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PubMed2026

Male accessory gland proteins in Grapholita molesta: Identification and reproductive functional validation of four accessory gland-specific lipases.

Accessory gland proteins (Acps), synthesized in the male accessory glands (AGs), are transferred to females via spermatophores during mating and elicit diverse post-mating physiological and behavioral responses. However, Acps have not been comprehensively characterized in Grapholita molesta, a cosmopolitan orchard pest. Here, using data-independent acquisition mass spectrometry, we describe an integrated proteomic approach combining comparative AG analyses (virgin vs. newly mated) with spermatophore profiling to identify Acps in G. molesta. According to the established screening criteria, we identified 83 confirmed Acps, which were classified into nine categories. Tissue-specific expression patterns of 20 randomly selected Acp genes were evaluated, revealing that these genes were specifically or highly expressed in male AGs. Among the 83 confirmed Acps, four Acps harbored the PLN02872 superfamily domain and were classified into the canonical lipase family. Notably, their transcripts were all highly expressed in the AGs during the pre-maturation stage. These four Acps were selected for preliminary validation of their male reproductive functions. RNAi-mediated knockdown of three out of four lipase genes in G. molesta males significantly decreased the fertility of mated females, with phenotypes including a significant reduction in egg production and egg hatching rate. This study provides a comprehensive catalog of high-confidence Acps, lays a foundation for subsequent in-depth functional characterization of these reproductive proteins, and offers promising molecular targets for the development of novel genetic regulation-based integrated pest management strategies.

Animals↗

PubMed2026

Organizational bullying among nursing faculty: A systematic review of consequences, contributing factors, and interventions.

BACKGROUND: Organizational bullying among nursing faculty is a systemic and pervasive issue with profound psychological, professional, and institutional consequences. Despite increasing awareness, the literature remains fragmented, and a comprehensive synthesis is lacking. METHODS: This systematic review followed PRISMA guidelines and examined empirical studies on organizational bullying among nursing faculty, with no date restrictions applied. A structured search across five databases (PubMed, Scopus, Web of Science, CINAHL, and Embase) identified studies that met inclusion criteria related to the consequences, contributing factors, and interventions. The Mixed Methods Appraisal Tool (MMAT) was used to assess study quality. RESULTS: Fifteen studies meeting the quality threshold were included. Organizational bullying was consistently associated with psychological distress (e.g., anxiety, depression, burnout, suicidal ideation), professional disengagement, and intent to leave. Contributing factors were categorized into structural and organizational (e.g., hierarchical power imbalances, toxic workplace culture), managerial and HR-related (e.g., lack of leadership support, poor reporting mechanisms), and individual/social (e.g., gender or ethnic discrimination, early-career vulnerability). Intervention strategies identified included policy reforms, leadership training, supportive reporting systems, and psychological support services, though evidence on their effectiveness remains limited. CONCLUSIONS: Organizational bullying in nursing academia is a serious and multifaceted challenge with detrimental effects on individuals and institutions. Addressing it requires a comprehensive, evidence-based approach that includes structural reforms, leadership development, and psychosocial support systems. Academic institutions must prioritize the creation of safe, inclusive, and respectful environments to retain faculty and sustain the quality of nursing education.

Faculty, Nursing↗

PubMed2026

A machine learning-derived and functionally validated circadian rhythm signature predicts clinical outcomes and in silico drug sensitivity in colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) displays considerable heterogeneity in clinical outcomes, highlighting the need for reliable prognostic biomarkers. While the aberrant expression of circadian rhythm-related genes has been implicated in cancer pathogenesis, its comprehensive role in CRC progression and predicted therapeutic vulnerabilities remains inadequately characterized. METHODS: Bulk and single-cell RNA-sequencing data were integrated from multiple CRC cohorts. A circadian rhythm signature (CRS) was developed through machine learning algorithms and validated for prognostic value. Comprehensive analyses of tumor microenvironment, genomic alterations, and drug sensitivity were performed. Furthermore, the biological function of the core gene, BHLHE40, was validated in CRC cell lines through CCK-8, EdU, and wound healing assays. RESULTS: Single-cell analysis demonstrated an elevated expression signature of circadian rhythm-related genes in dendritic cells. The optimized CRS, comprising 14 circadian rhythm-related genes, successfully categorized patients into high- and low-risk groups. Patients with a high CRS showed markedly poorer overall survival and computationally inferred immunosuppressive features, including reduced CD8+ T cell infiltration and increased M2 macrophage polarization. Genomic analysis revealed enhanced mutation burden in TP53 and alterations in RTK-RAS/WNT pathways. Notably, in vitro assays confirmed that BHLHE40 is significantly overexpressed in CRC cells. Knockdown of BHLHE40 markedly inhibited tumor cell proliferation and migration. Drug sensitivity profiling identified bexarotene and SMER-3 as potential therapeutic options for high-CRS patients. A nomogram integrating CRS with clinical parameters demonstrated superior predictive accuracy for 1-, 3-, and 5-year survival. CONCLUSIONS: The CRS represents a promising prognostic biomarker that reflects tumor immune status and genomic features, providing valuable insights for personalized treatment strategies in CRC.

Circadian rhythm↗

PubMed2026

The relationship between composite dietary antioxidant index and odds of depression: A systematic review and dose-response meta-analysis of observational studies.

BACKGROUND: Recently, the association between the composite dietary antioxidant index (CDAI) score and depression has received special attention from researchers. However, this possible association has not been comprehensively examined. Thus, the present study aims to comprehensively assess the relationship between CDAI score and depression odds. METHODS: A thorough literature search was performed using Scopus, PubMed, and Web of Science up to November 2025. Observational studies assessing the relationship between CDAI score and depression odds were included. The odds ratios (ORs) and their 95% confidence intervals (CIs) reported in each study were extracted, and a pooled effect size was calculated using a random-effects model with inverse-variance weighting. RESULTS: Four observational studies were included in the current systematic review and meta-analysis. The pooled effect size indicated that a higher CDAI score was associated with lower odds of depression (OR:0.62; 95%CI: 0.51-0.76, I2 = 48.5%; P-value = 0.121). In an exploratory linear dose-response analysis based on two eligible studies, no significant association was observed between a one-unit increase in CDAI score and the odds of depression (OR = 0.96; 95% CI: 0.91-1.02; I2 = 92.2%; P-value<0.001). Given the limited number of studies and substantial heterogeneity, these findings should be interpreted cautiously. CONCLUSIONS: Our findings suggest that higher CDAI scores, reflecting greater adherence to antioxidant-rich dietary patterns, are associated with lower odds of depression.

Humans↗

PubMed2026

Current Concepts and Emerging Technologies in Aesthetic Outcome Assessment of Breast Reconstruction.

Aesthetic outcomes are a crucial determinant of the overall success of breast reconstruction. Recently, aesthetic assessment has evolved from relying mainly on subjective impressions to incorporating more quantitative methods. This systematic review summarizes current concepts and emerging technologies in aesthetic outcome assessment after breast reconstruction. A comprehensive search of studies evaluating aesthetic outcomes following implant-based, autologous or hybrid breast reconstruction was performed between 2000 and 2025. Assessments were classified as subjective or objective. Extracted variables included assessment characteristics, aesthetic outcome domains, and patient-centered outcomes. Risk of bias was assessed using the Joanna Briggs Institute Critical Appraisal Checklist. Levels of evidence were classified according to the Oxford Centre for Evidence-Based Medicine. A total of 51 studies involving 7711 participants from 16 countries were included. Subjective tools were most frequently employed, led by the BREAST-Q (35/51, 69%), followed by expert- or panel-based evaluations (17/51, 33%) and the visual analog scale (2/51, 4%). Objective methods were applied in 19 studies and included 3-dimensional surface imaging (8/51, 16%), BCCT.core (7/51, 14%), eye tracking (3/51, 6%), and artificial intelligence-based analyses (3/51, 6%). Although subjective tools captured satisfaction with breast appearance, objective tools quantified morphological parameters and positional landmarks. BREAST-Q remains the cornerstone of outcome evaluation after breast reconstruction, providing patient-centered perspectives, including, but not limited to, aesthetic perception. A progressive shift toward multimodal evaluation was noticed, as no single modality comprehensively addressed all aesthetic domains. Future research should focus on integrating subjective and objective assessment methods within a unified framework. Level of Evidence: 3 (Therapeutic) For image description, please refer to the figure legend and surrounding text.

Humans↗

PubMed2026

Hyperbaric oxygen for the treatment of traumatic incomplete spinal cord injury: a systematic review and meta-analysis of randomized controlled trials.

The therapeutic efficacy of hyperbaric oxygen therapy for traumatic incomplete spinal cord injury remains a subject of debate. To comprehensively evaluate the impact of hyperbaric oxygen on motor function, sensory function, and activities of daily living in patients with traumatic incomplete spinal cord injury, we conducted a systematic review and meta-analysis. We performed a comprehensive search across PubMed, Embase, the Cochrane Library, Web of Science, and major Chinese databases for randomized controlled trials published through June 2025. A total of 15 randomized controlled trials were included. The pooled results indicated that hyperbaric oxygen therapy significantly improved the American Spinal Injury Association motor score (mean difference = 10.30, 95% confidence interval: 7.70-12.90), the total American Spinal Injury Association sensory score (mean difference = 29.29, 95% confidence interval: 18.82-39.75), the American Spinal Injury Association light touch score (mean difference = 9.84, 95% confidence interval: 6.15-13.53), and the American Spinal Injury Association pinprick score (mean difference = 8.75, 95% confidence interval: 4.40-13.11). Furthermore, hyperbaric oxygen therapy was associated with significant enhancements in the Barthel Index (mean difference = 16.60, 95% confidence interval: 10.51-22.68) and the Functional Independence Measure (mean difference = 17.41, 95% confidence interval: 10.83-23.98). In conclusion, adjunctive hyperbaric oxygen therapy appears to improve motor function, sensory function, and activities of daily living in patients with traumatic incomplete spinal cord injury compared to conventional treatments alone. However, due to methodological limitations and potential publication bias in the included studies, these findings should be interpreted with caution, and further high-quality, multi-center randomized controlled trials are warranted.

Humans↗

PubMed2026

Prenatal exposure to particulate matter (PM) and autism spectrum disorder (ASD) among children: a systematic review and meta-analysis.

The global surge in Autism Spectrum Disorder (ASD) cases, coupled with evidence linking prenatal Particulate Matter (PM) exposure to developmental disruption, demands a comprehensive review to design targeted health interventions. This systematic review and meta-analysis aim to evaluate the strength and consistency of evidence linking prenatal PM exposure to ASD across studies, quantifying this relation to identify actionable environmental risk thresholds. This study employed PRISMA protocols to systematically extract and evaluate evidence from PubMed, Web of Science, Scopus, and ScienceDirect (2010-2024), and screened 4,013 articles to identify qualified case-control and cohort studies (n=29). Data synthesis employed random-effects modeling, accompanied by comprehensive assessment through I2 statistics, Q-tests, funnel plots, Duval and Tweedie's trim-and-fill analysis, and Egger's regression, to ensure validity. A meta-analysis of 16 case-control studies revealed a 34 % increased risk of ASD associated with prenatal PM exposure (pooled OR=1.34; 95 % CI: 1.13-1.54), despite substantial between-study heterogeneity (I2=94.02 %, p<0.001). Publication bias was not significant (Egger's test p value=0.114). Critical trimester-specific analysis uncovered that third-trimester exposure significantly increased ASD risk (OR=1.17; 95 % CI: 1.01-1.34), while first-trimester (OR=1.02; 95 % CI: 0.92-1.11; I2=49.18 %, p<0.10) and second-trimester exposures (OR=1.13; 95 % CI: 0.88-1.38; I2=92.59 %, p<0.001) showed non-significant associations. This review identified prenatal and early life exposure to PM as a risk factor for ASD, indicating a trimester-specific vulnerability. It highlighted the necessity of focused air quality interventions and targeted guidance to reduce prenatal PM exposure to alleviate ASD risk during the critical-window.

Child↗

PubMed2026

Assessing comorbidities and predicting risk: A primer for APRNs.

Today's clinical environments are rife with tools designed to comprehensively account for medical complexity and comorbidities while predicting risk for a host of adverse health-related outcomes. Therefore, it is imperative that advanced practice registered nurses (APRNs) understand the structure and function of these tools, their similarities and differences, their limitations, and strategies for appropriate incorporation into practice. This article offers a practical overview for APRNs, emphasizing clinical implications and guidance for aligning assessment tools with the clinical population of interest to improve care delivery, quality, and patient outcomes.

Humans↗

PubMed2026

Evaluating the utility of melatonin in spine surgery: a systematic review and meta-analysis of randomized clinical trials.

BACKGROUND: Spine surgery is increasingly performed worldwide, and acute postoperative stressors such as pain and anxiety remain highly prevalent despite historical management with opioids and other pharmacological agents. Recently, interest has emerged in melatonin administration given its endogenous physiological roles, low cost, favorable adverse event profile, and documented benefits throughout surgical literature. PURPOSE: This study aims to consolidate the existing evidence on melatonin's utility specifically in spine surgery, an area not yet comprehensively evaluated, to inform clinical practice and enhance spine surgeon comprehension. STUDY DESIGN/SETTING: Preregistered on PROSPERO, this systematic review queried PubMed/MEDLINE, CINAHL, SPORTDiscus, and Web of Science on November 21st, 2025, for studies reporting outcomes following melatonin administration in patients undergoing spine surgery. METHODS: Study quality was assessed using the Cochrane Risk-of-Bias 2 tool. Extracted variables included demographics, comparator medications, dosages, and other relevant details. Statistical analyses included frequency-weighted means (FWMs), associated standard deviations, narrative syntheses, and limited meta-analyses, where appropriate. RESULTS: A total of 6 moderate-quality randomized trials were included from 749 screened. Melatonin (3-10 mg) was administered to 227 patients (FWM age=43.3±8.6 years; 46.2% male; BMI=26.6±3.2 kg/m2), placebo to 125 patients (age=43.2±10.1 years; 60% male; BMI=28.5±4.3 kg/m2), and active pharmacologic comparators (fentanyl, gabapentin, dexmedetomidine, zolpidem) to 151 patients (age=46.6±8.9 years; 40.5% male; BMI=26.3±3.5 kg/m2). Procedures primarily involved uncomplicated lumbar laminectomies (1-4 levels), with outcomes assessed up to 24 hours postoperatively. Melatonin was associated with significant improvements in early postoperative VAS-pain scores, blood-pressure-related, analgesic-related, and anxiety-related outcomes versus placebo across most reporting studies. Compared with active pharmacologic agents, significant benefits were observed only in select nausea- and anxiety-related instances. Limited meta-analysis (n=2) demonstrated higher 24-hour VAS-pain for melatonin versus gabapentin, though mean difference was near-negligible and harbored extensive statistical constraints. CONCLUSION: Melatonin demonstrates variable utility following spine surgery, with generally consistent anxiolysis and frequent benefit versus placebo but less consistent and comparatively weaker efficacy relative to active pharmacologic comparators. Future outcome-homogenous studies incorporating more granular, expansive comparator arms and more robust quantitative analyses are needed to further elucidate melatonin's role in advancing spine care. LEVEL OF EVIDENCE: Level II.

Humans↗

PubMed2026

The landscape of pruning for large language models: A systematic review and unified taxonomy.

Confronting the inherent tension between the exceptional capabilities and the immense computational costs of Large Language Models (LLMs), pruning has become a crucial technique for achieving efficient deployment. However, a systematic analytical framework dedicated specifically to LLM pruning remains absent. In this paper, we aim to bridge this gap. We first elucidate the theoretical foundations that underpin the effectiveness of pruning, namely overparameterization and redundancy, and then propose a multidimensional taxonomy that organizes existing approaches along the axes of granularity, timing, and criteria. Building upon this unified perspective, we further analyze performance recovery mechanisms and the broader evaluation ecosystem, while also exploring forward-looking challenges such as interpretability, automation, and hardware-algorithm co-design. Through this comprehensive synthesis, we seek to provide an integrated and coherent analytical lens for advancing both research and practice in LLM pruning.

Large Language Models↗

PubMed2026

Effect of Perioperative Sucralfate Administration on Pain Control After Tonsillectomy: A Systemic Review and Meta-Analysis.

OBJECTIVES: This study evaluated the efficacy of perioperative intraoral sucralfate in reducing postoperative pain following tonsillectomy through a systematic review and meta-analysis. METHODS: A comprehensive search of PubMed, SCOPUS, Embase, Web of Science, and Cochrane up to September 2025 identified 13 studies comparing perioperative intraoral sucralfate with placebo or no treatment. Outcomes included throat pain, otalgia, swallowing pain, analgesic consumption, and perioperative morbidities. RESULTS: Sucralfate increased the proportion of patients reporting no or mild throat pain and otalgia, improved mucosal healing at 5 to 7 days, and reduced throat pain, swallowing pain, otalgia, analgesic use, and time to resume >50% of a regular diet. No significant differences were observed in postoperative bleeding or nausea/vomiting. CONCLUSION: Perioperative intraoral sucralfate may be an effective adjuvant therapy that improves postoperative pain control, enhances wound healing, reduces analgesic requirements, and facilitates earlier dietary resumption after tonsillectomy.

Humans↗

PubMed2026

Patient-reported outcomes in pediatric regional anesthesia trials: current use and limitations.

PURPOSE OF REVIEW: This review examines the current use and limitations of patient-reported outcome measures (PROMs) in pediatric regional anesthesia research. Despite the increasing emphasis on patient-centered outcomes, existing pediatric outcome assessment frameworks may inadequately capture the pain experience and interference with daily living. RECENT FINDINGS: Across 17 identified randomized controlled trials and 15 ongoing studies, PROM use remains highly variable, with consistent reliance on observational pain scales such as the Face, Legs, Activity, Cry, and Consolability scale and limited incorporation of standardized, longitudinal health-related quality-of-life measures. SUMMARY: Current pediatric PROM frameworks remain fragmented, limiting comprehensive evaluation of recovery. Greater standardization and incorporation of developmentally appropriate, longitudinal outcome measures are needed to better align clinical research with meaningful patient-centered endpoints and to improve assessment of functional and psychosocial recovery.

Humans↗

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↗

PubMed2025

Examining Behavioral Interventions for Infancy and Early Toddlerhood: A Systematic Review of Intervention Effects, Parameters, and Participants.

Rapid advancement is paving the way to identify children who would likely benefit from early intervention during the first years of life, prior to the onset of significant delays in development. With the widely acknowledged benefits of early intervention, key questions arise: Does behavioral intervention targeted to infancy and early toddlerhood improve developmental outcomes? What procedures might be used, and under what circumstances? Who do these interventions work for? The current review comprehensively examined the literature on behavioral interventions based in operant learning, focused on key developmental areas with children in the first two years of life. We located and synthesized 69 studies with unique participant cohorts that included 1735 children. The search revealed many studies focused on the first year of life, of which a large proportion investigated approaches to increase communication. We provide implications, limitations, and future directions on how behavioral interventions for infants and young toddlers can inform current practice and future intervention research this population.

Humans↗