Optimization of extended-release hydrophilic matrix tablets by support vector regression

Ethanol-induced dose dumping from sodium alginate matrix tablets: Investigation of the effects of medium viscosity and pH

In this work, the swelling and disintegration of drug-free sodium alginate (SA) compacts and the release of metformin HCl from SA matrix tablets were investigated in acidic media of different ethanol concentrations (0, 10, 20, and 40 % v/v), pH (1.2 and 4.5) and HPMC K4M concentrations (0-1 % w/v). The investigated dissolution media represented the consumption of different alcoholic beverages, the pH of fasted and fed states, and a range of viscosity resembling diluted homogenized FDA meal. The dissolution efficiency and the time to 50 % release (t_50%) were selected as release parameters. It was found that both ethanol concentration and medium pH affected drug release from SA matrix tablets and the swelling of SA compacts. Dose dumping occurred at high ethanol concentration (40 %) at both media pH with almost complete drug release within 15-30 min associated with rapid matrix disintegration. HPMC at 0.5-1 % concentrations increased the medium's viscosity, preventing dose dumping at high ethanol concentrations. Erosion and disintegration of SA compacts were decelerated by increasing HPMC concentration in hydroethanolic media in consonance with decreased release rate from matrix tablets. ANOVA tests showed significant effects of pH and concentrations of ethanol and HPMC in the dissolution medium on the release parameters.

A Study Using Optimized LSSVR for Real-Time Fault Detection of Liquid Rocket Engine

Health monitoring and fault diagnosis of liquid rocket engine (LRE) are the most important concerning issue for the safety of rocket’s flying, especially for the man-carried aerospace engineering. Based on the sensor measurement signals of a certain type of hydrogen-oxygen rocket engine, this paper proposed a real-time fault detection approach using a genetic algorithm-based least squares support vector regression (GA-LSSVR) algorithm for the real-time fault detection of the rocket engine. In order to obtain effective training samples, the data is normalized in this paper. Then, the GA-LSSVR algorithm is derived through comprehensive considerations of the advantages of the Support Vector Regression (SVR) algorithm and Least Square Support Vector Regression (LSSVR). What is more, this paper provided the genetic algorithm to search for the optimal LSSVR parameters. In the end, the computational results of the suggested approach using the rocket practical experimental data are given out. Through the analysis of the results, the effectiveness and the detection accuracy of this presented real-time fault detection method using LSSVR GA-optimized is verified. The experiment results show that this method can effectively diagnose this hydrogen-oxygen rocket engine in real-time, and the method has engineering application value.

Non-Targeted Metabolomic Analysis of Chicken Kidneys in Response to Coronavirus IBV Infection Under Stress Induced by Dexamethasone

Stress in poultry can lead to changes in body metabolism and immunity, which can increase susceptibility to infectious diseases. However, knowledge regarding chicken responses to viral infection under stress is limited. Dexamethasone (Dex) is a synthetic glucocorticoid similar to that secreted by animals under stress conditions, and has been widely used to induce stress in chickens. Herein, we established a stress model in 7-day-old chickens injected with Dex to elucidate the effects of stress on IBV replication in the kidneys. The metabolic changes, immune status and growth of the chickens under stress conditions were comprehensively evaluated. Furthermore, the metabolic profile, weight gain, viral load, serum cholesterol levels, cytokines and peripheral blood lymphocyte ratio were compared in chickens treated with Dex and infected with IBV. An LC-MS/MS-based metabolomics method was used to examine differentially enriched metabolites in the kidneys. A total of 113 metabolites whose abundance was altered after Dex treatment were identified, most of which were lipids and lipid-like molecules. The principal metabolic alterations in chicken kidneys caused by IBV infection included fatty acid, valine, leucine and isoleucine metabolism. Dex treatment before and after IBV infection mainly affected the host’s tryptophan, phenylalanine, amino sugar and nucleotide sugar metabolism. In addition, Dex led to up-regulation of serum cholesterol levels and renal viral load in chickens, and to the inhibition of weight gain, peripheral blood lymphocytes and IL-6 production. We also confirmed that the exogenous cholesterol in DF-1 cells promoted the replication of IBV. However, whether the increase in viral load in kidney tissue is associated with the up-regulation of cholesterol levels induced by Dex must be demonstrated in future experiments. In conclusion, chick growth and immune function were significantly inhibited by Dex. Host cholesterol metabolism and the response to IBV infection are regulated by Dex. This study provides valuable insights into the molecular regulatory mechanisms in poultry stress, and should support further research on the intrinsic link between cholesterol metabolism and IBV replication under stress conditions.