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Silent crises in the COVID-19 pandemic shadow: a six-year medico-legal review of non-lethal intimate partner violence in Morocco.

Intimate partner violence (IPV) is a major global public health concern and one of the most prevalent forms of gender-based violence, with significant consequences. This study analyzes non-lethal IPV cases reported to a medico-legal unit of Casablanca between 2018 and 2023. Data from 4,784 female victims were reviewed, focusing on socio-demographics, violence types, perpetrator relationships, and judicial involvement across the pre-COVID, peak COVID-19, and post-COVID periods. Married women represented 59.2% of victims. Physical violence predominated (83.1%), while sexual violence was underreported (14.7%). The year 2020 marked a sharp increase in reported non-lethal IPV cases (n = 1,005), correlating with pandemic confinement. Among married women, judicial requisition (legal request for forensic examination) and medico-legal certification (medical documentation for judicial use) rates were high (81.5% and 81.0%, respectively). Post-pandemic years declined moderately but remained above pre-COVID levels. International comparison confirmed a global rise in IPV during COVID-19, with Morocco displaying comparatively higher rates of medico-legal documentation and judicial involvement. IPV in Morocco is entrenched and intensified by COVID-19. While the medico-legal system is robust in documentation, the system must evolve by integrating systematic psychological assessment into medico-legal evaluations, standardizing certification and referral protocols, and strengthening coordination between medico-legal, health, and social support services to improve victim protection.

Humans

The Case for Master Protocols for Rare Neurological Diseases.

Master protocol trials allow for simultaneous multiple hypothesis testing within a common framework and might be applicable for rare diseases. In May 2025, the Network for Excellence in Neuroscience Clinical Trials convened a multistakeholder conference to discuss master protocol trials in rare neurological disorders. In this paper, we explore how master protocol trial designs may apply to rare neurological disorders, using the neuronal ceroid lipofuscinoses as an example. Through shared protocol elements and trial infrastructure, master protocols may decrease cost and improve efficiency in testing potential therapeutics in rare disease, accelerating the delivery of urgently needed therapies to patients. ANN NEUROL 2026;100:477-486.

Humans

Machine learning-ready genomic biomarkers: ATF3 polymorphisms predict postoperative analgesic demand through AI-compatible phenotyping.

PURPOSE: To determine whether ATF3 polymorphisms can serve as genetic biomarkers for machine learning-based precision analgesia by establishing a genotype-phenotype association suitable for predictive modeling of postoperative opioid requirements. METHODS: In a prospective cohort of 167 adults undergoing abdominal surgery, ATF3 SNPs rs3122721 and rs3125293 were genotyped. A structured dataset architecture was developed to represent genetic profiles as input features for supervised learning models, enabling translational analysis of genotype‑dependent opioid consumption over 72 h. RESULTS: Patients with homozygous genotypes of the ATF3 SNPs had significantly higher opioid requirements than non‑carriers, despite reporting similar subjective pain scores. This consistent genotype‑dependent pattern provided a clinically relevant phenotype suitable for integration into predictive algorithms. CONCLUSION: ATF3 genotyping offers a promising biomarker for computationally informed precision analgesia. By linking genomic variability to clinically meaningful outcomes within a structured clinical and genomic framework, this approach supports the future development of risk-stratified clinical decision-support systems to optimize postoperative pain management.Trial registration ChiCTR1900021991, registered 30 April 2019. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at https://doi.org/10.1007/s13755-026-00480-9.

ATF3

A transcription factor-focused CRISPR screen identifies SKI as a BCL11A-independent repressor of ζ-globin.

The regulation of α-like globin genes, particularly the embryonic ζ-globin gene (HBZ), remains incompletely understood. To identify transcriptional regulators of HBZ, we establish a GFP reporter system based on the HBZ-P2A-GFP allele in erythroid cell lines and conduct a CRISPR/Cas9 screen targeting 1639 transcription factors. This screen identifies SKI as a potent HBZ repressor. Functional validation shows that SKI loss increases HBZ expression without impairing erythropoiesis, whereas SKI overexpression suppresses HBZ. Tet-on-inducible SKI overexpression and auxin-inducible SKI degradation indicate that SKI rapidly represses HBZ transcription. Transcriptome profiling further reveals that SKI deletion activates HBZ while minimally affecting other erythroid genes. Mechanistically, genome-wide occupancy analyses show that SKI binds the distal enhancers HS-10 and HS-40, with partial co-occupancy by BCL11A. Despite this overlap, dual knockout of SKI and BCL11A synergistically increases HBZ expression, as does base editing of the SKI-binding site within HS-10. We also identify a naturally occurring variant (chr16:193207G>A) within this enhancer in α-thalassemia patients with elevated ζ-globin levels. Together, these findings establish SKI as a direct, BCL11A-independent transcriptional repressor of ζ-globin. This work advances our understanding of globin gene regulation and suggests targeted ζ-globin reactivation as a potential therapeutic strategy for α-thalassemia.

Enhancer

Mapping Wastewater Pathogens and Their Associated Environmental and Public Health Risk Factors: A Systematic Review and Meta-Analysis.

BACKGROUND: Wastewater-based epidemiology (WBE) has emerged as a critical tool for public health surveillance, yet its application across diverse pathogens and geographical settings remains inconsistent. This systematic review synthesizes global evidence on wastewater surveillance to identify associated risk factors. METHODS: Following PRISMA 2020 guidelines (PROSPERO: CRD420261297382), a systematic search was conducted across PubMed, Scopus, Google Scholar, and Web of Science for studies published between 2000 and 2025. RESULTS: Thirty-nine peer-reviewed studies were included. The evidence base is geographically skewed toward the European Region (48.7%) and the Americas (23.1%), with significant underrepresentation in LMICs. Viruses were the primary biological target (89.7%), followed by bacteria (7.7%) and parasites (2.6%). A proportion meta-analysis of 31 eligible studies demonstrated a pooled wastewater pathogen detection prevalence of 62% (95% CI: 47.5-74.6%), with the European Region yielding the highest regional estimate (73%) and the African Region the lowest (8.3%). Conventional PCR and sequencing methods showed higher pooled detection rates (92.4% and 90.1%, respectively) than RT-qPCR (47.9%). CONCLUSION: WBE provides a robust early-warning system indicating a need for broader pathogen diversity, incorporating bacterial and parasitic surveillance and expansion into rural and resource-limited regions.

Contamination

Context matters: coordinated transcriptional regulation and root plasticity under multinutrient conditions.

Plants often encounter simultaneous imbalances in multiple nutrients, but the regulatory logic coordinating their responses remains poorly understood. We aimed to uncover shared transcriptional programs and regulatory nodes underpinning multinutrient adaptation in Arabidopsis thaliana roots. We analyzed publicly available RNA-seq datasets spanning 15 nutrient and beneficial element conditions using differential expression, co-expression network (WGCNA), and gene regulatory network analysis. Selected transcription factors (TFs) were validated via root phenotyping, suberin staining, and ionomic profiling under two-nutrient stress conditions. We identified a core set of 2050 genes responsive to multiple nutrient treatments, enriched for suberin biosynthesis, and structured into modular co-expression clusters. Eight prioritized candidate TFs (ARR10, GBF3, HHO5, NAC32, NF-YA3, NF-YB2, SARD1, and WRKY33) were shown to modulate root system architecture under specific nutrient combinations. WRKY33 and NF-YB2, in particular, regulated nutrient-responsive suberin deposition and ionomic plasticity. These findings reveal suberin remodeling as a shared downstream process in multinutrient responses and suggest that plasticity is not a fixed trait but a modular, polygenic, and context-dependent outcome. Repurposed TFs with pleiotropic functions coordinate structural and physiological traits, providing regulatory entry points for improving nutrient resilience.

Plant Roots

Comparison of three tracking methods to assess usage of two pediatric powered mobility devices for young children with cerebral palsy.

Powered mobility devices are underutilized for promoting self-initiated mobility in young children with cerebral palsy due to prioritization of walking, caregiver effort, device characteristics, and environmental factors. Understanding device usage patterns is important to assess the impact of powered mobility interventions on child outcomes. As part of clinical trial (NCT04684576), three objective tracking methods including integrated loggers, Global Positioning System trackers (GPST), and caregiver reported activity logs (CRAL) were compared to provide insights into device usage patterns. Metrics included play session frequency, session duration, total usage minutes, and unique usage days for two powered mobility devices: Modified Ride-on Cars (MROC) and the Permobil Explorer Mini (EM). Twelve children with cerebral palsy used each device for eight consecutive weeks in home and community settings (16 weeks total), with device ordered randomized. Results showed no significant differences among tracking methods for the MROC. For the EM, only session duration differed between GPST and CRAL. Correlation analysis revealed variable relationships amongst tracking methods for both devices. The EM was used more frequently than the MROC, with significantly greater total usage minutes and session duration via CRAL, not GPST. The findings highlight the need for reliable tracking technologies that can be used across powered mobility devices.

Child, Preschool

Revealing potential biomarkers and metabolic mechanisms of ovarian aging in hens during late laying period based on machine learning and metabolomics.

Ovarian function decline during the late laying period represents a major bottleneck for the economic efficiency of the global poultry industry. However, the underlying metabolic mechanisms and reliable early-warning biomarkers for ovarian aging remain poorly understood. In this study, we performed the first untargeted LC-MS/MS metabolomics analysis of ovarian tissues from Taihe silky fowls at peak laying (30 weeks) and late laying (50 weeks) stages, and employed an ensemble machine learning strategy integrating LASSO, random forest, and support vector machine (SVM) algorithms to identify high-confidence core biomarkers of ovarian aging. Gene expression analysis was further conducted to validate the potential molecular mechanisms. Our results showed that the metabolic profiles of ovarian tissues differed significantly between the two groups. A total of 6 core biomarkers were identified, 4 of which were long-chain acylcarnitines. Mechanistic analysis revealed that downregulation of key genes in the carnitine shuttle system led to impaired mitochondrial fatty acid β-oxidation, which in turn triggered excessive oxidative stress and compromised ovarian endocrine function. In conclusion, this study identifies long-chain acylcarnitines as potential metabolic biomarkers for ovarian aging in Taihe silky fowls. These findings provide novel insights into the metabolic basis of poultry ovarian aging and lay a theoretical foundation for the precise regulation of reproductive performance in indigenous poultry breeds.

Animals

Care Navigation for Methamphetamine Use Disorder: A Randomized Clinical Trial.

IMPORTANCE: Stimulant-involved deaths continue to increase in the US, and methamphetamine use remains a weighty public health concern. Treating methamphetamine use disorders is complicated. Contingency management has demonstrated the best effectiveness but is not widely implemented. OBJECTIVE: To examine the effectiveness of dedicated care navigation in linking patients to treatment. DESIGN, SETTING, AND PARTICIPANTS: This prospective randomized clinical trial was conducted at an integrated safety-net health system in Denver, Colorado, between April 10, 2023, and December 31, 2024. Eligible participants were 18 years or older who had a methamphetamine-related encounter in an acute care setting; those with involuntary treatment holds, substance treatment in past 90 days or actively seeking treatment, and inability to provide consent were excluded. Participants completed baseline, 30-day, and 90-day study visits. INTERVENTION: Dedicated care navigation, incorporating contingency management principles, with a focus on addressing health-related social needs. MAIN OUTCOMES AND MEASURES: Linkage to treatment within 30 and 90 days of enrollment defined as a composite measure of at least 1 of the following: electronic health record data indicating a visit at the health system's substance treatment clinic, a behavioral health encounter at an outpatient clinic, temporary residential treatment, or self-reported treatment on the 30- and/or 90-day follow-up survey. RESULTS: Of 192 participants enrolled in the Beginning Early and Assertive Treatment for Methamphetamine Use trial, 156 (81.3%) were male, and the median age was 39 (IQR, 31-47) years. Most participants were unstably housed (163 [84.9%]), not currently employed (158 [82.3%]), and without regular access to a working phone (94 [49.0%]). Of the 96 participants randomized to the intervention, 60 (62.5%) engaged in 2 or more navigation sessions, 45 (46.9%) completed the 30-day study visit, and 47 (49.0%) completed the 90-day study visit compared with 44 (46.3%) and 37 (38.5%), respectively, of the 96 randomized to the control arm. No statistically significant differences in treatment linkage were observed at 30 days (24 participants [25.0%] in both arms; risk ratio, 1.00 [95% CI, 0.61-1.63]) or 90 days post enrollment, (32 [33.3%] in intervention vs 24 [25.0%] in control arms; risk ratio, 1.33 [95% CI, 0.85-2.09]). CONCLUSIONS AND RELEVANCE: In this randomized clinical trial, integrating principles of contingency management into the intervention may have increased engagement with a dedicated care navigator but did not increase likelihood of linkage to treatment for methamphetamine use disorder. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT06033365.

Humans

Delphi study robot consenso: Strategies for the implementation of robotic surgery in general surgery in the Spanish hospital network.

INTRODUCTION: The implementation of robotic surgery in public hospitals presents multiple logistical, educational, and organizational challenges. In the absence of unified guidelines, a national consensus is required to optimize its safe and efficient adoption. This study aimed to establish a set of consensus-based and measurable recommendations for the implementation of robotic surgery programs in hospitals within the Spanish National Health System, based on the experience of centres with established robotic programs and intended to serve as guidance for hospitals that are initiating or planning their implementation. METHODS: A national Delphi study was conducted with the participation of robotic surgery experts from 26 public hospitals. The expert panel was composed exclusively of digestive surgeons with experience in robotic surgery. Three iterative rounds of expert panel evaluation were conducted between March 2024 and March 2025. The questions were grouped into five thematic blocks. Consensus was defined as an agreement level of ≥66.7%. Kendall's W coefficient was used to assess concordance. RESULTS: High levels of consensus were achieved on key aspects related to infrastructure, structured training, cost evaluation, and quality assurance mechanisms. Areas of disagreement were also identified, such as the need for a dedicated anaesthesiologist, purchase of accessory instruments during the initial phase, and official accreditation pathways. CONCLUSIONS: This study provides a guideline for developing a national robotic surgery strategy focused on patient safety, program sustainability, and standardized training of surgical teams. These recommendations can guide hospitals at different stages of robotic technology adoption. Given that the consensus was reached from an exclusively surgical perspective, the recommendations focus on patient safety, program sustainability, and standardized training of the surgical team, and should be interpreted in an adaptable manner according to each centre's context, case volume, and available resources.

Cirugía Asistida por Robot

Influence of microplastics on microalgal performance during wastewater polishing.

Microplastics (MPs) are emerging contaminants that are increasingly accumulating in aquatic ecosystems due to excessive anthropogenic activity and insufficient mitigation strategies, posing serious environmental and public health risks. Their impact on wastewater (WW) treatment processes remains poorly understood. This study evaluated the effects of five MPs commonly found in WW - polypropylene, polystyrene, polyamide, low-density polyethylene, and high-density polyethylene - on the physiology and bioremediation performance of the microalga Chlorella vulgaris in synthetic WW (SWW). Metabolic responses were assessed via esterase activity and intracellular reactive oxygen species (ROS), while nitrogen (N), phosphorus (P), and glucose removal were monitored to evaluate bioremediation efficiency. MPs inhibited esterase activity and elevated ROS levels, indicating oxidative stress. Nevertheless, C. vulgaris maintained a high bioremediation capacity (> 75 % N, > 60 % P, and > 70 % for glucose). Environmental conditions modulated microalga response to MPs exposure. Under N-limited conditions, C. vulgaris exhibited enhanced nutrient uptake and biomass production, but a 12 h/12 h light/dark photoperiod reduced N removal but stimulated glucose consumption via heterotrophic metabolism. In contrast, C-limited conditions exacerbated oxidative stress and compromised nutrient removal, resulting in residual concentrations exceeding legal limits. These findings highlight that environmental factors can either mitigate or exacerbate the physiological stress induced by MPs, ultimately affecting WW polishing. This work provides a comprehensive insight into the cellular and metabolic effects of MPs on microalgae and supports C. vulgaris as a resilient and sustainable approach for nutrient and carbon removal in MP-contaminated WW systems.

Microalgae

Pre-treatment polyfunctionality percentage (PFA) of CD8+ T cells is associated with development of immune-related adverse events (irAEs) in patients receiving immune checkpoint inhibitors (ICIs).

INTRODUCTION: Immune checkpoint inhibitors (ICIs) have improved cancer survival, but immune-related adverse events (irAEs) occur frequently and can have devastating consequences. There are no validated methods to evaluate risk of irAEs prior to initiation of ICIs. MATERIALS AND METHODS: We conducted a pilot study evaluating the ability of blood-based, single-cell secretomic analysis to characterize irAEs. A total of 10 patients with thoracic malignancies who were scheduled to receive ICIs were enrolled. Each patient had a pre-ICI blood sample drawn as well as a sample at the time of irAE development or 12 weeks after ICI initiation, whichever came first. Utilizing IsoPlexis's IsoLight system, polyfunctionality percentages (PFAs) and strength indices (PSIs) were analyzed for CD4+ and CD8+ T cells. RESULTS: Five patients developed irAEs and 5 patients did not develop irAEs. Pre- and post-ICI CD8+ T cell PFA was significantly elevated in patients who developed irAEs compared with those who did not (p = 0.017 and p = 0.014, respectively). CONCLUSIONS: In this pilot study, pre-ICI CD8+ T cell PFA was associated with development of irAEs. While this is a pilot study, this is a first step toward developing a blood-based, streamlined assay to assess risk of irAEs prior to initiation of ICIs. Validation in larger cohorts is warranted.

Humans

Elucidation of the immunotoxicity of PEDOT: PSS on RAW264.7 macrophages by oxidative stress, inflammatory response, and NF-κB pathway activation.

Poly(3,4-ethylenedioxythiophene): poly(styrenesulfonate) (PEDOT: PSS) nanoparticles, widely used conductive polymers, pose environmental and health risks due to their nanoscale dispersion. However, the characteristics of PEDOT: PSS in aquatic systems and the underlying mechanisms of its toxicity in animal and cell models remain poorly understood. This study aimed to investigate the toxicological effects of PEDOT: PSS nanoparticles on macrophages, with a focus on RAW 264.7 cells. After an acute exposure to PEDOT: PSS nanoparticles at different concentrations (5, 10, 20 μg/mL), we observed significant impairments in cell viability, proliferation, migration, adhesion, and phagocytosis, as well as morphological alterations. Concurrently, there was a marked upregulation of inflammatory markers, including reactive oxygen species (ROS), tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), and interleukin-1 beta (IL-1β), indicating the induction of oxidative stress and inflammation. Mechanistically, PEDOT: PSS nanoparticles activated the nuclear factor kappa B (NF-κB) signaling pathway, a key regulator of inflammatory responses, suggesting that they may mediate inflammatory responses and cell damage via activation of the NF-κB signaling pathway. These findings reveal the toxic mechanism of PEDOT: PSS nanoparticles in macrophages and provide new insights into their biological safety implications.

Animals

Overcoming Immunological Barriers in MSC-Derived Insulin-Producing Cells through CRISPR-Based Hypoimmunogenic Engineering and Translational Perspectives for Type 1 Diabetes.

Mesenchymal stromal cell (MSC)-derived insulin-producing cells (IPCs) represent an emerging strategy for β-cell replacement in type 1 diabetes mellitus (T1DM) owing to their differentiation potential, intrinsic immunomodulatory properties, and lower tumorigenic risk compared with pluripotent stem cell-derived platforms. However, accumulating evidence indicates that differentiation-associated immunogenicity, context-dependent immune recognition, and recurrent autoimmune responses may substantially limit long-term graft survival and therapeutic durability following transplantation. This review critically examines the immunological barriers associated with MSC-derived IPCs, including altered MHC expression, susceptibility to alloimmune and autoimmune-mediated rejection, and potential reactivation of autoreactive immune memory. We discuss the application of CRISPR-based hypoimmunogenic engineering strategies targeting antigen presentation pathways, NK-cell activation, and immune checkpoint modulation to generate more immune-evasive MSC-derived IPCs while preserving β-cell functionality. By integrating insights from T1DM immunopathogenesis, MSC biology, genome editing, and translational immunology, we propose a framework linking immune engineering with controlled differentiation, functional maturation, and long-term safety evaluation. In parallel, we comparatively position MSC-derived IPCs alongside clinically advancing iPSC-derived β-cell platforms to highlight their distinct translational niche, including potential advantages related to safety, immunomodulatory capacity, manufacturing accessibility, and scalability, while acknowledging the superior functional maturity and clinical progression currently demonstrated by iPSC-derived systems. Finally, we discuss key translational challenges, including genomic stability, immune-evasion durability, GMP-compliant manufacturing, and the need for rigorous functional and immunological benchmarking prior to clinical application of hypoimmunogenic MSC-derived IPC therapies in T1DM.

Humans

Food-derived extracellular vesicles as delivery platforms for medicine-food homology components in metabolic syndrome.

Diet-induced obesity and associated metabolic syndromes have become major global public health challenge, highlighting the urgent need for safe and effective strategies. Recently, food-derived extracellular vesicles (FDEVs) have garnered increasing attention as natural nanocarriers due to their excellent biocompatibility and specific targeted delivery capabilities. FDEVs can efficiently deliver medicine-food homology components (MFHCs) to precisely regulate lipid metabolism, inflammatory responses, and insulin sensitivity, thereby improving obesity and its metabolic abnormalities. This systematic review summarizes recent advances in the use of FDEVs as delivery vehicles for MFHCs to suppress diet-induced obesity and metabolic syndrome, with a particular focus on the underlying molecular mechanisms, including signaling pathway regulation and cellular metabolic remodeling. In addition, the clinical translational potential and industrial application prospects of FDEVs are evaluated, and key challenges related to preparation techniques, safety assessment, and large-scale production are discussed. By integrating current evidence, this review aims to provide theoretical framework and future perspectives for the development of FDEVs as a novel targeted delivery platform and treatment of metabolic diseases.

Extracellular Vesicles

Glycemic and safety outcomes of the insulin-only bionic pancreas in older adults and individuals with impaired awareness of Hypoglycemia: a post hoc analysis of a randomized pivotal trial.

AIMS: Evaluate the efficacy and safety of iLet Bionic Pancreas (BP) in older adults and individuals with impaired awareness of hypoglycemia (IAH). METHODS: This post hoc analysis used individual participant-level data from the Insulin-Only Bionic Pancreas Pivotal Trial (n = 440; NCT04200313). Eligible participants (n = 96) with type 1 diabetes, aged ≥ 60 years and/or had IAH (Clarke score ≥ 4), were randomized to BP with aspart/lispro (BP-Asp/Lis; n = 45), BP with fast-acting aspart configuration (BP-Fiasp; n = 31), or standard care (SC; n = 20) for 13 weeks. RESULTS: Compared with SC, time-in-range (70-180 mg/dL) significantly increased by 7.49 % (95 % CI: 2.61 to 12.38; ∼1.8 h/day) with BP-Asp/Lis and by 8.28 % (95 % CI: 3.15 to 13.41; ∼2.0 h/day) with BP-Fiasp, driven by reduced hyperglycemia. No significant differences were observed in hypoglycemia exposure. Severe hypoglycemia occurred in four participants (four events) on BP-Asp/Lis and one participant (two events) on SC. One diabetic ketoacidosis event occurred on BP-Fiasp due to an infusion set failure. CONCLUSIONS: In high-risk, clinically vulnerable populations, the BP system significantly improved glycemic control while maintaining safety parity with respect to hypoglycemia risk, providing a resilient therapeutic alternative for vulnerable cohorts.

Humans

The Role of Artificial Intelligence Combined With Digital Cholangioscopy for Indeterminant and Malignant Biliary Strictures: A Systematic Review and Meta-analysis.

BACKGROUND: Current endoscopic retrograde cholangiopancreatography (ERCP) and cholangioscopic-based diagnostic sampling for indeterminant biliary strictures remain suboptimal. Artificial intelligence (AI)-based algorithms by means of computer vision in machine learning have been applied to cholangioscopy in an effort to improve diagnostic yield. The aim of this study was to perform a systematic review and meta-analysis to evaluate the diagnostic performance of AI-based diagnostic performance of AI-associated cholangioscopic diagnosis of indeterminant or malignant biliary strictures. METHODS: Individualized searches were developed in accordance with PRISMA and MOOSE guidelines, and meta-analysis according to Cochrane Diagnostic Test Accuracy working group methodology. A bivariate model was used to compute pooled sensitivity and specificity, likelihood ratio, diagnostic odds ratio, and summary receiver operating characteristics curve (SROC). RESULTS: Five studies (n=675 lesions; a total of 2,685,674 cholangioscopic images) were included. All but one study analyzed a deep learning AI-based system using a convoluted neural network (CNN) with an average image processing speed of 30 to 60 frames per second. The pooled sensitivity and specificity were 95% (95% CI: 85-98) and 88% (95% CI: 76-94), with a diagnostic accuracy (SROC) of 97% (95% CI: 95-98). Sensitivity analysis of CNN studies (4 studies, 538 patients) demonstrated a pooled sensitivity, specificity, and accuracy (SROC) of 95% (95% CI: 82-99), 88% (95% CI: 72-95), and 97% (95% CI: 95-98), respectively. CONCLUSIONS: Artificial intelligence-based machine learning of cholangioscopy images appears to be a promising modality for the diagnosis of indeterminant and malignant biliary strictures.

Humans

Artificial intelligence for dental caries detection: An umbrella review.

Artificial intelligence (AI) has been proposed as a tool to improve dental caries detection across imaging modalities; however, its clinical value remains uncertain. This umbrella review aimed to synthesize and critically appraise systematic reviews evaluating AI for caries detection and diagnosis. An umbrella review was conducted following PRIOR guidance (PROSPERO CRD420261340728). Searches were performed in MEDLINE, Embase, Scopus, Web of Science, and Google Scholar up to 15 March 2026. Methodological quality was assessed using AMSTAR 2, and overlap of primary studies was quantified using the corrected covered area (CCA). Seventeen systematic reviews were included, of which five reported diagnostic test accuracy meta-analyses using bivariate or HSROC models. Across these meta-analyses, pooled sensitivity ranged from 0.76 to 0.94 and specificity from 0.85 to 0.91. Most systems were based on deep learning models applied to bitewing radiographs and intraoral photographs. However, substantial heterogeneity was observed in imaging modalities, lesion thresholds, analytical tasks, and evaluation metrics. In addition, a high degree of overlap across reviews and recurrent methodological limitations, including reliance on retrospective datasets, limited external validation, and inconsistent reporting, substantially weaken the reliability of the evidence. Although AI models demonstrate high diagnostic performance under experimental conditions, current evidence does not support their use as stand-alone diagnostic tools. Their clinical applicability remains limited, and implementation should be restricted to decision-support contexts until robust prospective validation demonstrates meaningful impact on clinical decision-making and patient outcomes.

Dental Caries