Dubin-Johnson syndrome (DJS) and Rotor syndrome (RS) are rare, autosomal recessive disorders that result in chronic, predominantly conjugated hyperbilirubinemia without cholestasis or hepatocellular injury. Although both conditions are benign and non-progressive, they reflect distinct molecular defects in hepatocellular transport pathways. DJS arises from mutations in the ABCC2 gene encoding the canalicular transporter multidrug resistance–associated protein 2, leading to impaired biliary excretion of conjugated bilirubin and organic anions. In contrast, RS results from combined deficiencies of the sinusoidal transporters OATP1B1 and OATP1B3, encoded by SLCO1B1 and SLCO1B3 genes, respectively, which mediate hepatic reuptake of conjugated bilirubin from the sinusoidal blood. These defects explain the characteristic biochemical and clinical distinctions between the syndromes, including the black hepatic pigmentation and markedly elevated urinary coproporphyrin I fraction in DJS, and the absence of pigmentation with moderate coproporphyrin I predominance in RS. Recent studies have expanded the understanding of how these transporters influence not only bilirubin handling but also the hepatic disposition of various drugs and endogenous metabolites. Recognition of DJS and RS is essential to prevent misdiagnosis of cholestatic or hepatocellular disease, avoid unnecessary investigations, and anticipate altered pharmacokinetics in affected individuals. This review synthesizes current evidence from molecular, biochemical, and clinical studies to highlight how these syndromes illuminate broader principles of hepatic transporter physiology and its relevance to inherited and acquired disorders of bilirubin metabolism.

Predicting the malignant transformation of rectal precancerous lesions remains challenging because conventional Whole Slide Images (WSIs) capture morphological information but lack molecular insight. Multiomics data provide complementary biological signals that often precede visible morphological changes. This study aimed to develop an artificial intelligence (AI)-based multimodal framework integrating WSI and multiomics data for accurate early prediction of malignant transformation.

WSI patches (512×512 px at 20× magnification) and matched multiomics profiles were used for 450 rectal tissue samples from the publicly available The Cancer Genome Atlas dataset. A multimodal architecture was designed, employing a Vision Transformer (ViT-B/16) for WSI feature extraction and a Variational Autoencoder for multiomics representation learning. Features were fused via a cross-attention mechanism to capture inter-modality dependencies. Baseline models, including a convolutional neural network-only image model and an omics-only multilayer perceptron, were trained for comparison. Five-fold cross-validation was applied, with binary cross-entropy loss, the AdamW optimizer, early stopping, and hyperparameter tuning to ensure reproducibility.

The multimodal Vision Transformer–Variational Autoencoder fusion model outperformed unimodal baselines, achieving an accuracy of 0.892 ± 0.012 and an area under the receiver operating characteristic curve of 0.927 ± 0.009, corresponding to a 7–10% improvement over WSI-only and omics-only models. Cross-attention–based fusion improved prediction stability and classification performance, while interpretability analyses (Grad-CAM and SHAP) highlighted biologically meaningful histopathological regions and molecular feature contributions.

This study presents a robust and scalable AI-based framework for integrating WSI and multiomics data in rectal precancerous lesions. The model improves predictive precision compared with unimodal baselines and offers preliminary interpretability insights through attention mechanisms. These findings support the potential of multimodal AI for early cancer risk assessment and precision pathology.

Hepatic ischemia–reperfusion (HIR) injury impairs outcomes post–liver transplantation. Therefore, we aimed to investigate the role and mechanism of miR-381-3p in HIR.

The study enrolled 150 healthy controls, 82 non-HIR-injured patients, and 68 patients with HIR injury following liver transplantation. Clinical data were analyzed. Multivariate analysis identified HIR risk factors; the predictive value of miR-381-3p was assessed via receiver operating characteristic analysis. An in vitro hypoxia/reoxygenation (H/R) model was established and employed. The cellular effects of miR-381-3p and JAK2 were evaluated using CCK-8, flow cytometry, ELISA, luciferase, RIP, and bioinformatics.

Serum miR-381-3p was significantly elevated in HIR compared with the other groups. miR-381-3p was the strongest independent HIR risk factor, which was confirmed by receiver operating characteristic analysis. H/R upregulated miR-381-3p. Inhibiting miR-381-3p counteracted H/R-induced decreased viability and increased apoptosis, inflammation, and oxidative stress. miR-381-3p directly bound to and suppressed JAK2 via its 3′ untranslated region (validated by luciferase and RIP). Transfection of si-JAK2 abolished the protective effects of miR-381-3p inhibition.

miR-381-3p exacerbates post-transplant HIR by directly targeting JAK2, amplifying inflammation and oxidative stress. Thus, our findings nominate serum miR-381-3p as a promising non-invasive biomarker and suggest its potential as a therapeutic target for mitigating HIR injury.

Diabetic cardiomyopathy (DCM), a diabetes-specific cardiovascular complication, is pathologically characterized by cardiomyocyte apoptosis, oxidative stress, inflammatory responses, and myocardial fibrosis, distinguishing it from other cardiac disorders, such as hypertension and coronary artery disease. Challenges in early diagnosis, coupled with the limited efficacy and adverse effects of current treatments, have made DCM a significant contributor to heart failure and mortality in patients with diabetes. Natural products, recognized for their diverse sources, structural variety, and multitarget therapeutic potential, have shown promise in preventing and treating DCM. Drawing on advances over the past five years, this review systematically summarizes the pharmacological effects and molecular mechanisms of natural products (e.g., flavonoids, terpenoids, phenylpropanoids, alkaloids, and polysaccharides) in the treatment of DCM, with the aim of providing a theoretical foundation for further research and drug development.

Mild traumatic brain injury (mTBI) represents the majority of head injury presentations in emergency departments (EDs), yet only a minority of patients have acute intracranial lesions on computed tomography (CT). This leads to widespread use of unnecessary CT scans. Point-of-care (POC) biosensing, defined as analytical testing performed at or near the site of patient care, offers a promising solution to this dilemma by enabling rapid biomarker quantification to inform CT decision-making. This review aims to evaluate POC-compatible biosensing strategies for ultra-early mTBI triage, with emphasis on platforms, matrix effects, and benchmarking aligned with CT-based decision-making. Two key precedents support this approach: (1) the integration of S100B into Scandinavian Neurotrauma Committee guidelines, which has demonstrated the potential for safe reduction of CT scans, and (2) the regulatory clearance of glial fibrillary acidic protein (GFAP) and ubiquitin C-terminal hydrolase-L1 (UCH-L1) testing to rule out the need for head CT in adults with suspected mTBI (Glasgow Coma Scale 13–15) when serum is collected within 12 hours of injury. Accordingly, this review focuses on the most implementable use case for mTBI, namely CT triage/rule-out. It synthesizes the current biomarker landscape (S100B, GFAP, UCH-L1), analyzes POC-suitable sensing modalities, and proposes a practical validation and benchmarking framework aligned with this intended use. A critical component is interference testing and real-world sample robustness, including vulnerabilities such as hemolysis-related elevation of UCH-L1. In conclusion, the most reliable path for biosensor translation in mTBI is to anchor development and validation to the ED CT-triage use case, emphasizing decision-point robustness and resilience to real-world sample variability over pure analytical sensitivity.

Glioblastoma remains a highly challenging malignancy with a pronounced tendency for recurrence. The hypoxic microenvironment is a key contributor to its therapy resistance. Hyperbaric oxygen therapy (HBOT), which elevates tissue oxygen pressure and reverses hypoxia, exhibits a “dual effect” in glioblastoma management. This review aims to evaluate the therapeutic potential of HBOT in glioblastoma by examining its multifaceted effects on tumor biology and treatment response. On one hand, it enhances radiosensitivity through reactive oxygen species generation, increases chemotherapy efficacy by augmenting cytotoxicity and improving vascular perfusion, and remodels the tumor microenvironment via vessel normalization, edema reduction, and immune cell modulation. Furthermore, HBOT attenuates cancer stem cell properties by downregulating stemness markers and inhibiting self-renewal capacity. On the other hand, HBOT may also promote tumor progression: oxidative stress can induce genomic instability, while concomitant activation of HIF-, NF-κB-, and VEGF-mediated pro-survival pathways may facilitate malignant cell adaptation and proliferation. Given these opposing considerations, the clinical application of HBOT in glioblastoma management remains exploratory. In conclusion, future research should focus on optimizing HBOT protocols. In addition, exploring combination with other therapeutic approaches is equally important. These efforts are essential for the safe and effective integration of HBOT into comprehensive treatment strategies for glioblastoma.

Pediatric low-grade gliomas (pLGGs) exhibit distinct biological and clinical characteristics compared to adult gliomas, and their treatment strategies differ substantially from those used in adults. Since the release of the 2016 World Health Organization Classification of Tumors of the Central Nervous System and its subsequent updates, significant advances have been made in understanding the diagnosis and management of pLGGs. Therefore, updated guidelines tailored to current clinical practice are needed. In this document, we present the consensus guidelines for the diagnosis and management of pLGGs in China. The recommendations were developed through a comprehensive review of relevant domestic and international guidelines and literature, combined with expert consensus meetings and external peer review to ensure rigorous validation. The guideline integrates the levels of evidence from published studies, expert consensus, and practical clinical considerations. All recommendations were reviewed and approved by a multidisciplinary panel of experts from the Pediatric Neurosurgery Group. This guideline is intended to serve as guidance for healthcare professionals involved in pediatric neuro-oncology, as well as for patients, caregivers, and other healthcare providers participating in the management of pLGGs.