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.

Hepatocellular carcinoma (HCC) remains challenging to treat in advanced stages, primarily due to the development of resistance to sorafenib. There is an urgent need for novel therapeutic strategies to overcome this resistance. This study aimed to investigate the potential of oleanolic acid (OA), a natural hepatoprotective compound, in mitigating sorafenib resistance and elucidate its underlying molecular mechanisms.

Sorafenib-resistant Huh7 and HepG2 cell lines were established to mimic the resistant phenotype. The effects of OA on these cells were evaluated by assessing cell invasion, migration, and sensitivity to sorafenib. Gene expression analysis was conducted to identify molecular changes induced by OA treatment, with a focus on fabp3 expression.

Oleanolic acid significantly inhibited the invasive and migratory capabilities of sorafenib-resistant Huh7 and HepG2 cells (p < 0.01). Furthermore, OA treatment downregulated fabp3 expression and restored the cells’ sensitivity to sorafenib.

Oleanolic acid shows promise as an adjunct therapy for overcoming sorafenib resistance in HCC. By reducing cell aggressiveness and restoring drug sensitivity, OA may enhance the therapeutic efficacy of current treatments for advanced HCC.

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.

Heme oxygenase 1 (HO-1) has an influential yet insufficiently investigated effect on Sirtuin 1 (SIRT1), a histone deacetylase activated by nicotinamide adenine dinucleotide, which may impact the transforming growth factor-β (TGF-ß)/Smad3 pathway in nonalcoholic fatty liver disease (NAFLD)-related liver fibrosis. This study aimed to elucidate the regulation of NAFLD-related liver fibrosis induced by HO-1 through the SIRT1/TGF-ß/Smad3 pathway.

HO-1 induction and inhibition were established in C57BL/6J mice fed a methionine- and choline-deficient (MCD) diet. Additionally, wild-type mice were fed either a normal diet or an MCD diet. Hematoxylin and eosin, Masson’s trichrome, and Sirius Red staining were used to assess hepatic steatosis, inflammation, and fibrosis. In vitro, plasmid overexpression and small interfering RNA silencing of HO-1 were performed in LX-2 cells. Cell viability was assessed using the Cell Counting Kit-8, and apoptosis was evaluated via terminal deoxynucleotidyl transferase dUTP nick-end labeling and immunofluorescence. Flow cytometry was employed to assess apoptosis and reactive oxygen species production. Western blot and real-time quantitative reverse transcription polymerase chain reaction were used to analyze the mRNA and protein expression of genes related to HO-1, SIRT1, the TGF-ß signaling pathway, and fibrosis.

MCD-fed mice developed significant liver damage, including steatosis, inflammatory infiltration, and pericellular fibrosis. Zinc protoporphyrin treatment exacerbated these conditions. Corroborating these findings, silencing HO-1 in LX-2 cells increased the expression of fibrosis-related genes. Furthermore, HO-1 overexpression not only increased SIRT1 expression but also reduced the activity of key regulatory factors in the TGF-ß signaling pathway, suggesting a potential interaction between HO-1 and the SIRT1/TGF-ß pathway.

HO-1 inhibits the activation of the TGF-ß/Smad3 pathway in NAFLD-related liver fibrosis through SIRT1. These findings provide insights into new therapeutic strategies for treating NAFLD-associated liver fibrosis.

The tumor microenvironment (TME) consists of a complex mix of cellular and non-cellular components, including immune cells, stromal cells, extracellular matrix, cytokines, and growth factors. These elements interact with tumor cells to influence tumorigenesis, growth, invasion, and metastasis. Long noncoding RNAs (lncRNAs)—a class of non-coding RNAs longer than 200 nucleotides—have attracted considerable attention for their roles in regulating gene expression at the epigenetic, transcriptional, and post-transcriptional levels. Emerging evidence suggests that lncRNAs are crucial in shaping the TME by modulating processes such as immune evasion, angiogenesis, metabolic reprogramming, and the maintenance of cancer stem cells. This review provides an overview of the current understanding of lncRNAs in the TME, focusing on their involvement in key signaling pathways and cellular interactions that drive tumor progression. We discussed how lncRNAs contribute to extracellular matrix remodeling, facilitate communication between tumor and stromal cells, and regulate immune cell infiltration and function within the TME. Additionally, we explore the potential of lncRNAs as biomarkers for early cancer detection and prognosis, as well as their promise as therapeutic targets to disrupt tumor-microenvironment crosstalk. The review also addresses challenges in targeting lncRNAs therapeutically, such as ensuring specificity, minimizing off-target effects, and achieving effective in vivo delivery of lncRNA-targeted therapies. Strategies to overcome these challenges include the development of highly specific lncRNA knockout technologies and the use of advanced delivery systems, such as nanoparticles and viral vectors, to precisely target tumor-associated cells. Overall, this review underscores the significant role of lncRNAs in the TME and their potential as novel tools for enhancing cancer diagnosis and treatment. By elucidating the multifaceted roles of lncRNAs in the TME, we aimed to provide insights that could lead to more effective, targeted therapeutic strategies, ultimately advancing cancer research and improving patient care.

Chronic liver cirrhosis (LC) and acute-on-chronic liver failure (ACLF) are interconnected hepatic disorders associated with substantial morbidity and mortality. Despite their distinct clinical characteristics, both conditions share common pathogenic pathways that remain inadequately understood. This study aimed to identify shared gene signatures and elucidate underlying molecular mechanisms.

In this study, we employed Weighted Gene Co-Expression Network Analysis to explore transcriptomic data from the Gene Expression Omnibus for LC and ACLF.

Key co-expression modules enriched with genes involved in glycolysis and gluconeogenesis pathways were identified, implicating metabolic dysfunction as a central feature in both conditions. Furthermore, microRNA analysis revealed that hsa-miR-122 and hsa-miR-194 play pivotal roles in regulating these metabolic pathways, potentially contributing to immune dysregulation.

Our findings indicate that these shared molecular mechanisms are critical in the progression from LC to ACLF, providing novel insights into potential therapeutic targets for mitigating disease severity and improving clinical outcomes.

Prostate cancer (PCa) often manifests insidiously, with most patients being diagnosed at an advanced stage, leading to a poor prognosis. Early detection of PCa can significantly prolong overall survival by impeding the progression of metastasis. A commonly utilized screening method for detecting PCa is the prostate-specific antigen test. However, since the prostate-specific antigen lacks specificity and sensitivity for PCa identification, there is a paramount urgency to develop precise diagnostic biomarkers for early detection. Extracellular vesicles, known as exosomes, are released by cells into body fluids. Exosomes derived from cancer cells can carry genetic information about the tumor, including DNA, RNA, and proteins, which play crucial roles in tumor initiation, invasion, metastasis, and drug resistance. Studies have indicated that exosomes (including messenger RNAs, microRNAs, long noncoding RNAs and others) can enhance the sensitivity and specificity of PCa diagnosis, indicating their potential for early detection. This review highlights the biological characteristics and functions of exosomes, as well as recent advancements in their use for the diagnosis, prognosis, and treatment of prostate cancer.

End-stage liver disease is associated with disruptions in gut microbiota composition and function, which may facilitate gut-to-liver bacterial translocation, impacting liver graft integrity and clinical outcomes following liver transplantation. This study aimed to assess the impact of two liver graft preservation methods on fecal microbiota and changes in fecal and breath organic acids following liver transplantation.

This single-center, non-randomized prospective pilot study enrolled liver transplant patients whose grafts were preserved using either static cold storage or ex situ normothermic machine perfusion (NMP). Fresh stool and breath samples were collected immediately before surgery and at postoperative months 3, 6, and 12. Stool microbiota was profiled via 16S rRNA gene sequencing, stool short-chain fatty acids were measured using gas chromatography/-mass spectrometry, and breath volatile organic compounds (VOCs) were analyzed with selected-ion flow-tube mass spectrometry.

Both cohorts experienced a loss of microbiota diversity and dominance by single taxa. The NMP cohort demonstrated enrichment of several beneficial gut taxa, while the static cold storage cohort showed depletion of such taxa. Various gut bacteria were found to correlate with stool short-chain fatty acids (e.g., lactic acid, butyric acid) and several VOCs.

Fecal microbiota alterations associated with end-stage liver disease do not fully normalize to a healthy control profile following liver transplantation. However, notable differences in microbiota composition and function were observed between liver graft preservation methods. Future research with larger randomized cohorts is needed to explore whether the NMP-associated shift in gut microbiota impacts clinical outcomes and if breath VOCs could serve as biomarkers of the clinical trajectory in liver transplant patients.

The number of molecular abnormalities identified in hematopoietic and lymphocytic neoplasms has grown exponentially over the past decades. Patients with genetic biomarker-matched targeted therapies have experienced significantly improved survival rates. Modern molecular laboratories, equipped with advanced technologies such as next-generation sequencing, can simultaneously test hundreds of genes and thousands of hotspots in a single run with multiple samples analyzed side by side. Bioinformatics tools provide seamless, evidence-based information to determine whether the detected mutations are benign or pathogenic, somatic or germline, druggable or diagnostic. This review is divided into five sections, each aiming to provide a comprehensive overview of the genetic landscape of myeloid and lymphocytic neoplasms. It highlights the challenges and proposes potential solutions to facilitate interpretation and maximize the clinical utility of molecular profiling results.