Key 1H- and 13C-NMR spectral data for identification of isoflavonoid classes.
\\n\\n
Dr. Pletser’s experience includes 30 years of working with the European Space Agency as a Senior Physicist/Engineer and coordinating their parabolic flight campaigns, and he is the Guinness World Record holder for the most number of aircraft flown (12) in parabolas, personally logging more than 7,300 parabolas.
\\n\\nSeeing the 5,000th book published makes us at the same time proud, happy, humble, and grateful. This is a great opportunity to stop and celebrate what we have done so far, but is also an opportunity to engage even more, grow, and succeed. It wouldn't be possible to get here without the synergy of team members’ hard work and authors and editors who devote time and their expertise into Open Access book publishing with us.
\\n\\nOver these years, we have gone from pioneering the scientific Open Access book publishing field to being the world’s largest Open Access book publisher. Nonetheless, our vision has remained the same: to meet the challenges of making relevant knowledge available to the worldwide community under the Open Access model.
\\n\\nWe are excited about the present, and we look forward to sharing many more successes in the future.
\\n\\nThank you all for being part of the journey. 5,000 times thank you!
\\n\\nNow with 5,000 titles available Open Access, which one will you read next?
\\n\\nRead, share and download for free: https://www.intechopen.com/books
\\n\\n\\n\\n
\\n"}]',published:!0,mainMedia:null},components:[{type:"htmlEditorComponent",content:'
Preparation of Space Experiments edited by international leading expert Dr. Vladimir Pletser, Director of Space Training Operations at Blue Abyss is the 5,000th Open Access book published by IntechOpen and our milestone publication!
\n\n"This book presents some of the current trends in space microgravity research. The eleven chapters introduce various facets of space research in physical sciences, human physiology and technology developed using the microgravity environment not only to improve our fundamental understanding in these domains but also to adapt this new knowledge for application on earth." says the editor. Listen what else Dr. Pletser has to say...
\n\n\n\nDr. Pletser’s experience includes 30 years of working with the European Space Agency as a Senior Physicist/Engineer and coordinating their parabolic flight campaigns, and he is the Guinness World Record holder for the most number of aircraft flown (12) in parabolas, personally logging more than 7,300 parabolas.
\n\nSeeing the 5,000th book published makes us at the same time proud, happy, humble, and grateful. This is a great opportunity to stop and celebrate what we have done so far, but is also an opportunity to engage even more, grow, and succeed. It wouldn't be possible to get here without the synergy of team members’ hard work and authors and editors who devote time and their expertise into Open Access book publishing with us.
\n\nOver these years, we have gone from pioneering the scientific Open Access book publishing field to being the world’s largest Open Access book publisher. Nonetheless, our vision has remained the same: to meet the challenges of making relevant knowledge available to the worldwide community under the Open Access model.
\n\nWe are excited about the present, and we look forward to sharing many more successes in the future.
\n\nThank you all for being part of the journey. 5,000 times thank you!
\n\nNow with 5,000 titles available Open Access, which one will you read next?
\n\nRead, share and download for free: https://www.intechopen.com/books
\n\n\n\n
\n'}],latestNews:[{slug:"stanford-university-identifies-top-2-scientists-over-1-000-are-intechopen-authors-and-editors-20210122",title:"Stanford University Identifies Top 2% Scientists, Over 1,000 are IntechOpen Authors and Editors"},{slug:"intechopen-authors-included-in-the-highly-cited-researchers-list-for-2020-20210121",title:"IntechOpen Authors Included in the Highly Cited Researchers List for 2020"},{slug:"intechopen-maintains-position-as-the-world-s-largest-oa-book-publisher-20201218",title:"IntechOpen Maintains Position as the World’s Largest OA Book Publisher"},{slug:"all-intechopen-books-available-on-perlego-20201215",title:"All IntechOpen Books Available on Perlego"},{slug:"oiv-awards-recognizes-intechopen-s-editors-20201127",title:"OIV Awards Recognizes IntechOpen's Editors"},{slug:"intechopen-joins-crossref-s-initiative-for-open-abstracts-i4oa-to-boost-the-discovery-of-research-20201005",title:"IntechOpen joins Crossref's Initiative for Open Abstracts (I4OA) to Boost the Discovery of Research"},{slug:"intechopen-hits-milestone-5-000-open-access-books-published-20200908",title:"IntechOpen hits milestone: 5,000 Open Access books published!"},{slug:"intechopen-books-hosted-on-the-mathworks-book-program-20200819",title:"IntechOpen Books Hosted on the MathWorks Book Program"}]},book:{item:{type:"book",id:"1052",leadTitle:null,fullTitle:"Appendicitis - A Collection of Essays from Around the World",title:"Appendicitis",subtitle:"A Collection of Essays from Around the World",reviewType:"peer-reviewed",abstract:"This book is a collection of essays and papers from around the world, written by surgeons who look after patients of all ages with abdominal pain, many of whom have appendicitis. 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\r\n\tFoams had always been a paramount material form for industry and science thanks to their wide application range in several industrial, civil and chemical processes. Foams also have many desirable properties, like lightness, resilience, thermal and acoustic insulation, noise absorption, adjustable airflow resistivity and porosity, resistivity to the diffusion of energy flow like heat and so on. They are also stable materials that can absorb gases or liquids and can be used as filters, bio-scaffolds for tissue engineering. Their principal characteristic is to feature a high surface area capable of storing energy or convert it from one form to another. This property could be used to enhance the performance of foams in terms of life existence, robustness and reliability. For these reasons, this book aim is to offer to readers a broad state-of-the-art situation of the current applications of foams, including thermal and acoustic issues and focusing on their new functions, usages and future trends.
",isbn:"978-1-83969-585-8",printIsbn:"978-1-83969-584-1",pdfIsbn:"978-1-83969-586-5",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,hash:"9495e848f41431e0ffb3be12b4d80544",bookSignature:"Dr. Marco Caniato",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/10699.jpg",keywords:"Foaming, Vacuum, Molten Metal, Formability, Lightweight, Insulation, Vibration Reduction, Absorption, Resistance, Shock, Environmental Protection, Recycling",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"February 24th 2021",dateEndSecondStepPublish:"March 24th 2021",dateEndThirdStepPublish:"May 23rd 2021",dateEndFourthStepPublish:"August 11th 2021",dateEndFifthStepPublish:"October 10th 2021",remainingDaysToSecondStep:"a month",secondStepPassed:!1,currentStepOfPublishingProcess:2,editedByType:null,kuFlag:!1,biosketch:'Dr. Marco Caniato is an internationally-oriented scientist with 10 years of experience in the Italian Universities of Trieste and of Ferrara. He is the inventor of 6 registered patents among which are "Acoustic panel for noise barriers and noise barrier provided with such a panel" and “Multilayer panel for building use".',coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"312499",title:"Dr.",name:"Marco",middleName:null,surname:"Caniato",slug:"marco-caniato",fullName:"Marco Caniato",profilePictureURL:"https://mts.intechopen.com/storage/users/312499/images/system/312499.jpg",biography:"Dr. Marco Caniato is an internationally-oriented scientist with 10 years of experience in well-known Italian universities. His research is focused on the effects of materials thermal and acoustic insulation and behavior. Specifically, his interests are addressed to their influence on human beings' comfort. Dr. Caniato published more than 80 papers, including conference proceedings, journal papers, and book chapters. 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Later in 1926 [2], the structure was identified. Genstin (1) was isolated from Soybeans in 1941 [3]. Although the main source of isoflavonoids is member of the Fabaceae [4], some were reported from other families such as Amaranthaceae [5, 6], Rosacease [7] and Poaceae [8]. Isoflavonoids were also reported from fungi [9] and Propolis [10]. The dietary consumption of isoflavonoid-rich sources is linked with health advantages toward osteoporosis, post-menopausal symptoms, cardiovascular diseases and chemo-prevention [11]. People from SE Asia have much lower risk of developing prostate cancer compared to Americans due to high consumption of soy rich in isoflavonoids. Upon immigration to the USA and changing the dietary components, this difference rapidly disappears [12]. Isoflavonoids are also classified as dietary antioxidants [13]. These facts were the driving force behind the use of isoflavonoid-rich sources as nutraceutical and dietary supplements [14].
Isoflavonoids are a large subclass of the most common plant polyphenols containing 15 carbon atoms known as flavonoids [15]. In isoflavonoids (3-phenylchromans), the phenyl ring B is attached to heterocyclic ring C at position 3 rather than 2 in flavonoids [16]. Generally, flavonoids are biosynthesised via Shikimic acid pathway. Shikimic acid is also a precursor for the biosynthesis of phenylpropanoids and aromatic acids. At certain stages, the activity of the key enzyme chalcone isomerase (CHI) resulted in the formation of flavanones that converted to isoflavonoids under the influence of isoflavone synthase [17]. The biosynthesis of isoflavonoids, consequently, is considered as an offshoot from the flavonoids biosynthetic pathway [18]. Highest level of isoflavonoids occurs usually in roots, seedlings and seeds [18, 19].
Isoflavonoids are sub-classified into many subclasses based on the oxidation status of ring C as well as the formation of a forth ring ‘D’ by coupling between rings B and C. Subclasses free from ring D include isoflavones, isoflavanones, isoflavan-4-ol, homoisoflavonoids, isoflavans and isoflav-3-ene. Rotenoids, pterocarpans, coumaronochromones and coumaronochromene represent the subclasses with additional ring D formation [11].
This chapter will deal with the different aspects of the isoflavonoid subclasses keeping the original three-ring skeleton (Figure 1). Occurrence, isolation, key spectroscopic characters and biological activities will be covered starting from 2000 to date.
The skeletons of the isoflavonoids with three-ring structures.
The most popular method used for extraction of isoflavonoids is maceration with either MeOH or EtOH containing various percentages of H2O at room temperature followed by liquid-liquid fractionation using solvents with different polarities [6, 10, 19–32]. Another method of extraction used MeOH or EtOH under reflux or in soxhlet apparatus [5, 33–36]. Mixture of MeOH and CHCl3 or CH2Cl2 (1:1) was also applied for extraction [37–41]. Other research groups extracted the plant materials with acetone [42–44], CHCl3 [45, 46], CH2Cl2 [47–50] or diethyl ether [51] at room temperature. Successive extraction starting with petroleum ether or hexane, CHCl3, EtOAc and MeOH using soxhelt apparatus [52–56] was also reported. The isoflavone contents of soybeans were extract using supercritical fluid extraction [57].
The majority of purification and isolation steps utilized silica gel in the form of column, Preparative Thin Layer Chromatography (PTLC) or Centrifugal Preparative Thin Layer Chromatography (CPTLC) [19, 21, 45]. Combination of silica gel and Sephadex LH-20 was also applied for isoflavonoid purification [6, 10, 54, 55]. In addition to silica gel, semi-preparative C18 High Performance Liquid Chromatography (HPLC) columns were used for final purification of isoflavonoids [23, 30, 31, 38, 48]. The polar n-butanol fraction of Ononis serrata was fractionated on C18 silica gel applying the Vacuum Liquid Chromatography (VLC) technique followed by normal silica gel column for purification of isoflavonoid glucosides [27]. Two isoflavenes were isolated from Lespedeza homoloba after chromatography on porous polymer gel Diaion followed by silica gel column. Final purification step was performed on preparative C18 HPLC column [36]. Isoflavonoids from Iris germanica were purified by silica gel VLC and CC, and final purification was achieved via LiChrolut EN/RP-18 solid phase extraction tubes [26]. High-speed counter-current chromatography (HSCCC) was applied for the purification of flavan glycoside and isoflavones from Astragalus membranaceus, the seeds of Millettia pachycarpa and soy flour [20, 58, 59]. Isolation and identification of isoflavanones, biflavanones and bisdihydrocoumarins were achieved using Liquid Chromatography- Mass Spectrometry (LC-MS), Liquid Chromatography- Solid Phase Extraction- Nuclear Magnetic Resonance (LC-SPE-NMR) and Electronic Circular Dichroism (ECD). In this method, MS of target compounds was measured directly in the LC effluent. For NMR analyses, the peaks were collected from 20 LC runs, loaded on SPE cartilages, dried with nitrogen gas and finally eluted with CD3OD [32].
Both phenolic hydroxyls and carbonyl groups are present in most of the isoflavonoid classes. However, the most characteristic feature of isoflavans and isoflavenes is the lack of carbonyl function bands. The absorption bands for the C-4 carbonyl in isoflavones and isoflavanones present in the range 1606–1694 cm−1 [9, 23–26]. Differentiation between isoflavones and isoflavanones from the position of C-4 carbonyl bands in the IR spectra is not achievable.
In spite of the tremendous advances in 2D-NMR and MS, the UV absorption spectra in MeOH and MeOH with shift reagent still can provide useful information for flavonoids identification. In all isoflavonoids except isoflavenes, ring B has no or little conjugation with the main chromophore composed of rings A and C. This fact is expressed as intense band II and diminished band I [60].
For isoflavones, band II shows absorption at λmax 245–275 nm. Shift reagents can be used to detect hydroxylation at ring A. NaOAc induces 6–20 nm bathochromic shift as an indication of free 7-hydroxyl group. The 10–14 nm shift with AlCl3/HCl is diagnostic for free 5-OH group. The absence of any shift with NaOMe is an evidence for the absence of free hydroxyls in ring A [19, 27, 28, 50, 60].
The UV spectra of about 28 published isoflavanone were reviewed. Band II absorption was found in the range 270–295 nm [5, 9, 23, 25, 29, 33, 39, 41, 43, 44, 47–50, 55, 61, 62]. Among these publications, only three used shift reagents with five isolated isoflavanones. Analysis of the obtained results revealed that AlCl3 induced 17–23 nm bathochromic shift in band II due to the complex formed between C-4 carbonyl and C-OH groups. All the entitled compounds contain C-7 free hydroxyl groups, and NaOAc produced 34–37 nm bathochromic shift in band II [39, 47, 50]. However, more data are required to draw a solid conclusion.
The few available UV data of homoisoflavonoids showed band II absorption in the same range reported for isoflavanones [63].
Isoflavans UV spectra show one prominent maxima representing band II between 270 and 295 nm [21, 37, 38, 45]. The available UV data of isoflavenes indicated the presence of two bands at 235–245 and 320–337 nm along with a shoulder 287–300 nm [29, 30, 31, 35, 36].
Saturation of the double bond between C-2 and C-3 creates a new asymmetric center in the molecules. The orientation at these centers is in most cases determined from the CD spectra.
Isoflavanones show three absorption maxima at 200–240, 260–300 and 320–352 nm. Determination of the absolute configuration at C-3 is based on the n→π* carbonyl transition between 320 and 352 nm. The positive sign at this region is diagnostic for (3R) orientation with ring B having equatorial position. The coupling constant between the trans-diaxial H2β and H3 can confirm the equatorial orientation of ring B [64]. Optical inactivity of isoflavanones most probably is a result of racemization that can occur during extraction and purification [64]. The isolation of two racemic mixtures, 3S- and 3R-7-O-glucosyldiphysolones (2, 3) and (3S)- and (3R)-7,4′-di-O-glucosyldiphysolones (4, 5), from Ormocarpum kirkii was explained as result of isomerization in aqueous solution [32]. The same observation was reported in three isolated isoflavanones from Platycelphium voënse and Desmodium canum [41, 47]. Due to the positive cotton effect at 337 nm, the (3R) orientation was assigned to eryzerin B (6). However, eryzerin A (7) was reported in the same publication with undetermined absolute stereochemistry [44]. The (3R) orientation was also assigned to 2,3-dihydro-7-demethylrobustigenin (8) and saclenone (9) isolated from Erythrina sacleuxii based on the positive cotton effect at 320 and 334 nm, respectively [49].
Isoflavans configuration is much more complicated. The heterocyclic ring C is expected to have the half-chair form a fact that can be diagnosed from the vicinal coupling constants between H-2, H-3 and H-4 protons. Such J values along with the CD curves can then lead to determination of the absolute configuration [64]. (3S)-isoflavans with oxygenation at both the A and B rings display positive and negative cotton effects at 240 and 270–280 nm regions, respectively. The opposite was observed for the (3R)-enantiomers. The 7-deoxy (3S)-isoflavans with mono- and di-oxygenation at ring B displayed negative cotton effects in both the 230–240 and 270–290 nm regions, and the opposite was observed for the (3R)-enantiomers [64]. The difficulty in assigning the absolute configuration of isofalvans was reflected by Bedane et al. [37]. The authors isolated two new isoflavans, erylivingstone J (10) and erylivingstone K (11). The measured CD spectrum showed negative cotton effect near 306 nm and a positive cotton effect near 240 nm supporting (S)-configuration. Three known compounds, 2′-methoxyphaseollinisoflavan (12), 7,4′-dihydroxy-2′,5-dimethoxy isoflavan (13) and 7,4′-dihydroxy-2′-methoxy-3′-(3-methylbut-2-enyl) isoflavan (14), with (R)-absolute configuration were isolated from the same source in this study. Suspicions about the purity of the new compounds and isolation of compounds with (R)-absolute configuration led the authors to report the new compounds without absolute configuration [37]. The enantiomer (3S) (+) 2′-O-methylphaseollidinisoflavan (15) was isolated from Erythrina caffra along with the (3R) (−) erythbidin A (16). The configuration was assigned based on 1H-NMR J values, optical rotation and CD spectra. However, the reported CD data did not cover the lower range of the spectrum near 240 nm [45]. The absolute configuration of abruquinone L (17) was successfully assigned by combination of 1H-NMR analyses of the J values between ring C protons and the CD spectrum which showed a strong positive cotton effect at 202 nm and two negative cotton effects at 212 and 233 nm [38]. Due to the positive cotton effect at 337 nm, the (3R) orientation was assigned to eryzerin C (18). However, eryzerin D (19) was reported with undetermined absolute stereochemistry [44].
In case of isoflavan-4-ol, C-4 becomes a new chiral center and 4 isomers could exist. Out of the possible isomers, two are cis- and two are trans-. Hata et al. synthesized and compared the CD spectra of four stereoisomers. The 3R, 4S-trans-isoflavan-4-ol stereoisomer showed negative cotton effect between 250 and 300 nm and positive cotton effect between 220 and 240 nm. The other 3S, 4R-trans-isoflavan-4-ol stereoisomer showed CD spectrum having cotton effect at the same ranges but with opposite sign. The 3S, 4S cis-isoflavan-4-ol stereoisomer expressed positive cotton effect between 245 and 300 nm, while the other enantiomer 3R, 4R-isoflavan-4-ol has a negative cotton effect at the same region [65].
1H- and 13C-NMR spectra provide key information for the identification of the isoflavonoids skeleton. The proton and carbon signals for positions 2–4 in ring C (Table 1) provide a unique feature for each class.
Position 2 | Position 3 | Position 4 | ||||
---|---|---|---|---|---|---|
1H | 13C | 1H | 13C | 1H | 13C | |
Isoflavones | 7.82–8.45 s | 150.9–155.0 | – | 121.5–125.5 | – | 173.9–181.5 |
Isoflavanones | 4.46–4.76 (dd, ax) 4.34–4.63 (dd, eq) | 69.6–72.3 | 3.93–4.32 (dd) | 45.3–51.1 | – | 193.0–198.8 |
Homoisoflavonoids | 4.06–4.32 (dd) | 68.8–69.3 | 2.65–2.80 (m) | 46.8–48.7 | – | 192.7–198.3 |
Isoflavans | 4.33–3.83 (t, ddd, tdd, dt, dd) | 69.2–71.2 | 3.36–3.55 (tdd, dd, dddd, m) | 30.79–33.6 | 2.64–2.98 (dd, ddd) | 26.1–31.9 |
Isoflavan-4-ol | 4.21–3.60 (dd, t) | 66.8–66.9 | 3.52–3.49 (ddd) | 40.5–40.6 | 5.47–5.49 (d) | 79.0–79.6 |
Isoflavenes | 4.83–5.25 (s, d) | 67.6–68.8 | – | 127.5–129.6 | 6.47–6.74 (s, d) | 118.3–121.9 |
Key 1H- and 13C-NMR spectral data for identification of isoflavonoid classes.
The simplest ring C spectrum is that of isoflavones as it shows only one downfield proton singlet for H-2. The oxygenated C-2 chemical shift is also characteristic for isoflavones. The wide range for C-4 carbonyl resulted from the effect of C-5 substitutions. The lack of C5 free hydroxyl resulted in the upfield shift of the C-4 carbonyl chemical shift to a value less than 175.0 ppm in most cases [27, 34]. With the presence of C-5 free hydroxyl and formation of hydrogen bond C-4 carbonyl, the carbonyl chemical shift value is usually above 180.0 ppm [19, 24, 28].
Saturation of the double bond between C-2 and C-3 of isoflavones leads to the formation of the isoflavanone skeleton. Such array contains a CH2-O and CH-aryl and renders the 1H-NMR signals of ring C more complex making an AMX spin system. The three protons appear as dd with different J values due to ax-ax, ax-eq and/or eq-eq splitting. In some cases, some signals may appear as t or interfere with other signals in the molecule [23, 41, 55, 61, 62]. Absolute configuration of isoflavanones was determined by a simple 1H-NMR experiment in the presence of (R)- and (S)-binol as chiral solvating agent. The presence of (R)- or (S)-binol produces variable changes in the chemical shifts of the most downfield H-2 proton. Comparing these chemical shift changes enables the assignment of the absolute configuration [66].
No significant difference can be observed when the chemical shifts of positions 2–4 are compared in the 1H-and 13C-NMR spectra of isoflavanones and homoisoflavonoids. The splitting pattern of H-3 is expected to be much more complex. However, the additional C-9 in homoisoflavonoids provides the key evidence for their identification. The H-9 protons appear in the range of δH 2.62–3.13 (dd) as a result of coupling with H-3 proton. The C-9 methylene appears at δC 31.9–32.2 ppm [63, 67].
Isoflavans lacks the C-4 carbonyl present in isoflavanones with expected two more proton signals from ring C to form an ABMXZ spin system. Although the H-4 proton signals are more upfield compared to H-2 and H-3, the splitting pattern is more complex than the corresponding isoflavanones. This pattern along with the 13C-NMR chemical shifts of C-2, C-3 and C-4 is the diagnostic feature for the isoflavan nucleus [20–22]. Isoflavan-4-ol is characterized by two oxygenated methines in both 1H- and 13C-NMR spectra.
Formation of double bond between C-3 and C-4 in isoflavans led to the emerging of the isoflav-3-ene class. The ring C 1H-NMR signals of isoflavenes is simplified to two singlet for the 2H of C-2 and 1H of C-4. In some reports, a long-range coupling with small J value (1–2 Hz) was observed between H-2 and H-4 protons [35, 36, 43, 56].
1H-NMR and different 13C-NMR experiments like Distortionless Enhancement by Polarization Transfer (DEPT 45, DEPT 90 and DEPT 135) in most cases enable the identification of the main skeleton of the isoflavonoids as well as the substitution pattern. Heteronuclear Single-Quantum Correlation (HSQC) experiment is applied to correlate protons and carbons through one bond. So, assignment of protons and carbons as CH3, CH2 and CH can be confirmed undoubtfully. 1H-1H-Correlation Spectroscopy (COSY) or similar experiments are applied to identify the spin systems in the compounds. These experiments identified protons separated by 3 bonds as well as different arrays present in the aromatic systems. The obtained COSY data allow the identification of the adjacent groups in the compounds and substitution pattern in the aromatic systems. Heteronuclear Multiple-Bond Correlation (HMBC) experiment acquired at different J values can identify correlation between protons and carbons through 2, 3 or sometimes 4 bonds especially in the aromatic systems. HMBC data play a key role in the determination of substituents location on the main skeleton. For example, the location of the furan ring in 4′-O-methylerythrinin C (20) at C-6 was assigned from HMBC correlations [28]. The location of the prenyl group at C-8 in erysubin F (21) was also assigned from correlations obtained from HMBC experiment [42].
Nuclear Overhauser Effect (NOE) is an effect observed between protons close to each other in space regardless to the number of bonds separating them [68]. The NOE effect can be clarified via One dimensional Nuclear Overhauser effect (1D-NOESY), Gradient-Enhanced Nuclear Overhauser Effect (GOESY) experiments or the now more favorable 2D-NOESY or Rotating Frame Nuclear Overhauser Effect (ROESY) experiments. The NOE effect is sometimes crucial for correct assignments of substitutions especially in the absence of significant UV data with shift reagents that can give information about OH group positions. The NOE effect in some situations is more decisive than HMBC due to the few number of correlations that can be observed and the fact that correlations are dependent on distance in space rather than direct bond correlations.
The positions of ring B substituents in lysisteisoflavanone (22) were assigned utilizing GOESY experiment where irradiation of the OCH3 and H-1″ of the prenyl group resulted in enhancement in their neighboring protons [50]. The NOE enhancement experiment was utilized to determine the position of OCH3 in olibergin B (23) [24]. Position of OCH3 in platyisoflavanone B (24) [41], vestitol (25), lotisoflavan (26) [21], erypoegin D (27) [43] and eryzerin B (6) [44] was assigned based on NOESY experiment results. The NOESY experiment was also employed to determine the position of glucose in ormosinoside A (28) [25].
NOESY data were also utilized to analyse the relative stereochemistry of the isoflavanol pumilanol (29) ring C protons [46].
Mass spectroscopy with different techniques and the great advances in instrumentation can provide accurately the molecular weight and the exact molecular formula. In addition, some common routes of fragmentation can provide additional evidences about the substitution pattern on both rings A and B. The mass fragments derived from a retro-Diels Alder (RDA) type cleavage give an idea about the substituent’s on ring A and ring B as well (Figure 2). These MS fragments were used for the confirmation of ring A and ring B substitution pattern in the structure elucidation. Observation of MS ion fragments at m/z 177 and 153 as a result of RDA type cleavage followed by a hydrogen transfer indicated the location of two methoxyls and a hydroxyl group on the B ring of the isoflavone olibergin A (30) [24]. The placement of two hydroxyl group at ring A and methylenedioxy and one methoxyl at ring B in the structure of (±)5,7-dihydroxy-2′-methoxy-3′,4′-methylenedioxyisoflavanone (31) was confirmed by MS fragments [33]. (S)-Platyisoflavanone A (32) mass spectrum showed fragment at m/z 232 indicating two methoxyls and 3-methylbut-2-enyl group at ring B [41]. The base peak in the MS spectrum of uncinanone D (33) at m/z 194 [C11H14O3] resulted from retro-Diels Alder (RDA) cleavage of ring C supported the presence of 3 methoxyl groups at ring B [48]. Similarly, the location of three methoxyl groups on ring B and two hydroxyl groups on ring A in the structure of the isoflavanone (±)5,7-Dihydroxy-2′,3′,4′-trimethoxy-isoflavanone (34) was supported by MS fragmentation [33]. The fragmentation of 5,7-Dihydroxy-2′,4′,5′-trimethoxyisoflavanone (35) generated mass fragments at m/z 153 corresponding with ring A with two hydroxyls and at m/z 194 for ring B with three methoxyls [39]. The location of the methyl group in desmodianone A (36), desmodianone B (37), desmodianone D (38), desmodianone E (39) and 6-methyltetrapterol A (40) at C-6 was confirmed from the MS fragment at m/z 167 for A-ring [47]. The MS fragments at m/z 346 [508−163+H]+ and 194 indicated the presence of a sugar moiety in the A ring and three methoxyl groups in the B ring in the structure of 5,7-dihydroxy-2′,3′,4′-trimethoxy-isoflavanone 7-O-β-glucopyranoside (41) [33]. With a fragment 30 mass units less at m/z 164 in the spectrum of 5,7-Dihydroxy-2′,4′-dimethoxy-isoflavanone 7-O-β-glucopyranoside (42), only two methoxyls were assigned to ring B and sugar was placed on ring A [33].
Main fragments of retro-diels–alder (RDA) type cleavage.
In addition to providing the M+ at 328 m/z of 2-methoxyjudaicin (43) the fragment at m/z 297 due to loss of the two methoxyls was very supportive for the structure since the MS spectrum of judaicin (44) show only fragment due to loss of one methoxyl group at C-2’. The MS data of judaicin 7-O-glucoside (45) and judaicin 7-O-(6″-O-malonylglucoside) (46) showed common ion at m/z 298 corresponding to the aglycone part after the loss of the glycosyl moieties at C-7 [30, 31].
The isolated isoflavonoids from natural sources are presented in Tables 2–6, and their structures are provided in Figures 3–7. Isoflavones, isoflavanones and isoflavans from 2000 to date are arranged according to publication date in Tables 2–4, respectively. Due to the limited number of isoflavenes, the current survey includes all isolated members available in the literature (Table 5). Synthetic compounds are not included in this chapter.
Name | Source | Ref. |
---|---|---|
2,3-Dehydrokievitone (47) | Erythrina sacleuxii | [49] |
5′-Prenylpratensein (48) | Erythrina latissima | [39] |
Erysubin F (21) | Erythrina suberosa | [42] |
6″-O-Malonylgenistin (49) | Glycine max | [59] |
Irisolone (50) | Polygala stenopetala | [69] |
Isoerysenegalensein E (51), Alpinumisoflavone (52), Wighteone (53) | Erythrina lysistemon | [50] |
2″,6″-O-Diacetyloninin (54) | Glycine max | [70] |
Isoprunetin 7,4′-di-O-β-D-glucopyranoside (55) Genistein 7,4′-di-O-β-D-glucopyranoside (56) | Genista morisii | [54] |
Genistein (57) | Desmodium uncinatum | [62] |
Olibergin A (30), Olibergin B (23), Genistein (57), Formononetin (58) Biochanin A (59) | Dalbergia oliveri | [24] |
Rothindin(60) | Ononis serrata | [27] |
4′-O-Methylerythrinin C (20), 4′-O-Methylalpinumisoflavone (61) 4′-O-Methyl-2″-hydroxydihydroalpinumisoflavone (62) 7-O-Methylbiochanin A (63) | Lotus polyphyllos | [28] |
Genistin (1), Genistein (57), Daidzein (64), Daidzin (65) Glycitein (66), Glycitin (67) | Semen sojae praeparatum | [71] |
7-O-Geranylbiochanin A (68) | Tephrosia tinctoria | [72] |
Olibergin B (23), Biochanin A (59), 8-C-Geranyl-7-O-methylbiochanin A (69) | Dalbergia paniculata | [73] |
Biochanin A (59), 6-Hydroxy-7,4′-dimethoxyflavone (70) 6,7,4′-Trimethoxyflavone (71) | Gynerium sagittatum | [8] |
4′-O-Methylderrone (72) | Lotus polyphyllos | [19] |
4′,5′-Dimethoxy-6,6-dimethylpyranoisoflavone (73) | Millettia pachycarpa | [58] |
Erypoegin D (27), Alpinumisoflavone (52), Wighteone (53) 5,4′-Dihydroxy-7-methoxy-3′-(3-methylbuten-2-yl)isoflavone (74) 5,2′,4′-Trihydroxy-7-methoxy-5′-(3-methylbuten-2-yl)isoflavone (75) 5,4′-Dihydroxy-7-methoxy-3′-(3-methyl-2-hydroxybuten-3-yl)isoflavone (76) 3′-Formyl-5,4′-dihydroxy-7-methoxyisoflavone (77) 5-Hydroxy-3″-hydroxy-2″,2″dimethyldihydropyrano[5″,6″:3′,4′]isoflavone (78) 3′-Isoprenylgenistein (79), Isolupabigenin (80) | Erythrina poeppigiana | [74] |
Genistein (57), Formononetin (58), Biochanin A (59), Calycosin (81) Ononin (82), Sissotrin (83) | Cicer arietinum | [75] |
Tlatlancuayin (2′,5-dimethoxy-6,7-methylenedioxyisoflavone) (84) | Iresine herbstii | [5] |
2′-Hydroxygenistein (85), 3′-Omethylorobol (86) 7-O-Methyltectorigenin (87), Prunetin (88), Licoagroisoflavone (89) Cajanin (90), Lachnoisoflavone A (91) | Crotalaria lachnophora | [76] |
Pierreione A (92), Pierreione B (93), Pierreione C (94), Pierreione D(95) | Antheroporum pierrei | [77] |
Genistein 5-O-β-glucopyranoside (96), Prunetin 5-O-β-glucopyranoside (97) | Potentilla astracanica | [7] |
Erysubin F (21), Erythraddison I (98), Erythraddison II (99) Echrenone b10 (100) | Erythrina addisoniae | [23] |
Ormosinosides A (28), Genistein (57), Biochanin A (59), Daidzein (64) Daidzin (65), Sissotrin (83), 7-O-Methylbiochanin A (63) Isoformononetin (101), 4′,7-Di-O-methyldaidzein (102), Isoprunetin (103) Sophoricoside (104), Isoprunetin-7-O-β-D-glucoside (105) 6″-β-D-Xylose-genistin (106) | Ormosia henryi | [25] |
Genistein (57),Biochanin A (59), Daidzein (64) 3′-Hydroxydaidzein-7-O-glucopyranoside (107) Calycosin-7-O-glucopyranoside (108) | Trifolium scabrum | [78] |
5,6-Dihydroxy-7,8,3′,5′-tetramethoxyisoflavone (109) | Iris pseudacorus | [79] |
Formononetin (58), Ononin (82), Calycosin (81) Calycosin-7-O-glucopyranoside (108) | Astragalus mongholicus | [80] |
Formononetin (58) | Dalbergia oliveri | [53] |
Genistein (57), Biochanin A (59), Calycosin-7-O-glucopyranoside (108) | Dalbergia odorifera | [81] |
Neobavaisoflavone (110) | Erythrina excels, Erythrina senegalensis | [40] |
Biochanin A (59) | Dothideomycetes fungus CMU-99 | [9] |
Neoraudiol (111) | Neorautanenia mitis | [52] |
Genistin (1), Daidzein (64), Daidzin (65), Puerarin (112) | Pueraria lobata | [34] |
Formononetin (58), Ononin (82), 3-(4-(Glucopyranosyloxy)-5-hydroxy-2-methoxyphenyl)-7-hydroxy-4H-chromen-4-one (113) | Ononis angustissima | [82] |
7,2′,5′-Trimethoxy-3′,4′-methylenedioxyisoflavone (114) 6,7-Dimethoxy-3′,4′-methylenedioxyisoflavone (115) 5,4′-Dihydroxy-7,2′,5′-trimethoxyisoflavone (116) | Piscidia carthagenensis | [83] |
Isosideroxylin (117) | Leiophyllum buxifolium | [84] |
Achyranthoside A (118), Achyranthoside B (119) | Achyranthes bidentata | [6] |
Genistein (57), Biochanin A (59), Prunetin (88), Tectorigenin (120) | Dalbergia odorifera | [85] |
8-Hydroxyirilone 5-methyl ether (121), 8-Hydroxyirilone (122) Irilone 4′-methyl ether (123), Irilone (124), Irisolidone (125) Irigenin S (126), Irigenin (127), Iridin S (128), Iridin (129) 4′-O-β- | Iris germanica | [26] |
Isolated isoflavones from natural sources since 2000 to date.
Name | Source | Ref. |
---|---|---|
(R)-2,3-Dihydro-7-demethylrobustigenin (8), (R)-saclenone (9) | Erythrina sacleuxii | [49] |
5,7-Dihydroxy-2′,4′,5′-trimethoxyisoflavanone (35) | Erythrina latissima | [39] |
Bolusanthol B (131), Bolusanthol C (132) 5,7,3′-Trihydroxy-4′-methoxy-5′-γ,γ-dimethylallylisoflavanone (133) 5,7,2′-Trihydroxy-4′-methoxy-6,5′-di(γ,γ-dimethylallyl)isoflavanone (134) 5,7,2′,4′-Tetrahydroxy-8,3′-di(γ,γ-dimethylallyl)-isoflavanone (135) | Bolusanthus speciosus | [86] |
Lysisteisoflavanone (22) | Erythrina lysistemon | [50] |
Seputheisoflavone (136) | Ptycholobium contortum | [87] |
Dihydrodaidzin (137), Dihydrogenistin (138) | Glycine max | [70] |
Erypoegin C (139), Erypoegin D (140) | Erythrina poeppigiana | [43] |
Eryzerin B (6), Eryzerin A (7) | Erythrina zeyheri | [44] |
Erypoegin G (141) | Erythrina poeppigiana | [61] |
Cajanol (142) | Crotalaria lachnophora | [76] |
7,4′-Dihydroxy-2′-methoxy-6-geranylisoflavanone (143) 2′,4′-Dihydroxy-6″-methyl-6″-(4‴-methylpent-3-enyl) pyrano(3″,2″:6,7)-isoflavanone (144) | Lespedeza bicolor | [88] |
Desmodianone A (36), Desmodianone B (37), Desmodianone D (38) Desmodianone E(39), 6-Methyltetrapterol A (40) | Desmodium canum | [47] |
Uncinanone A (145), Uncinanone B (146), Uncinanone C (147) | Desmodium uncinatum | [62] |
(±)5,7-Dihydroxy-2′-methoxy-3′,4′-methylenedioxyisoflavanone (31) (±)5,7-Dihydroxy-2′,3′,4′-trimethoxy-isoflavanone (34) 5,7-Dihydroxy-2′,3′,4′-trimethoxy-isoflavanone 7-O-β-glucopyranoside (41) 5,7-Dihydroxy-2′-methoxy-3′,4′-methylenedioxyisoflavanone 7-O-β-glucopyranoside (148) 5,7-Dihydroxy-2′,4′-dimethoxy-isoflavanone 7-O-β-glucopyranoside (42) 5,7,4′-Trihydroxy-2′,3′-dimethoxy-isoflavanone 7-O-β-glucopyranoside (149) | Desmodium styracifolium | [33] |
Uncinanone D (33), Uncinanone E (150) | Desmodium uncinatum | [48] |
Ferreirin (151), Dihydrocajanin (152), Dalbergioidin (153) Dihydrobiochanin A (154) | Gynerium sagittatum | [8] |
5,7-Dihydroxy-2′-methoxy-3′,4′-methylenedioxyisoflavanone (31) Uncinanone A (37), Dalbergioidin (153) 4′,5-Dihydroxy-2′,3′-dimethoxy-7-(5-hydroxyoxychromen-7yl)-isoflavanone (155), Parvisoflavanone (156), Isoferreirin (157) | Uraria picta | [55] |
Dalhorridin (158), Dalhorridinin (159) | Dalbergia horrida | [89] |
5,3′-Dihydroxy-4′-methoxy-5′-(3-methyl-1,3-butadienyl)-2″,2″-dimethylpyrano[5, 6:6,7]isoflavanone (160) 5,3′-Dihydroxy-5′-(3-hydroxy-3-methyl-1-butenyl)-4′-methoxy-2″,2″-dimethylpyrano[5, 6:6,7]isoflavanone (161) | Erythrina costaricensis | [90] |
Sophoronol A (162), Sophoronol B (163), Sophoronol C (164) Sophoronol D (165), Sophoronol E (166), Sophoronol F (167) | Sophora mollis | [91] |
3-Hydroxy-kenusanone B (168), Sophoraisoflavanone A (169) Kenusanone H (170) | Echinosophora koreensis | [92] |
Desmodianone F (171), Desmodianone G (172) | Desmodium canum | [93] |
5,7,3′-Trihydroxy-4′-methoxy-6,5′-di(γ, γ-dimethylallyl)-isoflavanone (173) 5,3′-Dihydroxy-4′-methoxy-5′-γ,γ-dimethylallyl-2″,2″-dimethylpyrano[5, 6: 6,7]isoflavanone (174) 5,3′-Dihydroxy-2″,2″-dimethylpyrano[5, 6: 6,7]-2′″,2′″-dimethylpyrano[5, 6: 5,4]isoflavanone (175) | Erythrina costaricensis | [94] |
Glabraisoflavanone A (176), Glabraisoflavanone B (177) | Glycyrrhiza glabra | [95] |
Isodarparvinol B (178), Dalparvin (179), (3S)-Sativanone (180) | Dalbergia parviflora | [96] |
2′,2,5-Trimethoxy-6,7-methylenedioxyisoflavanone (181) | Iresine herbstii | [5] |
Erythraddison III (182), Erythraddison IV (183) | Erythrina addisoniae | [23] |
Dalbergioidin (153) | Lespedeza cyrtobotrya | [29] |
3(R)-2′-Methoxyl-5,7,4′-trihydroxy-6-(3-methylbut-2-enyl)-isoflavanone (184) 3′-Geranyl-3,5,7,2′,4′-pentahydroxyflavonol (185) | Campylotropis hirtella | [97] |
Triquetrumone E (186), Triquetrumone F (187) | Tadehagi triquetrum | [98] |
Hirtellanine H (188), Hirtellanine I (189), Hirtellanine J (190) | Campylotropis hirtella | [99] |
Ormosinol (191) | Ormosia henryi | [25] |
7-O-Glucosyldiphysolone (2, 3), (3R)-7,4′-Di-O-glucosyldiphysolone (4) (3S)-7,4′-Di-O-glucosyldiphysolone (5), 4″-hydroxydiphysolone (192) | Ormocarpum kirkii | [32] |
Platyisoflavanone B (24), Platyisoflavanone A) (32) Platyisoflavanone C (193), Platyisoflavanone D (113) Sophoraisoflavanone A (169), Glyasperin F (194) | Platycelphium voënse | [41] |
(+)-Violanone (195) | Dalbergia oliveri | [53] |
(3S)-2′,4′-Dimethoxy-3,7-dihydroxyisoflavanone (196) (3S)-2′,4′,5′-Trimethoxy-7-hydroxyisoflavanone (197) (3R)-4′-Methoxy-2′,3,7-trihydroxyisoflavanone (198) (3R)-Violanone (199), (3R)-3′-O-methylviolanone (200) (3R)-Sativanone (201) | Dalbergia odorifera | [100] |
Dalbergioidin (153) (3R) 5,7,3′,4′-Tetrahydroxy-2′-methoxyisoflavanone (202) (3R) 5′,8-Di-(γ,γ-dimethylallyl)-2′,5-dihydroxyl-4′,7-dimethoxyl-isoflavanone (203) 5,7-Dihydroxy-2′,4′-dimethoxyisoflavanone (204) | Uraria clarkei | [101] |
Uncinanone E (150) 5,7-dihydroxy-2′-methoxy-3′,4′-methylenedioxy isoavanone (155) (3R) 7,2′,4′-Trihydroxy-3′-methoxy-5-methoxycarbonylisoflavanone (205) (3R) 7,2′-Dihydroxy-3′,4′-dimethoxy-5-methoxycarbonylisoflavanone (206) | Cassia siamea | [102] |
Sigmoidin H (207) | Erythrina excels, Erythrina senegalensis | [40] |
6,3′-di(3-hydroxy-3-methylbutyl)-5,7,2′, 4′-tetrahydroxyisoflavanone (208) 3(R)-6,3′-di(3-hydroxy-3-methylbutyl)-2′-methoxyl-5,7,4′-trihydroxyisoflavanone (209) | Campylotropis hirtella | [103] |
Uncinanone D (33), Desmodianone E (144), Desmodianone F (171) Grabraisoflavanone A (176) (3R)-7-Hydroxy-4′-methoxy-5-methoxycarbonyl-isoflavanone (210) (3R)-8-Hydroxy-4′-methoxy-7-methoxycarbonyl-isoflavanone (211) (3R)-7,2′,4′-Trihydroxy-3′-methoxy-5-methoxycarbonyl-isoflavanone (205) | Desmodium oxyphyllum | [104] |
Glycitein (66), Dihydrodaidzein (133), Dihydrogenistein (134) Dothideoisoflavanone (212), (3S)-3,4′,7-trihydroxyisoflavanone (213) | Dothideomycetes fungus CMU-99 | [9] |
Neotenone (214) | Neorautanenia mitis | [52] |
Eryvarins Y (215), Eryvarins Z (216), Orientanol E (217) 2,3-Dihydroauriculatin (218) | Erythrina variegata | [105] |
Isolated isoflavonones from natural sources since 2000 to date.
Name | Source | Ref. |
---|---|---|
5,7-Dimethoxy-3-(4-hydroxybenzyl)-4-chromanone (219) 5,6-Dihydroxy-7-methoxy-3-(4-hydroxybenzyl)-4-chromanone (220) 7-O-Methyl-3,9-dihydropunctatin (221) 5,7-Dihydroxy-3-(4-hydroxybenzyl)-4-chromanone (222) | Drimiopsis burkei Drimiopsis maculata | [63] |
Isolated homoisoflavonoids from natural sources since 2000 to date.
Name | Source | Ref. |
---|---|---|
Bolusanthol A (223) | Bolusanthus speciosus | [86] |
Neocandenatone (224) | Dalbergia congestiflora | [22] |
(3R)-(−)-7,2′-Dihydroxy-3′,4′-dimethylisoflavan-7-O-β-D-glucopyranoside (225) | Astragalus membranaceus | [20] |
Eryzerin C (18), Eryzerin D (19) | Erythrina zeyheri | [44] |
6-Desmethyldesmodian A (226), Desmodian A (227) Desmodian B (228), 6-Desmethylesmodian B (229) Desmodian C (230), 3′-Hydroxydesmodian B (231) | Desmodium canum | [106] |
Pumilanol (29) | Tephrosia pumila | [46] |
Salisoflavan (232) | Salsola imbricata | [107] |
Desmodian A (227), Desmodian D (233) | Desmodium canum | [93] |
3S (+) 2′-O-Methylphaseollidinisoflavan (15) 3R(-)Erythbidin A (16) | Erythrina caffra | [45] |
Vestitol (25), Neovestitol (234) | Brazilian propolis | [10] |
(3S,4R)-4′-Hydroxy-6,3′-dimethoxyisoflavan-4-ol (235) | Taxus yunnanensis | [108] |
Cordifoliflavanes A (236), Cordifoliflavanes B (237) | Codonopsis cordifolioidea | [109] |
Vestitol (25), Lotisoflavan (26) | Lotus lalambensis | [21] |
Abruquinone A (238), Abruquinone D (239), Abruquinone J (240) Abruquinone K (241), Abruquinone L (17) | Abrus precatorius | [38] |
Erylivingstone J (10), Erylivingstone K (11) 2′-Methoxyphaseollinisoflavan (12) 7, 4′-Dihydroxy-2′,5′-dimethoxy isoflavan (13) 7,4′-Dihydroxy-2′-methoxy-3′-(3-methylbut-2-enyl) isoflavan (14) | Erythrina livingstoniana | [37] |
Kotstrigoisoflavanol (242) | Kotschya strigosa | [110] |
Isolated isoflavans from natural sources since 2000 to date.
Name | Source | Ref. |
---|---|---|
Neorauflavene (243) | Neorautanenia edulis | [51] |
Sepiol (244), 2′-O-Methylsepiol (245) | Gliricidia speium | [111] |
Dimethoxytrihydroxyisoflavene (246) | Baphia nitida | [56] |
Haginin A (247), Haginin B (248) | Lespedeza cyrtobotrya | [35] |
7,3′,4′-Triacetoxy-6′-methoxyisoflav-3-ene (249) 7, 2′-Diacetoxy-4′-methoxyisoflav-3-ene (250) | Millettia sp. | [112] |
2-Methoxyjudaicin (43) | Cicer bijugum | [30] |
Judaicin (44), Judaicin 7-O-glucoside (45) Judaicin 7-O-(6″-O-malonylglucoside) (46) | Cicer judaicum | [31] |
Haginin C (251), Haginin D (252) | Lespedeza cyrtobotrya | [113] |
Haginin D (253), Haginin E (Phenoxodiol) (254) | Lespedeza homoloba | [36] |
Erypoegin A (255), Erypoegin B (256) | Erythrina poeppigiana | [43] |
Glabrene (257) | Glycyrrhiza glabra | [114] |
Haginin A (247) | Lespedeza cyrtobotrya | [29] |
Haginin E (Phenoxodiol) (254) | Dothideomycetes fungus CMU-99 | [9] |
Isolated isoflavenes from natural sources.
Isolated isoflavones from natural sources since 2000 to date.
Isolated isoflavanones from natural sources since 2000 to date.
Isolated homoisoflavonoids from natural sources since 2000 to date.
Isolated isoflavans from natural sources since 2000 to date.
Isolated isoflavenes from natural sources since 2000 to date.
Isoflavonoids are reported to have a variety of bioprotective effects, including antioxidant, antimutagenic, anticarcinogenic and antiproliferative activities. Isoflavonoids may protect the body from hormone-related cancers, like breast, endometrial (uterine) and prostatic [115–119]. Isoflavonoids have gained a lot of public interest due to the possible correlation between their dietary consumption and health beneficial effects toward osteoporosis and post-menopausal symptoms [120, 121].
Among the isoflavonoids isolated from dothideomycetes fungus CMU-99, Biochanin A (59) showed weak cytotoxic activity against lung cancer cells (NCI-H137) and noncancerous Vero cells. Dothideoisoflavanone (212) exhibited cytotoxic effect against oral human carcinoma (KB) but was non-toxic against noncancerous Vero cells [9]. Among the isoflavonoids isolated from Erythrina addisoniae, Echrenone b10 (100) was found to be more than three times as potent as tamoxifen against MCF7/ADR and MDA-MB-231. Erythraddison III (182) was twice as potent as tamoxifen [23]. The isoflavanone Ormosinol (191) significantly inhibited adenocarcinomic human alveolar basal epithelial cells (A549) and human hepatic cell line (HepG2) [25]. Neobavaisoflavone (110) and Sigmoidin H (207) were selectively active in vitro against the resistant cancer cells 6/9, 4/9, CCRF-CEM, HCT116 (p53+/+), MDA-MB-231-BCRP and U87MG [40]. Platyisoflavanone A (32) showed cytotoxic effect against noncancerous Vero cells [41]. 2″,6″-O-diacetyloninin (54) was active against human stomach carcinoma (Hs 740.T, Hs 756 T), breast adenocarcinoma (Hs 578 T, Hs 742.T) and prostate carcinoma (DU 145, LNCaP-FGC) cell lines [70]. Pierreione A (79) and Pierreione B (93) demonstrated selective toxicity to solid tumor cell lines with minimal cytotoxicity [77]. Isosideroxylin (117) was selectively active against the against ER− MDA-MB-231 breast cancer cell line [84]. (3R) 5′,8-Di-(γ,γ-dimethylallyl)-2′,5-dihydroxyl-4′,7-dimethoxyl-isoflavanone (203) isolated from Uraria clarkei possessed good activity against the tested Hela, K562 and HL60 cell lines [101].
Haginin E (Phenoxodiol) (254) inhibits cell proliferation of a wide range of human cancer cell lines including leukemia, breast and prostate carcinomas, and is 5–20 times more potent than genistein [122]. Primary ovarian cancer cells resistant to conventional chemotherapy undergo apoptosis following Haginin E (Phenoxodiol) (254) treatment. Haginin E (Phenoxodiol) (254) is an efficient inducer of cell death in ovarian cancer cells and sensitizes the cancer cells to Fas-mediated apoptosis [123]. Haginin E (Phenoxodiol) (254) also exhibits significant ability to induce cell death in the prostate cancer cell lines LNCaP, DU145 and PC3 that utilize different signaling pathways than those reported in ovarian cancer studies [124]. Haginin E (Phenoxodiol) (254) development as an antitumor drug was based to a large extent on its low toxicity in normal tissues, but potent topoisomerase-II inhibitory effects in rapidly dividing tumor cells. This advantage led to its fast-track FDA approval for Phase II/III clinical trials [125].
Platyisoflavanone A (32) showed antibacterial activity against Mycobacterium tuberculosis (TB) in the microplate alamar blus assay (MABA) [41]. Isoflavonoids isolated from roots of Erythrina zeyheri were tested against methicillin-resistant Staphylococcus aureus (MRSA). Anti-MRSA potency of the isoflavan Eryzerin C (18) was the highest followed by Eryzerin D (19) [44]. 5,7,3′-Trihydroxy-4′-methoxy-6,5′-di(γ, γ-dimethylallyl)-isoflavanone (173) isolated from Erythrina costaricensis was also active on MRSA [94]. The two isoflavans 3S (+) 2′-O-Methylphaseollidinisoflavan (15) and 3R(-)Erythbidin A (16) isolated from E. caffra as well as the two isoflavanones 5,7-Dihydroxy-2′-methoxy-3′,4′-methylenedioxyisoflavanone (31) and 4′,5-Dihydroxy-2′,3′-dimethoxy-7-(5-hydroxyoxychromen-7yl)-isoflavanone (155) isolated from Uraria picta were active against S. aureus [45, 55]. The isoflavone Neoraudiol (111) displayed antimicrobial activity on Bacillus subtilis, Salmonella typhii and Candida albicans [52]. Lachnoisoflavone A (91) from Crotalaria lachnophora showed moderate inhibitory activities against Escherichia coli and Klebsiella pneumonia [76].
Isoflavanones from the Stem of Cassia siamea were evaluated for their anti-tobacco mosaic virus (Anti-TMV) activities [102]. (3R) 7,2′,4′-Trihydroxy-3′-methoxy-5-methoxycarbonylisoflavanone (205) was the most active among the tested compounds [102]. In addition to anti-TMV, cordifoliflavanes A (236) cordifoliflavanes B (237) expressed anti-HIV-1 activities [109].
As a part of plant phenolics, isoflavonoids are expected to have antioxidant activities. Ormosinol (191) showed significant antioxidant activity against DPPH radicals [25]. The isoflavene Haginin A (247) and the isoflavonones dalbergioidin (153) showed antioxidant properties in both 2,2′-Azino-bis(3-ethylbenzthiazoline-6-sulfonic acid) (ABTS) and 1,1-Diphenyl-2-picryl-hydrazyl (DPPH) assays [29]. Seputheisoflavone (132) from Ptycholobium contortum was active in the ABTS assay [87]. Isoflavones from the Astragalus mongholicus were examined for antioxidant potential in DPPH assay. Results indicated that Calycosin (81) and Calycosin-7-O-glucopyranoside (108) are more active than Formononetin (58) [80].
The in vitro antiprotozoal activity of isoflavan quinines from Abrus precatorius was tested against Plasmodium falciparum (K1 strain), Trypanosoma brucei rhodesiense (STIB 900 strain), Trypanosoma cruzi (Tulahuen strain C2C4 w/LacZ) and Leishmania donovani (strain MHOM/ET/67/L82). Abruquinone D (239) and abruquinone K (241) were the most active against T. brucei rhodesiense [38]. Pumilanol (29), an isoflavan from Tephrosia pumila, exhibited significant antiprotozoal activities against T. brucei rhodesiense, T. cruzi and L. donovani [46]. Sophoronol C (164) and Sophoronol E (166) exhibited moderate anitplasmodial activity against the CQS D10 strain of P. falciparum [91].
Daidzein (64) and Daidzin (65) possess a vasorelaxant action through opening of K+ channels and inhibition of Ca2+ influx in the vascular smooth muscle cells. This cerebral vasodilator activity may be beneficial to patients with obstructive cerebrovascular diseases [126].
Other studies reported on the effects of isoflavonoids on specific enzymes are presented in Table 7.
Compound name | Activity | Significance | Ref. |
---|---|---|---|
Tlatlancuayin (84) 2′,2,5-Trimethoxy-6,7-methylenedioxyisoflavanone (181) | a-glucosidase inhibitory | Weak | [5] |
Achyranthoside A (118) Achyranthoside B (119) | Lipopolysaccharide (LPS)-induced nitric oxide (NO) production | Significant inhibition | [6] |
Erysubin F (21), Erythraddison II (99) Echrenone b10 (100), Erythraddison III (182) Erythraddison IV (183) | Protein tyrosine phosphatase 1B (PTP1B) | Significant inhibition | [23] |
Sophoraisoflavanone A (169) Kenusanone H (170) | Alcohol dehydrogenase (ADH) Aldehyde dehydrogenase (ALDH) | Significant activation | [92] |
Glabrene (257) | Tyrosinase inhibition | Significant inhibition | [114] |
Effect of isoflavonoids on specific enzyme activities.
Public pressure led to the introduction of many different types of constraint at an increasing number of airports in an effort to keep both annoyance and complaints to a minimum. Noise pollution surrounding IKIA airport is a growing concern in Tehran.
\nThe computer simulation of the noise exposure level that we use at IKIA airport and its surrounding areas is conducted using the noise exposure forcasting modeling, The Noise Exposure Forecasting modeling, as used in the current study, computes noise exposure levels. The noise metric computed by the model is the annual average Day–Night Sound Level. The widely-used DNL metric is known to be highly correlated with community annoyance and is associated with a variety of land use guidelines that suggest where incompatibilities are expected to exist between the noise environment and various human activities [1].
\nNoise is an adverse factor in the living environments of today’s communities. This type of pollution has drawn attention to itself in the three recent decades, being a major problem in larger cities and seen as one of the significant environmental problems which is on the rise due to an array of factors including increased population density, motor vehicles, industrial activities in the proximity of urban areas and construction activities. Above-standard noise levels negatively affect all living beings and are therefore classified as environmental pollution. Research shows that both short- and long-term exposure to noise pollution weakens hearing, increases blood pressure leading to cardiovascular disorders, causes sleep and mood disorders, and changes behavior patterns [2]. Basner et al. studied the auditory and non-auditory influences of noise on cardiac diseases and neural disorders [3]. Therefore studying noise pollution and generating noise level maps for metropolises such as Tehran is of significant importance. Sound measuring in each certain area would take a considerable time and cost [4] because the level of noise emitted by vehicles in streets varies depending on traffic condition and such variation needs to be considered in measurements.
\nAnother way used to measure noise pollution in a certain area is employing noise pollution models, which indeed is a mathematical technique. Mostly traffic-based parameters, which are very diverse, are used as the model’s inputs. There are many factors that may affect sound emission in the space; hence, numerous models have been developed in this area so far. Most of them are physical factors which cover sound properties. As a result, measuring and examining such parameters is very difficult and complicated. However, other parameters including traffic-related ones such as velocity of vehicles and traffic flow are measured very easily [4].
\nMany studies have focused on noise pollution with different methods. Bilasco et al. proposed an information system model to identify areas exposed to noise pollution. Their model generated a noise map using sound measurements, building heights, land uses, digital land altitude model, and wind speed and direction in GIS software [5]. Subramani et al. analyzed noise pollution at different crossroads. They first performed a time analysis on sound data in different time periods at different crossroads, thus generating the noise map via GIS [6]. In another work, Mendal et al. assessed and analyzed noise pollution in Kolkata, India at the time of a festival [7]. Abbaspour et al. performed a hierarchical analysis of noise pollution in a region of Tehran [8]. Investigating the research performed on noise pollution analysis indicates that for noise pollution studies, GIS system is highly capable in generating noise maps and data analysis. The most important influential factors on the subject are traffic, width and type of roads, urban land use, green space, and slope. Traffic is important because increased traffic means increased vehicles, therefore increased noise. Road width also influences the capacity for holding vehicles. Road slope influences vehicle speeds, with higher speeds generating higher levels of noise. Land use influences generated noise by changing the population density and commenting levels.
\nThe paper studied Tehran, Iran. The study areas consisted of Tajrish Sq. (region 1) street of Tehran. The study areas were selected based on their traffic and urban importance. Measurements were performed during 7–8 am on August 5–8, 2018. The survey measured sound levels, road slope, road width, traffic, and land use (residential, commercial, administrative, and green space) that are presented in the following sections.
\nThe computer simulation of the noise exposure level that use at IKIA airport and its surrounding areas is conducted using the noise exposure forecasting modeling, The noise exposure forecasting modeling, as used in the current study, computes noise exposure levels. The noise metric computed by the model is the annual average Day–Night Sound Level. The widely-used DNL metric is known to be highly correlated with community annoyance and is associated with a variety of land use guidelines that suggest where incompatibilities are expected to exist between the noise environments and various human activities. Data input to the NEF includes runway coordinates, flight tracks, flight operations and types of aircraft. NEF computes the overall noise exposure at points on the ground around the airport. Data was modeled for a period of one year. The use of NEF in computer-based noise modeling not only gives the noise exposure levels based on the current flight operations, but also allows for the prediction of future noise levels due to a projected increase in flight operations. This is especially useful for a rapidly growing city like Tehran and IKIA airport.
\nThe data and assumptions used for leading such a study are presented and detailed below.
\nData summary:
Distance to city center: 40 km
Airport site area: 13,500 Ha
Airport reference point coordinates:
Latitude: 35°24′58″N;
Longitude: 051°09′08″E;
Elevation: 1007 m.
Specifications for all planned runways are summed up below:
Length of scheduled runways is 4200 m;
Width of runways is 60 m with 15 m shoulders;
Distance between parallel runways will be 400 m;
According to IKIA existing Airport Information Publication (AIP), the procedures for outbound aircraft are mainly concentrated on seven radials originating from IMAM KHOMAINI VOR/DME or destination to KAHRIZAK NDB. These exit radials were used to model the flight tracks followed by the various aircraft that will be accommodated at IKIA airport. Straight-in approaches were assumed on each runway.
\nThis paper uses the noise exposure forcasting because its availability. The NEF consists of a map of the noise contours plotted over the airport layout at each time period. Noise contours for NEF 30, 35, 40 and 45 noise levels are shown on the map.
\nIn this software, NEF+35 = DECIBEL and for discussion, should change the numbers of NEF to decibels. In the chart below, define the steps for modeling the noise of the airport .
\nContours of the noise around the airport. Invert the output of software to decibels: Black contour: 80 dB; Brown contour: 75 dB; red contour: 70 dB; and at last contour 65 dB.
It does this first by making the runways shown in Figure 1 and then with the data from the runway, start the software.
\nStandard suggestion of the environmental organization of Iran for noise is shown in Table 1. From the results of contour map and this table, divide four the regions and in Figure 1 the result is shown.
\nWith comparison the noise map from the noise exposure forecast modeling with the ICAO land use recommendations in Table 1, and knowing that in the airport, we also have noise pollution from numerous vehicles and factories that may develop in the near future, should have a master plan for decreasing the noise of the airport, should do it first at the origin of it and then by barriers with a suitable plan for building near IKIA. The next section suggests some recommendations that may be used for the airport.
\nRoad slope greatly influences commuting, traffic arrangement, speed, and driving patterns. Noise pollution varies between roads with different slopes. The mean slope of the study areas was 0–3%.
\nThe National Cartographic Center’s 1:2000 maps, field studies, and Google Maps™ were used to calculate land use (residential, commercial, administrative, and natural ground).
\nConsidering the direct influence of urban traffic on the noise level, the authors measured raw data for the number of vehicles, survey time, and other data at each point in order to calculate the traffic of survey points via extra processing. The correlation between traffic level and noise level made this data essential. A reasonable high-traffic hour at the peak mounting traffic (7–8 am) was selected to measure peak traffic. The vehicle data, converted to their equivalent according to saloon vehicles, were calculated using Eq. (1) [10].
\nwhere Va is traffic volume in a complete period, V is the calculated traffic during the measurement time in a period, Cf is the correction factor of the measurement.
\nCf is calculated via Eq. (2)\n
\nwhere \n
Due to high traffic and impossibility of direct measurements, road widths were estimated base on the number of lanes (every 3–3.65 m) and matching them with Google Earth maps and the mean value for multiple sections of each road.
\nThe sound data were collected using the device TES Sound Level Meter 1353H (calibrated by a qualified company) measurements were performed in the mornings at 15–20 m intervals. The longitude and latitude of each measurement point were recorded via a Garmin GPS device.
\nIf during measurements, a vehicle with very high noise levels (bus, heavy truck, etc.) passed nearby the measuring device at low speeds or stopped, the authors attempted to remove its effect from measurements as it would introduce abnormal variations in measurements leading to statistical errors.
\nData analysis was performed via ArcGIS 10.4.1. Raster polygon layers of sound data for the four studied areas are presented in Figure 2.
\nNoise level map of Tajrish.
The data model:
\nAfter testing the relationship between noise level variable and different combinations of independent variables, the best model was selected using Eq. (3).
\nwhere L\n\neq(m) is the noise level (dB), Trafficm\n is the vehicle traffic, and Residential denotes the percentage of residential land use.
\nAs shown, noise level is related to the traffic volume and residential land use independent variables. There is a positive linear relationship between noise level and vehicle volume, indicating that higher vehicle volumes resulted in increased noise. The relationship predicts that one vehicle per hour increase in vehicle traffic volume will increase noise level by 0.002 dB. There is a negative, linear relationship between noise level and percentage of residential land use, indicating that 1% increase in residential land use will increase noise level by 0.078 dB. Tables 2 and 3 show the data for observation times, goodness of fit indices (R2\n, \n
Night (10 pm–7 am) Unit in dB | \nDay (7 am–10 pm) Unit in dB | \nType of region | \n
---|---|---|
45 | \n55 | \nResidential region | \n
50 | \n60 | \nResidential-commercial region | \n
55 | \n65 | \nCommercial region | \n
60 | \n70 | \nResidential-industry region | \n
65 | \n75 | \nIndustry region | \n
Standard for noise values [9].
\n | Traffic | \nsound Level | \nSlope | \nResidential | \nCommercial | \nAdministrative | \nNatural Ground | \nRoad Width | \n
---|---|---|---|---|---|---|---|---|
Traffic | \n1 | \n\n | \n | \n | \n | \n | \n | \n |
Sound Level | \n0.6931 | \n1 | \n\n | \n | \n | \n | \n | \n |
Slope | \n−0.5235 | \n−0.4349 | \n1 | \n\n | \n | \n | \n | \n |
Residential | \n−0.6140 | \n−0.6486 | \n0.6459 | \n1 | \n\n | \n | \n | \n |
Commercial | \n0.1575 | \n−0.1258 | \n−0.1251 | \n0.0715 | \n1 | \n\n | \n | \n |
Administrative | \n−0.6536 | \n−0.3095 | \n0.0749 | \n0.0175 | \n0.0557 | \n1 | \n\n | \n |
Natural Ground | \n0.5788 | \n0.5876 | \n−0.2807 | \n−0.7782 | \n−0.5012 | \n−0.3898 | \n1 | \n\n |
Road Width | \n0.8285 | \n0.6242 | \n−0.5469 | \n−0.5731 | \n−0.0680 | \n−0.6015 | \n0.7075 | \n1 | \n
Variable correlations.
Model | \nR | \nR2\n | \nAdjusted R2\n | \nStd. error of the estimate | \nChange statistics | \nDurbin-Watson | \n||||
---|---|---|---|---|---|---|---|---|---|---|
R2 change | \nF change | \ndf1 | \ndf2 | \nSig. F Change | \n||||||
1 | \n0.800 | \n0.640 | \n0.638 | \n2.8233 | \n0.641 | \n497.107 | \n1 | \n280 | \n0.000 | \n\n |
2 | \n0.826 | \n0.682 | \n0.680 | \n2.6577 | \n0.042 | \n36.980 | \n1 | \n279 | \n0.000 | \n1.936 | \n
Model summary.
\nFigure 3 shows residuals according to their frequencies, representing a relatively normal distribution.
\nThe frequency of the regression model residuals.
The linearity analysis was performed using a graph separating dependent and independent variables. According to Figures 4 and 5, the maximum value of goodness of fit index for the traffic and noise level relationship was 0.64, followed by 0.489 for the percentage of residential land use. Road width ranked third however it could simultaneously be used in the regression model due to very high correlation with the traffic variable.
\nNoise level and vehicle volume relationship.
Noise level and road slope relationship.
The negative impact of aircraft noise, in particular around airports, is increasing. More and more people suffer not only from annoyance, but recent studies indicate that intermediate and high noise levels also contribute to physiological and psychological effects that in extreme cases can cause severe health problems. The aircraft industry has launched an ambitious plan for the next 15 years to reduce the noise emission levels from aircraft by as much as 20 dB. Even if this goal can be reached, reduced noise emission levels for new aircraft will have little or no influence on the total noise situation around airports in future. This is due to a slow renewal rate for aircraft combined with an increase in passenger volume.
\nIn order to stay competitive and to cope with an increasing number of neighborhood complaints and noise-impact related constraints, airport owners will have to look for novel solutions to reduce noise emission levels.
\nThe International Civil Aviation Organization (ICAO) has defined a four-point “balanced approach” that includes:
Reduction of noise at source;
For improving this method airports authorities should develop and buy new aircrafts that have less noise such as boeing 757 instead of boeing 727 and etc.
Land-use planning;
The results indicate the critical significance of urban traffic in noise pollution, as by a large difference it had the highest contribution to noise level, followed by green space, administrative, and commercial land use; road width, and road slope.
\nCommercial and business land uses generated the highest noise pollutions. With their high commuting levels and passenger traffic, malls and commercial centers produce high noise levels, especially at certain hours in the morning, resulting in higher noise and environmental pollutions compared to natural ground or residential areas. Sound levels above 70 dB irritate humans.
\nFor reduced noise pollution in Tehran and generally all urban areas, it is recommended to promote good driving behaviors and vehicle technical control for their sound level as well as implementing sound barriers for preventing the sound leaking into residential areas. Further, it is recommended that for future roads or revamping the existing ones, more lanes be implemented to produce wider roads, prevent the construction of tall buildings on the sided of main roads, and maintaining a standard distance between buildings and main roads, freeways, and other motorways.
\nThe negative impact of aircraft noise, in particular around airports, is increasing. More and more people suffer not only from annoyance, but recent studies indicate that intermediate and high noise levels also contribute to physiological and psychological effects that in extreme cases can cause severe health problems. The aircraft industry has launched an ambitious plan for the coming 15 years to reduce the noise emission levels from aircraft by as much as 20 dB [1].
\nOther strategies for reducing noise pollution in urban areas include designating suitable locations for land uses in comprehensive and development plans, use of standard, low-noise vetches, imposing limitations on the passage of automobiles and motorcycles, imposing speed limits, improving traffic behaviors and extending public transport. Sound barriers around motorways and the use of sound-absorbent materials in commercial and residential buildings or natural ground near residential areas or roads will greatly reduce noise pollution levels. In addition, proper city-wide planning requires establishing sufficient noise-pollution measurement stations and sound level maps for different urban regions and land uses.
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\n\nCorresponding authors will receive a 25% discount on their Open Access Publication Fees (OAPF) for Open Access book chapters. A 20% discount for publishing a long-form monographs, 25% for compacts and 23% for short-form monographs.
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