Cardiovascular diseases (CVDs) remain the leading cause of global morbidity and mortality, highlighting the urgent need for innovative diagnostic and prognostic approaches to address their complex pathophysiology. Recent advances in molecular cardiology have unveiled immune-derived microRNAs (miRNAs), or immuno-miRs, as pivotal regulators in the interplay between immune responses and cardiovascular pathology. Secreted by immune cells such as T lymphocytes, macrophages, and neutrophils, these small non-coding RNAs modulate critical signaling pathways by regulating gene expression. Immuno-miRs influence essential processes, including inflammation, endothelial dysfunction, and fibrotic remodeling—core mechanisms underlying conditions such as atherosclerosis, myocardial infarction, and heart failure. Moreover, their presence in systemic circulation within extracellular vesicles underscores their role in intercellular communication, impacting both immune and non-immune cardiovascular cells, such as cardiomyocytes and endothelial cells. This dual functionality renders immuno-miRs promising candidates as diagnostic biomarkers for early disease detection and as prognostic tools for assessing disease progression and therapeutic efficacy. Furthermore, emerging miRNA-based interventions—such as miRNA mimics and inhibitors—show considerable promise in modulating immune dysregulation in CVDs, although clinical translation remains a significant challenge. In this review, we comprehensively examine the regulatory roles of immuno-miRs in both innate and adaptive immune responses and explore recent advancements in miRNA-based therapies. By consolidating current knowledge and identifying existing gaps, we provide a comprehensive overview of the transformative potential of immuno-miRs in CVD management. Integrating these molecules into personalized medicine may pave the way for more effective, targeted, and minimally invasive strategies to combat one of the world’s most pressing health challenges.

Oxidative stress could be a key process in acyclovir (ACV)-induced nephrotoxicity. N-acetylcysteine (NAC) is a water-soluble antioxidant with anti-inflammatory activity. This study aimed to evaluate the protective effect of NAC on ACV-induced nephrotoxicity in adult Wistar rats.

Forty adult male Wistar rats (200–220 g) were used. The rats were randomly divided into eight groups (n = 5/group) and were treated intraperitoneally daily for seven days as follows: Group 1 (Control) was administered water (0.2mL), while groups 2–4 were administered NAC (25, 50, and 100 mg/kg). Group 5 was administered ACV (150 mg/kg), while groups 6–8 were supplemented with NAC (25, 50, and 100 mg/kg) prior to treatment with ACV (150 mg/kg). On day 8, the rats were weighed and euthanized, and blood samples were collected for the assessment of biochemical markers. The kidneys were weighed and subjected to oxidative stress markers and histological evaluations.

ACV had no significant (p > 0.05) effects on the body and kidney weights of rats compared to the control. ACV produced significant (p < 0.001) elevations in kidney malondialdehyde, serum urea, creatinine, and uric acid levels in rats, which differed from the control. There were significant (p < 0.001) decreases in kidney glutathione, superoxide dismutase, peroxidase, and catalase, as well as serum chloride, potassium, bicarbonate, and sodium levels in ACV-treated rats compared to the control. ACV caused widening of Bowman’s space and tubular necrosis in the kidneys of rats. Nonetheless, NAC supplementation abrogated ACV-induced nephrotoxicity in a dose-dependent manner. Kidney histology was restored by NAC supplementation.

NAC protected against ACV-induced nephrotoxicity. This finding shows that NAC may have therapeutic potential for nephrotoxicity caused by ACV.

Primary biliary cholangitis (PBC) is a chronic progressive autoimmune disorder characterized by small non-purulent intrahepatic bile duct destruction (ductopenia) and cholestasis. While the etiology of PBC remains unclear, it is believed to involve genetic-environmental interactions. Emerging evidence highlights gut microbiota dysbiosis in PBC patients, with increased symbiotic bacteria and decreased pathogenic bacteria. Microbial alterations potentially influence disease pathogenesis through multiple mechanisms, including immune dysregulation, intestinal barrier damage, BA metabolic dysregulation, and cholestasis. These findings suggest that the gut microbiota can serve not only as a non-invasive biomarker for diagnosis and prognosis evaluation but also as a therapeutic target for the disease. In this review, we summarize changes in PBC patients’ gut microbiota, explain how these changes affect disease occurrence and development, and discuss treatment methods with potential clinical value that intervene in gut microbiota.

Hermansky-Pudlak syndrome (HPS) is a rare, autosomal recessive disorder predominantly affecting individuals of Puerto Rican descent. It is characterized by oculocutaneous albinism, platelet storage pool deficiency, and lysosomal ceroid accumulation in tissues. Lysosomal dysfunction has been shown to be associated with pulmonary fibrosis and granulomatous colitis in HPS patients, accounting for a significant portion of morbidity and mortality in this population. Clinical and endoscopic gastrointestinal manifestations in HPS patients are similar to those of active Crohn’s disease, including abdominal pain, bleeding, fissures, fistulas, and perianal involvement. Histology reveals granulomatous colitis that can be difficult to distinguish from Crohn’s disease. Identifying distinct morphologic features from Crohn’s disease is crucial for the diagnosis of HPS. Here, we present a case of a 27-year-old male with a history of HPS and refractory granulomatous colitis with severe perianal disease, who underwent total proctocolectomy and perianal excision. The unique, distinguishing morphologic features from Crohn’s disease in this case are: 1) grossly diffuse ulceration in the ano-rectum and cecum, 2) ulcerative and granulomatous inflammation predominantly involving the mucosa and submucosa of the colon, and 3) accumulation of ceroid pigment in the histiocytes of the lamina propria throughout the entire gastrointestinal tract. Immunohistochemical stains for CD3 and FoxP3-positive T cells in the granulomatous colitis were further analyzed. Thus, we fully document the extent of disease involvement and morphologic features in this patient and extensively discuss the similarities and differences between HPS and Crohn’s disease.

With the widespread application of systemic treatments for hepatocellular carcinoma, liver injury caused by molecular targeted drugs and immune checkpoint inhibitors has become a common clinical problem. The Chinese Society of Hepatology, Chinese Medical Association, organized domestic experts to summarize and analyze adverse liver reactions, as well as advances in the diagnosis and treatment related to systemic therapy for liver cancer, both domestically and internationally. Based on this work, we formulated the “Consensus on the Management of Liver Injury Associated with Targeted Drugs and Immune Checkpoint Inhibitors for Hepatocellular Carcinoma”, aiming to provide practical recommendations and decision-making guidance for clinicians in hepatology and related specialties. This guidance focuses on the monitoring, diagnosis, prevention, and treatment of liver injury during targeted and immune checkpoint inhibitor therapy, ultimately helping more liver cancer patients benefit from targeted immunotherapy.

Large-scale data on the hepatitis D virus (HDV)/hepatitis B virus (HBV) co-infection rate is needed to estimate the current epidemiology of HDV in China. This study aimed to estimate the current epidemiology of HDV.

Patients with chronic HBV infection, with documented serum hepatitis B surface antigen (HBsAg) positivity for more than six months, were enrolled across China. Blood samples were collected at baseline for central evaluations of HDV antibody and HBsAg quantification. Assessments for antibodies of hepatitis A virus, hepatitis C virus, hepatitis E virus, and human immunodeficiency virus, as well as HDV RNA quantification, were performed in patients who tested positive for HDV antibodies.

Of the 5,044 enrolled patients between September 24, 2021, and December 28, 2022, 4,936 patients were included in the analysis. The mean age (±standard deviation) was 42.9 ± 9.9 years, and 69.8% of patients were male. The mean alanine aminotransferase level was 34 ± 58 U/L, and 1,509 (30.6%) patients were hepatitis B e antigen-positive. The mean (standard deviation) HBsAg level at baseline was 3,535 ± 11,292 IU/mL among 4,842 patients who were HBsAg positive. The rate of HBV infection and HDV antibody positivity was 0.24% (95% confidence interval: 0.1–0.4%), and only one patient was HDV RNA positive.

The prevalence of HDV antibody positivity was 0.24% in Chinese patients with chronic HBV infection, and only one patient with both anti-HDV antibody and HDV RNA positivity was observed in this study.

Artificial intelligence (AI) is profoundly transforming the paradigm of solid tumor drug development. By integrating multi-omics data, spatial transcriptomics, and advanced computational models, AI has significantly accelerated the discovery and validation of new targets, compressing the traditional ten-year research and development cycle to two to three years. Generative AI platforms have optimized small molecule inhibitors, biologics, and messenger RNA vaccines, achieving breakthroughs in overcoming tumor heterogeneity, improving efficacy, and predicting drug resistance. However, clinical translation still faces challenges such as data bias, algorithm transparency, and the validation gap between models and real-world human experience. This review aims to systematically elaborate on the transformative role of AI in solid tumor drug development and to promote interdisciplinary cooperation as well as the construction of ethical frameworks to enable the full realization of precision oncology.

Insulinoma is a neuroendocrine tumor originating in the pancreas that secretes excess amounts of insulin, leading to severe hypoglycemia. The clinical presentation of hypoglycemia is classically described by Whipple’s Triad. Due to the rarity of this diagnosis, it can often be mistaken for other etiologies with similar presentations. In this paper, we present the case of a woman in her 70s with metastatic insulinoma involving the liver, who was initially diagnosed with an insulin-like growth factor 2-secreting hepatocellular carcinoma. Biochemical and immunohistochemical analyses were instrumental in distinguishing between these two etiologies.

Blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) is essential for non-invasively investigating brain function. However, conventional fMRI methods are limited by low spatial and temporal resolution. This narrative review evaluates recent advancements in deep learning techniques for high-resolution BOLD-fMRI reconstruction, focusing on super-resolution, segmentation, and image registration. A comprehensive literature search was conducted across PubMed, IEEE, Scopus, and Web of Science databases for the period 2000–2023. Studies employing deep learning methods, including convolutional neural networks, transformer-based models, and generative adversarial networks for super-resolution, segmentation, and registration of BOLD-fMRI, were included. Deep learning approaches demonstrated significant improvements in spatial resolution, segmentation accuracy, and registration robustness. Convolutional neural network-based models, particularly generative adversarial networks, notably improved image reconstruction quality and detail preservation. Preliminary studies targeting specific brain regions such as the cerebellum and hippocampus showed promise; however, systematic evaluations across broader brain areas and large-scale clinical validations remain limited. While deep learning techniques have led to substantial advancements in high-resolution BOLD-fMRI reconstruction, future research should focus on standardized protocols, multi-center validation, and improving computational efficiency and model generalization to enhance clinical utility.