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Forensic taphonomy in fluvial water: A systematic review.

Human remains are frequently recovered from fluvial (lotic) water environments. Rivers, streams, canals and other flowing water bodies pose distinct challenges in forensic practice, particularly due to their current. Compared to other aquatic contexts, fluviatile taphonomy is underrepresented in the forensic literature and the last comprehensive summary was written over a decade ago. Therefore, a systematic review was performed to collect and summarise the current knowledge in forensics about fluvial taphonomy, including decomposition of remains, transport characteristics, search, postmortem submersion interval (PMSI) estimation, taphonomic alterations, and differences to other water bodies. 92 reports met the inclusion criteria for this review, most of them showed a moderate risk of bias. Their main findings were summarised and two major challenges identified. First, predictions about fluvial transport of human bodies pose a tremendous issue in forensic practice, leading to later detection and lower recovery rate of remains, complicating various subsequent analyses. Second, PMSI estimations are difficult particularly due to variable environmental conditions in fluviatile systems. Recommendations for future research in the area of fluvial forensic taphonomy include that case-related data such as the detailed decomposition state and river characteristics need to be made available. More standardised research protocols are required for a facilitated comparison between studies, environments and regions. This review provides forensic practitioners with a comprehensive, updated resource for the investigation of fluvial remains. It also guides future research towards a more efficient practice to build the basis for a broader, more robust and comprehensive synthesis, subsequently supporting analyses in forensic casework.

Humans

Cross-tissue multi-omics integration highlights BPHL and mitochondrial targets in Alzheimer's disease.

BACKGROUND: Mitochondrial dysfunction is a hallmark of Alzheimer's disease (AD), yet specific molecular targets remain to be fully characterized. METHODS: A summary-data-based Mendelian randomization (SMR) framework integrated AD genome-wide association study (GWAS) statistics (39,918 cases) with blood DNA methylation quantitative trait loci (mQTL), gene expression (eQTL), and protein (pQTL) data for 1136 mitochondria-related genes. Associations were assessed using Bayesian colocalization and HEIDI testing. Tissue relevance was evaluated in four brain regions (hippocampus, amygdala, cortex, frontal cortex) using GTEx and external transcriptomic datasets. RESULTS: Screening identified eight candidates supported across blood mQTL and eQTL layers. Stepwise central nervous system (CNS) evaluation singled out biphenyl hydrolase-like (BPHL) as the consistent candidate. Higher genetically predicted BPHL expression was associated with reduced AD risk across the hippocampus (OR=0.920, 95% CI 0.873-0.970), amygdala (OR=0.925, 95%CI 0.880-0.973), cortex (OR=0.943, 95% CI 0.908-0.978), and frontal cortex (OR=0.938, 95%CI 0.901-0.976). These findings aligned with protein-protein interactions connecting BPHL to respiratory complexes and lower BPHL expression in independent AD brains. Functional enrichment converged on oxidative phosphorylation pathways. CONCLUSIONS: By integrating multi-omics data with tissue-specific validation, this study nominates BPHL as a consistent protective candidate in the brain. These findings provide genetic support for mitochondrial molecular perturbations in AD, offering insights for future validation.

Alzheimer Disease

Artificial intelligence-supported double reading in European population breast cancer screening: A systematic review and meta-analysis of prospective programs.

BACKGROUND: Most European population mammography screening programs rely on double reading with arbitration, a model that delivers mortality benefit but is increasingly challenged by radiologist workload, variable specificity, and interval cancers. Artificial intelligence (AI) is being evaluated to support or optimize these established European screening pathways. PURPOSE: To synthesize prospective or program-embedded evaluations of AI conducted within European-style population screening programs and to estimate exploratory program-level absolute risk differences (RDs) per 1000 examinations for cancer detection rate (CDR) and recall. MATERIALS AND METHODS: We performed a prespecified, focused evidence synthesis of three large studies embedded within routine population screening programs operating under European-relevant workflows: MASAI (randomized AI-supported risk triage within a national program), ScreenTrustCAD (prospective paired-reader evaluation with AI as an independent reader in a double-reading framework), and PRAIM (nationwide decision-referral implementation). Outcomes were harmonized as AI-control RDs per 1000 examinations. Random-effects pooling used Hartung-Knapp-Sidik-Jonkman models. For the paired-reader design, sensitivity analyses applied a Kish effective sample-size approach across plausible within-examination correlations (ρ = 0.3-0.8). Positive predictive value (PPV) and workflow/time outcomes were summarized descriptively. RESULTS: Across 597,419 examinations, the pooled CDR RD was +0.9 per 1000 (95% CI -0.0 to +1.8; I2 ≈ 12%), consistent with a modest directional increase with borderline statistical uncertainty. The pooled recall RD was -0.6 per 1000 (95% CI -3.1 to +2.1; I2 ≈ 41-43%), indicating no consistent recall increase across screening programs. Where reported, PPV was higher with AI-supported screening. Efficiency signals included 44.3% fewer total readings in MASAI and shorter reading times for AI-normal examinations in PRAIM; in PRAIM, a program-level safety-net mechanism recovered 204 cancers that would otherwise have been missed. CONCLUSION: In European population screening programs characterized by double reading and arbitration, prospective program-embedded evidence suggests that AI integration may yield a small absolute increase in cancer detection (≈1/1000) without a consistent increase in recall, alongside improved PPV and efficiency signals. These findings suggestAI primarily as a complementary reader within European screening workflows, with implementation requiring explicit quality assurance and monitoring of interval cancers and stage distribution.

Humans

Candidate biomarkers for early Giardia duodenalis infection revealed by time-resolved secretome proteomics.

Giardia duodenalis is a zoonotic protozoan parasite that causes giardiasis in humans and other mammals. Early diagnosis remains challenging because current diagnostic methods, including microscopy and enzyme-linked immunosorbent assays (ELISAs), primarily detect established infections. Consequently, a critical diagnostic gap exists during the early stage of infection within the first 2-48 h following exposure. To address this limitation, we characterized the proteins released by in vitro-cultured G. duodenalis trophozoites under serum-free conditions and evaluated their potential as early diagnostic biomarkers. Proteomic analysis of culture supernatants collected during early trophozoite incubation identified 31,773 peptides corresponding to 2504 quantifiable proteins. Temporal profiling showed distinct secretion patterns, including proteins that peaked during the early stage, progressively accumulated over time, or remained persistently abundant throughout the incubation period. Based on their secretion characteristics and predicted immunogenic properties, five candidate biomarkers were selected for further evaluation. Polyclonal antibodies raised against selected candidates successfully detected the corresponding proteins in serum-free culture supernatants, providing preliminary evidence for their potential utility as early-stage diagnostic targets. These findings identify stage-associated candidate proteins that may serve as a resource for future early giardiasis diagnostic development, provide a valuable resource for investigating host-parasite interactions, and establish a foundation for future diagnostic assay development. However, further validation in clinical and biological samples is required to confirm their diagnostic applicability. SIGNIFICANCE: Giardiasis, caused by Giardia duodenalis, is a major diarrheal disease worldwide. Although enzyme-linked immunosorbent assays (ELISAs) provide rapid detection, their diagnostic utility is limited by the lack of biomarkers capable of identifying infection during its earliest stages, creating a critical gap in the detection of active infection within 2-48 h following exposure. Using data-independent acquisition proteomics, this study provides a time-resolved characterization of proteins released by G. duodenalis trophozoites into serum-free culture supernatants. Our findings reveal temporal secretion dynamics of protein secretion and identify candidate biomarkers with potential utility for the development of early-stage diagnostic assays pending rigorous biological and clinical validation. In addition, this proteomic resource provides a foundation for investigating host-parasite interactions and may facilitate the development of future point-of-care diagnostic strategies.

Giardiasis

How Do Climatic Factors Directly Influence the Incidence and Risk of Meningococcal Meningitis Across the African Meningitis Belt? A Narrative Literature Review.

Globally, the highest incidence of meningococcal meningitis occurs within the African meningitis belt, spanning 26 countries across sub-Saharan Africa. Meningococcal meningitis incidence is highly seasonal in this region specifically, with outbreaks mostly occurring during the dry season, characterized by low rainfall and atmospheric humidity, high temperature, and increased dust and wind speed. The strong seasonality of meningococcal outbreaks coincides with seasonal variation in climatic factors. This multicollinearity can make it difficult to identify environmental drivers of disease and the mechanisms by which they operate. This review aims to collate existing evidence to better clarify the mechanisms by which climatic variables influence meningococcal meningitis incidence. We examined the impact of dust, wind speed, temperature, rainfall, and land cover on meningococcal meningitis outbreaks. Within the literature, atmospheric dust and wind speed had the strongest statistical association with meningococcal outbreaks and demonstrated greater predictive probability than other climatic variables. However, several climatic factors have demonstrable influences on one another, reflected in the seasonality of meningococcal meningitis. Atmospheric dust can reduce precipitation levels in part through its radiative properties. Decreased rainfall and increasing temperatures can dry out soil, increasing its availability to be uplifted as dust. Alongside, this lower atmospheric humidity increases evaporative demand, leading to faster soil moisture loss and enhanced surface drying. We argue that rainfall, temperature, and land cover variability may act as part of a broader climatic mechanism, increasing atmospheric dust. This increases the incidence and risk of meningococcal meningitis.

Africa

Effects of exercise snacking on neuromuscular performance in insufficiently active adults: A systematic review and meta-analysis.

OBJECTIVE: To examine the effects of exercise snacking (ES) on neuromuscular performance in insufficiently active adults. METHODS: Six databases were searched from inception to July 17, 2026. Randomized controlled trials and non-randomized studies of interventions involving insufficiently active adults undertaking ES interventions were included. Outcomes were functional performance, muscular strength, and muscular power. A three-level random-effects meta-analysis was performed. Risk of bias was assessed with RoB 2 or ROBINS-I, and certainty of evidence was evaluated using GRADE. RESULTS: Nine studies (13 reports) involving 313 participants were included. In the primary three-level model, ES showed a small positive overall effect on neuromuscular performance (g = 0.37, 95% CI 0.16-0.58, p = 0.001), which remained supported under trial-clustered robust inference with small-sample adjustment. Domain-specific estimates for muscular power/velocity, functional performance, and muscular strength were positive but imprecise and were not statistically supported after small-sample robust adjustment. Robust moderator tests provided no evidence of between-subgroup differences, and the certainty of evidence was low for all outcomes. CONCLUSION: Current low-certainty evidence suggests that ES may produce a small improvement in overall neuromuscular performance. However, domain-specific effects remain uncertain because of the limited number of independent trials, and the overall prediction interval crossed zero, indicating uncertainty across future populations and settings. Larger, preregistered randomized controlled trials are needed to confirm these preliminary findings.

Adult

Microbial diversity, functional activities, and safety risks in fermented tea: a comprehensive review.

Microbial fermented teas are gaining global popularity due to their unique sensory profiles and health benefits. The quality and safety of these products are governed by complex microbial ecosystems that orchestrate the biotransformation of tea leaf components. This review addresses a critical paradox in the field: the same microbial activities that generate desirable bioactive metabolites, such as theabrownins and organic acids, also create ecological niches for mycotoxigenic fungi, posing significant health risks from contaminants like ochratoxin A, citrinin, and aflatoxins. While extensive research has cataloged the microbial diversity in these systems, a comprehensive framework linking processing environments to microbial community assembly, functional outcomes, and quantifiable safety risks remains elusive. This review systematically bridges this gap by synthesizing current knowledge on the microbial consortia-dominated by Aspergillus, Penicillium, Bacillus, and Lactiplantibacillus species-that drive tea fermentation. We critically analyze their functional roles in enhancing flavor, bioactivity, and potential probiotic activity while simultaneously evaluating the mechanisms of mycotoxin production and accumulation. By integrating microbial ecology, biochemistry, and food safety, we propose a forward-looking perspective focused on transitioning the industry from traditional, spontaneous fermentation to modern, controlled biotechnological processes. This approach, centered on the use of defined starter cultures, predictive modeling, and active biocontrol strategies, provides a roadmap for ensuring the consistent quality and safety of fermented tea products, ultimately unlocking their full potential as high-quality functional foods.

Tea

The Dual Role of Executive Functioning in the Association Between Family Socioeconomic Status and Children's Problem Behaviors.

Although prior research suggests that executive functioning may either mediate or moderate the association between family socioeconomic status (SES) and children's problem behaviors, examining these roles separately provides an incomplete account: mediation models may understate individual differences that are not attributable to the environment, whereas moderation models may understate the role of the environment in shaping personal characteristics. To integrate these perspectives, the present longitudinal study examined whether executive functioning simultaneously mediates and moderates the association between family SES and children's internalizing and externalizing problems. A total of 308 children in the early years of elementary school (MageT1 = 7.34 years; 138 girls) were assessed and followed up 39 months later. After controlling for children's gender, age, and grade, lower family SES at T1 significantly predicted higher levels of both internalizing and externalizing problems at T2. Executive functioning at T1 partially mediated these associations, indicating that differences in children's executive functioning partly accounted for socioeconomic disparities in problem behaviors. Executive functioning also moderated both associations: SES was negatively associated with problem behaviors among children with lower executive functioning but not among those with higher executive functioning. These findings highlight the dual role of executive functioning in the longitudinal association between SES and children's problem behaviors and suggest that executive functioning may be a promising target for efforts to reduce mental health disparities associated with socioeconomic disadvantage.

Humans

Bioactive peptides for meat quality and preservation: Integrating peptidomics and computational screening.

Bioactive peptides generated from meat proteins, fermented meat products, and slaughter by-products have attracted increasing attention as functional molecules for improving meat quality and preservation. In meat systems, peptides can be produced through endogenous postmortem proteolysis, microbial fermentation, gastrointestinal digestion, or controlled enzymatic hydrolysis of underutilized animal by-products. These peptides are closely associated with key meat science endpoints, including postmortem tenderization, oxidative stability, color retention, flavor development, microbial inhibition, and the valorization of processing by-products. However, although high-resolution peptidomics has greatly expanded the identification of meat-derived peptide sequences, their translation into practical meat applications remains limited by matrix interactions, processing stability, sensory constraints, safety concerns, and insufficient validation in real meat systems. This review synthesizes recent advances in meat-related peptidomics and computational screening, including sequence-based prediction, machine learning, molecular docking, molecular dynamics, stability assessment, and safety-oriented filtering. Particular attention is given to how these approaches can prioritize peptides with antioxidant, antimicrobial, flavor-modulating, and preservation-related functions under meat-specific technological constraints. By integrating peptide generation pathways, mass spectrometry-based identification, in silico prioritization, and meat quality endpoints, this review proposes a stage-gated framework for translating meat-derived bioactive peptides from discovery to application. Future research should strengthen matrix-specific validation, standardized peptidomic reporting, and safety assessment to support the use of bioactive peptides in meat quality improvement, clean-label preservation, and circular utilization of meat industry by-products.

Animals

Alternative End Joining Dependency Imposed by miR-21-5p Defines Radiation Resistance and a Targetable Vulnerability in Oral Squamous Cell Carcinoma.

PURPOSE: Clinical control of oral squamous cell carcinoma (OSCC) is constrained by heterogeneous radiosensitivity driven by divergent DNA damage response programs. The architecture and functional contribution of alternative end joining (Alt-EJ), an error-prone DNA double-strand break (DSB) repair pathway frequently upregulated in cancer, to radiation resistance remains poorly defined. METHODS AND MATERIALS: We profiled microRNAs in radioresistant OSCC clones and performed multiomic integration across an institutional OSCC cohort, an external OSCC cohort from the Gene Expression Omnibus, The Cancer Genome Atlas pan-cancer tumors, and cell lines characterized by Sanger Genomics of Drug Sensitivity in Cancer to infer DNA damage response characteristics, genomic scar features, drug sensitivity, and radiation therapy outcomes. DSB repair capacity and pathway usage were validated using functional assays, including Alt-EJ reporters and droplet digital PCR quantification of microhomology-mediated repair events. Core Alt-EJ effectors such as PARP1 and POLQ were perturbed genetically and pharmacologically. Therapeutic efficacy of PARP or POLQ inhibition with or without irradiation was tested in a syngeneic OSCC model, followed by bulk tumor transcriptomics to assess pathway engagement. RESULTS: Upregulation of miR-21-5p was not only selectively detected in radioresistant OSCC, but also modulated radiosensitivity in vitro and in vivo, and was associated with inferior postradiation therapy survival. A calibrated miR-21-5p target-gene signature tracked Alt-EJ activity across patient and mouse tumors and cancer cell lines, correlated with microhomology-mediated indels and broader genomic scarring, and predicted sensitivity to clinically available PARP inhibitors. Functionally, enforced miR-21-5p expression increased Alt-EJ usage and accelerated DSB repair, whereas inhibition or depletion of key Alt-EJ effectors reduced repair efficiency and restored radiosensitivity. In vivo, Alt-EJ targeting with PARP or POLQ inhibitor abrogated miR-21-5p-driven radiation resistance; transcriptomic profiling supported suppression of Alt-EJ programs as the operative mechanism. CONCLUSIONS: These findings establish a mechanistic link between miR-21-5p activity and Alt-EJ dependence, provide a clinically deployable signature to identify Alt-EJ-dependent OSCC, and support rational combinations of Alt-EJ targeting agents with radiation therapy to overcome treatment failure and advance precision radiation oncology.

MicroRNAs

Genome-wide identification and expression profiling of CSP and OBP genes in Stictocephala bisonia reveals candidate genes potentially associated with insecticide response.

Stictocephala bisonia is an important invasive agricultural pest. Due to the frequent application of insecticides in its habitat, this species is under intense selection pressure. Chemosensory proteins (CSPs) and odorant-binding proteins (OBPs) are known to play key roles in insecticide resistance, but their specific functions in S. bisonia remain unclear. In this study, we identified a total of 22 SbisCSPs and 16 SbisOBPs based on the S. bisonia genome. To screen for candidate genes potentially linked to insecticide resistance, we adopted a multi-criteria screening strategy that integrated phylogenetic analysis, molecular docking with three insecticides, and tissue-specific expression profiling. Phylogenetic analysis identified several SbisCSPs and SbisOBPs clustering with genes known to be involved in insecticide resistance, serving as an initial evolutionary filter. Molecular docking results indicated that λ-Cyhalothrin exhibited the strong predicted binding affinity with most of SbisCSPs and SbisOBPs. Subsequent qPCR validation of seven prioritized candidates revealed distinct expression patterns: SbisCSP22 was highly expressed in adults and demonstrated strong binding affinity to all three insecticides tested, suggesting a potential role in mediating multi-insecticide response. Conversely, SbisCSP17 was significantly upregulated in larvae, clustered with genes known to mediate imidacloprid resistance, and exhibited strong binding affinity to imidacloprid. Given its larval-specific expression and the soil-dwelling behavior of larvae, we hypothesize that SbisCSP17 is a key candidate gene for larvae coping with soil-treated insecticides.

Animals

Genome-wide characterization of heat shock protein genes reveals thermal stress-responsive candidates in Litopenaeus vannamei.

Heat shock proteins (HSPs) are conserved molecular chaperones involved in protein folding, refolding, aggregation prevention, and degradation of damaged proteins. However, the genomic organization and thermal responsiveness of HSP genes in the Pacific white shrimp (Litopenaeus vannamei) remain incompletely understood. Here, we performed a genome-wide analysis of the HSP gene family and examined its phylogenetic relationships, structural features, duplication patterns, sequence variation, interaction networks, and transcriptional responses to acute heat stress. A total of 34 HSP genes were identified and classified into the HSP90, HSP70, HSP40/DNAJ, HSP60, and small HSP families. Phylogenetic, motif, gene structure, synteny, and subcellular localization analyses revealed evolutionary conservation and structural diversification among family members. Three duplicated gene pairs were identified, comprising two segmental duplications and one tandem duplication. All pairs exhibited Ka/Ks ratios below 1, consistent with purifying selection of varying strength. Sequence analysis identified 295 nonsynonymous single-nucleotide polymorphisms, of which 12 were consistently predicted to be deleterious by multiple algorithms. Protein-protein interaction analysis indicated enrichment of protein-folding and cellular stress-response functions. RT-qPCR analysis showed significant induction of HSPA4, HSP90AA1, TRAP1, BiP, and DNAJA1 after 6, 12, and 24 h of exposure to 34 °C, whereas DNAJC3 was significantly induced only at 12 h. All six genes reached their highest transcript abundance at 12 h. These findings may provide a genomic framework for HSP genes in L. vannamei and identify candidate genes and variants associated with thermal stress responses.

Animals

Modelling peak microbial pollution events caused by combined sewer overflows in a source-to-sea system.

Predicting peak microbial pollution events in downstream coastal bathing waters caused by combined sewer overflows (CSOs) is essential for protecting public health. In urban areas, wastewater effluents, CSOs, and surface runoff can contribute to elevated microorganism loads to downstream waters. These pressures are likely to be intensified by growing population density and more frequent heavy rainfalls due to climate change. This study developed a process-based model to simulate Escherichia coli (E. coli) emissions, transport, and fate from the initial sources to coastal beaches. A three-year retrospective simulation (2017-2019) shows that E. coli concentrations in CSO discharges varied widely across the catchment (4.6 - 7.3 (log10 CFU 100 ml-1)). 99th percentile E. coli concentrations (4.0 (log10 CFU 100 ml-1)) at the inland water outlet were dominated by local CSO emissions, whereas 90th percentile E. coli concentrations (3.6 (log10 CFU 100 ml-1)) reflected cumulative upstream contributions from both CSO and effluent emissions. With the simulation accuracy of 89%, the model reliably reproduced the E. coli dynamics on the downstream beach and showed strong performance in representing peak concentrations based on Complementary Cumulative Distribution Function (CCDF) analysis. The process-based model enables quantitative tracking of source contributions and identification of pollution hotspots, providing support for mitigation measures. The study lays down a source-to-sea modelling framework for representing pollution transport across the aquatic continuum and provides a transferable tool for microbial pollution forecasting and climate adaptation planning.

Climate projection

Penalized Cumulative Probability Model for a Continuous Outcome Subject to Detection Limits.

Mixed-type outcome data occur when the outcome variable's distribution is a mixture of both continuous and discrete ordinal variables. Such mixed-type outcomes are common in biomedical, psychological, and the health sciences, particularly for variables having either a detection or quantitation limit. When interest lies in identifying a combination of genomic features associated with a mixed-type outcome, any method used would require a variable selection strategy for high-dimensional data. Unfortunately, few variable selection methods exist for modeling a mixed-type outcome when the covariate space is high dimensional. This study develops a high-dimensional penalized cumulative probability model (CPM), to allow for the identification of genomic features associated with mixed-type outcome of interest. We demonstrated how such model may be estimated using the iterative penalization procedure-the generalized monotone incremental forward stagewise (GMIFS) algorithm. The Model-X knockoffs procedure was combined with the estimation algorithm to control the false discovery rates (FDR) when performing variable selection. Through extensive simulation studies, our penalized CPM was shown to outperform alternative methods in terms of controlled variable selection performance by achieving high statistical power with the FDR being controlled at the target level. We demonstrate the utility of our method by applying it to predict estimated glomeruli filtration rate (eGFR) in kidney transplant recipients at 24 months post-transplant using baseline gene expression data as predictors. Our CPM model identified five genes associated with this mixed-type outcome which have important links to renal disease, which may provide prognostic guidance for kidney transplantation recipients.

Models, Statistical

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

A systematic review of macaque brain stimulation: Trends and future directions.

Neurostimulation techniques can powerfully modulate neural circuit activity and provide causal insights into the relationship between brain function and behavior. Macaque monkeys have long been a key animal model for brain stimulation studies. While stimulating the macaque brain with one or a few electrodes has already taught us much about brain function and dysfunction, recent technological advances promise a future with more precise stimulation using many more electrodes. However, such possibilities also increase the number of choices an experimenter has when designing their study. We can learn from a rich past, but a comprehensive overview of which brain regions have been studied and with what stimulation parameters is lacking. Here, we present a PRISMA-compliant systematic review of 734 macaque brain stimulation studies using electrical and/or optogenetic stimulation. We find a striking bias in which brain areas have traditionally been stimulated: a mere 10 brain regions account for half of all studies, with the remainder of studies investigating approximately 150 other areas. Across studies, stimulation frequency robustly predicted direct behavioral effects independent of brain region, while amplitude did not. Future studies could more systematically explore less studied regions through lower stimulation frequencies (e.g., 20-50 Hz) alongside established ranges (∼200 Hz). Tools such as fMRI or optical imaging can capture neural circuit engagement evoked by these frequencies, even when behavioral effects are absent or remain subtle. Our synthesis offers a guide towards the next steps in high-channel-count, high-precision stimulation approaches.

Animals

A prospective crossover study comparing ICCS-recommended and Palmer-adjusted filling rates in children with spina bifida.

OBJECTIVE: This study aimed to investigate whether the maximal cystometric capacity (MCC) in children with spina bifida (SB) is indeed lower, as predicted by the Palmer formula, and to evaluate the impact of different bladder filling rates on urodynamic parameters. MATERIALS AND METHODS: This prospective, randomized, two-sequence crossover-controlled study included 70 children aged 3-18 years with spina bifida under regular follow-up. In Group 1, the first two bladder fillings were performed at the ICCS-recommended rate, and the third at 75% of that rate (Palmer formula). In Group 2, the sequence was reversed. Urodynamic parameters, including maximal cystometric capacity (MCC), bladder compliance, detrusor activity, filling pressures, and detrusor leak point pressure (DLPP), were analyzed across fillings. RESULTS: Cystometric bladder capacity was lower during fillings performed at the Palmer-adjusted rate compared with those at the ICCS-recommended rate. The proportion of reduced compliance significantly decreased in Group 1 (p = 0.046) but remained unchanged in Group 2. A significant positive correlation was observed between expected bladder capacity (EBC) and measured MCC in both groups (ρ ≈ 0.5-0.6). The highest correlation and agreement were found in Group 1 during the third filling at the Palmer rate (ICC = 0.606). No significant intra- or intergroup differences were observed in detrusor pressure, end-filling pressure, DLPP, or overactive bladder prevalence. CONCLUSION: Bladder filling rate was associated with differences in both cystometric capacity and bladder compliance in children with spina bifida. Fillings performed according to the Palmer formula (approximately 75% of the ICCS-recommended rate) were associated with capacities that more closely approximated age-expected values and with modest differences in bladder compliance. Conversely, faster filling rates did not produce similar benefits. These findings suggest that slower filling strategies may improve measurement consistency and agreement with expected bladder capacity estimates. However, the magnitude and direct clinical impact of these differences should be interpreted cautiously, particularly in light of the potential influence of sequence-related effects.

Humans

The global potential of freshwater microbes for plastic degradation.

Plastic pollution is becoming increasingly severe on a global scale, and the potential for biodegradation as a treatment method that is environmentally friendly merits greater attention. A significant number of genes that associated the degradation of plastic (PDAGs) have been identified, however, the distribution of these genes among microorganisms in global inland waters remains to be elucidated. A global-scale meta-analysis was conducted, incorporating approximately 1000 metagenome datasets of inland waters across seven continents. A total of 13,109 metagenome-assembled genomes (MAGs) were obtained by means of metagenomics binning, and 22,621 PDAGs were identified from these. Among these recognized PDAGs, phenylacetaldehyde dehydrogenase (PAD) was the most dominant (n = 16,664), followed by catalase (n = 5931). The predominant hosts for PAD and catalase were identified as Gamma-proteobacteria and Bacteroidia, respectively. The largest number of both PAD and catalase was found in MAGs from North America, while the average gene number in single MAG was highest in MAGs from Oceania. In accordance with the prediction of traits, PDAG-carrying MAGs from Europe demonstrated the fastest growth rate and the lowest optimal growth rate. Furthermore, 25 styrene monooxygenase (StyA) enzymes were identified, which were found to cluster into two distinct groups hosted by Alpha-proteobacteria and Gamma-proteobacteria, respectively. Moreover, 11 MAGs were observed to possess the complete pathway of polystyrene degradation. These results explored the potential of inland water microorganisms as a biological resource for plastic degradation and provided valuable microbial reference information that can be used to develop biological treatment technologies for mitigating plastics.

Plastics