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PubMed2026

Diagnostic Performance of Machine Learning for Systemic Lupus Erythematosus: Systematic Review and Meta-Analysis.

BACKGROUND: Early and accurate diagnosis of systemic lupus erythematosus (SLE) and its organ involvement is essential. Previous reviews of machine learning (ML) in SLE combined heterogeneous tasks and validation strategies and may have overinterpreted model performance. OBJECTIVE: This study evaluated the diagnostic performance of ML and deep learning (DL) models for 3 clinically distinct SLE-related tasks: SLE classification or diagnosis, lupus nephritis (LN) diagnosis, and neuropsychiatric systemic lupus erythematosus (NPSLE) discrimination. We also assessed methodological quality and certainty of evidence. METHODS: PubMed, Embase, Cochrane Library, Web of Science, and IEEE Xplore were searched from January 2014 to April 2026. Eligible peer-reviewed diagnostic accuracy studies developed or validated ML or DL models for 1 of the 3 prespecified tasks, used an accepted reference standard, and provided data for a 2×2 contingency table. Bivariate random-effects meta-analyses with the Hartung-Knapp-Sidik-Jonkman adjustment were used to pool sensitivity and specificity. We reported 95% prediction intervals (PIs), assessed risk of bias using the Quality Assessment of Diagnostic Accuracy Studies for Artificial Intelligence tool (QUADAS-AI; Viknesh Sounderajah [Imperial College London]), and evaluated certainty of evidence using the Grading of Recommendations Assessment, Development, and Evaluation framework for diagnostic test accuracy. RESULTS: Twenty-nine studies were included: 17 for SLE classification, 5 for LN diagnosis, and 7 for NPSLE discrimination. In the primary task-stratified analysis, pooled sensitivity was 0.91 (95% CI 0.86-0.94; 95% PI 0.56-0.99), and pooled specificity was 0.94 (95% CI 0.91-0.96; 95% PI 0.69-0.99), with low heterogeneity (I²=23.9% and 22.9%, respectively). DL models showed a sensitivity of 0.93 and specificity of 0.95, compared with 0.88 and 0.94 for traditional ML models. Certainty of evidence was high for most analyses but low for LN diagnosis because of inconsistency and imprecision. All studies were retrospective, and only 9 of 29 (31%) performed independent external validation. Overall risk of bias was high or unclear in 22 of 29 (75.9%) studies. No study reported model calibration, decision-curve analysis, or net clinical benefit. CONCLUSIONS: ML models showed promising diagnostic accuracy across 3 distinct SLE-related tasks, but wide PIs, limited external validation, and pervasive risk of bias restrict conclusions about real-world generalizability. Prospective multicenter studies with standardized tasks and reference standards, independent external validation, and formal assessment of calibration and clinical utility are required before clinical implementation.

Humans↗

PubMed2026

Impacts of climate-driven yield changes on the affordability of healthy diets: a modelling study.

BACKGROUND: Food security is central to global nutrition improvement and public health goals, and healthy diets represent a higher-level aspiration beyond merely avoiding hunger. Climate change poses an increasing threat to food systems by affecting crop yields and food prices. Although climate change-driven risks to hunger have been widely studied, the extent to which climate change undermines the affordability of healthy diets while accounting for socioeconomic responses and regional inequalities remains insufficiently understood. This study aimed to quantify the effects of climate change on the future affordability of healthy diets under alternative socioeconomic and climate scenarios. METHODS: We developed an integrated modelling framework that explicitly couples multimodel crop-yield projections with an integrated assessment model (Global Change Analysis Model [GCAM]). Yield responses from six global gridded crop models driven by four climate models were integrated into GCAM, allowing endogenous socioeconomic adjustments such as land-use shifts, production reallocation, and price responses to emerge under shared socioeconomic pathways (SSPs). Diet affordability was then assessed using the Food and Agriculture Organization of the UN's Cost and Affordability of a Healthy Diet framework across three socioeconomic-climate scenarios (SSP1-2.6, SSP2-4.5, and SSP3-6.0). FINDINGS: Under a high-emissions pathway (ie, SSP3-6.0), climate change was projected to render healthy diets unaffordable for a model-mean of 119 million people globally by 2100, even when CO2 fertilisation effects are included, with the upper end of the model ensemble reaching about 1·6 billion people. In contrast, climate-induced affordability losses were found to be negligible under both a low-emissions pathway (ie, SSP1-2.6; -0·3 million) and a medium-emission pathway (SSP2-4.5; +0·2 million). Under a high-emission pathway, model-mean projections indicated that diet costs could increase by up to 12% in the most affected regions by the end of the century. Under medium emissions, cost increases were projected to remain below 4%, whereas under low emissions, affordability changes were projected to be minimum across regions (within approximately 0·5%). Substantial regional disparities emerged, with the largest and most consistent affordability losses concentrated in low-income regions that contributed least to historical greenhouse gas emissions. Under SSP3-6.0, these disparities persisted particularly in regions of Africa and Asia despite projected three-to-five-fold increases in income over the century, with climate-induced disruptions to food systems increasing the number of people unable to afford a healthy diet through mid-century. INTERPRETATION: Climate change is likely to exacerbate global nutritional inequalities by disproportionately increasing the affordability risks of healthy diets in regions that have contributed least to historical greenhouse gas emissions. Under high-warming scenarios, socioeconomic development alone is insufficient to fully offset these risks, highlighting the structural vulnerability of low-income food systems to climate-driven price shocks. These findings suggest that in the absence of targeted interventions, climate change could continue to undermine progress towards equitable and health-oriented nutrition outcomes. FUNDING: Ministry of Science and Technology of the People's Republic of China; National Natural Science Foundation of China; National Aeronautics and Space Administration Goddard Institute for Space Studies Climate Impacts Group; Future of Life Institute; and Global Alliance for Improved Nutrition.

Journal Article↗

PubMed2026

Isometric Exercises for Tendinopathies: A Systematic Literature Review.

PURPOSE: Musculoskeletal disorders are among the most common reasons for medical consultation, with tendinopathies accounting for up to 30% of such presentations. Although exercise remains the cornerstone of management, the most effective modality continues to be debated. Eccentric exercise has long been the mainstay, but the role of isometric exercise in pain modulation and functional recovery remains unclear. This systematic review aims to evaluate the current evidence on the efficacy of isometric exercises in the management of tendinopathies across various anatomic sites. METHODS: A systematic search was conducted in PubMed, MEDLINE, Embase, and the Cochrane Library from inception to August 1, 2025. Eligible studies included randomized controlled trials and prospective or retrospective cohort studies assessing isometric exercise interventions for tendinopathy, with or without comparator groups. Case series and case reports were excluded. Data extracted included participant demographic characteristics, site of tendinopathy, symptom duration, treatment duration, adherence, and outcome measures such as Victorian Institute of Sports Assessment (A, P, or G), visual analog scale, Patient-Specific Functional Scale, 36 item short form health survey (SF-36), and EuroQol 5-Dimension questionnaires. Imaging outcomes (ultrasound or magnetic resonance imaging) were recorded where available. Methodological quality and risk of bias were assessed using the Cochrane Risk of Bias tool in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. FINDINGS: The search identified 304 articles, of which 13 randomized controlled trials met the inclusion criteria, encompassing 336 participants (40% female). Tendinopathy sites included the patellar (n = 4), Achilles (n = 3), lateral elbow (n = 2), rotator cuff (n = 2), wrist extensor (n = 1), and gluteal (n = 1) tendons. Median symptom duration was 23 months (interquartile range, 3-51 months). Intervention periods ranged from a single 45-minute session to 4-month exercise programs. Treatment adherence was high initially (nearly 100%) but declined over time, with 70% of participants in the isometric and 58% in the control (isotonic) groups completing ≥80% of sessions. Pain reduction and functional improvement were statistically significant in only 3 studies. Imaging-based outcomes were inconsistently reported, and study heterogeneity precluded meta-analysis. Overall methodological quality was rated as good in 3 studies and poor in 10. IMPLICATIONS: Current evidence provides limited support for the superiority of isometric exercise in tendinopathy management. Although isometric regimens appear tolerable and may confer short-term analgesic benefits, their long-term efficacy relative to eccentric or isotonic protocols remains uncertain. Future research should prioritize standardized outcome measures, longer follow-up, and uniform diagnostic criteria to strengthen the evidence base for exercise prescription in tendinopathies.

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

Factors associated with periprosthetic joint infection following total knee arthroplasty: an updated systematic review and meta-analysis.

BACKGROUND: This study aimed to systematically evaluate factors associated with periprosthetic joint infection (PJI) following total knee arthroplasty (TKA), and thereby to provide evidence-based references for clinical prevention and perioperative risk stratification. METHODS: Computerized searches were conducted in the following databases from their inception until May 26, 2025: PubMed, Web of Science, Embase, the Cochrane Library, CINAHL, China National Knowledge Infrastructure, Wanfang Database, Chinese Scientific Journal Database, and Chinese Biomedical Literature Database. Two researchers independently screened the literature, extracted data, and assessed study quality. The methodological quality was assessed using the Newcastle-Ottawa Scale. Quantitative synthesis was performed when at least two studies reported comparable exposure definitions and sufficient comparator information; otherwise, narrative synthesis was used. Review Manager 5.4 software was used for the primary analysis. This study is registered on PROSPERO (CRD420251079339). RESULTS: A total of 25 observational studies were included in the qualitative synthesis, of which 24 contributed to the primary quantitative synthesis. Quantitatively pooled factors associated with PJI included male sex (OR = 1.39, 95% CI 1.27-1.51), BMI ≥30 kg/m2 (OR = 5.72, 95% CI 2.65-12.36), prolonged operative time, type 2 diabetes mellitus (OR = 2.09, 95% CI 1.45-3.01), rheumatoid arthritis (OR = 2.64, 95% CI 1.38-5.02), smoking (OR = 1.65, 95% CI 1.34-2.04), blood transfusion (OR = 2.27, 95% CI 1.59-3.25), American Society of Anesthesiologists score ≥3 (OR = 2.73, 95% CI 1.02-7.32), history of hormone therapy (OR = 4.88, 95% CI 2.90-8.22), postoperative urinary tract infection (OR = 3.59, 95% CI 1.15-11.21), intraoperative blood loss >200 ml (OR = 1.51, 95% CI 1.03-2.22), postoperative drainage tube placement duration ≥24 h (OR = 2.23, 95% CI 1.50-3.32), preoperative anemia (OR = 1.82, 95% CI 1.67-1.99), and combined pulmonary disease (OR = 5.54, 95% CI 1.93-15.96). Age was narratively summarized because its classification differed substantially across studies. CONCLUSION: Multiple demographic, comorbidity-related, and perioperative factors were associated with PJI after TKA. However, because the included studies were observational and clinically heterogeneous, these findings should be interpreted as associations rather than causal effects. Optimization of modifiable factors may help reduce the burden of PJI, but further prospective studies using standardized PJI definitions and adjusted effect estimates are required.

Humans↗

PubMed2026

Exploring Professional Experiences in Caring for Vulnerable Migrants in an Italian Rural Reception Centre: A Qualitative Study Using Multidimensional Textual Analysis-Professional Experiences in Rural Migrant Care.

AIM: This study aims to explore the experiences, strengths, challenges, and potential improvements for professionals in managing the complex needs of vulnerable migrants (VM) in an Italian rural reception centre. METHODS: A qualitative study using semi-structured interviews was conducted in April 2024. Data were analysed using the Automatic Analysis of Textual Data, based on Fraire's seven-step model for Exploratory Multidimensional Data Analysis. DATA SOURCES: Data were collected from 16 professionals working in a rural reception centre in southern Italy. Interviews were conducted and analysed using AATD in April 2024. FINDINGS: The analysis identified two main dimensions of professionals' roles: balancing systemic responsibilities with personal engagement and managing immediate needs versus long-term integration goals. Professionals face significant challenges, such as resource scarcity, bureaucratic inefficiencies, and emotional fatigue, which impact their well-being and the quality of care provided to migrants. Resilience, adaptability, and multidisciplinary collaboration were identified as key strengths. CONCLUSION: The study highlights the dual nature of professionals' work in reception centres, requiring them to balance operational tasks with emotional involvement in migrant care. Targeted interventions and systemic reforms are necessary to support professionals and enhance the quality of care for vulnerable migrants, particularly in resource-constrained rural settings. IMPLICATIONS FOR PRACTICE AND/OR PATIENT CARE: This study underscores the importance of providing targeted support to professionals working in reception centres, including training in intercultural competence, stress management, and coping strategies. Policies should address systemic challenges and provide resources to enhance healthcare delivery and social integration programs. REPORTING METHOD: This study adhered to the EQUATOR guidelines for reporting qualitative research (COREQ). The findings were reported in compliance with these guidelines, ensuring methodological rigour and transparency. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: This study highlights the critical need for targeted support and training for professionals working in reception centres, particularly in rural settings. To improve care for vulnerable migrants, professionals should receive training in intercultural competence, stress management, and coping strategies to better navigate the complex challenges they face. Furthermore, systemic changes are necessary to alleviate the pressures on reception centres, such as streamlining bureaucratic processes and enhancing healthcare infrastructure, particularly in rural areas where resources are limited. By addressing these needs, we can improve the well-being of both the professionals and the migrants they serve, fostering more effective support systems and better care outcomes. Additionally, fostering multidisciplinary collaboration and community engagement can contribute to more comprehensive and sustainable care models. PROTOCOL REGISTRATION: The Ethics Committee of the University of Rome Tor Vergata approved this study on 07/07/2021 (protocol registration number 160.21).

Humans↗

PubMed2026

Diagnostic performance of panfungal PCR on tissue specimens for the diagnosis of invasive fungal diseases: a systematic review and meta-analysis of the Fungal PCR Initiative (FPCRI).

UNLABELLED: Invasive fungal diseases are difficult to diagnose because of the limited sensitivity of culture. Panfungal PCR amplicon sequencing assays (targeting ribosomal RNA, such as 18S, 28S, ITS) are recommended for fungal identification in histopathology samples showing fungal elements. However, data describing its overall performance and consistency are lacking. This systematic literature review and meta-analysis assessed the performance of panfungal PCR on formalin-fixed paraffin-embedded (FFPE) and non-fixed (fresh or frozen) tissue samples. A systematic literature search was performed to include studies reporting the use of panfungal PCR for fungal identification in FFPE or non-fixed tissue samples. PCR sensitivity and specificity were assessed using the reference standard of histopathology showing fungal elements. Quality assessment was performed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Pooled estimates were obtained using random-effects meta-analysis. Twenty-eight studies were included. In FFPE samples (18 studies, 852 samples), sensitivity and specificity were 75.4% (95% confidence interval [CI], 59.2-86.6) and 93.5% (70.2-98.9), respectively. Sensitivity in non-fixed samples (13 studies, 207 samples) was 86.5% (74.7-93.3), while specificity could not be assessed (insufficient data). Comparative analyses showed a significantly higher sensitivity of panfungal PCR over culture (88.2%; 76-94.7 vs 52.2%; 39-65, P = 0.001). Sub-analyses could not demonstrate the superiority of one PCR target over another due to limited data. Panfungal PCR exhibited adequate sensitivity and good specificity in FFPE samples. Sensitivity was even higher in non-fixed samples and largely superior to culture. Nevertheless, large interstudy variability was observed, warranting interlaboratory studies to define the optimal PCR target and standardized protocols. IMPORTANCE: Invasive fungal diseases are difficult to diagnose because of the low sensitivity of culture. Panfungal PCRs are widely used for fungal identification in tissue specimens but suffer from heterogeneous procedures and performance. This meta-analysis shows an acceptable sensitivity (75.4% and 86.5% in fixed and non-fixed samples, respectively) and good specificity (93.5%) of panfungal PCR, supporting its use, not only on histopathology-positive fixed samples but also in non-fixed samples concomitantly with other diagnostic tools (cultures and fungal-specific PCRs if available). These results provide a strong basis for further standardization of panfungal PCR techniques via interlaboratory assays to assess reproducibility and optimize analytical protocols. CLINICAL TRIALS: This study is registered with PROSPERO as CRD42023461148.

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

Interfacial engineering of cobalt tungstate-halloysite nanotube nanocomposite for electrochemical detection of synthetic vanillin in food matrices.

In processed foods and medicine, synthetic vanillin is widely used, although excessive intake poses toxicological risks. Due to the rising usage of synthetic vanillin in food products and associated health hazards, quick, sensitive, and reliable analytical methods are needed to precisely measure vanillin in complex food matrices. This work introduces a CoWO4@F-HNT/GCE nanocomposite as an efficient electrocatalytic modifier for glassy carbon electrodes aimed at trace-level synthetic vanillin detection. Structural and microscopic analyses confirmed phase-pure monoclinic CoWO4, preservation of the tubular aluminosilicate framework, and homogeneous nanoparticle anchoring on F-HNT. Differential pulse voltammetry provided a broad linear range from 0.01 to 372.14 μM and a low detection limit of 4.3 nM, together with excellent selectivity against common interferents, good cycling stability, and high inter-electrode reproducibility. These characteristics position the CoWO4@F-HNT-modified electrode as a cost-effective and reliable platform for on-site quality control of synthetic vanillin in complex food matrices.

Benzaldehydes↗

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

Machine learning-assisted Mn-N-C nanozyme colorimetric sensor array for trace-level detection of biogenic amines in meat.

Accurate detection of biogenic amines (BAs) in meat remains challenging due to their high structural similarity and co-occurrence. Herein, an Mn-N-C nanozyme was synthesized via a metal-organic framework confined pyrolysis strategy, possessing excellent oxidase (OXD)- and peroxidase (POD)-like activities. The dual enzyme-like activity showed Km values of 0.1584 mM (OXD) and 0.1498 mM (POD), respectively, in detection system. Leveraging these properties, a colorimetric sensor array was constructed, enabling the detection of four representative BAs within a concentration range of 2-10 ppm with 100% classification accuracy. In addition, a concentration independent recognition model based on an artificial neural network was developed to address signal nonlinearity interference in meat. The integrated system achieved accurate trace-level identification of BAs in perishable fish, pork, and chicken, demonstrating its applicability for early-stage BAs monitoring and quality deterioration warning during storage and transportation.

Biogenic Amines↗

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

Hot vs cold knife for endoscopic ablation of posterior urethral valves: a systematic review by the EAU-YAU paediatric urology working group.

INTRODUCTION: Posterior urethral valves (PUV) are the most frequent cause of congenital lower urinary tract obstruction in males. Despite early surgical ablation, up to 22% of patients develop chronic kidney disease and 11% progress to end-stage renal disease. Multiple endoscopic modalities have been described for valve ablation but the optimal technique remains uncertain. This systematic review aims to determine whether cold or hot knife ablation provides superior effectiveness for primary endoscopic treatment of PUV in a single surgical session. MATERIAL AND METHODS: A systematic search of PubMed and Embase databases was conducted to identify studies comparing cold and hot knife techniques for endoscopic ablation of PUV in children, covering all publications up to December 2025. The review was performed in accordance with PRISMA 2020 guidelines and was prospectively registered in PROSPERO (ID CRD420251180556). Original studies including patients <18 years who underwent primary valve ablation with postoperative cystoscopy or VCUG and ≥6 months of follow-up were included. Quality assessment was done using RoB 2.0 for randomized trials and MINORS for observational studies. RESULTS: A total of 1581 studies were identified, of which 26 met the inclusion criteria, comprising one randomized controlled trial, five prospective, and 20 retrospective studies constituting a sum of 1725 paediatric patients. The overall methodological quality of included studies was moderate, with marked heterogeneity in design, follow-up duration, and outcome reporting, limiting direct comparisons across series. Thus statistical analysis was not possible. Of these, 829 (48.1%) underwent cold valve ablation and 896 (51.9%) underwent hot ablation techniques. Within the cold group, most patients were treated with a cold knife (80.2%), followed by balloon dilatation (7%), the Mohan valvotome (6.5%), cold hook (5%), and, rarely, a modified venous valvulotome (1.3%). Among hot techniques, 32.8% of procedures were performed by electro-fulguration with a resectoscope, 29.4% using a Bugbee electrode, 23.8% with a hook electrode and 14% with laser-based systems. Follow-up ranged from 6 months to 22 years across studies. Single-session success rates for valve ablation ranged from 22% to 100% in the cold resection group and from 71.4% to 100% in the hot resection group. Reintervention for residual valves was reported in 0%-78% of cold cases and in 0%-28.6% of hot resections. Urethral stricture rates ranged from 0% to 11.1% after cold incision and from 0% to 23.8% after hot techniques. Reporting of postoperative outcomes such as urinary tract infection, incontinence, bladder dysfunction, vesicoureteral reflux (VUR) resolution, hydronephrosis improvement, and renal function varied widely among studies and was assessed using different methodologies. CONCLUSIONS: Both cold and hot ablation techniques for PUV achieved high single-session success rates and low complication rates. Cold resection appeared slightly safer, although this finding should be interpreted cautiously given the heterogeneity and observational nature of the available data.

Humans↗

PubMed2026

Digital health interventions for diabetes management in the eastern mediterranean region: A systematic review of types and effectiveness.

AIM: The aim of this study was to systematically review and evaluate the types and effectiveness of digital health interventions used for diabetes management in the Eastern Mediterranean Region (EMRO). METHODS: This systematic review, conducted according to PRISMA guidelines, searched PubMed, Web of Science, and Scopus up to May 2025 to identify studies on digital interventions for diabetes management in EMRO countries. Methodological quality of the included studies was evaluated using the EPHPP tool, and findings were categorized by intervention type, outcome measures, and intervention effectiveness. RESULTS: A total of 46 studies were included, mainly from Iran and Saudi Arabia. Phone calls and SMS were the most common digital tools. Digital interventions significantly improved HbA1c, fasting blood sugar, and several behavioral outcomes such as physical activity, medication adherence, and self-efficacy, while effects on psychological outcomes were mixed. CONCLUSION: Digital health interventions, especially phone calls and SMS, effectively improve glycemic control and self-care behaviors, though their impact on psychological outcomes remains inconsistent.

Humans↗

PubMed2026

Activity shapes large herbivores' ecological influences.

The ecological effects of large herbivores are shaped by their spatial and temporal patterns of activity (i.e. where, when and how intensely they use specific locations). When large herbivores' ecological influences are perceived to be undesirable, the traditional approach has been to reduce their population size. This numbers-first logic assumes that ecological effects scale primarily with abundance. We argue that this framing provides an incomplete understanding of large herbivores' ecological impacts. Using African elephants (Loxodonta africana) as a well-documented case study, we show that ecological effects on plants, animals and ecosystem processes correlate more with spatio-temporal patterns of activity than with population size. In large, open systems characterized by strong gradients of water availability, forage quality, shade and risk, elephants concentrate into predictable hotspots while relaxing activity elsewhere, generating localized impacts and opportunities for recovery. By contrast, in small, fenced or fragmented landscapes, where movements are constrained, and gradients are weak, spatial self-regulation breaks down, producing homogenized use and widespread ecological effects. We contend that understanding where, when and under what constraints herbivores use space provides a more general and mechanistic basis for interpreting ecological influence than abundance alone, with implications that extend beyond elephants to large herbivores globally.

Animals↗

PubMed2026

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

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

Soil Pollutants↗

PubMed2026

The interplay between circadian misalignment or sleep disturbances and cognition and brain function in individuals with different degrees of insulin resistance - a systematic review.

Disruption of sleep increases the risk of type 2 diabetes and worsens cognitive outcomes, yet few studies have evaluated the interaction between insulin resistance and sleep parameters in relation to cognitive outcomes or the risk of dementia. This systematic review examines how circadian misalignment and sleep disturbances affect cognition and neuroimaging findings in individuals with varying degrees of insulin resistance. Across 27 studies, disrupted circadian rhythmicity and sleep disturbances were negatively associated with brain health, possibly through its effects on insulin sensitivity, whereas the impact of sleep duration and quality were inconclusive. Methodological heterogeneity, reliance on cross-sectional designs, and limited control for confounders restricted definitive conclusions and highlighted the need for longitudinal and interventional studies with objective measurements. Nonetheless, the findings support circadian rhythmicity as a potentially modifiable risk factor for preserving cognition in insulin-resistant populations. Future research should prioritise prospective and interventional studies and focus on biological markers rather than self-reported outcomes.

Humans↗

PubMed2026

A smartphone-integrated Pt@Cu-HCF nanozyme-based paper sensor for on-site determination of total antioxidant capacity in marine oils.

Total antioxidant capacity (TAC) serves as a key indicator for evaluating the nutritional quality of foods. In this study, we designed a platinum-embedded copper hexacyanoferrate (denoted as Pt@Cu-HCF) nanozyme that exhibits high oxidase-like activity, efficiently catalyzing the oxidation of chromogenic substrates to generate robust colorimetric signals. Antioxidants quench hydroxyl radicals (∙OH) produced during the catalytic process, leading to a concentration-dependent suppression of the color signal. Leveraging this mechanism, a smartphone-integrated, colorimetric paper sensor for on-site TAC quantification was developed, using vitamin E as the calibration standard. The sensor was applied to determine TAC in fish oil, algal oil, and krill oil, demonstrating a linear response range of 9.78-312.5 μM and a limit of detection (LOD) of 6.41 μM. Validation using real-world marine oil samples showed excellent agreement with a commercial assay kit, confirming the reliability and practical applicability of this portable sensor for TAC measurement in complex biological matrices.

Antioxidants↗