses the latest techniques for utilizing the piezoelectric materials in energy harvesters, sensors and actuators for various building systems. With advanced methods for improving the cementations piezoelectricity and applying the material piezoelectricity for different building functions, more renewable and sustainable building systems are anticipated.",book:{id:"10511",slug:"multifunctional-ferroelectric-materials",title:"Multifunctional Ferroelectric Materials",fullTitle:"Multifunctional Ferroelectric Materials"},signatures:"B. Chandra Sekhar, B. Dhanalakshmi, B. Srinivasa Rao, S. Ramesh, K. Venkata Prasad, P.S.V. Subba Rao and B. Parvatheeswara Rao",authors:[{id:"335022",title:"Dr.",name:"B. Chandra",middleName:null,surname:"Sekhar",slug:"b.-chandra-sekhar",fullName:"B. Chandra Sekhar"},{id:"422021",title:"Dr.",name:"B.",middleName:null,surname:"Dhanalakshmi",slug:"b.-dhanalakshmi",fullName:"B. Dhanalakshmi"},{id:"422022",title:"Dr.",name:"B.Srinivasa",middleName:null,surname:"Rao",slug:"b.srinivasa-rao",fullName:"B.Srinivasa Rao"},{id:"422023",title:"Dr.",name:"S.",middleName:null,surname:"Ramesh",slug:"s.-ramesh",fullName:"S. Ramesh"},{id:"422024",title:"Dr.",name:"K.Venkata",middleName:null,surname:"Prasad",slug:"k.venkata-prasad",fullName:"K.Venkata Prasad"},{id:"422025",title:"Dr.",name:"P.S.V",middleName:null,surname:"Subba Rao",slug:"p.s.v-subba-rao",fullName:"P.S.V Subba Rao"},{id:"422026",title:"Dr.",name:"B.Parvatheeswara",middleName:null,surname:"Rao",slug:"b.parvatheeswara-rao",fullName:"B.Parvatheeswara Rao"}]}],onlineFirstChaptersFilter:{topicId:"1169",limit:6,offset:0},onlineFirstChaptersCollection:[{id:"81438",title:"Research Progress of Ionic Thermoelectric Materials for Energy Harvesting",slug:"research-progress-of-ionic-thermoelectric-materials-for-energy-harvesting",totalDownloads:25,totalDimensionsCites:0,doi:"10.5772/intechopen.101771",abstract:"Thermoelectric material is a kind of functional material that can mutually convert heat energy and electric energy. It can convert low-grade heat energy (less than 130°C) into electric energy. Compared with traditional electronic thermoelectric materials, ionic thermoelectric materials have higher performance. The Seebeck coefficient can generate 2–3 orders of magnitude higher ionic thermoelectric potential than electronic thermoelectric materials, so it has good application prospects in small thermoelectric generators and solar power generation. According to the thermoelectric conversion mechanism, ionic thermoelectric materials can be divided into ionic thermoelectric materials based on the Soret effect and thermocouple effect. They are widely used in pyrogen batteries and ionic thermoelectric capacitors. The latest two types of ionic thermoelectric materials are in this article. The research progress is explained, and the problems and challenges of ionic thermoelectric materials and the future development direction are also put forward.",book:{id:"10037",title:"Thermoelectricity - Recent Advances, New Perspectives and Applications",coverURL:"https://cdn.intechopen.com/books/images_new/10037.jpg"},signatures:"Jianwei Zhang, Ying Xiao, Bowei Lei, Gengyuan Liang and Wenshu Zhao"},{id:"77670",title:"Thermoelectric Elements with Negative Temperature Factor of Resistance",slug:"thermoelectric-elements-with-negative-temperature-factor-of-resistance",totalDownloads:72,totalDimensionsCites:0,doi:"10.5772/intechopen.98860",abstract:"The method of manufacturing of ceramic materials on the basis of ferrites of nickel and cobalt by synthesis and sintering in controllable regenerative atmosphere is presented. As the generator of regenerative atmosphere the method of conversion of carbonic gas is offered. Calculation of regenerative atmosphere for simultaneous sintering of ceramic ferrites of nickel and cobalt is carried out. It is offered, methods of the dilated nonequilibrium thermodynamics to view process of distribution of a charge and heat along a thermoelement branch. The model of a thermoelement taking into account various relaxation times of a charge and warmth is constructed.",book:{id:"10037",title:"Thermoelectricity - Recent Advances, New Perspectives and Applications",coverURL:"https://cdn.intechopen.com/books/images_new/10037.jpg"},signatures:"Yuri Bokhan"},{id:"79236",title:"Processing Techniques with Heating Conditions for Multiferroic Systems of BiFeO3, BaTiO3, PbTiO3, CaTiO3 Thin Films",slug:"processing-techniques-with-heating-conditions-for-multiferroic-systems-of-bifeo3-batio3-pbtio3-catio",totalDownloads:96,totalDimensionsCites:0,doi:"10.5772/intechopen.101122",abstract:"In this chapter, we have report a list of synthesis methods (including both synthesis steps & heating conditions) used for thin film fabrication of perovskite ABO3 (BiFeO3, BaTiO3, PbTiO3 and CaTiO3) based multiferroics (in both single-phase and composite materials). The processing of high quality multiferroic thin film have some features like epitaxial strain, physical phenomenon at atomic-level, interfacial coupling parameters to enhance device performance. Since these multiferroic thin films have ME properties such as electrical (dielectric, magnetoelectric coefficient & MC) and magnetic (ferromagnetic, magnetic susceptibility etc.) are heat sensitive, i.e. ME response at low as well as higher temperature might to enhance the device performance respect with long range ordering. The magnetoelectric coupling between ferromagnetism and ferroelectricity in multiferroic becomes suitable in the application of spintronics, memory and logic devices, and microelectronic memory or piezoelectric devices. In comparison with bulk multiferroic, the fabrication of multiferroic thin film with different structural geometries on substrate has reducible clamping effect. A brief procedure for multiferroic thin film fabrication in terms of their thermal conditions (temperature for film processing and annealing for crystallization) are described. Each synthesis methods have its own characteristic phenomenon in terms of film thickness, defects formation, crack free film, density, chip size, easier steps and availability etc. been described. A brief study towards phase structure and ME coupling for each multiferroic system of BiFeO3, BaTiO3, PbTiO3 and CaTiO3 is shown.",book:{id:"10037",title:"Thermoelectricity - Recent Advances, New Perspectives and Applications",coverURL:"https://cdn.intechopen.com/books/images_new/10037.jpg"},signatures:"Kuldeep Chand Verma and Manpreet Singh"},{id:"78034",title:"Quantum Physical Interpretation of Thermoelectric Properties of Ruthenate Pyrochlores",slug:"quantum-physical-interpretation-of-thermoelectric-properties-of-ruthenate-pyrochlores",totalDownloads:78,totalDimensionsCites:0,doi:"10.5772/intechopen.99260",abstract:"Lead- and lead-yttrium ruthenate pyrochlores were synthesized and investigated for Seebeck coefficients, electrical- and thermal conductivity. Compounds A2B2O6.5+z with 0 ≤ z < 0.5 were defect pyrochlores and p-type conductors. The thermoelectric data were analyzed using quantum physical models to identify scattering mechanisms underlying electrical (σ) and thermal conductivity (κ) and to understand the temperature dependence of the Seebeck effect (S). In the metal-like lead ruthenates with different Pb:Ru ratios, σ (T) and the electronic thermal conductivity κe (T) were governed by ‘electron impurity scattering’, the lattice thermal conductivity κL (T) by the 3-phonon resistive process (Umklapp scattering). In the lead-yttrium ruthenate solid solutions (Pb(2-x)YxRu2O(6.5±z)), a metal–insulator transition occurred at 0.2 moles of yttrium. On the metallic side (<0.2 moles Y) ‘electron impurity scattering’ prevailed. On the semiconductor/insulator side between x = 0.2 and x = 1.0 several mechanisms were equally likely. At x > 1.5 the Mott Variable Range Hopping mechanism was active. S (T) was discussed for Pb-Y-Ru pyrochlores in terms of the effect of minority carrier excitation at lower- and a broadening of the Fermi distribution at higher temperatures. The figures of merit of all of these pyrochlores were still small (≤7.3 × 10−3).",book:{id:"10037",title:"Thermoelectricity - Recent Advances, New Perspectives and Applications",coverURL:"https://cdn.intechopen.com/books/images_new/10037.jpg"},signatures:"Sepideh Akhbarifar"},{id:"77635",title:"Optimization of Thermoelectric Properties Based on Rashba Spin Splitting",slug:"optimization-of-thermoelectric-properties-based-on-rashba-spin-splitting",totalDownloads:125,totalDimensionsCites:0,doi:"10.5772/intechopen.98788",abstract:"In recent years, the application of thermoelectricity has become more and more widespread. Thermoelectric materials provide a simple and environmentally friendly solution for the direct conversion of heat to electricity. The development of higher performance thermoelectric materials and their performance optimization have become more important. Generally, to improve the ZT value, electrical conductivity, Seebeck coefficient and thermal conductivity must be globally optimized as a whole object. However, due to the strong coupling among ZT parameters in many cases, it is very challenging to break the bottleneck of ZT optimization currently. Beyond the traditional optimization methods (such as inducing defects, varying temperature), the Rashba effect is expected to effectively increase the S2σ and decrease the κ, thus enhancing thermoelectric performance, which provides a new strategy to develop new-generation thermoelectric materials. Although the Rashba effect has great potential in enhancing thermoelectric performance, the underlying mechanism of Rashba-type thermoelectric materials needs further research. In addition, how to introduce Rashba spin splitting into current thermoelectric materials is also of great significance to the optimization of thermoelectricity.",book:{id:"10037",title:"Thermoelectricity - Recent Advances, New Perspectives and Applications",coverURL:"https://cdn.intechopen.com/books/images_new/10037.jpg"},signatures:"Zhenzhen Qin"},{id:"75364",title:"Challenges in Improving Performance of Oxide Thermoelectrics Using Defect Engineering",slug:"challenges-in-improving-performance-of-oxide-thermoelectrics-using-defect-engineering",totalDownloads:215,totalDimensionsCites:0,doi:"10.5772/intechopen.96278",abstract:"Oxide thermoelectric materials are considered promising for high-temperature thermoelectric applications in terms of low cost, temperature stability, reversible reaction, and so on. Oxide materials have been intensively studied to suppress the defects and electronic charge carriers for many electronic device applications, but the studies with a high concentration of defects are limited. It desires to improve thermoelectric performance by enhancing its charge transport and lowering its lattice thermal conductivity. For this purpose, here, we modified the stoichiometry of cation and anion vacancies in two different systems to regulate the carrier concentration and explored their thermoelectric properties. Both cation and anion vacancies act as a donor of charge carriers and act as phonon scattering centers, decoupling the electrical conductivity and thermal conductivity.",book:{id:"10037",title:"Thermoelectricity - Recent Advances, New Perspectives and Applications",coverURL:"https://cdn.intechopen.com/books/images_new/10037.jpg"},signatures:"Jamil Ur Rahman, Gul Rahman and Soonil Lee"}],onlineFirstChaptersTotal:6},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:0,limit:8,total:null},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:87,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:98,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:27,numberOfPublishedChapters:288,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:9,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:139,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:129,numberOfOpenTopics:0,numberOfUpcomingTopics:2,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!1},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:107,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:10,numberOfPublishedChapters:103,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:12,numberOfOpenTopics:2,numberOfUpcomingTopics:1,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:0,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!1},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:0,numberOfPublishedChapters:11,numberOfOpenTopics:4,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}},{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. The whole process of submitting an article and editing of the submitted article goes extremely smooth and fast, the number of reads and downloads of chapters is high, and the contributions are also frequently cited.",author:{id:"55578",name:"Antonio",surname:"Jurado-Navas",institutionString:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",slug:"antonio-jurado-navas",institution:{id:"720",name:"University of Malaga",country:{id:null,name:"Spain"}}}}]},series:{item:{id:"11",title:"Biochemistry",doi:"10.5772/intechopen.72877",issn:"2632-0983",scope:"Biochemistry, the study of chemical transformations occurring within living organisms, impacts all areas of life sciences, from molecular crystallography and genetics to ecology, medicine, and population biology. Biochemistry examines macromolecules - proteins, nucleic acids, carbohydrates, and lipids – and their building blocks, structures, functions, and interactions. Much of biochemistry is devoted to enzymes, proteins that catalyze chemical reactions, enzyme structures, mechanisms of action and their roles within cells. Biochemistry also studies small signaling molecules, coenzymes, inhibitors, vitamins, and hormones, which play roles in life processes. Biochemical experimentation, besides coopting classical chemistry methods, e.g., chromatography, adopted new techniques, e.g., X-ray diffraction, electron microscopy, NMR, radioisotopes, and developed sophisticated microbial genetic tools, e.g., auxotroph mutants and their revertants, fermentation, etc. More recently, biochemistry embraced the ‘big data’ omics systems. Initial biochemical studies have been exclusively analytic: dissecting, purifying, and examining individual components of a biological system; in the apt words of Efraim Racker (1913 –1991), “Don’t waste clean thinking on dirty enzymes.” Today, however, biochemistry is becoming more agglomerative and comprehensive, setting out to integrate and describe entirely particular biological systems. The ‘big data’ metabolomics can define the complement of small molecules, e.g., in a soil or biofilm sample; proteomics can distinguish all the comprising proteins, e.g., serum; metagenomics can identify all the genes in a complex environment, e.g., the bovine rumen. This Biochemistry Series will address the current research on biomolecules and the emerging trends with great promise.",coverUrl:"https://cdn.intechopen.com/series/covers/11.jpg",latestPublicationDate:"May 24th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:27,editor:{id:"31610",title:"Dr.",name:"Miroslav",middleName:null,surname:"Blumenberg",slug:"miroslav-blumenberg",fullName:"Miroslav Blumenberg",profilePictureURL:"https://mts.intechopen.com/storage/users/31610/images/system/31610.jpg",biography:"Miroslav Blumenberg, Ph.D., was born in Subotica and received his BSc in Belgrade, Yugoslavia. He completed his Ph.D. at MIT in Organic Chemistry; he followed up his Ph.D. with two postdoctoral study periods at Stanford University. Since 1983, he has been a faculty member of the RO Perelman Department of Dermatology, NYU School of Medicine, where he is codirector of a training grant in cutaneous biology. Dr. Blumenberg’s research is focused on the epidermis, expression of keratin genes, transcription profiling, keratinocyte differentiation, inflammatory diseases and cancers, and most recently the effects of the microbiome on the skin. He has published more than 100 peer-reviewed research articles and graduated numerous Ph.D. and postdoctoral students.",institutionString:null,institution:{name:"New York University Langone Medical Center",institutionURL:null,country:{name:"United States of America"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:3,paginationItems:[{id:"19",title:"Animal Science",coverUrl:"https://cdn.intechopen.com/series_topics/covers/19.jpg",isOpenForSubmission:!0,editor:{id:"259298",title:"Dr.",name:"Edward",middleName:null,surname:"Narayan",slug:"edward-narayan",fullName:"Edward Narayan",profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",biography:"Dr. Edward Narayan graduated with Ph.D. degree in Biology from the University of the South Pacific and pioneered non-invasive reproductive and stress endocrinology tools for amphibians - the novel development and validation of non-invasive enzyme immunoassays for the evaluation of reproductive hormonal cycle and stress hormone responses to environmental stressors. \nDr. Narayan leads the Stress Lab (Comparative Physiology and Endocrinology) at the University of Queensland. A dynamic career research platform which is based on the thematic areas of comparative vertebrate physiology, stress endocrinology, reproductive endocrinology, animal health and welfare, and conservation biology. \nEdward has supervised 40 research students and published over 60 peer reviewed research.",institutionString:null,institution:{name:"University of Queensland",institutionURL:null,country:{name:"Australia"}}},editorTwo:null,editorThree:null},{id:"20",title:"Animal Nutrition",coverUrl:"https://cdn.intechopen.com/series_topics/covers/20.jpg",isOpenForSubmission:!0,editor:{id:"175967",title:"Dr.",name:"Manuel",middleName:null,surname:"Gonzalez Ronquillo",slug:"manuel-gonzalez-ronquillo",fullName:"Manuel Gonzalez Ronquillo",profilePictureURL:"https://mts.intechopen.com/storage/users/175967/images/system/175967.png",biography:"Dr. Manuel González Ronquillo obtained his doctorate degree from the University of Zaragoza, Spain, in 2001. He is a research professor at the Faculty of Veterinary Medicine and Animal Husbandry, Autonomous University of the State of Mexico. He is also a level-2 researcher. He received a Fulbright-Garcia Robles fellowship for a postdoctoral stay at the US Dairy Forage Research Center, Madison, Wisconsin, USA in 2008–2009. He received grants from Alianza del Pacifico for a stay at the University of Magallanes, Chile, in 2014, and from Consejo Nacional de Ciencia y Tecnología (CONACyT) to work in the Food and Agriculture Organization’s Animal Production and Health Division (AGA), Rome, Italy, in 2014–2015. He has collaborated with researchers from different countries and published ninety-eight journal articles. He teaches various degree courses in zootechnics, sheep production, and agricultural sciences and natural resources.\n\nDr. Ronquillo’s research focuses on the evaluation of sustainable animal diets (StAnD), using native resources of the region, decreasing carbon footprint, and applying meta-analysis and mathematical models for a better understanding of animal production.",institutionString:null,institution:{name:"Universidad Autónoma del Estado de México",institutionURL:null,country:{name:"Mexico"}}},editorTwo:null,editorThree:null},{id:"28",title:"Animal Reproductive Biology and Technology",coverUrl:"https://cdn.intechopen.com/series_topics/covers/28.jpg",isOpenForSubmission:!0,editor:{id:"177225",title:"Prof.",name:"Rosa Maria Lino Neto",middleName:null,surname:"Pereira",slug:"rosa-maria-lino-neto-pereira",fullName:"Rosa Maria Lino Neto Pereira",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bS9wkQAC/Profile_Picture_1624519982291",biography:"Rosa Maria Lino Neto Pereira (DVM, MsC, PhD and) is currently a researcher at the Genetic Resources and Biotechnology Unit of the National Institute of Agrarian and Veterinarian Research (INIAV, Portugal). She is the head of the Reproduction and Embryology Laboratories and was lecturer of Reproduction and Reproductive Biotechnologies at Veterinary Medicine Faculty. She has over 25 years of experience working in reproductive biology and biotechnology areas with a special emphasis on embryo and gamete cryopreservation, for research and animal genetic resources conservation, leading research projects with several peer-reviewed papers. Rosa Pereira is member of the ERFP-FAO Ex situ Working Group and of the Management Commission of the Portuguese Animal Germplasm Bank.",institutionString:"The National Institute for Agricultural and Veterinary Research. Portugal",institution:null},editorTwo:null,editorThree:null}]},overviewPageOFChapters:{paginationCount:19,paginationItems:[{id:"81793",title:"Canine parvovirus-2: An Emerging Threat to Young Pets",doi:"10.5772/intechopen.104846",signatures:"Mithilesh Singh, Rajendran Manikandan, Ujjwal Kumar De, Vishal Chander, Babul Rudra Paul, Saravanan Ramakrishnan and Darshini Maramreddy",slug:"canine-parvovirus-2-an-emerging-threat-to-young-pets",totalDownloads:8,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Recent Advances in Canine Medicine",coverURL:"https://cdn.intechopen.com/books/images_new/11580.jpg",subseries:{id:"19",title:"Animal Science"}}},{id:"81271",title:"The Diversity of Parvovirus Telomeres",doi:"10.5772/intechopen.102684",signatures:"Marianne Laugel, Emilie Lecomte, Eduard Ayuso, Oumeya Adjali, Mathieu Mével and Magalie Penaud-Budloo",slug:"the-diversity-of-parvovirus-telomeres",totalDownloads:23,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Recent Advances in Canine Medicine",coverURL:"https://cdn.intechopen.com/books/images_new/11580.jpg",subseries:{id:"19",title:"Animal Science"}}},{id:"79909",title:"Cryopreservation Methods and Frontiers in the Art of Freezing Life in Animal Models",doi:"10.5772/intechopen.101750",signatures:"Feda S. Aljaser",slug:"cryopreservation-methods-and-frontiers-in-the-art-of-freezing-life-in-animal-models",totalDownloads:172,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Animal Reproduction",coverURL:"https://cdn.intechopen.com/books/images_new/10664.jpg",subseries:{id:"28",title:"Animal Reproductive Biology and Technology"}}},{id:"79782",title:"Avian Reproduction",doi:"10.5772/intechopen.101185",signatures:"Kingsley Omogiade Idahor",slug:"avian-reproduction",totalDownloads:152,totalCrossrefCites:0,totalDimensionsCites:0,authors:[{name:"Kingsley O.",surname:"Idahor"}],book:{title:"Animal Reproduction",coverURL:"https://cdn.intechopen.com/books/images_new/10664.jpg",subseries:{id:"28",title:"Animal Reproductive Biology and Technology"}}}]},overviewPagePublishedBooks:{paginationCount:10,paginationItems:[{type:"book",id:"7233",title:"New Insights into Theriogenology",subtitle:null,coverURL:"https://cdn.intechopen.com/books/images_new/7233.jpg",slug:"new-insights-into-theriogenology",publishedDate:"December 5th 2018",editedByType:"Edited by",bookSignature:"Rita Payan-Carreira",hash:"74f4147e3fb214dd050e5edd3aaf53bc",volumeInSeries:1,fullTitle:"New Insights into Theriogenology",editors:[{id:"38652",title:"Prof.",name:"Rita",middleName:null,surname:"Payan-Carreira",slug:"rita-payan-carreira",fullName:"Rita Payan-Carreira",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRiFPQA0/Profile_Picture_1614601496313",biography:"Rita Payan Carreira earned her Veterinary Degree from the Faculty of Veterinary Medicine in Lisbon, Portugal, in 1985. She obtained her Ph.D. in Veterinary Sciences from the University of Trás-os-Montes e Alto Douro, Portugal. After almost 32 years of teaching at the University of Trás-os-Montes and Alto Douro, she recently moved to the University of Évora, Department of Veterinary Medicine, where she teaches in the field of Animal Reproduction and Clinics. Her primary research areas include the molecular markers of the endometrial cycle and the embryo–maternal interaction, including oxidative stress and the reproductive physiology and disorders of sexual development, besides the molecular determinants of male and female fertility. She often supervises students preparing their master's or doctoral theses. She is also a frequent referee for various journals.",institutionString:null,institution:{name:"University of Évora",institutionURL:null,country:{name:"Portugal"}}}]},{type:"book",id:"7144",title:"Veterinary Anatomy and Physiology",subtitle:null,coverURL:"https://cdn.intechopen.com/books/images_new/7144.jpg",slug:"veterinary-anatomy-and-physiology",publishedDate:"March 13th 2019",editedByType:"Edited by",bookSignature:"Catrin Sian Rutland and Valentina Kubale",hash:"75cdacb570e0e6d15a5f6e69640d87c9",volumeInSeries:2,fullTitle:"Veterinary Anatomy and Physiology",editors:[{id:"202192",title:"Dr.",name:"Catrin",middleName:null,surname:"Rutland",slug:"catrin-rutland",fullName:"Catrin Rutland",profilePictureURL:"https://mts.intechopen.com/storage/users/202192/images/system/202192.png",biography:"Catrin Rutland is an Associate Professor of Anatomy and Developmental Genetics at the University of Nottingham, UK. She obtained a BSc from the University of Derby, England, a master’s degree from Technische Universität München, Germany, and a Ph.D. from the University of Nottingham. She undertook a post-doctoral research fellowship in the School of Medicine before accepting tenure in Veterinary Medicine and Science. Dr. Rutland also obtained an MMedSci (Medical Education) and a Postgraduate Certificate in Higher Education (PGCHE). She is the author of more than sixty peer-reviewed journal articles, twelve books/book chapters, and more than 100 research abstracts in cardiovascular biology and oncology. She is a board member of the European Association of Veterinary Anatomists, Fellow of the Anatomical Society, and Senior Fellow of the Higher Education Academy. 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He is also Member of the Laboratory of genetic, animal and feed resource and member of Animal science Department of INAT. He graduated from Higher School of Agriculture of Mateur, University of Carthage, in 2002 and completed his masters in 2006. Dr. M’HAMDI completed his PhD thesis in Genetic welfare indicators of dairy cattle at Higher Institute of Agronomy of Chott-Meriem, University of Sousse, in 2011. 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