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PubMed2026

MET-Aberrant non-small cell lung cancer: from kinase dependence to cell-surface targetability-mechanistic basis and biomarker framework for bispecific antibodies and antibody-drug conjugates.

MET-aberrant non-small cell lung cancer (NSCLC) is not a uniform therapeutic entity. Its biology, diagnostic pathways, and treatment sensitivity differ across MET exon 14 skipping alteration (METex14), MET amplification, and MET overexpression. This heterogeneity cannot be fully explained by conventional event-based classification and is reflected in the distinct clinical activity of MET tyrosine kinase inhibitors (MET-TKIs), bispecific antibodies (BsAbs), and antibody-drug conjugates (ADCs). With the emergence of antibody-based therapies, MET has evolved from a signaling driver to a cell-surface target for receptor modulation and payload delivery. We therefore propose a clinically anchored two-dimensional framework for interpreting therapeutic relevance in MET-aberrant NSCLC: kinase dependence and cell-surface targetability. Neither dimension should be regarded as a directly measurable binary variable. Kinase dependence is inferred from genomic and treatment-contextual proxies, most strongly METex14 and, more conditionally, high-level focal MET amplification. Cell-surface targetability is approximated by drug-specific IHC assessment of assay-defined c-MET protein expression; however, receptor internalization, intracellular trafficking, and payload delivery capacity remain incompletely measurable in routine clinical practice. Within this framework, MET-TKIs have the most evidence-supported established role in tumors with evidence of MET-driven kinase dependence. EGFR × MET BsAbs have demonstrated clinical activity in broad post-osimertinib EGFR-mutant NSCLC, while EGFR/MET co-dependence or MET-mediated bypass activation provides a mechanistic rationale for their use; MET-defined preferential benefit remains to be prospectively established. MET-directed antibody-drug conjugates (MET-ADCs) are supported in drug- and assay-defined populations with high c-MET protein overexpression, although the predictive relevance of delivery-related factors remains hypothesis-generating. Accordingly, MET testing should shift from single-event detection to platform-oriented stratification: next-generation sequencing (NGS) for driver alterations and resistance profiles, fluorescence in situ hybridization (FISH) for high-level focal amplification, and immunohistochemistry (IHC) for surface expression relevant to antibody-based therapies. This framework is intended to organize current biological and clinical evidence rather than to replace drug-specific companion diagnostics, regulatory indications, or prospectively validated treatment-selection algorithms. Precision treatment of MET-aberrant NSCLC is thus moving from event-based drug selection toward mechanism-based therapeutic matching. Future priorities include standardizing biomarkers, defining optimal target populations, and aligning biological subtypes, diagnostic strategies, and therapeutic platforms.

Antibody-drug conjugate↗
PubMed2026

Mortality of Individuals With PRNP Variants Associated With Prion Disease in the United States, 1998-2024.

BACKGROUND AND OBJECTIVES: To characterize the survival of individuals with pathogenic PRNP variants-including to estimate annual hazards, to judge the accuracy of previously reported survival data, and to evaluate the utility of public record searches in determining vital status. METHODS: In this single-center cohort study, we gathered data on individuals who received positive antemortem PRNP genetic tests at the US National Prion Disease Pathology Surveillance Center (NPDPSC), including both diagnostic tests in symptomatic individuals, and predictive tests in asymptomatic individuals. Genetic test and autopsy results were queried from the NPDPSC database, and public record searches were conducted using online tools. RESULTS: Four hundred four individuals received positive genetic test results. Of 206 cases symptomatic at the time of genetic testing, 188 are likely now deceased based on typical disease duration for their genetic variants. Combined autopsy and public record searches in combination confirmed 174 of these deaths, for an estimated 92.6% sensitivity. We evaluated the age-dependent penetrance of the reportedly highly penetrance variants D178N and E200K and the reportedly low-penetrance variant V210I. Among 99 initially asymptomatic individuals with the pathogenic E200K variant, more than 936 person-years of follow-up, 18 deaths were observed, significantly fewer than 27.4 expected according to life tables based on retrospective data. The age-dependent penetrance of E200K calculated from these longitudinal data was significantly lower than that from retrospective data, with 69% penetrance by age 80 and a median age at death of 75. For the pathogenic D178N variant, the median age at death was 57, which was numerically later, but not significantly different from, that seen in retrospective data. For V210I, just 2 deaths occurred, both after age 90, consistent with minimal penetrance. DISCUSSION: Our data support high penetrance of PRNP D178N and E200K variants and low penetrance of V210I. For E200K, the age at onset distribution appears to be shifted slightly later, and lifetime risk slightly lower, than previously reported. Autopsy data and public death records in combination were sensitive and concordant for determining long-term outcomes, but additional prospective data should be gathered to support future preventive trials.

Journal Article↗
PubMed2026

ADAM10's combined influence on the diagnostic usefulness of IL 22, IL 10, IL-17 A, and IL-17D in autism spectrum disorders: Predicted role on gut leakiness as co-morbidity.

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder with increasing global prevalence but a lack of reliable diagnostic biomarkers. Emerging evidence suggests that immune dysregulation, gut-brain axis dysfunction, and increased intestinal permeability play key roles in ASD pathophysiology. This study investigated the combined diagnostic value of ADAM10 and cytokines (IL-10, IL-22, IL-17 A, and IL-17D). Multivariable logistic regression produces an improved ROC curve that improves diagnostic accuracy over individual markers by combining numerous predictors into a single risk score (linear predictor). The technique, which frequently raises individual marker AUCs, entails modelling a binary result, calculating the probability, and visualizing ROC based on the projected probabilities. In this case-control study, plasma levels of ADAM10, IL-10, IL-22, IL-17 A, and IL-17D were measured in 37 male children with ASD and 37 age-matched controls. Group comparisons, correlation analyses, and receiver operating characteristic (ROC) curve analyses, including combined ROC models, were performed. ADAM10, IL-22, and IL-17 A levels were significantly reduced in children with ASD compared to controls, whereas IL-10 and IL-17D showed no significant differences. ADAM10, IL-17 A, and IL-22 demonstrated good diagnostic performance, with AUC values of 0.886, 0.855, and 0.812, respectively. In contrast, IL-10 and IL-17D showed poor discriminatory ability, with AUC values of 0.524 and 0.599, respectively. Combined ROC analysis markedly improved diagnostic accuracy, with all panels including ADAM10 achieving AUC values above 0.90, and some reaching as high as 0.988, with high sensitivity and specificity. The combination of ADAM10 with selected cytokines significantly enhances diagnostic performance compared to individual markers, supporting a link between immune dysregulation, barrier dysfunction, and gut permeability in ASD.

Humans↗
PubMed2026

Future promise, current clinical ambiguity: a systematic review of machine learning algorithm outputs predicting risk of cardiovascular disease.

OBJECTIVE: To examine whether the outputs of machine learning algorithms designed to predict risk of cardiovascular disease (CVD) address known deficiencies of the Framingham Risk Score (FRS) and improve risk estimates. METHODS: For this critical review, Medline, Embase and IEEE were searched from inception to 1 January 2025. Included were studies describing machine learning algorithms designed to specifically compare output of cardiovascular risk assessment with the FRS. Commentaries, letters, unpublished work or non-peer-reviewed papers were excluded.Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, two reviewers screened titles and abstracts independently, then populated a purpose-built data extraction form. A subsequent qualitative thematic analysis focused on algorithms' strengths, added value, potential harms, unintended consequences and equity implications.The main outcome assessed was whether, among healthy adults, the algorithm improved CVD risk prediction relative to the FRS. RESULTS: Of 707 studies retrieved, 29 met inclusion criteria. 23 reported improved predictive ability relative to the FRS. Most datasets and/or medical records used included sociodemographic predictors of CVD not included among FRS inputs. Some added costly diagnostic tests like CT angiography to FRS screening indicators. When they were defined, inputs and outcomes such as hypertension or myocardial infarction did not always adhere to FRS values. Statistical significance was generally taken as a proxy for clinical significance. Some algorithms overestimated the number at risk compared with the FRS without discussing whether that larger proportion might be at risk of overdiagnosis rather than CVD, while a few decreased the proportion found to be at risk. CONCLUSIONS: Use of artificial intelligence to improve accuracy of risk assessment for CVD demonstrates the technological capacity to merge known sociodemographic predictors with biologic variables and examine non-linear interactions among these. Still needed to achieve patient benefit is clinical insight, adherence to screening principles and cost-benefit assessment of inputs selected.

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↗
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

Methylation profiling in CNS tumor diagnostics: a single-centre real-world experience from Central Europe.

Genome-wide DNA methylation profiling has transformed neuro-oncology by providing an objective, machine learning-based taxonomy that mitigates interobserver variability and refines the histo-molecular criteria of the current WHO classification. We evaluate the real-world diagnostic performance and clinical utility of this modality in a prospective, consecutively accrued three-year cohort of 291 central nervous system (CNS) tumors across a mixed adult-pediatric population. Successful profiling was completed in 95.9% of cases. Using the Epignostix classifier, a high-confidence diagnostic match (calibrated score [CS]&#x2009;&#x2265;&#x2009;0.84) was achieved in 70.3% of analyzable samples, while 26.5% returned lower-confidence scores (&#x2265;&#x2009;0.3 to <&#x2009;0.84) and only 3.2% remained completely unclassifiable (CS&#x2009;<&#x2009;0.3). When integrated into a comprehensive diagnostic framework, methylation profiling provided clinically useful results in 81.1% of cases, establishing diagnoses in 70 cases submitted for molecular subclassification and resolving diagnostic uncertainty or prompting major revisions in 149 histologically challenging tumors. Within truly ambiguous lesions, integration of methylome data dictated tumor grade modifications in 38.8% of cases (upgrading in 29.4% and downgrading in 9.4%), shifting patient risk stratification. Crucially, over half (52.7%) of the lower-confidence cases yielded meaningful clinical integration when supported by histomorphology and ancillary genetic or immunohistochemical markers, demonstrating that rigid score cutoffs should not dictate assay failure. Discrepant or misleading classifications occurred in 1.9%. Updating bioinformatic pipelines from version 11b4 to 12.8 rescued multiple ambiguous entries, increasing overall clinical utility to 84.1%. These findings demonstrate that integrating computational epigenomics with classical neuropathology enhances diagnostic precision, while highlighting the ongoing need for careful clinical-pathological correlation.

Central nervous system tumors↗
PubMed2026

Current Diagnostic Pathways for Rheumatoid Arthritis-Associated Interstitial Lung Disease Result in Substantial Underdiagnosis and Excess Mortality: A Multicenter Norwegian Quality Assurance Audit.

OBJECTIVE: Recent guidelines suggest risk-stratified screening for rheumatoid arthritis-associated interstitial lung disease (RA-ILD). However, the diagnostic gap between current routine care and this screening approach remains unquantified. We assessed currently detected RA-ILD in Norway, benchmarking findings against recent screening-based estimates of the true disease burden. METHODS: This 10-year quality assurance audit across six centers covered 43% of the Norwegian population. RA-ILD cases identified via ICD-10 codes were confirmed by manual chart review. Prevalence was calculated relative to a registry-derived total RA background population and benchmarked against a 10% expected target derived from recent prospective studies. Mortality was compared to a 3:1 frequency-matched RA control group using Cox proportional hazards regression. RESULTS: Among 17,305 RA patients, 188 (1.1%) had verified ILD; when benchmarked against an expected 10% prevalence, this indicates an 89% diagnostic gap in routine clinical care. Mean age at ILD detection was 67.5 years. Most cases (93.6%) possessed &#x2265;2 established risk factors for RA-ILD: 93.6% were seropositive, 76.1% had smoking histories, while RA onset age &#x2265;60 and persistently increased inflammatory laboratory markers were present in over half of patients. RA-ILD was associated with significantly increased mortality; 66 (4.1/100 person-years) deaths occurred in the RA-ILD group vs. 120 (2.3/100 person-years) among RA controls (HR 1.77; 95% CI: 1.31-2.39, p<0.001). CONCLUSION: When comparing to prevalence expectations, current routine care may leave a substantial proportion of cases undetected, primarily capturing a high-risk phenotype with excess mortality. Systematic, risk-stratified screening is needed to bridge this diagnostic gap, aiming to enable earlier intervention.

Interstitial lung disease↗
PubMed2026

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

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

Humans↗
PubMed2026

An Overview of Red Breast Syndrome: A Qualitative Systematic Review of the Literature and a Single-Center Case Series.

Red breast syndrome (RBS) is an uncommon inflammatory complication that may occur following implant-based breast reconstruction and can clinically mimic surgical-site infection. This qualitative systematic review, based on comprehensive PubMed and Scopus searches, summarizes the existing literature on RBS, focusing on its etiology, clinical presentation, diagnostic characteristics, and therapeutic approaches following breast reconstruction using acellular dermal matrices (ADMs). A management protocol is proposed based on available data, and a single-center case series is presented from our Hospital, including patients who developed RBS after direct-to-implant reconstruction with ADM between January 2022 and December 2024. Twenty-nine studies met the inclusion criteria, comprising case reports, case series, and retrospective or prospective cohort studies. The reported incidence of RBS ranged from 0% to 29.6%. Proposed etiologies include endotoxin contamination, residual cellular debris, delayed hypersensitivity reactions, and lymphatic or vascular impairment of mastectomy flaps. Most reports described localized erythema confined to the area of the ADM, with normal inflammatory markers and negative imaging findings, whereas antibiotic therapy frequently failed to achieve improvement. Corticosteroids represented the most consistently effective treatment, although some cases required ADM removal or replacement. In our institutional case series (n = 8), symptom onset occurred between 4 weeks and 7 months postsurgery. Inflammatory markers remained within normal limits, imaging rarely demonstrated fluid collections, and symptoms resolved within days to weeks with corticosteroid therapy or conservative management. This review consolidates current evidence, proposes a diagnostic-therapeutic algorithm and highlights the need for prospective investigations and manufacturer-level endotoxin testing to elucidate pathogenesis and optimize clinical management. Level of Evidence: 2 (Risk) For image description, please refer to the figure legend and surrounding text.

Humans↗
PubMed2026

Development of a new recombineering system for Edwardsiella species.

Edwardsiella species are important aquaculture pathogens that also cause opportunistic infections in humans, necessitating efficient genome editing tools to study their pathogenesis and develop control strategies. In this study, we identified and characterized six endogenous recombinases pairs from Edwardsiella and its phages. Among these, the BAS_MS17 system exhibited the highest recombination efficiency in E. piscicida EIB202&#x394;p. Extending homology arms from 150 bp to 200 bp improved editing efficiency by 2-fold, while the addition of Redg or Plug further enhanced recombination by 3-fold and 2.5-fold, respectively, without compromising accuracy (100%). More importantly, when applied to E. piscicida sdu12S, Redg or Plug improved the editing efficiency by 8-fold and 7-fold, respectively. Deletion of the phage-derived single-strand binding protein (SSB) reduced efficiency to 25% of the BAS_MS17 level, whereas expression of the endogenous RecA-family SSB (rSSB) increased recombinant yield by 5-fold, highlighting functional conservation. Furthermore, SSB proteins from heterologous hosts failed to enhance recombination efficiency. Using the optimized system, we successfully knocked out ten distinct genes, including virulence-associated loci, with editing accuracy exceeding 85%. Phenotypic analysis revealed that luxR, but not the other tested genes, contributes to biofilm formation. Virulence evaluation results showed that aroA, fur, and hfq are critical virulence-associated factors. Collectively, this streamlined recombineering system provides a simple, rapid, and efficient genetic tool for Edwardsiella, supporting mechanistic studies of virulence and the development of live attenuated vaccine candidates.

Edwardsiella piscicida↗
PubMed2026

Ultrastructural Insights Into the Reproductive Anatomy and Eggs of Cotton Pink Bollworm, Pectinophora gossypiella Saunders (Lepidoptera: Gelechiidae).

The pink bollworm, Pectinophora gossypiella Saunders is a major pest of cotton, notorious for its high reproductive potential and rapid evolution of resistance to Bacillus thuringiensis (Bt) toxins. Despite its economic significance, detailed knowledge of its reproductive anatomy and egg ultrastructure has remained limited, constraining the development of advanced molecular control strategies such as CRISPR/Cas9-based genome editing. The present study provides the first comprehensive characterization of the reproductive system and egg surface morphology of P. gossypiella using stereomicroscopy and scanning electron microscopy (SEM) techniques. The male reproductive system consists of fused, bean-shaped testes, seminal vesicles, duplex and simplex ejaculatory ducts, and paired accessory glands. The female reproductive system comprises paired ovaries with four polytrophic ovarioles per ovary, lateral and common oviducts, accessory glands, corpus bursae, and spermathecal glands. Eggs are oval, dorsoventrally flattened, exhibit a reticulated chorion with distinct micropylar and aeropylar regions. SEM images revealed 6-9 rosette cells encircling a circular micropylar plate, 14-19 first order and 17-23&#x2009;s order ribs, and 250-291 polygonal surface cells. The structural features of P. gossypiella eggs reveal key sites for sperm entry, aeropylar respiration, and candidate zones for microinjection in gene editing applications. These findings establish a morphological baseline critical for optimizing embryo manipulation and ribonucleoprotein (RNP) delivery in lepidopteran genome editing. This study represents a pioneering effort to integrate classical egg morphology with molecular entomology, thereby advancing precision genetic interventions aimed at resistance management and population suppression in P. gossypiella.

Animals↗
PubMed2026

Unraveling a Diagnostic Enigma: A TECPR2 Case Solved Through Multi-Omic Genomics.

TECPR2 is a key regulator of autophagy, encoded by the TECPR2 gene. Pathogenic variants in this gene have been linked to a rare hereditary sensory and autonomic neuropathy with intellectual disability (HSAN9). We report a teenage female with a syndromic intellectual disability disorder associated with neuromuscular abnormalities. Multi-omics analysis including genomics, transcriptomics, and proteomics, together with muscle biopsy from the affected individual, were used in this clinical case. Through trio exome sequencing we identified two heterozygous variants in the TECPR2 gene, NM_014844.4: c.480G>A; p.(Gln160=) and c.2846C>A; p.(Ala949Glu). Both were classified as variants of uncertain significance due to the lack of supporting evidence for pathogenicity. Subsequent long-read sequencing phased the variants and confirmed they were in trans. Additional functional studies using RNAseq and proteomics analyses verified the pathogenicity of the variants. This case study demonstrated the value of a multi-omics assisted analysis, which complemented the traditional phenotype-first approach in reaching a definitive clinical diagnosis.

Humans↗
PubMed2026

Diagnostic performance of panfungal PCR on tissue specimens for the diagnosis of invasive fungal diseases: a systematic review and meta-analysis of the Fungal PCR Initiative (FPCRI).

UNLABELLED: Invasive fungal diseases are difficult to diagnose because of the limited sensitivity of culture. Panfungal PCR amplicon sequencing assays (targeting ribosomal RNA, such as 18S, 28S, ITS) are recommended for fungal identification in histopathology samples showing fungal elements. However, data describing its overall performance and consistency are lacking. This systematic literature review and meta-analysis assessed the performance of panfungal PCR on formalin-fixed paraffin-embedded (FFPE) and non-fixed (fresh or frozen) tissue samples. A systematic literature search was performed to include studies reporting the use of panfungal PCR for fungal identification in FFPE or non-fixed tissue samples. PCR sensitivity and specificity were assessed using the reference standard of histopathology showing fungal elements. Quality assessment was performed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Pooled estimates were obtained using random-effects meta-analysis. Twenty-eight studies were included. In FFPE samples (18 studies, 852 samples), sensitivity and specificity were 75.4% (95% confidence interval [CI], 59.2-86.6) and 93.5% (70.2-98.9), respectively. Sensitivity in non-fixed samples (13 studies, 207 samples) was 86.5% (74.7-93.3), while specificity could not be assessed (insufficient data). Comparative analyses showed a significantly higher sensitivity of panfungal PCR over culture (88.2%; 76-94.7 vs 52.2%; 39-65, P = 0.001). Sub-analyses could not demonstrate the superiority of one PCR target over another due to limited data. Panfungal PCR exhibited adequate sensitivity and good specificity in FFPE samples. Sensitivity was even higher in non-fixed samples and largely superior to culture. Nevertheless, large interstudy variability was observed, warranting interlaboratory studies to define the optimal PCR target and standardized protocols. IMPORTANCE: Invasive fungal diseases are difficult to diagnose because of the low sensitivity of culture. Panfungal PCRs are widely used for fungal identification in tissue specimens but suffer from heterogeneous procedures and performance. This meta-analysis shows an acceptable sensitivity (75.4% and 86.5% in fixed and non-fixed samples, respectively) and good specificity (93.5%) of panfungal PCR, supporting its use, not only on histopathology-positive fixed samples but also in non-fixed samples concomitantly with other diagnostic tools (cultures and fungal-specific PCRs if available). These results provide a strong basis for further standardization of panfungal PCR techniques via interlaboratory assays to assess reproducibility and optimize analytical protocols. CLINICAL TRIALS: This study is registered with PROSPERO as CRD42023461148.

Humans↗
PubMed2026

Diagnostic Value and Limitations of Dermoscopy in Humans and Animals: A Critical Comparative Analysis.

BACKGROUND: Dermoscopy is a noninvasive imaging technique that is well-established in human dermatology, where it enhances the diagnosis of neoplastic, inflammatory, infectious, and alopecic skin disorders. In veterinary dermatology, its use is expanding yet remains heterogeneous and largely descriptive, despite growing evidence of conserved dermoscopic patterns across species. HYPOTHESIS/OBJECTIVES: To review the applications of dermoscopy in veterinary dermatology, and to provide a comparative analysis of dermoscopic features observed in dogs, cats, and horses in relation to corresponding findings in human dermatology. MATERIALS AND METHODS: A systematic review of the literature reporting dermoscopic findings in veterinary dermatology was conducted in accordance with PRISMA guidelines. PubMed, Scopus and Google Scholar were searched for studies published up to 30 July 2025. Eligible studies included original articles describing dermoscopic features in dogs, cats, or horses. Extracted data included species, dermatological condition, dermoscopic findings, device type and histopathological correlation, when available. Levels of evidence were assessed using the Oxford Centre for Evidence-Based Medicine criteria. RESULTS: Thirty studies met the inclusion criteria. Most were descriptive case reports or case series. Dermoscopy was applied to a wide range of conditions, including alopecias, parasitic infestations, dermatophytosis, neoplastic and sebaceous lesions, inflammatory dermatoses, and congenital vascular anomalies. Recurrent dermoscopic features showed strong similarities to those described in human dermatology, although species-specific anatomical differences influenced interpretation. CONCLUSIONS: Dermoscopy represents a valuable adjunct diagnostic tool in veterinary dermatology, with clear translational relevance. Standardisation of terminology and further prospective studies are required to support its broader clinical integration.

Animals↗
PubMed2026

Prenatal exome sequencing of fetuses with central nervous system anomalies based on prenatal ultrasound and magnetic resonance imaging diagnosis: A retrospective cohort study with a systematic review and meta-analysis.

INTRODUCTION: Fetal central nervous system (CNS) abnormalities have diverse etiologies, with genetic factors as a major contributor. Prenatal exome sequencing (ES) is a powerful tool for precise molecular diagnosis of CNS anomalies, but its diagnostic yield varies among studies. This study aimed to evaluate the additional diagnostic yield of prenatal ES compared with chromosomal microarray analysis (CMA) in fetuses with CNS anomalies detected by prenatal imaging. MATERIAL AND METHODS: We collected ES results from fetuses diagnosed with CNS anomalies by prenatal imaging (2019-2024) who had negative results. Subgroup analyses assessed phenotype-specific ES diagnostic yield for associated genes and variants. A systematic review and meta-analysis incorporating our data and published studies further explored the association between phenotype and diagnostic yield. RESULTS: In the cohort study of 219 cases, ES identified pathogenic/likely pathogenic single nucleotide variations in 36 cases (16%). The highest diagnostic yield of ES was in cases with multisystem malformations (25%, 14/55), followed by multiple CNS anomalies (15%, 2/13) and isolated CNS anomalies (13%, 20/151). The most commonly identified isolated CNS anomaly was agenesis of the corpus callosum (31%, 5/16). Neural tube defects with urogenital anomalies were associated with a positive ES finding in 57% (4/7) of cases. The meta-analysis of 989 cases from 22 studies showed a pooled diagnostic yield of ES of 27% (95% CI, 21%-34%). The highest diagnostic yield of ES was in cases of corpus callosum anomalies with facial abnormalities (75%, 8/11) and neural tube defects with urogenital malformations (80%, 12/15). The diagnostic yield of ES for three or more CNS abnormalities was 43% (95% CI, 31%-58%), significantly higher than that for only two abnormalities (10%, 95% CI, 4%-18%). No significant difference in diagnostic yield was found between cases identified by prenatal MRI combined with ultrasound (27%, 95% CI, 20%-36%) and those identified by ultrasound alone (25%, 95% CI, 17%-35%). CONCLUSIONS: ES provided a significantly higher diagnostic yield than CMA for fetal CNS abnormalities, with diagnostic yields varying by phenotype. The systematic review and meta-analysis confirmed that the complexity and combination of malformations are key factors associated with differences in ES diagnostic yield.

Humans↗
PubMed2026

A narrative systematic review of definitions and diagnostic criteria for disordered eating and eating disorders in type 1 diabetes.

AIMS/HYPOTHESIS: Type 1 diabetes and disordered eating (T1DE) affects 8-37.1% of adults and is associated with high rates of morbidity and mortality. The absence of a standardised case definition of T1DE and its severity hinders effective screening, diagnosis and treatment. This systematic review aimed to (1) synthesise existing case definitions and diagnostic criteria for T1DE in adults and (2) identify key characteristics to inform consensus for future diagnostic criteria. METHODS: A systematic review was conducted following the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) guidelines. Eligible studies involved adults (&#x2265;18 years) with type 1 diabetes assessing disordered eating; paediatric studies, mixed samples without disaggregated data, non-empirical designs and non-English publications were excluded. PubMed, MEDLINE, EMBASE, CINAHL and PsycINFO were searched up to November 2025 for peer-reviewed studies involving adults with T1DE. Qualitative and quantitative data on definitions, diagnostic criteria and assessment tools were extracted. Study quality was appraised using a modified Graphical Appraisal Tool for Epidemiological studies (GATE) checklist. Due to heterogeneity of data, a narrative synthesis of findings was performed to describe current definitions of T1DE. RESULTS: Sixty-one studies met the inclusion criteria, with a pooled sample of 111,208 participants (76% women) from over 22 countries. T1DE was defined using a heterogeneous array of terms, diagnostic frameworks and assessment tools (29 distinct methods). The Diabetes Eating Problem Survey-Revised (DEPS-R) was the most used questionnaire, but many studies relied on criteria adapted from general eating disorder classifications or generic questionnaires. Approximately three-quarters of the studies assessed insulin omission behaviours, but the operationalisation of the cognitions for insulin omission varied widely. Beyond physiological markers such as HbA1c and BMI, studies explored various diabetes-related and psychological constructs, although often considering diabetes and disordered eating separately rather than as an integrated condition. CONCLUSIONS/INTERPRETATION: This systematic review highlights the lack of a unified, evidence-based definition of T1DE, resulting in inconsistent screening, diagnostic and reporting practices. Establishing clear, consistent, evidence-based diagnostic criteria and screening questionnaires for T1DE is critical to improving early detection and developing targeted interventions. These findings provide a foundation for refining T1DE definitions as a stepping stone to an international consensus definition. STUDY REGISTRATION: PROSPERO registration no. CRD420250223622 FUNDING: King's College London and King's College Hospital through the KMRT KCH Joint Research Committee studentship. This work was also conducted as part of the National Institute for Health Research (NIHR; CS-2017-17-023)-funded STEADY project (Safe management of people with Type 1 diabetes and EAting Disorders studY). NZ's salary was part-funded by the NIHR via the NIHR Clinician Scientist award to MS; JT and KI are part-funded by the NIHR Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London. MS was funded through her NIHR Clinician Scientist Fellowship (CS-2017-17-023).

Humans↗