Search Results (23,878)

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

The composition of the gut and/or tumor microbiome has been intricately involved in the onset of carcinogenesis, tumor progression, therapy response, and patient outcomes in diverse solid cancers. The microbiome type, composition, and their metabolome have been functionally implicated in the multifarious cellular processes, transformation, proliferation, tumor immune evasion, cellular migration, etc. Despite such compelling evidence on the role of microbiome interactions in cancer, the realization of their role in neuroblastoma (NB), the deadly extracranial tumor in infants is few and fragmentary. This review comprehends the composition, diversity, and significance of microbiota in human health. Further, this review discusses the microbiota composition, their mode of action, and their signaling flow through and cellular processes in diverse cancers including NB. Precisely, this study for the first time has realized the functional relevance and clinical significance of the gut and tumor microbiome for NB. Interestingly, large cohort clinical and preclinical in vivo models of NB realized the following: gut microbiota predicts the risk for NB; postnatal (and or not maternal transmission) microbiome rearrangements; gut microbial effect on NB pathogenesis; tumor-altering gut microbial composition; microbial composition predicts treatment outcomes in NB; prebiotic remedies for stabilizing NB-associated microbial rearrangements; microbial composition in tumor-infiltrating microbiota predicts NB outcomes. Full article

Circadian rhythms are intrinsic 24 h cycles that regulate metabolic processes across multiple tissues, with skeletal muscle emerging as a central node in this temporal network. Muscle clocks govern gene expression, fuel utilisation, mitochondrial function, and insulin sensitivity, thereby maintaining systemic energy homeostasis. However, circadian misalignment, whether due to behavioural disruption, nutrient excess, or metabolic disease, impairs these rhythms and contributes to insulin resistance, and the development of obesity, and type 2 diabetes mellitus. Notably, the muscle clock remains responsive to non-photic cues, particularly exercise, which can reset and amplify circadian rhythms even in metabolically impaired states. This work synthesises multi-level evidence from rodent models, human trials, and in vitro studies to elucidate the role of skeletal muscle clocks in circadian metabolic health. It explores how exercise entrains the muscle clock via molecular pathways involving AMPK, SIRT1, and PGC-1α, and highlights the time-of-day dependency of these effects. Emerging data demonstrate that optimally timed exercise enhances glucose uptake, mitochondrial biogenesis, and circadian gene expression more effectively than time-agnostic training, especially in individuals with metabolic dysfunction. Finally, findings are integrated from multi-omic approaches that have uncovered dynamic, time-dependent molecular signatures that underpin circadian regulation and its disruption in obesity. These technologies are uncovering biomarkers and signalling nodes that may inform personalised, temporally targeted interventions. By combining mechanistic insights with translational implications, this review positions skeletal muscle clocks as both regulators and therapeutic targets in metabolic disease. It offers a conceptual framework for chrono-exercise strategies and highlights the promise of multi-omics in developing precision chrono-medicine approaches aimed at restoring circadian alignment and improving metabolic health outcomes. Full article

Background and Objectives: With the widespread integration of digital media into daily life, social media addiction (SMA) has become a growing concern for university students’ mental health. Based on attachment theory, this study examined how attachment anxiety and avoidance influence SMA through fear of negative evaluation (FNE) and loneliness. Methods: A sample of 400 Chinese university students completed the 16-item short version of the Experiences in Close Relationships Scale (ECR), the 8-item Brief Fear of Negative Evaluation Scale (BFNE), the 6-item Revised UCLA Loneliness Scale–Short Form (RULS-6), and the 6-item Bergen Social Media Addiction Scale (BSMAS). Using the PROCESS macro (Model 6), a chained mediation model was tested. Results: Attachment anxiety positively predicts SMA (β = 0.42); the chained mediation pathway through FNE and loneliness accounts for ab = 0.06 of this effect, alongside additional single-mediator paths. In contrast, attachment avoidance shows a weaker total effect (β = −0.08) and a small negative chained mediation effect (ab = −0.02), offset by opposing single-mediator paths via FNE (negative) and loneliness (positive), resulting in a nonsignificant total indirect effect. Discussion: These findings suggest that in the Chinese cultural context, where social evaluation and belonging are emphasized, insecure attachment may heighten emotional reliance on social media. This study elucidates the socio-emotional mechanisms underlying SMA and extends the application of attachment theory to the digital media environment. Full article

This study evaluated the effect of pearl millet subjected to different processing on the intestinal health of rats. The animals were fed a standard iron-free diet (28 days) (hemoglobin depletion: 8.65 + 1.40 g/dL of hemoglobin). Subsequently, they were divided into four groups for hemoglobin repletion (21 days): standard diet + ferrous sulfate (SD + FS); standard diet + non-germinated open-pan cooked millet flour (SD + NGOPCMF); standard diet + germinated open-pan cooked millet flour (SD + GOPCMF); and standard diet + extrusion-cooked millet flour (SD + ECMF). Hemoglobin level did not differ among groups. The SD + NGOPCMF, SD + GOPCMF and SD + ECMF groups demonstrated a higher Chao index in the microbiome and a higher number and area of goblet cells and longitudinal muscle layer width. The SD + NGOPCMF and SD + GOPCMF groups demonstrated increased cecum weight, crypt depth, crypt thickness, and circular muscle layer width; lower fecal pH; and a higher relative abundance of Bacteroidota, while the SD + FS group showed the highest abundance of Actinobacteriota. The SD + GOPCMF group stood out for showing the lowest fecal pH, better α-diversity (Chao and Shannon index), and the highest width of the longitudinal muscle layer. In conclusion, pearl millet subjected to different processing, mainly germination, has the potential to improve the composition of the intestinal microbiota and the intestinal morphology in rats induced to iron deficiency. Full article

The increase in the elderly population globally reflects a change in the population’s mindset regarding preventive health measures and necessitates a rethinking of healthcare strategies. The integration of machine learning (ML)-type algorithms in geriatrics represents a direction for optimizing prevention, diagnosis, prediction, monitoring, and treatment. This paper presents a systematic review of the scientific literature published between 1 January 2020 and 31 May 2025. The paper is based on the applicability of ML techniques in the field of geriatrics. The study is conducted using the Web of Science database for a detailed discussion. The most studied algorithms in research articles are Random Forest, Extreme Gradient Boosting, and support vector machines. They are preferred due to their performance in processing incomplete clinical data. The performance metrics reported in the analyzed papers include the accuracy, sensitivity, F1-score, and Area under the Receiver Operating Characteristic Curve. Nine search categories are investigated through four databases: WOS, PubMed, Scopus, and IEEE. A comparative analysis shows that the field of geriatrics, through an ML approach in the context of elderly nutrition, is insufficiently explored, as evidenced by the 61 articles analyzed from the four databases. The analysis highlights gaps regarding the explainability of the models used, the transparency of cross-sectional datasets, and the validity of the data in real clinical contexts. The paper highlights the potential of ML models in transforming geriatrics within the context of personalized predictive care and outlines a series of future research directions, recommending the development of standardized databases, the integration of algorithmic explanations, the promotion of interdisciplinary collaborations, and the implementation of ethical norms of artificial intelligence in geriatric medical practice. Full article

Background: The relationship between sports participation and food preferences in adults, as well as the influence of gender, is still unclear. Objective: The objective of this study was to investigate the association between sports participation and individual food preferences and to explore potential gender differences among sports participants in a large group of Italian adults. Methods: This cross-sectional study involved 2665 adults (aged ≥ 18 years) who lead normal lives and underwent a routine lifestyle and dietary assessment at a clinical centre specialising in nutrition, metabolic health, and lifestyle counselling in Rome. Participants completed an online questionnaire on food preferences (19 foods) and sports practice. Multivariate logistic regression models, adjusted for age, sex, and smoking, were used to assess associations. Results: Sports participation was defined as engaging in structured physical activity at least once per week and was reported by 53.5% of subjects (men: 60.1%; women: 49.0%; p < 0.0001). After adjustment, active individuals were significantly more likely to prefer plant-based drinks, low-fat yoghurt, fish, cooked and raw vegetables, fruit, whole grains, tofu, and dark chocolate (all p < 0.05) and less likely to prefer cow’s milk (p = 0.018). Among sport participants, males were more likely to prefer meat (general, white, red, processed) and eggs, while females preferred plant-based drinks. No significant gender differences were observed for dairy products, legumes, or fish. Differences in food preferences were also observed according to the type of sport, with bodybuilders showing higher preference for tofu and dark chocolate. The strongest associations were found in the 25–44 age group. Conclusions: Sports participation is independently associated with specific food preferences, characterised by greater preference for plant-based and fibre-rich foods, and gender differences in food choices persist even among active adults. These findings highlight the need to consider both sports participation and gender when designing nutritional interventions. Full article

Quercetin, a natural polyphenolic flavonoid with antioxidant and anti-allergic properties, is extensively found in foods and holds significant importance for human health. In this study, a simple switch-off fluorescent sensor based on copper nanoclusters (Cu NCs) was proposed for the sensitive determination of quercetin. Glutathione acted as the reducing and protective agent in the synthesized process of Cu NCs via a facile, green one-pot method. As anticipated, the glutathione-capped Cu NCs (GSH-Cu NCs) exhibited favorable water solubility and ultrasmall size. The fluorescence property of GSH-Cu NCs was further enhanced with Al³⁺ ion through the aggregation-induced emission effect. When quercetin was present in the sample solution, the system exhibited effective fluorescence quenching, which was attributed to the internal filter effect. The GSH-Cu NCs/Al³⁺-based fluorescent sensor showed a good linear relationship to quercetin in the concentration range from 0.1 to 60 μM. A detection limit of 24 nM was obtained. Moreover, the constructed sensor was employed for the successful determination of quercetin in tea samples. Full article

Background/Objectives: Health education plays a vital role in training health professionals and caregivers, supporting both prevention and the promotion of self-care. In this context, technology serves as a valuable ally by enabling continuous and flexible learning. Among the various domains of health education, nutrition stands out as a key element in the management of Amyotrophic Lateral Sclerosis (ALS), helping to prevent malnutrition and enhance patient well-being. Accordingly, this study aimed to evaluate the effectiveness of the teaching and learning processes within a learning pathway focused on food and nutrition in the context of ALS. Methods: This study adopted a longitudinal, quantitative design. The learning pathway, titled “Food and Nutrition in ALS,” consisted of four self-paced and self-instructional Massive Open Online Courses (MOOCs), offered through the Virtual Learning Environment of the Brazilian Health System (AVASUS). Participants included health professionals, caregivers, and patients from all five regions of Brazil. Participants had the autonomy to complete the courses in any order, with no prerequisites for enrollment. Results: Out of 14,263 participants enrolled nationwide, 182 were included in this study after signing the Informed Consent Form. Of these, 142 (78%) completed at least one course and participated in the educational intervention. A significant increase in knowledge was observed, with mean pre-test scores rising from 7.3 (SD = 1.8) to 9.6 (SD = 0.9) on the post-test across all courses (p < 0.001). Conclusions: The self-instructional, technology-mediated continuing education model proved effective in improving participants’ knowledge about nutrition in ALS. Future studies should explore knowledge retention, behavior change, and the impact of such interventions on clinical outcomes, especially in multidisciplinary care settings. Full article

Avocado (Persea americana), originally from Mesoamerica, has emerged as a focus of intense scientific and industrial interest due to its unique combination of nutritional richness, bioactive potential, and technological versatility. Its pulp, widely consumed across the globe, is notably abundant in monounsaturated fatty acids, especially oleic acid, which can comprise over two-thirds of its lipid content. In addition, it provides significant levels of dietary fiber, fat-soluble vitamins such as A, D, E and K, carotenoids, tocopherols, and phytosterols like β-sitosterol. These constituents are consistently associated with antioxidant, anti-inflammatory, glycemic regulatory, and cardioprotective effects, supported by a growing body of experimental and clinical evidence. This review offers a comprehensive and critical synthesis of the chemical composition and functional properties of avocado, with particular emphasis on its lipid profile, phenolic compounds, and phytosterols. It also explores recent advances in environmentally sustainable extraction techniques, including ultrasound-assisted and microwave-assisted processes, as well as the application of natural deep eutectic solvents. These technologies have demonstrated improved efficiency in recovering bioactives while aligning with the principles of green chemistry. The use of avocado-derived ingredients in nanostructured delivery systems and their incorporation into functional foods, cosmetics, and health-promoting formulations is discussed in detail. Additionally, the potential of native cultivars and the application of precision nutrition strategies are identified as promising avenues for future innovation. Taken together, the findings underscore the avocado’s relevance as a high-value matrix for sustainable development. Future research should focus on optimizing extraction protocols, clarifying pharmacokinetic behavior, and ensuring long-term safety in diverse applications. Full article

The agony of medical negligence for all involved is well documented. Health practitioners involved in harm events are described in the literature as “second victims”. Injured patients report that clinical negligence litigation is traumatic, slow, expensive, and does not meet their needs. Clinical negligence lawyers have complained that healthcare injury cases are so complex and expensive that many firms do not accept these cases. This article uses a qualitative case study research design to analyse two cases from the United States of America (US) to explore the promise of an alternative resolution process: the communication-and-resolution program (CRP). CRPs involve the hospital disclosing the healthcare injury, investigating and explaining what happened, apologising and, sometimes, offering compensation to injured patients and families. In the US, CRPs have not replaced tort law. The two case studies analysed in this article offer a rare insight into the accounts of those who have experienced clinical negligence and an alternative non-litigation approach. The case study approach delves into the detail, providing an in-depth glimpse into the complexity of healthcare injuries in their real-life context. The case studies provide valuable lessons for reshaping resolution processes to better meet injured patients’ needs. Full article

Background/Introduction: Psychological inflexibility, which includes experiential avoidance, is a transdiagnostic process associated with multiple mental health issues in adolescence. Physical fitness (PF) has shown benefits for mental well-being, yet its specific relationship with psychological inflexibility remains understudied, particularly among youth. Objectives: To examine the association between components of PF and psychological inflexibility, measured by the Acceptance and Action Questionnaire-II (AAQ-II), in a representative sample of Spanish adolescents. Methods: A cross-sectional analysis was conducted using data from 631 adolescents (aged 12–17) participating in the Eating Healthy and Daily Life Activities (EHDLA) study. PF was assessed by the Assessing the Levels of PHysical Activity and Fitness (ALPHA-Fit) Test Battery (cardiorespiratory fitness, muscular strength, agility, and flexibility). Psychological inflexibility was measured using the AAQ-II. Generalized linear models (GLMs) were used to evaluate associations, adjusting for age, sex, body mass index, socioeconomic status, physical activity, sedentary behavior, sleep duration, and energy intake. Results: Unadjusted analyses showed weak but significant associations between psychological inflexibility and performance in the 20 m shuttle run test (p = 0.002), the 4 × 10 shuttle run test (p = 0.005), and the sit-and-reach test (p < 0.001). However, after adjusting for covariates, none of the PF components maintained a statistically significant association with the AAQ-II scores. Conclusions: In this adolescent sample, PF components were not independently associated with psychological inflexibility after adjustment for key confounders. These findings suggest that, while PF may contribute to general well-being, it is not a primary determinant of psychological inflexibility. Further longitudinal and intervention studies are needed to clarify the mechanisms linking physical and psychological health in youth. Full article

The health of crops is a major challenge for productivity growth in agriculture, with plant diseases playing a key role in limiting crop yield. Identifying and understanding these diseases is crucial to preventing their spread. In particular, greenhouse pepper leaves are susceptible to diseases such as mildew, mites, caterpillars, aphids, and blight, which leave distinctive marks that can be used for disease classification. The study proposes a seven-class classifier for the rapid and accurate diagnosis of pepper diseases, with a primary focus on pre-processing techniques to enhance colour differentiation between green and yellow shades, thereby facilitating easier classification among the classes. A novel algorithm is introduced to improve image vibrancy, contrast, and colour properties. The diagnosis is performed using a modified VGG16Net model, which includes three additional layers for fine-tuning. After initialising on the ImageNet dataset, some layers are frozen to prevent redundant learning. The classification is additionally accelerated by introducing flattened, dense, and dropout layers. The proposed model is tested on a private dataset collected specifically for this study. Notably, this work is the first to focus on diagnosing aphid and caterpillar diseases in peppers. The model achieves an average accuracy of 92.00%, showing promising potential for seven-class deep learning-based disease diagnostics. Misclassifications in the aphid class are primarily due to the limited number of samples available. Full article

Ongoing changes in the distribution and abundance of several tick species of medical relevance in Canada have prompted the development of the eTick platform—an image-based crowd-sourcing public surveillance tool for Canada enabling rapid tick species identification by trained personnel, and public health guidance based on tick species and province of residence of the submitter. Considering that more than 100,000 images from over 73,500 identified records representing 25 tick species have been submitted to eTick since the public launch in 2018, a partial automation of the image processing workflow could save substantial human resources, especially as submission numbers have been steadily increasing since 2021. In this study, we evaluate an end-to-end artificial intelligence (AI) pipeline to support tick identification from eTick user-submitted images, characterized by heterogeneous quality and uncontrolled acquisition conditions. Our framework integrates (i) tick localization using a fine-tuned YOLOv7 object detection model, (ii) resolution enhancement of cropped images via super-resolution Generative Adversarial Networks (RealESRGAN and SwinIR), and (iii) image classification using deep convolutional (ResNet-50) and transformer-based (ViT) architectures across three datasets (12, 6, and 3 classes) of decreasing granularities in terms of taxonomic resolution, tick life stage, and specimen viewing angle. ViT consistently outperformed ResNet-50, especially in complex classification settings. The configuration yielding the best performance—relying on object detection without incorporating super-resolution—achieved a macro-averaged F1-score exceeding 86% in the 3-class model (Dermacentor sp., other species, bad images), with minimal critical misclassifications (0.7% of “other species” misclassified as Dermacentor). Given that Dermacentor ticks represent more than 60% of tick volume submitted on the eTick platform, the integration of a low granularity model in the processing workflow could save significant time while maintaining very high standards of identification accuracy. Our findings highlight the potential of combining modern AI methods to facilitate efficient and accurate tick image processing in community science platforms, while emphasizing the need to adapt model complexity and class resolution to task-specific constraints. Full article

Background: Asprosin is a relatively recently discovered glucogenic adipokine secreted during fasting that plays an important role in various biochemical processes in the body, including those connected with obesity and insulin resistance. The aim of this exploratory study was to investigate the associations between selected hormonal, anthropometric, and lifestyle-related parameters and serum asprosin concentration. As studies concerning fertility and asprosin have so far been limited to men or women with PCOS, its role in the general female population remains largely unexplored. The direction of this exploration was thus pointed toward possible connections with female fertility. Methods: The case-control study group included 56 women of reproductive age (25–42 years), who were patients of the Reproductive Health Clinic and the Clinic of Endocrinology, Diabetology, and Internal Medicine of the Medical University of Białystok, Poland. The levels of selected hormones, including anti-Müllerian hormone (AMH), estradiol, sex hormone-binding globulin (SHBG), and testosterone, body composition parameters, and a lifestyle parameter—night fasting duration—were assessed to test their associations with serum asprosin concentration. Results: A weak negative correlation was found between AMH level and serum asprosin concentration, suggesting a potential link between asprosin and ovarian reserve. Furthermore, a moderate positive correlation was found between the percentage of total body water (TBW) and serum asprosin concentration. No significant associations were observed between the levels of the other tested hormones and serum asprosin concentration, or between body composition parameters or night fasting duration and serum asprosin concentration. The multivariate model designed in the study shows that AMH, TBW, and night fasting duration explain 23.4% of asprosin variability. Conclusions: Although the nature of the study is exploratory, the findings indicate that the role of asprosin in the female population—particularly its role in fertility—requires further research. Not only is the number of available studies on asprosin insufficient, but the results of this study partly contradict what is known about the hormone from previous studies, which were largely performed with male cohorts. In addition, the results of this study suggest that asprosin may indeed be involved in mechanisms related to female fertility, particularly those connected with ovarian reserve. Nevertheless, studies performed in larger, more homogeneous populations are necessary to confirm the role of asprosin in women, including its association with female fertility. Full article