A 56-year-old female was admitted to Department of Gastroenterology at Peking Union Medical College Hospital with diarrhea for seven months, and abnormal liver function for six months. She had a history of type 1 diabetes. The main clinical manifestations were recurrent fatty diarrhea and abnormal liver function, accompanied by abdominal and retroperitoneal lymphadenopathy, elevated CA19-9 and CEA. Progressive impairment of hepatic synthetic function and shrinkage of liver developed in a short period of time. The pathology of liver biopsy suggested that nodular regeneration of hepatocytes was followed by hyperplasia of thin bile ducts after submassive necrosis. Intestinal mucosa biopsies were performed twice. The pathology showed that the intestinal villi were completely blunt, accompanied with crypt hyperplasia. Goblet cells disappeared with reduced mucin. Paneth cells were barely seen without intraepithelial infiltration of lymphocytes. Rifaximin was not effective, while glucocorticoids improved clinical situation. The diagnosis of autoimmune enteropathy was finally confirmed by multidisciplinary team including departments of gastroenterology, pathology, endocrinology, hematology, infectious diseases, and rheumatology. With the administration of glucocorticoid and sirolimus, diarrhea relieved and liver function returned to normal.

Objective:To construct a predictive model for intensive care unit (ICU) and in-hospital mortality risk in patients with traumatic brain injury (TBI) and validate its performance.Methods:A retrospective cohort study was conducted to analyze the clinical data of 3 907 patients with TBI published until May 2018 in the eICU Collaborative Research Database v2.0 (eICU-CRD v2.0), including 2 397 males and 1 510 females, aged 18-92 years [63.0(43.0, 79.0)years]. According to whether the patients died in ICU or at hospital stay, they were divided into ICU survival group ( n=3 575) and ICU mortality group ( n=332), and hospital survival group ( n=3 413) and hospital mortality group ( n=494). The general data, admission diagnosis, laboratory tests, therapeutic interventions, and clinical outcomes were extracted as variables of interest. Univariate analysis and multivariate Logistic regression analysis were conducted on both the survival groups and the mortality groups to identify the independent risk factors that affect ICU and in-hospital mortality in TBI patients, based on which a Logistic regression prediction model was constructed and represented by Nomograms. The extracted dataset was randomly divided into training set ( n=2 735) and validation set ( n=1 172) with a ratio of 7∶3, and was applied for internal validation of the of the predictive model. Meanwhile, the data of TBI patients in the MIMIC-III v1. 4 database were extracted for external validation of the predictive model. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used for discriminability evaluation of the model, and the Hosmer-Lemeshow (H-L) goodness of fit test and calibration curve were used for calibration evaluation of the model. Results:The statistically significant variables identified in the univariate analysis were included in the multivariate logistic regression analysis of ICU mortality and in-hospital mortality risk. The results revealed that acute physiology and chronic health evaluation IV (APACHE IV) score ( OR=1.04, 95% CI 1.03, 1.04, P<0.01), Glasgow coma scale (GCS) ( OR=0.66, 95% CI 0.59, 0.73, P<0.01), cerebral hernia formation ( OR=6.91, 95% CI 3.13, 15.26, P<0.01), international normalized ratio (INR) ( OR=1.33, 95% CI 1.09, 1.62, P<0.01), use of hypertonic saline ( OR=0.45, 95% CI 0.21 0.94, P<0.05), and use of vasoactive agents ( OR=2.19, 95% CI 1.36, 3.52, P<0.01) were independent risk factors for ICU mortality in TBI patients. The age (with 10 years as a grade) ( OR=1.28, 95% CI 1.17, 1.40, P<0.01), APACHE IV score ( OR=1.03, 95% CI 1.02, 1.04, P<0.01), GCS ( OR=0.75, 95% CI 0.71, 0.80, P<0.01), cerebral hernia formation ( OR=6.44, 95% CI 2.99, 13.86, P<0.01), serum creatinine level ( OR=1.07, 95% CI 1.01, 1.15, P<0.05), INR ( OR=1.49, 95% CI 1.20, 1.85, P<0.01), use of hypertonic saline ( OR=0.41, 95% CI 0.21, 0.80, P<0.01), and use of vasoactive agents ( OR=2.27, 95% CI 1.46, 3.53, P<0.01) were independent risk factors of in-hospital mortality of TBI patients. Based on the forementioned independent risk factors for ICU mortality, the model equation was constructed: Logit P (ICU)=7.12+0.03×"APACHE IV score"-0.42×"GCS"+1.93×"cerebral hernia formation"+0.28×"INR"-0.81×"use of hypertonic saline"+0.79×"use of vasoactive agents". Based on the forementioned independent risk factors for in-hospital mortality, the model equation was constructed: Logit P (in-hospital)=2.75+0.25×"age"(with 10 years as a grade)+0.03×"APACHE IV score"-0.28×"GCS"+1.86×"cerebral hernia formation"+0.07×"serum creatinine level"+0.40×"INR"-0.90×"use of hypertonic saline"+0.82×"use of vasoactive agents". In the prediction model for ICU mortality, the AUC of the training set and validation set was 0.95 (95% CI 0.94, 0.97) and 0.91 (95% CI 0.87, 0.95). The result of H-L goodness of fit test of the training set was P=0.495 with the average absolute error in the calibration curve of 0.003, while the result of H-L goodness of fit test of the validation set was P=0.650 with the average absolute error in the calibration curve of 0.012. In the prediction model for in-hospital mortality, the AUC of the training set and validation set was 0.91 (95% CI 0.89, 0.93) and 0.91(95% CI 0.88, 0.94). The result of H-L goodness of fit test of the training set was P=0.670 with the average absolute error in the calibration curve of 0.006, while the result of H-L goodness of fit test of the validation set was P=0.080 with the average absolute error in the calibration curve of 0.021. In the external validation set of ICU mortality risk, the AUC of the prediction model was 0.88 (95% CI 0.86, 0.90), while the result of H-L goodness of fit test was P=0.205 with the average absolute error in the calibration curve of 0.031. In the external validation set of in-hospital mortality risk, the AUC of the prediction model was 0.88 (95% CI 0.85, 0.91), while the result of H-L goodness of fit test was P=0.239 with the average absolute error in the calibration curve of 0.036. The internal and external validation of the model indicated that both the prediction models for ICU and in-hospital mortality had good discriminability and calibration. Conclusion:The ICU mortality prediction model constructed by APACHE IV score, GCS, cerebral hernia formation, use of hypertonic saline, vasoactive agents use of and INR, and the in-hospital mortality prediction model constructed by age grading, APACHE IV score, GCS, cerebral hernia formation, serum creatinine level, hypertonic saline use of, use of vasoactive agents and INR can predict the mortality risk of TBI patients well.

OBJECTIVES: Cardiac hypertrophy and fibrosis are major pathological manifestations observed in left ventricular remodeling induced by angiotensin II (AngII). Low-intensity pulsed ultrasound (LIPUS) has been reported to ameliorate cardiac dysfunction and myocardial fibrosis in myocardial infarction (MI) through mechano-transduction and its downstream pathways. In this study, we aimed to investigate whether LIPUS could exert a protective effect by ameliorating AngII-induced cardiac hypertrophy and fibrosis and if so, to further elucidate the underlying molecular mechanisms. METHODS: We used AngII to mimic animal and cell culture models of cardiac hypertrophy and fibrosis. LIPUS irradiation was applied in vivo for 20 min every 2 d from one week before mini-pump implantation to four weeks after mini-pump implantation, and in vitro for 20 min on each of two occasions 6 h apart. Cardiac hypertrophy and fibrosis levels were then evaluated by echocardiographic, histopathological, and molecular biological methods. RESULTS: Our results showed that LIPUS could ameliorate left ventricular remodeling in vivo and cardiac fibrosis in vitro by reducing AngII-induced release of inflammatory cytokines, but the protective effects on cardiac hypertrophy were limited in vitro. Given that LIPUS increased the expression of caveolin-1 in response to mechanical stimulation, we inhibited caveolin-1 activity with pyrazolopyrimidine 2 (pp2) in vivo and in vitro. LIPUS-induced downregulation of inflammation was reversed and the anti-fibrotic effects of LIPUS were absent. CONCLUSIONS These results indicated that LIPUS could ameliorate AngII-induced cardiac fibrosis by alleviating inflammation via a caveolin-1-dependent pathway, providing new insights for the development of novel therapeutic apparatus in clinical practice.