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PubMed2026

Comprehensive study on pesticide residues and mycotoxins in freeze-dried strawberries and raspberries.

Freeze-dried fruit has gained popularity because it preserves the flavour and nutritional value of fresh fruit while providing extended shelf life. Despite this, there are concerns regarding its chemical safety. This study evaluated 58 freeze-dried fruit products from the Czech retail market, focusing on potential contamination. Pesticide residues and mycotoxins were determined using LC-MS/MS and GC-MS/MS. Overall, 111 pesticide residues (or their metabolites) and 3 mycotoxins were quantified. After applying processing factors, 12 pesticide residues exceeded EU maximum residue limits. Prohibited substances, including carbofuran, omethoate, and haloxyfop, were detected. Tenuazonic acid was found in 71% of samples, while alternariol and tentoxin were detected less frequently. More than half (54%) of strawberry samples contained 10 or more pesticide residues, indicating potential cumulative exposure concerns, particularly for children with lower body weight. These findings highlight the need for continued monitoring of freeze-dried fruits and further assessment of dietary exposure.

Pesticide Residues↗
PubMed2026

Stroke risk following BNT162b2 vaccination: a systematic review and meta-analysis of self-controlled case series studies.

INTRODUCTION: Whether BNT162b2 (Pfizer-BioNTech) vaccination increases stroke risk remains a public health concern. This is the first meta-analysis to synthesize self-controlled case series (SCCS)-derived stroke risk estimates specifically for BNT162b2 vaccination. METHODS: PubMed and Embase were searched from inception through 9 May 2026, following PRISMA 2020 guidelines. Eight eligible SCCS studies were pooled using a random-effects model with restricted maximum likelihood (REML) estimation and the Knapp-Hartung adjustment. RESULTS: Eight studies across six countries encompassing several million vaccinated individuals were included. The pooled incidence rate ratio (IRR) was 0.967 (95% CI 0.892-1.049; I2 = 69.2%), indicating no statistically significant increase in stroke risk. Subgroup analyses showed no evidence of effect modification across continent, risk-window length, dose category, SCCS variant, or age group. CONCLUSIONS: These findings provide no evidence of increased short-term stroke risk following BNT162b2 vaccination at the population level. The observed heterogeneity appeared to be partly driven by methodological differences rather than true biological variation in vaccine effect.

Humans↗
PubMed2026

Effects of Time-Based and Distance-Based Repeated Sprint Training on Physical and Physiological Adaptations in Collegiate Basketball Players.

PURPOSE: This study aimed to compare the effects of time-based (TB) and distance-based (DB) repeated-sprint training (RST) on athletic performance adaptations in collegiate basketball players during preseason and to examine whether the 2 training prescriptions produce different levels of homogeneity in the magnitude of individual adaptations. METHODS: Thirty young male basketball players (age = 21.3 [1.4]&#xa0;y) were randomly and equally assigned to 3 groups (n = 10): DB-RST, TB-RST, and an active control group. Participants completed a 7-week RST program performed 3 times per week, consisting of 4 sets of 4 to 9 repetitions per session. The DB-RST group completed each sprint by covering a fixed 35-m distance, whereas the TB-RST group performed each sprint maximally for a fixed 5-second duration. Performance assessments including countermovement vertical jump, 20-m sprint, Illinois change-of-direction speed, reactive strength index, Wingate anaerobic power, and cardiorespiratory fitness were conducted before and after the 7-week training period. RESULTS: Both training groups demonstrated significant performance improvements over the 7-week intervention and relative to the control group (P < .05). Similar gains were observed in the magnitude of adaptations in the countermovement vertical jump, 20-m sprint, Illinois change-of-direction speed, and reactive strength index for the DB-RST and TB-RST groups. Interestingly, the TB-RST group showed more gains than the DB-RST in the magnitude of adaptations in the peak and mean power outputs, as well as cardiorespiratory fitness. Moreover, the TB-RST group showed lower intersubject variability in adaptive responses across the measured performance outcomes following the training intervention. CONCLUSION: Our findings indicate that RST effectively enhances the performance of basketball players, and that implementing a TB-RST protocol is more effective than a DB-RST approach for producing greater adaptations in physiological variables-specifically anaerobic power output and cardiorespiratory fitness-over the 7-week preseason period.

Humans↗
PubMed2026

A point-of-use SERS assay for rapid detecting difenoconazole and flusilazole residues in fruit juices using Au/COF substrate.

We developed a ready-to-use surface-enhanced Raman scattering (SERS) sensor for rapid, pretreatment-free detection of difenoconazole (DIF) and flusilazole (FLU) in peach and lychee juices. The substrate combines Au nanoparticles (AuNPs) with covalent organic frameworks (COF) and is implemented on a portable 25-well plate, enabling in situ testing. Juices can be directly applied to the SERS-active Au/COF composite, allowing simultaneous adsorption and signal generation. The correlation between SERS intensity and logarithmic concentration yielded R-values between 0.925 and 0.986, meeting the monitoring needs of non-laboratory scenarios. The entire workflow completes within 12&#xa0;min, offering a faster alternative to conventional methods while maintaining high sensitivity and reproducibility. Detection limits reach 0.96-1.22&#xa0;ppb for DIF and FLU, both of which are below the regulatory maximum residue limits. Distinct SERS fingerprints enable reliable discrimination of mixed residues across juice matrices, supporting rapid on-site monitoring and cost-effective pesticide surveillance.

Triazoles↗
PubMed2026

Mul-PheG2P: decoupled learning and prediction-space fusion enables robust and interpretable multi-phenotype genomic prediction.

Genomic prediction of multiple phenotypes is crucial in modern plant breeding; however, existing methods struggle with negative transfer and lack interpretability, particularly across high-dimensional small-sample data and diverse species. To address this, we propose Mul-PheG2P, a novel paradigm based on decoupled learning and predictive space fusion. It employs a two-stage design: first training phenotype-specific encoders using genetic data, then decoupling phenotype-specific learning from cross-phenotype aggregation via an interpretable prediction layer. Mul-PheG2P outperforms existing methods across diverse crop datasets, including maize (Zea mays), wheat (Triticum aestivum), and tomato (Solanum lycopersicum). It provides a multi-scale interpretability chain: at the macro level, it quantifies phenotypic contributions via attention-based weighting; at the micro level, Integrated Gradients reveal the genetic basis of predictions. Notably, the model successfully identified the CCT (CONSTANS, CO-like, and TOC) motif regulating photoperiodism and the SQUAMOSA (SQUAMOSA promoter binding protein) promoter for inflorescence development, confirming its ability to capture functional biological mechanisms. These results highlight the high performance and interpretability of Mul-PheG2P, showcasing its value for low-cost, large-scale screening to advance precision breeding.

Phenotype↗
PubMed2026

Pilot randomized trial of intermittent theta-burst stimulation versus H-Coil transcranial magnetic stimulation for treatment-resistant depression.

BACKGROUND: Intermittent theta burst stimulation (figure-8-coil iTBS) and H7-coil repetitive transcranial magnetic stimulation (rTMS) are FDA-cleared treatments for major depression; yet their comparative effectiveness in treatment-resistant depression (TRD) has not been evaluated in randomized trials. This pilot randomized trial was designed to obtain preliminary comparative estimates and to explore whether baseline cognitive functioning relates to early remission. METHODS: Twenty-eight adults with TRD were randomized to six weeks of figure-8-coil iTBS delivered to the dorsolateral prefrontal cortex (DLPFC) (n = 15) or H7-coil rTMS delivered to the dorsomedial prefrontal cortex (DMPFC) (n = 13). The primary outcome was change in 17-item Hamilton Depression Rating Scale (HRSD-17) score from baseline to week 6, analyzed with ANCOVA. Additional outcomes included response, remission, and symptom trajectories through week 18. Exploratory analyses examined the association between baseline cognitive functioning, such as executive functions and memory, and remission. RESULTS: Twenty-five participants completed all 30 sessions. Adjusted week-6 HRSD-17 scores did not differ between groups (mean difference -0.40, 95% CI -5.23 to 4.43; p=.865). Response rates were 40.0% for figure-8-coil iTBS and 50.0% for H7-coil rTMS (p>.60), and remission rates were identical across groups (20.0%). Remitters showed higher baseline executive functioning than non-remitters in exploratory analyses, although these associations were not confirmed in adjusted models. CONCLUSION: In this pilot trial, figure-8-coil iTBS and H7-coil rTMS showed symptom improvement, with no clear between-group differences. Exploratory findings suggest a potential signal involving executive functioning that warrants further investigation. These results inform the feasibility and design of larger comparative trials. TRIAL REGISTRATION: ClinicalTrials.gov (NCT05902312).

Adult↗
PubMed2026

Recovery of polysaccharides from marc and pomace through sequential extractions assisted by ultrasound, enzymes and acid maceration.

This study evaluated the pilot-scale recovery of polysaccharides from Vitis vinifera pomace/marc using sequential extraction strategies combining high-power ultrasound (UAE), enzymes (EAE), and acid maceration (AAE). Laboratory-scale trials identified optimal conditions for enzyme dosage and liquid/solid ratio (L/S). Pilot-scale trials demonstrated that the extraction sequence and the processing byproducts influenced extraction efficiency, total soluble polysaccharide in the extract (TSP), and polysaccharide composition. Post-maceration at pH&#xa0;3.2, with/without the maximum enzyme dose after UAE in a L/S of 1.3/1, improved structural polysaccharide extraction from Viura pomace, while Tempranillo marc showed better recovery of pectic families and TSP with UAE&#xa0;+&#xa0;EAE. Separating grape pomace extract (UAE) from the post-maceration stage at pH&#xa0;3.2 produced two extracts: E1, with higher yield (19.9%), enriched in structural polysaccharides and oligosaccharides, and E2, enriched in high and medium molecular weight pectic polysaccharides (58.03%), a low degree of esterification (17.1%) and more complex rhamnogalacturan structures.

Polysaccharides↗
PubMed2026

Comparing the Effects of Push and Hold Isometric Training on Strength and Musculotendinous Adaptations: A Within-Subject Randomized Controlled Trial.

Lum, D, Oranchuk, DJ, Chen, SE, and Kong, PW. Comparing the effects of push and hold isometric training on strength and musculotendinous adaptations: A within-subject randomized controlled trial. J Strength Cond Res 40(9): 1050-1058, 2026-Despite recent interest in delineating pushing (PIMA) and holding (HIMA) isometric muscle actions, training-induced adaptations have not been examined. As such, we compared the strength and morphological adaptations between PIMA and HIMA training. Twenty limbs across 10 adults (5 men, 5 women, age: 31.4 &#xb1; 6.5 years) were randomly assigned to PIMA or HIMA conditions and underwent 12 training sessions over 6 weeks. PIMA required subjects to exert force against a fixed lever while the HIMA limb maintained a set joint angle while resisting an isotonic lever. During each contraction, subjects had to exert force at 70% of maximal voluntary contraction for 20 seconds at an 80&#xb0; knee angle, for 4-6 repetitions. Subjects completed isometric, concentric, and eccentric knee extension assessments for both limbs before and after the intervention. Pre- and postintervention ultrasound scans were performed to determine quadriceps muscle architecture and patellar tendon thickness. Increased isometric torque was found following both conditions (p < 0.05, g = 0.30-0.36), while concentric (p < 0.05, g = 0.31) and eccentric (p < 0.01, g = 0.50) torque only increased following PIMA. Both conditions increased muscle thickness (p < 0.05, g = 0.27-0.88) and vastus lateralis fascicle length (p < 0.05, g = 0.20-0.31). Only HIMA increased patellar tendon thickness (p < 0.05, g = 0.12). The increase in total quadriceps (p < 0.05, g = 0.46) and especially rectus femoris (p < 0.05, g = 1.44) thickness was greater in HIMA. The results suggest that PIMA may be more effective at improving strength, while HIMA may be superior for inducing morphological adaptations. Larger sample sizes and more ecologically valid training programs are warranted to further elucidate potential differences between different isometric types.

Humans↗
PubMed2026

Effects of essential amino acid supplementation on musculotendinous recovery following eccentric plantar flexor exercise: a randomized controlled trial.

BACKGROUND: Exercise-induced muscle damage (EIMD) resulting from eccentric contractions leads to transient impairments in muscle function. Essential amino acids (EAAs) stimulate muscle protein synthesis and may support recovery following damaging exercise. However, limited research has examined the effects of EAAs on muscle function following eccentric plantar flexor exercise. The purpose of this study was to examine the effects of EAA supplementation on indirect markers of muscle and musculotendinous recovery following EIMD. METHODS: Thirty-six recreationally active males (age: 21.2&#x2009;&#xb1;&#x2009;2.7&#x2009;years) were randomly assigned to an EAA group (10&#x2009;g of EAAs), placebo (10&#x2009;g of maltodextrin), or control (no supplementation). Supplements were consumed 30&#x2009;minutes before and immediately after an eccentric plantar flexor protocol (4&#x2009;&#xd7;&#x2009;50 repetitions followed by one set to failure) and during the 72&#x2009;hours recovery period. Indirect markers of muscle damage were assessed pre-exercise, immediately post-exercise, and 24, 48, and 72&#x2009;hours post-exercise, consisting of perceived soreness (NPRS), pain pressure threshold (PPT), calf muscle thickness and Achilles tendon thickness (ultrasound), and calf circumference. RESULTS: The eccentric protocol elicited responses consistent with EIMD, including increased soreness (p&#x2009;<&#x2009;0.001), increased calf muscle thickness and circumference (p&#x2009;<&#x2009;0.001), and reduced PPT (p&#x2009;=&#x2009;0.018). EAA supplementation attenuated soreness at 24&#x2009;hours compared with placebo. Calf muscle thickness increased following exercise in both groups; however, swelling returned to baseline by 72&#x2009;hours in the EAA group but remained elevated in placebo (Condition&#x2009;&#xd7;&#x2009;Time, p&#x2009;<&#x2009;0.001). Achilles tendon thickness decreased immediately post-exercise (p&#x2009;=&#x2009;0.005) but was not influenced by supplementation. CONCLUSIONS: EAA supplementation modestly reduced soreness and was associated with faster recovery of muscle swelling but did not influence tendon morphology within 72&#x2009;hours.

Humans↗
PubMed2026

External load metrics and monitoring in women's football match play: A systematic review.

This systematic review aimed to identify the most commonly used variables for monitoring external load during elite women's football matches and to compare reporting practices internationally and in Brazil. Searches were conducted in Web of Science, PubMed, and SciELO using the PICOS framework between February and March 2026, resulting in the inclusion of 35 studies. The main outcomes analysed were total distance covered (TD), distance covered across speed zones (HSR, VHSR, sprint), number of accelerations and decelerations, and maximum speed. TD and distance covered across speed zones were the most frequently reported indicators (94.3%), followed by HSR (82.8%) and sprint distance (68.5%). Considerable variability was observed in the classification of speed zones and thresholds used to define accelerations and decelerations, limiting comparisons between studies. External load values varied according to playing position and competition level, with international matches generally imposing greater demands than national competitions. Brazilian research remains limited and demonstrates notable methodological variability. This review proposes standardised speed and acceleration/deceleration thresholds based on the most recurrent ranges reported in the literature, supporting improved consistency in monitoring practices across elite women's football contexts.

Humans↗
PubMed2025

Systematic Review of Symptoms of Catatonia in Autism Spectrum Disorder.

Catatonia is a complex neuropsychiatric syndrome characterized by disturbances in mood, motor function, behavior and speech. It is increasingly recognized in individuals with autism spectrum disorder (ASD), although its identification remains challenging due to the overlapping clinical features of the two conditions. Shared characteristics, such as echophenomena, mannerisms, social indifference and repetitive behaviors can obscure accurate diagnosis. Although reports suggest a significant prevalence of catatonia among individuals with ASD, the condition remains poorly understood and frequently under recognized, leading to substantial diagnostic and treatment challenges. A systematic review was conducted to characterize the symptoms of catatonia in individuals with ASD. The literature search included peer-reviewed journal articles published in English from 1980 onward, focusing on studies examining co-occurring catatonia and ASD. A qualitative framework analysis was implemented to evaluate 45 peer-reviewed studies, with findings interpreted in relation to, and extending beyond, the diagnostic criteria for catatonia outlined in the International Classification of Diseases, 11th revision (ICD-11). The objective was to identify symptom patterns extending beyond current diagnostic frameworks and to support improved clinical recognition and diagnostic precision in ASD populations. The review identified six primary symptom clusters associated with catatonia in individuals with ASD: (1) psychomotor activity, (2) speech disturbances, (3) changes in behavior/skills/functions, (4) mental health symptoms, (5) physiological symptoms, and (6) symptoms related to arousal and awareness. Notably, several symptoms observed within these clusters are not currently included in the ICD-11 diagnostic criteria for catatonia. These additional symptoms include tics, motor compliance, incoherent speech, self-injury, impaired cognition, and appetite changes, suggesting a broader clinical presentation of catatonia in ASD populations than is presently captured in existing diagnostic frameworks. The findings of this review highlight the significance of enhancing clinicians' awareness and understanding of how catatonia manifests in individuals with ASD. Most notably, six symptom clusters, psychomotor changes, speech disturbances, behavioral and functional regression, affective and psychiatric symptoms, physiological symptoms, and arousal/awareness disturbances, were observed. Several symptoms identified in this review are not included in the current diagnostic criteria, and their recognition may facilitate in earlier identification and timely intervention, potentially preventing the severe consequences of untreated catatonia in this population.

Humans↗
PubMed2026

AI-enabled viral genomics: from virus discovery to host prediction and emerging variant forecasting.

The rapid expansion of metagenomic sequencing has generated vast repositories of viral sequence data that far outpace our capacity to interpret them using conventional approaches. Highly divergent sequences, sparse functional annotation, and taxonomically uneven sampling present fundamental challenges for reference-dependent methods, which lose sensitivity precisely for novel and understudied viruses with high public health relevance. Artificial intelligence (AI) provides a new avenue to address these challenges by enabling predictive inference from viral genomes and proteins while reducing dependence on sequence similarity. In this Review, we discuss representative advances in AI for virus discovery, taxonomic classification and functional annotation, prediction of host range and zoonotic potential, and efforts toward forecasting emerging variants. These advances are transforming viral genomics from a largely descriptive discipline into one with increasing predictive capability. We also critically assess the major challenges that constrain current approaches, including the availability of high-quality and representative datasets, rigorous model evaluation, biological interpretability and responsible governance for increasingly capable AI models.

Artificial Intelligence↗
PubMed2026

Systematic review of machine learning approaches for predicting sickle cell crisis and mortality risk at the climate-health nexus.

BACKGROUND: Sickle cell anemia (SCA) is a severe genetic blood disorder characterized by recurrent vaso-occlusive crises and increased mortality, with the greatest burden occurring in low- and middle-income countries. Climatic and environmental conditions, including temperature variability, humidity, rainfall, air pollution, and seasonal changes, have been associated with disease exacerbation. However, the extent to which these factors have been incorporated into predictive models remains unclear. This study systematically reviews the application of machine learning (ML) models for predicting SCA crises and mortality in relation to climate and environmental factors. METHODOLOGY: The PRISMA guidelines were used, and 34 peer-reviewed studies published between 2005 and 2026 were analyzed to identify the climate variables, ML approaches employed, and predictive performance. The reviewed studies applied a range of ML techniques, including artificial neural networks, random forests, support vector machines, decision trees, logistic regression, and deep learning models. Temperature, humidity, rainfall, wind speed, air quality indicators, and seasonal patterns were the most frequently examined environmental variables. RESULTS: The findings indicate that most existing models rely predominantly on clinical and demographic data, with limited integration of climate information and inadequate representation of high-burden regions, especially Sub-Saharan Africa. Studies incorporating environmental variables reported improved predictive performance and highlighted the potential of climate-informed early warning systems for SCA management. CONCLUSION: The review recommends development of interdisciplinary, climate-aware ML frameworks, expansion of longitudinal environmental datasets, and increased research in underrepresented regions to support climate-resilient and patient-centered SCA care.

Humans↗
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

Construction of precision clinical-proteomics risk model based on machine learning for predicting heart failure in type II diabetes mellitus.

BACKGROUND AND AIMS: Heart failure (HF) is a severe complication in type 2 diabetes mellitus (T2DM), but current risk stratification scores have limited predictive accuracy. We aimed to develop novel prediction tools integrating clinical variables with proteomics to improve risk stratification of hospitalization for HF in T2DM. METHODS AND RESULTS: In this study, we included 2111 UK Biobank participants with T2DM but no prior HF, and profiled 2920 proteins to predict 10-year incident HF hospitalization. Participants were randomly divided into training (70%), tuning (10%), and validation (20%) sets.Three prediction models were developed: a Clinical model based on demographic characteristics, comorbidities, medication use, and laboratory indices; a Protein model based on 40 proteins selected by the Light Gradient Boosting Machine (LGBM); and the Clinical OMics and Protein ASSessment for Heart Failure (COMPASS-HF) model, which integrated both clinical variables and the LGBM-selected proteins. Models were evaluated for area under the curve (AUC), sensitivity, and specificity. During follow-up, 168 participants (7.96%) developed incident HF. The COMPASS-HF model showed better discrimination than the Clinical model, with an AUC of 0.897 (95% CI: 0.850-0.945) versus 0.790 (95% CI: 0.723-0.856). It also demonstrated higher sensitivity (0.882; 95% CI: 0.725-0.967) and consistent performance in subgroups. COMPASS-HF effectively stratified risk of hospitalization for HF, with cumulative incidence rates of 31.9% in the high-risk group and 1.2% in the low-risk group. CONCLUSIONS: By combining clinical and proteomic variables, we developed a high-performance HF prediction model for T2DM, enabling precise risk stratification and informing early intervention strategies.

Humans↗
PubMed2026

Predictive evolutionary genomics: principles, validation, and practice.

Climate change and habitat loss are driving rapid evolutionary responses in populations world-wide, which creates an urgent need for evolutionary forecasting in conservation and agriculture. Such forecasting can be categorized into three time scales: trait-based models that use multivariate quantitative genetic equations to project correlated phenotypic responses up to c.&#xa0;20 generations, allele-based analyses that model allele frequency dynamics up to 100 generations, and composite adaptation scores that aggregate many small effects to yield predictions across longer horizons. However, these approaches have remained largely disconnected. Here, we present a Bayesian framework that integrates these three complementary approaches for evolutionary prediction. Our framework combines genomic, phenotypic, and environmental data to yield probabilistic predictions with explicit uncertainty. We show how predictive evolutionary forecasts can be validated with experimental evolution, field experimentation, historical specimens, and reciprocal transplants. These validated forecasts can help advance conservation and agricultural programmes by helping predict which populations are at risk of future extinction, optimizing breeding programmes for future climates, and planning ecosystem management under environmental change. By supporting a shift towards more predictive approaches in evolutionary biology, this framework may help improve our ability to manage biodiversity and food security in a changing world.

Genomics↗
PubMed2025

Predictive Validity of Violence Screening Tools in Emergency and Psychiatric Services: A Systematic Review.

Violence against healthcare staff, including a threat or an act of violence toward people during their work, poses a physical and psychological risk to workers internationally. Screening is an important strategy in preventing violence against healthcare professionals. The aim of this systematic review was to synthesize evidence on the predictive validity of risk assessment tools used to screen for violence and aggression risk toward healthcare workers in emergency and psychiatric departments (PD). Primary studies that examined the predictive validity of risk assessment tools for workplace violence were identified via a systematic search of Medline, PsycINFO, Embase, and the Cochrane databases. There were 62 eligible studies, ten of which had a lower risk of bias (RoB). Those studies with high RoB were primarily due to a failure to present calibration measures as part of the analysis. All included studies adopted a longitudinal design and were conducted in PDs. The ten highest-quality studies reported on eight different instruments, four of which showed acceptable to outstanding predictive performance. The Dynamic Appraisal of Situational Aggression and the Br&#xf8;set Violence Checklist showed the best predictive performance; they were also validated in emergency departments and are best suited for short-term risk prediction. We recommend that the selection of a risk assessment tool should consider the following: (a) the target population, (b) the violence operationalization, and (c) the purpose of the monitoring. We note that the use of a screening tool should be a part of a multicomponent strategy to ensure staff safety.

Humans↗