Search Results (2,649)

Sustainable agricultural development requires regional agricultural systems to balance output growth, resource efficiency, ecological protection, and long-term resilience. In mountainous and ecologically sensitive regions, identifying the development constraints and statistically derived marginal contribution thresholds of agriculture is essential for promoting green transformation and sustainable land use. Taking Yunnan Province, China, as a representative plateau mountainous agricultural region, this study uses provincial annual data from 1990 to 2023 to quantitatively identify the key drivers and threshold characteristics of agricultural development under multidimensional constraints. A multidimensional indicator system was constructed covering fiscal and investment support, agricultural production inputs, rural infrastructure, and labor and population conditions. Ridge regression was employed to address multicollinearity among explanatory variables, Bootstrap approximate inference was used to improve the robustness of coefficient estimation, and the SHAP interpretation framework was introduced to rank key driving factors and identify marginal contribution thresholds. By integrating ridge regression, Bootstrap approximate inference, SHAP-based contribution ranking, and threshold identification, the proposed framework advances prior agricultural sustainability studies by linking coefficient-based factor analysis with interpretable marginal contribution thresholds under conditions of high multicollinearity and multidimensional resource constraints. The results show that agricultural development in Yunnan is characterized by multidimensional resource and infrastructure constraints. Rural electricity consumption, total reservoir storage capacity, fixed asset investment in agriculture, forestry, animal husbandry and fisheries, local public fiscal budget expenditure, and agricultural population generally act as positive supporting factors. Rural electricity consumption is the most stable and core driver across the aggregate and three sectoral models. In contrast, pesticide and fertilizer inputs show significant negative associations in most models, suggesting that future agricultural development in Yunnan is unlikely to be sustainably supported by continued expansion of high-intensity chemical inputs. Sectoral heterogeneity is also evident: agriculture and animal husbandry are more dependent on energy, water resources, and mechanization, whereas forestry shows a more distinct operational structure. The SHAP dependence analysis identifies several statistically derived marginal contribution thresholds, including rural electricity consumption of approximately 6.055 billion kWh, total reservoir storage capacity of approximately 10.395 billion m³, total agricultural machinery power of approximately 19.8324 million kW, pesticide use of approximately 37,500 tons, and fertilizer application of approximately 1.5238 million tons. These values should be interpreted as empirical transition points in the modeled marginal contributions rather than definitive biophysical ecological limits. They indicate that the sustainability-related constraint structure of agricultural development in Yunnan is not a single output ceiling but a composite interval shaped by infrastructure support capacity, factor allocation conditions, and the declining marginal contribution of high-intensity chemical inputs. The findings provide directional quantitative evidence for sustainable agricultural governance, agricultural green transformation, and differentiated policy discussion in mountainous agricultural regions and offer reference implications for advancing SDG 2 and SDG 15 through the coordination of food-related production, resource use efficiency, and ecosystem conservation. The identified thresholds should be interpreted as model-derived marginal contribution transition points rather than operational policy cutoffs or directly enforceable ecological standards. Full article

Accurate beef cattle body measurement data are crucial for growth assessment, phenotypic analysis, breeding management, and precision livestock farming. Traditional manual measurements are labor-intensive, time-consuming, and likely to cause stress in animals, making it difficult to meet the demands of large-scale livestock farming. This paper employs a structured systematic literature review method, in accordance with the PRISMA 2020 guidelines, to summarize research progress in vision-based beef cattle body measurement. This paper focuses on reviewing technical approaches such as 2D image-based measurement, 3D measurement using RGB-D and LiDAR, and multi-view fusion. It analyzes key technologies including image segmentation, keypoint detection, point cloud processing, 3D reconstruction, and geometric calculations, and compares the advantages and disadvantages of different methods in terms of measurement accuracy, robustness, cost, and farm applicability. The results indicate that 2D image-based methods are low-cost and flexible to deploy but have limited expressiveness for 3D body measurement parameters; RGB-D and LiDAR methods can provide spatial information but are affected by point cloud noise, occlusion, equipment costs, and data processing complexity; multi-view fusion can improve the completeness of body surface information but places high demands on calibration, registration, and system integration. Current research still faces challenges such as a lack of public datasets, inconsistent annotation standards, uncertainty regarding ground truth, insufficient cross-ranch generalization validation, and limited practical applications. Future research should focus on developing standardized datasets, conducting cross-scenario validation, advancing multimodal perception, creating lightweight models, and applying edge computing to drive the evolution of visual body measurement toward continuous monitoring and intelligent decision-making. Full article

Background: This study focuses on developing a model of a non-healing wound that recapitulates the pathogenesis of the corresponding human pathology. Methods: A non-healing wound was modeled in mice with streptozotocin-induced diabetes. The following parameters were assessed: re-epithelialization, epidermal hypertrophy, wound contraction, relief index, angiogenesis, and granulation tissue maturation. These parameters were compared between diabetic mice and healthy controls. Results: The proposed model demonstrated a significant delay in regenerative processes compared to healthy animals. Conclusions: These findings support the relevance of this model to human pathology and indicate that it may be applicable for preclinical studies of drugs aimed at promoting wound regeneration. Full article

Brain-derived neurotrophic factor (BDNF) is one of the most pleiotropic signaling molecules in mammalian biology, regulating processes ranging from neuronal survival and synaptic plasticity to metabolic homeostasis. Under physiological conditions, BDNF expression is tightly regulated; however, it may be disrupted by a variety of adverse factors, including chronic psychological stress, sleep deprivation, oxidative stress, inflammation, aging, and metabolic imbalance. Prolonged exposure to any of these factors can chronically reduce BDNF levels, contributing to numerous disorders whose systemic consequences remain difficult to define conclusively. This uncertainty arises because the available evidence is drawn from heterogeneous sources including many species, wild-type and various gene-knockout models, and pharmacological studies of differing specificity—yielding findings that are often inconsistent and difficult to compare. Consequently, the full spectrum of multisystemic effects resulting from long-term partial BDNF deficiency remains incompletely characterized. The SD-BDNFtm1sage rat line, developed by SAGE/Envigo/Inotiv using zinc finger nuclease technology, was created to fill this gap. Sprague–Dawley rats with a heterozygous genotype retain one functional allele of the Bdnf gene, resulting in a partial, permanent reduction in BDNF expression that persists throughout life. This chronic and moderate BDNF deficiency allows the animal to survive but is insufficient to maintain normal homeostasis, disrupting many physiological systems and behavioral responses. This review summarizes findings from studies using the SD-BDNFtm1sage rat line and shows that its phenotypic spectrum—susceptibility to mental disorders, sleep disturbances, metabolic abnormalities, altered nociception, and impaired neuromuscular adaptation—closely reflects the multisystemic consequences of chronic BDNF deficiency. This broad relevance makes the model particularly useful for research with potential medical applications. Full article

The rising prevalence of chronic kidney disease represents a major global health burden. Limitations of current renal replacement therapies, including donor organ shortages, rejection, and dialysis-related complications, underscore the need for innovative treatment options. This narrative review assesses the feasibility of bioengineered kidneys as an alternative to current treatments by discussing advances in decellularization, recellularization, and the transplantation of cell-on-scaffold kidneys. We propose that the development of functional bioengineered kidneys follows a hierarchical, staged process, in which vascular patency is the primary prerequisite for graft survival, followed by partial restoration of glomerular filtration, with complete tubular function remaining the final and most challenging milestone. Perfusion-based whole-organ decellularization has made significant progress in preserving the extracellular matrix, enabling the production of acellular human kidney scaffolds. However, complete recellularization of whole kidneys has not yet been achieved. Nevertheless, partially repopulated kidney scaffolds have been shown to withstand physiological blood pressure, produce urine, and exhibit filtration in large-animal models. Complete endothelial coverage of the vascular network proved essential for preventing thrombosis after transplantation. Current work on bioengineered kidneys shows promising results regarding feasibility for clinical application. It is important to note that most of the included studies are proof-of-concept, characterized by small sample sizes and short observation periods. Although these findings are crucial for further research, they cannot be generalized, and larger trials are recommended. In addition to cell-on-scaffold kidneys, 3D bioprinting is a promising technique that could eliminate the need for donor scaffolds. Full article

Commonly occurring polychlorinated biphenyls (PCBs) in the environment have been linked to a broad range of adverse toxicological effects in both animals and humans. In this study, in vitro, in silico, and in vivo models were used to investigate the surface interactions of PCBs with green-engineered clays (GECs). Earlier studies showed that these GECs significantly reduced the toxicities of important planar aromatic chemicals such as benzene and aflatoxin B₁ along with ochratoxin A, a chlorinated aromatic chemical. The overall objective for this study was to show that GECs could tightly adsorb PCBs, resulting in a decrease in toxicity of a commercial PCB mixture (Aroclor 1260). Gastrointestinal pH and temperature were simulated in vitro, and the clay surface binding interactions of six PCBs were characterized using isothermal analyses. Molecular dynamics (MD) simulations were employed to provide atomistic understanding into PCB congener interactions with parent and chlorophyll-amended clays. To confirm the ability of GECs to protect a living organism, Aroclor 1260 was investigated using a well-established hydra bioassay. According to simulations, coplanar PCBs had an increased probability of binding to parent clay compared to non-coplanar ones, in line with experiments, due to their ability to lay flat on the clay surface. Chlorophyll amendments enhanced binding of all PCBs according to both experiments and computations. Within the simulations, chlorophyll amendments facilitated both coplanar as well as non-coplanar PCBs to directly bind to the clay and additionally interact with chlorophyll amendments, as well as to bind to chlorophyll amendments without necessarily interacting with the clay. Aroclor 1260 caused irreversible damage to hydra. At 0.05% inclusion, parent clay offered limited protection (20%) while GECs offered 55% to 65% protection, showing the advantage of GECs over parent clays. The findings of this study indicate that edible GECs adsorb PCBs, with the highest sorption associated with the coplanar congeners. Further studies are warranted to determine the application of GECs as potential disaster-response supplements in the diet to reduce the bioavailability of PCBs from contaminated food and water, especially following floods and other emergencies. Full article

Periprosthetic joint infection (PJI) remains a major clinical challenge after total joint arthroplasty because of its association with prolonged antimicrobial therapy, repeated surgery, implant failure, functional disability, and substantial socioeconomic burden. Current strategies, including systemic antibiotics, debridement with implant retention, staged revision, and antibiotic-loaded cement spacers, remain indispensable but are limited by mature biofilm tolerance, protected microbial reservoirs, insufficient local drug penetration, persistent inflammation, and compromised periprosthetic bone repair. Increasing evidence indicates that PJI is not merely bacterial colonization of an implant surface, but a dynamic prosthetic interface disorder involving biofilm persistence, immune dysregulation, inflammatory osteolysis, and failed osseointegration. This review summarizes recent advances in anti-infective prosthetic interface design, emphasizing the transition from passive antibacterial coatings toward multifunctional immuno-antibacterial osseointegrative systems. The pathogenic basis of PJI is first discussed, including conditioning film formation, bacterial adhesion, biofilm maturation, protected reservoirs, immune evasion, and osteolysis. Current clinical management limitations are then evaluated, followed by emerging biomaterial strategies, including anti-adhesive and contact-killing surfaces, active antimicrobial coatings, mature biofilm disruption, biological antibiofilm therapies, smart infection-responsive delivery systems, and osteoimmunomodulatory interfaces. Particular attention is given to balancing early antibacterial activity with cytocompatibility, immune resolution, angiogenesis, mechanical durability, and long-term osseointegration. Finally, key translational barriers are highlighted, including load-bearing and tribological constraints, insufficiently standardized mature biofilm and animal models, limited clinical evidence for advanced smart materials, manufacturing reproducibility, sterilization compatibility, regulatory complexity, and application-specific clinical readiness. Future anti-PJI interfaces should evolve beyond unidirectional bacterial killing toward stage-specific systems integrating biofilm control, immune restoration, vascularized bone regeneration, and durable mechanical performance. Full article

Influenza viruses continue to pose a significant threat to both animal and public health due to their rapid evolution and the frequent emergence of antiviral resistance. Host-directed antiviral (HDA) strategies, which target host factors essential for viral replication, may represent an alternative to conventional virus-targeting approaches. However, the identification of reliable and therapeutically actionable host targets remains a major challenge, primarily due to the complexity and context dependency of host–virus interactions. Recent advancements in multi-omics technologies, including functional genomics, transcriptomics, and proteomics, have facilitated the systematic characterization of host factors involved in influenza virus infection. These methodologies have unveiled intricate regulatory networks that govern viral replication and host immune responses. Nonetheless, translating large-scale datasets into biologically meaningful targets necessitates robust integrative frameworks. In this context, artificial intelligence (AI) and machine learning methods offer powerful tools for data integration, target prioritization, and predictive modeling. In this Review, we summarize current insights into host factors that regulate influenza virus infection and discuss how multi-omics and AI-driven approaches are expediting host target discovery. Furthermore, we highlight the potential of these strategies to enhance antiviral development while addressing key challenges related to specificity, safety, and translational application. Collectively, these advancements lay a foundation that may support the rational design of next-generation host-directed antivirals. Full article

Camel milk is increasingly recognized as a premium functional food, attributed to its rich nutraceutical compounds. Recent research has concentrated on the nanoscale extracellular vesicles derived from camel milk (CM-EVs), which exhibit distinctive properties. This review examines the methodologies for isolating and characterizing CM-EVs, alongside their potential health benefits in functional foods and nutraceuticals. CM-EVs have the capacity to safeguard functional proteins, noncoding RNAs, and bioactive lipids from degradation within the gastrointestinal tract, rendering them particularly suitable for incorporation into infant formulas, adult dietary supplements, and nutraceuticals targeting chronic inflammatory and metabolic disorders. Preclinical models indicate that CM-EVs can mitigate oxidative stress, enhance intestinal barrier integrity, and modulate gut microbiota, thereby contributing to the reduction in colonic injury and inflammation. Nonetheless, the majority of these findings are derived from laboratory and animal studies, highlighting a substantial deficiency in human clinical trials. Critical research gaps remain, necessitating further investigation into the elucidation of molecular mechanisms, assessment of long-term safety, evaluation of bioavailability, and compatibility with dairy processing techniques. This review underscores the significance of CM-EVs as bioactive food components and delineates research priorities, such as standardizing isolation methods, investigating food matrix integration, and providing translational evidence for their application in nutrition and preventive medicine. Full article

Since its inception in 2017, temporal interference stimulation (TIS) has attracted increasing attention as a novel neuromodulation approach with the potential to non-invasively target deep brain structures. As the field moves from initial biophysical validation toward broader experimental and translational applications, a macroscopic understanding of its developmental trajectory and thematic evolution is needed. In this study, we systematically mapped the scientific landscape of TIS research using bibliometric methods to characterize its knowledge structure, core themes, and emerging frontiers. The analysis shows that TIS research has expanded rapidly from foundational animal studies and biophysical mechanism validation toward computational head modeling, individualized electric field optimization, and early human applications. Current research is increasingly focused on cross-species scaling, stimulation dosimetry, comparative advantages over other neuromodulation techniques, precise targeting strategies, and potential physiological risks such as high-frequency conduction block. Overall, TIS is evolving from an exploratory biophysical concept into a promising but technically and physiologically complex neuromodulation tool. Overcoming current engineering and translational barriers, particularly through individualized modeling, rigorous optimization, and well-designed human studies, will be essential for establishing TIS as a reliable therapeutic intervention. Full article

Background/Objectives: African swine fever (ASF) is a highly lethal disease of domestic pigs and wild suids that continues to cause substantial economic losses worldwide. Despite recent progress in live attenuated ASF vaccine development, evidence supporting durable protection under repeated exposure conditions representative of endemic settings remains limited. Here, we assessed the long-term safety and protective efficacy of a live attenuated ASFV-G-ΔI177L/ΔLVR vaccine using a repeated-challenge experimental design intended to model re-exposure in ASF-endemic regions. Methods: Vaccinated pigs were subjected to homologous virulent ASF virus challenges at multiple intervals, including repeated challenges (three sequential inoculations) and single challenges administered at 8 and 12 weeks post-vaccination. Results: Across all challenge regimens, vaccinated animals survived and remained clinically healthy, including those receiving three challenges, supporting sustained protection under repeated exposure pressure. Animals challenged at 8 or 12 weeks post-vaccination likewise exhibited complete survival, indicating maintained efficacy through at least 12 weeks. No vaccine-associated adverse clinical outcomes were detected over the study period, and post-challenge viral shedding was minimal. Conclusions: Overall, these data demonstrate that the candidate live attenuated ASF vaccine provides excellent protective efficacy and confers sustained protection against homologous ASF virus infection. This result is expected to be equally applicable under repeated exposure conditions in regions with unstable ASF biosecurity, making it a sufficiently promising model experiment for field application in ASF epidemic areas. However, this is still a vaccine variant, and further studies are planned to evaluate its genomic stability and transmissibility. Full article

This review analyses and logically structures modern intelligent sensor technologies in the context of animal husbandry, feed production, and veterinary medicine. The main research discussed in the article focuses on machine learning based on modern neural network models, computer vision, and sensor systems that are transforming the methods for assessing the health, behavior, and nutrition of farm animals. The first part examines modern approaches to quality control and optimization of mineral and vitamin premixes, including visual inspection using visual sensors and neural networks. Key roles are played by precise dosing, component stability (minerals, vitamins), and the transition to more bioefficient organic forms of micronutrients to reduce environmental impact. Improvements in feed and premix production are analyzed, including automation, energy management, and the use of machine learning for non-destructive quality control, defect detection, mixing homogeneity assessment, and vitamin stability prediction. The second part analyzes methods for animal location and behavior detection. This article presents computer vision-based systems, including modifications of YOLO, for automatically tracking and classifying key behavioral patterns (lying down, standing, feeding, and aggression) in cattle and pigs, even in crowded conditions. It also discusses the use of ultra-wideband (UWB) systems and accelerometers combined with machine learning for high-precision positioning and detection of specific behavioral anomalies, such as lameness and playfulness. The third section focuses on the application of machine learning in veterinary diagnostics, including the automated interpretation of medical images (X-ray, ultrasound, and MRI) as sensor data streams for the diagnosis of cardiovascular, oncological, and orthopedic diseases in farm and small animals. Furthermore, the article examines the use of machine learning models for proactive disease diagnosis in farm animals and poultry based on multimodal data and image analysis. Considerable attention is given to methods and tools for radiometric diagnosis of animal diseases at an early stage using microwave sensors, as well as laser therapy and surgery in veterinary medicine. The review concludes that the integration of intelligent systems enables a transition to data-driven livestock management, significantly improving animal welfare and, consequently, the efficiency and sustainability of agricultural production. Full article

Multiple Myeloma (MM) is a hematological malignancy characterized by the clonal proliferation and survival of neoplastic plasma cells (PCs) within the bone marrow (BM), where disease progression is critically supported by interactions with the BM tumor microenvironment (TME). Despite significant advances in therapeutic strategies, MM remains incurable, underscoring the need for improved preclinical models to better understand the disease biology and therapeutic response. This review summarizes current and emerging MM treatment approaches and critically examines the development of models designed to more accurately recapitulate interactions between MM-PCs and the surrounding BM niche. We describe established and emerging modeling platforms, with emphasis on advanced three-dimensional (3D) culture systems and highlight their unique contributions to the preclinical assessment of both existing and novel therapies. The advantages of 3D models, including in vitro and in silico systems, over traditional two-dimensional (2D) models are discussed, alongside a comparative evaluation of scaffold-free and scaffold-based approaches. In addition, the benefits and recent advances in the customization of BM niche simulation using microfluidic technologies and organ-on-a-chip platforms are reviewed. The application of 3D models in MM research is increasingly enabling the study of disease pathogenesis, progression, drug resistance and precision-medicine approaches (informed by biomarker discovery). Although standardized preclinical approaches for evaluating MM therapeutics are currently lacking, the growing imperative to reduce reliance on preclinical animal models highlights the importance of alternate systems. Consequently, the development and adoption of physiologically relevant models that accurately recapitulate MM-PC interactions with the BM TME will be critical for advancing future therapeutic strategies in MM. Full article

The efficacy of enzyme therapy is limited by their poor stability under physiological conditions. Thermostable enzymes, derived from extremophilic organisms or generated by advanced protein engineering, offer a revolutionary solution to this long-standing challenge. They are widely used in industrial biocatalysis. Their therapeutic applications are poorly investigated and spread across diverse disciplines. While most applications are in the preclinical stages, emerging evidence from animal models demonstrates proof-of-concept for thermostable antioxidant enzymes in cardiovascular, neurodegenerative, and inflammatory diseases. This review critically assesses the translational landscape, distinguishing between established therapeutic enzymes (e.g., asparaginase, PEGylated SOD) and emerging experimental candidates. This narrative review consolidates existing knowledge about thermostable enzyme engineering and their emerging functions as molecular therapies, particularly in oxidative stress-related diseases. This review synthesizes recent advances in structural biology, computational protein design, biomaterials engineering, and translational antioxidant strategies, highlighting how breaking down disciplinary barriers is accelerating the development of sustainable and self-regenerating antioxidant platforms. By integrating molecular precision with systems-level therapeutic design, engineered thermostable antioxidant enzymes exemplify the future of biological development, where multidisciplinary collaboration drives innovation against oxidative stress-driven pathologies. Engineered thermostable enzymes provide a versatile basis for next-generation therapeutics, with the potential to address medical needs through improved stability, targeted activity, and multifunctional design. Full article

Ex vivo liver perfusion (EVLP) sustains human or large animal livers outside the body under near-physiological conditions, enabling functional monitoring for lactate clearance, bile production, and oxygen consumption and allowing targeted therapeutic interventions. Originally developed to optimize donor grafts for transplantation, EVLP has evolved into a powerful translational research platform bridging preclinical discovery and early clinical translation. This review discusses EVLP as a platform for gene therapy, immunotherapy, pharmacology, and personalized medicine, with particular emphasis on gene- and immune-based interventions as mechanistically mature exemplars. We consolidate advances in pharmacological testing and toxicity modeling, viral and non-viral gene delivery, genome engineering, and immunomodulation using perfused livers. We further describe emerging applications, including autologous EVLP pathways for organ-confined therapy, ex vivo liver surgery, and bioengineering strategies such as biliary organoid repair, RNA interference, and mitochondrial transfer. We highlight how these applications align with a paradigm shift in biomedical research, including the NIH’s recent initiative to prioritize human-based experimental models over animal-only studies. By leveraging transplant-declined or surgically resected organs that would otherwise be unused, ex vivo perfusion bridges the gap between pre-clinical testing and clinical practice, enabling real-time evaluation of interventions in functional human tissue. We discuss both the scientific opportunities afforded by EVLP and the technical, biosafety, and ethical challenges that must be addressed to enable responsible clinical translation. Full article