The NHE3 Inhibitor Tenapanor Prevents Intestinal Obstructions in CFTR-Deleted Mice

Mutations in the CFTR chloride channel result in intestinal obstructive episodes in cystic fibrosis (CF) patients and in CF animal models. In this study, we explored the possibility of reducing the frequency of obstructive episodes in cftr^−/− mice through the oral application of a gut-selective NHE3 inhibitor tenapanor and searched for the underlying mechanisms involved. Sex- and age-matched cftr^+/+ and cftr^−/− mice were orally gavaged twice daily with 30 mg kg⁻¹ tenapanor or vehicle for a period of 21 days. Body weight and stool water content was assessed daily and gastrointestinal transit time (GTT) once weekly. The mice were sacrificed when an intestinal obstruction was suspected or after 21 days, and stool and tissues were collected for further analysis. Twenty-one day tenapanor application resulted in a significant increase in stool water content and stool alkalinity and a significant decrease in GTT in cftr^+/+ and cftr^−/− mice. Tenapanor significantly reduced obstructive episodes to 8% compared to 46% in vehicle-treated cftr^−/− mice and prevented mucosal inflammation. A decrease in cryptal hyperproliferation, mucus accumulation, and mucosal mast cell number was also observed in tenapanor- compared to vehicle-treated, unobstructed cftr^−/− mice. Overall, oral tenapanor application prevented obstructive episodes in CFTR-deficient mice and was safe in cftr^+/+ and cftr^−/− mice. These results suggest that tenapanor may be a safe and affordable adjunctive therapy in cystic fibrosis patients to alleviate constipation and prevent recurrent DIOS.     

Investigation of N + SiGe Gate Stacked V-TFET Based on Dopingless Charge Plasma for Gas Sensing Application

Silicon - In this paper, a novel n + SiGe pocket layer gate stacked VTFET doping less charge plasma is proposed and analyzed using Silvaco TCAD simulation software. The proposed device...     

EEG based personality prediction using genetic programming

The reliable correlation between personality and brain signal ensures that inferences from cognitive processes can be achieved. This research aims primarily to predict one's personality using brain signals. On grounds of Psychology, the inference of personality in this work is performed on the basis of the Myers–Briggs Type Indicator (MBTI) personality inventory. Personality consists of different types of thinking, feeling and behavior patterns. EEG signals are produced when a person is exposed to situations or scenarios via visual information and experiences various emotions or sentiments. In this study, by evaluating brain waves while a person watches personality traits elicitation materials, the identification of the personality traits of an individual is done. The elicitation materials used for the collection of the dataset comprise approximately 50 videos with the pre-defined personality of the dramatic personae and therefore, it is considered to be the ground truth for the experimental procedure of this work. For creating a dataset, sixty participants contributed and gave brain signals. The GP model with the proposed BSH crossover, known as the BSHGP model, is implemented. The maximum performance of the BSHGP model for a 10-fold partition scheme is 84.34%.