Background and Aims: Rifampicin (RFP) and isoniazid (INH) are widely used as anti-tuberculosis agents. However, the mechanisms underlying the involvement of reactive oxygen species and mitochondria in RFP- and INH-related hepatotoxicity have not been established yet. This study aimed to observe the intracellular mechanisms leading to mitochondrial dysfunction and morphological changes in RFP- and INH-induced hepatocyte injury. Methods: Cell injury, changes in mitochondrial function, and expression and activation of dynamin related protein 1 (Drp1), known as the main protein for mitochondrial fission, were analyzed in cultured QSG7701 cells exposed to RFP and INH. Results: INH and RFP treatment induced pronounced hepatocyte injury and increased cell death. In the similar context of aspartate aminotransferase elevation and adenosine triphosphate synthesis decrease, changes in mitochondrial membrane permeability and reactive oxygen species in hepatocytes induced by RFP were significantly different from those induced by INH ( p < 0.05). Particularly, we observed the overactivation and mitochondrial translocation of Drp1 in RFP-induced cell injury, which was not occurred with exposure to INH. Conclusions: RFP-induced hepatotoxicity may be closely related to mitochondrial dysfunction and Drp1-mediated mitochondrial fission.

High temperature plastic deformation behavior of non-orientated electrical steel was investigated by Gleeble 1500 thermo-mechanical simulator at strain rate of 0.01−10 s −1 and high temperature of 500−1 200 ℃. The stress level factor (α), stress exponent (n), structural factor (A) and activation energy (Q) of high temperature plastic deformation process of non-orientated electrical steel in different temperature ranges were calculated by the Arrhenius model. The results show that, with dynamic elevation of deformation temperature, phase transformation from α-Fe to γ-Fe takes place simultaneously during plastic deformation, dynamic recovery and dynamic recrystallization process, leading to an irregular change of the steady flow stress. For high temperature plastic deformation between 500 and 800 ℃, the calculated values of α, n, A, and Q are 0.039 0 MPa −1 , 7.93, 1.9×10 18 s −1 , and 334.8 kJ/mol, respectively, and for high temperature plastic deformation between 1 050 and 1 200 ℃, the calculated values of α, n, A, and Q are 0.125 8 MPa −1 , 5.29, 1.0×10 28 s −1 , and 769.9 kJ/mol, respectively.

Rapid and accurate fault diagnosis of smart meters can greatly improve the operational and maintenance ability of power systems. Focusing on the historical fault data information of smart meters, a fault diagnosis model of smart meters based on an improved capsule network (CapsNet) is proposed. First, we count the sample size of each fault type, and a mixed sampling method combining undersampling and oversampling is used to solve the problem of distribution imbalance of sample size. The one-hot encoding method is adopted to solve the problem of the fault samples containing more discrete and disordered data. Then, the strong adaptive feature extraction capability and nonlinear mapping capability of the deep belief network (DBN) are utilized to improve the single convolution layer feature extraction part of a traditional capsule network; DBN can also address the problem of high data dimensions and sparse data due to one-hot encoding. The important features and key information of the input sample are extracted and used as the input of the primary capsule layer, and the dynamic routing algorithm is used to construct the digital capsule. Finally, the results of experiments show that the improved capsule network model can effectively improve the accuracy of diagnosis and shorten the training time.

Background COVID-19 is a disease caused by SARS-CoV-2, which can cause mild to serious infections in humans. We aimed to explore the effect of growth hormone (GH)/estrogen/androgen in normal human lung epithelial BEAS-2B cells on COVID-19-type proinflammatory responses. Methods A BEAS-2B COVID-19-like proinflammatory cell model was constructed. After that, the cells were treated with GH, 17β-estradiol (E2), and testosterone (Tes) for 24 h. CCK-8 assays were utilized to evaluate cell viability. The mRNA expression of ACE2, AGTR1, TMRRSS2, and ISG15 and the protein expression of ACE2, AGTR1, TMRRSS2, and ISG15 were measured by qRT‒PCR and Western blotting, respectively. ELISAs were performed to determine IL-6, MCP-1, MDA and SOD expression. Flow cytometry was used to measure ROS levels. Finally, MAPK/NF-κB pathway-related factor expression was evaluated. Results The COVID-19-type proinflammatory model was successfully constructed, and 1000 ng/mL RBD treatment for 24 h was selected as the condition for the model group for subsequent experiments. After RBD treatment, cell viability decreased, the mRNA expression of ACE2, AGTR1, TMRRSS2, and ISG15 and the protein expression of ACE2, AGTR1, TMRRSS2, and ISG15 increased, IL-6, MCP-1, MDA and ROS levels increased, and MDA levels decreased. The mRNA levels of MAPK14 and RELA increased, but the protein levels did not change significantly. In addition, phospho-MAPK14 and phospho-RELA protein levels were also increased. Among the tested molecules, E2 had the most pronounced effect, followed by GH, while Tes showed the opposite effect. Conclusion GH/E2 alleviated inflammation in a COVID-19-type proinflammatory model, but Tes showed the opposite effect.

In response to the problem that weights in product planning and design are difficult to accurately reflect the real needs of users, a design method for hexagonal shaft straightening machines based on quality function configuration and evidence theory is proposed. First, based on the method of quality function deployment and evidence theory, the demand indicator and its importance are determined by market research and the Kano model. Second, to solve the conflict problem in the process of expert opinion aggregation, combined with evidence theory, taking expert knowledge as evidence, the possible value space of causal strength among nodes constitutes the recognition framework, which is used to synthesize the knowledge of multiple experts. The indicator correlation degree is reflected by using a correlation weight matrix, and effective solutions to the relevant theoretical problems and algorithms, such as those for competitive indicator evaluation, weight calculation and planning target value cases, are proposed. Finally, according to the analysis results for the various structural elements of the house of quality, a hexagonal shaft straightening machine function for master planning house of quality was constructed, and propose a design and build the main experimental platform. The relevant test results show that the technical specifications of the hexagonal shaft straightening machine basically meet the requirements of the overall planning target values, verifying the effectiveness and feasibility of the proposed method.