GHR is involved in gastric cell growth and apoptosis via PI3K/AKT signalling.

Growth hormone receptor (GHR), the cognate receptor of growth hormone (GH), is a membrane bound receptor that belongs to the class I cytokine receptor superfamily. GH binding GHR induces cell differentiation and maturation, initiates the anabolism inside the cells and promotes cell proliferation. Recently, GHR has been reported to be associated with various types of cancer. However, the underlying mechanism of GHR in gastric cancer has not been defined. Our results showed that silence of GHR inhibited the growth of SGC-7901 and MGC-803 cells, and tumour development in mouse xenograft model. Flow cytometry showed that GHR knockout significantly stimulated gastric cancer cell apoptosis and caused G1 cell cycle arrest, which was also verified by Western blot that GHR deficiency induced the protein level of cleaved-PARP, a valuable marker of apoptosis. In addition, GHR deficiency inhibited the activation of PI3K/AKT signalling pathway. On the basis of the results, that GHR regulates gastric cancer cell growth and apoptosis through controlling G1 cell cycle progression via mediating PI3K/AKT signalling pathway. These findings provide a novel understanding for the role of GHR in gastric cancer.

Computed tomography texture analysis combined with preoperative clinical factors serve as a predictor of early efficacy of transcatheter arterial chemoembolization in hepatocellular carcinoma.

AIM: To investigate a pre-therapeutic radiomics nomogram to accurately predict hepatocellular carcinoma (HCC) lesion responses to transcatheter arterial chemoembolization (TACE). METHODS: This retrospective study from January 2012 to 2022 included 92 TACE-treated patients who underwent liver contrast-enhanced CT scan 7 days before treatment, having complete clinical information. We extracted quantitative texture parameters and clinical factors for the largest tumors on the baseline arterial and portal venous phase CT images. An adaptive least absolute shrinkage and selection operator (LASSO)-penalized logistic regression identified independent predictors of tumor activity after TACE. RESULTS: We fitted an adaptive LASSO regression model to narrow down the texture features and clinical risk factors of the tumor activity status. The selected texture features were used to construct radiomic scores (RadScore), which demonstrated superior performance in predicting tumor activity on both the training (area under the curve (AUC): 0.881, 95% CI: 0.799-0.963) and testing sets (AUC: 0.88, 95% CI: 0.726-1). A logistic regression-based nomogram was developed using RadScore and four selected clinical features. In the testing set, nomogram total points were significant predictors (P = 0.034), and the training set showed no departure from perfect fit (P = 0.833). Internal validation of the nomogram was obtained for the training (AUC: 0.91, 95% CI: 0.837-0.984) and testing (AUC: 0.889, 95% CI: 0.746-1) sets. CONCLUSION: We propose a nomogram to predict the early response of HCC lesions to TACE treatment with high accuracy, which may serve as an additional criterion in multidisciplinary decision-making treatment.

Role of clinical data and multidetector computed tomography findings in acute superior mesenteric artery embolism.

BACKGROUND: Superior mesenteric artery embolism (SMAE) has acute onset and fast progression, which seriously threatens the life of patients. Multidetector computed tomography (MDCT) is one of the most important diagnostic methods for SMAE, which plays an important role in the diagnosis and prognosis of SMAE. AIM: To evaluate the value of combined clinical data and MDCT findings in the diagnosis of acute SMAE and predict the risk factors for SMAE-related death. METHODS: Data from 53 SMAE patients who received abdominal MDCT multi-phase enhancement and superior mesenteric artery digital subtraction angiography examinations were collected. Univariate cox regression and multivariate cox model were used to analyze the correlation between death risk and clinical and computed tomography features in SMAE patients. RESULTS: Univariate Cox regression model showed that intestinal wall thinning, intestinal wall pneumatosis, blood lactate > 2.1 mmol/L and blood pH < 7.35 increased the risk of death in patients with SMAE. After adjusting for age, sex, embolic involvement length and embolic distribution region, multivariate Cox regression model I showed that blood lactate > 2.1 mmol/L (HR = 5.26, 95%CI: 1.04-26.69, P = 0.045) and intestinal wall thinning (HR = 9.40, 95%CI: 1.05-83.46, P = 0.044) were significantly increases the risk of death in patients with SMAE. CONCLUSION: For patients with SAME, increased blood lactate and intestinal wall thinning are the risk factors for death; hence, close monitoring may reduce the mortality rate. Clinical observation combined with MDCT signs can significantly improve SMAE diagnosis.