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With the advancement of in vivo studies and clinical trials, the pathogenesis of neurodegenerative diseases has been better understood. However, gaps still need to be better elucidated, which justifies the publication of reviews that explore the mechanisms related to the development of these diseases. Studies show that vitamin E supplementation can protect neurons from the damage caused by oxidative stress, with a positive impact on the prevention and progression of neurodegenerative diseases. Thus, this review aims to summarize the scientific evidence of the effects of vitamin E supplementation on neuroprotection and on neurodegeneration markers in experimental models. A search for studies published between 2000 and 2023 was carried out in the PubMed, Web of Science, Virtual Health Library (BVS), and Embase databases, in which the effects of vitamin E in experimental models of neurodegeneration were investigated. A total of 5669 potentially eligible studies were identified. After excluding the duplicates, 5373 remained, of which 5253 were excluded after checking the titles, 90 articles after reading the abstracts, and 11 after fully reviewing the manuscripts, leaving 19 publications to be included in this review. Experiments with in vivo models of neurodegenerative diseases demonstrated that vitamin E supplementation significantly improved memory, cognition, learning, motor function, and brain markers associated with neuroregeneration and neuroprotection. Vitamin E supplementation reduced beta-amyloid (Aβ) deposition and toxicity in experimental models of Alzheimer’s disease. In addition, it decreased tau-protein hyperphosphorylation and increased superoxide dismutase and brain-derived neurotrophic factor (BDNF) levels in rodents, which seems to indicate the potential use of vitamin E in preventing and delaying the progress of degenerative lesions in the central nervous system.

The biomedical sciences have recently undergone revolutionary change, due to the ability to digitize and store large data sets. In neuroscience, the data sources include measurements of neural activity measured using electrode arrays, EEG and MEG, brain imaging data from PET, fMRI, and optical imaging methods. Analysis, visualization, and management of these time series data sets is a growing field of research that has become increasingly important both for experimentalists and theorists interested in brain function. The first part of the book contains a set of chapters which provide non-technical conceptual background to the subject. Salient features include the adoption of an active perspective of the nervous system, an emphasis on function, and a brief survey of different theoretical accounts in neuroscience. The second part is the longest in the book, and contains a refresher course in mathematics and statistics leading up to time series analysis techniques. The third part contains applications of data analysis techniques to the range of data sources indicated above, and the fourth part contains special topics.

Social network analysis is used widely in the social sciences to study interactions among people, groups, and organizations, yet until now there has been no book that shows behavioral biologists how to apply it to their work on animal populations.Exploring Animal Social Networksprovides a practical guide for researchers, undergraduates, and graduate students in ecology, evolutionary biology, animal behavior, and zoology. Existing methods for studying animal social structure focus either on one animal and its interactions or on the average properties of a whole population. This book enables researchers to probe animal social structure at all levels, from the individual to the population. No prior knowledge of network theory is assumed. The authors give a step-by-step introduction to the different procedures and offer ideas for designing studies, collecting data, and interpreting results. They examine some of today's most sophisticated statistical tools for social network analysis and show how they can be used to study social interactions in animals, including cetaceans, ungulates, primates, insects, and fish. Drawing from an array of techniques, the authors explore how network structures influence individual behavior and how this in turn influences, and is influenced by, behavior at the population level. Throughout, the authors use two software packages--UCINET and NETDRAW--to illustrate how these powerful analytical tools can be applied to different animal social organizations.

Autism spectrum disorder (ASD) is a group of human neurodevelopmental disorders with significant global prevalence. Deficits in social communication and interaction and repetitive, stereotyped patterns of behaviour characterise ASD. The aetiology of ASD is unclear, but several genetic and environmental risk factors, either alone or in combination, are implicated in its development. To date, the underlying pathogenic mechanisms of ASD remain incompletely understood due to its heterogeneity. To better understand the pathogenesis of ASD, various animal models have been developed. The use of animals in ASD research allows the exploration of the biological substrates of social behaviour, cognition, and reward sensitivity, which are key components of ASD symptoms. This review outlines the commonly employed animal models in ASD research and explores their applications and the associated challenges.

Our knowledge of reproductive biology has increased enormously in recent years on cellular, molecular, and genetic levels, leading to significant breakthroughs that have directly benefitted in vitro fertilization (IVF) and other assisted reproductive technologies (ART) in humans and animal systems. Animal Models and Human Reproduction presents a comprehensive reference that reflects the latest scientific research being done in human reproductive biology utilizing domestic animal models. Chapters on canine, equine, cow, pig, frog, and mouse models of reproduction reflect frontier research in placental biology, ovarian function and fertility, non-coding RNAs in gametogenesis, oocyte and embryo metabolism, fertilization, cryopreservation, signal transduction pathways, chromatin dynamics, epigenetics, reproductive aging, and inflammation. Chapters on non-human primate models also highlight recent advancements into such issues as human in vitro fertilization (IVF) and assisted reproductive technologies (ART). This book offers animal scientists, reproductive biology scientists, clinicians and practitioners, invaluable insights into a wide range of issues at the forefront of human reproductive health.

Leishmaniasis remains a major unmet medical need, with limited oral options and persistent constraints related to efficacy, tolerability, and treatment duration. We investigated 18-methoxycoronaridine (18-MC), an iboga-type indole alkaloid, as an oral candidate against integrating rodent and non-human primate efficacy, toxicology, and pharmacokinetics to support clinical translation. Antileishmanial activity was first assessed in BALB/c mice treated orally with 18-MC (20 mg/kg/day). Translational efficacy was evaluated in non-human primates receiving oral 18-MC at 30 or 90 mg/kg/day for 28 days. Safety was characterized through acute and repeated-dose toxicology to establish the no-observed-adverse-effect level (NOAEL), complemented by pharmacokinetic analyses. A 5-day oral regimen of 18-MC reduced murine tissue parasite burden (expressed as viable parasites per whole organ) by >99%. In , 18-MC produced an exposure-dependent reduction in lesion burden, achieving ∼98% inhibition at 90 mg/kg/day, with marked re-epithelialization and no persistent clinical abnormalities. Pharmacokinetic modeling demonstrated a steep exposure-response relationship (EC50 ≈ 209 ng⋅h/mL) and a therapeutic index of approximately 5.4. The NOAEL was 50 mg/kg/day across species. 18-MC demonstrates potent orally bioavailable antileishmanial activity with rodent-primate translational concordance and a safety profile compatible with first-in-human evaluation, supporting Phase I advancement with an estimated human equivalent dose of ∼16 mg/kg/day.

This book offers pathologists, toxicologists, other medical professionals, and students an introduction to the discipline and techniques of neuropathology – including chemical and environmental, biological, medical, and regulatory details important for performing an analysis of toxicant-induced neurodiseases. In addition to a section on fundamentals, the book provides detailed coverage of current practices (bioassays, molecular analysis, and nervous system pathology) and practical aspects (data interpretation, regulatory considerations, and tips for preparing reports).

The Arctic climate system is host to many processes which interact vertically over the tightly coupled atmosphere, sea ice and ocean. The coupled Atmosphere‐Ocean Single‐Column Model (AOSCM) allows to decouple local small‐scale and large‐scale processes to investigate the model performance in an idealized setting. Here, an observed Arctic warm air intrusion event is used to show how to identify model deficiencies using the AOSCM. The AOSCM allows us to effectively produce a large number of perturbation simulations, around 1,000, to map sensitivities of the model results due to changes in physical and model properties as well as to the large‐scale tendencies. The analysis of the summary diagnostics, that is, aggregated results from sensitivity experiments evaluated against modeled physical properties, such as surface energy budget and mean sea ice thickness, reveals sensitivities to the chosen parameters. Further, we discuss how the conclusions can be used to understand the behavior of the global host model. The simulations confirm that the horizontal advection of heat and moisture plays an important role for maintaining a low‐level cloud cover, as in earlier studies. The combined cloud layers increase the energy input to the surface, which in turn enhances the ongoing melt. The clouds present an additional sensitivity in terms of how they are represented but also their interaction with the large‐scale advection and the model time step. The methodology can be used for a variety of other regions, where the coupling to the ocean is important. Plain Language Summary A novel methodology to improve process descriptions and to facilitate model development in a global climate model is presented. It is based on a column taken from a global host model and used in combination with observations. The single column model extends from the bottom of the ocean to the top of the atmosphere. The location is chosen based on the observations, and a large set of sensitivity simulations is performed to explore numerous ways to improve the model. We chose to illustrate the methodology for an Arctic location in summer, where the presence of low clouds affects the melting sea ice. The advantages of a single column model are that it is computationally cheap and that vertical processes can be isolated from horizontal processes. About 1,000 model simulations are analyzed using different diagnostics that capture the impact of perturbations of selected model parameters on key physical processes. Key Points In this study we illustrate how the Atmosphere‐Ocean Single‐Column Model (AOSCM) can be set up and utilized to explore model sensitivity to various uncertain parameters We use observations from a warm air Arctic intrusion over melting sea ice to showcase how the AOSCM can be applied

Individual-based models are an exciting and widely used new tool for ecology. These computational models allow scientists to explore the mechanisms through which population and ecosystem ecology arises from how individuals interact with each other and their environment. This book provides the first in-depth treatment of individual-based modeling and its use to develop theoretical understanding of how ecological systems work, an approach the authors call \"individual-based ecology.? Grimm and Railsback start with a general primer on modeling: how to design models that are as simple as possible while still allowing specific problems to be solved, and how to move efficiently through a cycle of pattern-oriented model design, implementation, and analysis. Next, they address the problems of theory and conceptual framework for individual-based ecology: What is \"theory\"? That is, how do we develop reusable models of how system dynamics arise from characteristics of individuals? What conceptual framework do we use when the classical differential equation framework no longer applies? An extensive review illustrates the ecological problems that have been addressed with individual-based models. The authors then identify how the mechanics of building and using individual-based models differ from those of traditional science, and provide guidance on formulating, programming, and analyzing models. This book will be helpful to ecologists interested in modeling, and to other scientists interested in agent-based modeling.

AimsTo investigate the effect of succinic acid on the development of experimental autoimmune uveitis (EAU) and the underlying mechanism.MethodsSuccinic acid was administrated intraperitoneally to evaluate its effects on immune response and EAU in mice. Intraocular inflammation was evaluated by histopathological scoring. Frequencies of Th1/Th17 cells were measured by flow cytometry. Concentrations of IFN-γ/IL-17A, neutrophil elastase (NE) and myeloperoxidase (MPO) were determined by enzyme-linked immunosorbent test. Infiltration of neutrophils and generation of neutrophil extracellular traps (NETs) within the eye were assessed by immumofluorescence. NETs formation in extracellular matrix was visualised by laser scanning confocal microscopy. Succinate receptor (SUCNR1) antagonist was used to investigate its effect on the generation of NETs.ResultsIntraperitoneal injection of succinic acid exacerbated EAU severity as evidenced by severe histological changes in association with elevated frequencies of splenic Th1/Th17 cells, and upregulated levels of IFN-γ/IL-17A and NETs in plasma. In vitro experiments showed that succinic acid could promote the generation of NETs by neutrophils as shown by increased expression of NE and MPO.NETs could increase the frequencies of Th1/Th17 cells in CD4+ T cells and their expression of IFN-γ/IL-17A. In the experiment of receptor antagonism, the upregulatory effect of succinic acid on NETs could be significantly blocked by SUCNR1 antagonist.ConclusionsSuccinic acid could worsen EAU induced by IRBP in mice. This effect was possibly mediated by its upregulation on NETs generation and frequencies of Th1/Th17 cells in affiliation with increased production of IFN-γ/IL-17A through succinic acid-SUCNR1 axis.