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Assessment of atypical glandular cell interpretation in Pap tests using the Hologic Genius Digital Diagnostics System.

Atypical glandular cells (AGC) are a diagnostic challenge. The aim of this study was to evaluate the efficacy and diagnostic performance of AGC detection on the Hologic Genius Digital Diagnostics System (HGDDS). A retrospective analysis of 451 ThinPrep Pap cases was conducted, including 207 cases of AGC, 27 cases of high-grade squamous intraepithelial lesion (HSIL), 25 cases of low-grade squamous intraepithelial lesion (LSIL), and 192 benign cases. All AGC cases had follow-up histologic diagnoses, with 66 cases subsequently diagnosed as adenocarcinoma. The slides were randomized, scanned, and analyzed by the HGDDS. Patient age and HPV test results were provided to reviewers, an experienced cytologist, who screened the cases, followed by two cytopathologists who independently examined the cases on the HGDDS. Diagnostic concordance between the two cytopathologists indicated strong agreement (κ = 0.829). Sensitivity of AGC on Papanicolaou (Pap) tests for adenocarcinoma detection on HGDDS was 98.5% and 95.5%, respectively, comparable to the original ThinPrep interpretation (OTPI). Specificity for adenocarcinoma detection was significantly higher (84.6% and 85.6%) with the HGDDS than 27.7% with OTPI. Overall, the diagnostic performance for AGC/HSIL interpretation to detect CIN2/3/adenocarcinoma appeared to have improved with HGDDS compared with OTPI, particularly for specificity and positive predictive value (PPV). This is the first study evaluating AGC diagnosis using the HGDDS. The findings demonstrate that the sensitivity of adenocarcinoma detection as AGC on HGDDS is comparable to the ThinPrep Imaging System, but the specificity and PPV are improved. This suggests the potential of artificial intelligence to augment the performance of cervical cancer screening.

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

Diagnostic accuracy of nuclear STAT6 immunohistochemistry for solitary fibrous tumour: a systematic review and meta-analysis.

Nuclear STAT6 immunohistochemistry is the diagnostic surrogate for the NAB2::STAT6 fusion of solitary fibrous tumour (SFT); its sensitivity is established, but specificity varies for unexamined reasons. This review quantified pooled accuracy and tested whether antibody clone and nuclear threshold govern specificity. PubMed, Scopus and Web of Science were searched to 29 June 2026 for studies reporting nuclear STAT6 immunohistochemistry against a reference standard (NAB2::STAT6 confirmation and/or expert consensus) in SFT and comparators, with extractable two-by-two data. Two reviewers screened, extracted data and applied QUADAS-2. A bivariate generalised linear mixed model gave summary sensitivity and specificity, and exploratory subgroup analysis and meta-regression tested antibody clone, anatomical site and reference-standard type. Twenty-three studies (1216 SFT and 4715 comparators) were included. Summary sensitivity was 98.7% (95% confidence interval 96.7-99.5) and specificity 99.1% (97.8-99.6); the diagnostic odds ratio was approximately 8656. The monoclonal YE361 subgroup (8 studies) reached specificity 99.9% (99.3-100), with one false positive among 861 comparators, versus 98.1% (96.0-99.1) for polyclonal and other antibodies. False positives concentrated in dedifferentiated liposarcoma and prostatic stromal tumours. Estimates were stable after removing studies at higher risk of bias (98.9%/99.1%) and on leave-one-out analysis; the Deeks test was non-significant (p = 0.08). Nuclear STAT6 immunohistochemistry is therefore highly sensitive and specific for SFT, and the residual specificity loss is structured and largely avoidable: the monoclonal YE361 read at a strict nuclear threshold is preferred, with MDM2 and CDK4 applied to exclude dedifferentiated liposarcoma when nuclear STAT6 is unexpectedly positive.

Humans

Molecular diagnostic yield and barriers in inherited retinal diseases: a retrospective cohort study.

OBJECTIVE: To evaluate the diagnostic yield of panel-based genetic testing for inherited retinal diseases (IRDs) and identify barriers to molecular resolution. DESIGN: Retrospective cohort. PARTICIPANTS: A total of 404 patients with clinically confirmed IRDs who were evaluated at the Adult Inherited Retinal Dystrophy Service, Ontario, Canada (October 2021-September 2024). METHODS: Patients underwent targeted massive parallel sequencing panel testing. Diagnostic yield was calculated, and unresolved cases were reviewed. Associations between yield, phenotype, ethnicity, and sex were assessed using χ² analysis. RESULTS: Of 685 referrals, 570 had confirmed IRDs. After we excluded 140 pending results and 26 patients who declined testing, 404 patients were analyzed. At referral, 94 patients (23.2%) had a previous molecular diagnosis, and 138 (34.0%) were diagnosed through clinic-initiated testing, giving an overall yield of 57.4%. Yield varied significantly by phenotype (χ², P = 1.4 × 10⁻⁶), from 94.4% in vitelliform macular dystrophies to 25.0% in vitreoretinopathies, with no sex association (P = 1.0). Disease-causing variants were identified in 83 IRD-associated genes, most frequently ABCA4, USH2A, and BEST1. Of 172 unresolved cases, 62 (36.0%) had negative panels, and 110 (63.9%) were inconclusive, including 30 with unphased pathogenic variants in recessive genes and 10 with high-suspicion variants of uncertain significance. Key barriers included limited family availability for phasing, restricted access to functional assays, and lack of public coverage for whole-exome or whole-genome sequencing. CONCLUSIONS: Massive parallel sequencing-based panel testing achieved a 57% diagnostic yield in this IRD population. Success was strongly phenotype-dependent with substantial heterogeneity. Whole-exome sequencing, whole-genome sequencing, family segregation, and functional genomics could improve diagnostic outcomes and management.

Humans

Diagnostic utility of high-risk HPV polymerase chain reaction-based testing in head and neck FNA specimens with indeterminate cytomorphology.

BACKGROUND: Fine-needle aspiration (FNA) is critical in the initial diagnosis of many high-risk human papillomavirus (HR-HPV)-associated, metastatic oropharyngeal squamous cell carcinomas. Updated guidelines recommend HR-HPV-specific polymerase chain reaction (PCR) analysis over p16 immunohistochemistry on FNA specimens because p16 performs poorly on cytology material. PCR-based assays on liquid cytology material have demonstrated excellent analytic performance; however, the diagnostic utility of a positive HR-HPV PCR result in specimens with indeterminate cytomorphology remains uncharacterized. METHODS: The authors retrospectively identified 279 head and neck FNA specimens that had paired HR-HPV PCR testing on residual liquid cytology material over a 5-year period. The positive predictive value for histopathologically confirmed squamous cell carcinoma on surgical follow-up was calculated within each cytologic interpretive category. RESULTS: The HR-HPV PCR results were positive in 50.2% of specimens, negative in 40.9%, and indeterminate in 9.0%. The HR-HPV positivity rate ranged from 0% in specimens categorized as negative for malignancy to 57.3% in cytologically positive specimens, with 19.0%, 41.2%, and 50.0% positivity in the atypical, suspicious, and nondiagnostic categories, respectively. Among cytologically indeterminate specimens with positive HR-HPV PCR results (n = 14), the positive predictive value was 100% (95% confidence interval, 78.5%-100.0%). Blinded slide review additionally identified 15 cytologically positive specimens in which the definitive malignant interpretation depended substantially on HR-HPV positivity; all 15 were confirmed as squamous cell carcinoma. CONCLUSIONS: A positive HR-HPV PCR result on liquid cytology material carries a positive predictive value of 100% for malignancy in cytologically indeterminate head and neck FNA specimens. These findings support integrating HR-HPV PCR analysis into routine cytologic interpretation with the potential to upgrade some indeterminate specimens to malignant when HR-HPV is detected, expediting definitive treatment and sparing patients additional, invasive sampling.

Humans

Diagnostic and Predictive Value of Circulating and Exosomal microRNAs in Ferroptosis-Associated Neurological Conditions: A Systematic Review and Meta-analysis.

Circulating microRNAs (miRNAs) have emerged as potential non-invasive markers for intracranial pathology, yet their diagnostic accuracy and relationship with ferroptosis-mediated neuronal damage remain poorly defined. The primary objective of this study was to evaluate the diagnostic and predictive potential of circulating and exosomal miRNAs across ferroptosis-associated neurological conditions and to explore their associations with ferroptosis-related pathways. Following PRISMA-DTA guidelines, a systematic literature search was conducted across PubMed, Scopus, Cochrane, and ScienceDirect, identifying 205 records. After screening for human clinical cohort validation, 7 studies were included in the qualitative synthesis and 5 in the quantitative meta-analysis. Pooled Area-under-the-Curve (AUC) was calculated using a random-effects inverse-variance model, while prognostic correlation coefficients (r) were synthesized using Fisher's Z-transformation. Methodological quality was assessed via QUADAS-2. Analysis of 7 clinical cohorts provided heterogeneous evidence on the diagnostic and prognostic potential of miRNAs. Random-effects pooling of the two eligible diagnostic AUC estimates yielded an exploratory pooled AUC of 0.87 (95% CI, 0.79-0.94; I2 .90%). Prognostic synthesis of Group 2 identified an exploratory association between miRNA levels and clinical severity scales (exploratory pooled correlation coefficient of 0.67 (95% CI: 0.56-0.76; I2 .714.4%). Selected miRNAs were mapped to ferroptosis-associated regulators, including SLC7A11, ABCB8, and SLC40A1. Exosomal miRNAs hold potential to indicate disease-associated molecular information, although comparative clinical evidence remains yet to be explored. Circulating and exosomal miRNAs show promising diagnostic and prognostic potential across selected neurological conditions. These findings highlight a potential mechanistic association between miRNA expression and ferroptosis-mediated neuronal injury.

Humans

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

The role of artificial intelligence in the diagnosis and prognosis of traumatic brain injury based on brain CT scans: a systematic review.

Traumatic brain injury (TBI) is a leading cause of emergency department visits and a major contributor to injury-related mortality and long-term neurological disability. Non-contrast computed tomography (CT) is the gold-standard imaging modality for the rapid diagnosis of TBI. Clinical outcomes depend strongly on early detection and prompt acute management. Artificial intelligence (AI)-based models may support faster automated identification of traumatic findings and early prediction of patient prognosis. A systematic literature search was conducted in PubMed/MEDLINE, Scopus, IEEE Xplore, ACM Digital Library, and the Cochrane Library in accordance with PRISMA 2020 guidelines to evaluate AI-based models for automated detection of TBI-related findings on CT and for prediction of clinical outcomes. Risk of bias and applicability were assessed using QUADAS-2 for diagnostic accuracy studies and PROBAST + AI for prediction model studies. Twenty-two studies were included. Sixteen studies evaluated diagnostic tasks and 10 evaluated prognostic outcomes, with four studies contributing to both categories. Diagnostic performance was generally high, with many studies reporting AUC values approaching or exceeding 0.90, particularly for larger lesion volumes.Prognostic performance was more variable, with moderate to high discrimination and substantial heterogeneity. Only 9 studies incorporated independent external validation, and performance was frequently lower in external cohorts. All prognostic model studies were judged to be at high overall risk of bias using PROBAST + AI, and most diagnostic accuracy studies also demonstrated high or unclear risk of bias in at least one QUADAS-2 domain, most frequently in patient selection. AI-based models applied to brain CT demonstrate strong technical performance for both diagnostic and prognostic tasks in TBI. However, most studies relied on retrospective designs and lacked independent external validation which limits models generalizability and raises concern for potential overfitting. Prospective, multicenter studies with standardized methodologies and rigorous external validation are required before widespread clinical implementation.

Humans

Novelty seeking and rapid symptom improvement across active and sham accelerated iTBS conditions: A pooled individual-patient data analysis.

INTRODUCTION: Major depressive disorder (MDD) is highly prevalent and often treatment-resistant. Accelerated intermittent theta burst stimulation (aiTBS) is a promising intervention for treatment-resistant depression (TRD), though outcomes vary. Personality traits have been examined in relation to rTMS outcomes, yet their role in aiTBS remains underexplored. This pooled individual-patient-data analysis of two randomized, sham-controlled trials examined associations between baseline Temperament and Character Inventory (TCI) traits and one-week symptom change, and whether they differed by condition. METHODS: The left dorsolateral prefrontal cortex was targeted for 20 sessions over 4 days. Personality was assessed with the TCI, depression severity with the 17-item Hamilton Depression Rating Scale (HDRS-17). TCI-symptom-change associations were examined with a robust linear mixed-effects model, adjusting for age, gender, repeated measurements, and study membership. RESULTS: 104 participants were included (M/F 45/59; mean age 40.9 ± 12.7; active/sham 50/54). The model yielded a Time × Novelty Seeking interaction (β = -1.70, p = 0.021): higher baseline Novelty Seeking was associated with faster symptom reduction, without a between-arm difference. However, the interaction did not survive Holm correction across 14 trait-interaction tests (adjusted p = 0.294) and is therefore exploratory. No other interaction reached the uncorrected threshold. CONCLUSIONS: Higher baseline Novelty Seeking showed a nominal association with faster symptom reduction, without a difference between active and sham conditions. Because it did not survive multiplicity correction and was not reproduced in within-arm analyses, it is preliminary and may reflect contextual or nonspecific processes. Independent replication is required before temperament assessment can be clinically informative.

Humans

Global molecular and serological evidence of dengue and chikungunya infection: a systematic review and meta-analysis of 158,608 tested participants.

INTRODUCTION: Dengue virus (DENV) and chikungunya virus (CHIKV) are Aedes-borne arboviruses with overlapping clinical manifestations, shared vectors, and substantial diagnostic challenges in co-endemic settings. This systematic review and meta-analysis synthesized published evidence on molecular detection, serological positivity, and DENV-CHIKV dual positivity/co-infection in human clinical, surveillance, and community-based study populations. CONTENT: Following PRISMA 2020 guidance, five bibliographic databases (PubMed/MEDLINE, Scopus, Web of Science, ScienceDirect, and Google Scholar) and supplementary grey-literature/preprint sources were searched for English-language studies published from 1 January 1980 to 31 December 2024. No prospective PROSPERO or OSF protocol registration was available. Eligible records reported extractable numerators and denominators for DENV and/or CHIKV in humans using recognized molecular or serological assays. A total of 196 studies comprising 158,608 tested or suspected participants were included in the extraction table. The pooled CHIKV estimate was 14.0 % (95 % CI: 12.0-16.4; I2=97.5 %), with molecular and serological estimates of 9.8 and 15.7 %, respectively. The pooled DENV estimate was 13.8 % (95 % CI: 10.9-17.3; I2=99.0 %), with molecular and serological estimates of 13.1 % (95 % CI: 7.9-21.0) and 14.3 % (95 % CI: 10.2-19.8), respectively. DENV-CHIKV dual positivity/co-infection was 52.9 % (95 % CI: 48.7-57.1) among studies that tested and reported both outcomes. Country-level estimates varied widely and should be interpreted as summaries of available studies rather than nationally representative burden estimates. Funnel-plot asymmetry was statistically significant in DENV analyses but not in the overall CHIKV analysis. SUMMARY: Available evidence indicates extensive but highly heterogeneous DENV and CHIKV positivity across selected clinical and surveillance populations. The pooled estimates should be interpreted cautiously because of substantial between-study heterogeneity, diagnostic variability, outbreak-period sampling, and uneven geographic representation. OUTLOOK: The findings support integrated arboviral surveillance, multiplex diagnostics, and vector-control preparedness in co-endemic regions.

Humans

Accelerated Diagnostic Pathways for Suspected Acute Coronary Syndrome in Practice: A Randomized Trial of 0/1-Hour vs 0/3-Hour Troponin Testing.

BACKGROUND: For suspected acute coronary syndrome (ACS), guidelines recommend using high-sensitivity troponins (hs-cTn) in accelerated diagnostic pathways (ADPs) with 0/1-hour recommended over 0/3-hour ADP. However, implementation of these ADPs, with universal use of hs-cTns, has not been directly compared in randomized trials OBJECTIVES: This study sought to compare the efficiency and safety of the European Society of Cardiology (ESC) 0/1-hour and a 0/3-hour ADP when implemented in real-world clinical practice. METHODS: This pragmatic, randomized, noninferiority implementation trial compared the safety and efficiency of clinician decision making using these 2 pathways. To prevent incorporation bias, an independent hs-cTnI was used for formal adjudication using the fourth universal definition of myocardial infarction (MI). Efficiency was judged by the proportion of patients discharged within 4 hours. The safety endpoint was major adverse cardiac events (MACE) within 30 days (adjudicated index or representation type 1 MI, cardiovascular death, and urgent coronary revascularization) for those who were considered not to have ACS and discharged. The noninferiority margin, for absolute difference in sensitivity, between the ESC 0/1-hour and the 0/3-hour ADP was set at 3%, assessed with a 1-sided 97.5% CI. RESULTS: From December 2021 to July 2024, of 13,983 screened 3,543 individual patients with suspected ACS were recruited and consented from 2 major emergency departments in North-West England, with 100% follow-up achieved for all representations to any national hospital. The median age was 60 years (IQR: 49.5-70.5 years), 53% were men, 6.7%, and 7.6% had adjudicated index type 1 MI and MACE within 30 days, respectively. The turnaround time from sample to result for central laboratory hs-cTnT was 81 minutes (IQR: 69-101 minutes). The proportion of patients discharged within 4 hours was relatively low and did not differ substantially (21.8% vs 19.2%, P = 0.07). In addition, the 0/1-hour pathway was noninferior for safety, in patients discharged, compared with the 0/3-hour pathway, absolute difference in sensitivity was +4.2% (1-sided 97.5% CI: -2.5) in favor of the 0/1-hour pathway. The calculated sensitivities were 93.7% (95% CI: 88.4%-97.1%) vs 89.5% (95% CI: 82.7%-94.3%), respectively. CONCLUSIONS: Implementation of the ESC 0/1-hour pathway failed to discharge significantly more patients within 4 hours of presentation compared with the 0/3-hour ADP. In addition, The ESC 0/1-hour was noninferior to the 0/3-hour hs-cTn pathway for safety of discharge, although safety for both pathways was less than that imputed by observational studies. This trial demonstrates that perceived benefits to emergency department efficiency of a reduced sampling interval are mitigated by central laboratory turnaround times as well as system constraints. (Pragmatic Randomised Trial of the ESC 0/​1 Versus 0/​3 Hour Troponin Pathway [MACROS2]; NCT05322395).

Acute Coronary Syndrome

Feasibility of routine clinical liquid-based cytology for lung cancer compact panel testing.

BACKGROUND: The Lung Cancer Compact Panel (cPANEL) is a recently approved highly sensitive multiplex gene panel in Japan that supports both DNA- and RNA-based next-generation sequencing. Although cytological specimens are acceptable for cPANEL, unfixed cell pellets or dedicated preservation tubes are typically recommended. However, evidence remains limited regarding whether residual liquid-based cytology (LBC) cell suspensions prepared for routine cytological diagnosis can be used directly for cPANEL testing without dedicated molecular preservation or additional preanalytical processing. In this study, we evaluated the feasibility of applying LBC specimens that are widely used in contemporary clinical practice to cPANEL. METHODS: We analyzed DNA and RNA quality in 69 clinical LBC specimens. Among these, 51 specimens containing non-small cell lung cancer cells with previously determined driver alteration status were subjected to cPANEL testing to evaluate assay concordance with clinical companion diagnostic results. RESULTS: DNA integrity was generally well preserved (DNA Integrity Number [DIN]: 6.2 ± 1.5). In contrast, RNA integrity showed greater variability (DV200: 16.4 ± 12.1%). ThinPrep-fixed specimens demonstrated lower DIN and DV200 values compared with CytoRich Red-fixed specimens. Although all samples successfully passed the DNA-based cPANEL assay, six cases (11.8%) failed the RNA-based assay, with RNA yield being a major contributing factor. Among the 46 evaluable specimens, concordance was 95.7% and sensitivity was 92.3%, or 88.9% including RNA module failures as cPANEL-negative. CONCLUSIONS: With appropriate fixative selection and adequate cellularity, cPANEL using clinical LBC specimens may serve as a practical diagnostic platform. We demonstrated that routine LBC specimens can be directly applied to cPANEL without special preanalytical processing.

Humans

Diagnostic performance of machine learning models versus established risk stratification for intracranial aneurysm rupture: a systematic review and bivariate meta-analysis.

BACKGROUND: Machine learning (ML) models have been proposed to improve the discrimination of intracranial aneurysm rupture status beyond established clinical risk stratification tools. However, reported performance is heterogeneous and the relative contribution of model architecture and feature dominance remains unclear. METHODS: We performed a Preferred Reporting Items for Systematic Reviews and Meta-Analyses-diagnostic test accuracy systematic review and diagnostic meta-analysis of studies evaluating ML models for intracranial aneurysm rupture discrimination. PubMed, Embase and CENTRAL were searched to February 2026. Sensitivity and specificity were pooled using a bivariate random-effects model, with summary receiver operating characteristic curves generated across training, internal testing and external validation datasets. Models were compared with regression-based approaches and Population, Hypertension, Age, Size of aneurysm, Earlier subarachnoid haemorrhage, Site of aneurysm (PHASES) scores. Subgroup and meta-regression analyses explored associations between algorithm family and feature domain. RESULTS: Sixty-two retrospective cohorts (29 709 patients 209 models) met the inclusion criteria. In training datasets, pooled sensitivity and specificity for ML were 0.81 (95% CI 0.75 to 0.85) and 0.83 (0.80-0.86), with an area under the curve (AUC) of 0.878, exceeding PHASES (AUC 0.667). In testing datasets, ML retained higher discrimination (AUC 0.837) than regression models (0.806) and PHASES (0.646). In external validation, sensitivity was preserved (0.82), but specificity declined (0.66). Deep learning demonstrated the highest AUCs (training and testing). Incorporation of haemodynamic or radiomic features improved pooled discrimination relative to morphology alone. Evidence of small-study effects and mostly unclear Prediction Model Risk Of Bias Assessment Tool ratings were observed. CONCLUSIONS: ML approaches demonstrate higher pooled discrimination for aneurysm rupture status than conventional risk scores in retrospective datasets, but reduced external validation specificity and heterogeneity limit confidence for clinical translation. Prospective, externally validated, calibrated models are required before integration into routine cerebrovascular risk stratification.

Humans

Real-world clinical utility of exome sequencing in pediatric drug-resistant epilepsy: Experience from a tertiary center in Thailand.

BACKGROUND: Genomic testing has increasingly contributed to the diagnosis and management of pediatric drug-resistant epilepsy (DRE), particularly in patients with suspected genetic etiologies. This study evaluated the diagnostic yield and real- world clinical utility of whole-exome sequencing (WES) in children with DRE. METHODS: Children with DRE and seizure onset before 15 years of age were enrolled between January 2020 and December 2023. Clinical data, including demographics, seizure characteristics, developmental history, electroencephalography (EEG), brain magnetic resonance imaging (MRI), and prior investigations, were reviewed. WES was performed in all probands and, when available, their parents. Variants were interpreted according to standard guidelines. Clinical utility and 1-year seizure and developmental outcomes were assessed from follow-up records. RESULTS: Fifty-six patients (23 males, 33 females) were included. The median age at seizure onset was 1 year (interquartile range [IQR] 0.3-4 years), and 96.4% had developmental comorbidities. Pathogenic or likely pathogenic variants were identified in 39% (22/56), with the highest diagnostic yield in children with seizure onset before 3 years of age. Channelopathies accounted for most genetically solved cases (68%), predominantly involving sodium channel genes. Genetic diagnoses provided clinical utility in 73% (16/22) of solved cases by guiding treatment and precision management. At 1-year follow-up, genetically solved patients showed more favorable seizure and developmental outcomes than those with genetically unsolved patients. CONCLUSION: WES achieved a 39% diagnostic yield and substantial clinical utility in pediatric DRE, particularly in early-onset and channelopathy-related disorders. These findings support early molecular diagnosis to facilitate genotype-informed management in appropriately selected children. However, the more favorable developmental and seizure outcomes observed in genetically solved patients should be interpreted with caution, as they may have been influenced by multiple factors beyond genetic diagnosis. In resource-limited settings, careful clinical phenotyping remains essential for treatment decisions and for prioritizing children for genomic testing.

Clinical utility

Translating single-cell RNA sequencing into monocyte direct leukocyte subpopulation-transcript abundance assay ratio-based biomarkers (IFI27/PSAP or IFI27/CTSS) for clinical detection of viral infection.

A rapid method for triaging febrile patients by aetiology (e.g., viral or bacterial infection) using gene expression in peripheral blood (PB) is an intensively researched area. However, gene expression in blood represents a composite sum of gene expression of all the component cell types present in the sample. As a result, numerous genes are measured in most proposed signatures. Herein, we propose a simple ratio-based biomarker (RBB) called direct leukocyte subpopulation-transcript abundance assay (DIRECT LS-TA) that recapitulates gene expressions of a single cell type in PB (i.e., monocytes). Based on single-cell RNA sequencing (scRNAseq) data and bulk expression data, IFI27 and SIGLEC1 are found as interferon-stimulated genes (ISGs) predominantly expressed by monocytes. The DIRECT LS-TA method can use a simple ratio of two genes measured in PB as an RBB to represent the target gene expression in monocytes without the need for monocyte purification. Both scRNAseq and bulk RNA sequencing datasets were used to evaluate the correlation between ISG expression in monocytes and PB, with a particular focus on monocyte expression of IFI27. An iceberg plot of bulk transcriptome data was used to identify genes that were predominantly expressed by monocytes in PB. DIRECT LS-TA RBBs of the three genes (IFI27, IFI44L and SIGLEC1) were evaluated by group-wise comparison, receiver operating characteristic and meta-analysis. In addition, the conventional interferon (IFN) score was evaluated for comparison of diagnostic performance. In viral infection datasets, DIRECT LS-TA of IFI27 (IFI27/PSAP or IFI27/CTSS) was most intensely activated (p value by t test <1e-9) and had the best area under the curve (0.94) among the three potential monocyte ISGs analysed. DIRECT LS-TA SIGLEC1 was also another monocyte biomarker but showed a lower activation (p<9e-5). IFI27/PSAP showed better diagnostic performance than the conventional IFN score. On the other hand, IFI44L was not a predominant monocyte expression gene. DIRECT LS-TA of IFI27 (IFI27/PSAP or IFI27/CTSS) measured in PB was the best biomarker of viral infection and IFN activation among ISGs predominantly expressed by monocytes. It performed even better than the conventional IFN score which required quantification of eight genes. The results suggest that DIRECT LS-TA of IFI27 is a monocyte-informative biomarker which is easy to determine in PB without the need for cell sorting.

Humans

RFC1 Repeat Expansions in Chronic Idiopathic Axonal Polyneuropathy: Prevalence, Phenotype, and Diagnostic Implications.

BACKGROUND AND AIMS: Chronic idiopathic axonal polyneuropathy (CIAP) accounts for approximately 20%-30% of adult-onset axonal polyneuropathies. Pathogenic RFC1 repeat expansions have emerged as a frequent cause of idiopathic sensory neuropathy, but their recognition in routine clinical practice may be challenging, particularly in the presence of potentially confounding comorbidities. We aimed to determine the prevalence of pathogenic RFC1 repeat expansions in a well-defined CIAP cohort, characterize the associated clinical and electrophysiological phenotype, and evaluate whether coexisting well-controlled diabetes mellitus (DM) or monoclonal gammopathy of undetermined significance (MGUS) may hinder recognition of RFC1-related neuropathy. METHODS: We performed a retrospective observational study of adult patients with CIAP followed at a tertiary neuromuscular unit. All patients underwent RFC1 genetic testing. Clinical and electrophysiological features were compared between RFC1+ and RFC1- patients in the full cohort and after exclusion of patients with DM or MGUS. RESULTS: Ninety patients met CIAP criteria and were analyzed. Twenty-four (27%) carried biallelic pathogenic AAGGG repeat expansions in RFC1, of whom 6 (25%) had coexisting DM or MGUS. Compared with RFC1- patients, RFC1+ individuals more frequently exhibited dysautonomic symptoms, unsteadiness, history of falls, need for walking support, chronic cough, impaired vibration sense in the upper limbs and up to the knees in the lower limbs, brisk upper-limb reflexes, mild cerebellar signs, an abnormal head-impulse test, and a positive Romberg's test. Most of these differences persisted after exclusion of DM or MGUS. Electrophysiological studies in RFC1+ patients showed widespread sensory nerve involvement, including the upper limbs, with relative motor sparing, whereas RFC1- patients exhibited a more typical length-dependent pattern. INTERPRETATION: Biallelic AAGGG repeat expansions in RFC1 were identified in 27% of patients with CIAP. Specific clinical and electrophysiological features may help distinguish RFC1-related disease from other forms of CIAP and identify candidates for genetic testing, even in the presence of potentially confounding comorbidities such as well-controlled DM or MGUS.

Humans

Cost-Effectiveness and the Economics of Genomic Testing and Molecularly Matched Therapies.

Cost-effectiveness analysis of precision oncology can help guide value-driven care. Next-generation sequencing is increasingly cost-efficient over single gene testing because diagnostic algorithms require multiple individual gene tests to determine biomarker status. Matched targeted therapy is often not cost-effective due to the high cost associated with drug treatment. However, genomic profiling can promote cost-effective care by identifying patients who are unlikely to benefit from therapy. Additional applications of genomic profiling such as universal testing for hereditary cancer syndromes and germline testing in patients with cancer may represent cost-effective approaches compared with traditional history-based diagnostic methods.

Humans

Polygenic risk scores in major depressive disorder: A systematic review across diagnostic, treatment, course/severity, and subtype domains.

BACKGROUND: Major depressive disorder (MDD) is heterogeneous across diagnostic, treatment-related, course/severity, and subtype domains. Polygenic risk score (PRS) studies have examined these domains, but differences in PRS sources, samples, methods, and endpoint definitions have fragmented the evidence. We synthesised findings and examined potential contributors to heterogeneity. METHODS: PubMed/MEDLINE, Embase, PsycINFO, and Web of Science were searched for studies published from January 2016 through 25 November 2025. Result records were synthesised using SWiM, and certainty was assessed with an adapted GRADE framework. RESULTS: Sixty studies contributed 493 retained records; 450 were descriptively classified as positive, null, or reverse, although records were not independent. Positive findings accounted for 44/56 diagnostic, 61/273 treatment-related, 64/100 course/severity, and 14/21 subtype records. For MDD/depression-derived PRSs and case-control MDD status, all 10 contributing studies showed higher liability in cases (exploratory exact sign test p&#xa0;=&#xa0;0.002; FDR q&#xa0;=&#xa0;0.004). The same PRS group showed positive findings for overall depressive symptom severity (14/18), although the study-level test was imprecise (5/5 studies; p&#xa0;=&#xa0;0.063). Pharmacological response/remission findings for these PRSs were mostly null or directionally mixed (10 positive, 18 null, and 9 reverse). Treatment-resistant depression (TRD) findings differed by operational definition. Atypical and psychotic subtype signals arose mainly from single-study PRS and endpoint contrasts. CONCLUSIONS: PRS evidence was clearest for MDD diagnostic status and showed a tentative pattern for overall symptom burden. Treatment and subtype findings were less consistent or less replicated. Larger, ancestrally diverse studies with standardised endpoints and transparent PRS methods are needed.

Humans