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Integrated genomic and biochemical diagnosis of a novel homozygous start-loss variant in AKR1D1 associated with neonatal cholestasis.

INTRODUCTION: Congenital bile acid synthesis defects are rare autosomal recessive disorders that typically present in early infancy with cholestasis, progressive liver dysfunction, and, in severe cases, acute liver failure. These conditions may mimic other metabolic diseases detected in newborn screening, complicating early diagnosis. The AKR1D1 gene encodes Δ4-3-oxosteroid 5β-reductase, a key enzyme in primary bile acid synthesis, and pathogenic variants cause bile acid synthesis defect type 2 (OMIM #235555). CASE DESCRIPTION: We report a 3-month-old male infant with severe neonatal cholestasis and a history of elevated tyrosine levels in newborn screening. Pregnancy was high risk and unmonitored, with birth outside a hospital. Parental consanguinity was first-degree. Early metabolic evaluation showed transient normalization of tyrosine levels, but subsequent analyses revealed recurrent hyper-tyrosinemia. Urinary organic acids showed increased 4-hydroxyphenyl metabolites, with absent succinylacetone, excluding tyrosinemia type I. Progressive cholestasis developed, accompanied by coagulopathy, hyperbilirubinemia, hyperammonemia, and markedly elevated alpha-fetoprotein. Imaging revealed no structural liver abnormalities. Clinical exome sequencing identified a novel homozygous start-loss variant in AKR1D1, likely abolishing functional enzyme production. Metabolic studies confirmed increased urinary excretion of 3-oxocholenoic acids consistent with abnormal bile acid synthesis and supporting a diagnosis of bile acid synthesis defect type 2. Oral cholic acid therapy led to stabilization and improvement in clinical and biochemical parameters. DISCUSSION/CONCLUSION: This case illustrates the diagnostic complexity of neonatal cholestasis, particularly when initial metabolic findings suggest alternative etiologies. It highlights the importance of newborn screening as a tool for broader diagnostic suspicion and the critical role of early molecular diagnosis and multidisciplinary care. Timely recognition and targeted therapy can improve outcomes, prevent liver transplantation, and enable accurate genetic counseling, especially in consanguineous families.

Humans

Long-term outcomes of surgical correction of ventral penile curvature in children: Patient-reported measures, surgical results, and decisional regret.

INTRODUCTION: There is a dearth of data on long-term outcomes, including patient-reported outcomes (PROMs), decisional regret, and complication rates for surgical correction of isolated ventral penile curvature in childhood. PATIENTS AND METHODS: Twenty-six children treated for ventral curvature between 1993 and 2008 were identified; 24 met inclusion criteria (isolated ventral curvature without hypospadias or need for urethral reconstruction). Surgical correction consisted of degloving alone or degloving with Nesbit-like dorsal plication when residual curvature >20° persisted after degloving. PROMs were collected via pre-mailed validated questionnaires after puberty: Danish Prostatic Symptom Score (DAN-PSS) for LUTS, Erection Hardness Score (EHS) for erectile function, Penile Perception Score (PPS) for cosmetic perception, and items assessing decisional regret and perceived appropriateness of surgical timing. RESULTS: Curvature was corrected intraoperatively in all 24 patients. Twelve underwent degloving alone and 12 required additional dorsal plication. During long-term follow-up (median 14.2 years), one patient (4%) underwent re-operation for residual curvature, and three (13%) underwent cosmetic revisions; two (8%) underwent cystoscopy for flow concerns. 71% returned PROMs at a median age of 16.2 years. LUTS were uncommon, with low bother scores. Erectile function was favorable: 87% (13/15) reported EHS 4 and 93% (14/15) reported ejaculation. Cosmetic outcomes were favorable, with PPS dissatisfaction rates comparable to controls. Two patients reported dissatisfaction with overall appearance, and one with residual subjective curvature. No patient expressed decisional regret, and 88% felt timing of surgery was appropriate. CONCLUSION: Early surgical correction of isolated ventral penile curvature using degloving with or without dorsal plication provided durable anatomical correction and favorable long-term functional and cosmetic outcomes. These findings support early intervention as an effective approach with sustained patient-perceived benefits.

Humans

Diagnostic value of blood p-tau subtypes in Alzheimer's disease progression and pathology: systematic review and meta-analysis.

BACKGROUND: Alzheimer's disease (AD) is the most common neurodegenerative disease and the most likely to lead to dementia. With the availability of the latest therapies, the need for Alzheimer's disease diagnosis is now gradually increasing. Whereas blood phosphorylated-tau (p-tau) has demonstrated excellent performance in the prediction and diagnosis of disease progression and A&#x3b2; positivity in AD, there are differences between different p-tau subtypes. Therefore, a pooled analysis of different blood p-tau subtypes is of more important clinical value. METHOD: Relevant literature was screened by complete search in four databases, Pubmed, Embase, Cochrane Library and Scopus. Relevant data and AUC and their confidence intervals of the included literature were extracted and analyzed by classification according to p-tau subtypes. Quality assessment was performed using the QUADAS-2 tool. RESULT: Our results reveal that p-tau217 performs better in the diagnostic performance in most stages of AD, which is consistent with the guidelines. However, our results concluded that p-tau217 has poorer diagnostic performance in the stages of cognitive unimpaired or less cognitively impaired, especially in the A&#x3b2; positivity diagnosis of SCD and CU. Head-to-head meta-analyses formally confirmed that p-tau217 significantly outperforms p-tau181 across AD dementia, A&#x3b2; positivity, tau positivity, and biological staging (all P&#x2009;<&#x2009;0.05), whereas no significant difference was observed between p-tau231 and p-tau181. CONCLUSION: By integrating single-arm pooled AUC estimates with formal head-to-head statistical comparisons, our study provides evidence-based support for plasma p-tau217 as the subtype with the most robust diagnostic performance across AD pathology and biological staging. Head-to-head analyses formally confirmed that p-tau217 significantly outperforms p-tau181 in A&#x3b2; positivity, Tau positivity, and biological staging.

Humans

Generation of spCAS9 expressing human mesenchymal stem cell line to study gene function during osteoblast differentiation.

Human bone marrow-derived stromal cells (hMSCs) are a great resource for studying how genes influence cell fate and differentiation into various cell types like osteoblasts, adipocytes, and chondrocytes, among other cell types. However, genetic manipulation of primary hMSCs has been challenging due to their short lifespan and cellular senescence after limited passaging. Their low and unstable transfection efficiency also complicates gene delivery or inactivation, hindering long-term functional studies. The limited lifespan has been effectively solved by immortalizing hMSCs with telomerase reverse transcriptase (hMSCs-TERT). The use of these cells is ideal for functional studies of osteoblast and adipocyte differentiation through genetic manipulation, providing a stable and reliable model. Here, we have engineered a stable CAS9 expressing hMSC-TERT cell line (hMSC-TERTCAS9) via lentiviral transduction. The constitutive expression of spCas9 enables efficient and reproducible gene editing. We demonstrate the potential of these hMSC-TERTCAS9 cells for generating gene disruptions using plasmid delivery of guide RNAs as a fast and efficient strategy for targeted genome editing. The edited cells can be sorted and expanded as single cells to obtain homogenous clonal cell lines with mono- as well as bi-allelic gene deletions, a crucial step for producing reliable experimental results. We further validate this cell line as a powerful tool for studying gene function during hMSC proliferation and differentiation, providing 3 distinct examples of its utility. Through the generation of indels, single-cell sorting, and clonal selection, we have efficiently inactivated the vitamin D receptor and created both larger (256 nucleotides) gene disruptions in Forkhead box protein O1 and precise removals of a small genomic sequence (73 nucleotides) coding for microRNA MIR675. This novel hMSC-TERTCAS9 cell line represents a significant advancement, offering a stable, efficient, and versatile platform for advanced genetic studies, high-throughput screening, and the creation of reliable cellular disease models.

CRISPR-Cas9

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&#xd7;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 (I&#xb2;=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

Enhanced fracture detection on radiographs with AI assistance for clinicians: a systematic review and meta-analysis.

BACKGROUND: Emergency radiographic interpretation for fractures is prone to missed or misdiagnoses. Artificial intelligence (AI) is expected to become a powerful tool to assist clinicians in fracture detection. PURPOSE: A systematic review and meta-analysis was performed to assess whether AI improves clinicians' ability to detect fractures on radiographs. MATERIALS AND METHODS: A literature search was conducted in PubMed, Web of Science, and Cochrane Library for studies published between January 1, 2010, and October 10, 2025. A meta-analysis of diagnostic accuracy studies was performed using a Summary Receiver Operating Characteristic (SROC) curve. The quality of included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool. Subgroup analysis and meta-regression were conducted to explore potential sources of heterogeneity. RESULTS: A total of 26 studies were included . The pooled sensitivity of clinicians increased from 77% (95% CI: 72-81) to 87% (95% CI: 83-90) with AI assistance, while the pooled specificity improved from 88% (95% CI: 85-90) to 92% (95% CI: 89-94). The corresponding AUC values were 0.90 (95% CI: 0.87-0.92) before and 0.95 (95% CI: 0.93-0.97) after AI assistance. Eight studies were rated as high risk of bias. Subgroup analysis and meta-regression identified potential sources of heterogeneity, including fracture location, AI model type, high risk of bias, and reference standards. CONCLUSION: AI assistance significantly improves clinicians' diagnostic performance in detecting fractures on radiographs for extremity and trunk fractures.

Humans

Quantitative susceptibility mapping in neurodegenerative diseases: An umbrella review of iron-related biomarkers and mechanisms.

Pathological iron accumulation is a common pathophysiological hallmark across multiple neurodegenerative diseases (NDDs), motivating the need for accurate, non-invasive quantification methods. Quantitative susceptibility mapping (QSM) is an advanced magnetic resonance imaging (MRI) technique that enables in vivo measurement of tissue magnetic susceptibility (&#x3c7;), providing a sensitive proxy for iron content. This umbrella review systematically evaluates the diagnostic accuracy, clinical correlations, and distinct iron distribution patterns of QSM in major NDDs, such as Parkinson's disease (PD), Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), and atypical Parkinsonism. We included 15 (13/15 were rated Low or Critically Low on AMSTAR 2) systematic reviews and meta-analyses (through July 15, 2026); however, the findings should be interpreted cautiously because of heterogeneity and the low methodological quality. A Corrected Covered Area (CCA) analysis demonstrated only slight overlap of primary studies across the included reviews (CCA&#xa0;=&#xa0;5.42%). Collectively, the evidence indicates that QSM provides comparable or higher diagnostic sensitivity and reliability than conventional R2* and SWI techniques, particularly for deep gray matter structures. The findings support significant iron overload in the substantia nigra, particularly in the pars compacta, as a robust biomarker for PD that correlates with motor severity and disease duration. Furthermore, regional iron profiling in the basal ganglia is critical for differential diagnosis; specifically, elevated &#x3c7; in the putamen and globus pallidus effectively distinguishes multiple system atrophy and progressive supranuclear palsy from idiopathic PD. Distinctively, AD and ALS exhibit specific &#x3c7; alterations in the thalamus, motor cortex, and hippocampus, reflecting divergent iron-related pathophysiological mechanisms, which correlate with cognitive impairment and upper motor neuron signs. Overall, QSM shows diagnostic promise and offers mechanistic insights into iron-related neurodegenerative processes.

Humans

Artificial Intelligence for Diagnosing Meibomian Gland Dysfunction: A Systematic Review and Meta-Analysis of Diagnostic Test Accuracy Studies.

PURPOSE: To identify, appraise, and synthesize the performance of artificial intelligence-based meibography reading as compared with human graders in diagnosing meibomian gland dysfunction. METHODS: We followed Cochrane methodology and reporting guidelines for diagnostic test accuracy reviews. To assess potential risk of bias and applicability, we used a modified Quality Assessment of Diagnostic Accuracy Studies-2 checklist. We applied bivariate logistic models to estimate summary sensitivity and specificity when appropriate and used the GRADE framework to rate the certainty of the evidence. RESULTS: We identified 14 eligible studies involving 5511 predominantly middle-aged participants (average age: 27-55 years) who were primarily female (&#x2265;54.5%). A total of 18,926 meibography images were obtained through noncontact infrared (11 studies) or in vivo confocal microscopy (three studies). Two studies reported external validation of deep learning models, 12 reported internally validated models, and one reported both. All but one study had high risk of bias in at least one domain; 12 studies raised high or intermediate concern about applicability. Based on three external evaluations, the summary sensitivity and specificity for diagnosing meibomian gland dysfunction from normal glands were 97.5% (95% confidence interval: 77.5%-99.8%) and 85.5% (95% confidence interval: 47.3%-97.5%). Sources of heterogeneity in internally validated models included study population, case mix, and others. The overall evidence was very low to low certainty because of imprecision, high risk of bias, and concerns about applicability. CONCLUSIONS: Artificial intelligence-based meibography grading appears less accurate than human graders. Future studies should adopt rigorous designs, including a more diverse participant pool (or image set), and external validation.

Humans

A Pilot Study: Developing a Lactating Dairy Goat Model to Study Staphylococcus aureus Mastitis in Women.

INTRODUCTION: Lactational mastitis is common in lactating women, with Staphylococcus aureus as the most commonly isolated agent associated with infectious lactational mastitis. Currently, there are no evidence-based guidelines for antimicrobial treatment due to barriers in obtaining pharmacokinetic data from lactating women. To overcome this barrier, a suitable large animal model is needed. Goats are an ideal translational model for human mastitis due to their anatomical and physiological similarity to humans. The objective of this pilot study was to assess if goats would develop clinical mastitis following intramammary inoculation with a clinical human isolate of S. aureus with the goal of establishing an alternative in&#xa0;vivo model for future research. The hypothesis was that the infected mammary gland half would show similar clinical signs to women with mastitis and demonstrate a similar local immune response when compared to the control mammary gland half. METHODS: One half of the mammary gland of two healthy lactating does was inoculated with a clinical human isolate of S. aureus. The other half of the mammary gland was sham inoculated with sterile buffered saline. Physical examinations, mammary gland assessments, and sterile milk samples were collected every 12 hours post inoculation. At 96 hours post inoculation, the goats were euthanized, and the mammary glands were examined for pathological changes. RESULTS: Goats did not develop systemic signs of disease following inoculation. Focal infected mammary gland changes included warmth, swelling, redness, discoloration, and reduced milk production; the other mammary gland half remained normal throughout the study period. S. aureus was enumerated from only the infected mammary gland half. The microscopic findings of the infected half showed neutrophilic inflammation and cell necrosis consistent with acute mastitis. DISCUSSION: This pilot study demonstrated lactating does can develop clinical signs like those observed in women. Goats have the potential to be a promising animal model to study infectious lactational mastitis.

Animals

Performance of Automated Hematology Analyzer Criteria in Detecting Peripheral Blood Smear Abnormalities: A Systematic Literature Review.

OBJECTIVES: Criteria for visual examination of stained peripheral blood smear (PBS) differ among institutions in the United States and internationally. In an effort to standardize review criteria, the International Consensus Group for Hematology Review (ICGHR) proposed in 2005 a consensus list of rules for CBC findings that should trigger a review of automated cell counter results and potentially lead to further testing or blood smear review. The primary aim of this paper is to report on the published literature in the past 20&#x2009;years regarding PBS review criteria and their ability to identify relevant peripheral blood abnormalities. METHODS: We performed a systematic review of the published literature from 2005 to 2025 to investigate and summarize PBS review criteria and performance in the context of automated hematology analyzers in clinical laboratories. RESULTS: Of 5351 citations, 68 studies met our search criteria. These studies included 22 countries and all major hematology analyzer manufacturers. Marked variability was observed in study populations, analyzer flagging criteria, details of PBS visual review, definitions of a "positive" smear, and approaches to statistical data analysis. Across studies, the blast flag sensitivity ranged from 18% to 100% while the blast flag specificity ranged from 17% to 100%. Wide ranges in sensitivity/specificity were also seen for atypical and/or abnormal lymphocyte flags across studies. For studies analyzing the same patient population, less striking variation was seen across instruments. CONCLUSIONS: This systematic review provides a 20-year overview of the literature, highlighting significant variability in PBS review criteria, dependence on study design and hematology analyzer, and the importance of developing harmonized evidence-based guidelines.

Humans

Evaluating the persistence of semen under controlled environmental conditions.

When semen is deposited at a crime scene, it may be exposed to harmful environmental conditions. It is important to understand to what extent the different components of semen, specifically acid phosphatase (AP), prostate specific antigens (PSA), sperm and DNA, may become less detectable after exposure to high temperatures and varying levels of humidity. In this study, semen (50&#xa0;&#x3bc;L) was deposited onto squares of black cotton and exposed to 45&#xa0;&#xb0;C and a relative humidity (RH) of 10 or 80% for 0, 7, 14, 21 or 28&#xa0;days (n&#xa0;=&#xa0;5 per day, per climate condition). Source testing included AP test reagent, ABAcard&#xae; p30 immunoassay kits, and hematoxylin and eosin staining. DNA was extracted using the DNA IQ&#x2122; System (Promega, Australia) and quantified using Quantfiler Trio&#x2122; (Thermo Fisher Scientific, Australia). Over the 28-day period under both RH conditions, the time taken for a positive AP test to develop increased significantly (p&#xa0;<&#xa0;0.01) and the number of sperm observed decreased significantly (p&#xa0;<&#xa0;0.01). All ABAcard&#xae; p30 tests were positive regardless of exposure time or conditions. No impact on the quantity of DNA recovered was observed when semen was exposed to 45&#xa0;&#xb0;C and 10% RH, with a higher median quantity of DNA recovered at day 28 compared to day 0. In contrast, when the RH was raised to 80%, the median quantity of DNA recovered was substantially less at day 28 (81.5&#xa0;ng, IQR: 87.5&#xa0;ng) compared to day 0 (181.5&#xa0;ng, IQR: 1172.4&#xa0;ng). This study highlights the impact that temperature and RH may have on the persistence of AP, PSA, sperm and DNA over time.

Humans

Fundamentals of pacemakers ECG interpretation - part 2.

BACKGROUND: Modern pacemakers incorporate arrhythmia-response algorithms, ventricular pacing minimization protocols, and safety mechanisms that generate ECG patterns indistinguishable from pathological AV block, sensing malfunction, or device-mediated tachycardia. Failure to recognize these algorithm-driven signatures leads to unnecessary interventions, misdiagnosis, and inappropriate device reprogramming. This manuscript is the second in a two-part series on pacemaker ECG interpretation. METHODS: We conducted a narrative review of peer-reviewed literature and device-specific documentation on algorithm-driven ECG behavior, synthesizing evidence across arrhythmia recognition, upper rate physiology, ventricular pacing minimization, mode switching, safety mechanisms, and hysteresis algorithms. RESULTS: Pacemaker-mediated tachycardia produces regular paced wide-complex tachycardia locked at the upper tracking rate, initiated by any event with retrograde VA conduction. Ventricular tachycardia is identified by QRS morphology diverging from the known paced pattern, absent pacing spikes, and AV dissociation. Upper rate Wenckebach behavior mimics Mobitz type I AV block; 2:1 upper rate response mimics second-degree AV block. Ventricular pacing minimization algorithms produce isolated nonconducted P waves and prolonged AV intervals that simulate pathological conduction disease. Mode switching causes abrupt rate drops misidentified as output failure. Ventricular safety pacing generates a conspicuously short, fixed AV interval. Three discrete pacing artifacts reflect AV-sequential cardiac resynchronization therapy (CRT), ventricular safety pacing in CRT, or His-bundle pacing with backup RV output. Rate and AV hysteresis produce pauses and wandering AV intervals mimicking oversensing or Wenckebach periodicity. CONCLUSIONS: Recognizing algorithm-driven ECG patterns requires knowledge of device timing intervals and refractory periods, which lets clinicians distinguish programmed behavior from true malfunction or cardiac arrhythmia.

Humans

Physical reconfiguration of limb electrodes for Precordial Bipolar Lead acquisition: Morphological validation against digital subtraction.

BACKGROUND: The V2&#xa0;-&#xa0;V1 Precordial Bipolar Lead (PBL) selectively evaluates the right-to-left retrosternal axis and has shown diagnostic value beyond the standard 12&#x2011;lead electrocardiogram. However, its use has been limited by the need for raw electrocardiographic data and post-processing software. This study evaluated whether a simple physical reconfiguration of limb electrodes could reproduce the digitally derived V2&#xa0;-&#xa0;V1 morphology with sufficient accuracy for clinical application. METHODS: Thirty-seven subjects underwent two sequential 10-s 12&#x2011;lead recordings using a Cardiovit FT-1 electrocardiograph sampled at 1000&#xa0;Hz. In the standard recording, the digital PBL was calculated as V2&#xa0;-&#xa0;V1. In the second recording, the right-arm and left-arm electrodes were repositioned to the V1 and V2 sites so that Lead I directly recorded the retrosternal dipole. Signals were filtered, synchronized, and analyzed using median beats. Morphological agreement was assessed with Pearson correlation on Z-normalized signals, while absolute agreement was evaluated using Lin's concordance correlation coefficient (CCC), intraclass correlation coefficient (ICC (Lewis, 1931; Nehb, 1938 [1,2])), root mean square error (RMSE), and Bland-Altman analysis. RESULTS: Mean Pearson correlation between digital and physical PBL was 0.955 (SD 0.043), with segment-specific correlations of 0.953 (SD 0.054) for QRS and 0.967 (SD 0.052) for ST-T. Lin's CCC and ICC(2,1) were both 0.871 (SD 0.110), and RMSE was 0.091 (SD 0.049) mV. Bland-Altman analysis showed minimal bias (-0.008&#xa0;mV). CONCLUSIONS: Physical acquisition of the V2&#xa0;-&#xa0;V1 PBL achieved high agreement with the digitally derived signal, supporting a simplified analog method for broader clinical implementation.

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

Enhancing Hemoglobin Bart's hydrops fetalis syndrome prevention: a single-tube multiplex real-time PCR assay for the comprehensive detection of four significant &#x3b1;0-thalassemia deletions (--SEA, --THAI, --CR, and --SA) found in Thailand.

BACKGROUND: Hemoglobin (Hb) Bart's hydrops fetalis is a major public health concern in Southeast Asia, particularly in Thailand. Current screening strategies target the two most common &#x3b1;0 -thalassemia deletions (--SEA and --THAI). METHOD: In this study, we developed a single-tube multiplex real-time PCR assay for the simultaneous detection of four clinically relevant &#x3b1;0-thalassemia deletions (--SEA, --THAI, --CR, and --SA). The assay was validated using 538 clinical samples with diverse thalassemia genotypes and compared against conventional gap-PCR as the reference method. Analytical performance, including sensitivity, specificity, and limit of detection (LOD), was evaluated. In addition, clinical utility was assessed in 22 prenatal diagnosis cases at risk of Hb Bart's hydrops fetalis. RESULTS: The study cohort demonstrated substantial genetic heterogeneity, comprising 43 distinct genotypes. The developed assay achieved 100% sensitivity and specificity for all targeted deletions, with complete concordance with gap-PCR results. No cross-reactivity was observed with &#x3b1;+-thalassemia. The assay demonstrated a high analytical sensitivity with a LOD of 9.76&#x2009;&#xd7;&#x2009;10-3&#x2009;ng per reaction. Whereas in prenatal diagnosis, all 22 fetal genotypes were accurately identified, including five cases of homozygous --SEA and one rare compound heterozygous --SEA/--CR fetus. CONCLUSIONS: This study presents a rapid, accurate, and cost-effective multiplex real-time PCR assay capable of detecting both common and rare &#x3b1;0-thalassemia deletions in a single reaction. The assay demonstrates strong potential for implementation in routine clinical laboratories and large-scale population screening, contributing to improved prevention and control of severe thalassemia syndromes in high-prevalence regions.

Humans

A multi-scale fusion model based on multi-phase contrast-enhanced CT for predicting pancreatic cancer resectability.

Purpose.Develop a multi-scale fusion model (MSFM) based on multi-phase contrast-enhanced computed tomography (CECT) to predict pancreatic cancer (PC) resectability, thereby assisting expert decision-making.Methods.This retrospective study enrolled 280 patients with PC from four institutions, which were randomly divided into a training cohort (202 patients) and an independent test cohort (78 patients). Three-phase CECT images (arterial, venous, and delayed phases) were used for modeling. The MSFM comprises two sub-networks: (1) a multi-phase fusion network for extracting cross-phase shared fusion features, (2) a phase-specific branch network for capturing phase-specific features; and a post-fusion strategy to generate the final predictive score by integrating the shared fusion features and three groups of phase-specific features. Additionally, a human-machine fusion deep learning model (HMfDL) was constructed by fusing the predictive score of the MSFM with expert assessments.Results.In the independent test, the MSFM achieved an AUC (area under the receiver operating characteristic curve) of 0.8385 (95% CI: 0.7521-0.9249), accuracy of 84.62%, sensitivity of 72.00%, and specificity of 90.57%. This performance outperformed single-phase models (AUC range: 0.7638-0.7781), two-phase models (AUC range: 0.7826-0.7864), and ten states-of-the-art classifiers (AUC range: 0.7404-0.7796). The HMfDL further improved the performance, reaching an AUC of 0.8626 (95% CI: 0.7853-0.9400), accuracy of 91.03%, sensitivity of 80.00%, and specificity of 96.23%. Notably, the HMfDL corrected 58.82% of misdiagnosis made by experts.Conclusions. The MSFM effectively fuses multi-phase CECT to enable highly accurate predictions of PC resectability, and provides valuable support for expert decision-making through HMfDL.

Humans

Efficacy of current approaches to non-invasive diagnosis of skin cancer and the potential impact of artificial intelligence: A systematic review and meta-analysis.

BACKGROUND: Skin cancer is one of the most prevalent malignancies worldwide, particularly within Caucasian populations. This systematic review and meta-analysis aimed to quantitatively review the current literature on non-invasive diagnosis of skin cancer and evaluate the current evidence to support the use of tools in addition to, or in replacement of clinician face-to-face assessment. METHODS: A literature search was conducted for publications in PubMed, Medline and Embase databases. Articles describing accuracy, sensitivity, specificity and outcomes of their mode of assessment were included. A total of 208 articles met the inclusion criteria. RESULTS AND CONCLUSION: This systematic review and meta-analysis showed that the diagnostic performance of artificial intelligence (AI) in the interpretation of dermatoscopic images was high for melanoma diagnosis, basal cell carcinoma or malignancy, in comparison to dermatoscopic assessment alone by clinicians and experts. Although AI interpretation of images demonstrated higher sensitivity for melanoma diagnosis in comparison to clinical assessment combined with dermatoscopic assessment, it is unclear if this is also the case for basal cell carcinoma and squamous cell carcinoma diagnosis. Reflectance confocal microscopy, a non-invasive high resolution imaging technique, is known to have a high sensitivity for diagnosing cutaneous malignancy, and this may have applications within secondary care. Therefore, AI could help reduce resource burden and aid in clinical assessment, particularly within primary care settings.

Humans

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