BACKGROUND/OBJECTIVES: Increased levels of uremic toxins and decreased antioxidant capacity have a significant impact on the progression of chronic kidney disease (CKD). However, it remains unclear whether they interact with each other to mediate the damage of kidney function. The purpose of this study was to investigate whether uremic toxins (i.e., homocysteine and indoxyl sulfate [IS]), as well as glutathione-dependent antioxidant enzyme activities are dependently or independently associated with kidney function during different stages of CKD patients. SUBJECTS/METHODS: One hundred thirty-two patients diagnosed with CKD at stages 1 to 5 participated in this cross-sectional study. RESULTS: Patients who had reached an advanced CKD stage experienced an increase in plasma uremic toxin levels, along with decreased glutathione peroxidase (GSH-Px) activity.Plasma homocysteine, cysteine, and IS concentrations were all positively associated with each other, but negatively correlated to GSH-Px activity levels after adjusting for potential confounders in all CKD patients. Although plasma homocysteine, cysteine, IS, and GSHPx levels were significantly associated with kidney function, only plasma IS levels still had a significant association with kidney function after these parameters were simultaneously adjusted. In addition, plasma IS could interact with GSH-Px activity to be associated with kidney function. CONCLUSIONS IS plays a more dominant role than homocysteine and GSH-Px activity in relation to kidney function.

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.

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.

OBJECTIVE: The purpose of this study was to quantify lesions on chest radiographs in patients with severe acute respiratory syndrome (SARS) and analyze the severity of the lesions with clinical parameters. MATERIALS AND METHODS: Two experienced radiologists reviewed chest radiographs of 28 patients with SARS. Each lung was divided into upper, middle, and lower zones. A SARS-related lesion in each zone was scored using a four-point scale: zero to three. The mean and maximal radiographic scores were analyzed statistically to determine if the scorings were related to the laboratory data and clinical course. RESULTS: Forward stepwise multiple linear regression showed that the mean radiographic score correlated most significantly with the number of hospitalized days (p < 0.001). The second most significant factor was the absolute lymphocyte count (p < 0.001) and the third most significant factor was the number of days of intubation (p = 0.025). The maximal radiographic score correlated best with the percentage of lymphocytes in a leukocyte count (p < 0.001), while the second most significant factor was the number of hospitalized days (p < 0.001) and the third most significant factor was the absolute lymphocyte count (p = 0.013). The mean radiographic scores of the patients who died, with comorbidities and without a comorbidity were 11.1, 6.3 and 2.9, respectively (p = 0.032). The corresponding value for maximal radiographic scores were 17.7, 9.7 and 6.0, respectively (p = 0.033). CONCLUSION: The severity of abnormalities quantified on chest radiographs in patients with SARS correlates with the clinical parameters.
Adolescent ; Adult ; Aged ; Aged, 80 and over ; Biological Markers/blood ; Blood Gas Analysis/statistics & numerical data ; Female ; Humans ; Intubation, Intratracheal/statistics & numerical data ; Length of Stay ; Lung/*radiography ; Lymphocyte Count/statistics & numerical data ; Male ; Middle Aged ; Observer Variation ; Predictive Value of Tests ; Prognosis ; Retrospective Studies ; Severe Acute Respiratory Syndrome/blood/*diagnosis/mortality ; Severity of Illness Index ; Survival Analysis

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.