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PubMed2026

Diagnostic accuracy of bronchoalveolar lavage fluid-based testing for pulmonary cryptococcosis: A systematic review and meta-analysis.

BACKGROUND: Pulmonary cryptococcosis(PC) presents diagnostic challenges because of its non-specific clinical and radiological manifestations. Bronchoalveolar lavage fluid (BALF)-based testing, which includes latex agglutination (LA) and lateral flow assay (LFA), offers a minimally invasive diagnostic method, yet its pooled diagnostic accuracy remains unclear. METHODS: We systematically searched PubMed, Embase, Cochrane Library, and Scopus from inception to May 2026. Studies evaluating BALF-based testing for PC with extractable 2 × 2 data were included. The methodological quality of relevant studies was assessed by the QUADAS-2 tool. Pooled sensitivity, specificity, likelihood ratios, and diagnostic odds ratio (DOR) were estimated using a bivariate random-effects model. Subgroup analyses were performed by testing method and reference standard type. Heterogeneity was evaluated through paired forest plots, HSROC visualization, and exploratory bivariate meta-regression. RESULTS: The pooled sensitivity was 0.87 (95% CI: 0.81-0.91), and the specificity was 0.99 (95% CI: 0.982 - 0.995). The pooled positive likelihood ratio (PLR) was 88.00 (95% CI: 47.39 - 163.42), the negative likelihood ratio (NLR) was 0.13 (95% CI: 0.09 -0.20), and the DOR was 658.50 (95% CI: 285.36-1519.55). No significant threshold effect or publication bias was detected. Exploratory meta-regression suggested a possible assay-method effect in the joint model (P = 0.03), mainly driven by specificity (P = 0.01). CONCLUSIONS: The study demonstrates the high accuracy of CrAg in BALF for the diagnosis of pulmonary cryptococcosis, supporting its role as an important adjunctive diagnostic tool, particularly when tissue biopsy is not feasible or rapid results are needed. Larger prospective studies with standardized protocols are needed to validate these estimates.

Humans↗

PubMed2026

Vitamin B12 Deficiency in Sickle Cell Disease: Method-Driven Estimates and Systematic Diagnostic Misclassification.

OBJECTIVES: To determine whether the reported 0%-70% prevalence of vitamin B12 deficiency in sickle cell disease (SCD) reflects true population variation or diagnostic misclassification. METHODS: We conducted a PRISMA 2020-compliant systematic review of observational studies (January 1, 2000-May 13, 2026; PROSPERO CRD420251087800) assessing B12 status in SCD. PubMed, AJOL, and Google Scholar were searched with citation tracking and dual screening. Diagnostic validity was assessed across biomarker strategy, analytical platform, thresholds, and confounder control using a proposed context-integrated framework to classify methodological robustness and discordance. RESULTS: Fourteen studies were included (57% high-income; 43% LMIC). The evidence base was dominated by limited diagnostic approaches: 71% used immunoassays, over one-third relied on circulating B12 alone, and functional biomarkers were inconsistently applied without systematic confounder adjustment. Prevalence estimates were strongly influenced by diagnostic methods rather than underlying population biology, ranging from 0% to 70% in single-marker studies (mostly 0%-7.1%, with outliers ~50%-70%) and 6.9%-53% in multi-marker studies. Discordance was substantial and greater in LMIC settings than HIC. CONCLUSION: Current diagnostic approaches in SCD appear method-dependent, generating heterogeneous prevalence estimates with uncertain clinical validity. These findings challenge existing estimates and have implications for clinical practice, research design, and diagnostic equity. TRIAL REGISTRATION: ClinicalTrials.gov identifier: CRD420251087800.

Humans↗

PubMed2026

A systematic review and meta-analysis to estimate the global prevalence of leptospirosis in sheep.

Leptospirosis in sheep is a zoonotic concern considering sheep may act as potential reservoirs for Leptospira spp. infection to humans. This study aimed to estimate the pooled prevalence of leptospirosis in sheep worldwide. A comprehensive literature search was conducted across databases following PRISMA guidelines. Meta-analyses were performed using a random effect model in R software (version 4.3.1) to calculate pooled prevalence with 95% confidence intervals (CI). Subgroup analyses were performed based on prevalence types, diagnostic methods and continental regions to explore sources of heterogeneity. A total of 138 studies comprising 54,174 samples and 10,299 positive detections were included in this study. The global pooled prevalence of leptospirosis in sheep was 15.69% (95% CI: 12.69-19.25) with overall heterogeneity (I2) 98%. The prediction interval ranged from 1.09% to 75.91%, indicating wide inter-study variability. The seroprevalence was 16.16% (95% CI: 12.91-20.04) and infection prevalence was 12.98% (95% CI: 8.07-20.22), showing no significant difference (P = 0.40). In addition, the prevalence of leptospirosis in sheep differed significantly across diagnostic methods and continents (P < 0.01), indicating substantial variation influenced by both methodological and geographical factors. The funnel plot revealed marked asymmetry, suggesting potential publication bias which was confirmed by Egger's regression test (P < 0.01). In conclusion, leptospirosis is widely prevalent in sheep globally, with marked geographical and methodological heterogeneity. These findings highlight the epidemiological importance of sheep in leptospirosis transmission and underscore the need for improved surveillance, standardized diagnostic approaches, and targeted control strategies within a One Health framework.

Animals↗

PubMed2025

Worldwide prevalence of haemorrhoids: a systematic review and meta-analysis.

BACKGROUND: Haemorrhoidal disease (HD) is one of the most common anorectal disorders globally, significantly impacting individuals' quality of life and productivity. Despite its importance, global prevalence remains unclear due to limited population-specific studies. This study aimed to systematically assess the global prevalence of HD through a systematic review and meta-analysis. METHODS: We conducted a systematic review and meta-analysis by searching PubMed, Scopus, Embase, Web of Science, and Google Scholar up to March 31, 2025, without language restrictions. Studies reporting prevalence of haemorrhoids in general, clinical, or high-risk populations were included. Exclusion criteria comprised studies lacking total sample size, focusing on other anorectal conditions, or using duplicate or insufficient data. Four independent reviewers extracted and appraised study quality using the Joanna Briggs Institute tool. The primary outcome was pooled point prevalence of HD, analyzed using a random-effects model with 95% confidence intervals (CIs). The study was registered in PROSPERO (CRD420251045600). RESULTS: From 6,312 records, 150 studies (210 datasets) comprising 8,960,338 individuals were included. The global pooled point prevalence was 25.92% (95% CI: 22.62-29.22). Lifetime prevalence was 27.19% (95% CI: 14.77-39.60), and one-year prevalence was 21.65% (95% CI: 14.33-28.97). Prevalence was higher in women (27.33%, 95% CI: 21.84-32.82) than in men, and highest in the African region 28.07% (95% CI: 15.34-40.79). Invasive diagnostic methods (28.05%, 95% CI: 23.86-32.26) yielded higher prevalence estimates than non-invasive methods. Also, factors showing associations with HD in unadjusted analyses include older age, obesity, pregnancy, diabetes, family history, constipation, and hypertension. CONCLUSION: HD remains a prevalent condition globally, with minor variation across regions. The burden is consistent regardless of socioeconomic context. Diagnostic method and population characteristics influence prevalence estimates. These findings underscore the importance of targeted prevention and early intervention strategies, especially for at-risk groups.

Humans↗

PubMed2026

Clinical and Genomic Insights into the Allodiploid Hybrid Pathogen Aspergillus latus: A Retrospective Case Series.

Aspergillus latus is an emerging cryptic allodiploid hybrid pathogen within Aspergillus section Nidulantes that closely resembles related species and therefore prone to misidentification by routine diagnostic methods. Therefore, its true clinical burden is likely underestimated. In this study, we retrospectively characterized five patients with A. latus infections identified by metagenomic next-generation sequencing (mNGS) at a tertiary hospital in China. Clinical manifestations varied according to host immune status, ranging from a subclinical pulmonary lesion in an immunocompetent individual to aggressive disease in highly immunocompromised patients. Conventional microbiological methods showed limited sensitivity and consistently misidentified the isolates as A. nidulans, whereas mNGS enabled accurate detection of A. latus together with complex co-infections. Three viable clinical isolates were recovered for morphological characterization, antifungal susceptibility testing, and whole-genome sequencing (WGS). All tested isolates demonstrated reduced susceptibility to echinocandins but remained susceptible to mold-active triazoles and amphotericin B. Furthermore, WGS and macrosynteny analyses confirmed their allodiploid hybrid nature, revealing a mosaic genome derived from A. spinulosporus and an A. quadrilineatus-related lineage. Collectively, these findings highlight that A. latus may be missed by routine diagnostic methods and may exhibit a distinct antifungal susceptibility profile. Molecular approaches such as mNGS and WGS may therefore help achieve accurate species-level identification and support targeted antifungal therapy. Given this small retrospective case series, larger prospective and multicenter studies are needed to validate these observations and better define the epidemiology, clinical spectrum, and therapeutic implications of this emerging allodiploid hybrid pathogen.

Retrospective Studies↗

PubMed2024

Development of a clinical metagenomics workflow for the diagnosis of wound infections.

BACKGROUND: Wound infections are a common complication of injuries negatively impacting the patient's recovery, causing tissue damage, delaying wound healing, and possibly leading to the spread of the infection beyond the wound site. The current gold-standard diagnostic methods based on microbiological testing are not optimal for use in austere medical treatment facilities due to the need for large equipment and the turnaround time. Clinical metagenomics (CMg) has the potential to provide an alternative to current diagnostic tests enabling rapid, untargeted identification of the causative pathogen and the provision of additional clinically relevant information using equipment with a reduced logistical and operative burden. METHODS: This study presents the development and demonstration of a CMg workflow for wound swab samples. This workflow was applied to samples prospectively collected from patients with a suspected wound infection and the results were compared to routine microbiology and real-time quantitative polymerase chain reaction (qPCR). RESULTS: Wound swab samples were prepared for nanopore-based DNA sequencing in approximately 4 h and achieved sensitivity and specificity values of 83.82% and 66.64% respectively, when compared to routine microbiology testing and species-specific qPCR. CMg also enabled the provision of additional information including the identification of fungal species, anaerobic bacteria, antimicrobial resistance (AMR) genes and microbial species diversity. CONCLUSIONS: This study demonstrates that CMg has the potential to provide an alternative diagnostic method for wound infections suitable for use in austere medical treatment facilities. Future optimisation should focus on increased method automation and an improved understanding of the interpretation of CMg outputs, including robust reporting thresholds to confirm the presence of pathogen species and AMR gene identifications.

Humans↗

PubMed2026

Integrating Optical Genome Mapping into the Genetic Diagnostic Algorithm: Clinical Utility in Unresolved Autosomal Recessive Disorders from a Large Cohort.

INTRODUCTION: The identification of precise genetic etiologies is indispensable for the clinical management of monogenic disorders. However, conventional diagnostic methods and exome sequencing (ES) frequently fail to identify complex structural variations (SVs), leaving the genetic basis unexplained in approximately 30-60% of suspected cases. Optical genome mapping (OGM) emerges as a high-resolution technology capable of detecting cryptic SVs inaccessible to standard methodologies. METHODS: In this study, we evaluated the clinical utility of integrating OGM into the diagnostic algorithm for unresolved monogenic diseases. Following negative or inconclusive results from standard ES pipelines, OGM was applied to a targeted subset of patients (n = 7) selected from a comprehensive clinical cohort of 1,257 individuals with suspected genetic disorders. RESULTS: The integration of OGM identified candidate SVs that may represent the second allelic alteration in two distinct cases; however, confirmation through parental segregation analysis remains pending. Specifically, OGM identified an intronic insertion in the TTLL5 gene and a deletion in a putative regulatory region approximately 400 kb upstream of the NMNAT1 gene, both of which were missed by prior diagnostic testing. CONCLUSION: Our findings suggest that OGM has potential value in investigating the missing heritability of autosomal recessive disorders. By detecting candidate SVs invisible to conventional methods, OGM may warrant consideration as a complementary diagnostic approach following inconclusive ES; however, larger cohorts and confirmatory functional studies are needed to establish its clinical utility.

Autosomal recessive disorders↗

PubMed2025

Bacteriophages as a modern diagnostic tool: innovations, applications and challenges.

Bacteriophages, viruses that specifically infect bacteria, have emerged as a valuable tool in diagnostics due to their unique specificity and adaptability. This review explores the diverse applications of bacteriophages in diagnostic methods, from traditional phage typing to advanced molecular techniques such as phage display and PCR-based diagnostics. It highlights their use in identifying bacterial strains, monitoring fermentation processes, and diagnosing critical conditions like tuberculosis, MRSA infections, and cancer. Innovations such as phage-based biosensors and reporter phages enhance the speed and precision of diagnostics, offering significant advantages over traditional methods. Challenges, including bacterial resistance and immune responses to phages, are also discussed alongside strategies for mitigation, such as phage cocktails and engineering. Integrating phage technology with modern bioscience holds promise for addressing antibiotic resistance and revolutionizing clinical and industrial diagnostics. This comprehensive analysis underscores the potential of bacteriophages to transform the diagnostic landscape while identifying areas requiring further research and development.

Bacteriophages↗

PubMed2026

Automated Classification of Lymphoma Subtypes From Histopathological Images Using a U-Net Deep Learning Model: Comparative Evaluation Study.

BACKGROUND: Accurate classification and grading of lymphoma subtypes are essential for treatment planning. Traditional diagnostic methods face challenges of subjectivity and inefficiency, highlighting the need for automated solutions based on deep learning techniques. OBJECTIVE: This study aimed to investigate the application of deep learning technology, specifically the U-Net model, in classifying and grading lymphoma subtypes to enhance diagnostic precision and efficiency. METHODS: In this study, the U-Net model was used as the primary tool for image segmentation integrated with attention mechanisms and residual networks for feature extraction and classification. A total of 620 high-quality histopathological images representing 3 major lymphoma subtypes were collected from The Cancer Genome Atlas and the Cancer Imaging Archive. All images underwent standardized preprocessing, including Gaussian filtering for noise reduction, histogram equalization, and normalization. Data augmentation techniques such as rotation, flipping, and scaling were applied to improve the model's generalization capability. The dataset was divided into training (70%), validation (15%), and test (15%) subsets. Five-fold cross-validation was used to assess model robustness. Performance was benchmarked against mainstream convolutional neural network architectures, including fully convolutional network, SegNet, and DeepLabv3+. RESULTS: The U-Net model achieved high segmentation accuracy, effectively delineating lesion regions and improving the quality of input for classification and grading. The incorporation of attention mechanisms further improved the model's ability to extract key features, whereas the residual structure of the residual network enhanced classification accuracy for complex images. In the test set (N=1250), the proposed fusion model achieved an accuracy of 92% (1150/1250), a sensitivity of 91.04% (1138/1250), a specificity of 89.04% (1113/1250), and an F1-score of 90% (1125/1250) for the classification of the 3 lymphoma subtypes, with an area under the receiver operating characteristic curve of 0.95 (95% CI 0.93-0.97). The high sensitivity and specificity of the model indicate strong clinical applicability, particularly as an assistive diagnostic tool. CONCLUSIONS: Deep learning techniques based on the U-Net architecture offer considerable advantages in the automated classification and grading of lymphoma subtypes. The proposed model significantly improved diagnostic accuracy and accelerated pathological evaluation, providing efficient and precise support for clinical decision-making. Future work may focus on enhancing model robustness through integration with advanced algorithms and validating performance across multicenter clinical datasets. The model also holds promise for deployment in digital pathology platforms and artificial intelligence-assisted diagnostic workflows, improving screening efficiency and promoting consistency in pathological classification.

Humans↗

PubMed2026

Higher Rates of PASS and SCB After Arthroscopic Subspine Decompression Are Associated With a Positive Diagnostic AIIS Injection: A Propensity Score-Matched Cohort Study.

BACKGROUND: Hip arthroscopy effectively treats femoroacetabular impingement syndrome (FAIS), but persistent pain may be related to concomitant extra-articular pathology such as subspine impingement syndrome (SSI). Standard diagnosis of SSI often relies on 3-dimensional computed tomography (3D-CT) morphology (Hetsroni type II/III), although this morphology is common in individuals who are asymptomatic and correlates poorly with symptoms. PURPOSE: To compare minimum 2-year clinical outcomes after arthroscopic subspine decompression in patients with concurrent FAIS and type II/III anterior inferior iliac spine (AIIS) morphology, stratified by diagnostic method: 3D-CT morphology alone versus 3D-CT morphology plus a positive ultrasound-guided diagnostic injection. STUDY DESIGN: Cohort study; Level of evidence, 3. METHODS: This study included patients aged 18 to 55 years with type II/III AIIS morphology who underwent primary hip arthroscopy for FAIS and SSI between January 2021 and November 2023 and had minimum 2-year follow-up. Patients diagnosed by CT morphology alone (CT classification group) were propensity score matched 1:1 to patients with a positive ultrasound-guided AIIS injection (injection group), with 57 patients per group. Matching variables were age, sex, body mass index, lateral center-edge angle, alpha angle, Tönnis grade, and Beighton score. All patients underwent arthroscopic subspine decompression. Patient-reported outcomes and rates of achieving the minimal clinically important difference, Patient Acceptable Symptom State (PASS), and substantial clinical benefit (SCB) were compared. RESULTS: Preoperative patient-reported outcome scores were similar between groups (all P > .05). At minimum 2-year follow-up, the injection group had significantly better scores on the modified Harris Hip Score (90.8 vs 84.2), Hip Outcome Score-Activities of Daily Living (88.4 vs 82.4), Hip Outcome Score-Sports Subscale (71.9 vs 64.1), 12-item International Hip Outcome Tool (83.9 vs 76.1), and visual analog scale for pain (1.2 vs 2.0) (all P < .001). Minimal clinically important difference rates were high in both groups, with higher rates in the injection group for modified Harris Hip Score (93% vs 77%; P = .033) and Hip Outcome Score-Activities of Daily Living (91% vs 75%; P = .042). PASS and SCB rates were significantly higher in the injection group across all patient-reported outcome measures (all P < .05). Revision and complication rates were low and did not differ significantly between groups. CONCLUSION: Both groups improved significantly after arthroscopic subspine decompression. However, patients with a positive ultrasound-guided diagnostic AIIS injection achieved higher PASS and SCB rates than those selected by CT morphology alone, suggesting that injection-confirmed SSI may improve patient selection for subspine decompression.

Humans↗

PubMed2026

Development and clinical validation of a CRISPR/Cas9-engineered reporter phage cocktail for rapid detection of Escherichia coli in urine.

Urinary tract infections are one of the most common infectious diseases, with Escherichia coli as the predominant pathogen. Traditional diagnostic methods fail to meet clinical demands for rapid and specific detection. Here, we developed an efficient urine E. coli detection strategy via a reporter phage cocktail. Four reporter phages (T2::Nluc, T4::Nluc, T5::Nluc, T6::Nluc) were constructed by the CRISPR/Cas9 system combined with homologous recombination. One-step growth curves, optimal multiplicity of infection, and lytic efficiency showed that the Nluc gene block insertion exerted heterogeneous effects on phages. Luminescence assays demonstrated that all five reporter phages (including previously preserved T7::Nluc) and the cocktail offered favorable limits of detection (≥103 CFU/mL), high specificity, and no urine matrix interference. However, single phages exhibited limited coverage among 177 clinical E. coli isolates. But the reporter phage cocktail remedies this limitation. In large-scale clinical validation, the cocktail achieved sensitivity 73.15% (63.76%-81.22%), specificity 100.00% (99.53%-100.00%), positive predictive value (PPV) 100.00% (95.44%-100.00%), and negative predictive value (NPV) 96.42% (95.18%-97.36%) (all 95% confidence interval [CI]), and excellent concordance with the gold-standard method (Kappa = 0.83, 95% CI: 0.77-0.89), greatly outperforming single reporter phages (~40.00% sensitivity). This method requires no sample pretreatment, is simple to operate, and completes detection within 4 h, significantly improving diagnostic efficiency. Accordingly, it provides a novel platform for pathogen detection and supports the clinical translation of reporter phage diagnostics.IMPORTANCEUrinary tract infections impose substantial economic and public health burdens. In this study, we successfully constructed Escherichia coli-specific reporter phages T2::Nluc, T4::Nluc, T5::Nluc, and T6::Nluc. Combined with the previously preserved T7::Nluc, these phages formed a reporter phage cocktail. Co-cultivation of this cocktail with clinical samples enabled rapid and specific detection of E. coli in clinical urine, with a significantly shortened detection time (4 h) and good concordance with the gold-standard detection method (Kappa = 0.83), effectively improving detection efficiency and accuracy. This novel pathogen detection platform, integrating specific recognition and signal amplification, not only provides a new technical approach for the rapid and accurate diagnosis of clinical urinary tract infections but also effectively promotes the coordinated improvement of infectious disease diagnosis and treatment in terms of timeliness-precision-cost.

Escherichia coli↗

PubMed2026

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↗

PubMed2025

A clinically applicable method for early interstitial lung disease detection in incident rheumatoid arthritis cases: integration of protein biomarkers and clinical factors.

BACKGROUND: This study aimed to develop an early diagnostic method integrating proteomic biomarkers and clinical parameters for screening interstitial lung disease (ILD) in patients with newly diagnosed rheumatoid arthritis (RA) through a multi-phase research strategy. METHODS: A three-phase study was conducted: (1) Discovery: Tandem mass tag (TMT)-labeled quantitative proteomics with liquid chromatography-tandem mass spectrometry (LC-MS/MS) analyzed serum protein profiles in 5 RA-ILD and 5 RA-non-ILD patients, identifying candidates via bioinformatics. (2) Verification: Enzyme-linked immunosorbent assay (ELISA) validated candidates in an independent cohort (13 RA-ILD vs 14 RA-non-ILD). (3) Application: Biomarkers combined with clinical indicators (Krebs von den Lungen-6 [KL-6], age, sex) were evaluated in 110 patients (51 RA-ILD vs 59 RA-non-ILD) to build a predictive model. RESULTS: Proteomic analysis identified matrix metalloproteinase-3 (MMP3), von Willebrand factor (VWF), and other significantly differentially expressed proteins. ELISA validation confirmed that serum MMP3 and VWF levels were significantly higher in the RA-ILD group than in the RA-non-ILD group (p = 0.025 and 0.027, respectively). Expanded validation demonstrated superior diagnostic performance when combining MMP3 and VWF with KL-6 (area under the curve [AUC] = 0.90). The nomogram prediction model based on univariate analysis exhibited excellent discrimination (AUC = 0.89) and calibration. CONCLUSION: This systematic study from discovery to validation identified MMP3 and VWF as potential biomarkers for RA-ILD. The integrated predictive model combining these biomarkers with clinical parameters (KL-6, age, sex) provides a potential tool for early ILD screening in RA patients, offering novel strategies for early diagnosis and intervention of RA-ILD.

Humans↗

PubMed2026

From host response to genomic targets: electrochemical biosensing of tuberculosis biomarkers.

Tuberculosis (TB) remains one of the leading causes of death from a single infectious agent worldwide, with timely diagnosis continuing to be a major challenge, particularly in resource-limited settings. Conventional TB diagnostic methods are limited by low sensitivity, long turnaround times, and an inability to reliably differentiate latent from active disease. Biomarker-based diagnostic strategies have therefore gained increasing attention as they offer the potential to improve early detection, disease differentiation, and treatment monitoring. Herein, we examine electrochemical biosensing strategies for TB diagnostics using a biomarker-class-driven framework, covering host-response biomarkers (IFN-γ and TNF-α), pathogen-derived antigens (ESAT6, CFP10, CFP10-ESAT6, MPT64, Ag85, HspX and LpqH), cell-wall signatures and whole-cell markers (LAM and whole cell Mtb), and genomic markers (Mtb DNA and IS6110). Through structured comparison of recognition elements, biointerface designs, signal amplification strategies, electrochemical techniques, matrices, and validation levels, this review identifies the most promising technical approaches for different TB biomarker classes. It further highlights key translational bottlenecks, including limited clinical validation, buffer-based testing, complex multistep amplification, redox-probe dependence, matrix fouling, and insufficient evidence of manufacturability. This review therefore provides practical guidance for developing electrochemical TB biosensors that are analytically sensitive, clinically relevant, and suitable for decentralized diagnostic applications.

Biosensing Techniques↗

PubMed2026

Prevalence and risk factors of nutritional anaemia among adolescents in India: a systematic review with meta-analysis of prevalence.

BACKGROUND: Nutritional anaemia is a major public health concern among adolescents in India, threatening physical growth, cognitive development, and future maternal health. This systematic review with meta-analysis of prevalence aimed to estimate the pooled prevalence of nutritional anaemia among Indian adolescents aged 10-19 years and identify key associated risk factors. METHODS: A systematic search was conducted across PubMed, Embase, Web of Science, and Scopus up to February 2025. Data were extracted on study design, setting, diagnostic methods, prevalence, and risk factors. Quality was assessed with a modified Newcastle-Ottawa Scale. A random-effects meta-analysis estimated pooled prevalence, with subgroup analyses by state and gender, and pooled odds ratios for risk factors. RESULTS: Forty-five studies encompassing diverse Indian regions and 159,979 adolescents were included. The pooled prevalence of nutritional anaemia was 56% (95% CI: 49%-63%), with higher rates among girls (62%) than boys (39%). Iron deficiency (OR 2.38-4.68), other micronutrient deficiencies, low socioeconomic status, poor dietary diversity, female gender, and inadequate supplementation were consistently associated with higher anaemia risk. CONCLUSION: Nutritional anaemia impacts more than half of Indian adolescents, with notable regional and gender differences. Its complex nutritional, socioeconomic, and behavioural causes demand targeted, context-specific interventions to enhance adolescent health nationwide.

Humans↗

PubMed2026

HPV circulating tumor DNA as a potential prognostic and predictive biomarker in head and neck squamous cell carcinoma: a systematic review.

PURPOSE: Human papillomavirus circulating tumor DNA (HPVctDNA) has emerged as a promising prognostic biomarker in HPV-related head and neck squamous cell carcinoma (HNSCC). This systematic review aimed to synthesize current evidence on the diagnostic accuracy and prognostic value of HPVctDNA in HNSCC management. MATERIAL/METHODS: We systematically reviewed a PubMed-indexed database of studies published between January 2012 and September 2025. Eligible studies were assessed for design, primary tumor site and stage, treatment modality, HPVctDNA detection method, diagnostic accuracy (sensitivity and specificity), and reported clinical endpoints. Descriptive syntheses were performed; sensitivity and specificity were standardized to proportions and summarized as median values per group. RESULTS: A total of 60 studies, including 8,234 patients were analyzed, of which 41 (68.3%) focused exclusively on oropharyngeal squamous cell carcinoma (OPSCC) and 17 (28.3%) included mixed HPV-related HNSCC subsites and HPV-positive cancers of unknown primary. The median follow-up across the included studies was 23 months. Among the included studies, 19 were retrospective (31.7%) and 33 were prospective (55.0%), with a small proportion of cross-sectional and randomized clinical trials. Overall, 40 (66.7%) evaluated the role of HPVctDNA in a curative setting. Plasma was the most common sample type, analyzed in 55 studies (91.7%), while 5 studies also included saliva. Detection methods varied: 40 employed droplet digital PCR (ddPCR), 16 used quantitative PCR (qPCR) and 4 applied NGS-based assays. Most of these studies (38, 63.3%) evaluated the prognostic utility of HPVctDNA, while only 4 (6.7%) assessed HPVctDNA in a screening or diagnostic setting. Regarding diagnostic accuracy, the median sensitivity across evaluable studies was 91.1%, while the median specificity was 99.4%. In OPSCC-only cohorts, the median sensitivity and specificity were 89.4% and 99.4%, respectively. Dynamic changes in HPVctDNA levels during or after treatment were consistently associated with outcomes: clearance or sustained negativity correlated with higher response rates, improved progression-free survival and overall survival, while persistent positivity or increasing levels predicted disease progression and recurrence. CONCLUSIONS: HPVctDNA demonstrates high diagnostic and prognostic accuracy in HPV-related HNSCC, especially OPSCC, supporting its use for prognosis, treatment monitoring and early detection of recurrence. However, prospective interventional studies are still required to demonstrate that HPVctDNA-guided treatment decisions improve clinical outcomes before routine implementation.

Humans↗

PubMed2026

Toward the clinical application of long-read sequencing in repeat-expansion disorders.

Repeat-expansion disorders (REDs) are a mechanistically and clinically well-defined subgroup of rare diseases caused by the expansion of short tandem repeats (STRs). These expansions can exceed several kilobases and show complex features, such as noncanonical secondary structures, somatic instability, repeat interruptions and allele-specific methylation. These characteristics are highly relevant for understanding disease mechanisms, clinical variability, prognosis and potentially therapeutic decision-making, but cannot be fully resolved using traditional diagnostic methods or short-read sequencing technologies. By contrast, long-read sequencing (LRS) enables accurate investigation of STR complexity in a single assay, facilitates the discovery of new pathogenic repeat expansions and drives advances in diagnostics, clinical and basic research, which may allow for better patient stratification in future clinical trials. This Perspective discusses recent LRS-driven discoveries, methodological and bioinformatic advances, and emerging diagnostic applications to illustrate the potential of LRS in reshaping both research and clinical practice.

Humans↗

PubMed2026

Urinary Small Extracellular Vesicle DNA as a Biomarker for the Non-Invasive Diagnosis of Bladder Cancer.

Existing diagnostic technologies for bladder cancer (BC) suffer from low sensitivity, low specificity, or a lack of validation. Therefore, validated, non-invasive diagnostic biomarkers with high sensitivity and specificity for early detection of BC are needed to complement and improve upon the limitations of existing diagnostic methods. We used low-pass whole genome sequencing (LP-WGS) technology to detect copy number variations (CNVs) in small extracellular vesicle (sEV) DNA isolated from urine samples of patients. Based on these results, we constructed and validated a diagnostic model to differentiate between benign and malignant bladder lesions. We conducted a receiver operating characteristic analysis and calculated the area under the curve (AUC) to evaluate the performance of the diagnostic model. The urine sEV-DNA LP-WGS data revealed CNV differences between benign and malignant samples. The diagnostic model achieved an AUC of 0.953, a sensitivity of 86.7%, and a specificity of 100% in the training cohort and an AUC of 0.985, a sensitivity of 90%, and a specificity of 100% in the validation cohort. Even at the lowest coverage depth of 0.01X, the performance of the diagnostic model remained relatively robust. Notably, the performance of this diagnostic model surpassed that of the biomarker neuron-specific enolase (sensitivity: 85.7% vs. 64.3%; specificity: 100% vs. 87.5%) and urinary cytology (sensitivity: 100% vs. 66.7%; specificity: 100% vs. 94.1%). Our study demonstrates that urine sEV-DNA exhibits high discriminatory power in distinguishing between benign and malignant bladder lesions, making it a promising tool for auxiliary diagnosis of BC.

Humans↗