Search Results (1,291)

Aggressiveness in dogs is a complex behavioral trait with implications for animal welfare and public safety. Despite domestication, dogs retain aggressive tendencies shaped by both genetic and environmental factors. This systematic review synthesizes the literature from 2000 to 2024 on the genetic and environmental bases of canine aggression. Using PRISMA 2020 guidelines, 144 articles were retrieved from Scopus and PubMed and screened in two phases, resulting in 33 studies selected for analysis. These were evaluated using a 20-question grid across seven categories, including phenotyping, genetic analysis, population structure, and future directions. The studies support a polygenic model of aggressiveness, with associations reported for genes involved in neurotransmission, hormone signaling, and brain function. However, inconsistencies in phenotyping, small sample sizes, and a limited consideration of environmental factors hinder robust conclusions. Most studies focused on popular companion breeds, while those commonly labeled as aggressive were underrepresented. The findings highlight the relevance of gene–environment interactions but underscore that aggression is often poorly defined and measured across studies. Future research should prioritize standardized phenotyping tools, broader breed inclusion, and the functional validation of genetic findings. These efforts will improve the understanding of dog aggression and inform breeding, behavioral assessment, and public policy. Full article

The Chinese red panda (Ailurus styani) is a rare and endangered animal in China; the increase in global temperature and the interference of human activities have caused irreversible effects on the suitable habitat of wild red pandas and threatened their survival. Therefore, it is necessary to carry out scientific research and protection for Chinese red pandas. In this study, the MaxEnt model was used to predict and analyze the suitable habitats of Chinese red pandas in the large and small Xiangling Mountains. The results showed that the main ecological factors affecting the suitable habitat distribution of Chinese red pandas in the Daxiangling Mountains are the average slope (45.6%, slope), the distance from the main road (24.2%, road), and the average temperature in the coldest quarter (11%, bio11). The main ecological factors affecting the suitable habitat distribution of Chinese red pandas in the Xiaoxiangling Mountains are bamboo distribution (67.4%, bamboo), annual temperature range (20.7%, bio7), and the average intensity of human activities (8.7%, Human Footprint). The predicted suitable habitat area of the Daxiangling Mountains is 123.835 km², and the predicted suitable habitat area of the Xiaoxiangling Mountains is 341.873 km². The predicted suitable habitat area of the Daxiangling Mountains accounts for 43.45% of the total mountain area, and the predicted suitable habitat area of the Xiaoxiangling Mountains accounts for 71.38%. The suitable habitat area of the Xiaoxiangling Mountains is nearly three times that of the Daxiangling Mountains, and the proportion of suitable habitat area of the Xiaoxiangling Mountains is much higher than that of the Daxiangling Mountains. The suitable habitat of Chinese red pandas in the Daxiangling Mountains is mainly distributed in the southeast, and the habitat is coherent but fragmented. The suitable habitat of Chinese red panda in Xiaoxiangling Mountains is mainly distributed in the east, and the habitat is more coherent. The results of this study can provide a scientific basis for the protection of the population and habitat of Chinese red pandas in Sichuan. Full article

Objective: To investigate the effects of oat fiber on animal constipation and elucidate its underlying mechanisms. Methods: Male BALB/c mice were randomly allocated into five groups: control group (CON), model control group (MODEL), low dose group (LOW), middle dose group (MIDDLE), high dose group (HIGH). Constipation was induced in the mice by intragastric administration of loperamide. Subsequently, the mice (except those in the CON and MODEL groups) were administered oat fiber intragastrically for 21 consecutive days. Results: Compared with the MODEL group, oat fiber significantly increased the number of fecal pellets, fecal wet weight, and fecal water content (p < 0.05), shortened the time to first black stool excretion (p < 0.05), and enhanced the small intestinal propulsion rate in constipated mice. Additionally, oat fiber significantly upregulated motilin (MTL) and gastrin (GAS) levels (p < 0.05), while downregulating vasoactive intestinal peptide (VIP) and somatostatin (SS) levels (p < 0.05). It also significantly reduced the transcription level of Aquaporin 8 (AQP8) (p < 0.05), effectively alleviating intestinal mucosal injury and immune inflammation. The relative expression levels of TNF-α and IL-1β were significantly decreased in the oat fiber group (p < 0.05). Gut microbiota analysis revealed that oat fiber increased both the abundance and diversity of gut microbiota in constipated mice. Specifically, oat fiber was found to enhance the relative abundance of Firmicutes while reducing that of Bacteroidetes. At the genus level, it promoted the proliferation of Lachnospiraceae_NK4A136_group and Roseburia. Conclusions: Oat fiber alleviates constipation in mice by modulating gastrointestinal regulatory peptides, gut microbiota, aquaporin and mitigating intestinal barrier damage and immune-inflammatory responses. Full article

Background: BDE-47, a pervasive environmental pollutant detected in >90% of human serum samples, is increasingly linked to metabolic disorders. This study investigates the specific impact of BDE-47 exposure on the gut microbiota in prediabetic mice and evaluates the efficacy of therapeutic interventions in mitigating these effects. Objectives: To determine whether BDE-47 exposure induces diabetogenic dysbiosis in prediabetic mice and to assess whether dietary interventions, such as grape exosomes and an antioxidant cocktail, can restore a healthy microbiota composition and mitigate diabetes risk. Methods: In this study, a prediabetic mouse model was established in 54 male SPF-grade C57BL/6J mice through a combination of high-sugar and high-fat diet feeding with streptozotocin injection. Oral glucose tolerance tests (OGTT) were conducted on day 7 and day 21 post-modeling to assess the establishment of the model. The criteria for successful model induction were defined as fasting blood glucose levels below 7.8 mmol/L and 2 h postprandial glucose levels between 7.8 and 11.1 mmol/L. Following confirmation of model success, a 3 × 3 factorial design was applied to allocate the experimental animals into groups based on two independent factors: BDE-47 exposure and exosome intervention. The BDE-47 exposure factor consisted of three dose levels—none, high-dose, and medium-dose—while the exosome intervention factor included three modalities—none, Antioxidant Nutrients Intervention, and Grape Exosomes Intervention. Fresh fecal samples were collected from mice two days prior to sacrifice. Cecal contents and segments of the small intestine were collected and transferred into 1.5 mL cryotubes. All sequences were clustered into operational taxonomic units (OTUs) based on defined similarity thresholds. To compare means across multiple groups, a two-way analysis of variance (ANOVA) was employed. The significance level was predefined at α = 0.05, and p-values < 0.05 were considered statistically significant. Bar charts and line graphs were generated using GraphPad Prism version 9.0 software, while statistical analyses were performed using SPSS version 20.0 software. Results: The results of 16S rDNA sequencing analysis of the microbiome showed that there was no difference in the α diversity of the intestinal microbiota in each group of mice (p > 0.05), but there was a difference in the Beta diversity (p < 0.05). At the gate level, the abundances of Proteobacteria, Campylobacterota, Desulfobacterota, and Fusobacteriota in the medium-dose BDE-7 group were higher than those in the model control group (p < 0.05). The abundance of Patellar bacteria was lower than that of the model control group (p < 0.05). The abundances of Proteobacteria and Campylobacterota in the high-dose BDE-7 group were higher than those in the model control group (p < 0.05). The abundance of Planctomycetota and Patescibacteria was lower than that of the model control group (p < 0.05), while the abundance of Campylobacterota in the grape exosome group was higher than that of the model control group (p < 0.05). The abundance of Patescibacteria was lower than that of the model control group (p < 0.05), while the abundance of Firmicutes and Fusobacteriota in the antioxidant nutrient group was higher than that of the model control group (p < 0.05). However, the abundance of Verrucomicrobiota and Patescibacteria was lower than that of the model control group (p < 0.05). At the genus level, the abundances of Bacteroides and unclassified Lachnospiraceae in the high-dose BDE-7 group were higher than those in the model control group (p < 0.05). The abundance of Lachnospiraceae NK4A136_group and Lactobacillus was lower than that of the model control group (p < 0.05). The abundance of Veillonella and Helicobacter in the medium-dose BDE-7 group was higher than that in the model control group (p < 0.05), while the abundance of Lactobacillus was lower (p < 0.05). The abundance of genera such as Lentilactobacillus and Faecalibacterium in the grape exosome group was higher than that in the model control group (p < 0.05). The abundance of Alloprevotella and Bacteroides was lower than that of the model control group (p < 0.05). In the antioxidant nutrient group, the abundance of Lachnospiraceae and Hydrogenophaga was higher than that in the model control group (p < 0.05). However, the abundance of Akkermansia and Coriobacteriaceae UCG-002 was significantly lower than that of the model control group (p < 0.05). Conclusions: BDE-47 induces diabetogenic dysbiosis in prediabetic mice, which is reversible by dietary interventions. These findings suggest that microbiota-targeted strategies may effectively mitigate the diabetes risk associated with environmental pollutant exposure. Future studies should further explore the mechanisms underlying these microbiota changes and the long-term health benefits of such interventions. Full article

Breast cancer (BC) is the most common malignancy and the second-leading cause of cancer-related mortalities in women. Epidemiological studies suggested the reduced BC incidence in Mediterranean populations due to the daily consumption of diets rich in extra-virgin olive oil (EVOO). EVOO secoiridoid phenolics are widely known for their positive outcomes on multiple cancers, including BC. The current study investigates the suppressive effects of individual and combined EVOO phenolics for BC progression and motility. Screening of a small library of EVOO phenolics at a single dose of 10 µM against the viability of the BC cell lines ZR-75-1 (luminal A) and MDA-MB-231 (triple negative BC, TNBC) identified oleocanthal (OC) and ligstroside aglycone (LA) as the most active hits. Screening of EVOO phenolics for BC cells migration inhibition identified OC, LA, and the EVOO lignans acetoxypinoresinol and pinoresinol as the most active hits. Combination studies of different olive phenolics showed that OC combined with LA had the best synergistic inhibitory effects against the TNBC MDA-MB-231 cells migration. A combination of 5 µM of each of OC and LA potently suppressed the migration and invasion of the MDA-MB-231 cells versus LA and OC individual therapies and vehicle control (VC). Animal studies using the ZR-75-1 BC cells orthotopic xenografting model in female nude mice showed significant tumor progression suppression by the combined OC-LA, 5 mg/kg each, ip, 3X/week treatments compared to individual LA and OC treatments and VC. The BC suppressive effects of the OC-LA combination were associated with the modulation of SMYD2–EZH2–STAT3 signaling pathway. A metastasis–clonogenicity animal study model using female nude mice subjected to tail vein injection of MDA-MB-231-Luc TNBC cells also revealed the effective synergy of the combined OC-LA, 5 mg/kg each, compared to their individual therapies and VC. Thus, EVOO cultivars rich in OC with optimal LA content can be useful nutraceuticals for invasive hormone-dependent BC and TNBC progression and metastasis. Full article

Renewable fuels produced from animal- and plant-based edible oils have emerged as an alternative to oil and natural gas. Burgeoning interest in renewables can be attributed to the rapid depletion of fossil fuels caused by the global energy demand and the environmental advantages of renewables, specifically reduced emissions of greenhouse gases. An important property of the feedstock that is crucial for the conversion of edible oils to renewable fuels is the total acid number (TAN), as even a small increase in TAN for the feedstock can lead to corrosion of the catalyst in the refining process. Currently, the TAN is determined by potentiometric titration, which is time-consuming, expensive, and requires the preparation of reagents. As part of an effort to promote the use of renewable fuels, a partial least squares regression method with orthogonal signal correction to remove spectral information related to the sample background was developed to determine the TAN from the mid-infrared (IR) spectra of the feedstock. Digitally blended mid-IR spectral data were generated to fill in regions of the PLS calibration where there were very few samples. By combining experimental and digitally blended mid-IR spectral data to ensure adequate sample representation in all regions of the spectra–property calibration and better understand the spectra–property relationship through the identification of sample outliers in the original data that can be difficult to detect because of swamping, a PLS regression model for TAN (R² = 0.992, cross-validated root mean square error = 0.468, and bias = 0.0036) has been developed from 118 experimental and digitally blended mid-IR spectra of commercial feedstock. Thus, feedstock whose TAN value is too high for refining can be flagged using the proposed mid-IR method, which is faster and easier to use than the current titrimetric method. Full article

Ochratoxin A (OTA), as a mycotoxin, can contaminate a variety of feeds and foods. Existing studies have shown that the main toxicity of OTA to organisms is nephrotoxicity, but the toxic mechanism to other organs is still worthy of further study. Whether OTA causes intestinal damage through the necroptosis pathway mediated by RIPK1/RIPK3/MLKL remains to be elucidated. Astaxanthin (AST), a feed additive with strong antioxidant properties, was used as an antidote to evaluate the alleviation effect on OTA-induced intestinal injury and the underlying mechanism in this research. Chickens are the most sensitive animals to OTA except pigs. Therefore, 70 white-feathered chickens (n = 15) and Chicken Small Intestinal Epithelial Cells (CSIECs) were used as experimental subjects. Experimental models were established by single or combined exposure of OTA (1.0 mg/kg on chickens for 21 d; 2 μM on CSIEC for 24 h) and AST (100 mg/kg on chickens for 21 d; 40 μM on CSIEC for 24 h). In this study, AST significantly ameliorated OTA-induced intestinal damage by restoring the expression of tight junction proteins (Occludin-1, Claudin-1, and ZO-1), attenuating severe histopathological alterations, mitigating the inflammatory response (elevated pro-inflammatory cytokines and reduced anti-inflammatory mediators), and suppressing necroptosis through downregulation of RIPK1, RIPK3 and MLKL expression. Combined evidence from animal experiments and cell culture experiments demonstrated that AST alleviated the necroptosis and inflammation caused by OTA in CSIECs and the intestine of chickens through the RIPK1/RIPK3/MLKL signaling pathway, thereby reducing the damage caused by OTA. Full article

Our previous research identified 12 small Cajal body-specific RNAs (scaRNAs) with reduced expression in the right ventricle in infant patients with tetralogy of Fallot. Likewise, we showed that there were significant changes in mRNA processing in the RV in these patients. ScaRNAs play a crucial role in the biochemical maturation of spliceosomal RNAs (pseudouridylation and 2′-O-methylation). We showed that variations in scaRNA1 levels resulted in changes in alternative splicing in human cells. To investigate further the role that scaRNAs play in mRNA processing, we examine here the impact of knocking down scaRNA1 in quail myoblast cells (Coturnix japonica, a well-established animal model for studying embryonic development). Following the knockdown of scaRNA1, transcriptome analysis revealed that the genes Tjp1, Map3k7, and Sppl2a were alternatively spliced. Growing evidence indicates that alternative splicing of mRNA plays an important role in regulating cell differentiation and tissue development. Our data presented here provide additional support for research to clarify the specific roles that individual scaRNAs play in regulating spliceosome function and mRNA splicing. Full article

Background/Objectives: Artificial intelligence (AI) is beginning to be applied in wound ballistics, showing preliminary potential to improve the accuracy and objectivity of forensic analyses. This review explores the current state of AI applications in forensic firearm wound analysis, emphasizing its potential to address challenges such as subjective interpretations and data heterogeneity. Methods: A systematic review adhering to PRISMA guidelines was conducted using databases such as Scopus and Web of Science. Keywords focused on AI and GSW classification identified 502 studies, narrowed down to 4 relevant articles after rigorous screening based on inclusion and exclusion criteria. Results: These studies examined the role of deep learning (DL) models in classifying GSWs by type, shooting distance, and entry or exit characteristics. The key findings demonstrated that DL models like TinyResNet, ResNet152, and ConvNext Tiny achieved accuracy ranging from 87.99% to 98%. Models were effective in tasks such as classifying GSWs and estimating shooting distances. However, most studies were exploratory in nature, with small sample sizes and, in some cases, reliance on animal models, which limits generalizability to real-world forensic scenarios. Conclusions: Comparisons with other forensic AI applications revealed that large, diverse datasets significantly enhance model performance. Transparent and interpretable AI systems utilizing techniques are essential for judicial acceptance and ethical compliance. Despite the encouraging results, the field remains in an early stage of development. Limitations highlight the need for standardized protocols, cross-institutional collaboration, and the integration of multimodal data for robust forensic AI systems. Future research should focus on overcoming current data and validation constraints, ensuring the ethical use of human forensic data, and developing AI tools that are scientifically sound and legally defensible. Full article

Accurate body condition score (BCS) monitoring in dairy cows is essential for optimizing health, productivity, and welfare. Traditional manual scoring methods are labor-intensive and subjective, driving interest in automated imaging-based systems. This study evaluated the effectiveness of 2D imaging and deep learning for BCS classification using three camera perspectives—front, back, and top-down—to identify the most reliable viewpoint. The research involved 56 Norwegian Red milking cows at the Center for Livestock Experiments (SHF) of Norges Miljo-og Biovitenskaplige Universitet (NMBU) in Norway. Images were classified into BCS categories of 2.5, 3.0, and 3.5 using a YOLOv8 model. The back view achieved the highest classification precision (mAP@0.5 = 0.439), confirming that key morphological features for BCS assessment are best captured from this angle. Challenges included misclassification due to overlapping features, especially in Class 2.5 and background data. The study recommends improvements in algorithmic feature extraction, dataset expansion, and multi-view integration to enhance accuracy. Integration with precision farming tools enables continuous monitoring and early detection of health issues. This research highlights the potential of 2D imaging as a cost-effective alternative to 3D systems, particularly for small and medium-sized farms, supporting more effective herd management and improved animal welfare. Full article

Axis definition plays a key role in the establishment of animal body plans, both in normal development and regeneration. The cnidarian Hydra can re-establish its simple body plan when regenerating from a random cell aggregate or a sufficiently small tissue fragment. At the beginning of regeneration, a hollow cellular spheroid forms, which then undergoes symmetry breaking and de novo body axis definition. In the past, we have published related work in a physics journal, which is difficult to read for scientists from other disciplines. Here, we review our work for readers not so familiar with this type of approach at a level that requires very little knowledge in mathematics. At the same time, we present a few aspects of Hydra biology that we believe to be linked to our work. These biological aspects may be of interest to physicists or members of related disciplines to better understand our approach. The proposed theoretical model is based on fluctuations of gene expression that are triggered by mechanical signaling, leading to increasingly large groups of cells acting in sync. With a single free parameter, the model quantitatively reproduces the experimentally observed expression pattern of the gene ks1, a marker for ‘head forming potential’. We observed that Hydra positions its axis as a function of a weak temperature gradient, but in a non-intuitive way. Supposing that a large fluctuation including ks1 expression is locked to define the head position, the model reproduces this behavior as well—without further changes. We explain why we believe that the proposed fluctuation-based symmetry breaking process agrees well with recent experimental findings where actin filament organization or anisotropic mechanical stimulation act as axis-positioning events. The model suggests that the Hydra spheroid exhibits huge sensitivity to external perturbations that will eventually position the axis. Full article

Reproductive efficiency is a critical determinant of productivity and profitability in sheep farming. Traditional selection methods have largely relied on phenotypic traits and historical reproductive records, which are often limited by subjectivity and delayed feedback. Recent advancements in artificial intelligence (AI), including video tracking, wearable sensors, and machine learning (ML) algorithms, offer new opportunities to identify behavior-based indicators linked to key reproductive traits such as estrus, lambing, and maternal behavior. This review synthesizes the current research on AI-powered behavioral monitoring tools and proposes a conceptual model, ReproBehaviorNet, that maps age- and sex-specific behaviors to biological processes and AI applications, supporting real-time decision-making in both intensive and semi-intensive systems. The integration of accelerometers, GPS systems, and computer vision models enables continuous, non-invasive monitoring, leading to earlier detection of reproductive events and greater breeding precision. However, the implementation of such technologies also presents challenges, including the need for high-quality data, a costly infrastructure, and technical expertise that may limit access for small-scale producers. Despite these barriers, AI-assisted behavioral phenotyping has the potential to improve genetic progress, animal welfare, and sustainability. Interdisciplinary collaboration and responsible innovation are essential to ensure the equitable and effective adoption of these technologies in diverse farming contexts. Full article

Umbilical cord mesenchymal stem cells (UCMSCs)-derived small extracellular vehicles (sEVs) are reported to offer therapeutic effects in regenerative medicine, but they lack safety and biodistribution profiles to support smooth translation at the clinical stage and regulatory requirements. Our study aimed to determine the safety and biodistribution profile in a healthy animal model before application in the metabolic syndrome model. Method: Healthy male Sprague Dawley (SD) rats were given an intravenous (IV) injection of normal saline (control group) or pooled fetal UCMSCs-derived sEVs (treated group) every three weeks for 90 days. Morbidity and mortality observation (daily), physical measurements (weekly), selected serum biochemistry (every three weeks), and hematology (every three weeks) were performed for 90 days. Acute toxicity (on day 14) and sub-chronic toxicity (on day 90) were assessed for gross necropsy, relative organ weight, and histopathological assessment of lungs, liver, spleen, kidney, and lymph nodes. Separately, a biodistribution study was conducted with the sEVs preparations labeled with PKH26 fluorescent dye, given intravenously to the rats. The organs were harvested 24 h post-injection. There were no drastic changes in either group’s morbidity or mortality, physical, hematological, and biochemistry evaluation. The histopathological assessment concluded moderate (focal) inflammation in the treated group’s kidneys and signs of recovery from the inflammation and vascular congestion in the liver. A biodistribution study revealed a higher accumulation of sEVs in the spleen. Multiple IV injections of the pooled fetal UCMSCs-derived sEVs in healthy male SD rats were deemed safe. The sEVs were abundantly distributed in the spleen 24 h post-injection. Full article

Expressive imitation in the performing arts is typically trained through animal behavior imitation, aiming not only to reproduce action trajectories but also to recreate rhythm, style and emotional states. However, evaluation of such animal imitation behaviors relies heavily on teachers’ subjective judgments, lacking structured criteria, exhibiting low inter-rater consistency and being difficult to quantify. To enhance the objectivity and interpretability of the scoring process, this study develops a machine learning and structured pose data-based auxiliary evaluation framework for imitation quality. The proposed framework innovatively constructs three types of feature sets, namely baseline, ablation, and enhanced, and integrates recursive feature elimination with feature importance ranking to identify a stable and interpretable set of core structural features. This enables the training of machine learning models with strong capabilities in structured modeling and sensitivity to informative features. The analysis of the modeling results indicates that temporal–rhythm features play a significant role in score prediction and that only a small number of key feature values are required to model teachers’ ratings with high precision. The proposed framework not only lays a methodological foundation for standardized and AI-assisted evaluation in performing arts education but also expands the application boundaries of computer vision and machine learning in this field. Full article

Background/Objective: The Rs1 exon-1-del rat (Rs1KO) XLRS model shows normal retinal development until postnatal day 12 (P12) when small cystic spaces start to form in the inner nuclear layer. These enlarge rapidly, peak at P15, and then collapse by P19. These events overlap with eye opening at P12–P15. We investigated whether new light-driven retinal activity could contribute to the appearance and progression of schisis cavities in this rat model of XLRS disease. Methods: For dark rearing (D/D), mating pairs of Rs1KO strain were raised in total darkness in a special vivarium at UC Davis. When pups were born, they were maintained in total darkness, and eyes were collected at P12, P15, and P30 (n = 3/group) for each of the D/D and cyclic light-reared 12 h light–12 h dark (L/D) Rs1KO and wild-type (WT) littermates. Eyes were fixed, paraffin-embedded, and sectioned. Tissue morphology was examined by H&E and marker expression of retinoschisin1 (Rs1), rhodopsin (Rho), and postsynaptic protein 95 (Psd95) by fluorescent immunohistochemistry. H&E-stained images were analyzed with ImageJ version 1.54h to quantify cavity size using the “Analyze Particles” function. Results: Small intra-retinal schisis cavities begin to form by P12 in the inner retina of both D/D and L/D animals. Cavity formation was equivalent or more pronounced in D/D animals than in L/D animals. We compared Iba1 (activation marker of immune cells) distribution and found that by P12, when schisis appeared, Iba1⁺ cells had accumulated in regions of schisis. Iba1⁺ cells were more abundant in Rs1KO animals than WT animals and appeared slightly more prevalent in D/D- than L/D-reared Rs1KO animals. We compared photoreceptor development using Rho, Rs1, and Psd95 expression, and these were similar; however, the outer segments (OSs) of D/D animals with Rho labeling at P12 were longer than L/D animals. Conclusions: The results showed that cavities formed at the same time in D/D and L/D XLRS rat pups, indicating that the timing of schisis formation is not light stimulus-driven but rather appears to be a result of developmental events. Cavity size tended to be larger under dark-rearing conditions in D/D animals, which could be due to the decreased rate of phagocytosis by the RPE in the dark, allowing for continued growth of the OSs without the usual shedding of the distal tip, a key mechanism behind dark adaptation in the retina. These results highlight the complexity of XLRS pathology; however, we found no evidence that light-driven metabolic activity accounted for schisis cavity formation. Full article