ATP-binding cassette (ABC) transporters are transmembrane proteins involved in the translocation of bilirubin, bile acids, phospholipids, and cholesterol into bile canaliculi. Mutations in particular genes encoding these transporters—including BSEP (ABCB11 gene), MDR3 (ABCB4 gene), sterolin-1 and sterolin-2 (ABCG5/8 genes), and MRP2 (ABCC2 gene)—result in a wide spectrum of liver diseases, ranging from benign conditions such as Dubin-Johnson syndrome to more severe presentations like progressive familial intrahepatic cholestasis. The severity of disease is influenced by many factors, including zygosity, mutation type, and environmental modifiers such as hormones, consanguinity, and founder effects. Homozygous and compound heterozygous mutations typically result in severe and early-onset diseases, while heterozygous single-allelic mutants generally result in milder diseases. Next-generation genetic testing has proven to have high diagnostic value and is important for prognostication. With knowledge of the underlying specific mutations, there is also potential for future targeted therapy for many severe diseases. The aim of this review is to update and discuss the hepatic diseases associated with ABC transporter mutations, the genetic and environmental effects that influence the severity of disease, typical presentations of these cholestatic hepatic diseases, diagnostic considerations, and treatment options.

Chronic hepatitis B (CHB) poses a major global health burden, with China particularly affected. Effective antiviral therapy is crucial to prevent disease progression, but responses may vary by Hepatitis B virus (HBV) genotype. This prospective study aimed to compare genotype-specific responses to 144-week entecavir (ETV) therapy in HBeAg-positive CHB patients, with particular emphasis on histological improvement assessed through paired liver biopsies.

We enrolled 49 treatment-naïve CHB patients (HBV DNA ≥ 20,000 IU/mL, alanine transaminase (ALT) > 2× ULN, and Scheuer system G ≥ 2) who received ETV 0.5 mg/day. HBV genotyping was performed using Polymerase Chain Reaction and fragment length analysis. The primary endpoint was histological improvement (i.e., ≥ 2-grade reduction in necroinflammatory activity without fibrosis progression), evaluated via paired biopsies (baseline and week 144) by blinded pathologists. Secondary endpoints included virological response (i.e., serum HBV DNA < 100 IU/mL), HBeAg seroconversion, and ALT normalization.

The cohort included 24 genotype B and 24 genotype C patients (one genotype A patient was excluded from genotype-specific analyses). Genotype B showed significantly higher histological improvement rates (91.3% vs. 63.2%, P = 0.027) and greater inflammation resolution (0 ≤ G < 1: 56.5% vs. 26.3%, P = 0.048). Virological suppression was excellent in both groups (100% vs. 100%). HBeAg seroconversion trended higher in genotype C (29.2% vs. 50.0%, P = 0.140). All patients achieved ALT normalization by week 48, with no safety concerns.

HBV genotype B demonstrates superior histological responses to ETV therapy compared with genotype C, supporting the clinical value of HBV genotyping for personalized CHB management. These findings highlight the importance of considering viral genotype when evaluating treatment outcomes.

Lung cancer remains the leading cause of cancer-related mortality worldwide. Early detection of pulmonary nodules is crucial for timely diagnosis and effective treatment. Conventional computer-aided detection systems have shown limitations, including high false-positive rates and low sensitivity. Recent advances in deep learning, particularly convolutional neural networks (CNNs), have shown great potential in improving the accuracy and reliability of nodule detection and classification. This study aimed to develop and evaluate an automatic method for lung nodule detection and classification using a CNN-based architecture applied to computed tomography images from the publicly available LIDC-IDRI database.

This retrospective study was conducted on 82 patients (10,496 computed tomography slices) selected from the LIDC-IDRI database. The proposed method consists of five main steps: image preprocessing, lung parenchyma segmentation using Otsu’s thresholding and morphological operations, detection of nodule candidates, feature extraction, and classification using a CNN model. The CNN architecture includes two convolutional layers (20 and 30 filters, 3×3 kernel), ReLU activation, max-pooling layers, and a Softmax output layer. The network was trained with a mini-batch size of 32 for 50 epochs using the Stochastic Gradient Descent with Momentum optimizer (learning rate = 0.001, momentum = 0.9). Model performance was evaluated in terms of sensitivity, specificity, precision, and accuracy.

The proposed CNN model successfully detected pulmonary nodules and achieved accurate classification between benign and malignant nodules. On the LIDC-IDRI dataset, the model achieved a sensitivity of 98.7%, specificity of 97.5%, precision of 97.9%, and accuracy of 98.4%. Comparative analysis with recent studies, including hybrid CNN-long short-term memory and ResNet-based models, demonstrated that the proposed method provides competitive performance while maintaining lower computational complexity. The classification of nodule subtypes (solid, partially frosted, totally frosted) showed satisfactory discrimination results.

The proposed CNN-based system demonstrates the feasibility and robustness of deep learning for automatic lung nodule detection and classification. Despite strong results, the study acknowledges limitations such as single-database validation and a relatively small training size. Future work will focus on validating the model across other datasets (e.g., ELCAP, NELSON) and optimizing multi-class classification performance to enhance generalizability and clinical applicability.

Micro- and nanoplastics (MNPs) are plastic particles smaller than 5 mm and 1 µm, respectively, and are emerging environmental pollutants with growing implications for human health. These particles stem from either ‘primary sources’, such as intentionally manufactured microbeads and industrial abrasives, or ‘secondary sources’, where larger plastic items break down into smaller fragments over time. Human exposure primarily occurs through ingestion and inhalation, with contaminated seafood and plastic-laden food packaging representing key routes of entry. Once ingested, MNPs can cross the intestinal barrier, accumulate in gastrointestinal (GI) tissues, and trigger biological responses. Mechanistic studies reveal that MNPs induce oxidative stress, DNA damage, chronic inflammation, and endocrine disruption, all of which are hallmarks of carcinogenic pathways. They also alter gut microbiota, potentially promoting dysbiosis and immune dysregulation. The GI tract is particularly vulnerable to these effects due to direct luminal mucosal contact and high epithelial turnover. Epidemiological data remain limited, but early evidence supports a plausible link between MNPs exposure and GI malignancies. Such findings are particularly concerning given the increasing global incidence and early age presentation of colorectal and esophageal cancers. Given that MNPs may represent a modifiable environmental risk factor in GI cancer prevention, public health strategies must prioritize reducing plastic exposure, promoting antioxidant-rich diets, and improving environmental monitoring. This review explores the potential carcinogenic effects of microplastics while also examining their emerging roles in cancer therapeutics. It highlights critical avenues for future investigation and underscores the importance of cross-disciplinary efforts to tackle this growing global health concern.

Febrile neutropenia (FN) is one of the acute and serious complications of chemotherapy-induced myelosuppression in tumor patients. Antibiotics and granulocyte colony-stimulating factor are the mainstays of its treatment. However, this therapy still faces many challenges and may trigger drug resistance, as well as adverse effects such as bone pain and vasculitis. How to minimize treatment-related toxicity while ensuring therapeutic efficacy has become a key issue to be addressed in current clinical practice. In recent years, traditional Chinese medicine (TCM) has demonstrated unique advantages in the prevention and treatment of FN. We conducted a comprehensive search of the PubMed, Web of Science, and CNKI databases using keywords such as TCM and FN, covering the period from their establishment to May 2025. Clinical studies have shown that the combination of TCM and modern medicine can significantly reduce the incidence of FN, while also enhancing the number of granulocytes, shortening the duration of fever, improving the quality of life of patients, and reducing other toxic effects of chemotherapy. These results suggest that TCM is a promising and safe complementary therapy. However, more high-quality trials are needed to verify its benefits. This review summarizes the latest progress in the treatment of FN with TCM and discusses future development directions.

Infections are frequent and lethal complications of acute-on-chronic liver failure (ACLF). Reliable biomarkers to distinguish fungal from bacterial infections remain limited. Given the central role of immune dysfunction in ACLF, we aimed to evaluate the diagnostic value of serum cytokines in differentiating invasive pulmonary aspergillosis (IPA) from bacterial pneumonia (BP) in HBV-associated ACLF.

This retrospective case-control study enrolled ACLF patients admitted to the Tongji Hospital, between 2018 and 2022. Patients were categorized into IPA, BP, and non-infection groups. The BP and non-infection groups were propensity score-matched to the IPA cases. Serum cytokines levels (IL-1β, sIL-2R, IL-6, IL-8, IL-10, TNF-α) and clinical data were collected, with the diagnostic performance of these cytokines as biomarkers assessed via ROC curves.

A total of 32 IPA, 96 BP, and 96 non-infection patients were enrolled, with balanced baseline characteristics. Compared with the non-infection group, the IPA group had higher sIL-2R (1,606.00 vs. 1,211.50 U/mL, P = 0.019) and IL-6 (69.03 vs. 15.98 pg/mL, P < 0.001) levels, but lower IL-8 levels (62.20 vs. 132.00 pg/mL, P = 0.025). The BP group showed elevated sIL-2R (1,792.00 U/mL), IL-6 (49.42 pg/mL), IL-10 (13.40 pg/mL) levels compared to the non-infection group (all P < 0.001). Also, IL-8 was lower in the IPA group than in the BP group (62.20 vs. 176.00 pg/mL, P < 0.001) and its assessment could best distinguish IPA from BP (AUC = 0.743, cut-off = 76.60 pg/mL; sensitivity = 66.7%, specificity = 82.1%).

Serum IL-8 exhibited superior diagnostic value for IPA in patients with HBV-ACLF and could effectively discriminate Aspergillus infections from bacterial infections.

Colorectal cancer (CRC), like all other cancers, results from genetic and epigenetic alterations of the genome. The mechanisms leading to epigenetic alterations include DNA methylation, histone modifications, and small non-coding RNAs. As shown in many studies, some histone modifications such as acetylation, methylation, and phosphorylation are reported to be altered in CRC. Since these epigenetic alterations are reversible, they can be targeted as a strategy for CRC treatment. Numerous studies demonstrate the effects of molecules (both natural and synthetic) as inhibitors of enzymes responsible for histone acetylation, methylation, and phosphorylation in CRC cell lines. Some of these molecules have reached clinical trial stages. Vorinostat and belinostat, as histone deacetylase inhibitors; pinometostat and ribavirin, as histone methyltransferase inhibitors; and staurosporine and barasertib, which target histone phosphorylation, are among the promising epigenetic modifiers targeting histone alterations. Some of these modifiers can be used alone or in combination with other anticancer drugs or radiotherapy to increase efficacy. This review aims to identify molecules that target enzymes responsible for altering acetylation, methylation, and phosphorylation of histones in CRC.

The Chinese Society of Hepatology of the Chinese Medical Association has invited experts in relevant fields to revise and rename the 2019 “Chinese Guidelines on the Management of Liver Cirrhosis” to “Chinese Guidelines for Clinical Diagnosis, Treatment, and Management of Cirrhosis (2025)”. These updated guidelines are aimed at providing recommendations for the clinical diagnosis and management of liver cirrhosis across the compensated, decompensated, and recompensated stages, as well as guidance on cirrhosis reversal and associated complications.

Nutrition plays a pivotal role in the prevention and management of gastrointestinal and hepatic diseases, yet dietary guidance remains generic, limiting its effectiveness. Conditions such as inflammatory bowel disease, irritable bowel syndrome, metabolic dysfunction-associated steatotic liver disease, celiac disease, and gastroesophageal reflux disease are significantly influenced by dietary factors. Personalized nutrition has emerged as a promising strategy to tailor interventions, but conventional approaches fail to account for individual metabolic, genetic, and microbiome variability, limiting their clinical impact. The rapid rise of artificial intelligence (AI) has transformed precision nutrition by integrating genomics, microbiome profiles, metabolic markers, and real-time dietary tracking to generate individualized recommendations. AI-driven systems are advancing dietary assessment, condition-specific nutrition optimization, and continuous monitoring through tools such as wearable devices and natural language processing-based diet analysis. These innovations hold transformative potential in gastroenterology and hepatology, offering dynamic, patient-specific strategies that may enhance clinical outcomes. However, challenges remain, including the lack of standardized AI-driven protocols, ethical concerns such as bias and data privacy, limited clinical validation, and the underrepresentation of nutrition in many current AI applications. Opportunities for progress include developing federated learning models, expanding real-world validation studies, and designing regulatory and ethical frameworks for safe implementation. This narrative review synthesizes literature published between 2015 and 2025 across five databases, highlighting key applications, limitations, and future directions of AI-driven personalized nutrition in gastroenterology and hepatology. It provides insights into how AI could reshape patient-centered care through more individualized, effective, and scalable dietary strategies.

Metabolism-associated fatty liver disease (MAFLD) is a disease of hepatic fat accumulation resulting from metabolic disorders. Currently, MAFLD is the most common cause of chronic liver disease in children and adolescents. No effective or safe drugs for treating children with MAFLD are available. The traditional Chinese medicine used for treating MAFLD in children is characterized by being holistically regulated, multileveled, multi-targeting, and very safe. In this paper, the progress in research involving treatment using traditional Chinese medicine for MAFLD in children is reviewed.