Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.

Background/Aims: Chronic hepatitis C (CHC) patients who failed antiviral therapy are at increased risk for hepatocellular carcinoma (HCC). This study assessed the potential role of metformin and statins, medications for diabetes mellitus (DM) and hyperlipidemia (HLP), in reducing HCC risk among these patients. Methods: We included CHC patients from the T-COACH study who failed antiviral therapy. We tracked the onset of HCC 1.5 years post-therapy by linking to Taiwan’s cancer registry data from 2003 to 2019. We accounted for death and liver transplantation as competing risks and employed Gray’s cumulative incidence and Cox subdistribution hazards models to analyze HCC development. Results: Out of 2,779 patients, 480 (17.3%) developed HCC post-therapy. DM patients not using metformin had a 51% increased risk of HCC compared to non-DM patients, while HLP patients on statins had a 50% reduced risk compared to those without HLP. The 5-year HCC incidence was significantly higher for metformin non-users (16.5%) versus non-DM patients (11.3%; adjusted sub-distribution hazard ratio [aSHR]=1.51; P=0.007) and metformin users (3.1%; aSHR=1.59; P=0.022). Statin use in HLP patients correlated with a lower HCC risk (3.8%) compared to non-HLP patients (12.5%; aSHR=0.50; P<0.001). Notably, the increased HCC risk associated with non-use of metformin was primarily seen in non-cirrhotic patients, whereas statins decreased HCC risk in both cirrhotic and non-cirrhotic patients. Conclusions Metformin and statins may have a chemopreventive effect against HCC in CHC patients who failed antiviral therapy. These results support the need for personalized preventive strategies in managing HCC risk.

Background/Aims: Steatotic liver disease (SLD) is a common manifestation in chronic hepatitis C (CHC). Metabolic alterations in CHC are associated with metabolic dysfunction-associated steatotic liver disease (MASLD). We aimed to elucidate whether hepatitis C virus (HCV) eradication mitigates MASLD occurrence or resolution. Methods: We enrolled 5,840 CHC patients whose HCV was eradicated by direct-acting antivirals in a nationwide HCV registry. MASLD and the associated cardiometabolic risk factors (CMRFs) were evaluated at baseline and 6 months after HCV cure. Results: There were 2,147 (36.8%) patients with SLD, and 1,986 (34.0%) of them met the MASLD criteria before treatment. After treatment, HbA1c (6.0% vs. 5.9%, p<0.001) and BMI (24.8 kg/m2 vs. 24.7 kg/m2, p<0.001) decreased, whereas HDL-C (49.1 mg/dL vs. 51.9 mg/dL, p<0.001) and triglycerides (102.8 mg/dL vs. 111.9 mg/dL, p<0.001) increased significantly. The proportion of patients with SLD was 37.5% after HCV eradication, which did not change significantly compared with the pretreatment status. The percentage of the patients who had post-treatment MASLD was 34.8%, which did not differ significantly from the pretreatment status (p=0.17). Body mass index (BMI) (odds ratio [OR] 0.89; 95% confidence intervals [CI] 0.85–0.92; p<0.001) was the only factor associated with MASLD resolution. In contrast, unfavorable CMRFs, including BMI (OR 1.10; 95% CI 1.06–1.14; p<0.001) and HbA1c (OR 1.19; 95% CI 1.04–1.35; p=0.01), were independently associated with MASLD development after HCV cure. Conclusions HCV eradication mitigates MASLD in CHC patients. CMRF surveillance is mandatory for CHC patients with metabolic alterations, which are altered after HCV eradication and predict the evolution of MASLD.

Objective:To compare and analyze the clinical characteristics between acute fatty liver of pregnancy (AFLP) and the hemolysis, elevated liver enzymes and low platelets (HELLP) syndrome.Methods:This is a retrospective cohort study. The clinical data of 13 cases with AFLP and 34 cases with HELLP syndrome were collected from three tertiary referral centers in Yunnan (the First Affiliated Hospital of Kunming Medical University, the Second Affiliated Hospital of Kunming Medical University, and Yan'an Hospital of Kunming City) from January 2016 to December 2021. The patients were diagnosed to AFLP and HELLP syndrome according to the Swansea criteria and the Tennessee classification system. The general characteristics, clinical features, laboratory results within 24 hours after admission, complications, maternal and neonatal outcomes were compared to analysis the differences between the two groups.Results:① Maternal characteristics: compared with HELLP syndrome group, AFLP group had lower body mass index (BMI) and blood pressure at admission (both P < 0.01). ②Clinical features: the most common symptoms in AFLP patients were skin jaundice, abdominal pain, nausea and vomiting, edema. The main manifestations of patients with HELLP syndrome were albuminuria, hypertension, edema, headache. Some patients had multiple symptoms concurrently. ③ Laboratory results: compared with HELLP syndrome group, the levels of platelet count (PLT), total bilirubin (TBil), direct bilirubin (DBil), γ-glutamyl transferase (γ-GGT), alkaline phosphatase (ALP), total bile acid (TBA), serum creatinine (SCr) and international standardized ratio (INR) in AFLP group were significantly increased within 24 hours after admission [PLT (×10 9/L): 107.69±51.13 vs.76.71±43.25, TBil (μmol/L): 121.60 (83.20, 170.00) vs.15.25 (7.22, 29.05), DBil (μmol/L): 86.50 (58.60, 104.00) vs. 4.30 (2.22, 10.10), γ-GGT (U/L): 87.00 (37.00, 127.00) vs. 41.00 (19.00, 64.42), ALP (U/L): 199.10 (109.00, 349.20) vs. 125.50 (90.50, 155.25), TBA (μmol/L): 51.50 (16.20, 117.40) vs. 4.15 (2.02, 6.95), SCr (μmol/L): 155.80 (129.00, 237.00) vs. 79.00 (65.43, 113.70), INR: 1.28 (1.17, 1.63) vs. 0.94 (0.88, 1.08), all P < 0.05], prothrombin time (PT) was significantly prolonged [seconds: 16.10 (14.50, 19.20) vs. 12.40 (11.43, 13.40), P < 0.05]. The level of blood glucose (GLU), fibrinogen (FIB) and the activity of antithrombin Ⅲ (ATⅢ) decreased significantly [GLU (mmol/L): 5.18±1.33 vs. 6.33±1.19, FIB (g/L): 1.96±1.46 vs. 3.81±1.58, ATⅢ (%): 40.61±25.84 vs. 66.39±24.11, all P < 0.05]; ④ Complications: compared with HELLP syndrome group, the incidence of patients with hypoglycemia [30.77% (4/13) vs. 0% (0/34)], acute liver failure [53.85% (7/13) vs. 5.88% (2/34)], acute renal insufficiency [69.23% (9/13) vs. 8.82% (3/34)], coagulopathy [76.92% (10/13) vs. 38.24% (13/34)], disseminated intravascular coagulation (DIC) [53.85% (7/13) vs. 5.88% (2/34)], and multiple organ dysfunction syndrome (MODS) [53.85% (7/13) vs. 5.88% (2/34)] were significantly higher in AFLP group (all P < 0.05). ⑤ Maternal and neonatal outcome: all patients delivered after admission. The total length of hospital and intensive care unit stay were significantly longer in the AFLP group than in the HELLP syndrome group [days: 17.00 (11.00, 25.00) vs. 9.00 (7.00, 12.00), 12.00 (4.00, 22.00) vs. 3.91 (0, 7.00), both P < 0.01]. Two AFLP patients died, including one due to intracranial venous thrombosis and one due to multiple organ failure and cardiopulmonary arrest. There were no deaths in the HELLP syndrome group. Conclusions:There are significant differences in maternal characteristics, laboratory results and complications between AFLP and HELLP syndrome. TBil, γ-GGT, SCr, FIB, INR and ATⅢ activity may help to distinguish the two diseases.

Cardiology ; China ; Consensus ; Heart Failure/therapy* ; Humans ; Self-Management ; United States

Background/Aims: Growth hormone (GH) is the main regulator of somatic growth, metabolism, and gender dimorphism in the liver. GH receptor (GHR) signaling in cancer is derived from a large body of evidence, although the GHR signaling pathway involved in the prognosis of hepatocellular carcinoma (HCC) in patients with hepatitis C virus (HCV)-related HCC, remains unclear. We aimed to explore the expression of GHR and analyze its association with clinicopathologic features and prognosis of patients with chronic hepatitis C and HCC. Methods: The expression of GHR mRNA was investigated by quantitative real-time polymerase chain reaction in paired tumors and adjacent non-tumorous (ANT) liver tissues of 200 patients with chronic hepatitis C and HCC. Western blotting and immunofluorescence assays using the HCV-infected Huh7.5.1 cell model was performed. Results: GHR mRNA was significantly lower in HCV-HCC tissues than in corresponding ANT liver tissues. GHR mRNA and protein levels also decreased in the HCV-infected Huh7.5.1 cell model. Notably, lower GHR expression was associated with age of >60 years (P=0.0111) and worse clinicopathologic characteristics, including alpha-fetoprotein >100 ng/mL (P=0.0403), cirrhosis (P=0.0075), vascular invasion (P=0.0052), pathological stage II–IV (P=0.0002), and albumin ≤4.0 g/dL (P=0.0055), which were linked with poor prognosis of HCC. Most importantly, the high incidence of recurrence and poor survival rates in patients with a low ratio of tumor/ANT GHR (≤0.1) were observed, indicating that low expression levels of GHR had great risk for development of HCC in patients with chronic hepatitis C. Conclusions Our study demonstrates a significant down-regulation of GHR expression as a new unfavorable independent prognostic factor in patients with chronic hepatitis C and HCC.