Effect of an Airbag-selective Portal Vein Blood Arrester on the Liver after Hepatectomy: A New Technique for Selective Clamping of the Portal Vein.

OBJECTIVE: A novel technique was explored using an airbag-selective portal vein blood arrester that circumvents the need for an intraoperative assessment of anatomical variations in patients with complex intrahepatic space-occupying lesions. METHODS: Rabbits undergoing hepatectomy were randomly assigned to 4 groups: intermittent portal triad clamping (PTC), intermittent portal vein clamping (PVC), intermittent portal vein blocker with an airbag-selective portal vein blood arrester (APC), and without portal blood occlusion (control). Hepatic ischemia and reperfusion injury were assessed by measuring the 7-day survival rate, blood loss, liver function, hepatic pathology, hepatic inflammatory cytokine infiltration, hepatic malondialdehyde levels, and proliferating cell nuclear antigen levels. RESULTS: Liver damage was substantially reduced in the APC and PVC groups. The APC animals exhibited transaminase levels similar to or less oxidative stress damage and inflammatory hepatocellular injury compared to those exhibited by the PVC animals. Bleeding was significantly higher in the control group than in the other groups. The APC group had less bleeding than the PVC group because of the avoidance of portal vein skeletonization during hepatectomy. Thus, more operative time was saved in the APC group than in the PVC group. Moreover, the total 7-day survival rate in the APC group was higher than that in the PTC group. CONCLUSION: Airbag-selective portal vein blood arresters may help protect against hepatic ischemia and reperfusion injury in rabbits undergoing partial hepatectomy. This technique may also help prevent liver damage in patients requiring hepatectomy.

Leaky Gut Plays a Critical Role in the Pathophysiology of Autism in Mice by Activating the Lipopolysaccharide-Mediated Toll-Like Receptor 4-Myeloid Differentiation Factor 88-Nuclear Factor Kappa B Signaling Pathway.

Increased intestinal barrier permeability, leaky gut, has been reported in patients with autism. However, its contribution to the development of autism has not been determined. We selected dextran sulfate sodium (DSS) to disrupt and metformin to repair the intestinal barrier in BTBR T+tf/J autistic mice to test this hypothesis. DSS treatment resulted in a decreased affinity for social proximity; however, autistic behaviors in mice were improved after the administration of metformin. We found an increased affinity for social proximity/social memory and decreased repetitive and anxiety-related behaviors. The concentration of lipopolysaccharides in blood decreased after the administration of metformin. The expression levels of the key molecules in the toll-like receptor 4 (TLR4)-myeloid differentiation factor 88 (MyD88)-nuclear factor kappa B (NF-κB) pathway and their downstream inflammatory cytokines in the cerebral cortex were both repressed. Thus, "leaky gut" could be a trigger for the development of autism via activation of the lipopolysaccharide-mediated TLR4-MyD88-NF-κB pathway.

Identification of an extracellular vesicle-related gene signature in the prediction of pancreatic cancer clinical prognosis.

Although extracellular vesicles (EVs) in body fluid have been considered to be ideal biomarkers for cancer diagnosis and prognosis, it is still difficult to distinguish EVs derived from tumor tissue and normal tissue. Therefore, the prognostic value of tumor-specific EVs was evaluated through related molecules in pancreatic tumor tissue. NA sequencing data of pancreatic adenocarcinoma (PAAD) were acquired from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC). EV-related genes in pancreatic cancer were obtained from exoRBase. Protein-protein interaction (PPI) network analysis was used to identify modules related to clinical stage. CIBERSORT was used to assess the abundance of immune and non-immune cells in the tumor microenvironment. A total of 12 PPI modules were identified, and the 3-PPI-MOD was identified based on the randomForest package. The genes of this model are involved in DNA damage and repair and cell membrane-related pathways. The independent external verification cohorts showed that the 3-PPI-MOD can significantly classify patient prognosis. Moreover, compared with the model constructed by pure gene expression, the 3-PPI-MOD showed better prognostic value. The expression of genes in the 3-PPI-MOD had a significant positive correlation with immune cells. Genes related to the hypoxia pathway were significantly enriched in the high-risk tumors predicted by the 3-PPI-MOD. External databases were used to verify the gene expression in the 3-PPI-MOD. The 3-PPI-MOD had satisfactory predictive performance and could be used as a prognostic predictive biomarker for pancreatic cancer.

Development and Validation of a Novel 8 Immune Gene Prognostic Signature Based on the Immune Expression Profile for Hepatocellular Carcinoma.

BACKGROUND: The immune microenvironment plays a vital role in the development of hepatocellular carcinoma (HCC). This study explored novel immune-related biomarkers to predict the prognosis of patients with HCC. METHODS: RNA-Seq data were downloaded from The Cancer Genome Atlas (TCGA). Univariate Cox regression was used to identify prognosis-related genes; the Lasso method was used to construct the prognosis risk model. Validation was performed on the International Cancer Genome Consortium (ICGC) cohort, and the C-index was calculated to evaluate its overall predictive performance. Western blots were conducted to evaluate the expression of genes. RESULTS: There were 320 immune-related genes, 40 of which were significantly related to prognosis. Eight immune gene signatures (CKLF, IL12A, CCL20, PRELID1, GLMN, ACVR2A, CD7, and FYN) were established by Lasso Cox regression analysis. This immune signature performed well in different cohorts and can be an independent risk factor for prognosis. In addition, the overall predictive performance of this model was higher than the other models reported previously. CONCLUSION: The predictive immune model will enable patients with HCC to be more accurately managed in immunotherapy.