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PubMed2026

Effects of Dynamic Neck Sensorimotor Biofeedback Training in Individuals With Mechanical Neck Pain: A Pilot Randomized Controlled Trial.

Mechanical neck pain (MNP) is commonly accompanied by pain-related functional limitations, sensorimotor disturbances, and fear of movement, which together may contribute to persistent disability. This preliminary randomized controlled trial study investigated the short-term effects of dynamic neck sensorimotor-based biofeedback training in individuals with MNP. 20 MNP patients from outpatient clinics were assigned to a biofeedback training group or a control group. The training group underwent dynamic biofeedback exercises twice weekly for 2 weeks, whereas the control group performed repeated cervical movements without biofeedback. Outcomes included cervical kinematics as repositioning errors (RPE), movement units (MU), maximal range of motion (ROM), and subjective measures, including pain intensity, Neck Disability Index (NDI), and Fear-Avoidance Beliefs Questionnaire (FABQ). All participants completed post-intervention assessments; adherence in the training group was 100%, with no missing data and no adverse events reported. Within the biofeedback training group, participants receiving biofeedback training demonstrated greater improvements in cervical repositioning accuracy during flexion (51.95%, p = 0.04) and extension (46.67%, p = 0.02), along with reductions in fear-avoidance beliefs related to physical activity and work (p < 0.05); these changes were less apparent in the active control group. Exploratory regression analyses suggested associations between improvements in repositioning accuracy and pain reduction, and between increased cervical range of motion and improvements in fear-avoidance beliefs related to physical activity. These pilot findings suggest that dynamic sensorimotor biofeedback training may improve proprioceptive acuity and fear-avoidance beliefs in individuals with MNP, supporting further evaluation in an adequately powered randomized trial.

Humans↗

PubMed2026

Dissociable neural mechanisms of cognitive enhancement through transcranial stimulation and behavioral training.

BACKGROUND: Transcranial direct current stimulation (tDCS) and adaptive working memory (WM) training are promising cognitive enhancement approaches; however, their neural mechanisms and potential synergies remain poorly understood. OBJECTIVE: We directly compared how tDCS and WM training modulate neural oscillations during WM performance and examined whether combining both interventions produces additive effects. METHODS: We randomized 112 healthy adults into four groups: control (sham tDCS + non-adaptive 1-back), tDCS-only (active tDCS + non-adaptive 1-back), training-only (sham tDCS + adaptive n-back training), or combined (active tDCS + adaptive training). Participants underwent five daily intervention sessions. We recorded high-density EEG during transfer n-back tasks at baseline, post-intervention, and one-week follow-up. RESULTS: All active interventions improved WM performance relative to the control group, with the combined group showing the largest gains (n-back accuracy: +15.6% vs. + 10.1% tDCS-only, +9.7% training-only, +0.7% control; all p < 0.001). Critically, tDCS selectively increased gamma-band (30-50 Hz) power in the frontal and parietal regions (cluster p = 0.018, d > 1.0), whereas WM training enhanced frontal theta-band (4-8 Hz) power and theta-gamma phase-amplitude coupling (both cluster p < 0.012, d > 0.85). The combined group exhibited both neural signatures. Brain-behavior correlations revealed dissociable relationships: gamma increases predicted n-back accuracy improvements (r = 0.61, p < 0.001), whereas theta enhancements correlated with operation span gains (r = 0.58, p = 0.002). CONCLUSIONS: tDCS and WM training enhance cognition through distinct yet complementary neural mechanisms: tDCS via gamma-mediated cortical excitability and WM training via theta-mediated cognitive control. These findings provide neurophysiological evidence for multimodal enhancement strategies that target parallel pathways within WM networks.

Humans↗

PubMed2026

Integrated multi-omics profiling of amniotic fluid identifies predictive biomarkers for fetal growth restriction trajectories.

BACKGROUND: Fetal growth restriction (FGR) is a complex condition with highly heterogeneous clinical outcomes, making prenatal distinction between transient and persistent growth failure challenging. This study aims to identify amniotic fluid (AF) biomarkers capable of differentiating distinct FGR trajectories and characterizing persistent growth failure mechanisms. METHODS: Integrated proteomic and metabolomic profiling was performed on AF samples from transient FGR (n = 11), persistent FGR (n = 9), and healthy controls (n = 13). Diagnostic and prognostic models were developed using multivariate analysis. Selected protein candidates were validated via ELISA in an independent cohort (n = 69). RESULTS: Multi-omics analysis revealed distinct molecular signatures for FGR stratification. A two-protein diagnostic panel (PDGFA and phospho-STAT5A) achieved an AUC of 1.000 in the discovery stage and 0.780 in the external validation cohort. For prognostic assessment, a molecular signature including IREB2, HLA-C, and PLXNB2 accurately predicted persistent growth failure from transient recovery (AUC = 0.966). Cross-platform integration highlighted the mass spectrometry-derived WASHC2C as a central hub protein with a significant progressive increase across the control, transient, and persistent groups (p < 0.001). CONCLUSIONS: This study establishes a multi-omics framework for prenatal FGR stratification. Our findings identify distinct molecular signatures reflecting the intrauterine environment and provide high-performance molecular tools for predicting divergent fetal growth trajectories to guide personalized clinical decision-making.

Humans↗

PubMed2026

Complication rates of 16- and 18-gauge needles for native kidney biopsies: a systematic review and proportional meta-analysis.

This systematic review and meta-analysis evaluated complication rates and diagnostic yield reported in studies of adult native kidney biopsy using 16-gauge (16 G) or 18-gauge (18 G) needles. We included randomized trials and cohort studies of real-time ultrasound-guided biopsies, including case series. MEDLINE, Embase, and CENTRAL were searched through October 2024. Two reviewers independently performed study selection, data extraction, and risk of bias assessment using Joanna Briggs Institute tools. Random-effects meta-analyses estimated pooled proportions with 95% confidence intervals (CI), and univariable random-effects meta-regression explored study-level associations with major complications, transfusion, or gross hematuria. We screened 4,499 titles and abstracts and reviewed 319 full-text articles; 62 studies comprising 68 biopsy series were included. The pooled major complication rate in studies using 16 G needles was 1.83% (95% CI: 1.20-2.79) and 1.29% (95% CI: 0.78-2.13) in studies using 18 G needles, with no statistically significant difference. Mean glomerular yield was 18.8 with 16 G and 17.5 with 18 G needles. In study-level meta-regression, studies with higher prevalence of acute kidney injury, lower mean estimated glomerular filtration rate, or lower mean hemoglobin reported higher pooled complication rates. Most studies were single-arm cohorts; between-needle differences therefore reflect indirect study-level contrasts. Interpretation is limited by retrospective design and heterogeneity across studies. Overall, studies using both needle sizes reported low complication rates and similar diagnostic yield, although definitions and reporting varied. Direct comparative studies are needed to determine whether meaningful differences exist.

Humans↗

PubMed2025

Worldwide prevalence of haemorrhoids: a systematic review and meta-analysis.

BACKGROUND: Haemorrhoidal disease (HD) is one of the most common anorectal disorders globally, significantly impacting individuals' quality of life and productivity. Despite its importance, global prevalence remains unclear due to limited population-specific studies. This study aimed to systematically assess the global prevalence of HD through a systematic review and meta-analysis. METHODS: We conducted a systematic review and meta-analysis by searching PubMed, Scopus, Embase, Web of Science, and Google Scholar up to March 31, 2025, without language restrictions. Studies reporting prevalence of haemorrhoids in general, clinical, or high-risk populations were included. Exclusion criteria comprised studies lacking total sample size, focusing on other anorectal conditions, or using duplicate or insufficient data. Four independent reviewers extracted and appraised study quality using the Joanna Briggs Institute tool. The primary outcome was pooled point prevalence of HD, analyzed using a random-effects model with 95% confidence intervals (CIs). The study was registered in PROSPERO (CRD420251045600). RESULTS: From 6,312 records, 150 studies (210 datasets) comprising 8,960,338 individuals were included. The global pooled point prevalence was 25.92% (95% CI: 22.62-29.22). Lifetime prevalence was 27.19% (95% CI: 14.77-39.60), and one-year prevalence was 21.65% (95% CI: 14.33-28.97). Prevalence was higher in women (27.33%, 95% CI: 21.84-32.82) than in men, and highest in the African region 28.07% (95% CI: 15.34-40.79). Invasive diagnostic methods (28.05%, 95% CI: 23.86-32.26) yielded higher prevalence estimates than non-invasive methods. Also, factors showing associations with HD in unadjusted analyses include older age, obesity, pregnancy, diabetes, family history, constipation, and hypertension. CONCLUSION: HD remains a prevalent condition globally, with minor variation across regions. The burden is consistent regardless of socioeconomic context. Diagnostic method and population characteristics influence prevalence estimates. These findings underscore the importance of targeted prevention and early intervention strategies, especially for at-risk groups.

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

Navigating Social Media: Balancing Connectivity With Media Literacy to Combat Misinformation and Protect Mental Well-Being.

BACKGROUND: The pervasive use of social media has created a complex digital ecosystem where high connectivity coexists with significant challenges, including the rapid spread of misinformation, particularly regarding mental health, and documented negative impacts on psychological well-being. Platform architectures designed for engagement maximization have been identified as central factors in both issues. OBJECTIVE: This paper critically analyzes the interconnected relationships between social media use, misinformation dissemination, and mental health impacts, with particular attention to psychiatric misinformation across diagnostic categories (e.g., depression, anxiety, ADHD). A primary objective is to evaluate the potential of advanced critical digital literacy frameworks to serve as protective mechanisms against these dual threats. METHODS: A systematic search was conducted following PRISMA 2020 guidelines across APA PsycInfo, PubMed, JSTOR, and Google Scholar for literature published between January 2018 and March 2026 (updated from the original 2023 search). The search yielded 2672 records. After removing 624 duplicates, 2048 records underwent title and abstract screening, with 1802 excluded. The remaining 246 full-text articles were assessed for eligibility, resulting in 86 studies included in the final qualitative synthesis. Inter-rater reliability was established (Cohen's κ = 0.82). Quality assessment was conducted using the Joanna Briggs Institute Checklist, AXIS, and CASP tools, with findings weighted by methodological quality. A thematic analysis was undertaken to synthesize findings. RESULTS: The analysis reveals that core architectural features of social media platforms, algorithmic curation and engagement-based metrics, simultaneously foster environments ripe for misinformation spread and contribute to psychological distress, including anxiety, depression, and harmful social comparison. Psychiatric misinformation specifically (e.g., inaccurate claims about treatment effectiveness, diagnostic criteria, and medication side effects) represents a growing concern, particularly on image- and video-based platforms. The findings indicate that conventional media literacy approaches focused solely on fact-checking are insufficient. Instead, a critical digital literacy framework encompassing algorithmic awareness, data literacy, and emotional awareness is essential for building user resilience, with evidence from high-quality systematic reviews supporting this approach. CONCLUSIONS: Navigating the complexities of modern social media requires an integrated approach combining "pedagogies of play" for experiential skill development with advocacy for structural change (e.g., algorithmic transparency, well being by design principles). This dual strategy empowers individual users to critically engage with digital content while advocating for ethical platform design, thereby safeguarding both mental well-being and democratic discourse. Implications for educators, mental health professionals (including competencies for addressing patient encounters with psychiatric misinformation), policymakers, and platform designers are discussed.

Humans↗

PubMed2026

Peptide molecular lock-engineered nanobodies enable an oriented dual-modal immunoassay for reliable detection of Cronobacter sakazakii.

Conventional nanobody ELISAs for trace Cronobacter sakazakii in powdered infant formula suffer from random orientation and low signal output. We developed an oriented dual-modal immunoassay that combines site-specific biotinylation via a C-terminal AviTag and a peptide molecular lock, enabling controlled surface orientation while preserving nanobody structural integrity. This strategy was further integrated with phage-displayed nanobodies for multivalent amplification and both fluorescent and colorimetric readouts. The assay exhibited a broad linear range of 103-106 CFU/mL, with limits of detection (LODs) of 6.70 × 102 CFU/mL for fluorescence and 1.55 × 103 CFU/mL for colorimetry, showing improved sensitivity compared with the conventional passive adsorption-based Nb-ELISA evaluated in this study. XGBoost-based multimodal fusion improved quantitative accuracy, and SHAP analysis elucidated modality contributions. In spiked powdered infant formula samples, recoveries ranged from 92.1% to 118% with coefficients of variation below 5.98%, confirming acceptable matrix tolerance and analytical reliability.

Cronobacter sakazakii↗

PubMed2026

Functional neuroimaging subtypes of obsessive-compulsive disorder: A systematic review and meta-analysis.

Obsessive-compulsive disorder (OCD) exhibits substantial clinical heterogeneity that may reflect underlying neurobiological diversity. Neuroimaging-based subtyping may advance precision psychiatry by identifying biologically distinct subgroups with differential treatment responses. This study systematically synthesized evidence from functional neuroimaging subtyping studies in OCD to identify reproducible neurobiological subtypes, characterize their clinical profiles, and establish a consensus-based classification framework. We reviewed 40 original studies employing machine learning, clustering, normative modeling, or classification approaches, encompassing approximately 8,150 patients. Consensus clustering identified three reproducible neurobiological subtypes. The Limbic-Hyperactive subtype, comprising approximately 40% of patients, exhibited amygdala and insula hyperconnectivity, elevated anxiety levels, predominant contamination and washing symptoms, and favorable response to cognitive-behavioral therapy. The Fronto-Striatal-Hypoconnected subtype, comprising approximately 35% of patients, demonstrated reduced orbitofrontal-striatal connectivity, cognitive inflexibility, predominant checking and ordering symptoms, and a favorable response to selective serotonin reuptake inhibitors. The Global-Disrupted subtype, comprising approximately 25% of patients, exhibited widespread connectivity disruption, greater symptom severity, and poor treatment response. Support vector machine classification achieved 81.5% accuracy for subtype assignment, though classification of OCD versus healthy controls showed limited generalizability in multisite settings (AUC 0.567-0.673). These findings support a neuroimaging-based framework for personalized treatment selection but require prospective validation.

Humans↗

PubMed2026

Development and validation of a novel LC-MS/MS method for simultaneous quantification of fidaxomicin and metabolite (OP-1118) from feces for gut pharmacobiome studies.

Fidaxomicin is a first-line antibiotic for treating Clostridioides difficile infection. While it has low systemic absorption and reaches high colonic concentrations, it is hydrolyzed to a less active metabolite, OP-1118. Few studies have completely described critical experimental details of liquid chromatography-tandem mass spectrometry (LC-MS/MS) for quantifying fecal fidaxomicin and OP-1118. This study developed and validated a simple, fast, and sensitive LC-MS/MS method to quantify fidaxomicin and OP-1118 in human and mouse feces. This method simplified fecal sample preparation without the use of solid phase extraction and optimized LC-MS/MS parameters. A broad working range (0.3-1000 ng/ml) in both diluted human and murine fecal matrices was achieved with good intra- and inter-day accuracy (93-107%), precision (1-7%), and recovery (70-105%) as well as little IS-normalized matrix effects. This method was utilized to quantify fidaxomicin and OP-1118 in human and murine fecal samples. This novel method was simple, fast, sensitive, and accurate in analyzing fecal fidaxomicin and OP-1118 and could be deployed to facilitate gut pharmacobiome research.

Feces↗

PubMed2026

Direct background subtraction LC-MS/MS assay for human plasma progesterone: Full validation and comparative application.

OBJECTIVE: To develop and validate a liquid chromatography-tandem mass spectrometry method based on direct background subtraction for the quantification of endogenous progesterone in human plasma. METHODS: Protein precipitation was used for sample preparation with deuterated progesterone as the internal standard. Chromatographic separation was performed on an ACQUITY C18 column using gradient elution with 0.1% formic acid in water and acetonitrile at a flow rate of 0.3 mL/min. Mass spectrometry was operated in positive electrospray ionization mode with multiple reaction monitoring. Instead of using analyte-stripped matrix or surrogate matrix, authentic plasma was directly used for all validation experiments. Quantitation was achieved by subtracting the background signal, and results were compared with those from the classical method using stripped matrix. RESULTS: Excellent linearity was achieved over 0.1-100 ng/mL (R2 ≥ 0.99). Precision, accuracy, recovery, matrix effect, and stability all met FDA and ICH M10 acceptance criteria. Compared with the classical method, the bias in Cmax and AUC0-t was within ±15%, indicating no significant difference between the two methods. CONCLUSION: The direct background subtraction method avoids laborious preparation of blank matrix, eliminates matrix effect discrepancies, and is simple, efficient, and low-cost. It can serve as a general strategy for endogenous substance determination.

Humans↗

PubMed2026

Ramu stunt virus genome reveals previously unreported segments and nucleocapsid domain duplication in Mechlorovirus.

Ramu stunt virus (RmSV), a member of the genus Mechlorovirus within the family Phenuiviridae, was previously described as a six-segmented RNA virus infecting sugarcane. In this study, we re-examined type material and additional isolates using high-throughput sequencing and RT-PCR validation, revealing that RmSV possesses a nine-segmented genome, making it the largest reported in the Phenuiviridae. This expanded architecture includes duplicated RNA segments (RNA 2a and RNA 2b) encoding nucleocapsid-like proteins and two novel segments (RNA 7 and RNA 8). Comparative analysis showed that RNA 2a and 2b share about 84% amino acid identity, while RNA 5 encodes a third nucleocapsid homolog, indicating unprecedented domain redundancy. Structural modeling confirmed that all three nucleocapsid proteins maintain a conserved fold despite low sequence identity, with electrostatic mapping suggesting differential RNA-binding potential. Additionally, RNA 6 encodes a hypothetical protein structurally similar to the rice stripe virus disease-specific S-protein, implicating a role in symptom development. Transcript abundance analysis revealed RNA 6 as the most highly expressed segment across isolates. These findings revise the genomic composition of RmSV, highlight mechanisms of genome plasticity and adaptive evolution in plant-infecting bunyaviruses, and underscore practical implications for diagnostic assay design, resistance breeding, and biosecurity surveillance.

Genome, Viral↗

PubMed2025

Influence of soil types with different soil-forming process on the qualitative and quantitative detection of microplastics by near-infrared spectroscopy.

Microplastics (MPs) have become a pressing global environmental threat, with soils-acting as sinks for MPs from multiple sources-gaining increasing attention. Near-infrared (NIR) spectroscopy offers a promising tool for MPs detection due to its rapid, non-destructive, and field-applicable features. Although previous studies have focused on the effects of individual soil components on the NIR detection performance of MPs, there is still a lack of systematic research on how the complex background-formed by the coupling of multiple physicochemical properties in natural soils-affects detection performance. This study focuses on soil types with different soil-forming processes, selected five representative agricultural soils to systematically evaluate how the combinations of physicochemical properties they represented affect the performance of NIR-based qualitative and quantitative analysis of MPs in soils. The results demonstrated that soil type significantly affected both the spectral response and detection performance of MPs. Brown Pedocals and Brown Earth exhibited clearer characteristic absorption and stronger linear responses, achieving higher identification accuracy under low (<1.5 %) or zero MPs concentrations and the best quantitative performance (R2 ≥ 0.988, prediction set root mean square error (RMSEP) ≤ 0.110 %). In contrast, Phaeozem and Red Soil were more prone to misclassification at low concentrations, while Fluvo-aquic Soil showed the poorest quantitative performance. This study is the first to reveal, at a holistic level, the critical constraints posed by natural soil complexity on the NIR detection of MPs, offering targeted empirical evidence to support the application of NIR technology in real-world soil environments.

Soil↗

PubMed2026

A systematic review of human avoidance learning: Cognition, computation, and methods.

Avoidance behaviour is fundamental for survival but can become maladaptive in clinical conditions. A large body of literature has accumulated on the dynamics of human avoidance learning. However, current theories and overviews do not provide an exhaustive account of this evidence. In this systematic review, we identify N = 116 studies on human avoidance learning. We analyse these studies with the goal of distilling robust empirical phenomena as a basis for theory-building, and examine their diagnostic value in differentiating between competing theories. We find that the evidence is difficult to reconcile with foundational two-factor and classical safety-signal accounts, and most strongly supports expectancy- and inference-based views, in which avoidance responses are selected with respect to represented consequences. At the same time, no current framework provides a complete account of the evidence: several findings point to an additional role for operant valuation, Pavlovian influences, and contextual or latent-state control over the expression of avoidance. Methodologically, we observe that the problem setting in the most common experimental paradigms is radically simpler than real-world avoidance and therefore unlikely to expose the limits of inferential or reflective mechanisms. Consequently, we argue that paradigms with greater computational demands and more realistic action affordances are required to identify the mechanisms underlying avoidance learning. Collectively, these insights provide a foundation for theoretical refinement, computational modelling, and methodological innovation, with implications for advancing interventions targeting maladaptive avoidance.

Humans↗

PubMed2026

An individualized nomogram for predicting progression-free survival in systemic anaplastic large cell lymphoma: a multicenter, retrospective, and internally validated study.

OBJECTIVES: To develop an individualized nomogram for predicting disease progression risk in systemic anaplastic large cell lymphoma (sALCL). METHODS: Independent predictors of progression-free survival (PFS) were identified using Cox regression in a multicenter retrospective cohort of 109 sALCL patients (2010-2022). These were incorporated into a three-factor nomogram, evaluated via bootstrapped internal validation (1000 resamples), ROC analysis, C-index, decision curve analysis (DCA), and clinical impact curve (CIC). RESULTS: A total of 29 PFS events occurred during a median follow-up of 31 months. Multivariable modelling selected serum β2-microglobulin elevation, extranodal disease, and front-line chemotherapy choice (CHOP versus CHOPE or BV+CHP) as autonomous progression drivers. Upon internal bootstrap validation, the nomogram yielded strong prognostic accuracy, achieving AUCs of 0.81, 0.85 and 0.87 for 1-, 3- and 5-year progression-free survival, alongside a corrected C-index of 0.779 (95% CI: 0.699 - 0.861). Calibration plots showed close agreement between predicted and observed outcomes, while DCA confirmed superior net clinical benefit versus conventional IPI or Ann Arbor stratification across multiple decision thresholds. CONCLUSION: This first sALCL-specific nomogram integrates clinical and treatment variables to provide personalized PFS risk estimation. While internally validated, this exploratory, observation-based tool requires external validation and recalibration in prospective cohorts before clinical implementation.

Humans↗

PubMed2026

Fused Deposition Modeling (FDM) of polyether-ether-ketone (PEEK) dental implants: A systematic review of the effect of printing parameters on mechanical behaviour and surface quality.

PURPOSE: This systematic review evaluated how FDM printing parameters influence mechanical behaviour and surface characteristics of 3D-printed PEEK and identified parameter combinations linked to the most favourable mechanical performance and surface quality. MATERIALS AND METHODS: An electronic search was conducted in: MEDLINE (Ovid), PubMed, Embase, Web of Science, Scopus, and Compendex (last update: January 2025). Studies that evaluated the effect of FDM printing parameters on mechanical and surface properties of PEEK were included. Outcomes comprised compressive, tensile, and flexural strengths, elastic modulus, fracture toughness, surface hardness, roughness, and wettability. RESULTS: Of 4005 reports screened, 54 manuscripts were included. 92.6% (n = 50) of articles showed low risk-of-bias, while 7.4% (n = 4) showed medium risk-of-bias. Tensile strength was the most investigated mechanical parameter (78%), followed by elastic modulus (41%), flexural strength (30%), compressive strength (20%), and fracture toughness (6%). Surface roughness was the most evaluated surface property (30%), followed by hardness (17%) and wettability (6%). Across studies, higher printing temperatures, lower printing speed, thinner layer thickness, and maximum infill ratio in a horizontal printing orientation were associated with higher strengths, less warpage, increased accuracy, and improved surface quality. CONCLUSION: Specific combinations of FDM printing parameters can significantly improve the mechanical and surface properties of PEEK. However, it is difficult to meet all the optimal conditions simultaneously. Thus, balancing between different parameters must be considered in practical production.

Benzophenones↗

PubMed2026

Navigated repetitive transcranial magnetic stimulation for post-stroke recovery: A systematic review and meta-analysis of randomized controlled trials.

Repetitive transcranial magnetic stimulation (rTMS) is a subcategory of non-invasive brain stimulation (NIBS), used to modulate brain plasticity and improve post-stroke recovery. Neuronavigation is used to improve the accuracy of stimulation with the aim of achieving a superior clinical outcome than with conventional targeting. The objective of this review is to evaluate the efficacy of navigated rTMS in subacute and chronic stroke patients in comparison to sham stimulation. We conducted a systematic-review and meta-analysis of randomized controlled trials (RCTs) identified from Pubmed, Scopus and Cochrane CENTRAL. Trials employing neuronavigated rTMS were included of these five types; high and low frequency rTMS, intermittent and continuous theta-burst stimulation (TBS) and Hebbian-type stimulation. 13 RCTs were included after a screening of 1900 studies. 606 patients receiving either active (n = 360) or sham stimulation (n = 246) were assessed. The pooled standardized mean difference (SMD) favored rTMS over sham SMD = 0.4 (95 %CI: 0.11-0.69), with moderate heterogeneity I2 = 55 %. Among stimulation modalities, continuous TBS showed the largest pooled effect. rTMS was also associated with significant improvements in disability-related outcomes, SMD = 0.61 (95 % CI 0.14-1.08). Navigated rTMS is associated with modest but significant improvements in motor and disability outcomes in subacute and chronic stroke. Large comparative trials are required to clarify the potential added value over conventional targeting approaches.

Humans↗

PubMed2026

Prevalence and risk factors of nutritional anaemia among adolescents in India: a systematic review with meta-analysis of prevalence.

BACKGROUND: Nutritional anaemia is a major public health concern among adolescents in India, threatening physical growth, cognitive development, and future maternal health. This systematic review with meta-analysis of prevalence aimed to estimate the pooled prevalence of nutritional anaemia among Indian adolescents aged 10-19 years and identify key associated risk factors. METHODS: A systematic search was conducted across PubMed, Embase, Web of Science, and Scopus up to February 2025. Data were extracted on study design, setting, diagnostic methods, prevalence, and risk factors. Quality was assessed with a modified Newcastle-Ottawa Scale. A random-effects meta-analysis estimated pooled prevalence, with subgroup analyses by state and gender, and pooled odds ratios for risk factors. RESULTS: Forty-five studies encompassing diverse Indian regions and 159,979 adolescents were included. The pooled prevalence of nutritional anaemia was 56% (95% CI: 49%-63%), with higher rates among girls (62%) than boys (39%). Iron deficiency (OR 2.38-4.68), other micronutrient deficiencies, low socioeconomic status, poor dietary diversity, female gender, and inadequate supplementation were consistently associated with higher anaemia risk. CONCLUSION: Nutritional anaemia impacts more than half of Indian adolescents, with notable regional and gender differences. Its complex nutritional, socioeconomic, and behavioural causes demand targeted, context-specific interventions to enhance adolescent health nationwide.

Humans↗