Search Results (7,382)

Subclinical mastitis in dairy cows poses a significant challenge to the dairy industry, leading to reduced milk yield, altered milk composition, compromised animal health, and substantial economic losses for dairy farmers. A model based on the XGBoost algorithm, optimized with an Improved GOOSE Optimization Algorithm (IGOOSE), is presented in this work as an innovative approach for predicting subclinical mastitis in order to overcome these problems. The Dairy Herd Improvement (DHI) records of 4154 cows served as the model’s original foundation. A total of 3232 samples with 21 characteristics made up the final dataset, following extensive data cleaning and preprocessing. To overcome the shortcomings of the original GOOSE algorithm in intricate, high-dimensional problem spaces, three significant enhancements were made. First, an elite inverse strategy was implemented to improve population initialization, enhancing the algorithm’s balance between global exploration and local exploitation. Second, an adaptive nonlinear control factor was added to increase the algorithm’s stability and convergence speed. Lastly, a golden sine strategy was adopted to reduce the risk of premature convergence to suboptimal solutions. According to experimental results, the IGOOSE-XGBoost model works better than other models in predicting subclinical mastitis, especially when it comes to recognizing somatic cell scores, which are important markers of the illness. This study provides a strong predictive framework for managing the health of dairy cows, allowing for the prompt identification and treatment of subclinical mastitis, which enhances the efficiency and quality of milk supply. Full article

Mastitis is a significant challenge in the buffalo industry, affecting both milk production and animal health and resulting in economic losses. This study presents the first fully automated AI-driven thermal imaging system integrated with robotic milking, specifically developed for the real-time, non-invasive monitoring of udder health in Italian Mediterranean buffalo. Unlike traditional approaches, the system leverages the synchronized acquisition of thermal images during milking and compensates for environmental variables through a calibrated weather station. A transformer-based neural network (SegFormer) segments the udder area, enabling the extraction of maximum udder skin surface temperature (USST), which is significantly correlated with somatic cell count (SCC). Initial trials demonstrate the feasibility of this approach in operational farm environments, paving the way for scalable, precision diagnostics of subclinical mastitis. This work represents a critical step toward intelligent, automated systems for early detection and intervention, improving animal welfare and reducing antibiotic use. Full article

The ship waterjet propulsion system is a crucial power unit for high-performance vessels, and the operational state of its core component, the waterjet pump, is directly related to navigation safety and mission reliability. To enhance the intelligence and accuracy of pump fault diagnosis, this paper proposes a novel diagnostic framework that integrates a supervised autoencoder (SAE) with a large language model (LLM). This framework first employs an SAE to perform task-oriented feature learning on raw vibration signals collected from the pump’s guide vane casing. By jointly optimizing reconstruction and classification losses, the SAE extracts deep features that both represent the original signal information and exhibit high discriminability for different fault classes. Subsequently, the extracted feature vectors are converted into text sequences and fed into an LLM. Leveraging the powerful sequential information processing and generalization capabilities of LLM, end-to-end fault classification is achieved through parameter-efficient fine-tuning. This approach aims to avoid the traditional dependence on manually extracted time-domain and frequency-domain features, instead guiding the feature extraction process via supervised learning to make it more task-specific. To validate the effectiveness of the proposed method, we compare it with a baseline approach that uses manually extracted features. In two experimental scenarios, direct diagnosis with full data and transfer diagnosis under limited-data, cross-condition settings, the proposed method significantly outperforms the baseline in diagnostic accuracy. It demonstrates excellent performance in automated feature extraction, diagnostic precision, and small-sample data adaptability, offering new insights for the application of large-model techniques in critical equipment health management. Full article

The widespread use of pesticides in modern agriculture has significantly enhanced food production by managing pests and diseases; however, their degradation in soil can lead to unintended consequences for soil fertility and nutrient cycling. This review explores the mechanisms of pesticide degradation, both abiotic and biotic, and the soil factors influencing these processes. It critically examines how degradation products impact soil microbial communities, organic matter decomposition, and key nutrient cycles, including nitrogen, phosphorus, potassium, and micronutrients. This review highlights emerging evidence linking pesticide residues with altered enzymatic activity, disrupted microbial populations, and reduced nutrient bioavailability, potentially compromising soil structure, water retention, and long-term productivity. Additionally, it discusses the broader environmental and agricultural implications, including decreased crop yields, biodiversity loss, and groundwater contamination. Sustainable management strategies such as bioremediation, the use of biochar, eco-friendly pesticides, and integrated pest management (IPM) are evaluated for mitigating these adverse effects. Finally, this review outlines future research directions emphasizing long-term studies, biotechnology innovations, and predictive modeling to support resilient agroecosystems. Understanding the intricate relationship between pesticide degradation and soil health is crucial to ensuring sustainable agriculture and food security. Full article

This paper presents WaveCORAL-DCCA, an unsupervised domain adaptation (UDA) framework specifically developed to address data distribution shifts and operational variabilities (OVs) in rotor fault diagnosis. The framework introduces the novel integration of discrete wavelet transformation for robust time–frequency feature extraction and an enhanced deep canonical correlation analysis (DCCA) network with correlation alignment (CORAL) loss for superior domain-invariant representation learning. This combination enables more effective alignment of source and target feature distributions without requiring any labelled data from the target domain. Comprehensive validation on both experimental and numerically simulated rotor datasets across three health conditions—i.e., normal, unbalanced, and misaligned—demonstrates that WaveCORAL-DCCA achieves an average diagnostic accuracy of 95%. Notably, it outperforms established UDA benchmarks by at least 5–17% in cross-domain scenarios. These results confirm that WaveCORAL-DCCA provides robust generalisation across machines, fault severities, and operational conditions, even with scarce target domain samples, offering a scalable and practical solution for industrial rotor fault diagnosis. Full article

Background and Objectives: Sarcopenic obesity, or the coexistence of sarcopenia and obesity, carries an additional load of health risks, including functional decline and metabolic disorders. Despite its increasing importance, data on Korean adults’ prevalence and risk factors are poor. The objective of this study was to estimate the prevalence of sarcopenic obesity, sarcopenia, and obesity to identify factors associated with each condition using the most recent nationally representative data. Materials and Methods: This study analyzed data from 4332 adults aged ≥ 40 years who participated in the 2022–2023 Korea National Health and Nutrition Examination Survey (KNHANES). Sarcopenia was defined using the appendicular skeletal muscle index (SMI) via bioelectrical impedance analysis (BIA), and obesity by waist circumference per Korean criteria. Participants were categorized into four body composition groups. Complex sample logistic regression was used to identify factors independently associated with each condition. Results: The prevalence rates of sarcopenic obesity, sarcopenia-only, and obesity-only were 1.9%, 14.4%, and 35.5%, respectively. Sarcopenic obesity was significantly more common among older women with low education level, poor subjective health, diabetes, and low HDL-C. They were associated with older age, lower physical activity, lower education level, past smoking, and poor health condition. Obesity was associated with male sex, diabetes, hypertension, dyslipidemia, and moderate-to-poor perceived health. Conclusions: Sarcopenic obesity, while less prevalent, is relatively uncommon and represents a high-risk phenotype associated with metabolic and functional deficits. These results highlight the importance of identifying vulnerable subgroups and implementing targeted strategies that address both muscle loss and adiposity in aging Korean adults. Full article

Insect pests cause severe damage and yield losses to many agricultural crops globally. The use of chemical pesticides on agricultural crops is not recommended because of their toxic effects on the environment and consumers. In addition, pesticide toxicity reduces soil fertility, poisons ground waters, and is hazardous to soil biota. Therefore, applications of entomopathogenic nematodes (EPNs) and plant growth-promoting rhizobacteria (PGPR) are an alternative, eco-friendly solution to chemical pesticides and mineral-based fertilizers to enhance plant health and promote sustainable food security. This review focuses on the biological and ecological aspects of these organisms while also highlighting the practical application of molecular communication approaches in developing a novel plant health product. This insight will support this innovative approach that combines PGPR and EPNs for sustainable crop production. Several studies have reported positive interactions between nematodes and bacteria. Although the combined presence of both organisms has been shown to promote plant growth, the molecular interactions between them are still under investigation. Integrating molecular communication studies in the development of a new product could help in understanding their relationships and, in turn, support the combination of these organisms into a single plant health product. Full article

Eutrophication has become the primary water quality issue for most of the freshwater and coastal marine ecosystems in the world. Caused by excessive nitrogen (N) and phosphorus (P) inputs, it has a significant impact on aquatic ecosystems, resulting in algal blooms, oxygen depletion, and biodiversity loss. Zeolites have been identified as effective adsorbents for removal of these pollutants, improving water quality and ecosystem health. Kinetic and isotherm adsorption experiments were conducted to examine the adsorption efficiency of four zeolites of various origins (Greek, Slovakian, Turkish, and Bulgarian) and a specific modification (ZeoPhos) to determine the most effective material for N and P removal. The aim of the study is to discover the best zeolite for chemical adsorption in eutrophic waters by comparing their adsorption capacities and pollutant removal efficiencies along with SEM, TEM, and X-RD spectrographs. Slovakian ZeoPhos has been identified as the best-performing material for long-term and efficient water treatment systems for eutrophication management. Full article

Background and Objective: Adverse pathology to high-risk prostate cancer (PCa) after radical prostatectomy (upgrading) poses a threat to risk stratification and treatment planning. The impact on sexual function, urinary continence, and health-related quality of life (HRQOL) remains unclear. Methods: From 2004 to 2024, 4189 patients with preop low-/intermediate-risk PCa (Gleason score 6 or 7a, PSA ≤ 20 ng/mL) underwent radical prostatectomy at our department and were analyzed. Primary endpoint was HRQOL, erectile function, and urinary continence. Secondary endpoint was rate of salvage therapies and biochemical-free survival. Propensity score matching was performed using “operative time”, “robot-assisted surgery”, “blood loss”, “nerve-sparing surgery”, “age”, and “BMI” to represent comparable surgical approach. Median follow-up was 39 months (Interquartile-range (IQR) 15–60). Key Findings and Limitations: Patients who were upgraded to high-risk PCa showed a higher rate of postoperative radiotherapy and androgen-deprivation therapy compared to patients who were not upgraded (21% vs. 7%, p < 0.001; 9% vs. 3%, p = 0.002). Five-year biochemical recurrence-free survival was 68% in the upgrading group vs. 84% in the no-upgrading group (p < 0.001). We saw no difference in patient-reported HRQOL, urinary continence, or erectile function. Multivariable analysis showed that postoperative upgrading was a significant risk for not achieving good overall HRQOL (OR: 0.77, 95% CI: 0.61–0.97, p = 0.028) during the follow-up. Conclusions and Clinical Implications: Although postoperative upgrading to high-risk PCa leads to worse oncologic outcomes and higher salvage therapy rates, this study indicates that its impact on health-related quality of life is minimal and should not deter a cautious approach to radical prostatectomy. Full article

Heavy metal contamination in freshwater ecosystems poses persistent threats to aquatic organisms and public health. This study evaluates the transgenerational toxicity of cadmium chloride and copper sulfate on Culex pipiens, focusing on development, reproduction, and midgut histopathology over two successive generations. Larval bioassays showed cadmium chloride to be more toxic than copper sulfate, with early instars exhibiting higher sensitivity (LC₅₀ = 8.66 μg/L for Cd; 175.63 μg/L for Cu). Both metals significantly delayed larval and pupal development, reduced fecundity, and decreased egg hatchability in a dose-dependent manner. Histopathological examination revealed midgut epithelial degeneration, vacuolation, and brush border loss, with copper sulfate inducing more severe cytotoxicity. These findings confirm that sublethal, chronic metal exposure can impair physiological and reproductive traits across generations. Moreover, this study highlights the utility of mosquitoes as sensitive bioindicators of aquatic pollution, and underscores the long-term ecological implications of heavy metal contamination on vector dynamics and disease transmission. Full article

Helminth parasites of wild animals represent a major threat to the health of these animals, leading to significant losses in performance, health, and zoonotic implications. In some zoos, anthelmintics have traditionally been used to control these parasites, many of which are also zoonotic. Other actions, such as the removal of organic waste, have also been adopted. Few or no control measures are applied to free-ranging wild animals. Helminthophagous fungi are a promising biological alternative. When animals ingest fungal spores, they are excreted in their feces, where they trap and destroy helminth larvae and eggs, preventing and reducing the parasite load in the environment. Another alternative is to administer fungi by spraying them directly into the environment. This review aims to examine the use of helminthophagous fungi in the control of helminthiases in wild animals, highlighting their potential to minimize dependence on chemical treatments and promote sustainable animal breeding and production. There are many challenges to making this viable, such as environmental variability, stability of formulations, and acceptance of this new technology. These fungi have been shown to reduce parasite burdens in wild animals by up to 75% and can be administered through the animals’ feeding troughs. To date, evidence shows that helminthophagous fungi can reliably curb environmental parasite loads for extended periods, offering a sustainable alternative to repeated anthelmintic dosing. Their use has been linked to tangible gains in body condition, weight, and overall welfare in various captive and free-ranging wildlife species. Full article

Diabetes mellites (DM) is a chronic disease with increasing prevalence worldwide and multiple health implications. Among them, sarcopenia is a metabolic disorder characterized by loss of muscle mass and function. The two age-related diseases, DM and sarcopenia, share underlying pathophysiological pathways. This narrative literature review aims to provide an overview of the existing evidence on metabolomic studies evaluating DM associated with sarcopenia. Advancements in targeted and untargeted metabolomics techniques could provide better insight into the pathogenesis of sarcopenia in DM and describe their entangled and fluctuating interrelationship. Recent evidence showed that sarcopenia in DM induced significant changes in protein, lipid, carbohydrate, and in energy metabolisms in humans, animal models of DM, and cell cultures. Newer metabolites were reported, known metabolites were also found significantly modified, while few amino acids and lipids displayed a dual behavior. In addition, several therapeutic approaches proved to be promising interventions for slowing the progression of sarcopenia in DM, including physical activity, newer antihyperglycemic classes, D-pinitol, and genetic USP21 ablation, although none of them were yet validated for clinical use. Conversely, ceramides had a negative impact. Further research is needed to confirm the utility of these findings and to provide potential metabolomic biomarkers that might be relevant for the pathogenesis and treatment of sarcopenia in DM. Full article

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline, memory loss, and neuronal dysfunction. It is driven by the accumulation of amyloid-beta (Aβ) plaques, Tau protein hyperphosphorylation, oxidative stress, and neuroinflammation. Resveratrol (RSV) is a natural polyphenolic compound found in grapes, berries, and red wine that has garnered attention for its potential neuroprotective properties in combating AD. The neuroprotective effects of RSV are mediated through the activation of sirtuins (SIRT1), inhibition of Aβ aggregation, modulation of Tau protein phosphorylation, and the attenuation of oxidative stress and inflammatory responses. RSV also enhances mitochondrial function and promotes autophagy, which are important processes for maintaining neuronal health. Preclinical studies have demonstrated its efficacy in reducing Aβ burden, improving cognitive performance, and mitigating synaptic damage; however, challenges such as poor bioavailability, rapid metabolism, and limited blood–brain barrier penetration restrict its clinical applicability. Recent technological advances and selected modifications are being explored to overcome these limitations and enhance its therapeutic efficacy. This review summarizes the multifaceted neuroprotective mechanisms of RSV, the synergistic potential of natural compounds in enhancing neuroprotection, and the advancements in formulation strategies aimed at mitigating AD pathology. Leveraging the therapeutic potential of natural compounds represents a compelling paradigm shift for AD management, paving the way for future clinical applications. Full article

Down syndrome (DS), stemming from the triplication of human chromosome 21, results in intellectual disability, with early mid-life onset of Alzheimer’s disease (AD) pathology. Early interventions to reduce cognitive impairments and neuropathology are lacking. One modality, maternal choline supplementation (MCS), has shown beneficial effects on behavior and gene expression in neurodevelopmental and neurodegenerative disorders, including trisomic mice. Loss of basal forebrain cholinergic neurons (BFCNs) and other DS/AD relevant hallmarks were observed in a well-established trisomic model (Ts65Dn, Ts). MCS attenuates these endophenotypes with beneficial behavioral effects in trisomic offspring. We postulate MCS ameliorates dysregulated cellular mechanisms within vulnerable BFCNs, with attenuation driven by novel gene expression. Here, choline acetyltransferase immunohistochemical labeling identified BFCNs in the medial septal/ventral diagonal band nuclei of the basal forebrain in Ts and normal disomic (2N) offspring at ~11 months of age from dams exposed to MCS or normal choline during the perinatal period. BFCNs (~500 per mouse) were microisolated and processed for RNA-sequencing. Bioinformatic assessment elucidated differentially expressed genes (DEGs) and pathway alterations in the context of genotype (Ts, 2N) and maternal diet (MCS, normal choline). MCS attenuated select dysregulated DEGs and relevant pathways in aged BFCNs. Trisomic MCS-responsive improvements included pathways such as cognitive impairment and nicotinamide adenine dinucleotide signaling, among others, indicative of increased behavioral and bioenergetic fitness. Although MCS does not eliminate the DS/AD phenotype, early choline delivery provides long-lasting benefits to aged trisomic BFCNs, indicating that MCS prolongs neuronal health in the context of DS/AD. Full article

Background/Objectives: Feigning spectrum behavior (FSB) is the exaggeration, fabrication, or false imputation of symptoms. It occurs in compensable injury with great cost to society by way of loss of productivity and excessive costs. The aim of this study is to identify feigning by developing cut scores on the long and short forms (SF) of the Orebro Musculoskeletal Pain Screening Questionnaire (OMPSQ and OMPSQ-SF) and the Perceived Stress Scale (PSS and PSS-4). Methods: As part of pre-screening for a support program, 40 injured workers who had been certified unfit for work for more than 2 weeks were screened once with the OMPSQ and PSS by telephone by a mental health professional. A control sample comprised of 40 non-injured community members were screened by a mental health professional on four occasions under different aliases, twice responding genuinely and twice simulating an injury. Results: Differences between the workplace injured people and the community sample were compared using ANCOVA with age and gender as covariates, and then receiver operator characteristics (ROCs) were calculated. The OMPSQ and OMPSQ-SF discriminated (ρ < 0.001) between all conditions. All measures discriminated between the simulation condition and workplace injured people (ρ < 0.001). Intraclass correlation demonstrated the PSS, PSS-4, OMPSQ, and OMPSQ-SF were reliable (ρ < 0.001). Area Under the Curve (AUC) was 0.750 for OMPSQ and 0.835 for OMPSQ-SF for work-injured versus simulators. Conclusions: The measures discriminated between injured and non-injured people and non-injured people instructed to simulate injury. Non-injured simulators produced similar scores when they had multiple exposures to the test materials, showing the uniformity of feigning spectrum behavior on these measures. The OMPSQ-SF has adequate discriminant validity and sensitivity to feigning spectrum behavior, making it optimal for telephone screening in clinical practice. Full article