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PubMed2026

Association of the Charlson Comorbidity Index With 1-Year Outcomes in Patients With Macular Edema Secondary to Retinal Vein Occlusion.

OBJECTIVE: To determine the predictive value of the Charlson Comorbidity Index (CCI) for outcomes in patients with macular edema secondary to retinal vein occlusion (RVO). DESIGN: Retrospective clinical cohort study. SUBJECTS: Patients seen between 2013 and 2023 at the Cole Eye Institute, Cleveland Clinic, were included. All patients were >18, diagnosed with RVO (International Classification of Diseases (ICD)-9 and 10 codes), had a complete CCI score, and had at least 1 year of ophthalmic follow-up data after their first intravitreal injection (baseline). Patients with ocular surgery, trauma, or panretinal photocoagulation were excluded. METHODS: Age-adjusted CCI scores were calculated for each patient from chart review. For patients with bilateral RVO, one eye was selected randomly. Patients were stratified into tertiles by CCI distribution: tertile 1 (CCI 0-5; mean 3.4), tertile 2 (age-CCI 4.1-6; mean 4.9), and tertile 3 (CCI ≥ 8; mean 9.6). Multivariable linear regression was performed to determine the predictive value of CCI and other covariates on visual and anatomical outcomes. MAIN OUTCOME MEASURES: Best-corrected visual acuity (BCVA) and central subfield thickness (CST) at 1-year follow-up. RESULTS: A total of 972 patients met all criteria, with an average age-adjusted CCI score of 6.2. Each one-point increase in CCI predicted 0.38 fewer letters in BCVA at follow-up (P < .001). Baseline BCVA was a significant predictor of follow-up BCVA in all tertiles (P < .001). In the third tertile, each one-point increase in CCI was associated with a 0.72 letter reduction in follow-up BCVA (P < .001). For CST, baseline CST was strongly predictive of final CST (P < .001), while CCI was only significant in the first tertile, where each point increase in CCI predicted a 13.7 µm increase in CST (P = .02). In RVO subtype interaction models, the age-adjusted CCI × CRVO interaction was not statistically significant for either 1-year BCVA (P = .269) or 1-year CST (P = .695). CONCLUSIONS: Higher CCI scores are significantly associated with worse visual outcomes in patients with RVO, particularly in the combined population and most comorbid patients (tertile 3). CCI was significantly associated with higher (thicker) CST only among the least comorbid patients (tertile 1).

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

TWIST2-dependent transcriptional activation of TPI1 mediates TGF-β1-driven fibroblast activation in pulmonary fibrosis.

Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal interstitial lung disease characterized by aberrant profibrotic signaling and excessive extracellular matrix deposition, accompanied by fibroblast-to-myofibroblast transition. Despite extensive investigation, the molecular mechanisms underlying IPF pathogenesis remain incompletely understood. Here, we investigated the role of triosephosphate isomerase 1 (TPI1) in IPF progression and its regulation by transforming growth factor-β (TGF-β) signaling. Loss-of-function analyses identified TPI1 as a downstream effector of TGF-β1, as its knockdown markedly suppressed fibrotic marker expression, fibroblast proliferation, and migration. Mechanistically, TWIST2 was shown to function as a direct transcriptional regulator of TPI1, binding to its promoter and promoting transcriptional activation. Rescue experiments further confirmed that the TWIST2-TPI1 axis is central to the progression of pulmonary fibrosis. Notably, knockdown of either TPI1 or TWIST2 effectively attenuated TGF-β1-induced fibrotic phenotypes. Collectively, these findings define the TGF-β1/TWIST2/TPI1 signaling axis as an important regulator of pathogenic fibroblast behavior and pro-fibrotic responses through transcriptional control of TPI1, highlighting its potential as a therapeutic target for IPF.

Twist-Related Protein 1↗

PubMed2026

Protein sorting and proteostasis mechanisms in CFTR-related exocrine pancreas dysfunction: A systematic narrative review.

The pancreas consists of exocrine and endocrine compartments. In the exocrine pancreas, cystic fibrosis transmembrane conductance regulator (CFTR) functions mainly in ductal epithelial cells as a chloride and bicarbonate channel. Its activity depends on proper protein folding, trafficking, and localization to the apical membrane. This systematic narrative review aims to synthesize the available evidence on the role of protein sorting machinery in CFTR channelopathies and its contribution to exocrine pancreatic dysfunction. A thorough search was conducted using PRISMA criteria on PubMed, Wiley Online Library, and Scopus for studies published in English between January 2000 and November 2025. Twenty studies that met the inclusion criteria were included in this review. Pathogenic CFTR variants impair protein folding, endoplasmic reticulum (ER) exit, and endosomal recycling, resulting in reduced apical membrane expression and stability. These defects disrupt the localization of associated transporters and secretory proteins, impair ductal bicarbonate secretion, alter zymogen handling, and promote acinar injury, although these claims are supported mainly by indirect experimental models and therefore require clinical confirmation. CFTR channelopathies in the exocrine pancreas encompass both ion transport defects and broader disruptions of protein sorting machinery. CFTR may contribute to the assembly, stabilization, or localization of selected apical transport complexes, and its loss can secondarily alter epithelial organization. Therapeutic approaches targeting both channel correction and intracellular trafficking may improve pancreatic function and mitigate disease progression.

Humans↗

PubMed2026

Quantitative assessment of the fingerprint evidential value using machine learning.

Fingerprints as physical evidence have long supported criminal investigation and adjudication. In practice, however, fingerprint identification relies mainly on examiners' experience. Furthermore, expert opinions tend to be categorical, even though the opinions with the same conclusion could differ substantially in evidential strength. To quantitatively assess fingerprint evidential value, this study proposes a machine learning-based framework as an interpretable decision-support tool. A lightweight residual one-dimensional convolutional neural network was constructed, incorporating channel recalibration and a similarity-driven attention mechanism to learn adaptive contribution weights for different matched minutiae (minutiae for short). Controlled experiments revealed that the predicted evidential value increased with the number of minutiae and was significantly influenced by the quality of minutiae. With 10 minutiae, the mean predicted scores were 4.49, 7.00, and 9.09 for blurred, moderately blurred, and clear minutiae, respectively. Multiple regression analysis indicated that replacing a pair of blurred minutiae with a pair of clear minutiae increased the score by 0.492, whereas replacing it with a pair of moderately blurred minutiae increased the score by only 0.216. By mapping predicted scores to graded levels of evidential strength, the framework contributes to a paradigm shift from categorical expert opinions to graded ones, helping courts evaluate fingerprint evidence more scientifically.

Humans↗

PubMed2026

Transcriptomic analysis provides molecular insights into the innate immune defense of Mactra veneriformis against Vibrio alginolyticus infection.

Mactra veneriformis is an economically important bivalve mollusc in China, but its aquaculture is frequently threatened by Vibrio infections, particularly Vibrio alginolyticus. To investigate the molecular immune response of M. veneriformis to V. alginolyticus, we performed RNA-seq analysis of hepatopancreatic tissues collected at 48 h post-infection, the peak mortality time point, with PBS-injected individuals used as controls. Infection with V. alginolyticus caused severe histopathological damage in the hepatopancreas and resulted in a cumulative mortality of 53.3% over 14 d, compared with 3.3% in the control group. Transcriptomic analysis identified 2623 differentially expressed genes (DEGs), including 1585 significantly up-regulated genes and 1038 down-regulated genes. KEGG enrichment analysis demonstrated that DEGs were significantly enriched in immune related and metabolism pathways, including the JAK-STAT signaling pathway, RIG-I-like receptor (RLR) signaling pathway, and cytochrome P450 (CYP450) signaling pathway. Collectively, these findings revealed candidate immune related genes (tlr3, tlr5, myd88, nfkb1, il-17d, and ifi44l), a putative TLR-MyD88-NF-κB signaling axis, and KEGG signaling pathways, including JAK-STAT, RLR and CYP450, that may be involved in the innate immune response of M. veneriformis to V. alginolyticus infection. These results provide a transcriptomic basis for understanding host-pathogen interactions in this species and highlight candidate genes and pathways for future functional validation and potential application in disease-resistance breeding.

Animals↗

PubMed2026

Single-cell RNA sequencing provides further insights into the immunostimulatory action of freeze-dried Lactiplantibacillus plantarum on Penaeus vannamei shrimp.

Immunostimulation through dietary interventions opened new avenues in developing disease control and prevention tools for shrimp aquaculture. We have previously shown that feeding with freeze-dried Lactiplantibacillus plantarum (LAB) increased disease resistance of Penaeus vannamei against both Vibrio parahaemolyticus and white spot syndrome virus (WSSV) based on bulk RNA sequencing of shrimp gills. This tissue participates in ion transport and serves as a first line of defense against environmental stressors and pathogenic infections. However, characterization of their cell composition and functions remains limited. Here, we implemented a single-cell RNA sequencing approach to further gather insights into how feeding with freeze-dried LAB modulates host immunity which may not be evident with bulk RNA sequencing approach. A total of five clusters with unique transcriptional signatures were identified, corresponding to pillar cells, septal cells, and sessile hemocytes. Pseudo-bulk analyses at global- and cluster-levels showed differential expression of genes related to host immunity and metabolism. We further revealed how overall transcriptomic changes are not exclusively caused by gene expression changes but may also be driven by cell population dynamics. This study highlighted how single-cell RNA sequencing approach may shed light on the mechanisms of action of immunostimulants which may be masked in bulk transcriptome analyses.

Animals↗

PubMed2026

Clinical predictors of severe and fatal respiratory syncytial virus infection in adults and the elderly: A retrospective cohort study.

BACKGROUND: Respiratory syncytial virus (RSV) is increasingly recognized as a cause of severe respiratory illness in adults, especially the elderly and those with comorbidities. However, data on outcomes and risk factors for severe disease in this population remain limited. METHODS: We retrospectively analyzed 123 adult patients diagnosed with RSV infection at a tertiary center in Taiwan from 2015 to 2023. Clinical characteristics, laboratory data, detection of other pathogens, clinical course and outcome were reviewed. Multivariable logistic regression identified risk factors for severe RSV infection, including ICU admission and 30-day mortality. RESULTS: The mean age was 55.7 years; 50% were aged ≥60 years and 13% were ≥75 years. ICU admission occurred in 17%, with significant associations to viral coinfection and elevated C-reactive protein (CRP). Thirty-day mortality was 13%, and overall in-hospital mortality was 18%, all among patients with comorbidities. Independent predictors of 30-day mortality included late elderly (aOR 24.2, p = 0.03), high CRP > 11.5 mg/dL (aOR 16.4, p = 0.005) and thrombocytopenia < 34,103/μL (aOR 11.4, p = 0.01). CONCLUSION: Advanced age (≥75 years), high CRP, and severe thrombocytopenia are key predictors of mortality in adults RSV patients. These findings highlight the need for targeted prevention strategies, including vaccination, in high-risk populations.

Co-infection↗

PubMed2026

Venomous Lepidoptera: defensive toxin systems, venom composition, and clinical significance.

Venomous Lepidoptera constitute an underrecognized yet medically significant group of toxin-producing arthropods that employ contact-mediated defensive envenomation through specialized integumentary structures such as setae, spines, and scoli. Unlike actively stinging arthropods, these insects deliver venom passively upon contact, eliciting a diverse spectrum of clinical manifestations collectively termed lepidopterism. Clinical outcomes range from localized pain and dermatitis to severe systemic effects, including hemorrhagic syndromes, complement activation, and chronic inflammatory disorders. Recent advances in proteomic and transcriptomic technologies have transformed our understanding of lepidopteran venoms, revealing unexpectedly complex toxin repertoires comprising serine proteases, phospholipases, pore-forming proteins, disulfide-rich peptides, neuroactive RF-amide peptides, and immune-modulating components. These findings have provided new insights into the molecular basis of toxicity, host-pathogen interactions, and the evolutionary diversification of venom systems within Lepidoptera. This review synthesizes current knowledge on the morphology of venom-delivery structures, venom composition, mechanisms of action, and associated clinical manifestations, while highlighting medically important taxa, particularly species of the genus Lonomia. The successful development of antivenom against Lonomia envenomation underscores the translational relevance of lepidopteran toxin research and its potential for therapeutic innovation. By integrating molecular, clinical, and evolutionary perspectives, this review repositions venomous Lepidoptera as a legitimate and important component of arthropod toxinology. Furthermore, it identifies critical methodological limitations and key knowledge gaps, providing a framework for future investigations aimed at advancing our understanding of toxin biology, immunopathology, and the development of novel biomedical applications.

Animals↗

PubMed2026

Mechanisms linking the gut microbiota to colorectal cancer development and progression.

Colorectal cancer remains a leading cause of global cancer mortality, with a concerning rise in early-onset cases driven by complex interactions between environmental exposures, lifestyle factors, and host genetics. Mounting evidence indicates that gut microbiota dysbiosis critically modulates this oncogenic process, acting as an active participant rather than a passive bystander. This review systematically synthesizes the dichotomous roles of the intestinal microbiome in colorectal tumorigenesis through the conceptual framework of the driver-passenger model. We discuss how early initiating driver bacteria, such as Polyketide synthase-positive Escherichia coli and enterotoxigenic Bacteroides fragilis, compromise mucosal barriers, induce chronic mucosal inflammation, and inflict direct genomic instability. As the local tumor microenvironment undergoes profound metabolic remodeling, opportunistic passenger pathogens, notably Fusobacterium nucleatum, become enriched, further promoting cellular proliferation and facilitating tumor immune evasion. Conversely, protective commensals, exemplified by Clostridium butyricum and Streptococcus thermophilus, exert robust tumor-suppressive effects through multifaceted mechanisms. These beneficial microbes actively antagonize malignant progression by redirecting tumor metabolic fluxes toward oxidative stress, orchestrating deep epigenetic reprogramming, and degrading core oncoproteins to reverse chemoresistance. Transitioning from fundamental mechanisms to clinical application, we evaluate a comprehensive spectrum of microbiota-targeted interventions, encompassing non-invasive diagnostic biomarkers, fecal microbiota transplantation, engineered bacteria, phage therapy, and postbiotics. Finally, we critically address the formidable translational challenges associated with microbial heterogeneity, long-term safety, and regulatory standardization, aiming to provide a balanced perspective on integrating microbiome-based strategies into next-generation precision oncology for colorectal cancer.

Humans↗

PubMed2026

Artificial neural network data fusion-mediated dual-mode sensor based on Fe3O4@PdIr for Salmonellatyphimurium detection in food.

Salmonella Typhimurium (S. typhimurium) is a major foodborne pathogen that poses a serious threat to public health. In this study, a colorimetric/electrochemical dual-mode biosensor assisted by artificial neural network (ANN) was developed for the sensitive detection of S. typhimurium. Fe3O4@PdIr nanocomposites with enhanced peroxidase-like activity and electrochemical performance were prepared and conjugated with an aptamer specific to S. typhimurium to obtain Fe3O4@PdIr-Apt. Through the sandwich binding of Fe3O4@PdIr-Apt and Apt to the target, the nanocomposites were attached to microplates or Au electrodes, thereby generating colorimetric and electrochemical signals. The ANN model deeply resolved the complex nonlinear relationship between the dual signals, enabling mutual correction and ultimately performing data fusion to output a single detection result, which significantly reduced the mean square error while improving detection sensitivity and reliability. This sensor exhibited a wide linear range of 2.7-2.7 × 108 CFU/mL and a low detection limit of 1.66 CFU/mL. Additionally, this method was successfully applied to the detection of S. typhimurium in pork and milk, with a recovery rate of 95.19% ∼ 104.07%. It indicated that the constructed sensor holds great practical potential for S. typhimurium detection.

Neural Networks, Computer↗

PubMed2026

An Update on Inborn Errors of V(D)J Recombination.

V(D)J recombination is the fundamental process by which developing T and B lymphocytes generate diverse antigen receptors, enabling adaptive immunity. This tightly regulated program operates exclusively in lymphoid precursors during G1 phase and depends on the lymphocyte-specific RAG1-RAG2 recombinase to introduce programmed DNA double-strand breaks at recombination signal sequences, followed by repair through the classical nonhomologous end joining (c-NHEJ) pathway. Disruption of any step in this molecular choreography compromises antigen receptor diversity and underlies a spectrum of inborn errors of immunity (IEIs), ranging from severe combined immunodeficiency (SCID) to immune dysregulation with autoimmunity and granulomatous disease. In this review, we place disorders of V(D)J recombination within the broader framework of T-cell development, detailing the temporal waves of recombinase activity, chromatin accessibility, and DNA damage responses that guide thymocyte differentiation. We discuss pathogenic variants affecting the cleavage phase [RAG1, RAG2, and the recently identified RAG cochaperone NudC domain-containing 3 (NUDCD3)], end processing (ARTEMIS), ligation and repair (LIG4, XLF, XRCC4, PRKDC), and genome surveillance pathways (ATM, MRN complex, RNF168), highlighting genotype-phenotype correlations and mechanisms driving immune deficiency and dysregulation. We briefly review recent diagnostic advances, including newborn screening using T-cell receptor excision circles, repertoire sequencing, and functional assays, alongside current therapeutic strategies. Finally, we outline key unanswered questions and argue that continued integration of clinical observation with molecular discovery is essential to improve outcomes and deepen understanding of adaptive immune development.

Humans↗

PubMed2026

Construction of circRNA-miRNA-mRNA regulatory networks in the intestine of turbot (Scophthalmus maximus) following Vibrio anguillarum infection.

Circular RNAs (circRNAs) play pivotal roles in post-transcriptional regulation by acting as molecular sponges for microRNAs (miRNAs) within the competitive endogenous RNA (ceRNA) network. However, the regulatory mechanisms in teleost immune responses remain poorly understood. In this study, circRNA-miRNA-mRNA networks were investigated in turbot (Scophthalmus maximus) following Vibrio anguillarum infection to elucidate host-pathogen interactions. Through high-throughput sequencing of intestinal tissues, a total of 50 differentially expressed circRNAs (DE-circRNAs) (18 at 2 hpi, 16 at 12 hpi, 16 at 48 hpi), 212 DE-miRNAs (11 at 2 hpi, 70 at 12 hpi, 15 at 48 hpi), and 1774 DE-mRNAs were identified. Functional enrichment analyses (GO/KEGG) revealed significant associations with immune pathways, including the MAPK signaling pathway and gap junction. An integrated circRNA-miRNA-mRNA regulatory network was constructed, highlighting key interactions including novel_circ_0002573/DE-miR-27a-3p/FGB and novel_circ_0002423/novel_347/GNE, which may regulate inflammatory and antibacterial responses. The expression patterns of selected circRNAs, miRNAs and mRNAs were validated using qRT-PCR, confirming the reliability of the sequencing results. Importantly, fibrinogen beta chain (FGB) and CXCR4/CXCL12 signaling were identified as critical immune modulators. These findings provide insights of the ceRNA regulatory networks involved in teleost intestinal immunity and provide potential molecular targets for selective breeding of disease resistance in this species.

Animals↗

PubMed2026

Inhibitory mechanism of phloretin on the AgrA LytTR domain-agr operon complex formation and its application in beef.

Staphylococcus aureus (S. aureus) represents a major foodborne pathogen whose enterotoxin production poses significant challenges to food safety due to its high environmental resistance and limited efficacy of conventional sterilization. Since the expression of enterotoxins is predominantly governed by the agr quorum sensing system, targeting this regulatory pathway has become a strategic choice for virulence control. This study elucidated the mechanism by which phloretin, a potential quorum sensing inhibitor, interferes with the agr system to attenuate virulence. To achieve this, the recombinant AgrA LytTR domain was expressed and purified, and its interaction with phloretin was characterized using thermal shift assays (TSA), electrophoretic mobility shift assays (EMSA), and molecular dynamics (MD) simulations. The results showed that phloretin specifically binds to the AgrA LytTR domain, enhancing its thermal stability and disrupting AgrA LytTR-agr operon binding by reducing the free energy of interaction between them, without causing significant structural rearrangement. Mechanistic analysis indicated that phloretin sterically hinders key β-sheet turn residues (HIS169, ASN201, ARG233), thereby impairing DNA recognition, downregulating RNAIII transcription, and inhibiting agr signaling. In cooked beef, phloretin significantly inhibited the secretion of enterotoxins and α-hemolysin, while delaying lipid oxidation and protein degradation, and maintaining the meat texture. These findings suggested that phloretin is a multifunctional substance with anti-virulence, antioxidant, and preservative properties, demonstrating its potential as a natural food preservative.

Phloretin↗

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 EIB202Δp. 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

Automated CEAP Classification of Venous Duplex Reports Using Multimodal Artificial Intelligence.

OBJECTIVE: To develop and internally validate a prototype multimodal artificial intelligence system for automated CEAP (Clinical, Etiological, Anatomical and Pathophysiological) classification of venous duplex ultrasound (VDUS) reports, integrating natural language processing of free-text components with computer vision analysis of hand-drawn anatomical diagrams. METHODS: Single centre retrospective observational study using routinely collected clinical data. One thousand consecutive venous duplex ultrasound reports from Cambridge University Hospitals NHS Foundation Trust, UK (July 2024 - May 2025) were labelled according to the CEAP classification, excluding the Etiological component, which could not be reliably determined from duplex reports alone. Transfer learning was applied using ClinicalBERT for text and MobileNetV3 for diagrammatic data. Clinical classes were predicted from request line text. Text- and image-based pathophysiological models were developed for four anatomical territories (Great Saphenous Vein, Small Saphenous Vein, Deep system, Perforators), combined using late fusion with probability averaging. RESULTS: The clinical CEAP model achieved accuracy of 0.91, macro-F1 of 0.82, and macro-AUC of 0.98. Pathophysiological prediction varied, with text models broadly outperforming image models. Fusion yielded heterogeneous benefits, improving SSV performance but reducing Deep system accuracy. The performance of the final pathophysiological CEAP fusion models varied across anatomical territories: accuracy ranged from 0.70-0.92 and macro-AUC from 0.80-0.92. CONCLUSION: This study demonstrates the feasibility of automated CEAP classification from VDUS reports. Despite class imbalance affecting minority class predictions, the strong discriminatory performance validates this multimodal ML model for extracting clinically meaningful information from real-world data. This approach offers potential, pending external validation, to streamline vascular services through automated triage and guideline-compliant decision making.

Artificial intelligence↗

PubMed2026

Axial Length Adjustment and AL/R Ratio Optimization of IOL Power Calculation in Extremely Long Eyes.

PURPOSE: To evaluate the accuracy of modern intraocular lens (IOL) power calculation formulas and axial length (AL) adjustment methods in eyes with AL ≥ 30.0 mm. DESIGN: Retrospective consecutive cross-sectional study. PARTICIPANTS AND CONTROLS: A total of 308 eyes (308 patients) with AL ≥ 30.00 mm were included. METHODS: Accuracy of modern online formulas, alone or with established AL adjustments methods, was analyzed. Subgroup analyses were performed based on AL, keratometry (K), anterior chamber depth (ACD), lens thickness (LT), and AL-to-corneal radius (AL/R) ratio. MAIN OUTCOME MEASURES: Predictive accuracy was evaluated using the formula performance index (FPI), root mean square absolute prediction error (RMSAE), standard deviation (SD) of prediction error (PE), and percentage of eyes within ±0.25 and ±0.50 diopters (D). RESULTS: Overall, Holladay 1 combined with the nonlinear polynomial Wang-Koch axial length adjustment (H1-PWK) demonstrated the best overall performance, achieving the lowest SD (0.40), RMSAE (0.40), and highest FPI (0.494). A tendency toward hyperopic error was observed in eyes with AL ≥ 32.0 mm, K ≥ 46.0 D. The AL/R ratio showed a significant positive correlation with PE in the Ladas Super formula, Barrett Universal II, EVO, PEARL-DGS, and Hoffer QST formulas. Spline-based regression analysis indicated that the transition point of AL/R from myopic to hyperopic PE varied across different formulas. CONCLUSIONS: H1-PWK provides robust refractive accuracy in extremely long eyes. The AL/R ratio may provide a useful composite biometric stratification parameter compared to AL alone.

Humans↗

PubMed2026

Neuroimaging anxious children and adolescents before and after cognitive behavioral therapy: a systematic review.

OBJECTIVE: This systematic review investigates brain changes in youths with anxiety disorders following cognitive behavioral therapy (CBT) and neural markers that predict CBT responses. METHODS: We conducted a systematic search using the electronic databases PubMed, Web of Science, and ProQuest. The inclusion deadline was set to October 27, 2025. We included fifteen peer-reviewed neuroimaging studies that examined the effects of CBT in youths under 19 years old with a primary clinical diagnosis of an anxiety disorder based on DSM-5 criteria. RESULTS: Although the existing literature is marked by substantial diversity in methods and outcomes, task-related neural response in the anterior cingulate cortex (ACC, 2/8, 25.0%), insula (1/8, 12.5%) increased from pre to post CBT and these changes were further correlated with clinical symptom improvements. Moreover, CBT outcomes were predicted by pre-treatment activity or connectivity in the ACC and amygdala (3/13, 23.0%). A smaller proportion of studies (2/13, 15.3%) found that activity or connectivity in the insula, precuneus/cuneus, postcentral gyrus, and activity or structure in the nucleus accumbens (NAcc) predicted response to CBT. The low consistency of these findings was driven by methodological variability, low reliability of the neural markers, and relatively small sample sizes. CONCLUSIONS: This review highlights promises of neural predictors and outcomes to enhance anxiety disorder treatments in children and adolescents, facilitating future personalized and effective CBT. Beyond this initial promise, the field is hindered by methodological inconsistencies and limited replications. While longitudinal and personalized approaches are important next steps, the central challenge remains: identifying neural markers that are both reliable and robust.

Adolescent↗