Hasil untuk "Animal biochemistry"

H. Ohkawa, N. Ohishi, K. Yagi

B. Havsteen

Constance E. Clare, A. H. Brassington, W. Kwong et al.

One-carbon (1C) metabolism comprises a series of interlinking metabolic pathways that include the methionine and folate cycles that are central to cellular function, providing 1C units (methyl groups) for the synthesis of DNA, polyamines, amino acids, creatine, and phospholipids. S-adenosylmethionine is a potent aminopropyl and methyl donor within these cycles and serves as the principal substrate for methylation of DNA, associated proteins, and RNA. We propose that 1C metabolism functions as a key biochemical conduit between parental environment and epigenetic regulation of early development and that interindividual and ethnic variability in epigenetic-gene regulation arises because of genetic variants within 1C genes, associated epigenetic regulators, and differentially methylated target DNA sequences. We present evidence to support these propositions, drawing upon studies undertaken in humans and animals. We conclude that future studies should assess the epigenetic effects of cumulative (multigenerational) dietary imbalances contemporaneously in both parents, as this better represents the human experience.

R. Warner, T. Wheeler, M. Ha et al.

Meat tenderness is an important quality trait critical to consumer acceptance, and determines satisfaction, repeat purchase and willingness-to-pay premium prices. Recent advances in tenderness research from a variety of perspectives are presented. Our understanding of molecular factors influencing tenderization are discussed in relation to glycolysis, calcium release, protease activation, apoptosis and heat shock proteins, the use of proteomic analysis for monitoring changes, proteomic biomarkers and oxidative/nitrosative stress. Each of these structural, metabolic and molecular determinants of meat tenderness are then discussed in greater detail in relation to animal variation, postmortem influences, and changes during cooking, with a focus on recent advances. Innovations in postmortem technologies and enzymes for meat tenderization are discussed including their potential commercial application. Continued success of the meat industry relies on ongoing advances in our understanding, and in industry innovation. The recent advances in fundamental and applied research on meat tenderness in relation to the various sectors of the supply chain will enable such innovation.

Cassandra Upton, Gerhard Prinsloo, Paul Anton Steenkamp et al.

IntroductionSea cucumbers are ecologically and economically significant marine invertebrates, yet the metabolic diversity and bioactive potential of noncommercialized, endemic species remains poorly understood.MethodsThis study presents the first intra-species metabolomic analysis of Pseudocnella sykion, a species endemic to the Eastern coast of Southern Africa, using untargeted 1HNMR metabolomics and full-scan UPLC-QTOF-HR-MS.ResultsThe analysis revealed a diverse array of metabolites associated with protein synthesis, tissue growth, osmoregulation, and energy utilization, with distinct tissue-specific patterns across the body wall, gonad, and gut/mesentery. The gut/mesentery tissue showed higher levels of amino acids and energy-related compounds. UPLCQTOF-HR-MS tentatively identified several metabolites, including triterpene glycosides and rosmarinic acid, a phenolic compound typically associated with plants. Online resources, including the Dictionary of Marine Natural Products, contained no previously recorded compounds for P. sykion.DiscussionThese findings underscore the untapped potential of P. sykion as a source of novel metabolites and demonstrate the utility of untargeted metabolomics in generating baseline profiles for underexplored marine species. The results offer a foundation for future research into bioactivity, environmental monitoring, and cultivation strategies. While this study provides critical baseline data, challenges in metabolite identification and extraction underscore the need for further targeted analyses. Overall, this research enhances our understanding of the metabolic dynamics of sea cucumbers and advocates for continued exploration of lesser-known species to support conservation, bioprospecting, and sustainable aquaculture. It represents a pioneering effort in metabolomic profiling of Southern African sea cucumber species and lays the groundwork for future investigations into their metabolic pathways and potential bioactivities.

Levent Gülüm, Süheyla Esin Köksal, Emrah Güler et al.

The objective of this study was to evaluate the physicochemical, bioactive, and technological properties of pasta made from durum wheat semolina that was partially replaced with Acorn flour at levels of 10%, 20%, and 30%. The incorporation of Acorn flour had a substantial impact on the nutritional composition of the pasta, resulting in increases in total phenolic content (TPC), total flavonoid content (TFC), and antioxidant capacity in comparison with the control sample. The highest values for TPC and TFC were found in the samples containing 20% and 30% Acorn flour (p<0.05), demonstrating the functional potential of this formulation. However, an increase in the quantity of Acorn flour used in the pasta production process resulted in a noticeable darkening of the pasta's colour. This observation is consistent with the findings of previous research conducted on the use of non-traditional flours. While the increased amounts of Acorn flour resulted in enhanced nutritional and antioxidant profiles, the darker appearance and alterations in texture may have implications for sensory and visual acceptability. The present findings are corroborated by extant literature, which demonstrates that functional flours such as buckwheat, chickpea, lentil, chia, and sorghum have exhibited analogous trends in enhancing bioactive compounds and altering technological properties. Incorporation of Acorn flour at levels ranging from 10% to 20% optimises the health benefits of pasta while maintaining its desirable sensory and structural characteristics. Presented research contributes to the valorization of non-wood forest product (NWFP) resources and the development of innovative functional pasta products using sustainable ingredients.

Mangesh Vaidya, V. R. Patodkar, Prajakta Kuralkar et al.

Livestock-generated methane, particularly from cattle, was a significant contributor to climate change. Methane emissions from ruminant animals, such as cows and sheep, are primarily caused by the microbial fermentation of food in their digestive systems, a process known as enteric fermentation by making this process a prime source of greenhouse gas emissions in animal production. Considerable knowledge gaps existed in animal agriculture regarding effective strategies for mitigating these emissions while maintaining productivity. A key factor was the uncertainty surrounding methods for estimating emission rates, each having inherent limitations. For example, the suitability of the GreenFeed system varied based on specific experiment objectives. Compared to respiration chambers and the sulfur hexafluoride tracer method, the The GreenFeed system often required more time and a larger number of animals for treatment comparisons due to higher within-day variances. It measured numerous short-term methane emissions from individual animals at various times throughout the day over several days. Recent advancements focused on improving accuracy, ease of use, and cost-effectiveness, essential for better monitoring of greenhouse gases. Traditional methods, such as respiration chambers, while accurate, were costly and impractical for field measurements. The GreenFeed system’s software facilitated control over feed availability timing and CH4 measurement allocation. Therefore, careful planning was necessary to ensure accurate estimates of methane production. This review emphasized the need for effective measurement techniques to mitigate methane emissions from livestock.

Lincy Koodaly, Erika Friedmann, Nancy R. Gee et al.

<b>Background:</b> The growth of the older adult population calls for innovative and cost-effective ways of promoting their physical, psychological, and cognitive health. Human–animal interaction, including pet ownership, is related to positive and negative aspects of human health. Not all pet owners respond in the same way. The levels of pet attachment and pets’ influence on their owners’ lives could moderate the relationship between psychological status and health outcomes. <b>Purpose:</b> We examined the moderating role of pet attachment in the relationships of psychological status (mental wellbeing, happiness, anxiety, depression) to physical function (physical wellbeing, usual- and rapid-gait speeds, physical performance battery) in community-residing older adult pet owners. <b>Methods:</b> A cross-sectional, secondary analysis of pet-owning older adult participants in the Baltimore Longitudinal Study of Aging (n = 178). <b>Results:</b> In regression analyses, controlling for age, gender, and comorbidities, pet attachment and pet influence moderated the relationships of physical wellbeing to mental wellbeing and anxiety (<i>p</i> < 0.05). Pet influence also moderated the relationship between anxiety and usual gait speed (<i>p</i> < 0.05). <b>Conclusions:</b> Greater attachment and influence buffer the relationship of perceptions of poor mental function with perceptions of poor physical wellbeing suggesting one mechanism for health benefits of human-animal interaction.

Bartosz Orzechowski, Jan Miciński, Katarzyna Ząbek et al.

With the aim to investigate the immunomodulatory potential of selenitetriglycerides (SeTG), a new lipophilic Se (IV) compound, 30 sheep (15 sheep/treatment) were used in a completely random design to receive the SeGT supplement as follows: (1) no SeGT supplement (Control) and (2) daily dosage of 2 mL of SeGT (equivalent to 1 mg Se/kg BW) during the first 7 days of the evaluation, which lasted 28 d. Individually, blood samples were collected on days 0, 14, and 28 to measure and assess parameters of innate cellular and humoral immunity, including respiratory burst activity (RBA) and potential killing activity (PKA) of monocytes and granulocytes, proliferative response of lymphocytes stimulated with ConA (Concovalin A) and LPS (lipopolisaccharidde), lysozyme activity, ceruloplasmin activity, and gamma globulin levels. From the 14th day, supplemental SeTG saw significant increases (<i>p</i> ≤ 0.001) in RBA and PKA parameters, as well as enhanced proliferative responses of lymphocytes compared with controls. Both innate humoral immunity (elevated lysozyme activity) and adaptive humoral immunity (increased gamma globulin levels) were positively influenced (<i>p</i> ≤ 0.01), whereas ceruloplasmin activity remained unchanged. Under the conditions in which the current experiment was carried out, SeGT showed good promise to modulate immunity in a short period (28 d). Further research should explore experiments with a greater number of animals over long-term periods of evaluation under production system conditions.

Eklavya Sarkar, Mathew Magimai. -Doss

Animal vocalizations contain sequential structures that carry important communicative information, yet most computational bioacoustics studies average the extracted frame-level features across the temporal axis, discarding the order of the sub-units within a vocalization. This paper investigates whether discrete acoustic token sequences, derived through vector quantization and gumbel-softmax vector quantization of extracted self-supervised speech model representations can effectively capture and leverage temporal information. To that end, pairwise distance analysis of token sequences generated from HuBERT embeddings shows that they can discriminate call-types and callers across four bioacoustics datasets. Sequence classification experiments using $k$-Nearest Neighbour with Levenshtein distance show that the vector-quantized token sequences yield reasonable call-type and caller classification performances, and hold promise as alternative feature representations towards leveraging sequential information in animal vocalizations.

Enmin Zhong, Carlos R. del-Blanco, Daniel Berjón et al.

Recently, there has been a surge of interest in applying deep learning techniques to animal behavior recognition, particularly leveraging pre-trained visual language models, such as CLIP, due to their remarkable generalization capacity across various downstream tasks. However, adapting these models to the specific domain of animal behavior recognition presents two significant challenges: integrating motion information and devising an effective temporal modeling scheme. In this paper, we propose AnimalMotionCLIP to address these challenges by interleaving video frames and optical flow information in the CLIP framework. Additionally, several temporal modeling schemes using an aggregation of classifiers are proposed and compared: dense, semi dense, and sparse. As a result, fine temporal actions can be correctly recognized, which is of vital importance in animal behavior analysis. Experiments on the Animal Kingdom dataset demonstrate that AnimalMotionCLIP achieves superior performance compared to state-of-the-art approaches.

Gavin L. Simpson

Nonlinear relationships between covariates and a response variable of interest are frequently encountered in animal science research. Within statistical models, these nonlinear effects have, traditionally, been handled using a range of approaches including transformation of the response, parametric nonlinear models based on theory or phenomenological grounds, or through fixed degree spline or polynomial terms. If it is desirable to learn the shape of these relationships then generalized additive models (GAMs) are an excellent alternative. GAMs extend the generalized linear model such that the linear predictor includes one or more smooth functions, parameterised using penalised splines. A wiggliness penalty on each function is used to avoid over fitting while estimating the parameters of the spline basis functions to maximise fit to the data. Modern GAMs include automatic smoothness selection methods to find an optimal balance between fit and complexity of the estimated functions. Because GAMs learn the shapes of functions from the data, the user can avoid forcing a particular model to their data. Here, I provide a brief description of GAMs and visually illustrate how they work. I then demonstrate the utility of GAMs on three example data sets of increasing complexity, to show i) how learning from data can produce a better fit to data than that of parametric models, ii) how hierarchical GAMs can be used to estimate growth data from multiple animals in a single model, and iii) how hierarchical GAMs can be used for formal statistical inference in a designed experiment. The examples are supported by R code that demonstrates how to fit each of the models considered, and reproduces the results of the statistical analyses reported here. Ultimately, I show that GAMs are a modern, flexible, and highly usable statistical model that is amenable to many research problems in animal science.

Daniel Strömbom, Catherine Futterman

Moving animal groups consist of many distinct individuals but can operate and function as one unit when performing different tasks. Effectively evading unexpected predator attacks is one primary task for many moving groups. The current explanation for predator evasion responses in moving animal groups require the individuals in the groups interact via (velocity) alignment. However, experiments have shown that some animals do not use alignment. This suggests that another explanation for the predator evasion capacity in at least these species is needed. Here we establish that effective collective predator evasion does not require alignment, it can be induced via attraction and repulsion alone. We also show that speed differences between individuals that have directly observed the predator and those that have not influence evasion success and the speed of the collective evasion process, but are not required to induce the phenomenon. Our work here adds collective predator evasion to a number of phenomena previously thought to require alignment interactions that have recently been shown to emerge from attraction and repulsion alone. Based on our findings we suggest experiments and make predictions that may lead to a deeper understanding of not only collective predator evasion, but also collective motion in general.

D. Ndeh, H. Gilbert

Dwi Puspa Sukma Viranda, Rochmah Kurnijasanti, Kadek Rachmawati et al.

This study aims to determine the effect of porang (Amorphophallus oncophyllus) tuber extract on the histopathological features of the testicle of alloxan induced rats (Rattus norvegicus). Thirty male rats were randomly divided into six groups. Rats in group C- were injected with distilled water, while rats in groups C+, T0, T1, T2, and T3 were injected with 120 mg/kg bw alloxan. Blood glucose was measured three days after alloxan injection. Rats in groups C- and C+ were then administered with 1% Na-CMC, whereas rats in groups T0, T1, T2, and T3 were then administered with 45mg/kg bw metformin, and 100, 200, and 400 mg/kg bw of porang tuber extract, respectively. All solution were given orally once every day for 14 days. Spermatogenic activity was assessed using the Johnsen scoring system and analyzed by Kruskal-Wallis, followed by the Mann-Whitney test. The diameter and epithelial thickness of the seminiferous tubule were measured using image raster software and analyzed using Anova followed by Duncan's test. The results showed that spermatogenesis score, diameter, and epithelial thickness of seminiferous tubule of group C+ were smaller (p <0.05) than group C-. Spermatogenesis scores of groups T0, T1, T2, and T3 were higher (p <0.05) than group C+. Seminiferous tubule diameter and epithelial thickness in groups T0, T1, and T2 were greater (p <0.05) than group C+. It could be concluded that porang tuber extract at a dose of 200 mg/kg bw improved the spermatogenesis score, diameter seminiferous tubule, and thickness of the epithelium of diabetic rats.

Jeremy Lucas, Isabeau Prémont-Schwarz

This paper presents the Articulated Animal AI Environment for Animal Cognition, an enhanced version of the previous AnimalAI Environment. Key improvements include the addition of agent limbs, enabling more complex behaviors and interactions with the environment that closely resemble real animal movements. The testbench features an integrated curriculum training sequence and evaluation tools, eliminating the need for users to develop their own training programs. Additionally, the tests and training procedures are randomized, which will improve the agent's generalization capabilities. These advancements significantly expand upon the original AnimalAI framework and will be used to evaluate agents on various aspects of animal cognition.

Qingxin Li

Keratinases belong to a class of proteases that are able to degrade keratins into amino acids. Microbial keratinases play important roles in turning keratin-containing wastes into value-added products by participating in the degradation of keratin. Keratin is found in human and animal hard tissues, and its complicated structures make it resistant to degradation by common proteases. Although breaking disulfide bonds are involved in keratin degradation, keratinase is responsible for the cleavage of peptides, making it attractive in pharmaceutical and feather industries. Keratinase can serve as an important tool to convert keratin-rich wastes such as feathers from poultry industry into diverse products applicable to many fields. Despite of some progress made in isolating keratinase-producing microorganisms, structural studies of keratinases, and biochemical characterization of these enzymes, effort is still required to expand the biotechnological application of keratinase in diverse fields by identifying more keratinases, understanding the mechanism of action and constructing more active enzymes through molecular biology and protein engineering. Herein, this review covers structures, applications, biochemistry of microbial keratinases, and strategies to improve its efficiency in keratin degradation.

Xiuxiu Liu, Maoying Han, Wendong Weng et al.

Abstract A genetic system, ProTracer, has been recently developed to record cell proliferation in vivo. However, the ProTracer is initiated by an infrequently used recombinase Dre, which limits its broad application for functional studies employing floxed gene alleles. Here we generated Cre-activated functional ProTracer (fProTracer) mice, which enable simultaneous recording of cell proliferation and tissue-specific gene deletion, facilitating broad functional analysis of cell proliferation by any Cre driver.

Ying-jie Gao, Shi-rong Li, Yuan Huang

BackgroundDue to the viral infection, chronic inflammation significantly increases the likelihood of hepatocellular carcinoma (HCC) development. Nevertheless, an inflammation-based signature aimed to predict the prognosis and therapeutic effect in virus-related HCC has rarely been established.MethodBased on the integrated analysis, inflammation-associated genes (IRGs) were systematically assessed. We comprehensively investigated the correlation between inflammation and transcriptional profiles, prognosis, and immune cell infiltration. Then, an inflammation-related risk model (IRM) to predict the overall survival (OS) and response to treatment for virus-related HCC patients was constructed and verified. Also, the potential association between IRGs and tumor microenvironment (TME) was investigated. Ultimately, hub genes were validated in plasma samples and cell lines via qRT-PCR. After transfection with shCCL20 combined with overSLC7A2, morphological change of SMMC7721 and huh7 cells was observed. Tumorigenicity model in nude mouse was established.ResultsAn inflammatory response-related gene signature model, containing MEP1A, CCL20, ADORA2B, TNFSF9, ICAM4, and SLC7A2, was constructed by conjoint analysis of least absolute shrinkage and selection operator (LASSO) Cox regression and gaussian finite mixture model (GMM). Besides, survival analysis attested that higher IRG scores were positively relevant to worse survival outcomes in virus-related HCC patients, which was testified by external validation cohorts (the ICGC cohort and GSE84337 dataset). Univariate and multivariate Cox regression analyses commonly proved that the IRG was an independent prognostic factor for virus-related HCC patients. Thus, a nomogram with clinical factors and IRG was also constructed to superiorly predict the prognosis of patients. Featured with microsatellite instability-high, mutation burden, and immune activation, lower IRG score verified a superior OS for sufferers. Additionally, IRG score was remarkedly correlated with the cancer stem cell index and drug susceptibility. The measurement of plasma samples further validated that CCL20 upexpression and SLC7A2 downexpression were positively related with virus-related HCC patients, which was in accord with the results in cell lines. Furthermore, CCL20 knockdown combined with SLC7A2 overexpression availably weakened the tumor growth in vivo.ConclusionsCollectively, IRG score, serving as a potential candidate, accurately and stably predicted the prognosis and response to immunotherapy in virus-related HCC patients, which could guide individualized treatment decision-making for the sufferers.

Deny Jennes, Soumya Ramankutty, S. Anoop et al.

Platelet rich plasma (PRP) therapy is an integral part of regenerative medicine as the platelets possess a good healing capacity owing to the presence of a wide variety of growth factors in the platelet granules found in the cytoplasm of the platelet. Autologous PRP was prepared from the blood of the patient itself, without any preservatives. Storage of PRP was one of the main hurdles of the treatment modality. During storage, the platelet counts may get reduced, undergo activation or get contaminated with bacteria as no preservatives are used in the preparation of autologous PRP. Cytological changes and microbial quality of the PRP during storage at 4oC and -20oC for seven days were analysed in this study. Reduction in platelet count and the chance of microbial contamination were less when autologous PRP was stored at -20°C compared to 4°C.