N6-methyladenosine (m6A), the most prevalent internal RNA modification in eukaryotic cells, is a dynamic regulator of RNA metabolism and cancer biology. In colorectal cancer (CRC), dysregulated m6A reshapes transcriptomic programs that control tumor growth, metastasis, immune evasion, and therapeutic resistance. However, the context-dependent functions of individual m6A regulators remain incompletely defined, the integration of m6A with canonical oncogenic signaling remains incomplete, and its role in metabolic reprogramming lacks a systematic overview. This review aims to integrate current evidence on m6A regulatory machinery in CRC, clarify its coordination with oncogenic signaling and metabolic pathways, and highlight emerging translational implications. The key players regulating m6A in CRC progression are m6A “writers”, including methyltransferase-like 3 and methyltransferase-like 14; m6A “erasers”, including fat mass and obesity-associated protein and AlkB homolog 5; and m6A “readers”, including the YTH m6A RNA-binding protein family and the insulin-like growth factor 2 mRNA-binding protein family. m6A modification coordinates key oncogenic pathways, including Wnt/β-catenin, PI3K/Akt, MAPK, and p53 signaling. Moreover, m6A-dependent regulation of metabolic enzymes such as hexokinase 2, pyruvate kinase M2, and fatty acid synthase promotes the reprogramming of glucose, amino acid, and lipid metabolism, linking epitranscriptomic control to bioenergetic adaptation. We also discuss context-dependent and paradoxical functions of m6A regulators and advances in m6A-targeted therapies. In conclusion, m6A modification functions as a central regulatory hub in CRC by integrating signaling networks and metabolic pathways. Deeper mechanistic insights into spatiotemporal m6A regulation may accelerate the development of biomarkers and targeted therapies for precision CRC management.

End-stage liver disease (ESLD) is characterized by a dramatic deterioration of liver function, frequently accompanied by systemic inflammatory storms and multiple organ failures. Central to the onset and progression of ESLD, systemic inflammation arises from complex interactions among various inflammatory signaling molecules and immune cells within and beyond the liver. As key inflammatory modulatory molecules, bioactive oxylipins have been increasingly recognized for their complex molecular mechanisms implicated in various diseases. This review aims to summarize recent findings regarding the molecular and immunological mechanisms through which oxylipins contribute to the development of liver injury and failure, with emphasis on both substantial intrahepatic and extrahepatic immune and inflammatory dysregulation associated with ESLD. Furthermore, this review discusses the translational potential of targeting oxylipins for clinical diagnosis, prognosis, and therapeutic intervention in ESLD.

Microbial resistance and oxidative stress are two significant health issues associated with chronic illnesses and therapy failures. The antioxidant and antibacterial properties of Euphorbia cuneata Vahl. aerial component extracts made with various polarity solvents were assessed in this work.

Disc diffusion and minimum inhibitory concentration (MIC) tests were used to evaluate the 1,1-diphenyl-2-picrylhydrazyl radical scavenging activity, total phenolic and flavonoid contents, and antimicrobial activity of n-hexane, toluene, ethanolic, and aqueous extracts against specific ESKAPE pathogens (Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa, and Candida albicans). High-performance liquid chromatography and gas chromatography-mass spectrometry were used to further characterize the most active extract.

Compared to the aqueous (IC₅₀ = 51.61 µg/mL), toluene (IC₅₀ = 30.57 µg/mL), and n-hexane (IC₅₀ = 128.15 µg/mL) extracts, the ethanolic extract demonstrated the greatest 1,1-diphenyl-2-picrylhydrazyl radical scavenging activity (97.90 ± 0.8%; IC₅₀ = 28.52 µg/mL). Additionally, it has the highest levels of flavonoids (40.5 ± 1.5 mg luteolin equivalents/g) and phenolic (80.0 ± 0.2 mg gallic acid equivalents/g). While gas chromatography-mass spectrometry found methyl 12-hydroxy-9-octadecenoate (44.39%) as the main volatile molecule, high-performance liquid chromatography analysis identified caffeic acid, pyrogallol, rutin, and 7-hydroxyflavone as important ingredients. The ethanolic extract showed antifungal activity against C. albicans (MIC = 6.25 mg/mL) and moderate antibacterial activity with the lowest MIC values against S. aureus (450 µg/mL) and E. coli (500 µg/mL).

The ethanolic extract of Euphorbia cuneata demonstrated potent in vitro antioxidant activity and moderate antimicrobial effects, primarily attributable to its high phenolic and flavonoid content. These results support its potential as a natural source of bioactive compounds for further development.

Given the lack of efficient biomarkers for hepatocellular carcinoma (HCC) diagnosis, this study aimed to develop an HCC diagnostic strategy based on serum protein glycosylation signatures. We characterized differential N-glycosylation patterns of serum IgG to differentiate HCC from healthy controls and liver cirrhosis, and elucidated the molecular mechanisms driving aberrant Neu5Gc elevation in HCC to provide a theoretical basis for clinical application and differential diagnosis of HCC.

LIP-ELISA was applied to quantify serum Neu5Gc in 6,768 healthy individuals for baseline establishment. IgG was purified and subsequently analyzed by RPLC-MS/MS for glycosylation profiling in HCC and healthy samples. Bioinformatic analysis of CMAH and related gene clusters modulating Neu5Gc synthesis was conducted.

In a cohort of 1,114 participants, the LIP-ELISA platform achieved 80.21% sensitivity, 96.01% specificity, and 92.46% accuracy for primary HCC diagnosis. Serum IgG from HCC patients displayed multi-branched N-glycans modified with core fucose and Neu5Gc. Key molecules involved in glycan modification were identified, enabling the development of multiplexed gene detection for HCC, LC, and chronic hepatitis B. In vitro assays confirmed hypoxia-induced sialic acid accumulation in HCC cells. Meanwhile, CMAH-knockout mouse experiments verified that an exogenous high-sialic-acid diet compensates for endogenous Neu5Gc synthesis deficiency, revealing a dietary-mediated compensatory mechanism for Neu5Gc elevation.

This study established an LIP-ELISA-based clinical diagnostic platform combining AFP and Neu5Gc, defined sialic acid–modified glycan structures, and preliminarily identified regulators of Neu5Gc biosynthesis, providing novel insights for HCC diagnosis and mechanism research.

For individuals with decompensated advanced chronic liver disease (dACLD), the onset of refractory ascites (RA) represents a dramatic event. In this setting, a relevant proportion of RA patients develop kidney dysfunction, as well as hepatorenal syndrome-acute kidney injury, with limited therapeutic and survival chances. An 81-year-old woman with dACLD-RA was admitted with severe ascites and stage IV chronic kidney dysfunction. On the second day, hepatorenal syndrome-acute kidney injury occurred, requiring standard medical therapy. Intravenous human albumin (HA) and terlipressin administration were compromised by poor venous access and severe respiratory dysfunction. After excluding transjugular intrahepatic portosystemic shunt and transplantation due to age and comorbidities, peritoneal dialysis (PD) was initiated, leading to renal recovery and ascites resolution. Two weeks later, she was readmitted due to the unfeasibility of accessing peripheral veins for the intravenous administration of HA, which was essential to support circulatory function, preserve oncotic balance, and properly manage both RA and chronic kidney dysfunction. A novel PD+HA protocol was therefore started, with intraperitoneal infusion of HA-enriched dialysate to allow a positive albumin gradient from dialysate to blood. Over 12 months, serum albumin levels increased, and clinical stability and improved nutritional status were observed, with no additional hospitalizations or complications. This is the first case describing the application of HA-enriched PD in managing a dACLD patient with RA and kidney dysfunction. HA-enriched PD may represent a promising strategy in complex dACLD care by guaranteeing frequent and small-volume paracentesis and preservation of oncotic pressure without dialytic albumin loss.

Hepatic iron deposition (HID) in the reticuloendothelial system (RES) is associated with histological severity in metabolic dysfunction-associated steatotic liver disease (MASLD). This study aimed to assess the interaction between the transferrin (TF)-rs1049296 C>T variant and HID patterns on the risk of significant liver fibrosis in MASLD.

We analyzed 406 adults with liver biopsy-confirmed MASLD. HID was categorized as hepatocellular, RES, or mixed, based on Perl's iron staining. The association between iron-related genetic variants and significant liver fibrosis (fibrosis stage ≥ F2) was analyzed, focusing on the interactions between single-nucleotide polymorphism genotypes and iron deposition patterns. Multivariable logistic regression analysis was used to adjust for potential confounders.

HID was detected in 271 (66.7%) patients, with hepatocellular, RES, and mixed patterns accounting for 11.1%, 18.0%, and 37.7%, respectively. A significant interaction was observed between HID and the TF-rs1049296 genotype (P = 0.035 for interaction). In multivariable analysis, male sex, hypertension, severe lobular inflammation, and mixed hepatocellular/RES iron deposition were independent predictors of significant liver fibrosis. RES deposition markedly increased the risk of significant liver fibrosis (adjusted odds ratio: 6.65; 95% confidence interval: 1.84–23.97, p < 0.05), particularly in men with isolated RES iron deposition (adjusted odds ratio: 5.26; 95% confidence interval: 1.21–22.81, p < 0.05).

The TF-rs1049296 T allele interacts with RES iron deposition to identify a MASLD subpopulation at elevated risk of progressive liver disease, providing opportunities for refined risk stratification and personalized management.

Antimitochondrial antibody (AMA)-negative primary biliary cholangitis (PBC) is a rare presentation of PBC that comprises 5%–10% of all PBC patients. The pathogenesis of AMA-negative PBC appears to be similar to that of AMA-positive PBC. AMA-negative PBC presents similarly to AMA-positive PBC, with symptoms of cholestasis, fatigue, and pruritus most commonly reported. Defective bicarbonate production, resulting in acidification of bile and bile acids, has been proposed as the primary mechanism of damage to bile ducts and hepatocytes and is reflected in elevations of alkaline phosphatase and aminotransferases. Chronic damage can lead to the development of cirrhosis. The diagnosis is made by the finding of AMA negativity by ELISA or assays of similar sensitivity and a positive PBC-specific antinuclear antibody (ANA; anti-glycoprotein 210 and anti-speckled 100 kDa protein) test. In cases in which anti-glycoprotein 210 and anti-speckled 100 kDa protein assays are also negative, a liver biopsy is required to make the diagnosis after exclusion of other causes of cholestasis by magnetic resonance cholangiopancreatography or endoscopic retrograde cholangiopancreatography. Treatment for AMA-negative PBC is the same as for AMA-positive cases, with ursodeoxycholic acid as the first-line treatment. Current treatment is most effective in early stages, where it slows but does not eliminate progression. Risk stratification by validated tools such as the GLOBE and UK-PBC scores remains useful in AMA-negative PBC.

The prognostic nutritional index (PNI), calculated from serum albumin and lymphocyte count, reflects a patient’s immune-nutritional status and has been proposed as a prognostic marker in hepatocellular carcinoma (HCC). However, its role in advanced HCC patients treated with atezolizumab plus bevacizumab (Ate/Bev) remains unclear. In this study, we aimed to evaluate the prognostic value of PNI in patients receiving first-line Ate/Bev therapy.

We retrospectively analyzed 362 patients with unresectable HCC who received Ate/Bev between November 2020 and June 2023 across two centers. Based on prior literature, a cutoff of 45 was used to classify patients into low-PNI (<45) and high-PNI (≥45) groups. Propensity score matching was performed to balance baseline characteristics.

After propensity score matching, 130 patients (65 per group) were included in the analysis. The high-PNI group showed a significantly lower incidence of grade ≥ 3 treatment-related adverse events (10.8% vs. 24.6%, p = 0.039), a higher objective response rate (38.4% vs. 20.0%, p = 0.037), and significantly longer overall survival (16.7 vs. 7.9 months, p = 0.009). Although progression-free survival was longer in the high-PNI group (4.8 vs. 3.0 months), the difference was not statistically significant (p = 0.597). Multivariate analysis confirmed that PNI was an independent predictor of overall survival (hazard ratio: 0.574, 95% confidence interval: 0.353–0.933, p = 0.025), after adjusting for vascular invasion, alpha-fetoprotein levels, concurrent therapy, and post-treatment interventions.

PNI is an independent prognostic factor for overall survival in advanced HCC patients treated with Ate/Bev in real-world clinical practice. Incorporating PNI into routine assessments may enhance risk stratification and guide therapeutic decision-making.

Normalization can standardize and improve machine learning (ML) performance on omics data. However, it is unclear whether normalization is associated with overfitting (i.e., worse cross-dataset performance than intra-dataset performance). Therefore, we aimed to examine associations of normalization and regularization with overfitting of ML on omics data.

Using three paired transcriptomic and clinical datasets (lung adenocarcinoma: the Cancer Genome Atlas (TCGA)/Oncology Singapore; melanoma: TCGA/Dana-Farber Cancer Institute; glioblastoma: TCGA/Clinical Proteomic Tumor Analysis Consortium), we applied ANOVA-based gene selection methods, six normalization methods, and six ML models to classify cancer patients’ deaths. Balanced accuracy (BA) and area under the curve (AUC) in intra- and cross-dataset settings were compared using inferential analyses.

Normalization consistently improved intra-dataset performance (median BA/AUC changes: 0.035–0.214/0.115–0.279) on all data, particularly with Z_Raw, but decreased or slightly increased cross-dataset performance (median BA/AUC changes: −0.029–0.079/0.029–0.064). Least Absolute Shrinkage and Selection Operator (LASSO) model without normalization consistently outperformed most of the ML models in cross-dataset testing across cancer types. ML models on all and molecular-alone data showed similar best performances.

Normalization increases ML’s intra-dataset performance and overfitting in three paired cancer transcriptomic and clinical datasets. Regularized models such as LASSO appear to mitigate overfitting and achieve robust cross-dataset performance. Therefore, cross-dataset evaluation and regularized models are recommended to assess and reduce overfitting, while normalization should be used cautiously. Adding clinical data seems to have little impact on ML models’ performance. However, future work on other diseases and datasets is warranted.