Intrahepatic cholangiocarcinoma (iCCA) is the second most prevalent primary liver cancer, characterized by insidious onset and high malignancy. Many patients are diagnosed at an inoperable stage, and the effectiveness of chemotherapy and radiotherapy remains limited. This study aimed to provide a comprehensive review of the histological classification, genetic alterations, molecular subtypes, and corresponding imaging signatures of iCCA, highlighting its heterogeneity and offering insights into targeted therapy and personalized treatment. The heterogeneity of iCCA poses significant challenges to both targeted therapy and immunotherapy, necessitating in-depth exploration at the molecular and subtyping levels. Investigating genetic variations, signaling pathway alterations, and molecular subtypes can aid in patient stratification. Stratifying iCCA patients allows for more precise treatment selection, ultimately improving survival outcomes. Imaging, as a non-invasive tool, holds substantial potential for predicting subtypes and molecular profiles. It is possible to infer histological and molecular features from imaging, or to interpret imaging signatures in light of known histological and molecular data. This integrative approach, combining external imaging with internal molecular insights, fosters a comprehensive understanding of iCCA’s characteristics and enhances clinical management.

Craniopharyngioma (CP), although histologically benign, is a surgically challenging sellar-region tumor for which stereotactic irradiation is increasingly used as an alternative or adjuvant strategy. This review summarizes the role of stereotactic radiosurgery (SRS) in managing CP, with a focus on treatment outcomes, technical advances, and emerging strategies to support evidence-based clinical practice. Literature reports indicate that Gamma Knife radiosurgery achieves variable tumor control rates (36–100%), with optimal outcomes (79.6–91.4%) when marginal doses ≥12 Gy are delivered and patients receive adequate follow-up. Smaller tumors (<5 cm3) and those with higher solid components show particularly favorable outcomes. SRS demonstrates a favorable safety profile, with visual impairment occurring in approximately 4% of cases and endocrine dysfunction in 6%. Compared to conventional radiotherapy, SRS significantly reduces the risk of hypothalamic obesity in pediatric patients. The identification of BRAF mutations in papillary CPs has created novel opportunities for combining targeted therapies with SRS. Collectively, these advances underscore the role of SRS as an essential component of multidisciplinary CP management, particularly in the treatment of residual or recurrent lesions. It offers a more favorable toxicity profile and may improve quality of life outcomes compared to conventional radiotherapy. Further studies are needed to optimize patient selection, dosing strategies, and integration with novel systemic therapies.

Mesonephric carcinoma (MC) is a rare type of cervical carcinoma that arises from mesonephric remnants. It is characterized by a mixture of a wide variety of growth patterns and typically exhibits positive immunoreactivity for GATA binding protein 3, thyroid transcription factor 1, and apical common acute lymphoblastic leukemia antigen. A subset of adenocarcinomas in the uterine corpus and ovary with similar morphology and immunophenotype is classified as mesonephric-like adenocarcinoma (MLA) in the current World Health Organization classification. This review aimed to summarize the clinicopathological features of mesonephric remnants, mesonephric hyperplasia, and MC, provide an update on the current understanding of MLA, and highlight the molecular differences between MC and MLA.

A literature review was conducted on mesonephric remnants, mesonephric hyperplasia, MC, and MLA. The clinicopathological and molecular features were summarized from previously published studies and compared across these entities.

Both MC and MLA exhibit a mixture of growth patterns and show immunoreactivity for GATA binding protein 3, thyroid transcription factor 1, and common acute lymphoblastic leukemia antigen. They commonly harbor genetic alterations in KRAS and NRAS. However, key differences exist between these two entities. MC is associated with mesonephric remnants, whereas no such association has been identified for MLA. Additionally, although KRAS and NRAS mutations are common in both, a subset of MLA cases also harbors PIK3CA and/or PTEN mutations, genetic alterations commonly seen in endometrioid adenocarcinoma.

Although the exact pathogenesis of MLA remains unclear, it is favored to originate from Müllerian-derived epithelium undergoing differentiation along the mesonephric pathway, rather than from true mesonephric remnants. Both MC and MLA tend to follow a relatively aggressive clinical course, underscoring the importance of accurate diagnosis.

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.

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.

Autoimmune hepatitis (AIH) is a chronic, progressive inflammatory liver disease characterized by autoimmune-mediated hepatic injury. Currently, glucocorticoid drugs, primarily prednisone, with or without azathioprine, are commonly recommended as first-line therapeutic agents in treatment guidelines by many scientific associations. However, the primary objective of treatment is to achieve a complete biochemical response, which is defined as the normalization of both transaminases and immunoglobulin G levels within six to twelve months. Ideally, this should also be accompanied by histological remission. Nevertheless, corticosteroid therapy is associated with significant adverse effects, potentially resulting in treatment discontinuation. In this context, it has become evident that standard treatment is inadequate for a proportion of patients, leading to the emergence of other treatment options and lines. Novel immunomodulatory agents, a class of drugs that regulate the body’s immune functions, have been confirmed to possess properties that modulate immune balance and induce immune tolerance. In recent years, these agents have played an increasingly significant role in the clinical management of AIH. This article provided an in-depth review of recent advancements in the development of novel immunomodulators, including immune cell nucleic acid inhibitors, calmodulin phosphate inhibitors, mammalian target of rapamycin inhibitors, tumor necrosis factor-α inhibitors, interleukin-2, anti-CD20 monoclonal antibodies, and B cell-activating factor inhibitors, for the treatment of AIH.

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.

Soft tissue cytopathology plays a vital role in the diagnosis and management of soft tissue neoplasms, necessitating a standardized classification system to improve diagnostic accuracy and guide clinical decision-making. This article provides a concise review of the World Health Organization (WHO) Reporting System for Soft Tissue Cytopathology and presents a practical diagnostic approach to soft tissue cytopathology.

The WHO Reporting System is reviewed in conjunction with relevant literature. The reporting system employs a six-category framework: non-diagnostic, benign, atypical, soft tissue neoplasm of uncertain malignant potential, suspicious for malignancy, and malignant.

Each category is associated with a corresponding risk of malignancy and recommended clinical management guidelines. This classification aligns with the WHO Classification of Soft Tissue and Bone Tumours (5th edition) and incorporates cytomorphologic features, ancillary studies, and clinical correlation to enhance diagnostic reproducibility and communication among pathologists and clinicians. The system supports a probabilistic approach to risk stratification, enabling more consistent diagnostic and therapeutic strategies.

This framework provides a robust foundation for the interpretation of soft tissue fine-needle aspiration biopsies and optimized patient care.

Portal hypertension can cause serious complications such as upper gastrointestinal bleeding, primarily due to esophageal and gastric varices. The risk of mortality from variceal hemorrhage is significant, particularly when the hepatic venous pressure gradient exceeds 12 mmHg. Established treatments generally include endoscopic variceal band ligation and cyanoacrylate glue for gastric varices; however, challenges such as limited availability and a lack of technical expertise can hinder the use of glue, leading to preventable complications. This study investigates the efficacy of using a 50% glucose solution for injection sclerotherapy in cases of gastric varices. We present three unique patient cases. The first case involves a 21-year-old with persistent upper gastrointestinal bleeding and a portal vein thrombus, who experienced temporary relief after receiving injection sclerotherapy but tragically succumbed to significant bleeding later. The second case describes a 24-year-old who successfully managed his bleeding with the same treatment but was subsequently lost to follow-up. Lastly, a 72-year-old patient with recurrent painless hematemesis remained free of symptoms following injection sclerotherapy. Overall, while cyanoacrylate glue remains the preferred treatment, injection sclerotherapy with 50% dextrose shows promise as an effective alternative, particularly in settings where conventional treatments are not readily available, potentially reducing the risks associated with untreated variceal bleeding.