Spectral indices used.
\r\n\tDiagnostic tools are advancing: micro-and nano-diagnostics, advanced molecular genetics, and diagnosis of the aberrant clotting factor synthesis development and the options for the staging of the genetic abnormality - severe, moderate, and mild expression.
\r\n\tTreatment developments and advances start with prevention, intra-uterine approaches, genetic manipulation, genetic engineering, the high specificity of replacement factors, and recombinant technology.
\r\n\tIn addition to the above, the book will provide an update on the prevention of transmission of pathogens and potentially toxic substances used to stabilize and preserve treatment commodities. The role of big data and artificial intelligence through both machine learning and the application of deep learning and digital footprinting will also be addressed.
\r\n\tIn the developing world, there is an urgent need to collect, preserve and process plasma for the manufacturing of high yield, safe, and stabilized cryoprecipitate, or pharmaceutical fractionation of purified and specific clotting factors, as well as improvement on diagnostic and sociomedical approaches with an emphasis on patient and family care, and management of bleeding episodes.
The utilization of adjunctive, alternative or complementary treatment methods (CAM) has been growing in recent decades, driven by demand. Based on the report published by the National Institute of Mental Health (NIMH), there is a problem of burgeoning “off-label” medication prescription [1] and overrated effectiveness of pharmacological treatment for some conditions. Additionally, it has been found that best outcomes often depend on a combination of treatment strategies, including psychotherapy [2, 3, 4, 5, 6].
According to the definition proposed by the National Institute of Health (NIH), complementary medicine (CAM) constitutes a broad domain of healing resources that lie outside those intrinsic to the politically dominant health care system of a society [7]. Inevitably, CAM will include technologies that are in the preliminary stages of mainstream acceptance. Such a technology is neurofeedback, which typically utilizes specific frequencies of the EEG in feedback configuration in order to promote cerebral self-regulatory competence. Despite its origins in well-grounded animal research in the 1960s [8], and subsequent studies in application to epilepsy and attention deficit hyperactivity disorder (ADHD) in the 1970s and 1980s [9, 10], neurofeedback was not adopted into standard medical practice at the time.
Originally discovered in 1956 by Kamiya, what came to be called EEG biofeedback found its first clinical application to anxiety [11], but that finding was not welcomed by the mental health disciplines either. Nevertheless, neurofeedback has matured as a type of CAM over the last several decades, with some 2700 citations in PubMed for neurofeedback, EEG biofeedback, and neurotherapy. With refinements derived on the basis of “practice-based evidence,” neurofeedback is now belatedly entering the mainstream.
Neurofeedback belongs in the class of brain computer interface technologies, in that it allows the user to react to his own brain electrophysiological signals in real time [12]. These are registered from surface electrodes, subjected to frequency-selective signal processing, and rendered observable in the form of visual, auditory and tactile feedback. In its dominant realization, the feedback is based on frequencies within the conventional EEG spectrum of 0.5–40 Hz.
In infra-low frequency (ILF) neurofeedback, the modulation target is the brain rhythmic activity that lies below 0.5 Hz [13, 14]. Despite a multidecadal history of research, the organization and functional role of this low-frequency rhythmic activity remains unspecified, and this topic is currently garnering renewed research interest after a considerable hiatus.
The term ILF was introduced by a Soviet Union neurophysiologist Aladjalova in 1956 in her paper “Infra-slow rhythmic changes of the brain electrical potential” [15]. In this paper, she described brain oscillations in the ILF region and suggested a possible physiological basis for these phenomena. Since that time, a vast amount of empirical knowledge has been obtained in studies by Russian scientists in animal research and in studies on human subjects, through reliance on nonpolarizable electrodes to achieve low drift characteristics [16, 17]. The authors found two types of infra-slow oscillations with periods of 10s and 30–90s, respectively. In the United States, similar work was pursued by Kamiya et al. [18]. The ILF domain has also been studied in Austria and Germany [19, 20, 21, 22, 23, 24].
Spontaneous and evoked local field potentials were observed in various cortical and subcortical regions of patients in whom cortical and subcortical electrodes had been implanted for purposes of characterization, diagnosis, deep brain stimulation, or lesioning [25]. The cortical electrical potentials were found to be correlated with infra-slow metabolic oscillations such as fluctuations of local oxygen levels. It was also demonstrated that spectral characteristics of infra-slow oscillations of the human brain remained stable over days and weeks [25, 26]. Recently, ILF potentials have found increased interest in the international scientific community, especially with the growing scientific evidence for a significant role of infra-slow potential fluctuations in modulating the level of cortical excitability and thus regulating brain dynamical activity [27, 28, 29, 30, 31, 32].
Infra-low frequency training, developed by Susan and Siegfried Othmer, extended the conventional frequency-based training to the lower frequency range. Feedback is then a matter of observing the slowly undulating signal. The technique has been described in a paper titled Clinical Neurofeedback: Training Brain Behavior [33]. The first reported clinical application was to Post-Traumatic Stress Disorder among military veterans [34]. The second dealt with cases of epilepsy [13]. The method came to be applied broadly to mental health concerns, with a range of application that was even larger than that of EEG-based training. The method has demonstrated dramatically positive outcomes for a variety of mental conditions, including different forms of anxiety, depression, sleep disturbances, ADHD, the autism spectrum, developmental trauma, migraines and other headaches, and traumatic brain injury [35, 36].
A surprising observation with respect to ILF training is the rapidity with which results are sometimes achieved even with challenging clinical presentations. The tonic slow cortical potential appears to be an exquisite reflection of the dynamics of cortical excitability. When the signal is derived in bipolar montage, network relations are revealed, and thus the training impinges on functional connectivity. By operating in the ILF regime, the training preferentially accesses the functional connectivity of the intrinsic connectivity networks that were originally identified with fMRI [29]. These low frequencies also give preferential access to the glial role in the regulation of the glial-neuronal system [37].
In consequence, the ILF training impinges on the ultradian cyclic fluctuation of physiological arousal and related autonomic nervous system regulation [26, 38]. For example, in anxiety disorders, the disruption of autonomic stress regulation system results in a range of symptoms [39]. Indeed, the data of Smith and colleagues support the hypothesis that ILF training preferentially influences autonomic nervous system regulation and thus improves the emotional equilibrium of patients, which in turn positively influences attention and working memory [36]. Further evidence along those lines was recently documented in a large-scale compilation of pre-post continuous performance test data on a clinical population [40]. Improvement in performance was consistently observed, irrespective of the conditions being targeted in the training.
The previous studies showed that ILF patterns of both electrical and nonelectrical phenomena remained quite stable over time. The goal of the present study is to demonstrate that the ILF training procedure induces persistent changes in the amplitude distribution within the ILF spectral range.
Eight individuals (mean age 33.1; range 21–50) participated in our study: five males (mean age 36.2; range 23–50) and three females (mean age 28.0; range 21–35). All of them had normal mental and physical development, no history of head injury, convulsions or neurological diseases, and were not currently taking any medication or drugs. Despite the absence of any medical diagnosis, participants still reported physical or mental complaints. Some of them experienced fatigue, depressed mood, symptoms of anxiety or mood swings; others had headaches and sleep problems. Most subjects were not satisfied with their concentration and memory function, or with their high reactivity to stress factors. The investigation was carried out in accordance with the Declaration of Helsinki. All subjects gave informed consent after the procedures had been fully explained to them.
EEG was recorded using a Mitsar 21 channel EEG system (Mitsar, Ltd). Nineteen silver-chloride electrodes were applied according to the International 10–20 system. The input signals referenced to linked ears were filtered between 0 and 50 Hz and digitized at a rate of 250 Hz. The ground electrode was placed on the forehead. All electrode impedances were kept below 5kOhm. EEG was recorded during performance of the visual cued GO/NOGO task that uses pictures of 20 different animals, 20 different plants, and 20 different humans (together with a distracting beep tone) as stimuli [41].
One trial consisted of the sequential presentation of two pictures (prime and target), presented for 100 ms each, with an ISI of 1000 ms (SOA = 1100 ms). Trials were separated by 1500 ms. Patients were instructed to press the left button of the computer mouse as quickly as possible when an animal was followed by an animal (Go-condition) and not to respond when an animal was followed by a plant (NoGo-condition), or when a plant was followed by a plant or a human (distractor condition). The response interval lasted from 100 to 1000 ms.
The task consisted of 100 Go-trials, 100 NoGo trials, and 200 distractor trials. Trials were presented pseudo-randomly with equal probability. All trials were presented to the subject on a computer screen 1.5 m in front of them using the Psytask software (Mitsar Ltd.). The centrally presented stimuli subtended an approximate visual angle of 3°. Trials with omission and commission errors were excluded from analysis. Quantitative data were obtained using the WinEEG software.
The baseline investigation consisted of quantitative electroencephalogram (qEEG) in Visual Go/NoGo test, which took place 1–7 days before undertaking the course of NF training sessions. qEEG parameters were compared with the Human Brain Institute (HBI) normative Database. All the tests were repeated after 20 sessions in 1–7 days after the last session. The results of the second testing were compared with the pretreatment baseline.
The epochs with excessive amplitude of nonfiltered EEG and/or excessive high and slow frequency activity were automatically marked and excluded from further analysis. Eye blink artifacts were corrected by zeroing the activation curves corresponding to eye blinks. The method is similar to the one described in Vigario [42] and in Jung et al. [43].
Continuous artifact-free EEG epochs were selected manually for analysis. The duration of these epochs varied among the subjects from 550 to 1100 s.
The average spectral density in the 0–0.5 Hz frequency band was estimated for each electrode, each subject and each condition separately using the Thomson’s multitaper method, and logarithmically transformed for normalization before further statistical analysis.
The instrument used for the clinical neurofeedback was the Cygnet system (bee Medic), consisting of the NeuroAmp II and Cygnet software, integrated with Somatic Vision video feedback and run on a Windows 7 operating system using a standard personal computer (PC) with a high-resolution monitor.
The Othmer Method utilizes evidence-based and well-established neurofeedback protocols, the implementation of which has been refined through empirical optimization procedures and A-B testing over a large number of neurofeedback clients referred for a variety of conditions. The method is protocol-based and is further characterized by the following essential features:
It is a symptom-guided approach in which the symptom presentation from anamnesis is used to identify one of several basic patterns of dysregulation that are then targeted in a protocol-based manner;
The training is process-oriented, involving the ongoing optimization of feedback parameters according to observed symptom changes during sessions and from session to session;
The method utilizes bipolar EEG montages exclusively, and as such is oriented toward training the functional relationships between key cortical sites;
The method involves continuous waveform-following for the low-frequency aspect of the training in combination with conventional discrete reinforcements for inhibit-based training;
The inhibit-based training is triggered on transient anomalies observable within the conventional EEG spectrum;
The method utilizes mainly audio-visual real-time animations in order to deliver the ILF feedback signal beneath conscious awareness.
The two parameters selectable by the clinician are:
position of the electrodes, according to symptom profile and symptom changes;
adjustment of the reward frequency according to patient feedback.
Until 2006, the signal processing was very similar to the classical beta-SMR scheme [44]. However, the reward frequency setting of a 3 Hz wide variable bandpass-filter was user-adjustable over the entire conventional EEG spectrum from 1.5 to 40 Hz in center frequency. For that purpose, a horizontal slider was implemented in the graphical user interface. The inhibits were comprised 10 separate filter blocks in fixed frequency steps in the range between 1 and 40 Hz. For both the reward and inhibit scheme, threshold setting was auto-corrected to maintain a chosen level of difficulty, the “percent success.”
Specific design parameters in the signal-processing chain between initial EEG acquisition and ultimate feedback animation have always been assessed and optimized by means of an empirical approach based on qualitative evidence criteria. (A useful analogy to this process is the optimization of the suspension system of a car, where human factors come prominently into play.)
By expanding the underlying model of neurofeedback to incorporate the current understanding of the brain as a self-organizing dynamical system that interacts with itself by means of neurofeedback, improved approaches to signal processing and coupling to the feedback animations have been sought. This process got underway in 2001. In that regard, also slow cortical potentials were investigated. With the availability of greater computer power for additional signal processing as well as advanced signal acquisition technologies, it was found that the addition of such slow potentials appears to offer the brain a more direct and effective feedback interaction. It turned out that also with this scheme, tailoring of the parameter setting to the individual patient is beneficial or even necessary, just as was previously found for frequency-band training in the conventional EEG spectrum [45].
In contrast to the classical concept of a rewarding experience that is controlled by the amplitude of the EEG in a given frequency band, the goal here is to present the brain with the most relevant representation of its slow cortical potential. For that purpose, derivations from the measured signal control various features in the feedback animation in a way that optimizes the brain’s opportunity to engage with them.
For the purpose of continuity of the clinician’s experience with the earlier era, the terminology of “reward frequency” was retained, as the rules for settings and for the optimization procedure carried over into the ILF region. However, the absence of discrete rewards in the ILF training meant that the traditional terminology of reward had lost its meaning. The unfolding of the continuous ILF signal allowed for no external reinforcers. Additionally, the slider that controlled the target frequency within the EEG regime was retained in the new design, but its function in the ILF regime must be understood differently. With the adopted signal-processing scheme, the slider influences the natural frequency of the control loop that the brain forms with the feedback system during neurofeedback on a continuous signal. It functions effectively as a kind of gain control.
Training was performed with bipolar placement of silver/silver chloride scalp electrodes applied using Ten20 conductive electrode paste at one or both of two initial placements, T4-P4 and T4-T3 (according to the standard 10–20 system). These are relied upon to characterize the response of the trainee and to guide further optimization. Subsequently, T4-Fp2 and T3-Fp1 are added to the protocol as needed. The “ground” electrode was placed at Fpz.
Each trainee received 20 separate 30–45 min neurofeedback sessions over 7–8 weeks. For each subject, the target frequency in the infra-low frequency region was optimized with each of the standard placements. The placement of electrodes was the standard one developed by Othmer [46] and adopted in the Othmer Method.
Two-way repeated measures ANOVA with factors condition (before-after) and location (19 electrode positions) was used to estimate the statistical significance of the training effect on the slow EEG oscillations. The Greenhouse-Geisser procedure was used to compensate for deviations from sphericity or circularity.
After completion of 20 NFB sessions, all participants indicated improvement of their state. Most of them noticed a decrease of inner tension and reactivity to stressful factors. Further, they reported on stability of mood, improved body and space awareness, increase of energy level and of cognitive performance.
The post-training EEG patterns in all eight subjects revealed significant enhancement of spectral power in 0–0.5 Hz frequency band compared to the pre-training EEG. The locations of the most prominent changes were different: in some subjects, the dramatic ILF power increase was observed over the frontal-central region, in other cases over the posterior brain areas.
Figure 1 presents the EEG recordings before and after ILF NF course in one of the participants of our study.
Pre-training (on the left) and post-training (on the right) EEG in the 43-year-old male subject. EEG recorded in the linked ear montage/reference during VCPT performance. Scale: 200uV/cm, speed–1.875 mm/s, time constant–10.0 s (0.016 Hz), low frequency filter–0.5 Hz.
Figure 2 demonstrates the increase of the level of infra-slow activity in 0.03–0.05 Hz range in the post-training EEG in this participant. This increase is most prominent over frontal region.
EEG power spectra at Fz in the 43-year-old male subject before and after training. Pre-training–Lower curve, post-training–Upper curve, X-axis–Frequency and Y-axis–Spectral power in logarithmic scale.
Two-way ANOVA revealed a significant main effect of the factor “Condition” for the slow activity in 0–0.5 Hz frequency band F [1,7] = 18.4, p < 0.01. This effect is illustrated in Figure 3. An increase of the logarithmical power averaged in eight subjects in 0–0.5 Hz band is seen in all 19 electrodes localizations.
Influence of the ILF NF on the power of EEG activity in 0–0.5 Hz frequency band. X-axis
All participants had normal mental and physical development and had no history of any neurological abnormalities. However, most of them reported some form of self-perceived psychological and physiological issues such as fatigue, depressed mood, symptoms of inner tension, mood swings, headache, and sleep problems. These were accompanied by cognitive concerns such as diminished attention or poor working memory.
After 20 sessions of ILF training, the pattern of ILF activity at rest changed dramatically. The main difference was an increase in the amplitude of the ILF activity up to 0.3–1.0 mV in all recording sites.
These results indicate that ILF training modified the baseline brain state in each case. It is important to add here that the changes in brain dynamics were associated with improvement in subjective perception of stress, fatigue, mood disturbances, and sleep problems after completion of 20 sessions of ILF training. Decreases in inner tension and in stress reactivity were reported. The psychological evaluation also reflects positive changes, including improved stability of mood, better body and space awareness, increase in energy level, and improved concentration and cognitive performance (e.g., working memory).
The effect of ILF training on the subjective perception of positive psychological changes was previously reported by a number of researchers and practitioners that utilize ILF training in their practice [35, 47]. Our analysis has both supported previous observations and established a link between the observed improvement in participants’ condition with objective changes in physiological parameters that reflect the dynamics of the brain functional organization.
The previous studies have shown stability of the individual spectral characteristics of ILF brain potentials recorded both from scalp as well from intra-cortical and deep-brain electrodes [25, 26].
Consequently, the increase in the amplitude of the ILF activity found in the present study can be discussed in accordance with the mechanisms of the individual compensatory-adaptive brain-body regulation in response to stress factors [48]. In the present research, we assume that our participants had initial constraints in compensatory-adaptive brain reactions, which lead to the reduced brain tissue metabolic regulation followed by energy deficient state. The present study shows that ILF training outcomes are associated with an increase in amplitude of ILF. The increase in amplitude and regularity of ILF was previously described and discussed as a sign of improved tissue metabolic activity [48, 49, 50]. Therefore, the positive trend in ILF characteristics observed in our study may be linked to the increased compensatory mechanisms in the stress regulation systems.
It is important to mention that post-training enhancement of spectral power in the 0–0.5 Hz frequency band were the most prominent over the frontal-central and the posterior brain areas. The distribution of increased activity at infra low frequency is correlated with the principal hubs of the default mode network (DMN), located frontally and parietally on the midline. The DMN is by far the most dominant among our intrinsic connectivity networks (ICNs), typically accounting for more than 95% of the ambient activity of cortex. Among the ICNs, it bears the principal responsibility for the management of the tonic state of the brain. As such it can be thought of as setting the context for more specific functions such as cognitive and emotional control [51].
Previously published results discussed the possible involvement of ILF in the modulation of the internal organization of the DMN, which is associated with the brain homeostatic balance and is involved in the autonomic regulation [35, 36, 51]. These results support the hypothesis of the metabolic stress regulatory mechanisms [48] and raise the question on the role of DMN network in homeostatic balance and metabolic compensation in stress response.
At the same time, the disrupted connectivity within DMN was found in a number of diseases, especially related to faults in the stress-regulation system such as post-traumatic stress disorder [52], general anxiety disorder [53], major depressive disorder [54], and traumatic brain injuries [55].
Therefore, the positive effects of ILF feedback on the “renormalization of functional connectivity of resting-state networks” proposed by Othmer and colleagues can be linked with the normalization in the metabolic balance in the brain tissue as a specific effect of the ILF training [35].
The present research can be considered as the first step in uncovering the physiological basis of ILF training as the method that targets the balance within brain systems involved in metabolic regulation of brain and body. The role of ILF training on the DMN network regulation is a subject of future research, where the specific physiological effect of this practice in different brain diseases will be disclosed.
Our study has shown the changes in the amplitude distribution within the ILF spectral range in all participants that seems to be induced by the ILF training. In other words, the ILF training leads to the changes of the functional state of the brain. We suggest that the modification of the baseline ILF EEG pattern may reflect the normalization in the metabolic balance in the brain tissue and increasing efficiency of compensatory mechanisms in the stress regulation systems.
The authors thank Susan Othmer, Clinical Director of the EEG Institute, Woodland Hills, California, for development of neurofeedback protocols used in this study, and Siegfried Othmer, Chief Scientist of the EEG Institute for the critical review of the manuscript.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
VAG-Y recruited subjects, participated in experimental design, data acquisition, interpretation, and drafting of the manuscript. VAP performed statistical analysis and interpreted the data. BW developed the ILF NF technology. OK was involved in drafting of the manuscript. MG analyzed data. VAI participated in interpretation of data. JDK supervised the study and was involved in study design, interpretation of data and critical review of the manuscript.
The global structure and productivity of ecosystems are deeply impacted by joined climate conditions and human drivers, causing general vegetation degradation [1]. The phenomenon has kept increasing in the last four decades and eventually affects whole ecosystem, soil productivity, biological systems, biotic diversity, and other environmental systems’ ability to support human needs in concerned areas. Main indicators are the decline in parameters, such as low biomass, less ecological production, fragmentation, or lower canopy cover [2, 3].
Inside the tropics, vegetation is globally sensitive to seasonal and inter-annual variation in precipitations and temperatures. Extremes seasonally, i.e., longer rainy season and shorter dry season in lowest latitudes, versus the reverse phenomenon towards medium latitudes, influence the vegetation distribution with several phenological and physiological adaptations, including cover and status changes [4, 5, 6]. Typically, forest colonizes wetter areas, while savannas cover drier areas, with a gradual species distribution such as dense forest, tree savannas, grassy/herbaceous savannas, and isolated desert shrubs or clumps of dry grasses known as steppes. However, transitions are not rigidly determined by climate [7]. There is an extensive overlap between forest and savanna creating a mosaic of landscapes, and most studies on the subject remain widely hypothesized and modeled with controversial results, supported by questionable evidences. Biases include the high species turnover around 1000 mm to 2500 mm rainfall, the (un)stable states of forest and savanna maintained by feedbacks between tree cover and disturbances, and for the satellite-based approaches, the structural (in)difference between trees or grasses layer [8].
These specificities are challenging to spatialize at a point that sub-Saharan African ecosystems have played a key role in the development of remote sensing of vegetation for decades [9, 10, 11]. Nowadays, several satellite-based models provide scalable spectral information relevant to vegetation distribution and changes, physiology, and phenology, in broad terms, to monitor and combat land degradation, especially in African drylands [12, 13, 14, 15]. As such, numerous spectral indices measure the vegetation parameters [16]. The Normalized Difference Vegetation Index, NDVI, especially, has purposely been widely used [17]. However, some limitations like sensitivity to soil background effects and atmospheric influence as well as values saturation under dense and multilayered canopy, usually alter the NDVI capacity to simultaneously predict senesced vegetation and efficiently discriminate individual anomalies, i.e., growth, vigor, leaf area index, biochemical components (anthocyanin, carotenoids, cellulose, etc.), water content or pigmentation [18, 19, 20] with accuracy. Then some previous studies focused on identifying or modeling the direction of change as well as underlying drivers of drylands vegetation [21]. Those models applied to two or more spatially close and interwoven vegetation species, require to implementation of specific processings. To the best of our knowledge, the recent progress in modeling sub-Saharan vegetation transition introduced the term of “bistability” around lower and upper transition boundaries between forest and savanna [8]. This model is based on paleo-ecological evidences (soil, topography) and climatic parameters change and oscillation (rainfall and temperature), that influence (for the firsts) and predispose (for the seconds) these two species to coexistence. With the support of a floristic survey, the ambiguity of mischaracterizing savanna as a degraded forest was clarified at some point, by identifying, the dense forest, the “bistable” forest, the “bistable” savanna, and the proper savanna.
This study approaches the forest-savanna transition study, by investigating its different spectral behaviors and their statistical meaning, in a context lacking field data, and from an open-source/open-data perspective. The triple aim is to assess the dynamics, discriminate species disturbance based on their empirical spatial distribution, and predict their extent and boundaries. As such, assuming a blurred boundary and an overlapping spatial gradient between the two species, some phenological and physiological characteristics are considered as separately as possible in terms of anomalies, and further integrated beneath the same model, so as to locate the spots requiring permanent monitoring or sustainable actions, without mischaracterizing punctual changes, factual distribution, and most accurate delineation.
The study was conducted on the sub-Saharan mixed ecoregion, highly dependent on varied annual precipitations (AP) and yearly medium to high average temperatures (T0), which both influence relative humidity (RH) changes. The area belongs to the medium Cameroon (central Africa), between latitudes 500’-805’N and longitudes 1000′-1505′E, a climatic transition between the agroecological zones of western highlands (AP = 1800-2500 mm; T0 = 19.5°C; RH = 75%), bi-modal rainforest (AP = 1700-2000 mm; T0 = 24°C; RH = 80%), and then Guinean high savanna (AP = 1500–1800 mm; T0 = 30°C; RH = 60%) to Sudano-Sahelian savanna (AP = 400–1200 mm; T0 = 28°C; RH = 50%) for the core area. Specifically, the vegetation density broadly reflects the climate gradient of dense moist broadleaf forest and highland forest to sparse extensive savannas featuring the co-dominance of woody shrubs, grassland in plains, and herbaceous steppe at the edge of Sahel (Figure 1) [22].
Location of the study: (A) Cameroon in the context of African ecoregions based on Olson et al. (2001); (B) distribution of ecoregions in Cameroon; (C) preview of the subset ecoregions; (D) Sentinel2-a median image of the subset for mid-November 2020 to end march 2021.
The study was conducted using European Spatial Agency, ESA, Sentinel2-A multispectral instrument (MSI) data, which represents a very valuable opportunity for the fine characterization and monitoring of vegetation types on large scales, but is poorly investigated for the tropical biome study [11, 23]. This sensor provides 13 varied spectral bands from 0.443 to 2.190 micrometers, a 10-day repeat cycle, and a spatial resolution up to 10 meters (Additional material 1).
The phenological dry season, globally from November to March, was selected because of its high temperatures and less rainfalls, assuming they are ideal conditions to observe the vegetation adaptations to extremes, for years 2015 to 2021. In the GEE cloud coding environment and using the JavaScript opensource simplified coding, the median reducer function was appended as the pixel-wise computation of all bi-annual collection images, based on a band per band processing [24]. Then, applying a date filter from November 15 to end of March 31, a boundary filter for the study area, and a cloud cover acceptance filter below 10%, one image of 13 bands was outputted per bi-annual periods 2015–2016 to 2020–2021, displayed a,nd converted from 16 bits to 8 bits before further processings. Offline tools, i.e., desktop software, were used to extract statistics and for some complementary processings using less memory, including final layouts. Namely, Erdas Imagine 2020, ArcGIS Pro 2020, and Microsoft Excel with extension Xlstat were specifically used.
In arid and semi-arid regions, common changes in density, spatial distribution, chlorophyll, pigmentation, water stress, anthocyanin, nitrogen, carotenoids, leaf structure, and browning or senescence differently impact the biomass [25]. Previous spectral indices-based applications investigated that, the visible (0.4–0.7 μm) wavelengths respond to photosynthetic and non-photosynthetic pigments, the NIR (0.7–1.4 μm) wavelengths respond to the cellular structure and exhibit solar-induced fluorescence (SIF) and the SWIR (1.4–3 μm) wavelengths respond to senescent non-photosynthetic vegetation. As such, the anisotropic behavior of vegetation at visible-SWIR wavelengths has been parameterized to describe vegetation structure [26].
We computed twelve spectral indices, whose three were selected as reference data according to their ability to better highlight the land cover targeted, i.e., second modified soil adjusted vegetation index, MSAVI2 [27], to assess the vegetation cover, normalized difference soil drought index NDSoDI [14], to highlight the dry bare soils, and new water index, NWI [28], to map the surface water. After testing dozens of other indices, two assumptions were emitted for an efficient last casting, such as
Name | Equation | Primary goal | Reference |
---|---|---|---|
MSAVI2 | Map vegetation cover while reducing soil background | [27] | |
NDSoDI | Map dry soils while reducing surroundings source of moisture | [14] | |
NWI | Extract surface water | [28] | |
PVR | Photosynthetic vigor for crop monitoring | [29] | |
GVMI | Vegetation water content and evapotranspiration | [30] | |
PBI | General biochemical reflectance | [31] | |
REIP1* | Canopy chlorophyll, nitrogen content and polluted soil dynamics | [32] | |
mCRIG | Chlorophyll, carotenoids and anthocyanin | [33] | |
LWCI | Water content, change and stress | [34] | |
MARI | Chlorophyll, carotenoids and anthocyanin | [35] | |
SRPI** | Nitrogen content, water and chlorophyll | [36] | |
PSRI | Pigmentation and vigor changes dues to vegetation senescence | [37] |
Spectral indices used.
Was inverted after first preview, to better highlight vegetation patterns instead of soil dynamics.
Was adapted to SENTINEL2-A covered wavelengths by using band 6.
These indices were stacked and previewed with, MSAVI2, NDSoDI and NWI seeking the following:
Relationships between each analytical spectral index and both referential ones. The bright green curve represents the dependent variable, while the two others are explanatory variables (MSAVI2 = dark green; NDSoDI = light brown). N = 500 for all variables and regression parameters. The following is noticed from the trends of curves: PVR, PBI and GVMI have a neat positive correlation with MSAVI2, but a sharp negative one with NDSoDI; conversely, MARI and PSRI curves describe the exact opposite trends (positive with NDSoDI and negative with MSAVI2); mCRIG and LWCI curves evolve in another direction cutting the MSAVI2 and NDSoDI curves, while IREIP1 curve shows no real relationship them.
This process creates a difference image between two or more bands in a multi-temporal image analysis, so to detect changes in the type or the conditions of surface features. Depending on the study, change vector analysis (CVA) can use calculation principles of the Mahalanobis or the Euclidean distance as in this study, according to the following expression [38]:
Where
Four classes of magnitude are represented for either degradation or re-growing [39] (Additional material 4). For each binarized image, a CVA process was performed, the magnitudes of increase and decrease patterns were used, while the stability magnitudes were ignored. A total of twelve difference images per index resulted, i.e., six per selected magnitude. Considering the need of complementarity among indices, only one CVA magnitude, i.e., increase or decrease, was selected per index for further processing. Criteria used to optimize the selection were the original goal of each index, as well as its spatial and statistical relationship with MSAVI2, NDSoDI and NWI (Table 2).
Index | Targeted asset | Compared trends to MSAVI2 / NDSoDI / NWI | CVA |
---|---|---|---|
PVR | Age & Cover | Same with a plus / Inverted / Inverted | Decrease |
GVMI | Water content & Cover | Same with a plus / Inverted / Inverted | Decrease |
PBI | Inner composition & Cover | Same with a plus / Inverted / Inverted | Decrease |
IREIP1 | Height, Cover & Health | Different / Inverted / Inverted | Decrease |
mCRIG | Health & Composition | Different / Inverted / Inverted | Increase |
LWCI | Water stress | Different / Inverted / Close | Decrease |
MARI | Health & Inner composition | Inverted / Close / Inverted | Increase |
SRPI | Health & Inner composition | Inverted / Close / Inverted | Increase |
PSRI | Age & Cover | Inverted / Close / Inverted | Increase |
CVA magnitude selected per spectral index.
The moving standard deviation index, MSDI, is a filter applied to satellite images multispectral or derivative channels using the moving standard deviation calculation, generally to assess degradation [40]. One common application is the vegetation and soil of semi-arid systems, where the variability of the MSDI is used to indicate levels of habitat degradation [41, 42, 43]. MSTDI has been proven efficient to operate well in complex regions [40, 42, 44].
Here, the five derivative images per selected CVA were used as entries. A standard deviation was computed for each entry. Difference between consecutive standard deviations were calculated, giving four new images. Then, the averaged MSDI (aMSDI) was conceived as follows:
For all
The global Moran’s I index was computed to assess the spatial autocorrelation of aMSDI outputs along the 1544 pixels transect. Its integration in spatial analysis is important to avoid incorrect statistical inference from inefficient or biased parameter estimates [45]. The formula is expressed such as follows:
Where
Values closer to
Ordinary Least Squares (OLS) regression was computed as the non-spatial measure of the spatial convergence/divergence of aMSDI. This method predicts or models a dependent variable relationship with a set of explanatory variables. The regression coefficients are usually estimated by using least-square techniques such as:
Where,
Here, each aMSDI of the nine indices was considered as dependent variable, whereas MSAVI2’s aMSDI of both CVA, were simultaneous explanators. Three OLS parameters were selected for interpretation, i.e., adjusted R-squared, corrected Akaike’s information criterion (AICc) which assesses the best-fit model between spatial and non-spatial Ordinary Least Squares (OLS) models, root mean squares error (RMSE), and three graphs, i.e., scatterplots of the relationship among variables, histograms of standard deviation probability and plots of residuals versus predicted.
At this point, the spatial correlation was assessed through the cross-correlation mapping process using only the finest
Further, the individual maps of anomalies were used to produce a single one. The first step consisted in stacking the aMSDI for each
Based on visual trends, binarized images were regrouped in three axes of three indices of vegetation each. A principal component analysis, PCA, was performed for each ax using the covariance reducer algorithm, that reduces some number of
Training:Testing | Total | ||||
---|---|---|---|---|---|
Vegetation1 | Vegetation2 | Vegetation3 | Soil/Built-up | Water | |
100:100 | 100:100 | 100:100 | 100:100 | 100:100 | 500:500 |
Samples distribution.
Three machine learning algorithms were performed, such as the Classification and Regression Trees (CART), Random Forest (RF) and Support vector machine, (SVM) [47, 48, 49]. The metrics used to assess general performance of each classifier were overall accuracy, OA, and the kappa coefficient, KC [50, 51]. Whereas, the thorough assessment of their efficiency on individual LULC classes was done using the error matrix to extract the producer accuracy (PA) and the user accuracy (UA). Eqs. (7) and (8) formulate the main quality measures of the learning:
with,
Where,
Overview of the study design.
Globally, each index showed a different interseason sensitivity to dynamics for the two main magnitudes of change in the vegetation distribution. The indices detecting vigor, biochemical composition, and water content, i.e., PVR, PBI and GVMI, that are highly correlated with MSAVI2, invaded the upper medium area for the increasing magnitude, while their increasing patterns were more concentrated on the south and lower medium area (Figure 4a and
a. Decrease trends of CVA per index. The background layers are from 2021 to 2022. b. Increase trends of CVA per index. The background layers are from 2021 to 2022.
Moreover, all magnitudes agreed to the same total areas for all indices, when adding the unchanged magnitudes. For the extreme cases, LWCI indicates a brutal decrease in between 2015 and 2016 and 2016–2017 (Change1, Figure 5a), from 61,609 km2 to 22,030 km2, i.e., 58% of the total change for the study period (Figure 5b). While, GVMI indicates an important increase between 2019 and 2020 and 2020–2021 (Change 5, Figure 5a), from 1439 km2 to 41,215 km2, i.e., 69.4% of the total change for the study period (Figure 5b). Then all changes were complementary between the two magnitudes, except for IREIP1 in the last period, 2020–2021/2021–2022, which the decrease was unsignificant (4km2) compared to the increase (Figure 5a&
Areas(a), percentages(b) and hierarchy of changes (c) based on the CVA decrease (row1) and increase (row2) magnitudes.
The outputs of the aMSDI were all obtained in the same interval,
From the spatial autocorrelation model synthesized in Table 4, the expected Moran’s I index and p-values are identical for all, −
aMSDI | Moran’s I | Expected Moran’s I | Variance | Z-Scores > +2.58 | P-Values |
---|---|---|---|---|---|
MSAVI2_Decr | 0.9 | −0.000648 | 0.000457 | 42.2 | 0.00 |
MSAVI2_Incr | 0.81 | −0.000648 | 0.000457 | 37.9 | 0.00 |
PVR | 0.95 | −0.000648 | 0.000458 | 44.3 | 0.00 |
PBI | 0.85 | −0.000648 | 0.000458 | 39.6 | 0.00 |
GVMI | 0.84 | −0.000648 | 0.000457 | 39.5 | 0.00 |
IREIP1 | 0.76 | −0.000648 | 0.000457 | 35.4 | 0.00 |
mCRIG | 0.86 | −0.000648 | 0.000457 | 40.3 | 0.00 |
LWCI | 0.91 | −0.000648 | 0.000457 | 42.5 | 0.00 |
MARI | 0.91 | −0.000648 | 0.000457 | 42.5 | 0.00 |
SRPI | 0.86 | −0.000648 | 0.000457 | 40.4 | 0.00 |
PSRI | 0.84 | −0.000648 | 0.000458 | 39.3 | 0.00 |
Spatial autocorrelation model report. N = 1544 for all variables and parameters.
First outputs of the cross-correlation mapping algorithm informed on the spatial relationship between each MSAVI2’s aMSDI and individual aMSDI of analytical indices. About the MSAVI2 decrease CVA, the highest positive correlation of aMSDI was with PVR (
Cross-correlation maps between aMSDIs of MSAVI2 and the selected aMSDI for each index.
The multi-regression performed between each analytical aMSDI and simultaneously both MSAVI2’s aMSDI on
OLS regression results synthesis (
Spatial synthesis of the cross-correlation mapping algorithm confirms the distribution of patterns and global trends. The combined correlation among the nine indices’ aMSDI were found strong at different degrees, for both highest and lowest values, then indicating convergences of significant or non-significant anomalies at the South-west and North-East of the area (Figure 8). For the three windows of calculation, they were clearly separated from predicted vegetation statuses, i.e., highly and lowly affected, soil, built-up and water features (Figure 8). From the cross-correlation map synthesis, the simple linear combination (SLC) outputs for each window discriminated positive from negative spatial trends. Then, the largest spots of extremely severe anomalies are located in the south-west, south-east and north-east areas, well separated on
Anomaly trends and spots. The synthesized correlation maps on the first row shows patchwork of high correlation in the medium area for the
The repeated sampling of vegetation gave spectral curves with at least three pairs of same trends for vegetation (Figure 9a). As spatial evidence, the patterns of ML were identical for the three algorithms, with three distinguished classes of vegetation, well separated from soil/built-up and water (Figure 9b). The three classifiers performed with a high and identical OA of
Spectral curves (A), spatial patterns (B) and statistics (C) of the three axes of vegetation on LULC. In details: (A) CART; (B) RF; (C) SVM: (D) stacked axes of vegetation with soil (NDSoDI) and water (NWI) features for 2021–2022; E) Sentinel2-a image of 2021–2022.
Concerning the vegetation types, discrimination, and extent, RF and SVM gave the exact areas for the three classes, CART agreed with them for the second and third axes, whereas the stacked derivative only agreed with all the algorithms concerning the third ax, i.e.,
The efficiency of the whole proposed methodology was assessed and discussed on selected aspects and the comparison with existing methods was basically empirical. At first, depending on their goals, previous MSDI-based studies analyzed only the standard deviation of the red and near infrared wavelengths, while those integrating vegetation indices were limited to three of them [40, 43, 52]. Because the goal of proposing aMSDI in this study was to assess consecutives dry season anomalies and discriminate them from empirical statuses of the forest-savanna specificities, we integrated nine spectral indices, selected on the basis of targeted phenological or physiological weaknesses, and whose computations basically integrate several wavelengths. Interestingly, although only one CVA magnitude was chosen per index, all individual models showed the expected visual convergence of similarity or dissimilarity trends.
Moreover, previous applications stated that the common calculation of MSDI on raw spectral index, gives outputs with a minimum value of zero and a maximum value determined by those of the pixels evaluated [43]. Consequently, outputs value cannot be directly compared. Here, by applying the averaging process to binarized CVA,
Besides, common attempts of mapping distribution, typology, and delineation of forest and savanna, have always been supported by fieldwork, based on climate parameters, as well as including paleo-ecological evidences and detailed floristic survey to be efficient [8]. The methodology presented in this paper has predicted three different axes of vegetation, resulting from the PCA processing and thresholding (Table 5). For each of the six study periods, the first ax in the south part is composed by a dense and potentially healthier vegetation, highly correlated with the referential data MSAVI2. Whereas the other two axes, more and more sparse towards north, are divergent with the first one and somehow each with another (Figure 10a&
Vegetation trends | Regrouping | PCA threshold |
---|---|---|
1st axe | PVR, PBI, GVMI | |
2nd axe | IREIP1, MARI, PRSI | |
3rd axe | mCRIG, LWCI, SRPI |
Vegetation axes, proposed groups and PCA thresholds used to binarize.
a. the three main axes of vegetation’s spatial distribution. b. Pixels’ value along the transect of the vegetation’s axes.
To answer the interrogations behind these ambiguities, a simple multicollinearity test was run, showing how independent one ax is from another. When the correlation between two independent variables is considerably high, it is a problem in the modeling process. The VIF (variance inflation factor) and tolerance were used for diagnosis. VIF is the reciprocal of tolerance, knowing that, tolerance is
Axe | VIF | Tolerance | Percentile for value 1 |
---|---|---|---|
AXE1 | 1.33 | 0.75 | [49.9–99.97] |
AXE2 | 1.12 | 0.89 | [62.5–99.97] |
AXE3 | 1.35 | 0.74 | [78.3–99.97] |
Multicollinearity test results.
Although from this study, we cannot properly use the qualifier of “bistable” forest or savanna, because it highly depends upon climate and paleo-ecological parameters, it is important to notice how ambiguous is the distribution and blurry are the boundaries. Thoroughly, on any ML output, three zooms distributed on three different latitudes helped to notice different types of transitions (Figure 11). Between the lower latitudes 5030’-6030’North, the transition is from the first (moist broadleaf forest) to third ax of vegetation (shrubland savanna), although the second ax (grassland savanna) would have been “expected.” Between the middle latitudes 6030’-7030’North, the transition mixes in the below area, the “-‘unexpected” third ax (shrubland savanna) with the ‘expected’ first ax (moist broadleaf forest) of vegetation, before the wide expansion of the ‘expected’ second ax (grassland savanna). At this point, the only “expected” transition was inside the upper latitudes 7030’-8030’North, where the second ax (grassland savanna) gradually gave way to third ax (shrubland savanna) of vegetation. These elements of analysis support the qualifier of “bistable” area, while still questioning the anisotropic distribution with latitudes, and encouraging the finest scale of analysis, i.e., spatial and spectral resolution.
Zooms on the transitions, a sign of anisotropic distribution with latitudes. Yellow square = lower latitudes (5030’-6030’N) transition; red square = middle latitudes (6030’-7030’N) transition; blue = upper latitudes (7030’-8030’N) transition.
Anomalies versus LULC classes. (A) SVM classification map. (B) Two extreme classes of anomalies at
Finally, the display of anomalies with the LULC classes disambiguated the confusion of savanna and degraded forest. The observation was made by overlaying the highest and the lowest values of anomalies in the most concentrate area, on the SVM output. On three spots covered by grassland, shrubland and bare soil, the modeled extremely severe anomalies concern just a part of each class. Whereas, on two spots of lower to no-anomalies, savanna as well as bare soils are partially concerned (Figure 12).
This study has conducted an experimentation on the forest-savanna vegetation, with the goal of assessing dynamics, assuming anomalies and predicting boundaries. On Google Earth Engine platform and using Sentinel2-A satellite images of seven consecutive dry seasons, from 2015 to 2016 to 2021–2022, twelve spectral indices were selected according to their different phenological and physiological assessment of the vegetation, and other natural features to be discriminate. Using the processing of change vector analysis, CVA, it was successfully observed that each index brings a substantial information, to better assess increase or decrease patterns of the vegetation cover. Further, proposing the averaged moving standard deviation index, aMSDI, to face potential issues of simple MSDI, the scale of spatial trends appraisal was found identical between the same interval
To USGS for the free availability of satellite data. To all experts-developers of Google Earth Engine platform APIs. To StatsN’Maps Consulting Firm, for the logistic support. To our laboratories.
The authors declare no conflict of interest.
Conception, A.H.N.M.; study design, A.H.N.M.; acquisition of data, A.H.N.M., I.C.N.P., F.C.L.T., L.M.B., M.T. and J.V.M.M.; execution, A.H.N.M.; analysis and interpretation, A.H.N.M.; writing-original draft preparation, A.H.N.M.; writing-review and editing A.H.N.M., I.C.N.P., F.C.L.T., L.M.B., M.T. and J.V.M.M.; All authors have read and agreed to the published version of the manuscript.
Links to the code are available upon request.
Additional material 1. Characteristics of Sentinel-2A bands.
Sentinel-2A MSI | ||
---|---|---|
Name | Range (μm) | Bands (Resolution/m) |
Coastal aerosol | 0.421 − 0.457 | B1(60) |
Blue | 0.439 − 0.535 | B2(10) |
Green | 0.537 − 0.582 | B3(10) |
Red | 0.646 − 0.685 | B4(10) |
Red_edge1 | 0.694 − 0.714 | B5(10) |
Red_edge2 | 0.731 − 0.749 | B6(10) |
Red_edge3 | 0.768 − 0.796 | B7(10) |
NIR wide | 0.767 − 0.908 | B8(10) |
NIR narrow | 0.848 − 0.881 | B8A(20) |
Water vapor | 0.931 − 0.958 | B9(60) |
Cirrus | 1.338 − 1.414 | B10(60) |
SWIR1 | 1.539 − 1.681 | B11(20) |
SWIR2 | 2.072 − 2.312 | B12(20) |
Additional material 2. The spectral indices used. The first row is the supporting or reference data.
Additional material 3. Binarized indices and thresholds defined.
Additional material 4. Direction and magnitude of change as proposed by Kuzera et al. (2005).
Additional material 5a. Averaged MSDI patterns of MSAVI2.
Additional material 5b. Averaged MSDI patterns for PVR, PBI and GVMI.
Additional material 5c. Averaged MSDI patterns for IREIP1, mCRIG and LWCI.
Additional material 5d. Averaged MSDI patterns for MARI, SRPI and PSRI.
Additional material 6. Spatial autoregression sample plots of aMSDI for PVR (left) and MSAVI2 increase patterns (right). red square = spatial correlation targeted, for n = 1544 pixels.
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Saleh and Amal I. Hassan",coverURL:"https://cdn.intechopen.com/books/images_new/11120.jpg",editedByType:"Edited by",publishedDate:"June 23rd 2022",editors:[{id:"144691",title:"Prof.",name:"Hosam M.",middleName:null,surname:"Saleh",slug:"hosam-m.-saleh",fullName:"Hosam M. Saleh"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10696",title:"Applications of Calorimetry",subtitle:null,isOpenForSubmission:!1,hash:"8c87f7e2199db33b5dd7181f56973a97",slug:"applications-of-calorimetry",bookSignature:"José Luis Rivera Armenta and Cynthia Graciela Flores Hernández",coverURL:"https://cdn.intechopen.com/books/images_new/10696.jpg",editedByType:"Edited by",publishedDate:"June 23rd 2022",editors:[{id:"107855",title:"Dr.",name:"Jose Luis",middleName:null,surname:"Rivera Armenta",slug:"jose-luis-rivera-armenta",fullName:"Jose Luis Rivera Armenta"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},subject:{topic:{id:"235",title:"Gerontology",slug:"gerontology",parent:{id:"21",title:"Psychology",slug:"psychology"},numberOfBooks:4,numberOfSeries:0,numberOfAuthorsAndEditors:72,numberOfWosCitations:29,numberOfCrossrefCitations:39,numberOfDimensionsCitations:75,videoUrl:null,fallbackUrl:null,description:null},booksByTopicFilter:{topicId:"235",sort:"-publishedDate",limit:12,offset:0},booksByTopicCollection:[{type:"book",id:"7904",title:"Aging",subtitle:"Life Span and Life Expectancy",isOpenForSubmission:!1,hash:"4507619de679dfa85bc6e073d163f3c8",slug:"aging-life-span-and-life-expectancy",bookSignature:"Robert J. Reynolds and Steven M. Day",coverURL:"https://cdn.intechopen.com/books/images_new/7904.jpg",editedByType:"Edited by",editors:[{id:"220737",title:"Dr.",name:"Robert",middleName:null,surname:"J. Reynolds",slug:"robert-j.-reynolds",fullName:"Robert J. Reynolds"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"6704",title:"Geriatrics Health",subtitle:null,isOpenForSubmission:!1,hash:"7cac7767e0b34391318cd4a680ca0d68",slug:"geriatrics-health",bookSignature:"Hülya Çakmur",coverURL:"https://cdn.intechopen.com/books/images_new/6704.jpg",editedByType:"Edited by",editors:[{id:"190636",title:"Associate Prof.",name:"Hülya",middleName:null,surname:"Çakmur",slug:"hulya-cakmur",fullName:"Hülya Çakmur"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"6381",title:"Gerontology",subtitle:null,isOpenForSubmission:!1,hash:"bf232563c8fe15ef0848ed6ffb8f832d",slug:"gerontology",bookSignature:"Grazia D’Onofrio, Antonio Greco and Daniele Sancarlo",coverURL:"https://cdn.intechopen.com/books/images_new/6381.jpg",editedByType:"Edited by",editors:[{id:"272628",title:"Dr.",name:"Grazia",middleName:null,surname:"D'Onofrio",slug:"grazia-d'onofrio",fullName:"Grazia D'Onofrio"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"5925",title:"Perception of Beauty",subtitle:null,isOpenForSubmission:!1,hash:"11f483d631557ad26d48b577e23a724f",slug:"perception-of-beauty",bookSignature:"Martha Peaslee Levine",coverURL:"https://cdn.intechopen.com/books/images_new/5925.jpg",editedByType:"Edited by",editors:[{id:"186919",title:"Dr.",name:"Martha",middleName:null,surname:"Peaslee Levine",slug:"martha-peaslee-levine",fullName:"Martha Peaslee Levine"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}],booksByTopicTotal:4,seriesByTopicCollection:[],seriesByTopicTotal:0,mostCitedChapters:[{id:"60564",doi:"10.5772/intechopen.76249",title:"Ageing Process and Physiological Changes",slug:"ageing-process-and-physiological-changes",totalDownloads:6884,totalCrossrefCites:16,totalDimensionsCites:31,abstract:"Ageing is a natural process. Everyone must undergo this phase of life at his or her own time and pace. In the broader sense, ageing reflects all the changes taking place over the course of life. These changes start from birth—one grows, develops and attains maturity. To the young, ageing is exciting. Middle age is the time when people notice the age-related changes like greying of hair, wrinkled skin and a fair amount of physical decline. Even the healthiest, aesthetically fit cannot escape these changes. Slow and steady physical impairment and functional disability are noticed resulting in increased dependency in the period of old age. According to World Health Organization, ageing is a course of biological reality which starts at conception and ends with death. It has its own dynamics, much beyond human control. However, this process of ageing is also subject to the constructions by which each society makes sense of old age. In most of the developed countries, the age of 60 is considered equivalent to retirement age and it is said to be the beginning of old age. In this chapter, you understand the details of ageing processes and associated physiological changes.",book:{id:"6381",slug:"gerontology",title:"Gerontology",fullTitle:"Gerontology"},signatures:"Shilpa Amarya, Kalyani Singh and Manisha Sabharwal",authors:[{id:"226573",title:"Ph.D.",name:"Shilpa",middleName:null,surname:"Amarya",slug:"shilpa-amarya",fullName:"Shilpa Amarya"},{id:"226593",title:"Dr.",name:"Kalyani",middleName:null,surname:"Singh",slug:"kalyani-singh",fullName:"Kalyani Singh"},{id:"243264",title:"Dr.",name:"Manisha",middleName:null,surname:"Sabharwal",slug:"manisha-sabharwal",fullName:"Manisha Sabharwal"}]},{id:"55388",doi:"10.5772/intechopen.68944",title:"Beauty, Body Image, and the Media",slug:"beauty-body-image-and-the-media",totalDownloads:7678,totalCrossrefCites:5,totalDimensionsCites:12,abstract:"This chapter analyses the role of the mass media in people’s perceptions of beauty. We summarize the research literature on the mass media, both traditional media and online social media, and how they appear to interact with psychological factors to impact appearance concerns and body image disturbances. There is a strong support for the idea that traditional forms of media (e.g. magazines and music videos) affect perceptions of beauty and appearance concerns by leading women to internalize a very slender body type as ideal or beautiful. Rather than simply being passive recipients of unrealistic beauty ideals communicated to them via the media, a great number of individuals actually seek out idealized images in the media. Finally, we review what is known about the role of social media in impacting society’s perception of beauty and notions of idealized physical forms. Social media are more interactive than traditional media and the effects of self‐presentation strategies on perceptions of beauty have just begun to be studied. This is an emerging area of research that is of high relevance to researchers and clinicians interested in body image and appearance concerns.",book:{id:"5925",slug:"perception-of-beauty",title:"Perception of Beauty",fullTitle:"Perception of Beauty"},signatures:"Jennifer S. Mills, Amy Shannon and Jacqueline Hogue",authors:[{id:"202110",title:"Dr.",name:"Jennifer S.",middleName:null,surname:"Mills",slug:"jennifer-s.-mills",fullName:"Jennifer S. Mills"}]},{id:"59227",doi:"10.5772/intechopen.73385",title:"Differentiating Normal Cognitive Aging from Cognitive Impairment No Dementia: A Focus on Constructive and Visuospatial Abilities",slug:"differentiating-normal-cognitive-aging-from-cognitive-impairment-no-dementia-a-focus-on-constructive",totalDownloads:1329,totalCrossrefCites:3,totalDimensionsCites:6,abstract:"Constructive and visuospatial abilities in normal and in pathological aging (cognitive impairment, no dementia, CIND) are investigated. The sample includes 188 participants over 60 years of age, divided in 2 groups: healthy subjects (MMSE ≥28), without cognitive complaints, and individuals with CIND (MMSE between 24 and 27 and subjective cognitive complains). Drawing of cube and drawing of house, Benton Visual Retention Test (BVRT), and Block design are used to test the hypothesis that short visuoconstructive and visuospatial tests can distinguish normal from pathological cognitive aging in its very early stages. Results proved the discriminative sensitivity of BVRT general assessment criteria and of omissions and distortions in CIND. The diagnostic sensitivity of a modification of Moore and Wike [1984] scoring system for house and cube drawing tasks was confirmed as well. Drawing of cube and house could be used for quick screening of CIND in subjects over 60. Principal component analysis with oblimin rotation was performed to explore the different dimensions in the visuospatial and visuoconstructive abilities in old age. A four-factor structure was established, all four factors explaining 71% of the variance.",book:{id:"6381",slug:"gerontology",title:"Gerontology",fullTitle:"Gerontology"},signatures:"Radka Ivanova Massaldjieva",authors:[{id:"75907",title:"Associate Prof.",name:"Radka Ivanova",middleName:null,surname:"Massaldjieva",slug:"radka-ivanova-massaldjieva",fullName:"Radka Ivanova Massaldjieva"}]},{id:"59658",doi:"10.5772/intechopen.74748",title:"Ageing Better in the Netherlands",slug:"ageing-better-in-the-netherlands",totalDownloads:1175,totalCrossrefCites:1,totalDimensionsCites:4,abstract:"The Dutch National Care for the Elderly Programme was an initiative organized by the Netherlands Organisation for Health Research and Development (ZonMw) between 2008 and 2016. The aim of the programme was to collect knowledge about frail elderly, to assess their needs and to provide person-centred and integrated care better suited to their needs. The budget of EUR 88 million was provided by the Dutch Ministry of Health, Welfare and Sports. Putting the needs of elderly people at the heart of the programme and ensuring their active participation were key to the programme’s success. The programme outcomes included the establishment of eight geriatric networks around the medical universities with 650 organisations and the completion of 218 projects. These projects, involving 43,000 elderly people and 8500 central caregivers, resulted in the completion of 45 PhD theses and the publication of more than 400 articles and the development of 300 practice toolkits, one database and a website, www.beteroud.nl. The Dutch National Care for the Elderly Programme has since developed into a movement and continues under the consortium Ageing Better, made up of eight organisations. Through the use of ambassadors, Ageing Better promotes the message that ageing is not a disease but a new phase of life.",book:{id:"6381",slug:"gerontology",title:"Gerontology",fullTitle:"Gerontology"},signatures:"Betty Meyboom-de Jong, Klaske Wynia and Anjo Geluk-Bleumink",authors:[{id:"224997",title:"Emeritus Prof.",name:"Betty",middleName:null,surname:"Meyboom-De Jong",slug:"betty-meyboom-de-jong",fullName:"Betty Meyboom-De Jong"},{id:"232900",title:"Dr.",name:"Klaske",middleName:null,surname:"Wynia",slug:"klaske-wynia",fullName:"Klaske Wynia"},{id:"232901",title:"Mrs.",name:"Anjo",middleName:null,surname:"Geluk-Bleumink",slug:"anjo-geluk-bleumink",fullName:"Anjo Geluk-Bleumink"}]},{id:"57952",doi:"10.5772/intechopen.71904",title:"Neurocognitive Implications of Tangential Speech in Patients with Focal Brain Damage",slug:"neurocognitive-implications-of-tangential-speech-in-patients-with-focal-brain-damage",totalDownloads:1574,totalCrossrefCites:0,totalDimensionsCites:3,abstract:"There are no studies on the neurocognitive implications of tangential speech (TS). This research aims to take a step forward in the study of narrative processing, by evaluating TS in a sample that helps to detect this deficit when it is neurogenic and recently manifested. The relationship between TS, secondary to focal brain injury, and neuropsychological and neuroanatomical variables was explored. A comprehensive neuropsychological battery was administered to 175 volunteers: 95 alert inpatients, without aphasia, without psychiatric history and without TS history, and 80 healthy participants, without TS. Results: TS (prevalence 16%) was independent of type or site of injury. An adverse effect of TS on global neuropsychological performance was observed. This effect was significantly related to attentional errors along with prolonged processing times but not to correct responses. Reliability and validity indices for the present TS screening scale were provided. Conclusion: Present results support the hypothesis that this neurogenic inability to spontaneously find, organize and communicate verbal information, beyond single words, depends on extended brain networks involving processes such as sustained attention, complex-syntax comprehension, the (implicit) interpretation and spontaneous recall of a narrative, and emotional and behavioral alterations. Early TS detection is advisable for prevention and treatment at any age.",book:{id:"6381",slug:"gerontology",title:"Gerontology",fullTitle:"Gerontology"},signatures:"Nora Silvana Vigliecca",authors:[{id:"202008",title:"Dr.",name:"Nora",middleName:"Silvana",surname:"Vigliecca",slug:"nora-vigliecca",fullName:"Nora Vigliecca"}]}],mostDownloadedChaptersLast30Days:[{id:"60564",title:"Ageing Process and Physiological Changes",slug:"ageing-process-and-physiological-changes",totalDownloads:6884,totalCrossrefCites:16,totalDimensionsCites:31,abstract:"Ageing is a natural process. Everyone must undergo this phase of life at his or her own time and pace. In the broader sense, ageing reflects all the changes taking place over the course of life. These changes start from birth—one grows, develops and attains maturity. To the young, ageing is exciting. Middle age is the time when people notice the age-related changes like greying of hair, wrinkled skin and a fair amount of physical decline. Even the healthiest, aesthetically fit cannot escape these changes. Slow and steady physical impairment and functional disability are noticed resulting in increased dependency in the period of old age. According to World Health Organization, ageing is a course of biological reality which starts at conception and ends with death. It has its own dynamics, much beyond human control. However, this process of ageing is also subject to the constructions by which each society makes sense of old age. In most of the developed countries, the age of 60 is considered equivalent to retirement age and it is said to be the beginning of old age. In this chapter, you understand the details of ageing processes and associated physiological changes.",book:{id:"6381",slug:"gerontology",title:"Gerontology",fullTitle:"Gerontology"},signatures:"Shilpa Amarya, Kalyani Singh and Manisha Sabharwal",authors:[{id:"226573",title:"Ph.D.",name:"Shilpa",middleName:null,surname:"Amarya",slug:"shilpa-amarya",fullName:"Shilpa Amarya"},{id:"226593",title:"Dr.",name:"Kalyani",middleName:null,surname:"Singh",slug:"kalyani-singh",fullName:"Kalyani Singh"},{id:"243264",title:"Dr.",name:"Manisha",middleName:null,surname:"Sabharwal",slug:"manisha-sabharwal",fullName:"Manisha Sabharwal"}]},{id:"55388",title:"Beauty, Body Image, and the Media",slug:"beauty-body-image-and-the-media",totalDownloads:7678,totalCrossrefCites:5,totalDimensionsCites:12,abstract:"This chapter analyses the role of the mass media in people’s perceptions of beauty. We summarize the research literature on the mass media, both traditional media and online social media, and how they appear to interact with psychological factors to impact appearance concerns and body image disturbances. There is a strong support for the idea that traditional forms of media (e.g. magazines and music videos) affect perceptions of beauty and appearance concerns by leading women to internalize a very slender body type as ideal or beautiful. Rather than simply being passive recipients of unrealistic beauty ideals communicated to them via the media, a great number of individuals actually seek out idealized images in the media. Finally, we review what is known about the role of social media in impacting society’s perception of beauty and notions of idealized physical forms. Social media are more interactive than traditional media and the effects of self‐presentation strategies on perceptions of beauty have just begun to be studied. This is an emerging area of research that is of high relevance to researchers and clinicians interested in body image and appearance concerns.",book:{id:"5925",slug:"perception-of-beauty",title:"Perception of Beauty",fullTitle:"Perception of Beauty"},signatures:"Jennifer S. Mills, Amy Shannon and Jacqueline Hogue",authors:[{id:"202110",title:"Dr.",name:"Jennifer S.",middleName:null,surname:"Mills",slug:"jennifer-s.-mills",fullName:"Jennifer S. Mills"}]},{id:"56505",title:"Aesthetics of the Naked Human Body: From Pornography (Sexualised Lust Object) to Iconography (Aesthetics of Human Nobility and Wisdom) in an Anthropology of Physical Beauty",slug:"aesthetics-of-the-naked-human-body-from-pornography-sexualised-lust-object-to-iconography-aesthetics",totalDownloads:2081,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"In many religious circles and philosophies of life, the human body is excluded from the realm of spirituality and meaning. Due to a dualistic approach, nudity is viewed as merely a physical and corporeal category. In social media, there is the real danger that the naked human body is exploited for commercial gain. Advertisements often leave the impression that the body, very specifically the genitals, is designed merely for physical desire and corporeal chemistry. They become easily objects for lust, excluded from the beauty of graceful existence and noble courage. It is argued that the naked human body is not designed for pornographic exploitation and promiscuous sensuality but for compassionate intimacy and nurturing care in order to instil a humane dimension in human and sexual encounters. In this regard, antiquity and the Michelangelesque perspective can contribute to a paradigm shift from abusive exploitation to the beauty of vulnerable sensitivity. In order to foster an integrative approach to theory formation in anthropology, the methodology of stereometric thinking is proposed.",book:{id:"5925",slug:"perception-of-beauty",title:"Perception of Beauty",fullTitle:"Perception of Beauty"},signatures:"Daniel J Louw",authors:[{id:"200645",title:"Prof.",name:"Daniel",middleName:"Johannes",surname:"Louw",slug:"daniel-louw",fullName:"Daniel Louw"}]},{id:"56059",title:"A Plastic Surgeon’s Perspective on Stereotyping and the Perception of Beauty",slug:"a-plastic-surgeon-s-perspective-on-stereotyping-and-the-perception-of-beauty",totalDownloads:1890,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"In the world of plastic surgery, misconceptions may lead to irrational requests or outcomes not appreciated by patients. Those who manage aesthetics should always listen and recognize the variability of cultural identities, desires, attitudes, anxieties and uncertainties of the patient. Emerging from a diversity of cultures and its transforming trends, the scope of cosmetic surgery and its practice reflect not only the individual’s personality, but also the culture as a whole. When counseling an individual, one has to recognize that even in groups of seemingly identical social or cultural standards; there are subtle differences in expectations. To illustrate the potential for inaccuracy of ethnic profiling in the field of plastic surgery authors quote their own work on Asian subjects and facial beauty and resort to experience of others. To reaffirm their opinion and to exemplify how sometimes “fine” differences in the perception of beauty exist, an original study that evaluates the preferences among selected groups of Latina women in respect to buttock aesthetics has been included. This dissertation will focus on how cultural factors influence beauty perception; strengthen the fact that beauty is in the eye of the beholder and how variable differences exist even between small subgroups.",book:{id:"5925",slug:"perception-of-beauty",title:"Perception of Beauty",fullTitle:"Perception of Beauty"},signatures:"Johanna D’Agostino and Marek Dobke",authors:[{id:"17590",title:"Dr.",name:"Marek K.",middleName:null,surname:"Dobke",slug:"marek-k.-dobke",fullName:"Marek K. Dobke"},{id:"201244",title:"Dr.",name:"Johanna",middleName:null,surname:"D'Agostino",slug:"johanna-d'agostino",fullName:"Johanna D'Agostino"}]},{id:"80326",title:"Anti-Senescence Therapy",slug:"anti-senescence-therapy",totalDownloads:102,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"The development of therapeutic strategies aimed at the aging process of cells has attracted increasing attention in recent decades due to the involvement of this process in the development of many chronic and age-related diseases. Interestingly, preclinical studies have shown the success of a number of anti-aging approaches in the treatment of a range of chronic diseases. These approaches are directed against aging processes such as oxidative stress, telomerase shortening, inflammation, and deficient autophagy. Many strategies has been shown to be effective in delaying aging, including antiaging strategies based on establishing healthy lifestyle habits and pharmacological interventions aimed at disrupting senescent cells and senescent-associated secretory phenotype. Caloric restriction and intermittent fasting were reported to activate autophagy and reduce inflammation. In turn, immune-based strategies, senolytic agents, and senomorphics mediate their effects either by eliminating senescent cells through inducing apoptosis or by disrupting pathways by which senescent cells mediate their detrimental effects. In addition, given the association of the decline in the regenerative potential of stem cells with aging, many experimental and clinical studies indicate the effectiveness of stem cell transplantation in preventing or slowing the progress of age-related diseases by enhancing the repairing mechanisms and the secretion of many growth factors and cytokines.",book:{id:"10935",slug:null,title:"Mechanisms and Management of Senescence",fullTitle:"Mechanisms and Management of Senescence"},signatures:"Raghad Alshadidi",authors:null}],onlineFirstChaptersFilter:{topicId:"235",limit:6,offset:0},onlineFirstChaptersCollection:[{id:"82112",title:"Comparative Senescence and Lifespan",slug:"comparative-senescence-and-lifespan",totalDownloads:7,totalDimensionsCites:0,doi:"10.5772/intechopen.105137",abstract:"The word senescence is derived from the Latin word “senex” (meaning old). In biology, senescence is a process by which a cell ages and permanently stops dividing. Senescence is a natural universal phenomenon affecting all living organisms (e.g., humans, animals, and plants). It is the process of growing old (aging). The underlying mechanisms of senescence and aging at the cellular level are not fully understood. Senescence is a multifactorial process that can be induced by several stimuli including cellular stress, DNA damage, telomere shortening, and oncogene activation. The most popular theory to explain aging is the free radical theory. Senescence plays a role in the development of several age-related chronic diseases in humans (e.g., ischemic heart disease, osteoporosis, and cancer). Lifespan is a biological characteristic of every species. The lifespan of living organisms ranges from few hours (with mayfly) to potential eternity (with jellyfish and hydra). The maximum theoretical lifespan in humans is around 120 years. The lifespan in humans is influenced by multiple factors including genetic, epigenetic, lifestyle, environmental, metabolic, and endocrine factors. There are several ways to potentially extend the lifespan of humans and eventually surpass the maximum theoretical lifespan of 120 years. The tools that can be proposed include lifestyle, reduction of several life-threatening diseases and disabilities, hormonal replacement, antioxidants, autophagy inducers, senolytic drugs, stem cell therapy, and gene therapy.",book:{id:"10935",title:"Mechanisms and Management of Senescence",coverURL:"https://cdn.intechopen.com/books/images_new/10935.jpg"},signatures:"Hassan M. Heshmati"},{id:"81638",title:"Aging and Neuropsychiatric Disease: A General Overview of Prevalence and Trends",slug:"aging-and-neuropsychiatric-disease-a-general-overview-of-prevalence-and-trends",totalDownloads:24,totalDimensionsCites:0,doi:"10.5772/intechopen.103102",abstract:"The increasing trend of life-expectancy is becoming a significant demographic, societal and economic challenge. Currently, global number of people above sixty years of age is 900 million, while United Nations expect this number to rise to over 1.4 billion in 2030 and over 2.5 billion by 2050. Concordant to this trend, numerous physiological changes are associated with aging and brain-related ones are associated with neuropsychiatric diseases. The main goal of this chapter is to identify the most important neuropsychiatric diseases to assess in older patients to help to promote health and prevent diseases and complications associated with chronic illness, as these changes are progressive and require important psychological and setting-related social adjustments. Findings identify several health-aspects highly present in elderly: stroke, white matter lesions, dementia rise with age, changes in levels of neurotransmitters and hormones, depression as well as the bereavement following loss of the loved one, and the most common neurodegenerative disease—Alzheimer’s disease and Parkinson’s. In conclusion, studying the aging process should include all developmental, circumstantial, and individual aspects of aging. This offers opportunities to improve the health of elderly by using a wide range of skills and knowledge. Thus, further studies are necessary to elucidate what can be done do to improve the aging process and health of elderly in the future.",book:{id:"10935",title:"Mechanisms and Management of Senescence",coverURL:"https://cdn.intechopen.com/books/images_new/10935.jpg"},signatures:"Jelena Milić"},{id:"80326",title:"Anti-Senescence Therapy",slug:"anti-senescence-therapy",totalDownloads:102,totalDimensionsCites:0,doi:"10.5772/intechopen.101585",abstract:"The development of therapeutic strategies aimed at the aging process of cells has attracted increasing attention in recent decades due to the involvement of this process in the development of many chronic and age-related diseases. Interestingly, preclinical studies have shown the success of a number of anti-aging approaches in the treatment of a range of chronic diseases. These approaches are directed against aging processes such as oxidative stress, telomerase shortening, inflammation, and deficient autophagy. Many strategies has been shown to be effective in delaying aging, including antiaging strategies based on establishing healthy lifestyle habits and pharmacological interventions aimed at disrupting senescent cells and senescent-associated secretory phenotype. Caloric restriction and intermittent fasting were reported to activate autophagy and reduce inflammation. In turn, immune-based strategies, senolytic agents, and senomorphics mediate their effects either by eliminating senescent cells through inducing apoptosis or by disrupting pathways by which senescent cells mediate their detrimental effects. In addition, given the association of the decline in the regenerative potential of stem cells with aging, many experimental and clinical studies indicate the effectiveness of stem cell transplantation in preventing or slowing the progress of age-related diseases by enhancing the repairing mechanisms and the secretion of many growth factors and cytokines.",book:{id:"10935",title:"Mechanisms and Management of Senescence",coverURL:"https://cdn.intechopen.com/books/images_new/10935.jpg"},signatures:"Raghad Alshadidi"},{id:"79828",title:"Cellular Senescence in Bone",slug:"cellular-senescence-in-bone",totalDownloads:106,totalDimensionsCites:0,doi:"10.5772/intechopen.101803",abstract:"Senescence is an irreversible cell-cycle arrest process induced by environmental, genetic, and epigenetic factors. An accumulation of senescent cells in bone results in age-related disorders, and one of the common problems is osteoporosis. Deciphering the basic mechanisms contributing to the chronic ailments of aging may uncover new avenues for targeted treatment. This review focuses on the mechanisms and the most relevant research advancements in skeletal cellular senescence. To identify new options for the treatment or prevention of age-related chronic diseases, researchers have targeted hallmarks of aging, including telomere attrition, genomic instability, cellular senescence, and epigenetic alterations. First, this chapter provides an overview of the fundamentals of bone tissue, the causes of skeletal involution, and the role of cellular senescence in bone and bone diseases such as osteoporosis. Next, this review will discuss the utilization of pharmacological interventions in aging tissues and, more specifically, highlight the role of senescent cells to identify the most effective and safe strategies.",book:{id:"10935",title:"Mechanisms and Management of Senescence",coverURL:"https://cdn.intechopen.com/books/images_new/10935.jpg"},signatures:"Danielle Wang and Haitao Wang"},{id:"79668",title:"Identification of RNA Species That Bind to the hnRNP A1 in Normal and Senescent Human Fibroblasts",slug:"identification-of-rna-species-that-bind-to-the-hnrnp-a1-in-normal-and-senescent-human-fibroblasts",totalDownloads:73,totalDimensionsCites:0,doi:"10.5772/intechopen.101525",abstract:"hnRNP A1 is a member of the hnRNPs (heterogeneous nuclear ribonucleoproteins) family of proteins that play a central role in regulating genes responsible for cell proliferation, DNA repair, apoptosis, and telomere biogenesis. Previous studies have shown that hnRNPA1 had reduced protein levels and increased cytoplasmic accumulation in senescent human diploid fibroblasts. The consequence of reduced protein expression and altered cellular localization may account for the alterations in gene expression observed during senescence. There is limited information for gene targets of hnRNP A1 as well as its in vivo function. In these studies, we performed RNA co-immunoprecipitation experiments using hnRNP A1 as the target protein to identify potential mRNA species in ribonucleoprotein (RNP) complexes. Using this approach, we identified the human double minute 2 (HDM2) mRNA as a binding target for hnRNP A1 in young and senescent human diploid fibroblasts cells. It was also observed that alterations of hnRNP A1 expression modulate HDM2 mRNA levels in young IMR-90 cells. We also demonstrated that the levels of HDM2 mRNA increased with the downregulation of hnRNP A1 and decrease with the overexpression of hnRNP A1. Although we did not observe a significant decrease in HDM2 protein level, a concomitant increase in p53 protein level was detected with the overexpression of hnRNP A1. Our studies also show that hnRNP A1 directly interacts with HDM2 mRNA at a region corresponding to its 3′ UTR (untranslated region of a gene). The results from this study demonstrate that hnRNP A1 has a novel role in participating in the regulation of HDM2 gene expression.",book:{id:"10935",title:"Mechanisms and Management of Senescence",coverURL:"https://cdn.intechopen.com/books/images_new/10935.jpg"},signatures:"Heriberto Moran, Shanaz A. Ghandhi, Naoko Shimada and Karen Hubbard"},{id:"79295",title:"Genetic and Epigenetic Influences on Cutaneous Cellular Senescence",slug:"genetic-and-epigenetic-influences-on-cutaneous-cellular-senescence",totalDownloads:123,totalDimensionsCites:0,doi:"10.5772/intechopen.101152",abstract:"Skin is the largest human organ system, and its protective function is critical to survival. The epithelial, dermal, and subcutaneous compartments are heterogeneous mixtures of cell types, yet they all display age-related skin dysfunction through the accumulation of an altered phenotypic cellular state called senescence. Cellular senescence is triggered by complex and dynamic genetic and epigenetic processes. A senescence steady state is achieved in different cell types under various and overlapping conditions of chronological age, toxic injury, oxidative stress, replicative exhaustion, DNA damage, metabolic dysfunction, and chromosomal structural changes. These inputs lead to outputs of cell-cycle withdrawal and the appearance of a senescence-associated secretory phenotype, both of which accumulate as tissue pathology observed clinically in aged skin. This review details the influence of genetic and epigenetic factors that converge on normal cutaneous cellular processes to create the senescent state, thereby dictating the response of the skin to the forces of both intrinsic and extrinsic aging. From this work, it is clear that no single biomarker or process leads to senescence, but that it is a convergence of factors resulting in an overt aging phenotype.",book:{id:"10935",title:"Mechanisms and Management of Senescence",coverURL:"https://cdn.intechopen.com/books/images_new/10935.jpg"},signatures:"Tapash Jay Sarkar, Maiko Hermsmeier, Jessica L. Ross and G. 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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:"June 24th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:31,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:4,paginationItems:[{id:"10",title:"Animal Physiology",coverUrl:"https://cdn.intechopen.com/series_topics/covers/10.jpg",isOpenForSubmission:!0,editor:{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. Dr. Rutland has also written popular science books for the public. https://orcid.org/0000-0002-2009-4898. www.nottingham.ac.uk/vet/people/catrin.rutland",institutionString:null,institution:{name:"University of Nottingham",institutionURL:null,country:{name:"United Kingdom"}}},editorTwo:null,editorThree:null},{id:"11",title:"Cell Physiology",coverUrl:"https://cdn.intechopen.com/series_topics/covers/11.jpg",isOpenForSubmission:!0,editor:{id:"133493",title:"Prof.",name:"Angel",middleName:null,surname:"Catala",slug:"angel-catala",fullName:"Angel Catala",profilePictureURL:"https://mts.intechopen.com/storage/users/133493/images/3091_n.jpg",biography:"Prof. Dr. Angel Catalá \r\nShort Biography Angel Catalá was born in Rodeo (San Juan, Argentina). He studied \r\nchemistry at the Universidad Nacional de La Plata, Argentina, where received aPh.D. degree in chemistry (Biological Branch) in 1965. From\r\n1964 to 1974, he worked as Assistant in Biochemistry at the School of MedicineUniversidad Nacional de La Plata, Argentina. From 1974 to 1976, he was a Fellowof the National Institutes of Health (NIH) at the University of Connecticut, Health Center, USA. From 1985 to 2004, he served as a Full Professor oBiochemistry at the Universidad Nacional de La Plata, Argentina. He is Member ofthe National Research Council (CONICET), Argentina, and Argentine Society foBiochemistry and Molecular Biology (SAIB). His laboratory has been interested for manyears in the lipid peroxidation of biological membranes from various tissues and different species. Professor Catalá has directed twelve doctoral theses, publishedover 100 papers in peer reviewed journals, several chapters in books andtwelve edited books. Angel Catalá received awards at the 40th InternationaConference Biochemistry of Lipids 1999: Dijon (France). W inner of the Bimbo PanAmerican Nutrition, Food Science and Technology Award 2006 and 2012, South AmericaHuman Nutrition, Professional Category. 2006 award in pharmacology, Bernardo\r\nHoussay, in recognition of his meritorious works of research. Angel Catalá belongto the Editorial Board of Journal of lipids, International Review of Biophysical ChemistryFrontiers in Membrane Physiology and Biophysics, World Journal oExperimental Medicine and Biochemistry Research International, W orld Journal oBiological Chemistry, Oxidative Medicine and Cellular Longevity, Diabetes and thePancreas, International Journal of Chronic Diseases & Therapy, International Journal oNutrition, Co-Editor of The Open Biology Journal.",institutionString:null,institution:{name:"National University of La Plata",institutionURL:null,country:{name:"Argentina"}}},editorTwo:null,editorThree:null},{id:"12",title:"Human Physiology",coverUrl:"https://cdn.intechopen.com/series_topics/covers/12.jpg",isOpenForSubmission:!0,editor:{id:"195829",title:"Prof.",name:"Kunihiro",middleName:null,surname:"Sakuma",slug:"kunihiro-sakuma",fullName:"Kunihiro Sakuma",profilePictureURL:"https://mts.intechopen.com/storage/users/195829/images/system/195829.jpg",biography:"Professor Kunihiro Sakuma, Ph.D., currently works in the Institute for Liberal Arts at the Tokyo Institute of Technology. He is a physiologist working in the field of skeletal muscle. He was awarded his sports science diploma in 1995 by the University of Tsukuba and began his scientific work at the Department of Physiology, Aichi Human Service Center, focusing on the molecular mechanism of congenital muscular dystrophy and normal muscle regeneration. His interest later turned to the molecular mechanism and attenuating strategy of sarcopenia (age-related muscle atrophy). His opinion is to attenuate sarcopenia by improving autophagic defects using nutrient- and pharmaceutical-based treatments.",institutionString:null,institution:{name:"Tokyo Institute of Technology",institutionURL:null,country:{name:"Japan"}}},editorTwo:{id:"331519",title:"Dr.",name:"Kotomi",middleName:null,surname:"Sakai",slug:"kotomi-sakai",fullName:"Kotomi Sakai",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000031QtFXQA0/Profile_Picture_1637053227318",biography:"Senior researcher Kotomi Sakai, Ph.D., MPH, works at the Research Organization of Science and Technology in Ritsumeikan University. She is a researcher in the geriatric rehabilitation and public health field. She received Ph.D. from Nihon University and MPH from St.Luke’s International University. Her main research interest is sarcopenia in older adults, especially its association with nutritional status. Additionally, to understand how to maintain and improve physical function in older adults, to conduct studies about the mechanism of sarcopenia and determine when possible interventions are needed.",institutionString:null,institution:{name:"Ritsumeikan University",institutionURL:null,country:{name:"Japan"}}},editorThree:null},{id:"13",title:"Plant Physiology",coverUrl:"https://cdn.intechopen.com/series_topics/covers/13.jpg",isOpenForSubmission:!0,editor:{id:"332229",title:"Prof.",name:"Jen-Tsung",middleName:null,surname:"Chen",slug:"jen-tsung-chen",fullName:"Jen-Tsung Chen",profilePictureURL:"https://mts.intechopen.com/storage/users/332229/images/system/332229.png",biography:"Dr. Jen-Tsung Chen is currently a professor at the National University of Kaohsiung, Taiwan. He teaches cell biology, genomics, proteomics, medicinal plant biotechnology, and plant tissue culture. Dr. Chen\\'s research interests include bioactive compounds, chromatography techniques, in vitro culture, medicinal plants, phytochemicals, and plant biotechnology. He has published more than ninety scientific papers and serves as an editorial board member for Plant Methods, Biomolecules, and International Journal of Molecular Sciences.",institutionString:"National University of Kaohsiung",institution:{name:"National University of Kaohsiung",institutionURL:null,country:{name:"Taiwan"}}},editorTwo:null,editorThree:null}]},overviewPageOFChapters:{paginationCount:45,paginationItems:[{id:"82135",title:"Carotenoids in Cassava (Manihot esculenta Crantz)",doi:"10.5772/intechopen.105210",signatures:"Lovina I. Udoh, Josephine U. Agogbua, Eberechi R. Keyagha and Itorobong I. Nkanga",slug:"carotenoids-in-cassava-manihot-esculenta-crantz",totalDownloads:3,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Carotenoids - New Perspectives and Application",coverURL:"https://cdn.intechopen.com/books/images_new/10836.jpg",subseries:{id:"13",title:"Plant Physiology"}}},{id:"82112",title:"Comparative Senescence and Lifespan",doi:"10.5772/intechopen.105137",signatures:"Hassan M. Heshmati",slug:"comparative-senescence-and-lifespan",totalDownloads:7,totalCrossrefCites:0,totalDimensionsCites:0,authors:[{name:"Hassan M.",surname:"Heshmati"}],book:{title:"Mechanisms and Management of Senescence",coverURL:"https://cdn.intechopen.com/books/images_new/10935.jpg",subseries:{id:"11",title:"Cell Physiology"}}},{id:"81796",title:"Apoptosis-Related Diseases and Peroxisomes",doi:"10.5772/intechopen.105052",signatures:"Meimei Wang, Yakun Liu, Ni Chen, Juan Wang and Ye Zhao",slug:"apoptosis-related-diseases-and-peroxisomes",totalDownloads:11,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"The Metabolic Role of Peroxisome in Health and Disease",coverURL:"https://cdn.intechopen.com/books/images_new/10837.jpg",subseries:{id:"11",title:"Cell Physiology"}}},{id:"81723",title:"Peroxisomal Modulation as Therapeutic Alternative for Tackling Multiple Cancers",doi:"10.5772/intechopen.104873",signatures:"Shazia Usmani, Shadma Wahab, Abdul Hafeez, Shabana Khatoon and Syed Misbahul Hasan",slug:"peroxisomal-modulation-as-therapeutic-alternative-for-tackling-multiple-cancers",totalDownloads:4,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"The Metabolic Role of Peroxisome in Health and Disease",coverURL:"https://cdn.intechopen.com/books/images_new/10837.jpg",subseries:{id:"11",title:"Cell Physiology"}}}]},overviewPagePublishedBooks:{paginationCount:11,paginationItems:[{type:"book",id:"7264",title:"Calcium and Signal Transduction",subtitle:null,coverURL:"https://cdn.intechopen.com/books/images_new/7264.jpg",slug:"calcium-and-signal-transduction",publishedDate:"October 24th 2018",editedByType:"Edited by",bookSignature:"John N. Buchholz and Erik J. Behringer",hash:"e373a3d1123dbd45fddf75d90e3e7c38",volumeInSeries:1,fullTitle:"Calcium and Signal Transduction",editors:[{id:"89438",title:"Dr.",name:"John N.",middleName:null,surname:"Buchholz",slug:"john-n.-buchholz",fullName:"John N. Buchholz",profilePictureURL:"https://mts.intechopen.com/storage/users/89438/images/6463_n.jpg",biography:"Full Professor and Vice Chair, Division of Pharmacology, Loma Linda University, School of Medicine. He received his B.S. Degree in Biology at La Sierra University, Riverside California (1980) and a PhD in Pharmacology from Loma Linda University School of Medicine (1988). Post-Doctoral Fellow at University of California, Irvine, College of Medicine 1989-1992 with a focus on autonomic nerve function in blood vessels and the impact of aging on the function of these nerves and overall blood vessel function. Twenty years of research funding and served on NIH R01 review panels, Editor-In-Chief of Edorium Journal of Aging Research. 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She is also Invisalign certified. She’s working as a Senior Lecturer in the Department of Orthodontics, SRM Dental College since November 2019. She is actively involved in teaching orthodontics to the undergraduates and the postgraduates. Her clinical research topics include new orthodontic brackets, fixed appliances and TADs. She’s published 4 articles in well renowned indexed journals and has a published patency of her own. Her private practice is currently limited to orthodontics and works as a consultant in various clinics.",institutionString:null,institution:{name:"SRM Dental College",country:{name:"India"}}},{id:"323731",title:"Prof.",name:"Deepak M.",middleName:"Macchindra",surname:"Vikhe",slug:"deepak-m.-vikhe",fullName:"Deepak M. Vikhe",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/323731/images/13613_n.jpg",biography:"Dr Deepak M.Vikhe .\n\n\t\n\tDr Deepak M.Vikhe , completed his Masters & PhD in Prosthodontics from Rural Dental College, Loni securing third rank in the Pravara Institute of Medical Sciences Deemed University. He was awarded Dr.G.C.DAS Memorial Award for Research on Implants at 39th IPS conference Dubai (U A E).He has two patents under his name. He has received Dr.Saraswati medal award for best research for implant study in 2017.He has received Fully funded scholarship to Spain ,university of Santiago de Compostela. He has completed fellowship in Implantlogy from Noble Biocare. \nHe has attended various conferences and CDE programmes and has national publications to his credit. His field of interest is in Implant supported prosthesis. Presently he is working as a associate professor in the Dept of Prosthodontics, Rural Dental College, Loni and maintains a successful private practice specialising in Implantology at Rahata.\n\nEmail: drdeepak_mvikhe@yahoo.com..................",institutionString:null,institution:{name:"Pravara Institute of Medical Sciences",country:{name:"India"}}},{id:"204110",title:"Dr.",name:"Ahmed A.",middleName:null,surname:"Madfa",slug:"ahmed-a.-madfa",fullName:"Ahmed A. Madfa",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/204110/images/system/204110.jpg",biography:"Dr. Madfa is currently Associate Professor of Endodontics at Thamar University and a visiting lecturer at Sana'a University and University of Sciences and Technology. He has more than 6 years of experience in teaching. His research interests include root canal morphology, functionally graded concept, dental biomaterials, epidemiology and dental education, biomimetic restoration, finite element analysis and endodontic regeneration. Dr. Madfa has numerous international publications, full articles, two patents, a book and a book chapter. Furthermore, he won 14 international scientific awards. Furthermore, he is involved in many academic activities ranging from editorial board member, reviewer for many international journals and postgraduate students' supervisor. Besides, I deliver many courses and training workshops at various scientific events. Dr. Madfa also regularly attends international conferences and holds administrative positions (Deputy Dean of the Faculty for Students’ & Academic Affairs and Deputy Head of Research Unit).",institutionString:"Thamar University",institution:null},{id:"210472",title:"Dr.",name:"Nermin",middleName:"Mohammed Ahmed",surname:"Yussif",slug:"nermin-yussif",fullName:"Nermin Yussif",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/210472/images/system/210472.jpg",biography:"Dr. Nermin Mohammed Ahmed Yussif is working at the Faculty of dentistry, University for October university for modern sciences and arts (MSA). Her areas of expertise include: periodontology, dental laserology, oral implantology, periodontal plastic surgeries, oral mesotherapy, nutrition, dental pharmacology. She is an editor and reviewer in numerous international journals.",institutionString:"MSA University",institution:null},{id:"204606",title:"Dr.",name:"Serdar",middleName:null,surname:"Gözler",slug:"serdar-gozler",fullName:"Serdar Gözler",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/204606/images/system/204606.jpeg",biography:"Dr. Serdar Gözler has completed his undergraduate studies at the Marmara University Faculty of Dentistry in 1978, followed by an assistantship in the Prosthesis Department of Dicle University Faculty of Dentistry. Starting his PhD work on non-resilient overdentures with Assoc. Prof. Hüsnü Yavuzyılmaz, he continued his studies with Prof. Dr. Gürbüz Öztürk of Istanbul University Faculty of Dentistry Department of Prosthodontics, this time on Gnatology. He attended training programs on occlusion, neurology, neurophysiology, EMG, radiology and biostatistics. In 1982, he presented his PhD thesis \\Gerber and Lauritzen Occlusion Analysis Techniques: Diagnosis Values,\\ at Istanbul University School of Dentistry, Department of Prosthodontics. As he was also working with Prof. Senih Çalıkkocaoğlu on The Physiology of Chewing at the same time, Gözler has written a chapter in Çalıkkocaoğlu\\'s book \\Complete Prostheses\\ entitled \\The Place of Neuromuscular Mechanism in Prosthetic Dentistry.\\ The book was published five times since by the Istanbul University Publications. Having presented in various conferences about occlusion analysis until 1998, Dr. Gözler has also decided to use the T-Scan II occlusion analysis method. Having been personally trained by Dr. Robert Kerstein on this method, Dr. Gözler has been lecturing on the T-Scan Occlusion Analysis Method in conferences both in Turkey and abroad. Dr. Gözler has various articles and presentations on Digital Occlusion Analysis methods. He is now Head of the TMD Clinic at Prosthodontic Department of Faculty of Dentistry , Istanbul Aydın University , Turkey.",institutionString:"Istanbul Aydin University",institution:{name:"Istanbul Aydın University",country:{name:"Turkey"}}},{id:"240870",title:"Ph.D.",name:"Alaa Eddin Omar",middleName:null,surname:"Al Ostwani",slug:"alaa-eddin-omar-al-ostwani",fullName:"Alaa Eddin Omar Al Ostwani",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/240870/images/system/240870.jpeg",biography:"Dr. Al Ostwani Alaa Eddin Omar received his Master in dentistry from Damascus University in 2010, and his Ph.D. in Pediatric Dentistry from Damascus University in 2014. Dr. Al Ostwani is an assistant professor and faculty member at IUST University since 2014. \nDuring his academic experience, he has received several awards including the scientific research award from the Union of Arab Universities, the Syrian gold medal and the international gold medal for invention and creativity. Dr. Al Ostwani is a Member of the International Association of Dental Traumatology and the Syrian Society for Research and Preventive Dentistry since 2017. He is also a Member of the Reviewer Board of International Journal of Dental Medicine (IJDM), and the Indian Journal of Conservative and Endodontics since 2016.",institutionString:"International University for Science and Technology.",institution:{name:"Islamic University of Science and Technology",country:{name:"India"}}},{id:"42847",title:"Dr.",name:"Belma",middleName:null,surname:"Işik Aslan",slug:"belma-isik-aslan",fullName:"Belma Işik Aslan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/42847/images/system/42847.jpg",biography:"Dr. Belma IşIk Aslan was born in 1976 in Ankara-TURKEY. After graduating from TED Ankara College in 1994, she attended to Gazi University, Faculty of Dentistry in Ankara. She completed her PhD in orthodontic education at Gazi University between 1999-2005. Dr. Işık Aslan stayed at the Providence Hospital Craniofacial Institude and Reconstructive Surgery in Michigan, USA for three months as an observer. She worked as a specialist doctor at Gazi University, Dentistry Faculty, Department of Orthodontics between 2005-2014. She was appointed as associate professor in January, 2014 and as professor in 2021. Dr. Işık Aslan still works as an instructor at the same faculty. She has published a total of 35 articles, 10 book chapters, 39 conference proceedings both internationally and nationally. Also she was the academic editor of the international book 'Current Advances in Orthodontics'. She is a member of the Turkish Orthodontic Society and Turkish Cleft Lip and Palate Society. She is married and has 2 children. Her knowledge of English is at an advanced level.",institutionString:"Gazi University Dentistry Faculty Department of Orthodontics",institution:null},{id:"178412",title:"Associate Prof.",name:"Guhan",middleName:null,surname:"Dergin",slug:"guhan-dergin",fullName:"Guhan Dergin",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/178412/images/6954_n.jpg",biography:"Assoc. Prof. Dr. Gühan Dergin was born in 1973 in Izmit. He graduated from Marmara University Faculty of Dentistry in 1999. He completed his specialty of OMFS surgery in Marmara University Faculty of Dentistry and obtained his PhD degree in 2006. In 2005, he was invited as a visiting doctor in the Oral and Maxillofacial Surgery Department of the University of North Carolina, USA, where he went on a scholarship. Dr. Dergin still continues his academic career as an associate professor in Marmara University Faculty of Dentistry. He has many articles in international and national scientific journals and chapters in books.",institutionString:null,institution:{name:"Marmara University",country:{name:"Turkey"}}},{id:"178414",title:"Prof.",name:"Yusuf",middleName:null,surname:"Emes",slug:"yusuf-emes",fullName:"Yusuf Emes",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/178414/images/6953_n.jpg",biography:"Born in Istanbul in 1974, Dr. Emes graduated from Istanbul University Faculty of Dentistry in 1997 and completed his PhD degree in Istanbul University faculty of Dentistry Department of Oral and Maxillofacial Surgery in 2005. He has papers published in international and national scientific journals, including research articles on implantology, oroantral fistulas, odontogenic cysts, and temporomandibular disorders. Dr. Emes is currently working as a full-time academic staff in Istanbul University faculty of Dentistry Department of Oral and Maxillofacial Surgery.",institutionString:null,institution:{name:"Istanbul University",country:{name:"Turkey"}}},{id:"192229",title:"Ph.D.",name:"Ana Luiza",middleName:null,surname:"De Carvalho Felippini",slug:"ana-luiza-de-carvalho-felippini",fullName:"Ana Luiza De Carvalho Felippini",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/192229/images/system/192229.jpg",biography:null,institutionString:"University of São Paulo",institution:{name:"University of Sao Paulo",country:{name:"Brazil"}}},{id:"256851",title:"Prof.",name:"Ayşe",middleName:null,surname:"Gülşen",slug:"ayse-gulsen",fullName:"Ayşe Gülşen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/256851/images/9696_n.jpg",biography:"Dr. Ayşe Gülşen graduated in 1990 from Faculty of Dentistry, University of Ankara and did a postgraduate program at University of Gazi. \nShe worked as an observer and research assistant in Craniofacial Surgery Departments in New York, Providence Hospital in Michigan and Chang Gung Memorial Hospital in Taiwan. \nShe works as Craniofacial Orthodontist in Department of Aesthetic, Plastic and Reconstructive Surgery, Faculty of Medicine, University of Gazi, Ankara Turkey since 2004.",institutionString:"Univeristy of Gazi",institution:null},{id:"255366",title:"Prof.",name:"Tosun",middleName:null,surname:"Tosun",slug:"tosun-tosun",fullName:"Tosun Tosun",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/255366/images/7347_n.jpg",biography:"Graduated at the Faculty of Dentistry, University of Istanbul, Turkey in 1989;\nVisitor Assistant at the University of Padua, Italy and Branemark Osseointegration Center of Treviso, Italy between 1993-94;\nPhD thesis on oral implantology in University of Istanbul and was awarded the academic title “Dr.med.dent.”, 1997;\nHe was awarded the academic title “Doç.Dr.” (Associated Professor) in 2003;\nProficiency in Botulinum Toxin Applications, Reading-UK in 2009;\nMastership, RWTH Certificate in Laser Therapy in Dentistry, AALZ-Aachen University, Germany 2009-11;\nMaster of Science (MSc) in Laser Dentistry, University of Genoa, Italy 2013-14.\n\nDr.Tosun worked as Research Assistant in the Department of Oral Implantology, Faculty of Dentistry, University of Istanbul between 1990-2002. \nHe worked part-time as Consultant surgeon in Harvard Medical International Hospitals and John Hopkins Medicine, Istanbul between years 2007-09.\u2028He was contract Professor in the Department of Surgical and Diagnostic Sciences (DI.S.C.), Medical School, University of Genova, Italy between years 2011-16. \nSince 2015 he is visiting Professor at Medical School, University of Plovdiv, Bulgaria. \nCurrently he is Associated Prof.Dr. at the Dental School, Oral Surgery Dept., Istanbul Aydin University and since 2003 he works in his own private clinic in Istanbul, Turkey.\u2028\nDr.Tosun is reviewer in journal ‘Laser in Medical Sciences’, reviewer in journal ‘Folia Medica\\', a Fellow of the International Team for Implantology, Clinical Lecturer of DGZI German Association of Oral Implantology, Expert Lecturer of Laser&Health Academy, Country Representative of World Federation for Laser Dentistry, member of European Federation of Periodontology, member of Academy of Laser Dentistry. Dr.Tosun presents papers in international and national congresses and has scientific publications in international and national journals. He speaks english, spanish, italian and french.",institutionString:null,institution:{name:"Istanbul Aydın University",country:{name:"Turkey"}}},{id:"171887",title:"Prof.",name:"Zühre",middleName:null,surname:"Akarslan",slug:"zuhre-akarslan",fullName:"Zühre Akarslan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/171887/images/system/171887.jpg",biography:"Zühre Akarslan was born in 1977 in Cyprus. She graduated from Gazi University Faculty of Dentistry, Ankara, Turkey in 2000. \r\nLater she received her Ph.D. degree from the Oral Diagnosis and Radiology Department; which was recently renamed as Oral and Dentomaxillofacial Radiology, from the same university. \r\nShe is working as a full-time Associate Professor and is a lecturer and an academic researcher. \r\nHer expertise areas are dental caries, cancer, dental fear and anxiety, gag reflex in dentistry, oral medicine, and dentomaxillofacial radiology.",institutionString:"Gazi University",institution:{name:"Gazi University",country:{name:"Turkey"}}},{id:"256417",title:"Associate Prof.",name:"Sanaz",middleName:null,surname:"Sadry",slug:"sanaz-sadry",fullName:"Sanaz Sadry",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/256417/images/8106_n.jpg",biography:null,institutionString:null,institution:null},{id:"272237",title:"Dr.",name:"Pinar",middleName:"Kiymet",surname:"Karataban",slug:"pinar-karataban",fullName:"Pinar Karataban",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/272237/images/8911_n.png",biography:"Assist.Prof.Dr.Pınar Kıymet Karataban, DDS PhD \n\nDr.Pınar Kıymet Karataban was born in Istanbul in 1975. After her graduation from Marmara University Faculty of Dentistry in 1998 she started her PhD in Paediatric Dentistry focused on children with special needs; mainly children with Cerebral Palsy. She finished her pHD thesis entitled \\'Investigation of occlusion via cast analysis and evaluation of dental caries prevalance, periodontal status and muscle dysfunctions in children with cerebral palsy” in 2008. She got her Assist. Proffessor degree in Istanbul Aydın University Paediatric Dentistry Department in 2015-2018. ın 2019 she started her new career in Bahcesehir University, Istanbul as Head of Department of Pediatric Dentistry. In 2020 she was accepted to BAU International University, Batumi as Professor of Pediatric Dentistry. She’s a lecturer in the same university meanwhile working part-time in private practice in Ege Dental Studio (https://www.egedisklinigi.com/) a multidisciplinary dental clinic in Istanbul. Her main interests are paleodontology, ancient and contemporary dentistry, oral microbiology, cerebral palsy and special care dentistry. She has national and international publications, scientific reports and is a member of IAPO (International Association for Paleodontology), IADH (International Association of Disability and Oral Health) and EAPD (European Association of Pediatric Dentistry).",institutionString:null,institution:null},{id:"202198",title:"Dr.",name:"Buket",middleName:null,surname:"Aybar",slug:"buket-aybar",fullName:"Buket Aybar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/202198/images/6955_n.jpg",biography:"Buket Aybar, DDS, PhD, was born in 1971. She graduated from Istanbul University, Faculty of Dentistry, in 1992 and completed her PhD degree on Oral and Maxillofacial Surgery in Istanbul University in 1997.\nDr. Aybar is currently a full-time professor in Istanbul University, Faculty of Dentistry Department of Oral and Maxillofacial Surgery. She has teaching responsibilities in graduate and postgraduate programs. Her clinical practice includes mainly dentoalveolar surgery.\nHer topics of interest are biomaterials science and cell culture studies. She has many articles in international and national scientific journals and chapters in books; she also has participated in several scientific projects supported by Istanbul University Research fund.",institutionString:null,institution:null},{id:"260116",title:"Dr.",name:"Mehmet",middleName:null,surname:"Yaltirik",slug:"mehmet-yaltirik",fullName:"Mehmet Yaltirik",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/260116/images/7413_n.jpg",biography:"Birth Date 25.09.1965\r\nBirth Place Adana- Turkey\r\nSex Male\r\nMarrial Status Bachelor\r\nDriving License Acquired\r\nMother Tongue Turkish\r\n\r\nAddress:\r\nWork:University of Istanbul,Faculty of Dentistry, Department of Oral Surgery and Oral Medicine 34093 Capa,Istanbul- TURKIYE",institutionString:null,institution:null},{id:"172009",title:"Dr.",name:"Fatma Deniz",middleName:null,surname:"Uzuner",slug:"fatma-deniz-uzuner",fullName:"Fatma Deniz Uzuner",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/172009/images/7122_n.jpg",biography:"Dr. Deniz Uzuner was born in 1969 in Kocaeli-TURKEY. After graduating from TED Ankara College in 1986, she attended the Hacettepe University, Faculty of Dentistry in Ankara. \nIn 1993 she attended the Gazi University, Faculty of Dentistry, Department of Orthodontics for her PhD education. After finishing the PhD education, she worked as orthodontist in Ankara Dental Hospital under the Turkish Government, Ministry of Health and in a special Orthodontic Clinic till 2011. Between 2011 and 2016, Dr. Deniz Uzuner worked as a specialist in the Department of Orthodontics, Faculty of Dentistry, Gazi University in Ankara/Turkey. In 2016, she was appointed associate professor. Dr. Deniz Uzuner has authored 23 Journal Papers, 3 Book Chapters and has had 39 oral/poster presentations. She is a member of the Turkish Orthodontic Society. Her knowledge of English is at an advanced level.",institutionString:null,institution:null},{id:"332914",title:"Dr.",name:"Muhammad Saad",middleName:null,surname:"Shaikh",slug:"muhammad-saad-shaikh",fullName:"Muhammad Saad Shaikh",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Jinnah Sindh Medical University",country:{name:"Pakistan"}}},{id:"315775",title:"Dr.",name:"Feng",middleName:null,surname:"Luo",slug:"feng-luo",fullName:"Feng Luo",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Sichuan University",country:{name:"China"}}},{id:"423519",title:"Dr.",name:"Sizakele",middleName:null,surname:"Ngwenya",slug:"sizakele-ngwenya",fullName:"Sizakele Ngwenya",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of the Witwatersrand",country:{name:"South Africa"}}},{id:"419270",title:"Dr.",name:"Ann",middleName:null,surname:"Chianchitlert",slug:"ann-chianchitlert",fullName:"Ann Chianchitlert",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Walailak University",country:{name:"Thailand"}}},{id:"419271",title:"Dr.",name:"Diane",middleName:null,surname:"Selvido",slug:"diane-selvido",fullName:"Diane Selvido",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Walailak University",country:{name:"Thailand"}}},{id:"419272",title:"Dr.",name:"Irin",middleName:null,surname:"Sirisoontorn",slug:"irin-sirisoontorn",fullName:"Irin Sirisoontorn",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Walailak University",country:{name:"Thailand"}}},{id:"355660",title:"Dr.",name:"Anitha",middleName:null,surname:"Mani",slug:"anitha-mani",fullName:"Anitha Mani",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"SRM Dental College",country:{name:"India"}}},{id:"355612",title:"Dr.",name:"Janani",middleName:null,surname:"Karthikeyan",slug:"janani-karthikeyan",fullName:"Janani Karthikeyan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"SRM Dental College",country:{name:"India"}}},{id:"334400",title:"Dr.",name:"Suvetha",middleName:null,surname:"Siva",slug:"suvetha-siva",fullName:"Suvetha Siva",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"SRM Dental College",country:{name:"India"}}},{id:"334239",title:"Prof.",name:"Leung",middleName:null,surname:"Wai Keung",slug:"leung-wai-keung",fullName:"Leung Wai Keung",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Hong Kong",country:{name:"China"}}}]}},subseries:{item:{id:"20",type:"subseries",title:"Animal Nutrition",keywords:"Sustainable Animal Diets, Carbon Footprint, Meta Analyses",scope:"An essential part of animal production is nutrition. Animals need to receive a properly balanced diet. One of the new challenges we are now faced with is sustainable animal diets (STAND) that involve the 3 P’s (People, Planet, and Profitability). We must develop animal feed that does not compete with human food, use antibiotics, and explore new growth promoters options, such as plant extracts or compounds that promote feed efficiency (e.g., monensin, oils, enzymes, probiotics). These new feed options must also be environmentally friendly, reducing the Carbon footprint, CH4, N, and P emissions to the environment, with an adequate formulation of nutrients.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/20.jpg",hasOnlineFirst:!0,hasPublishedBooks:!0,annualVolume:11416,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. 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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"}}},subseries:[{id:"14",title:"Cell and Molecular Biology",keywords:"Omics (Transcriptomics; Proteomics; Metabolomics), Molecular Biology, Cell Biology, Signal Transduction and Regulation, Cell Growth and Differentiation, Apoptosis, Necroptosis, Ferroptosis, Autophagy, Cell Cycle, Macromolecules and Complexes, Gene Expression",scope:"The Cell and Molecular Biology topic within the IntechOpen Biochemistry Series aims to rapidly publish contributions on all aspects of cell and molecular biology, including aspects related to biochemical and genetic research (not only in humans but all living beings). We encourage the submission of manuscripts that provide novel and mechanistic insights that report significant advances in the fields. Topics include, but are not limited to: Advanced techniques of cellular and molecular biology (Molecular methodologies, imaging techniques, and bioinformatics); Biological activities at the molecular level; Biological processes of cell functions, cell division, senescence, maintenance, and cell death; Biomolecules interactions; Cancer; Cell biology; Chemical biology; Computational biology; Cytochemistry; Developmental biology; Disease mechanisms and therapeutics; DNA, and RNA metabolism; Gene functions, genetics, and genomics; Genetics; Immunology; Medical microbiology; Molecular biology; Molecular genetics; Molecular processes of cell and organelle dynamics; Neuroscience; Protein biosynthesis, degradation, and functions; Regulation of molecular interactions in a cell; Signalling networks and system biology; Structural biology; Virology and microbiology.",annualVolume:11410,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/14.jpg",editor:{id:"165627",title:"Dr.",name:"Rosa María",middleName:null,surname:"Martínez-Espinosa",fullName:"Rosa María Martínez-Espinosa",profilePictureURL:"https://mts.intechopen.com/storage/users/165627/images/system/165627.jpeg",institutionString:null,institution:{name:"University of Alicante",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"79367",title:"Dr.",name:"Ana Isabel",middleName:null,surname:"Flores",fullName:"Ana Isabel Flores",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRpIOQA0/Profile_Picture_1632418099564",institutionString:null,institution:{name:"Hospital Universitario 12 De Octubre",institutionURL:null,country:{name:"Spain"}}},{id:"328234",title:"Ph.D.",name:"Christian",middleName:null,surname:"Palavecino",fullName:"Christian Palavecino",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000030DhEhQAK/Profile_Picture_1628835318625",institutionString:null,institution:{name:"Central University of Chile",institutionURL:null,country:{name:"Chile"}}},{id:"186585",title:"Dr.",name:"Francisco Javier",middleName:null,surname:"Martin-Romero",fullName:"Francisco Javier Martin-Romero",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSB3HQAW/Profile_Picture_1631258137641",institutionString:null,institution:{name:"University of Extremadura",institutionURL:null,country:{name:"Spain"}}}]},{id:"15",title:"Chemical Biology",keywords:"Phenolic Compounds, Essential Oils, Modification of Biomolecules, Glycobiology, Combinatorial Chemistry, Therapeutic peptides, Enzyme Inhibitors",scope:"Chemical biology spans the fields of chemistry and biology involving the application of biological and chemical molecules and techniques. In recent years, the application of chemistry to biological molecules has gained significant interest in medicinal and pharmacological studies. This topic will be devoted to understanding the interplay between biomolecules and chemical compounds, their structure and function, and their potential applications in related fields. Being a part of the biochemistry discipline, the ideas and concepts that have emerged from Chemical Biology have affected other related areas. This topic will closely deal with all emerging trends in this discipline.",annualVolume:11411,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/15.jpg",editor:{id:"441442",title:"Dr.",name:"Şükrü",middleName:null,surname:"Beydemir",fullName:"Şükrü Beydemir",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003GsUoIQAV/Profile_Picture_1634557147521",institutionString:null,institution:{name:"Anadolu University",institutionURL:null,country:{name:"Turkey"}}},editorTwo:{id:"13652",title:"Prof.",name:"Deniz",middleName:null,surname:"Ekinci",fullName:"Deniz Ekinci",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYLT1QAO/Profile_Picture_1634557223079",institutionString:null,institution:{name:"Ondokuz Mayıs University",institutionURL:null,country:{name:"Turkey"}}},editorThree:null,editorialBoard:[{id:"241413",title:"Dr.",name:"Azhar",middleName:null,surname:"Rasul",fullName:"Azhar Rasul",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRT1oQAG/Profile_Picture_1635251978933",institutionString:null,institution:{name:"Government College University, Faisalabad",institutionURL:null,country:{name:"Pakistan"}}},{id:"178316",title:"Ph.D.",name:"Sergey",middleName:null,surname:"Sedykh",fullName:"Sergey Sedykh",profilePictureURL:"https://mts.intechopen.com/storage/users/178316/images/system/178316.jfif",institutionString:null,institution:{name:"Novosibirsk State University",institutionURL:null,country:{name:"Russia"}}}]},{id:"17",title:"Metabolism",keywords:"Biomolecules Metabolism, Energy Metabolism, Metabolic Pathways, Key Metabolic Enzymes, Metabolic Adaptation",scope:"Metabolism is frequently defined in biochemistry textbooks as the overall process that allows living systems to acquire and use the free energy they need for their vital functions or the chemical processes that occur within a living organism to maintain life. Behind these definitions are hidden all the aspects of normal and pathological functioning of all processes that the topic ‘Metabolism’ will cover within the Biochemistry Series. Thus all studies on metabolism will be considered for publication.",annualVolume:11413,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/17.jpg",editor:{id:"138626",title:"Dr.",name:"Yannis",middleName:null,surname:"Karamanos",fullName:"Yannis Karamanos",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002g6Jv2QAE/Profile_Picture_1629356660984",institutionString:null,institution:{name:"Artois University",institutionURL:null,country:{name:"France"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"243049",title:"Dr.",name:"Anca",middleName:null,surname:"Pantea Stoian",fullName:"Anca Pantea Stoian",profilePictureURL:"https://mts.intechopen.com/storage/users/243049/images/system/243049.jpg",institutionString:null,institution:{name:"Carol Davila University of Medicine and Pharmacy",institutionURL:null,country:{name:"Romania"}}},{id:"203824",title:"Dr.",name:"Attilio",middleName:null,surname:"Rigotti",fullName:"Attilio Rigotti",profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institutionString:null,institution:{name:"Pontifical Catholic University of Chile",institutionURL:null,country:{name:"Chile"}}},{id:"300470",title:"Dr.",name:"Yanfei (Jacob)",middleName:null,surname:"Qi",fullName:"Yanfei (Jacob) Qi",profilePictureURL:"https://mts.intechopen.com/storage/users/300470/images/system/300470.jpg",institutionString:null,institution:{name:"Centenary Institute of Cancer Medicine and Cell Biology",institutionURL:null,country:{name:"Australia"}}}]},{id:"18",title:"Proteomics",keywords:"Mono- and Two-Dimensional Gel Electrophoresis (1-and 2-DE), Liquid Chromatography (LC), Mass Spectrometry/Tandem Mass Spectrometry (MS; MS/MS), Proteins",scope:"With the recognition that the human genome cannot provide answers to the etiology of a disorder, changes in the proteins expressed by a genome became a focus in research. Thus proteomics, an area of research that detects all protein forms expressed in an organism, including splice isoforms and post-translational modifications, is more suitable than genomics for a comprehensive understanding of the biochemical processes that govern life. The most common proteomics applications are currently in the clinical field for the identification, in a variety of biological matrices, of biomarkers for diagnosis and therapeutic intervention of disorders. From the comparison of proteomic profiles of control and disease or different physiological states, which may emerge, changes in protein expression can provide new insights into the roles played by some proteins in human pathologies. Understanding how proteins function and interact with each other is another goal of proteomics that makes this approach even more intriguing. Specialized technology and expertise are required to assess the proteome of any biological sample. Currently, proteomics relies mainly on mass spectrometry (MS) combined with electrophoretic (1 or 2-DE-MS) and/or chromatographic techniques (LC-MS/MS). MS is an excellent tool that has gained popularity in proteomics because of its ability to gather a complex body of information such as cataloging protein expression, identifying protein modification sites, and defining protein interactions. The Proteomics topic aims to attract contributions on all aspects of MS-based proteomics that, by pushing the boundaries of MS capabilities, may address biological problems that have not been resolved yet.",annualVolume:11414,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/18.jpg",editor:{id:"200689",title:"Prof.",name:"Paolo",middleName:null,surname:"Iadarola",fullName:"Paolo Iadarola",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSCl8QAG/Profile_Picture_1623568118342",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorTwo:{id:"201414",title:"Dr.",name:"Simona",middleName:null,surname:"Viglio",fullName:"Simona Viglio",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRKDHQA4/Profile_Picture_1630402531487",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorThree:null,editorialBoard:[{id:"72288",title:"Dr.",name:"Arli Aditya",middleName:null,surname:"Parikesit",fullName:"Arli Aditya Parikesit",profilePictureURL:"https://mts.intechopen.com/storage/users/72288/images/system/72288.jpg",institutionString:null,institution:{name:"Indonesia International Institute for Life Sciences",institutionURL:null,country:{name:"Indonesia"}}},{id:"40928",title:"Dr.",name:"Cesar",middleName:null,surname:"Lopez-Camarillo",fullName:"Cesar Lopez-Camarillo",profilePictureURL:"https://mts.intechopen.com/storage/users/40928/images/3884_n.png",institutionString:null,institution:{name:"Universidad Autónoma de la Ciudad de México",institutionURL:null,country:{name:"Mexico"}}},{id:"81926",title:"Dr.",name:"Shymaa",middleName:null,surname:"Enany",fullName:"Shymaa Enany",profilePictureURL:"https://mts.intechopen.com/storage/users/81926/images/system/81926.png",institutionString:"Suez Canal University",institution:{name:"Suez Canal University",institutionURL:null,country:{name:"Egypt"}}}]}]}},libraryRecommendation:{success:null,errors:{},institutions:[]},route:{name:"profile.detail",path:"/profiles/338936",hash:"",query:{},params:{id:"338936"},fullPath:"/profiles/338936",meta:{},from:{name:null,path:"/",hash:"",query:{},params:{},fullPath:"/",meta:{}}}},function(){var e;(e=document.currentScript||document.scripts[document.scripts.length-1]).parentNode.removeChild(e)}()