Colorectal polyp detection from endoscopic images is critical for the early diagnosis of colorectal cancer. However, traditional deep learning methods often suffer from limited generalization when deployed across datasets containing different polyp morphologies. This work aimed to investigate whether vision-language foundation models can facilitate zero-shot generalization across multiple polyp datasets without target-domain fine-tuning.

We introduced a zero-shot colorectal polyp detection framework based on Contrastive Language-Image Pretraining (CLIP) to improve cross-dataset detection performance. Key innovations include: (1) a background patch contrastive loss using pseudo-normal tissue patches to teach the model to distinguish normal mucosa from polyps; (2) attribute-enhanced text prompts that incorporate domain-specific descriptors of polyp appearance, improving the model’s semantic generalization to novel polyp morphologies; and (3) an enhanced CLIP visual adapter with per-layer adaptive feature fusion and generalized mean pooling to capture multi-scale features for better polyp localization. During training, we use one annotated colorectal polyp dataset (e.g., CVC-ColonDB) to learn patch-level image-text correspondence. The model is then evaluated in a zero-shot manner on different polyp datasets (CVC-ClinicDB, Kvasir-SEG, and CVC-300), where we evaluate pixel-level anomaly detection performance.

The framework demonstrated robust zero-shot generalization on unseen test cohorts. Without any dataset-specific fine-tuning, the model achieved a mean pixel-level AUROC of 0.94 and a mean average precision of 0.81 across the 12 leave-one-dataset-out zero-shot transfer settings. In the CVC-ColonDB-source benchmark, the model achieved a mean Dice coefficient of 0.84 across CVC-ClinicDB, Kvasir-SEG, and CVC-300. This high level of performance was consistent across datasets with distinct visual characteristics, underscoring the ability of the model to detect diverse polyp morphologies that it had not been explicitly trained to recognize.

Our findings demonstrate that an anomaly-aware vision-language model significantly improves cross-dataset polyp detection generalization without requiring normal images for training. This multimodal strategy may facilitate the robust deployment of artificial intelligence-based colorectal screening systems by enabling reliable detection of diverse polyp morphologies across different clinical settings. Extension to non-polyp colorectal pathologies (e.g., ulcerative colitis and colorectal tumors) remains an important direction for future work, pending the availability of pixel-level annotated datasets for these lesion categories.

Chronic pelvic pain remains a significant clinical challenge, often refractory to conservative and interventional treatments. Superior hypogastric plexus block is an established technique; however, conventional anterior and posterior approaches may be limited by anatomical variability and potential risks to adjacent structures. Based on these anatomical findings, we propose that a posterior transosseous S1 pedicular approach represents a novel and anatomically robust corridor for accessing the superior hypogastric plexus. We hypothesize that the highly reproducible osseous anatomy of the S1 pedicle, combined with its consistent spatial relationship to the anterior sacral cortex and retroperitoneal compartment, may enable precise and fluoroscopically reproducible instrument guidance toward the plexus. Furthermore, this trajectory may mitigate the anatomical variability and procedural limitations associated with conventional anterior or paravertebral techniques while potentially reducing the risk of inadvertent injury to adjacent visceral, vascular, and neural structures. This concept is based on anatomical reasoning and fluoroscopic observations obtained during cadaveric anatomical orientation, suggesting that a transosseous trajectory through the S1 pedicle toward the anterior sacral cortex may offer improved spatial control and reproducibility compared with soft-tissue-based approaches. The proposed pathway remains conceptual and is not intended for clinical application at this stage. Further cadaveric, imaging-based, and clinical studies are required to evaluate its anatomical validity, safety, and potential clinical relevance.

Primary biliary cholangitis (PBC) significantly impairs health-related quality of life (HRQL), yet the impact of disease stage and fatigue on HRQL and psychological status remains insufficiently quantified. This study aimed to investigate differences in HRQL across disease stages and the impact of fatigue in patients with PBC.

This cross-sectional study recruited 219 patients with PBC from two Chinese tertiary hospitals (2011–2024). After excluding one preclinical case, 218 patients were analyzed. Quality of life was assessed using the validated Chinese versions of the SF-36 and Chronic Liver Disease Questionnaire (CLDQ); psychological status was assessed using the Self-Rating Anxiety Scale and Self-Rating Depression Scale. Between-group differences were quantified by mean differences (MDs) and odds ratios (ORs) with 95% confidence intervals (CIs). Baseline characteristics were balanced across stages (all P > 0.05).

Of the 218 patients (90.4% female; mean age, 57.2 ± 10.3 years), 41 were in the clinical stage, 75 in the fibrosis stage, and 102 in the cirrhosis stage. SF-36 scores were lowest in the cirrhosis stage (e.g., Physical Functioning MD, 17.26; 95% CI, 6.93–27.59 vs. clinical stage), with similar declines in CLDQ domains. Anxiety was highest in the clinical stage (58.5%; OR vs. cirrhosis, 4.13; 95% CI, 1.92–8.92), whereas depression was highest in the cirrhosis stage (55.9%; OR vs. clinical stage, 4.50; 95% CI, 1.95–10.38). Fatigue prevalence was 66.1% and increased with disease stage. Patients with fatigue had lower SF-36 scores in Physical Functioning, Bodily Pain, Vitality, Mental Health, and Physical Component Summary (e.g., Physical Component Summary MD, 38.22; 95% CI, 10.41–66.02).

HRQL declines progressively with PBC stage. Fatigue is strongly associated with impaired HRQL and is closely interrelated with anxiety and depression. Stage-specific psychological patterns suggest the need for tailored supportive interventions.

Pulmonary arterial hypertension (PAH) is a progressive cardiovascular disease with an increasing global burden. Although hemolytic disorders are established causes of PAH, their contribution to the global PAH burden remains unclear. This study aimed to evaluate the association between hemolysis-associated disorders and PAH incidence and to identify the relative contribution of hemolytic disorder subtypes compared with socio-demographic factors.

Using Global Burden of Disease 2021 data, temporal trends in the age-standardized incidence rate (ASIR) of PAH were analyzed using Joinpoint regression. Pearson correlation analysis assessed associations between PAH ASIR and the age-standardized prevalence rates of hemolytic disorder subtypes, hemolysis-related infections, malnutrition, and the Socio-demographic Index (SDI). Random forest regression was used to quantify the contributions of hemolytic disorders to PAH ASIR. Geographic distributions of PAH incidence and hemolytic disorder prevalence were compared, and Bayesian age-period-cohort modeling was used to project their burdens through 2050.

Global PAH ASIR increased from 0.50 to 0.52 per 100,000 from 1990 to 2021. The prevalence of hemoglobinopathies and hemolytic anemias correlated positively with PAH ASIR (R = 0.61, P = 7.70 × 10-22). The random forest model explained 73% of the variance in PAH ASIR (R² = 0.73, P = 0.01), with G6PD trait (percentage increase in mean squared error [%IncMSE]: 18.43), other hemoglobinopathies/hemolytic anemias of unknown etiology (%IncMSE: 18.38), and vitamin A deficiency (%IncMSE: 17.27) identified as the top predictors, surpassing SDI (%IncMSE: 13.25) and sex (%IncMSE: 1.25). Temporal changes in hemolytic disorder prevalence strongly mirrored changes in PAH incidence (R = 0.76, P = 6.34 × 10-39). Exploratory analyses suggested that natural product exposures may contribute to the unexplained hemolytic burden that drives PAH. Projections indicated a continued rise through 2050 in both PAH burden (ASIR increasing from 0.52 in 2022 to 0.57 per 100,000) and hemolytic disease burden (prevalence rising from 27,760.54 to 31,863.72 per 100,000).

Hemolysis-associated disorders, particularly G6PD trait, other hemoglobinopathies/hemolytic anemias, and vitamin A deficiency, are the predominant contributors to the global PAH burden. The projected continued rise in hemolytic disorder prevalence through 2050 signals a persistent exacerbation of the global PAH burden, underscoring the urgent need for targeted prevention strategies.

Antimitochondrial antibody (AMA)-negative primary biliary cholangitis (PBC) is a rare presentation of PBC that comprises 5%–10% of all PBC patients. The pathogenesis of AMA-negative PBC appears to be similar to that of AMA-positive PBC. AMA-negative PBC presents similarly to AMA-positive PBC, with symptoms of cholestasis, fatigue, and pruritus most commonly reported. Defective bicarbonate production, resulting in acidification of bile and bile acids, has been proposed as the primary mechanism of damage to bile ducts and hepatocytes and is reflected in elevations of alkaline phosphatase and aminotransferases. Chronic damage can lead to the development of cirrhosis. The diagnosis is made by the finding of AMA negativity by ELISA or assays of similar sensitivity and a positive PBC-specific antinuclear antibody (ANA; anti-glycoprotein 210 and anti-speckled 100 kDa protein) test. In cases in which anti-glycoprotein 210 and anti-speckled 100 kDa protein assays are also negative, a liver biopsy is required to make the diagnosis after exclusion of other causes of cholestasis by magnetic resonance cholangiopancreatography or endoscopic retrograde cholangiopancreatography. Treatment for AMA-negative PBC is the same as for AMA-positive cases, with ursodeoxycholic acid as the first-line treatment. Current treatment is most effective in early stages, where it slows but does not eliminate progression. Risk stratification by validated tools such as the GLOBE and UK-PBC scores remains useful in AMA-negative PBC.

Porto-sinusoidal vascular disease (PSVD) is a non-cirrhotic vascular liver disorder characterized by portal and sinusoidal microvascular lesions and is frequently complicated by portal hypertension. Accurate assessment of portal pressure is essential for diagnosis, risk stratification, therapeutic decision-making, and prognostic evaluation in PSVD. However, unlike cirrhosis, portal hypertension in PSVD is predominantly presinusoidal, making hepatic venous pressure gradient measurement prone to underestimating true portal pressure. Recent advances have promoted a transition from conventional invasive assessment toward a multimodal and precision-oriented strategy integrating non-invasive and minimally invasive techniques. Ultrasound elastography, computed tomography, and magnetic resonance imaging—particularly radiomics-based approaches—provide valuable tools for differentiating PSVD from cirrhosis and estimating the severity of portal hypertension. Endoscopic ultrasound-guided portal pressure gradient measurement has emerged as a promising minimally invasive technique for direct hemodynamic assessment and prognostic stratification. In addition, laboratory biomarkers, digital modeling, and artificial intelligence-assisted analysis may further improve individualized risk prediction and dynamic monitoring. This review summarizes current advances in portal pressure assessment in PSVD, critically discusses the strengths and limitations of existing approaches, and highlights future directions toward non-invasive, digital, and precision-guided management.