Diurnal changes in colonic motor profile in conscious dogs

Continuous strain gauge recordings of ileal and proximal colonic motility were performed in 5 dogs fitted with a cannula in the ileum. The 22-hr records obtained with a normal ileocolonic transit were repeated during external deviation of digesta and after vagotomy. In the fasted state, the motility of the proximal colon was characterized by phases of contractions occurring at 25-min mean intervals modulated by the occurrence of migrating motor complexes on the ileum. Food intake induced three consecutive changes in colonic motility: a supplementary phase of activity immediately after the meal, an inhibition during the second postprandial hour, and a period of increased frequency of the phases of activity lasting 8-10 hr. The fasted motor profile of the proximal colon reappeared at the end of the postprandial disruption of the ileal cyclic activity. External deviation of ileal content abolished the late colonic response to the meal. Vagotomy did not modify any diurnal variation.     

前房角切开术治疗青少年型开角型青光眼

小梁切除术联合丝裂霉素C是治疗青少年型开角型青光眼(junior open-angle glaucoma,JOAG)较常用的术式,缺点是存在低眼压性黄斑病变、滤过泡渗漏等潜在并发症的可能.前房角切开术是治疗原发性婴幼儿型青光眼较常用的术式.作者报告了波士顿市马萨诸塞眼耳医院采用前房角切开这一轻度侵人性手术治疗青少年型开角型青光眼的结果.     

CT‐based radiomics to predict development of macrovascular invasion in hepatocellular carcinoma: A multicenter study

BackgroundMacrovascular invasion (MaVI) occurs in nearly half of hepatocellular carcinoma (HCC) patients at diagnosis or during follow-up, which causes severe disease deterioration, and limits the possibility of surgical approaches. This study aimed to investigate whether computed tomography (CT)-based radiomics analysis could help predict development of MaVI in HCC.MethodsA cohort of 226 patients diagnosed with HCC was enrolled from 5 hospitals with complete MaVI and prognosis follow-ups. CT-based radiomics signature was built via multi-strategy machine learning methods. Afterwards, MaVI-related clinical factors and radiomics signature were integrated to construct the final prediction model (CRIM, clinical-radiomics integrated model) via random forest modeling. Cox-regression analysis was used to select independent risk factors to predict the time of MaVI development. Kaplan-Meier analysis was conducted to stratify patients according to the time of MaVI development, progression-free survival (PFS), and overall survival (OS) based on the selected risk factors.ResultsThe radiomics signature showed significant improvement for MaVI prediction compared with conventional clinical/radiological predictors (P < 0.001). CRIM could predict MaVI with satisfactory areas under the curve (AUC) of 0.986 and 0.979 in the training (n = 154) and external validation (n = 72) datasets, respectively. CRIM presented with excellent generalization with AUC of 0.956, 1.000, and 1.000 in each external cohort that accepted disparate CT scanning protocol/manufactory. Peel9_fos_InterquartileRange [hazard ratio (HR) = 1.98; P < 0.001] was selected as the independent risk factor. The cox-regression model successfully stratified patients into the high-risk and low-risk groups regarding the time of MaVI development (P < 0.001), PFS (P < 0.001) and OS (P = 0.002).ConclusionsThe CT-based quantitative radiomics analysis could enable high accuracy prediction of subsequent MaVI development in HCC with prognostic implications.