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PubMed2026

Aflatoxins and their biosynthetic precursors in lotus seeds: simultaneous UPLC-MS/MS determination, contamination profiling, and matrix-specific accumulation during Aspergillus flavus infection.

Aflatoxin (AF) contamination poses a severe global threat to food and medicinal material safety, yet existing research focuses on terminal AF metabolites while neglecting residual biosynthetic precursors, leading to potential underestimation of contamination risks. In this study, a UPLC-MS/MS method was established for the simultaneous quantification of six AFs and their five precursors in lotus seeds, with optimization of mass spectrum parameters, chromatographic separation conditions, and sample pretreatment. Method validation confirmed linearity (R2 > 0.99), LODs (0.03-0.36 μg/kg), and recoveries (76.53%-120.0%, RSD < 15%). Analysis of 41 natural lotus seed samples revealed a 63.4% AF contamination rate, dominated by B-group AFs, while O-methylsterigmatocystin (OMST) and versicolorin hemiacetal (VOH) were identified as the primary co-residual precursors with co-occurrence rates ≥ 50%. Notably, AFM1 was predominantly detected in natural samples with AFB1 concentrations exceeding 100 μg/kg. Artificial inoculation experiments further demonstrated that sterilization and sealing conditions modulated AF biosynthesis in lotus seeds, with non-sterilized and non-sealed groups showing delayed fungal metabolism and lower toxin accumulation. A significant linear correlation was observed between AFM1 and AFB1 levels (r = 0.94) in infected samples, demonstrating their accumulation levels are coupled with fungal overall metabolic flux. Given the high co-occurrence rate of OMST/VOH with AFB1 in natural samples, their individual and combined toxicities require in-depth investigation. This work deciphers matrix-specific AF dynamics in lotus seeds, supporting regulatory standard refinement (e.g., precursor inclusion) and targeted control (e.g., time-sensitive drying after harvest). Further studies will focus on exploring the molecular mechanisms of substrate-dependent AF synthesis.

Aflatoxins↗

PubMed2026

Sex- and age-specific associations of VEGFA polymorphisms with multiple sclerosis susceptibility.

AIM: To evaluate six VEGFA polymorphisms (rs1570360, rs699947, rs3025033, rs2146323, rs1413711 and rs833061) and serum VEGFA concentrations in 270 Lithuanian patients with multiple sclerosis (MS) and 270 matched healthy controls. METHODS: Genotyping was performed using real-time PCR, and serum VEGFA levels were measured by enzyme-linked immunosorbent assay. Statistical analyses were conducted using IBM SPSS version 31.0. RESULTS: Nominal differences in VEGFA genotype and allele distributions were observed in sex- and age-stratified analyses. Among females, the rs1413711 C allele was more frequent (p = 0.005), whereas the rs833061 C allele was less frequent (p = 0.006), in MS patients than controls. In participants aged >38 years, the rs1413711 C allele was also more frequent in MS cases (57.5% vs. 46.0%, p = 0.008). Logistic regression identified nominal associations, particularly for rs1413711, rs699947 and rs833061, but none remained significant after correction for multiple testing. Serum VEGFA levels were higher in MS patients than controls (p = 0.004). Nominal genotype-related differences in serum VEGFA levels and haplotype associations with reduced MS odds were also observed, but did not remain significant after multiple-testing correction. No consistent associations were found between VEGFA variants and clinical parameters. CONCLUSION: VEGFA genetic variation and elevated serum VEGFA may be associated with MS, but the genetic findings require confirmation in larger independent cohorts.

Humans↗

PubMed2026

Non-parametric differential methylation analysis characterizes histotype-specific promoter regions in epithelial ovarian cancer.

Epithelial ovarian cancer (EOC) is a heterogenous disease with frequent late-stage diagnosis and high mortality rates, for which no reliable screening tests exist. In recent years, epigenetic biomarkers in the form of DNA methylation in CpG-rich regions have gained increased attention in the scientific community due to their robust nature and accessibility, allowing for diagnosis without the need for invasive surgery. In this study, we investigated the aberrant methylation of promoter regions in early stage EOC through non-parametric methods, with the purpose of characterizing candidate epigenetic biomarkers. The approach was used on a cohort of early stage EOC samples, and results were compared to existing programs for differential methylation. Significant regions were then used to construct a CpG panel for stratifying EOC histotypes through predictive classification in external data. Identified promoter regions were highly reproducible across cohorts, and the constructed CpG model stratified histotypes in external cohorts through predictive classification. Comparisons against other DMP and DMR callers showed a degree of homogeneity between results but also revealed promoter regions that were overlooked despite clear signs of aberrant methylation. Finally, EOC histotypes were found to differ in their methylation distribution types, and results indicate that methods sensitive to non-normally distributed data may be poorly suited to compare groups with different distribution types. The non-parametric approach identified aberrantly methylated promoter regions that were highly reproducible across cohorts. Results from predictive classification indicate that these regions may be useful for the purpose of EOC histotype stratification.

Humans↗

PubMed2026

Longitudinal whole-genome analysis of bluetongue virus identifies conserved serotype-specific genomes and distinct genomic constellations within a Colorado sheep flock (2021-2023).

Bluetongue virus (BTV) is a segmented double-stranded RNA virus of ruminants transmitted by Culicoides spp. biting midges. Although the genome consists of ten segments, classification into serotypes is primarily based on genome segment 2. However, reassortment among genomic segments is a major driver of BTV evolution and diversity. This study used longitudinal whole-genome sequencing to characterize BTV genomes collected from 2021 to 2023 within a single sheep flock in Colorado, where multiple serotypes co-circulate. Whole-genome sequences were generated from fourteen blood samples representing four serotypes: BTV-6, -11, -13, and -17. Longitudinal sampling identified multiple BTV serotypes within individual sheep across consecutive years. Tanglegram analysis comparing segment phylogenies to the segment 2 tree demonstrated incongruent topologies across all genomic segments, suggestive of reassortment or the circulation of distinct genomic constellations. Nucleotide-level comparisons revealed high sequence homology among same-serotype samples from the same year, while the greatest genetic divergence was observed among BTV-17 genomes collected in different years. Additionally, all BTV-13 genomes contained a previously undescribed nonsynonymous substitution in segment 10 predicted to extend the encoded protein by three amino acids. Together, these findings demonstrate that highly conserved BTV genomes and distinct genomic constellations can be detected at the flock level across multiple years. This longitudinal whole-genome approach reveals the genetic complexity of endemic BTV populations, including novel variants and genomic patterns consistent with reassortment that are lost with conventional serotyped-based approaches, highlighting the need to integrate whole-genome characterization into endemic BTV monitoring programs.

Animals↗

PubMed2026

Evaluation of three Aspergillus antibody assays for screening of chronic pulmonary aspergillosis: prospective diagnostic accuracy study.

OBJECTIVES: Chronic pulmonary aspergillosis (CPA) is a frequent complication of pulmonary tuberculosis (PTB), particularly in high-burden settings where access to reliable serological diagnostics remains limited. We evaluated the diagnostic performance of two immunochromatographic technology (ICT) lateral flow assays (LFAs) and an ELISA for CPA screening among patients with active or previously treated PTB. METHODS: In this two-year prospective multicentre diagnostic evaluation, serum from adults with prior or active PTB was tested using the Era Biology Aspergillus IgG ICT LFA, LDBio Aspergillus IgG/IgM ICT LFA, and Bordier Aspergillus fumigatus IgG ELISA. CPA diagnosis was established using a consensus composite reference standard incorporating clinical, immunological, radiological, and microbiological criteria. The Bordier ELISA was used as part of the immunological component of the consensus CPA diagnosis, with a cutoff optical density of ≥1.0. Diagnostic accuracy, agreement statistics, receiver operating characteristic analysis, and latent class analysis (LCA) were performed. RESULTS: Among 340 participants, 24 (7.06%) had CPA. Proportion of participants with positive antibody tests among all tested individuals were 6.76% for LDBio ICT LFA, 20.0% for Era Biology ICT LFA, and 11.47% for Bordier ELISA. Against consensus CPA diagnosis, Bordier ELISA showed 87.50% sensitivity and 94.30% specificity, LDBio ICT LFA 58.33% sensitivity and 97.15% specificity, and Era Biology LFA 66.67% sensitivity and 83.54% specificity. LCA estimated CPA prevalence at 7.72%. LCA-derived sensitivities and specificities were 86.58% and 99.92% for LDBio ICT LFA, 83.39% and 85.31% for Era Biology LFA, and 79.10% and 94.19% for Bordier ELISA. CONCLUSIONS: The Bordier ELISA showed high sensitivity and specificity, while the LDBio ICT LFA demonstrated very high specificity with strong LCA-derived performance. These findings support the use of ELISA for laboratory diagnosis and ICT as a point-of-care screening tool for CPA in resource-limited settings. Era Biology Aspergillus IgG LFA demonstrated moderate sensitivity and acceptable diagnostic performance, indicating its potential utility as a supplementary screening assay for CPA in settings where rapid, point-of-care testing is required.

Humans↗

PubMed2026

Genomic characterization of a hypervirulent Aeromonas veronii NN0115 from Nile tilapia and head kidney transcriptome of infected fish reveals B-cell-dominated immune response with specific immunoglobulin downregulation.

Aeromonas veronii is a pathogen of multiple fish species, yet systematic understanding of its infection in Nile tilapia (Oreochromis niloticus) remains limited. A dominant strain, NN0115, was isolated from a natural outbreak and identified as A. veronii by 16S rRNA and whole-genome average nucleotide identity (ANI, 96.33%). Experimental infection revealed high virulence (LD50 = 3.41 × 106 CFU/mL, equivalent to 8.53 × 104 CFU/fish). The genome is 4.58 Mb (58.57% GC) and encodes 4216 proteins. Virulence factor analysis identified 1253 genes, dominated by motility-related (264) and immune modulation (208) factors. Genomic island GI2 harbors 7 virulence genes and two dual-function resistance-virulence genes. The strain is resistant to 9 of 25 agents tested but carries three RND efflux pump genes whose predicted resistance was not phenotypically observed. The head kidney transcriptome of tilapia at 24 h post-bacterial infection identified 773 differentially expressed genes; among them, 57 were immunoglobulin (Ig) genes, and 56 were down-regulated. Integration of published single-cell transcriptomic data showed that non-Ig B-cell marker genes were down-regulated by 32%, whereas Ig genes were reduced by 63%, indicating selective transcriptional suppression of Ig genes rather than a general decrease in B-cell transcriptional activity. Together, this study provides a comprehensive characterization of a highly virulent A. veronii from Nile tilapia and reveals that selective downregulation of B-cell Ig genes is the dominant transcriptional feature of the host head kidney response.

Animals↗

PubMed2026

Fatty acids and breast cancer: Epidemiology, subtype-specific metabolism, immune regulation, and clinical translation.

Fatty acids (FAs) are bioactive dietary and metabolic molecules that participate in membrane architecture, energy homeostasis, inflammatory signaling, gene regulation and immune function, all of which intersect with breast cancer (BC) risk, progression and treatment response. In this narrative review we integrate epidemiological, clinical, translational and mechanistic evidence on the role of FAs in BC. Saturated, monounsaturated, trans- and polyunsaturated FAs (PUFAs) are treated as distinct biological exposures rather than interchangeable measures of total fat intake. Similarly, evidence from dietary assessment, circulating biomarkers, erythrocyte membrane composition, adipose tissue stores and tumor lipid signatures is interpreted separately, because each captures exposure and biology at a different level. BC subtypes differ in FA synthesis, uptake, oxidation, storage and remodeling: luminal tumors are frequently linked to hormone-regulated lipogenesis, human epidermal growth factor receptor 2 (HER2)-positive tumors to growth-factor-driven lipid metabolism, and triple-negative tumors to exogenous FA uptake, inflammatory lipid mediators and ferroptosis-related vulnerabilities. FA-derived mediators also shape immune-cell polarization, cytokine signaling and the tumor microenvironment, and dietary FAs may reshape the gut microbiota; the fiber-derived short-chain FAs it produces, distinct from dietary FAs, likewise help regulate immune and inflammatory tone. Clinical data suggest possible roles for fat-quality modification and selected n-3 PUFA interventions, but findings are heterogeneous and not yet sufficient to support routine biomarker-guided precision onco-nutrition. Candidate biomarkers, such as erythrocyte n-6:n-3 composition, require prospective validation before clinical implementation. FA biology thus represents a modifiable but complex axis in BC prevention, tumor biology and supportive care.

Humans↗

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

Diagnostic and prognostic value of fibroblast growth factor 23 in acute kidney injury: systematic review and meta-analysis.

Background: Acute kidney injury (AKI) is associated with high mortality and adverse outcomes. Fibroblast growth factor 23 (FGF23) has emerged as a potential biomarker for AKI; however, its diagnostic and prognostic utility remains inconsistent.Methods: We conducted a systematic review and meta-analysis of studies evaluating circulating intact FGF23 (iFGF23) or C-terminal FGF23 (cFGF23) (PROSPERO: CRD42022302659). PubMed, EMBASE, CNKI, and Wanfang databases were searched through June 9, 2026. QUADAS-2 was used for quality assessment. A random-effects bivariate model pooled sensitivity, specificity, positive/negative likelihood ratio (PLR/NLR), diagnostic odds ratio (DOR), and area under the summary receiver operating characteristic curve (SROC AUC).Results: Twenty-three studies were included: 17 diagnostic, 6 prognostic (one addressing both). For AKI diagnosis, the pooled sensitivity was 0.79 (95% CI 0.73-0.86), specificity 0.82 (95% CI 0.75-0.89), PLR 4.40 (95% CI 2.59-6.21), NLR 0.25 (95% CI 0.16-0.34), DOR 17.49 (95% CI 8.67-35.16), and SROC AUC 0.87 (95% CI 0.81-0.92). Substantial heterogeneity was observed (I2 = 67%), with iFGF23 demonstrating higher accuracy than cFGF23 (AUC 0.91 vs 0.81). For AKI mortality, pooled sensitivity was 0.77 (95% CI 0.69-0.84), specificity 0.76 (95% CI 0.70-0.82), DOR 10.89 (95% CI 6.86-17.30), and SROC AUC 0.77 (95% CI 0.70-0.83). Significant heterogeneity was noted (I2 = 86.2% for sensitivity, 80.4% for specificity). No significant publication bias was detected.Conclusions: Circulating FGF23 exhibits moderate-to-high diagnostic and moderate prognostic performance in AKI, though interpretation is limited by substantial heterogeneity. It may serve as a complementary biomarker for risk stratification, pending further validation with standardized protocols.

Humans↗

PubMed2026

Diagnostic performance of machine learning models for malignant and non-malignant pleural effusion: Systematic review and meta-analysis.

BACKGROUND: Accurately distinguishing malignant pleural effusion (MPE) from non-malignant pleural effusion is clinically important, but the generalisability and methodological quality of machine-learning (ML) models remain uncertain. METHODS: We searched eight databases to 23 April 2026. Diagnostic performance was pooled using random-effects and Reitsma bivariate models, and study quality was assessed using PROBAST+AI. RESULTS: Forty-two studies were included; 17 contributed to the AUC meta-analysis and 14 to the bivariate analysis. The pooled AUC was 0.90 (95 % CI 0.85-0.94; 95 % prediction interval 0.62-0.98), with sensitivity of 0.80 (95 % CI 0.77-0.83) and specificity of 0.87 (95 % CI 0.79-0.92). Only nine studies reported external, temporal or independent validation. Externally validated studies had a lower pooled AUC than studies without external validation (0.83 vs 0.92), with lower specificity observed in the two externally validated studies contributing sensitivity and specificity data. All 42 development assessments had high overall quality concerns, and all 42 model evaluations were judged at high risk of bias. CONCLUSIONS: ML models showed good apparent accuracy for distinguishing MPE from non-MPE, but the evidence was limited by substantial heterogeneity, high risk of bias and scarce external validation. The pooled estimates reflect the average performance of different selected models rather than the expected accuracy of a single clinical test. ML models should be regarded as adjuncts to existing diagnostic pathways until they are confirmed by rigorous multicentre prospective external validation and clinical-impact studies.

Humans↗

PubMed2026

Can ChatGPT Replace Human Clinical Coders? A Comparative Study in Otology Billing.

OBJECTIVE: Evaluate the utility of the large language model (LLM), ChatGPT, for the analysis of operative notes and the generation of Current Procedural Terminology (CPT) codes in comparison to human clinical coders. STUDY DESIGN: CPT billing codes assigned by ChatGPT were compared to existing billing data. Otology practice within a tertiary academic center. METHODS: About 191 operative notes from a single surgeon (9/2022-10/2023) were analyzed. ChatGPT-3.5 and 4 models were prompted for CPT codes based on operative notes. Assessment included determining exact and partial match rates, sensitivity and specificity for targeted procedures, and work Relative Value Units (wRVU) differences between ChatGPT-generated and human-assigned codes. RESULTS: ChatGPT-3.5 achieved exact matches in 22% of cases and partial matches in 32%, while ChatGPT-4 achieved 14% exact and 33% partial matches. When cochlear implantation (CI) was excluded, performance dropped significantly. For CI, ChatGPT-3.5 demonstrated a sensitivity of 94% and specificity of 90%, while ChatGPT-4 showed a sensitivity of 96% and specificity of 92%. In contrast, performance on cartilage grafting was poor, with sensitivities of 4.2% for ChatGPT-3.5 and 0% for ChatGPT-4. ChatGPT-3.5 and 4 showed moderate CPT code matching accuracy among themselves, with slight agreement to human coders. Both models tended to underbill for wRVUs compared to human coders, with significant differences in the values generated. CONCLUSION: This study assessed ChatGPT's effectiveness in automating CPT code assignment for otologic surgeries. While the models achieved high sensitivity values for assigning codes related to cochlear implantation, both models struggled with complex cases, failed to apply modifiers, and often assigned fewer wRVUs. The findings highlight ChatGPT's potential in medical billing but indicate a need for further refinement.

Humans↗

PubMed2026

Tissue-derived extracellular matrix hydrogels instruct epigenetic adaptation in metastatic colonization.

The extracellular matrix (ECM) plays a central role in regulating tumor progression and metastatic colonization by providing biochemical and mechanical signals that shape cancer cell fate. However, most organoid culture systems rely on basement membrane extracts that fail to reproduce the tissue-specific extracellular environments encountered during metastasis. Here, we develop tissue-derived decellularized matrix hydrogels to reconstruct organ-specific microenvironments and investigate epigenetic adaptation to ECM cues during metastatic colonization. Patient-derived colorectal cancer organoids cultured in colon-derived matrices exhibited enhanced maintenance of stem-like phenotypes and colon-specific chromatin accessibility landscapes compared with cultures grown in basement membrane extracts, demonstrating improved physiological relevance for primary tumor modeling. When exposed to matrices derived from secondary organs, the organoids showed distinct growth phenotypes accompanied by rapid, tissue-dependent chromatin accessibility remodeling, indicating that ECM composition alone can reshape regulatory programs governing metastatic adaptation. Notably, liver-derived matrices selectively activated hepatocyte nuclear factor 4 alpha (HNF4A)-associated transcriptional networks and created a context-specific dependence on c-MET signaling for survival. Functional perturbation of HNF4A or c-MET signaling confirmed that both are required for organoid formation specifically within the liver matrix environment. Together, these findings establish tissue-derived matrix hydrogels as instructive bioactive materials that actively regulate cancer cell epigenetic states and reveal microenvironment-specific therapeutic vulnerabilities during early metastatic colonization.

Journal Article↗

PubMed2026

A mechanism-guided framework for prioritizing membrane-interaction anti-Vibrio peptides from peptidomics data.

A mechanism-guided framework for prioritizing membrane-interaction antimicrobial peptide candidates from proteomics-derived peptide mixtures is presented. The framework integrates conservative machine-learning-based antimicrobial peptide (AMP) screening with a literature-derived membrane-interaction plausibility (MAP) assessment and a data-driven membrane-interaction ranking function (AIPx), followed by structural visualization for interpretability. MAP encodes physicochemical characteristics commonly associated with peptide-membrane interaction and provides a graded plausibility assessment. Building upon this physicochemically interpretable framework, AIPx ranks peptides using feature weights calibrated from experimentally characterized anti-Vibrio peptides, where minimum inhibitory concentration (MIC) values are used as a coarse-grained ranking reference rather than a direct prediction target. In a peptidomics-based peptide fractionation study targeting Vibrio spp., AIPx exhibited a consistent relationship with experimentally observed antibacterial activity. Distributional analysis revealed that peptide fractions exhibiting high anti-Vibrio activity are characterized by enrichment of high-ranking peptides rather than by AMP abundance alone. By structuring AMP identification and prioritization as sequential stages, the MAP + AIPx framework enables interpretable and experimentally actionable candidate selection by reducing biologically implausible candidates. The framework facilitates species-oriented prioritization of AMP candidates, addressing a key challenge in antimicrobial peptide discovery where activity may depend on target-specific membrane characteristics. Moreover, the approach is extensible through species-specific calibration and supports interpretable, mechanism-informed prioritization in antimicrobial peptide discovery.

Proteomics↗

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

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 (χ), 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 = 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 χ in the putamen and globus pallidus effectively distinguishes multiple system atrophy and progressive supranuclear palsy from idiopathic PD. Distinctively, AD and ALS exhibit specific χ 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↗

PubMed2026

Divergent evolutionary strategies in spider venoms: A comparative proteomic profiling of four sympatric species from Yunnan.

Spider venoms comprise complex cocktails of bioactive molecules evolved for predation and defense, representing a valuable resource for biological research and pharmaceutical discovery. In this study, we performed a systematic analysis of venom gland extracts from four common spider species indigenous to Yunnan, China: Agelena limbata, Hippasa lycosina, Lycosa grahami, and Sinopoda pengi. Using an integrated transcriptomic and proteomic targeted profiling approach, we successfully annotated 141 distinct toxins. Comparative analysis revealed significant interspecific heterogeneity, suggesting distinct evolutionary trajectories and "weapon system economics." Both A. limbata and L. grahami exhibited a "peptide-dominant" profile anchored by neurotoxic peptides and isomerases, optimized for rapid chemical paralysis. In contrast, S. pengi displayed a distinct "protein-dominant" signature enriched with high-molecular-weight enzymes and CAP superfamily proteins, likely functioning to facilitate tissue degradation and toxin diffusion. Occupying an intermediate position, H. lycosina demonstrated a hybrid composition. These findings suggest that although these species share the same geographical range, their venom systems have undergone divergent evolutionary adaptations driven by specific ecological niches and hunting strategies. This study represents the first systematic proteomic characterization of these venom components, providing a valuable reservoir of molecular candidates while highlighting the bioinformatic nuances of analyzing whole-gland homogenates.

Animals↗

PubMed2026

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↗

PubMed2026

Enhancing Hemoglobin Bart's hydrops fetalis syndrome prevention: a single-tube multiplex real-time PCR assay for the comprehensive detection of four significant α0-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 α0 -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 α0-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 α+-thalassemia. The assay demonstrated a high analytical sensitivity with a LOD of 9.76 × 10-3 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 α0-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↗