Unlike the traditional staging treatment of tumors, the core of “Green Tumor Treatment” is to divide the treatment of tumors into three stages: Hegemony (directly targeting the cancer focus), Kingship (supporting the body’s vital energy and eliminating pathogenic factors), and Imperialism (improving the internal environment), based on the urgency of the tumor and the patient’s physical condition. This approach guides the clinical treatment of tumors. Its treatment system incorporates all minimally invasive and low-damage treatment methods, combining internal and external treatments, traditional Chinese medicine and Western medicine, as well as local and systemic treatments. It aims to maximize treatment outcomes while ensuring the patient’s quality of life, which is highly consistent with the treatment goals for primary liver cancer. This review aims to explore the integrated Traditional Chinese and Western medicine treatment model for primary liver cancer under the guidance of the Green Tumor Treatment concept.

Nonalcoholic fatty liver disease (NAFLD) is a prevalent metabolic disorder with a complex pathogenesis. Although epitranscriptomic modifications such as N6-methyladenosine (m6A) have been implicated in NAFLD, the role of N1-methyladenosine (m1A) and its regulators is largely unexplored. Recently, YTHDF1, a well-characterized m6A reader, was also shown to recognize m1A; however, the functional consequences of this dual specificity are unknown. This study aimed to investigate the role of YTHDF1 in NAFLD pathogenesis and to explore whether its function is mediated through recognition of RNA methylation modification on specific target mRNAs.

Expression of YTHDF1 in NAFLD was analyzed in the GEO database. Loss-of-function studies for YTHDF1 were conducted in vivo (high-fat diet-fed mice) and in vitro (free fatty acid-treated HepG2 cells) in models of NAFLD. We employed RNA-seq and m1A-MeRIP-seq to identify key targets, followed by mechanistic validation of the YTHDF1–m1A–NUPR1 axis using biochemical, histological, and mRNA stability assays.

We identified a critical role for YTHDF1 in promoting hepatic steatosis. NUPR1, a stress-induced transcriptional regulator, undergoes m1A modification. YTHDF1 directly binds to m1A-modified NUPR1 mRNA, enhancing its stability, thereby leading to elevated NUPR1 protein levels. Functionally, upregulated NUPR1 acts as a core driver of NAFLD pathogenesis by activating lipogenic and suppressing fatty acid β-oxidation genes, thereby exacerbating hepatic lipid accumulation.

Our study unveils a novel epitranscriptomic mechanism in which YTHDF1, functioning as a dual-specificity reader, governs NAFLD progression through the m1A-NUPR1 axis. This not only expands the understanding of RNA modification recognition but also establishes the YTHDF1–m1A–NUPR1 pathway as a promising therapeutic target for metabolic liver disease.

Primary sclerosing cholangitis (PSC) is an immune-mediated cholestatic liver disease. Its molecular etiology remains poorly defined, hindering the development of mechanism-based diagnostics and therapies. Therefore, this study aimed to identify key molecular drivers and causal biomarkers of PSC by integrating transcriptomics, machine learning, and genetic causal inference.

We deployed an integrated computational framework combining transcriptomics, network biology, machine learning, and genetic causal inference. Peripheral blood transcriptomes from PSC patients and controls were analyzed to identify disease-associated modules. Candidate genes were refined via protein-protein interaction networks and a multi-algorithm machine learning screen. Causal inference was performed using two-sample Mendelian randomization, integrating plasma protein quantitative trait loci with PSC genome-wide association study summary statistics.

Transcriptomic analysis revealed a PSC-associated module enriched in ribosome biogenesis and protein homeostasis pathways. A machine learning-optimized nine-gene signature (including PTMA, SUMO1, Shwachman-Bodian-Diamond syndrome (SBDS), RPL7, EIF1AX, ANP32A, PCNA, FAM98A, and MPHOSPH6) achieved high diagnostic accuracy (mean AUC = 0.908) and was consistently downregulated in PSC. This signature was linked to a remodeled immune microenvironment characterized by myeloid skewing and specific transcriptional-immune covariation patterns. Mendelian randomization identified SBDS as a putatively causal protective factor, where genetically instrumented higher plasma SBDS protein levels were robustly associated with a lower PSC risk (IVW OR = 0.525, 95% CI: 0.356–0.773, P = 0.001). Sensitivity analyses supported the validity of the Mendelian randomization assumptions.

Our study establishes disrupted ribosome homeostasis as a causal pathway in PSC and nominates plasma SBDS as a high-confidence diagnostic biomarker and therapeutic target. The integrative framework provides a generalizable strategy for discovering causal biomarkers in complex diseases.

The optimal surgical management for spontaneous supratentorial intracerebral hemorrhage (SSICH) remains controversial because conventional approaches often fail to balance rapid decompression with effective hematoma evacuation. This study aimed to evaluate the efficacy and safety of new combined surgical strategies (“two-in-one” and “three-in-one”) versus conventional methods for SSICH.

This retrospective cohort study included 451 SSICH patients treated between January 2019 and December 2023. Based on clinical severity, patients were stratified into Group I (non-herniation, n = 374) and Group II (herniation, n = 77). Within each subgroup, patients were further categorized by treatment period: a historical control cohort (2019–2020) receiving conventional surgery, and an intervention cohort (2021–2023) receiving combined strategies (“two-in-one” for Group I; “three-in-one” for Group II). Outcomes included decompression time, hematoma evacuation rate, complications, and six-month functional recovery (Glasgow Outcome Scale/modified Rankin Scale), were compared.

In Group I, the “two-in-one” strategy achieved faster decompression (4.65 min) and a high evacuation rate (92.15%), which was comparable to neuroendoscopy alone (90.58%) and significantly higher than stereotactic aspiration alone (44.55%). This was associated with improved six-month outcomes (poor outcome rates were 39.39%, 54.35%, and 42.86% in Groups I-A, I-B, and I-C, respectively, overall P = 0.034). In Group II, the “three-in-one” strategy demonstrated shorter decompression time (4.73 vs. 37.85 min, P < 0.001) and higher evacuation rates (80.51% vs. 63.50%, P < 0.001) than decompressive craniectomy alone. Logistic regression further supported the prognostic advantage of the “two-in-one” strategy in Group I.

These combined strategies may integrate the advantages of multiple techniques to enable rapid decompression and effective hematoma clearance in SSICH. Prospective studies are warranted.

Metabolic dysfunction-associated steatotic liver disease (MASLD) represents a major global health concern and encompasses a spectrum ranging from hepatic steatosis and metabolic dysfunction-associated steatohepatitis to liver fibrosis, cirrhosis, and ultimately hepatocellular carcinoma. Insulin resistance, the pathogenic cornerstone of MASLD, drives enhanced peripheral lipolysis and increased hepatic de novo lipogenesis, thereby overloading the liver with lipids and inducing steatosis. Subsequent lipotoxicity, inflammation, and gut microbiota dysbiosis further exacerbate disease progression. The gut microbiota and their metabolites communicate with the liver via the gut-liver axis, forming a complex signaling network that directly or indirectly modulates hepatic metabolism, systemic immune responses, oxidative stress, and intestinal barrier integrity. In this review, we synthesize evidence for the beneficial and detrimental effects of the major human gut microbial communities and their metabolites during the course of MASLD. We delineate how these gut-derived factors regulate hepatic function through an integrated tripartite “gut-liver axis–oxidative stress–metabolic reprogramming” mechanism. These insights may inform microbiome-based precision interventions and accelerate the development of therapeutic strategies targeting MASLD.

Hepatocellular carcinoma (HCC) remains one of the most fatal cancers, primarily due to late diagnosis and the lack of effective early biomarkers. Recent advances in multi-omics and liquid biopsy technologies hold promise for improving early detection, prognostication, and monitoring of HCC. Understanding the immune landscape of HCC through genetic and epigenetic signatures is essential for identifying therapeutic targets and improving immunotherapy outcomes. This review aims to present current findings on immune-related biomarkers, multi-omics strategies, and biomarker validation in HCC. It also aims to evaluate the role of liquid biopsy and gene signatures in predicting treatment responses, with a specific focus on their applications in immunotherapy. The goal is to provide a comprehensive framework for integrating these emerging tools into clinical practice. The integration of multi-omics approaches has led to the identification of robust gene signatures that predict HCC prognosis and response to immune checkpoint inhibitors. Liquid biopsy technologies, including circulating tumor DNA, provide non-invasive alternatives for monitoring tumor evolution and therapeutic responses. Despite promising results, challenges remain in clinical validation, particularly in cross-platform reproducibility and the interpretation of complex multi-omics data. While genetic biomarkers are rapidly advancing, their clinical application in personalized medicine remains hindered by technical and ethical challenges, such as data privacy, informed consent, and method standardization. The integration of multi-omics data and liquid biopsies offers a promising path toward real-time, personalized treatment and the development of universal prognostic signatures for HCC. However, successful clinical adoption depends on cross-disciplinary collaboration to standardize data protocols and overcome challenges regarding accuracy, reproducibility, and patient privacy.

Synucleinopathies, including Parkinson’s disease (PD), dementia with Lewy bodies, and multiple system atrophy (MSA), are a group of neurodegenerative diseases characterized by the oligomerization of α-synuclein protein in neurons or glial cells. Various splicing isoforms of α-synuclein have been described, each with different aggregation properties. The α-synuclein gene (SNCA) has been identified as a highly significant genetic risk locus associated with various synucleinopathies across populations. This study aimed to assess the association of SNCA genetic variants with MSA and the levels of SNCA transcripts in peripheral blood mononuclear cells (PBMCs) from MSA and PD patients.

In this retrospective case–control study, 96 MSA patients, 1086 PD patients, and 485 healthy volunteers were included. PCR followed by restriction endonuclease analysis was used to detect four SNCA single-nucleotide polymorphisms (rs356219, rs3756063, rs11931074, and rs356168) in these individuals. In addition, RT-qPCR was performed to detect the levels of α-synuclein transcripts (SNCA mRNA isoforms -140, -126, and -112) in PBMCs of 24 MSA patients (including parkinsonian (MSA-P) and cerebellar (MSA-C) variants), 31 PD patients, and 32 healthy volunteers.

The frequency of the ‘T’ allele (of rs11931074) was significantly higher in MSA patients than in the healthy controls. The level of SNCA-140 mRNA was significantly decreased in MSA and PD patients compared with the controls, while the level of SNCA-112 mRNA was significantly increased in MSA-P patients than in PD patients and the controls. SNCA-112 mRNA/SNCA-140 mRNA and SNCA-112 mRNA/SNCA-126 mRNA ratios were significantly increased in MSA patients than in the controls.

The SNCA rs11931074 polymorphism is associated with MSA. There is a pronounced alteration in the expression of SNCA transcripts in PBMCs of MSA and PD patients.

Pancreatic cystic neoplasms (PCNs) are increasingly detected in clinical practice, yet substantial variability exists in imaging interpretation and reporting, which may affect clinical decision-making. This guideline was developed to standardize diagnostic imaging evaluation and reporting for PCNs. A multidisciplinary expert panel conducted literature search and critical appraisal of domestic and international evidence, identified key clinical questions, and formulated recommendations using the Grading of Recommendations Assessment, Development and Evaluation framework. A modified Delphi consensus process and external review were performed to ensure the robustness of the recommendations. A total of 21 key questions were addressed, covering essential aspects of imaging evaluation and reporting for PCNs, including the preferred imaging modality for suspected lesions; standardized measurement of cyst size and mural nodules and their clinical significance; definitions of cyst wall and septal thickening; optimal imaging approaches for assessing the relationship between cystic lesions and the main pancreatic duct; measurement and evaluation of main pancreatic duct diameter and dilation; imaging-based classification of intraductal papillary mucinous neoplasms and serous cystic neoplasms; assessment of ductal obstruction, calcification, hemorrhage, and pancreatitis-related changes; criteria for suspicious lymph nodes; differentiation of PCNs from pancreatic pseudocysts or retention cysts; and recommended imaging modalities and follow-up intervals. This guideline provides a structured and evidence-based framework for imaging evaluation and reporting of PCNs, which may improve the consistency and clarity of imaging reports and support clinical decision-making.