Objective To improve the image quality of the electrical impedance tomography (EIT) by introducing the prior information into the regularization matrix.Methods The linear combination of the conductivity was established by background conductivity of dynamic variation,the covariance matrix was used here to remove the correlation between the background conductivity,and this prior information was introduced to construct the regularization matrix.Resnlts Compared with the traditional regularization matrix,the one involving in the prior information on the dynamic background gained more stable and better images.Conclusion Trials prove the efficacy of the regularization matrix on EIT imaging in 1 respiratory cycles (or heart beat),and following related researches may find theoretical references and support for feasibility.

ObjectiveTo systematically explore the underlying mechanisms of Huashi Baidu prescription （HBP） against myocardial injury through a multidimensional network analysis of "transcriptome-putative target-phenotype gene". MethodPutative targets of compounds in HBP were predicted using the Encyclopedia of Traditional Chinese Medicine （ETCM 2.0，http：//www.tcmip.cn/ETCM2/front/） and the Integrative Pharmacology-based Research Platform of Traditional Chinese Medicine （TCMIP v2.0，http：//www.tcmip.cn/TCMIP/index.php/Home/Login/login.html）. Clinical predominant symptom phenotypes for HBP against coronavirus disease 2019 （COVID-19） were collected from CNKI and PubMed databases， while clinical side effects of doxorubicin were gathered from the CTD database. Phenotype-related genes were collected from the HPO database and SoFDA data platform （http：//www.tcmip.cn/Syndrome/front/#/）. An interaction network of "transcriptome-putative target-phenotype gene" was constructed. Key nodes were identified through topological feature calculations， and functional enrichment analysis was conducted to explain the underlying mechanism. Pharmacodynamic evaluation and mechanism verification were performed using a doxorubicin-induced myocardial injury mouse model. Sixty-five SPF-grade C57BL/6J male mice were randomly divided into a control group， a doxorubicin model group， and low-， medium-， and high-dose HBP groups （HBP-L/M/H）， with 13 mice per group. Histopathological severity was assessed using hematoxylin-eosin （HE） and Masson staining. Fibrosis markers were measured by Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR）， and protein expression was detected by Western blot. ResultA total of 1 044 putative targets for HBP were obtained from ETCM 2.0 and TCMIP v2.0. From the CTD， HPO， and SoFDA databases， 1 223 potential effect-related targets were identified. Cardiac transcriptome sequencing （RNA-seq） yielded 214 genes related to doxorubicin-induced myocardial injury and 58 genes associated with the effects of HBP， using criteria of P-value<0.05 and FC > 1.5/< 0.667. Analysis of the multidimensional molecular network revealed that the mechanisms of HBP on myocardial injury were mainly related to immune-inflammation imbalance， cellular metabolism， myocardial cell function and fibrosis， angiogenesis， contraction and platelet activation， DNA synthesis， metabolism and repair， as well as cell death and oxidative stress. HBP improved cardiovascular abnormalities such as reduced ejection fraction， myocardial fibrosis， myocarditis， hypertriglyceridemia， and arterial/venous thrombosis. Animal experiments demonstrated that HBP reduced the abnormal high expression of Nod-like receptor heat protein domain Protein 3 （NLRP3）， Caspase-1， apoptosis-associated speck-like protein （ASC）， and Gasdermin D （GSDMD） in myocardial tissue induced by doxorubicin （P<0.05）， and improved the elevated mRNA levels of fibrosis markers transforming growth factor-β₁ （TGF-β₁）， Smad3， and α-smooth muscle actin （α-SMA） （P<0.05）. ConclusionHBP can improve myocardial injury through multiple components， targets， and effects， with the inhibition of the NLRP3 inflammasome activation pathway being a key pharmacodynamic mechanism. This study is expected to provide new insights for the development of targeted therapeutic drugs.