Objective. To investigate the value of coagulation indicators D-dimer (DD), prothrombin time (PT), activated partial thromboplastin time (APTT), thrombin time (TT), and fibrinogen (Fg) in predicting the severity and prognosis of COVID-19. Methods. A total of 115 patients with confirmed COVID-19, who were admitted to Tianyou Hospital of Wuhan University of Science and Technology between January 18, 2020, and March 5, 2020, were included. The dynamic changes of DD, PT, APTT, and Fg were tested, and the correlation with CT imaging, clinical classifications, and prognosis was studied. Results. Coagulation disorder occurred at the early stage of COVID-19 infection, with 50 (43.5%) patients having DD increased and 74 (64.3%) patients having Fg increased. The levels of DD and Fg were correlated with clinical classification. Among 23 patients who deceased, 18 had DD increased at the first lab test, 22 had DD increased at the second and third lab tests, and 18 had prolonged PT at the third test. The results from ROC analyses for mortality risk showed that the AUCs of DD were 0.742, 0.818, and 0.851 in three times of test, respectively; PT was 0.643, 0.824, and 0.937. In addition, with the progression of the disease, the change of CT imaging was closely related to the increase of the DD value (P<0.01). Conclusions. Coagulation dysfunction is more likely to occur in severe and critically ill patients. DD and PT could be used as the significant indicators in predicting the mortality of COVID-19.

Virtual simulation (VS) as an emerging interactive pedagogical strategy has been paid more and more attentions in the undergraduate medical education. Because of the fast development of modern computer simulation technologies, more and more advanced and emerging VS-based instructional practices are constantly increasing to promote medical education in diverse forms. In order to describe an overview of the current trends in VS-based medical teaching and learning, this scoping review presented a worldwide analysis of 92 recently published articles of VS in the undergraduate medical teaching and learning. The results indicated that 98% of included articles were from Europe, North America, and Asia, suggesting a possible inequity in digital medical education. Half (52%) studies reported the immersive virtual reality (VR) application. Evidence for educational effectiveness of VS in medical students’ knowledge or skills was sufficient as per Kirkpatrick’s model of outcome evaluation. Recently, VS has been widely integrated in surgical procedural training, emergency and pediatric emergency medicine training, teaching of basic medical sciences, medical radiation and imaging, puncture or catheterization training, interprofessional medical education, and other case-based learning experiences. Some challenges, such as accessibility of VS instructional resources, lack of infrastructure, “decoupling” users from reality, as well as how to increase students’ motivation and engagement, should be addressed.

There is growing evidence that angiotensin‐converting enzyme 2 is highly expressed on endothelial cells, endothelial dysfunction plays a critical role in coronavirus disease 2019 (COVID‐19) progression, but laboratory evidence is still lacking. This study established a multicenter retrospective cohort of 966 COVID‐19 patients from three hospitals in Wuhan, China. We found that male (62.8% vs. 46.5%), old age [72 (17) vs. 60.5 (21)], and coexisting chronic diseases (88.5% vs. 60.0%) were associated with poor clinical prognosis in COVID‐19. Furthermore, the deteriorated patients exhibited more severe multiorgan damage, coagulation dysfunction, and extensive inflammation. Additionally, a cross‐sectional study including 41 non‐COVID‐19 controls and 39 COVID‐19 patients assayed endothelial function parameters in plasma and showed that COVID‐19 patients exhibited elevated vascular cell adhesion molecule‐1 (VCAM‐1) (median [IQR]: 0.32 [0.27] vs. 0.17 [0.11] μg/ml, p < 0.001), E‐selectin (21.06 [12.60] vs. 11.01 [4.63] ng/ml, p < 0.001), tissue‐type plasminogen activator (tPA) (0.22 [0.12] vs. 0.09 [0.04] ng/ml, p < 0.001), and decreased plasminogen activator inhibitor‐1 (0.75 [1.31] vs 6.20 [5.34] ng/ml, p < 0.001), as compared to normal controls. Moreover, VCAM‐1 was positively correlated with d ‐dimer ( R = 0.544, p < 0.001); tPA was positively correlated with d ‐dimer ( R = 0.800, p < 0.001) and blood urea nitrogen ( R = 0.638, p < 0.001). Our findings further confirm the strong association between endothelial dysfunction and poor prognosis of COVID‐19, which offers a rationale for targeting endothelial dysfunction as a therapeutic strategy for COVID‐19.

Target identification of small molecules is an important and still changeling work in the area of drug discovery, especially for botanical drug development. Indistinct understanding of the relationships of ligand–protein interactions is one of the main obstacles for drug repurposing and identification of off-targets. In this study, we collected 9063 crystal structures of ligand-binding proteins released from January, 1995 to April, 2021 in PDB bank, and split the complexes into 5133 interaction pairs of ligand atoms and protein fragments (covalently linked three heavy atoms) with interatomic distance ≤5 Å. The interaction pairs were grouped into ligand atoms with the same SYBYL atom type surrounding each type of protein fragment, which were further clustered via Bayesian Gaussian Mixture Model (BGMM). Gaussian distributions with ligand atoms ≥20 were identified as significant interaction patterns. Reliability of the significant interaction patterns was validated by comparing the difference of number of significant interaction patterns between the docked poses with higher and lower similarity to the native crystal structures. Fifty-one candidate targets of brucine, strychnine and icajine involved in Semen Strychni (Mǎ Qián Zǐ) and eight candidate targets of astragaloside-IV, formononetin and calycosin-7-glucoside involved in Astragalus (Huáng Qí) were predicted by the significant interaction patterns, in combination with docking, which were consistent with the therapeutic effects of Semen Strychni and Astragalus for cancer and chronic pain. The new strategy in this study improves the accuracy of target identification for small molecules, which will facilitate discovery of botanical drugs.

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Chemoresistance is a huge clinical challenge in the treatment of advanced colorectal cancer (CRC). Non-coding RNAs (ncRNAs) and messenger RNA (mRNA) are involved in CRC chemoresistance. However, the profiles of long ncRNAs (lncRNAs), microRNAs (miRNAs), mRNAs, and competing endogenous RNA (ceRNA) networks in CRC chemoresistance are still largely unknown. Here, we compared the gene expression profiles in chemo-sensitive (HCT8) and chemo-resistant (HCT8/5-fluorouracil (5-Fu) and HCT8/cisplatin (DDP)) cell lines by whole-transcriptome sequencing. The common differentially expressed (DE) RNAs in two drug-resistant cells were selected to construct lncRNA-miRNA-mRNA networks. The ceRNA network closely related to chemoresistance was further established based on the widely accepted drug resistance-associated genes enriched in three signaling pathways involved in chemoresistance. In total 52 lncRNA-miRNA-mRNA pathways were screened out, among which EPHA2 and LINC02418 were identified as hub genes; thus, LINC02418/miR-372-3p/EPHA2 were further selected and proved to affect the 5-Fu and DDP resistance of CRC. Mechanistically, LINC02418 upregulated EPHA2 by functioning as a “sponge” of miR-372-3p to modulate the chemoresistance of CRC. Collectively, our study uncovered the underlying mechanism of LINC02418/miR-372-3p/EPHA2 in 5-Fu and DDP resistance of CRC, which may provide potential therapeutic targets for improving the chemosensitivity of CRC.

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Background: In recent years, the incidence of hyperlipidemic acute pancreatitis(HLAP) is rapidly increasing. It is important for clinicians to identify the severity at early stage of HLAP. AIMS: The goal of this paper was to compare bedside index for severity in acute pancreatitis(BISAP) and modified CT severity index(MCTSI) for predicting the severity and local complications of HLAP. Methods: We collected 167 patients with HLAP, including 133 cases of Mild acute pancreatitis(MAP), 34 cases of Moderately severe acute pancreatitis(MSAP) and Severe acute pancreatitis(SAP). The study retrospectively analyzed the clinical characteristics of two groups(MAP group,MSAP and SAP group) of patients. Correlation analysis was demonstrated by Spearman,s test. In addition,the accuracy was investigated through the study of the receiver operating characteristic(ROC) curve to predict the severity of HLAP by BISAP and MCTSI score. Results There are significantly statistical differences(P<0.05) in Triglycerides(TG), Total cholesterols(TC), Hospitalization days, Fatty liver and Local complications between two groups. However, there are no statistical differences(P>0.05) in Gender, Age,Serum amylase, Alanine aminotransferase(ALT), Aspertate aminotransferase(AST), Hypertension, Type2 diabetes and Hyperuricemia. The Area Under the Curve(AUC) of BISAP andMCTSI in predicting the severity of HLAP respectively were 0.89 0.78, sensitivity were 73.5% 79.4%, specificity were95.5% 60.2%, positive predictive value(PPV) were 80.6% 33.8%, negative predictive value(NPV) were 93.4% 92.0%. Furthermore, the AUC respectively were 0.73 0.87, sensitivity were 37.5% 90.1%, specificity were 93.2% 78.6%, PPV were 77.4% 72.5%, NPV were 70.6% 93.1% in predictionig local complications. Conclusion Compared to MCTSI score, BISAP score may be a better prognostic scoring system for predicting the severity of HLAP in view of accuracy and easiness.