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PubMed2026

A Meta-learning-driven strategy for adulteration detection in sweet potato starch and vermicelli using Raman spectroscopy.

To address the widespread adulteration of sweet potato starch and its vermicelli with cheaper starches and overcome conventional supervised learning's dependency on large labeled datasets, this study developed a few-shot discrimination method integrating Raman spectroscopy with meta-learning. We constructed a meta-learning framework using cassava- and wheat-adulterated sweet potato starch as the source domain for training, with potato-adulterated sweet potato starch and cassava-adulterated sweet potato vermicelli as two target domains for testing. Raman spectra showed high consistency between sweet potato vermicelli and its raw starch, laying the foundation for cross-domain detection. Testing yielded comprehensive classification accuracies of 95.33% and 98.00% for the two target domains, significantly outperforming SVM, RF, and CNN (max. 85.24%). This approach effectively identifies subtle starch variety differences in complex adulteration, providing novel food quality inspection solutions and verifying the feasibility of raw material-to-finished product cross-domain detection.

Ipomoea batatas↗

PubMed2026

Effects of exercise on aerobic capacity in people with prehypertension or hypertension: a systematic review and meta-analysis of randomized controlled trials.

This study aimed to quantify the effects of exercise on aerobic capacity in people with prehypertension or hypertension and to identify exercise prescription parameters that optimize improvements. A comprehensive search was conducted in PubMed, Web of Science, Embase, Cochrane Library, and Scopus from inception to 24 October 2025. Data were pooled using standardized mean differences (SMDs) with 95% confidence intervals (CI). Fifteen studies met the inclusion criteria. Exercise significantly improved aerobic capacity in people with prehypertension or hypertension (SMD = 0.88; 95% CI: 0.61-1.15; P  < 0.00001), with multicomponent training demonstrating superior efficacy. Exploratory subgroup analyses suggest that longer programs (≥12 weeks), lower frequency (<3 sessions/week), 60-min sessions or longer, total weekly exercise less than 180 min, and professional supervision may be associated with better outcomes.

Humans↗

PubMed2026

Non-destructive prediction of lead content in oilseed rape leaves by fluorescence hyperspectral technology based on neural network.

Based on fluorescence hyperspectral imaging (FHSI), this study targeted rapid, non-destructive quantification of lead (Pb) content in oilseed rape leaves treated with varying silicon (Si) concentrations, acquiring fluorescence spectra over the 484.43-1001.61 nm wavelength range. To optimize spectral data quality, preprocessing methods (Savitzky-Golay smoothing, first derivative, detrending) were comprehensively compared. Characteristic wavelengths were then selected via interval variable iterative shrinkage, which effectively compressed data dimensionality and reduced computational load. A hybrid SE-CL1DA model, fusing a 1D convolutional neural network, a long short-term memory network and SE attention mechanism was constructed, with Bayesian optimization tuning hyperparameters to boost stability. The BO-SE-CL1DA outperformed both traditional machine learning and insufficiently optimized deep learning model (Rp2=0.9609, RMSE = 0.0377 mg/kg, RPD = 5.1736), thus enabling accurate Pb estimation, supporting Si-regulated heavy metal stress management and facilitating agricultural contamination monitoring.

Plant Leaves↗

PubMed2026

Analysis of deep learning techniques in computer-aided diagnosis for meniscus injuries: a systematic literature review.

Meniscus informatics is a growing subject of study in the healthcare industry. One of the major hindrances to the healthcare system's transformation is obtaining knowledge and meaningful information from complicated, high-dimensional and diverse sources. Modern biomedical research, for instance, has seen an increase in the use of complex, dissimilar, poorly documented, and generally unstructured electronic health records, imaging, sensor data and text, even after many current techniques have been used to extract more robust and useful elements from the data for analysis. New efficient standards for building end-to-end learning models from complex data are therefore needed. Therefore, the current study aims to examine the most recent research on the use of deep learning techniques for diagnosing meniscus tears and recommend creating comprehensive and meaningful interpretable structures that might benefit the healthcare industry. We also draw attention to shortcomings and the need for better technique development, and we provide new perspectives about this exciting new development in the field.

Humans↗

PubMed2026

SGLF-Net:Staged Global-to-Local Cross-Scale Fusion Network for Colonoscopic Polyp Segmentation.

Polyp segmentation in colonoscopy images plays a pivotal role in computer-aided medical diagnosis and the early prevention of colorectal cancer. However, existing methods often suffer from performance degradation when confronted with extreme polyp scale variation and polyp boundary ambiguity. To address these challenges, we propose the Staged Global-to-Local Cross-Scale Fusion Network (SGLF-Net), which adopts a novel staged global-to-local learning paradigm to progressively refine segmentation from coarse global semantics to fine-grained local details. Specifically, the Global Semantic Perception Stage integrates a Swin Transformer Encoder and a Dynamic Attentive Decoder (DAD) to construct comprehensive multi-scale contextual representations. The Local Detail Refinement Stage employs an Edge-aware Dynamic Attentive Decoder (E-DAD) to enhance structural fidelity and boundary precision through explicit edge-guided supervision. Furthermore, we introduce the Cross Spatial-Scale Feature Aggregation and Reconstitution (CSSAR) module, equipped with hybrid attention mechanisms, to facilitate efficient semantic structural interaction between the two cascaded stages. Extensive experiments on five public benchmark datasets demonstrate that SGLF-Net consistently outperforms state-of-the-art methods in both segmentation accuracy and boundary preservation.

Journal Article↗

PubMed2026

ORBIT: Oncogenic Representation Learning via Bi-Prototype Contrastive Learning in Hyperbolic Space for cancer driver gene identification.

Accurate identification of cancer driver genes is crucial for precision oncology but remains challenging due to the complexity of integrating heterogeneous data and modeling dynamic biological systems. To address these limitations, we propose ORBIT (Oncogenic Representation Learning via Bi-Prototype Contrastive Learning in Hyperbolic Space). Our framework synergistically fuses multi-omics profiles with functional network data using a context-adaptive graph reweighting mechanism to capture cancer-specific dynamics. The model employs a bi-prototype contrastive learning strategy within hyperbolic space, which aligns gene representations around distinct driver and non-driver semantic anchors while preserving the intrinsic hierarchy of biological networks. Comprehensive evaluations demonstrate that ORBIT achieves highly competitive stability in pan-cancer analysis while consistently outperforming state-of-the-art methods in cancer-specific predictions. Furthermore, functional enrichment analysis confirms that the model effectively segregates core cancer pathways, and drug sensitivity profiling validates the clinical relevance of the identified drivers. By integrating hyperbolic geometry with context-adaptive learning, ORBIT offers a robust and interpretable paradigm for precision medicine. The source codes and datasets are publicly accessible at https://github.com/spcho-dev/ORBIT.

Humans↗

PubMed2026

Meta-analysis of source identification and apportionment in soil: A systematic review of analytical procedures, receptor modeling, and environmental applications.

Soil pollution poses significant risks to ecosystems and human health, necessitating accurate source identification and apportionment to guide mitigation strategies. This systematic review evaluates the application of Positive Matrix Factorization (PMF) and other receptor models in soil pollution studies, focusing on analytical procedures, tracer indicators, and environmental applications. This review aims to provide a comprehensive framework for conducting soil source apportionment studies, aiding policymakers in designing effective, region-specific environmental management strategies by compiling global trends and methodological insights. The study addresses sampling protocols, emphasizing representativeness and quality control. Data from 500 peer-reviewed publications highlight the dominance of research in China, Eastern Europe, and South Asia, with agricultural soils being the most frequently studied. Key findings reveal that traffic emissions (20.8 %) and industrial activities (19.4 %) are the primary global contributors to soil contamination, with regional variations such as coal combustion in cold climates and agricultural inputs in developing regions. Policy recommendations include stricter industrial regulations, sustainable agricultural practices, and targeted remediation efforts based on source-specific risks.

Soil Pollutants↗

PubMed2026

LC-IMS-MS profiling of avocado acetogenins reveals tissue-dependent distribution and cultivar-specific metabolic signatures.

This study presents a comprehensive characterisation of acetogenin-related metabolites in avocado using an LC-IMS-MS workflow. A total of 26 metabolites were semi-quantified across peel, pulp and seed tissues from three cultivars (Hass, Bacon and Fuerte). The integration of ion mobility spectrometry enabled the generation of the first experimental database of collision cross section (CCS) values for avocado acetogenins, improving confidence in metabolite annotation. Results revealed a pronounced tissue-dependent distribution, with seeds and pulp as the primary reservoir of several acetogenins, whereas the peel consistently exhibited lower concentrations. In contrast, acetogenin levels remained largely stable throughout ripening. Clear cultivar-dependent differences were observed, with Hass displaying a distinct metabolic profile compared to Bacon and Fuerte. Multivariate analysis confirmed these findings, showing tissue-dependent cultivar differentiation. This study provides new insights into avocado chemical diversity and highlights the potential of avocado by-products as consistent and promising sources of bioactive acetogenins.

Persea↗

PubMed2026

Leveraging environmental applications and risks of coal gangue: A critical review on authigenic inorganic heavy metals, organic contaminants, and the removal of exogenetic contaminants.

Coal gangue (CG) as bulk solid waste has seriously threatened the ecosystem. Therefore, identifying the key risk drivers and exploring feasible disposal methods for CG are essential for developing a sustainable strategy. However, there is currently a lack of comprehensive information that balances the contamination risks with the valuable constituents present in CG, which hinders its full potential for sustainable use without negative environmental impacts. Given the complex composition and associated risks, we propose that addressing the critical properties related to contamination is crucial for the efficient utilization of CG. On this premise, we summarized several practical resource pathways (ecological multifunctional materials, extraction of rare elements, and soil additives) that are more favorable for sustainable development relative to conventional disposals. Meanwhile, we also propose that coupling disposals could intensely reduce CG's environmental footprints and capital costs. Consequently, regardless of the number of challenges to be solved, we believe the CG has broad application prospects, and we hope this review will promote the conversion of CG into an asset with lower ecological and social impacts.

Metals, Heavy↗

PubMed2026

Hepatotoxicity of OBS: A review of the emerging PFOS substitute.

As an alternative to perfluorooctanesulfonic acid (PFOS), sodium perfluorononenyl oxobenzene sulfonate (OBS) is widely used due to its cost-effectiveness. Multiple studies have shown that the liver is a classic target organ for OBS. However, there is currently no systematic review on the hepatotoxic effects of OBS. This review systematically summarizes the exposure characteristics of OBS in the environment and human populations, as well as its mechanisms of liver toxicity. In vivo studies consistently demonstrate that OBS induces hepatotoxic effects, such as hepatomegaly, vacuolization, elevated serum transaminases, and lipid dysregulation, though the manifestation of these phenotypes varies across species and exposure routes. In vitro evidence further shows that OBS reduces cell viability and survival, and triggers necrosis accompanied by inflammation. Mechanistically, oxidative stress, inflammatory signaling, and metabolism disorder are implicated. Critically, most existing work addresses subacute or subchronic exposure, leaving a gap in chronic risk assessment for long-term, low-dose OBS exposure. Moreover, mechanistic studies have focused predominantly on downstream transcriptional and signaling changes, with limited exploration of upstream epigenetic controls. Overall, this study aims to provide a comprehensive reference for future toxicological investigations and liver injury risk assessments related to OBS exposure.

Humans↗

PubMed2026

Proteomics in environmental pollution research: Advances, challenges, and future directions.

Environmental proteomics has emerged as a powerful approach for elucidating the molecular mechanisms underlying pollutant-induced biological effects. Although this field has developed rapidly, the systematic review of recent proteomics applications in environmental pollution research remains limited. This review explored the emerging roles of toxicoproteomics in biomarker discovery and mechanistic elucidation, as well as ecotoxicoproteomics in ecological risk assessment and bioremediation strategies. Here, we review the field, highlighting recent trends such as the integration of proteomics with genomics, transcriptomics, and metabolomics to provide a comprehensive view of biological responses to environmental stressors. We further discuss the growing application of artificial intelligence in improving proteomics data interpretation and accelerating biomarker discovery. In addition, recent technological advances in environmental proteomics are highlighted, including next-generation tissue microarray proteomics, nanoscale proteomics, single-cell proteomics, and spatial proteomics. Despite its potential, proteomics faces challenges, such as high operational costs, computational complexity in analysis, and technical limitations in low-abundance protein detection. We propose that the convergence of proteomics with artificial intelligence and multi-omics approaches offers promising solutions to these challenges, enhancing the practical application of proteomics in environmental monitoring and risk assessment.

Proteomics↗

PubMed2026

Evolutionary architecture and lineage-specific diversification of Forkhead box transcription factors in Perna viridis.

The Forkhead box (Fox) transcription factors are evolutionarily conserved regulators of development, cell cycle, and apoptosis across metazoans. This study provides the first comprehensive genome-wide analysis of the Fox gene family in the Asian green mussel (Perna viridis). We identified 28 Fox genes distributed across 10 chromosomes. Comparative analysis reveals the absence of the FoxI, FoxQ1, FoxR and FoxS subfamily, consistent with other bivalves and indicative of lineage-specific gene loss during molluscan evolution. Notably, gene duplications in the FoxAB, FoxD, FoxH, FoxN1-4, FoxQ2 and FoxQD subfamilies may reflect functional diversification associated with environmental adaptation. Exon-intron structural variability, including intron loss in several paralogues, suggests structural diversification and potential regulatory variation. Phylogenetic reconstruction confirmed the monophyly of core Fox classes while highlighting divergent expansion patterns in lophotrochozoans. Selection analyses showed strong purifying selection across duplicated Fox paralogs, supporting functional conservation after lineage-specific expansion. Gene Ontology enrichment linked Fox genes to stress response, apoptosis, and transcriptional regulation. By integrating phylogenetic, structural, and transcriptomic analyses, this study provides a genomic framework for understanding Fox gene organisation, evolution, and tissue-associated expression patterns in Perna viridis and establishes a comparative resource for future functional studies in bivalves.

Animals↗

PubMed2026

Diet and sleep among college student populations: a systematic review.

College students are at-risk for both poor diet and poor sleep. We aimed to systematically review the evidence regarding associations between diet and sleep health within this population. A comprehensive electronic search was conducted in PubMed, Embase, Scopus, Web of Science, and PsycINFO from the earliest possible date through February 6, 2026. A total of 57 studies representing 44 countries were retained; most were cross-sectional. There were 22 studies that examined dietary patterns in relation to sleep, generally showing that healthier diet patterns, including the Mediterranean Diet, were related to better sleep quality. Among 20 studies that examined individual foods or nutrients, there was evidence that fruits, vegetables, dairy, protein, and lower intake of sugar-sweetened beverages were linked to better sleep health, although some findings were mixed. Finally, 15 studies related meal timing to sleep quality, showing that breakfast skipping and later last meals were associated with poor sleep health. Overall, these studies reveal robust cross-sectional associations between diet and sleep among college students, but more longitudinal studies and randomized controlled trials are needed to evaluate directionality. Moreover, a key direction for future study is consideration of sleep and nutrition situated within the unique contexts of college settings and academic schedules.

Humans↗

PubMed2026

Emphysematous pyelonephritis in children: Lessons from a case report and systematic review.

BACKGROUND: Emphysematous pyelonephritis (EPN) is a rare, life-threatening gas-producing renal infection. Literature on pediatric EPN remains scarce. OBJECTIVE: To describe a case of pediatric EPN and systematically review the data on clinical presentations, diagnostic modalities, management strategies, and prognosis in pediatric emphysematous pyelonephritis. METHODS: A comprehensive search in PubMed, Embase and Web of Science using defined search terms was done, along with the Joanna Briggs Institute (JBI) critical appraisal checklist for quality assessment. RESULTS: Of 100 records, 20 studies (n = 21) were included in the review. The median (IQR) age of presentation was 48 (8-138) months. The major risk factor was reflux/obstructive nephropathy (52.3 %), and E. coli was the common organism. Management included antibiotics (47.6 %), minimally invasive procedures (33.3 %), or nephrectomy (19 %). We additionally report an adolescent girl with Type 1 diabetes mellitus and class 3A right-sided EPN. She improved with antibiotics and percutaneous nephrostomy (PCN) insertion. CONCLUSION: Obstructive or reflux nephropathy is a major risk factor for pediatric EPN. Antibiotics are the mainstay for treatment with supportive management. Refractory cases may require percutaneous drainage or partial/total nephrectomy.

Humans↗

PubMed2026

Nursing students' perspective of dignity: A systematic review.

AIM: This review synthesizes research on nursing students' perceptions of dignity shaped by education and clinical experiences. BACKGROUND: Respect for human dignity is central to nursing ethics. While dignity is well studied in patient care, less focus has been given to how nursing students perceive and experience dignity during their education. DESIGN: A systematic review of quantitative, qualitative, and mixed-methods studies. METHODS: A comprehensive search was conducted across the Medline, PubMed, ScienceDirect, Scopus, and Web of Science databases for English-language studies published from 2000 to 2025. Quality was assessed using the Joanna Briggs Institute Critical Appraisal Checklist and the Mixed Methods Appraisal. Tool. Data were synthesized thematically. Reporting followed PRISMA guidelines. RESULTS: A total of 24 articles were included. Students viewed patient dignity as linked to respect, privacy, and autonomy. Although students had solid theoretical knowledge, they encountered institutional and professional barriers in delivering dignified care. Supportive environments and participation in decision-making enhanced their sense of dignity. Finally, educational strategies such as role-playing, simulations, and empathy exercises enhanced emotional and psychosocial awareness. CONCLUSIONS: These findings indicate that dignity is crucial in shaping nursing students' professional identity and ethical awareness throughout their education. Reinforcing ethical values and dignity in nursing education is essential for high-quality care.

Humans↗

PubMed2026

Advanced mitigation strategies for acrylamide formation in foods: Mechanistic insights, emerging innovations, and future perspectives.

Acrylamide is a heat-induced contaminant formed predominantly in carbohydrate-rich foods during high-temperature processing, posing significant concerns due to its potential carcinogenic, neurotoxic, and genotoxic effects. This review critically examines the mechanisms of acrylamide formation, emphasizing the role of the Maillard reaction and key precursors such as asparagine and reducing sugars, along with the influence of processing conditions including temperature, time, pH, and moisture. Various mitigation strategies are comprehensively discussed, ranging from raw material selection and genetic approaches to enzymatic treatments such as asparaginase and the application of natural and chemical inhibitors. Advances in processing technologies, including optimization of conventional thermal methods and emerging non-thermal techniques such as cold plasma and ultrasound, are evaluated for their effectiveness. The review also highlights the role of food additives, functional ingredients, and fermentation in reducing acrylamide formation. Furthermore, recent developments in analytical techniques, including chromatographic methods, biosensors, and artificial intelligence-based predictive models, are explored for improved detection and control. Risk assessment, toxicological implications, and global regulatory frameworks are also examined. Finally, future perspectives focusing on genetic engineering, personalized nutrition, and digital technologies such as AI and blockchain are discussed to support sustainable and industry-applicable mitigation strategies.

Acrylamide↗

PubMed2026

Association of media use with sleep of children and adolescents: an umbrella review.

Adequate sleep is essential for child and adolescent development, driving extensive research across scientific disciplines. This umbrella review provides a comprehensive overview of existing evidence on media consumption and sleep and thereby lays the foundation for identifying key concepts and gaps. An inclusive systematic search for reviews reporting literature searches was conducted in 02/2021 and updated last in 09/2024. Methodological quality of the included reviews was assessed using AMSTAR-2. We included 84 reviews reporting on the association between media use and sleep in individuals aged 0-18 years. The field is dominated by reviews of low methodological quality, mainly including original cross-sectional studies with subjective measures in older children and adolescents. A total of 475 original articles were covered by the reviews; only 10 of them appeared in at least seven and at most nine reviews. Screen time generally had a negative impact on sleep, though evidence varied from very low to strong. Evidence for effects of conventional books on sleep remains inconclusive. High quality systematic reviews are needed to evaluate robust studies using objective measures of sleep and contemporary media use across all age groups up to adolescence and to explore the impact of non-digital media use on sleep, considering age and gender differences.

Humans↗

PubMed2026

Hormonal contraceptives and women's sleep health: A systematic review.

Sex hormones and hormonal contraceptives influence the regulation of sleep-wake behavior. However, there are very few large-scale studies to date that have comprehensively evaluated how hormonal contraceptives influence women's sleep health. The purpose of this systematic review was to synthesize the existing research on hormonal contraceptive use and sleep in women ages 18-50. The systematic review was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement checklist. Nineteen studies were included in this review. Data were extracted and evaluated for risk of bias and heterogeneity. The included studies demonstrated high heterogeneity in terms of objective and/or subjective sleep-related measures and non-sleep primary study outcomes and demonstrated significant risks of bias, underscoring the need for methodological consistency in assessing women's sleep health. Several clinical considerations may be gleaned from this existing research in terms of the behavioral assessment and treatment of sleep difficulties in women using hormonal contraceptives. Additional investigation is needed to identify standardized research and clinical methodology guidelines for assessing and treating women's sleep health.

Humans↗