The practice and exploration of bilingual teaching for the course of microbiology has been made in order to improve the students foreign lingual level and to meet the higher requirement on tip-top person with the social development. As a result,bilingual teaching is welcome,and the teaching effect is so distinct that the aim was reached to either study the fundamental knowledge or enhance the English level.

OBJECTIVETo investigate the influences of verapamil preconditioning on cardiac function in vitro and intracellular free Ca2+ and L-type calcium current (I(Ca-L)) in rat cardiomyocytes post ischemia-reperfusion (I/R) injury.

METHODSThe isolated rat hearts in control group (37 degrees C Tyrode solution perfusion for 30 min, n = 6), I/R group (no flow for 30 min followed 30 min reperfusion with 37 degrees C Tyrode solution, n = 7) and verapamil preconditioning group [37 degrees C Tyrode solution perfusion for 10 min, adding verapamil (20 micromol/L) to Tyrode solution and perfusion for another 30 min, followed then by 30 min no flow and 30 min reperfusion, n = 7] using Langendorff perfusion system. The fluorescence intensity of intracellular Ca2+ was detected with Fluo-3/AM loading by the laser scanning confocal microscope. The I(Ca-L) was recorded via whole-cell patch clamp technique in enzymatically dissociated single rat ventricular myocytes.

RESULTSAs expected, arrhythmias and cardiac dysfunction were shown post I/R injury. The fluorescence intensities of intracellular free Ca2+ in cardiomyocytes were significantly increased compared with control group (P < 0.01). By voltage clamp protocol, peak current densities of I(Ca-L) was significantly reduced and I-V curve significantly elevated. Post I/R injury compared with control group (P < 0.01) which could be reversed by Verapamil preconditioning. Verapamil preconditioning also significantly improved diastolic and systolic functions, and reduced the incidence of arrhythmias.

CONCLUSIONSMyocardial I/R injury might significantly impair heart functions and induce arrhythmias via cellular Ca2+ overload. Verapamil preconditioning could prevent heart I/R injury and reduce arrhythmias by decreasing influx of I(Ca-L), thereby stabilizing cardiomyocytes in myocardial stunning and avoiding occurrence of Ca2+-induced Ca2+ release during I/R injury.

Animals ; Calcium ; metabolism ; Calcium Channels, L-Type ; drug effects ; Ischemic Preconditioning, Myocardial ; methods ; Myocardial Reperfusion Injury ; metabolism ; physiopathology ; Myocytes, Cardiac ; drug effects ; metabolism ; Rats ; Rats, Sprague-Dawley ; Verapamil ; pharmacology

The primary outbreak of severe acute respiratory syndrome coronavirus 2, causing pneumonia-like symptoms in patients named coronavirus disease 2019 (COVID-19) had evolved into a global pandemic. COVID-19 has surpassed Middle East respiratory syndrome and severe acute respiratory syndrome in terms of rate and scale causing more than one million deaths.Development of an effective vaccine to fight against the spread of COVID-19 is the main goal of many countries around the world and plant-based vaccines are one of the available methods in vaccine developments. Plant-based vaccine has gained its reputation among researchers for its known effective manufacturing process and cost effectiveness. Many companies around the world are participating in the race to develop an effective vaccine by using the plant system. This review discusses different approaches used as well as highlights the challenges faced by various companies and research groups in developing the plant-based COVID-19 vaccine.

Objective:To explore the model of first aid skills training based on competition.Method:The second-year residents who participated in the competition in 2021 ( n = 142) were selected. According to whether they attended BLS training in the first year, they were divided into group A ( n = 88) who attended BLS training and group B ( n = 54) who did not. Chi-square test, T test, Wilcoxon rank sum test and Logistic regression were used in our study. Results:There was no significant difference in gender and specialty between both groups (female, 62.5% vs. 68.5%, P= 0.466; TCM, 50% vs. 53.7%, P= 0.668), but the real resuscitation experience of group A was more than that of group B (40.9% vs. 9.3%, P= 0.000). The qualified rate of CPR and the compression score in group A was higher than that in group B [(81.8% vs. 61.1%, P = 0.006; (30±5) vs. (25 ±10), P= 0.001], including compression frequency, depth, rebound and compression/respiration rate (73.9% vs. 55.6%, P= 0.024; 88.6% vs. 70.4%, P= 0.006; 96.6% vs. 87%, P= 0.031). In the theoretical examination, the correct rates of electrocardiogram [(53.63±2.9)% vs. (50.44±2.57)%] and first aid medication [(57.38±3.55)%, P = 0.001] in the two groups were significantly lower than the qualified rate. After adjusting other factors, Logistic regression analysis showed that the CPR qualification rate in group A was 2.769 times higher than that in group B ( P= 0.015, 95% CI 1.215~6.311) Conclusions:The first aid skills training mode based on competition can objectively reflect first aid skills level of residents. We found that the quality of CPR skills was not related to gender, specialty and real CPR experiences but experience of BLS training was an independent influencing factor. And how to identify and manage arrhythmias and how to choose different emergency drugs are urgent emergency skills for residents to improve.

In recent years, the application of stent intervention in the treatment of non-vascular stenosis caused by benign and malignant factors has been widely concerned by researchers at home and abroad. The high incidence of malignant tumor diseases, further promotes the development of stent intervention. The conventional bare stents are prone to irritate luminal mucosa and produce restenosis and other complications. The emergence of drug-eluting stent is expected to solve this problem and become one of the important development trends of non-vascular stents. In this paper, the drug loading materials, drug loading layer drugs, preparation technology and quality evaluation methods of non-vascular drugeluting stent are described based on the recent research and clinical application documents, so as to provide basis and direction for the follow-up research and development.
Coronary Restenosis ; Drug-Eluting Stents ; Humans ; Prosthesis Design ; Treatment Outcome

BACKGROUND: The current deep learning diagnosis of breast masses is mainly reflected by the diagnosis of benign and malignant lesions. In China, breast masses are divided into four categories according to the treatment method: inflammatory masses, adenosis, benign tumors, and malignant tumors. These categorizations are important for guiding clinical treatment. In this study, we aimed to develop a convolutional neural network (CNN) for classification of these four breast mass types using ultrasound (US) images. METHODS: Taking breast biopsy or pathological examinations as the reference standard, CNNs were used to establish models for the four-way classification of 3623 breast cancer patients from 13 centers. The patients were randomly divided into training and test groups (n = 1810 vs. n = 1813). Separate models were created for two-dimensional (2D) images only, 2D and color Doppler flow imaging (2D-CDFI), and 2D-CDFI and pulsed wave Doppler (2D-CDFI-PW) images. The performance of these three models was compared using sensitivity, specificity, area under receiver operating characteristic curve (AUC), positive (PPV) and negative predictive values (NPV), positive (LR+) and negative likelihood ratios (LR-), and the performance of the 2D model was further compared between masses of different sizes with above statistical indicators, between images from different hospitals with AUC, and with the performance of 37 radiologists. RESULTS: The accuracies of the 2D, 2D-CDFI, and 2D-CDFI-PW models on the test set were 87.9%, 89.2%, and 88.7%, respectively. The AUCs for classification of benign tumors, malignant tumors, inflammatory masses, and adenosis were 0.90, 0.91, 0.90, and 0.89, respectively (95% confidence intervals [CIs], 0.87-0.91, 0.89-0.92, 0.87-0.91, and 0.86-0.90). The 2D-CDFI model showed better accuracy (89.2%) on the test set than the 2D (87.9%) and 2D-CDFI-PW (88.7%) models. The 2D model showed accuracy of 81.7% on breast masses ≤1 cm and 82.3% on breast masses >1 cm; there was a significant difference between the two groups (P < 0.001). The accuracy of the CNN classifications for the test set (89.2%) was significantly higher than that of all the radiologists (30%). CONCLUSIONS: The CNN may have high accuracy for classification of US images of breast masses and perform significantly better than human radiologists. TRIAL REGISTRATION Chictr.org, ChiCTR1900021375; http://www.chictr.org.cn/showproj.aspx?proj=33139.
Area Under Curve ; Breast/diagnostic imaging* ; Breast Neoplasms/diagnostic imaging* ; China ; Deep Learning ; Humans ; ROC Curve ; Sensitivity and Specificity