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Objective To evaluate the teaching performance of the traditional Chinese medicine (TCM)course for the first three grades of the “4+4” reform pilot class in clinical medicine at Peking Union Medical College. Methods An anonymous survey was conducted using Questionnaire Star and the responses from TCM Teaching Questionnaire completed by students were statistically analyzed and summarized. Results Most students expressed interest in TCM and deemed it necessary to study TCM course. They believed that teachers well prepared for teaching performance and the teaching content was well-aligned with the textbooks, syllabus, and lecture slides. The teaching content was closely integrated with clinical practice, and students were satisfied with the teaching methods and approaches. Conclusions Teaching evaluations help teachers to summarize their teaching experiences and improve the teaching quality of the TCM course.

Objective Studies on rehabilitation and nursing of stroke limb dysfunction at home and abroad was searched comprehensively, and the rehabilitation and nursing needs of stroke patients with limb dysfunction were summarized and analyzed, in order to provide reference for future related research. Methods The scoping review method was used to systematically search the Chinese and English databases of CNKI, Wanfang Data, VIP, CBM, PubMed, etc. , from the establishment of the database to July 26, 2021. The subject analysis of the included literatures was conducted based on the framework of the International Classification of Functioning, Disability and Health. Results Totally 19 literatures were included, and the results showed that the rehabilitation nursing needs of stroke patients with limb dysfunction were more diverse and complex, including five needs including disease and rehabilitation knowledge and information needs, activity participation needs, limb function recovery, social environment needs and psychological support needs. Conclusion The rehabilitation nursing needs of stroke patients with limb function are met at a low rate. Medical workers should pay attention to providing patients with diversified knowledge and education, and combine with multidisciplinary teams to develop individualized and scientific and comprehensive rehabilitation and nursing plans for stroke patients with limb dysfunction. (目的 全面检索国内外脑卒中肢体功能障碍康复护理相关研究, 对脑卒中肢体功能障碍患者康复护理需求现状、内容进行总结分析, 以期为今后相关研究提供参考。方法 采用范围综述法, 系统检索中国知网(CNKI)、万方(Wanfang Data)、维普数据库(VIP)、中国生物医学文献数据库(CBM)、PubMed等中英文数据库, 检索时间为建库至2021年7月26日, 并基于《国际功能、残疾和健康分类》(ICF)框架对纳入文献进行主题分析。结果 最终纳入19篇文献, 结果显示脑卒中肢体功能障碍患者康复护理需求种类较多, 且较为复杂, 主要包括疾病及康复知识信息需求、活动参与需求、肢体功能恢复、社会环境需求以及心理支持需求5个需求主题。结论 脑卒中肢体功能患者康复护理需求满足率较低, 医护人员需注重为患者提供多元化的知识教育, 并结合多学科团队, 为脑卒中肢体功能障碍患者制定个体化且科学全面的康复护理计划。)

The apprenticeship education of Traditional Chinese medicine(TCM) is an important pathway for the cultivation of talents in TCM education. The combination of institutional education and apprenticeship education is considered to be the most suitable educational model that aligns with the inherent characteristics of TCM education. The current status of TCM education in western medical institutions and the main challenges include the difficulty in transitioning between western and Chinese medical reasoning and limited clinical internship hours for TCM. The strengths and features of TCM apprenticeship education lie in cultural heritage, classical teachings, mentorship, practice orientation and personalized education. Therefore, integration of TCM apprenticeship education and clinical internships for western medical students represents a new educational model for medical undergraduates.

Non-small cell lung cancer (NSCLC) accounts for 85% of all lung cancer cases and is considered as the most common type of cancer. DLX4 was originally identified as a β-globin gene suppressor in red blood cells, which plays critical roles in several types of cancers. However, the role and related mechanism of DLX4 in NSCLC are still unclear. The study aimed to uncover the expression of DLX4 in human NSCLC cells and tissues, reveal its possible role in NSCLC, and investigate the underlying mechanisms. Immunoblot and TCGA database were used to detect the expression of DLX4 in human NSCLC cells and tissues. CCK-8, colony formation, and FCM assays were conducted to detect the effects of DLX4 on the viability and cell cycle of NCI-H2170 and A549 cells. Immunoblot assays were further performed to investigate the possible mechanism underlying DLX4 affecting the growth of NSCLC. We revealed that knockdown of DLX4 inhibited NSCLC cell proliferation. We further revealed that DLX4 knockdown induced the NSCLC cell cycle arrest. Our results further showed that downregulation of DLX4 suppressed YB-1 expression, which further suppressed CKS2 expression, thereby suppressing tumor growth of NSCLC. In conclusion, DLX4 has the potential to serve as a promising drug for NSCLC treatment.

Herein, curcumin (Cur) was encapsulated into poly(lactic-co-glycolic acid) (PLGA) nanoparticles to improve the water solubility of Cur, and the formulation was optimized by single factor experiments. The surface of PLGA nanoparticles was modified by human transferrin (Tf) to improve the absorption efficiency of active substances by intestinal cells. Our findings indicated that the optimal preparation method for Cur-PLGA-NP was solvent volatilization and mixing the oil phase with the aqueous phase at a volume ratio of 1:2.5, the optimal loading ratio was 1:15, and the optimal mass concentration of emulsifier F68 was 0.3%. The uptake of Tf-modified PLGA nanoparticles (Tf-NP) by human colon cancer cell line HT-29 cells was significantly higher than that of the control, indicating that both the loading efficiency of Cur and its absorption by intestinal cells were significantly improved by using Tf-NP as a delivery vehicle for Cur. In summary, the absorption efficiency of Cur can be improved by modifying Cur-loaded PLGA nanoparticles with Tf, which provides a reference for the design of delivery systems for active substances with poor water solubility.

Studies have shown that Internet financial news has become an important reference for investors in investment behavior. In order to simulate trading experiments that mimic the real stock market, this paper develops a stock volatility prediction model based on causal reasoning. It also gathers and cleans news and stock market data from the Internet, such as opening price, closing price, and change. The findings of the study indicate that the level of stock market volatility can be significantly influenced by online financial news. The proposed model can analyze the effects of news and stock market data in an explainable manner.

There are numerous stock market theories as a result of the gradual usage of mathematical models by researchers to forecast equities during the past few decades. By quantifying the rise and fall range, the prediction problem can be changed into a multi-classification problem based on the related data. This paper describes an Adversarial Learning-based stock forecast model by building a three-tier LSTM training network using the Adversarial Learning concept, selecting 300 stocks to represent the overall performance of the Chinese stock market, increasing the proportion of large to small training datasets, and strengthening the model’s ability to obtain detailed information from a small amount of data.

The current ideological education in colleges and universities is undergoing a series of changes, and the return of Chinese traditional culture to the system of ideological education in colleges and universities has become the development trend of the current ideological education. The study constructs the ARCS model of college civic education, integrating traditional culture according to the ARCS model, and improves the traditional hierarchical analysis method by introducing triangular fuzzy numbers so as to construct the evaluation index system of college civic education. The evaluation results of the ARCS model of Civic Education in Colleges and Universities, which integrates traditional culture, and its application effects on students’ civic performance and civic literacy are explored. In the three initial indexes of Teaching Content, Teaching Methods, and Teaching Effect, ARCS Civic Teaching in Colleges and Universities has a score of 0.826, 0.809, and 0.854, respectively. The scores of most of the second-level indexes are more than 0.8, and Civic Teaching in Colleges and Universities under ARCS has achieved a better evaluation result. The Civics scores of the experimental group and the control group do not have significant differences at the beginning of the experiment, and the significant p-value is 0.004 after the experiment, which is a significant difference. At the beginning of the experiment, the p-value of each Civic and Political Literacy of the two groups was greater than 0.05, and after the experiment, the p-value of each Civic and Political Literacy of the two groups was less than 0.05. The ARCS model of Civic and Political Education in Colleges and Universities, which integrates traditional culture, significantly improves the civic and political achievements and civic and political literacy of students.

Network ideological and political education is a great extension of school education, but the complex and confusing network information is also easy to give students bad emotional guidance. In this paper, microblogging data and topic clustering technology are used to obtain the emotional text data of network ideological and political education, based on the LDA model for topic feature extraction, to remove the data that has a lower degree of relevance to ideological and political education emotion in the data. Then, combined with the Jieba segmentation tool, based on the TF-IDF algorithm, for keyword extraction of the data that has been segmented. The text semantic features extracted based on the Word2Vec word vector model are used as the input information of this model, and the unique memory unit and gating structure of LSTM are utilized to solve the problem of storing memory of a priori knowledge and the problem of gradient dissipation caused by too long time threshold in long text classification. The Word2Vec-LSTM text sentiment classification model is developed and trained using Python and related machine learning libraries, and comparative experiments are carried out to validate the algorithm’s effectiveness and feasibility. The performance of Word2Vec-LSTM sentiment analysis on the dataset is higher than Word2Vec and LSTM algorithms. In addition, the value of sentiment perplexity is the smallest when the number of topics is set to be about 8, and its value is 0.542, and the positive sentiment density reaches the maximum value (0.648) as the sentiment score grows to 0.48. This paper explores the application of emotion analysis results in network ideological and political education to further improve the construction of a network ideological and political education system.

In order to confirm the performance of recessed green space in rainwater collection and utilization of urban roads, this paper proposes a corresponding experimental test program, which mainly covers the evaluation of rainwater infiltration, the evaluation of rainwater purification, and the simulation of rainfall-runoff reduction. Using the above test methods, the effectiveness of recessed green space in collecting and utilizing rainwater was analyzed. The results showed that in the one-way analysis of the compositional structure of the undercroft green space, the gravel layer, the media layer, and the vegetation layer had no significant difference in the infiltration rate sig red loam reactor (23.04 ml/min) > 2/8 mixed media reactor (23 ml/min) > black loam reactor (23.08 ml/min), while the order of purification effect was 3/7 mixed media > 2/8 mixed media > red loam > black loam. In addition, the combined high infiltration hypolimnetic green space had a better retention effect (flow yield range from 0 to 10 L) in rainfall-runoff with a reproduction period of 3 and 4 years. Based on the analysis results, the application effect of undercroft green space in urban road rainwater collection and utilization is comprehensively verified, and it is hoped that the investigation of this paper can bring certain references and references to the relevant personnel.

This paper firstly builds a diversified content system of ideological and political courses based on knowledge graph, extracts course knowledge, proposes a LEBERT-CRF entity recognition method that dynamically fuses words and word-level word vectors for the problems that arise in ideological and political courses, and uses dictionary adapters to integrate the features of ideological and political dictionaries into the BERT model, and then combines the resources of ideological and political courses to expand the data sources of knowledge graphs. Finally, taking the teaching and classroom of ideological and political courses in a university as an empirical study, the results show that the test results of the teaching objects on the feedback of ideological and political course content have very significant differences. The teaching observers give 8 “good” evaluations, 6 “average,” 5 “excellent” evaluations, and 2 “need for improvement” evaluations, indicating that the ideological and political elements are well integrated with the course content. The mean values of value orientation, ideological and political integration, ideological and political resources, discussion and interaction, reflection and evaluation, activity organization, technical support, resource push, and dual-line teaching were 3.776, 4.098, 3.874, 4.191, 4.075, 3.885, 4.265, 3.945, and 4.245, respectively. Students recognize the content system of ideological and political courses constructed in this paper. Therefore, the content system of ideological and political courses built in this paper can effectively solve the current situation of redundant and difficult-to-grasp ideological and political knowledge systematically.

The application of big data technology in the teaching of ideology and politics courses in colleges and universities can provide strong support for the precise reform and innovation of ideology and politics work. In this paper, we first sort out the status quo and dilemma of the teaching of ideology and politics courses in colleges and universities and analyze the advantages and feasibility of big data technology in the learning of ideology and politics. Then, based on the big data streaming computing Spark framework, a personalized learning service platform for teaching Civics and Politics courses in colleges and universities was established. Aiming at the online learning behavior of students on the platform, the K-mean algorithm is used to select their behavioral characteristics. The personalized recommendation of learning resources for Civics and Political Science courses is implemented based on the learning behavior. Data was utilized to analyze the effectiveness of the personalized learning platform in transforming the teaching of Civics and Political Science courses in colleges and universities using S University as the research object. The study found that the number of focused learners in category 1 of the online learning behavior reached 303, and the teaching of the Civic and Political Science course based on the personalized learning platform helped the students’ will cultivation score increase by 2.49 points and more than 95% of the students recognized the platform. The customized service learning platform for teaching Civics courses established based on big data can realize the innovative transformation of Civics courses in colleges and universities and improve the teaching quality and level of Civics courses in colleges and universities.

Evaluating innovation and entrepreneurship ability measurement of college students is one of the critical areas of research on innovation ability cultivation in colleges and universities. In this study, based on the existing Bayesian knowledge tracking model, the parameter matrix of innovation and entrepreneurship knowledge point relationship is added to improve the standard knowledge tracking model. The CS-BKT model is proposed to provide college teachers with detailed mastery of students’ innovation and entrepreneurship knowledge. Then the corresponding state space is delineated according to the mastery situation, and the evaluation model of innovation and entrepreneurship ability measurement for college students based on polymorphic rewarded Markov chain is constructed. Combined with different transfer probabilities, the model operates on student data to measure students’ innovation and entrepreneurship ability. The results of the study showed that there was a significant difference between the acceptance and non-acceptance of innovation and entrepreneurship education in students’ innovation and entrepreneurship competence, and the level of innovation and entrepreneurship competence of students who had accepted it was 3.71, which was higher than that of students who had not taken it (3.53). There is a significant positive correlation between the social level of the place of origin, the individual level of entrepreneurial experience, and the rank of professional achievement and innovation and entrepreneurship ability, with p-values of 0.008, 0.003, and 0.001 respectively are less than 0.01. This study concludes the factors influencing the innovation and entrepreneurship ability of college students, which provides a reference value to the formation and development of the innovation and entrepreneurship ability of the students.

Based on a large amount of energy consumption, performance indicators and base station configuration data that can be collected in the 5G network management system, this paper uses machine learning algorithms to establish an energy consumption calculation model for common AAU equipment on the existing network, and verifies the accuracy of the model. The test results show that the accuracy of the energy consumption calculation models established by this scheme for several common AAU devices in the existing network has reached more than 97%, which fully proves that the energy consumption modeling method has high practicability and promotion value.

Objective To understand the current situation of self-management and its influencing factors of elderly coronary heart disease (CHD) patients in rural areas of Beijing. Methods Using the convenience sampling method, elderly CHD patients in rural areas of Beijing were selected, and their knowledge level, self-management attitude and self-management behavior were surveyed, and 221 valid questionnaires were collected. Results The knowledge level and self-management behavior of elderly CHD patients in rural areas of Beijing were at a low level, and their self-management attitude was at a middle level. The results of the multiple linear regression analysis showed that gender, education level, household per capita monthly income, primary support site of access to care, knowledge of CHD, and self-management attitude were entered into the regression model. Conclusion There is much room for improvement of the knowledge level, attitude and behavior of elderly patients in rural areas of Beijing. Patient gender, educational level, the per capita monthly family income, primary support site of access to care, the knowledge of CHD, and the self-management attitude are the factors influencing the self-management behavior of elderly CHD patients in rural areas of Beijing. (目的 了解北京市农村地区老年冠心病患者自我管理现状及其影响因素。方法 采用方便抽样法从北京市抽取农村老年冠心病患者, 对其知识水平、自我管理态度和自我管理行为进行问卷调查。共发放250份问卷, 回收有效问卷221份。结果 北京市农村老年冠心病患者关于冠心病知识水平、自我管理行为处于低水平, 自我管理态度处于中等水平。多元线性回归分析结果显示, 性别、文化程度、家庭人均月收入、获得护理主要支持地点、冠心病知识、自我管理态度进入回归模型。结论 北京市农村地区老年冠心病患者的知识水平、态度以及行为均有较大提升空间。患者的性别、文化程度、家庭人均月收入、获得护理主要支持地点、冠心病知识、自我管理态度是北京市农村老年冠心病患者自我管理行为的影响因素。)

We use first-principles energy density method (EDM) to calculate atomic energies for isolated [Formula: see text]-type basal and prism screw dislocation cores in Mg and compute line energies and core energy differences. The atomic energy distribution in the dislocations reflect the slip in the cores and the elastic energy further afield. Line energies are computed by summing up atomic energies, from which core energies and energy differences are straightforward to determine. We compare our results with two different classical potentials.

Abstract The molecular control of osteoclast formation is still not clearly elucidated. Here, we show that a process of cell recognition mediated by Siglec15-TLR2 binding is indispensable and occurs prior to cell fusion in RANKL-mediated osteoclastogenesis. Siglec15 has been shown to regulate osteoclastic bone resorption. However, the receptor for Siglec15 has not been identified, and the signaling mechanism involving Siglec15 in osteoclast function remains unclear. We found that Siglec15 bound sialylated TLR2 as its receptor and that the binding of sialylated TLR2 to Siglec15 in macrophages committed to the osteoclast-lineage initiated cell fusion for osteoclast formation, in which sialic acid was transferred by the sialyltransferase ST3Gal1. Interestingly, the expression of Siglec15 in macrophages was activated by M-CSF, whereas ST3Gal1 expression was induced by RANKL. Both Siglec15-specific deletion in macrophages and intrafemoral injection of sialidase abrogated cell recognition and reduced subsequent cell fusion for the formation of osteoclasts, resulting in increased bone formation in mice. Thus, our results reveal that cell recognition mediated by the binding of sialylated TLR2 to Siglec15 initiates cell fusion for osteoclast formation.

The potato of the Netherlands shiwu and four edible oils were taken as the research objects, and the effects of oil types on the texture, the kinetic constant of water loss and oil absorption, the spatial distribution of moisture, the crystal structure and microstructure of French fries during the frying process were investigated. The results showed that the surface hardness of fries fried in palm oil and rice bran oil was higher than that of the other two oil. The results of water loss kinetics showed that the surface water loss rate of fries fried in palm oil was the fastest (0.053 6 s–1), followed by rice bran oil (0.027 5 s–1), and high oleic sunflower oil was the slowest (0.021 6 s–1). Magnetic resonance imaging also confirmed this result. X-ray diffraction results showed that the starch-lipid complex content of fries fried in rice bran oil and palm oil was higher than that of the other two. From the results of scanning electron microscopy, it can be seen that the surface of fries fried in palm oil and rice bran oil was more compact than others. In summary, the fast surface water loss, high starch-lipid complex content and surface compactness play an important role in improving the texture of French fries.

The effects of pretreatment combined with different maturing methods (such as blanching, microwaving, etc) and different freezing methods (such as, conventional freezing and ultra-low temperature freezing) on the oil absorption of fried potato strips were compared and analyzed. It was found that compared with blanching combined with conventional freezing pretreatment, changing the blanching to microwave reduced the total oil content of fried potato strips by 15.86%. Changing the conventional freezing to ultra-low temperature freezing reduced the total oil content by 6.09%. Microwaving combined with ultra-low temperature freezing pretreatment reduced the total oil content by 20.46%. The results of confocal laser microscope (CLSM), differential scanning calorimeter (DSC) and scanning electron microscope (SEM) confirmed that, compared with other pretreatment method, microwave combined with ultra-low temperature freezing pretreatment produced more VII type starch-lipid complexes in the crust layer of fried potato strips. The surface structure was smooth. The attached oil was less. The internal structure was less damaged. The results of sensory evaluation results showed that microwave combined with ultra-low temperature freezing pretreatment improved the quality of fried potato strips and reduced the oil absorption.

Abstract Osteoporosis (OP) is a common age-related disease characterized by a deterioration of bone mass and structure that predisposes patients to fragility fractures. Pharmaceutical therapies that promote anabolic bone formation in OP patients and OP-induced fracture are needed. We investigated whether a neutralizing antibody against Siglec-15 can simultaneously inhibit bone resorption and stimulate bone formation. We found that the multinucleation of osteoclasts was inhibited in SIGLEC-15 conditional knockout mice and mice undergoing Siglec-15 neutralizing antibody treatment. The secretion of platelet-derived growth factor-BB (PDGF-BB), the number of tartrate-resistant acid phosphatase-positive (TRAP+) mononuclear cells, and bone formation were significantly increased in the SIGLEC-15 conditional knockout mice and antibody-treated mice. The anabolic effect of the Siglec-15 neutralizing antibody on bone formation was blunted in mice with Pdgfb deleted in TRAP+ cells. These findings showed that the anabolic effect of the Siglec-15 neutralizing antibody was mediated by elevating PDGF-BB production of TRAP+ mononuclear cells. To test the therapeutic potential of the Siglec-15 neutralizing antibody, we injected the antibody in an ovariectomy-induced osteoporotic mouse model, which mimics postmenopausal osteoporosis in women, and in two fracture healing models because fracture is the most serious health consequence of osteoporosis. The Siglec-15 neutralizing antibody effectively reduced bone resorption and stimulated bone formation in estrogen deficiency-induced osteoporosis. Of note, the Siglec-15 neutralizing antibody promoted intramembranous and endochondral ossification at the damaged area of cortical bone in fracture healing mouse models. Thus, the Siglec-15 neutralizing antibody shows significant translational potential as a novel therapy for OP and bone fracture.

Objective To evaluate the online teaching of Traditional Chinese Medicine(TCM) for undergraduates in Nursing College of Peking Union Medical College in 2020. Methods Totally 144 students were asked to fill in the questionnaire of TCM teaching focusing on 7 parts of questions:the TCM and the courses, comparison of online with offline one, the evaluation of students' autonomous learning, the comprehensive evaluation of teaching, the evaluation of learning outcomes, and the evaluation of examination The overall evaluation of the course and the evaluation of the future application of TCM were statistically analyzed. Results Totally 144 questionnaires were collected. About 90% of the students were interested in TCM and was necessary to learn. There are 76.39% of the students thought that the teaching platform of Tencent conference was the best. In online teaching, 34.72% of the students fully joined the lectures, and the others only joined part of the course. Results also showed that 48.61% of students believed the learning outcome of online teaching was similar to that of offline teaching and 22.22% preferred online one. More than 99% of the students thought that teachers had mastered the skills of using online teaching platform, and the evaluation of quality and effect of teaching was good. Over half of students (66.67%) hoped to introduce MOOC, 45.83% hoped to introduce micro class,38.89% students hoped to use flipped classroom and 55.56% of them chose open book examination combined with usual attendance for final assessment. The results also showed that 39.58% of students thought that TCM was difficult to learn and 46.93% thought that TCM could not be self-taught. More than 50% of the students said that they would let their patients receive TCM treatment or nursing in the future. Conclusions It is necessary for undergraduates in hospital of Western Medicine to study TCM and to increase the teaching hours. Online teaching raises higher standards for teachers, and the evaluation can improve teaching quality.

The functional relationship between subchondral bone and articular cartilage is unclear. Here, the authors show that transforming growth factor-beta propagates the mechanical impact of subchondral bone on articular cartilage through αV integrin–talin mechanical transduction system in chondrocytes.

The China Loess Plateau (CLP) is a unique geomorphological unit with abundant coal resources but a fragile ecological environment. Since the implementation of the Western Development plan in 2000, the Grain for Green Project (GGP), coal mining, and urbanization have been extensively promoted by the government in the CLP. However, research on the influence of these human projects on the ecological environment (EE) is still lacking. In this study, we investigated the spatial–temporal variation of EE in a typical CLP region using a Remote Sensing Ecological Index (RSEI) based on the Google Earth Engine (GEE). We obtained a long RSEI time series from 2002–2022, and used trend analysis and rescaled range analysis to predict changing trends in EE. Finally, we used Geodetector to verify the influence of three human projects (GGP, coal mining, and urbanization). Our results show that GGP was the major driving factor of ecological changes in the typical CLP region, while coal mining and urbanization had significant local effects on EE. Our research provides valuable support for ecological protection and sustainable social development in the relatively underdeveloped region of northwest China.

MicroRNA （miRNA） belongs to a class of endogenous non-coding small RNA molecules with a length of 18-24 nucleotides. The expression of miRNA is highly conservative, has time sequence and is highly tissue-specific. MiRNA could not be easily degraded by ribonuclease, and is resistant to changes in environmental factors such as temperature and pH value. Moreover, miRNA can even be detected in corrupt tissue. As a result, miRNA has broad application prospects in many fields of forensic medicine such as source identification of body fluid and estimation of cause of death. This article briefly summarizes the application of miRNA in forensic practice, such as body fluid identification, determination of postmortem interval and cause of death analysis.

Objective To explore the role of teaching evaluation in the practice of “traditional Chinese medicine” course for eight-year undergraduates of Peking Union Medical College. Methods With a secret questionnaire survey, statistics and summarize both the teaching and teacher evaluation forms completed by students from 2012 to 2017. Results The 6-year overall satisfaction rate of students on teaching content, teaching methods, clinical apprenticeship, teaching effect, and use of textbooks was over 94.3%, and the dissatisfaction rate was 0-5.7%. The highest satisfaction rate was on clinical apprenticeship. The satisfaction rate of school-made textbook was around 98%. The praises given to the teachers were 90.1%-97.5%. The satisfaction rate in the first 3 years was higher than that in the later 3 years. Conclusions Teaching evaluation can promote the continues improvement of traditional Chinese medicine education in non-traditional medicine hospitals and optimize teaching quality.

Objective To investigate the clinical efficacy of single-clamp endoscopic 8-shaped suture for closure of iatrogenic perforation in the upper digestive tract following endoscopic full-thickness resection (EFTR). Methods We retrospectively analyzed the data of 38 patients with upper gastrointestinal submucosal tumors (SMT) with a diameter greater than 2 cm, which originated from the deep muscularis of the muscularis propria with bidirectional growth and were confirmed by preoperative abdominal CT and endoscopic ultrasonography in the Digestive Endoscopy Center of our hospital between November, 2018 and July, 2019. All these patients underwent EFTR of tumor, which resulted in iatrogenic perforation in the upper digestive tract. Single-clamp endoscopic 8-shaped suture was used to close the perforation, and the intra- and postoperative complications and postoperative follow-up data were analyzed to assess the feasibility, safety and efficacy of the approach. Results The patients had an average tumor diameter of 2.6±0.8 cm and a mean wound diameter of 3.8±0.5 cm. The perforation was successfully repaired in all the 38 cases with a mean suture time of 12.6±1.8 min. Six (15.8%) of the patients complained of abdominal pain and bloating after the operation, and 4 (10.5%) patients had fever postoperatively, which was transient in 3 cases and as a result of infection due to failure of suture disconnection in the other case. None of the patients had serious intraoperative and postoperative complications or conversion to open surgery during the operation. The postoperative hospital stay was 5-9 d, and the endoscopic wounds healed well at 1 month after the operation in all the cases with visible scar formation. Follow-up endoscopy at 3 months postoperatively revealed good wound healing without signs of tumor recurrence. Conclusion Single-clamp endoscopic 8-shaped suture can effectively repair iatrogenic perforation after EFTR, which has good safety and less invasiveness with a low cost and a low risk of conversion to open surgery.

Enterocytozoon bieneusi is a common pathogen in humans and various animals, threatening the breeding industry and public health. However, there is limited information on the molecular characteristics of E. bieneusi in yaks, an economically important animal mainly domesticated in the Qinghai Tibet Plateau in China. In the present study, nested PCR targeting the ITS gene region was applied to investigate the positive rates and genetic diversity of E. bieneusi in 223 faecal samples of yaks from three locations in Ganzi Tibetan Autonomous Prefecture, Sichuan Province. The total positive rate of E. bieneusi was 23.8% (53/223). Significant differences in positive rates were identified among yaks from three locations (χ2 = 8.535, p = 0.014) and four age groups (χ2 = 17.259, p = 0.001), with the highest positive rates in yaks from Yajiang and aged < 6 months, respectively. Sequence analysis identified seven known (EbpC, LW1, LQ10, PigEBITS5, ESH-01, J and BEB4) and five novel (Ganzi1–5) ITS genotypes. Phylogenetic analysis showed eight genotypes (EbpC, LW1, LQ10, PigEBITS5, ESH-01, Ganzi1, Ganzi2 and Ganzi4) in group 1 and three genotypes (J, BEB4 and Ganzi3) in group 2, indicating high genotype diversity and zoonotic potential of E. bieneusi in yaks from Ganzi. Considering the increasing zoonotic genotypes in yaks in the present study compared with previous findings, interventions should be developed to reduce the potential transmission of E. bieneusi between humans and animals.

Progress in science requires standardized assays whose results can be readily shared, compared, and reproduced across laboratories. Reproducibility, however, has been a concern in neuroscience, particularly for measurements of mouse behavior. Here, we show that a standardized task to probe decision-making in mice produces reproducible results across multiple laboratories. We adopted a task for head-fixed mice that assays perceptual and value-based decision making, and we standardized training protocol and experimental hardware, software, and procedures. We trained 140 mice across seven laboratories in three countries, and we collected 5 million mouse choices into a publicly available database. Learning speed was variable across mice and laboratories, but once training was complete there were no significant differences in behavior across laboratories. Mice in different laboratories adopted similar reliance on visual stimuli, on past successes and failures, and on estimates of stimulus prior probability to guide their choices. These results reveal that a complex mouse behavior can be reproduced across multiple laboratories. They establish a standard for reproducible rodent behavior, and provide an unprecedented dataset and open-access tools to study decision-making in mice. More generally, they indicate a path toward achieving reproducibility in neuroscience through collaborative open-science approaches.

The vlPAG in the midbrain is known to suppress REM sleep, but the precise neural correlates are not known. Here, the authors record the activity of vlPAG GABAergic neurons during the sleep–wake cycle and report fast changes at REM sleep transitions and slower changes that correlate with REM sleep pressure.

In recent years, global natural disasters have been frequent and resulted in great casualties and property loss. Since Wenchuan earthquake, the disaster emergency rescue system of China has obtained considerable development in various aspects including team construction, task scheduling, personnel training, facilities and equipments, logistics, etc. On April 25, 2015, an earthquake that measured 8.1 on the Richter scale attacked Nepal. Chinese government firstly organized a medical team, named China Medical Team, and sent it to the attacked region in Nepal to implement medical rescue. The medical team completed the rescue mission successfully and creatively based on their experiences.

Studying the biology of sleep requires the accurate assessment of the state of experimental subjects, and manual analysis of relevant data is a major bottleneck. Recently, deep learning applied to electroencephalogram and electromyogram data has shown great promise as a sleep scoring method, approaching the limits of inter-rater reliability. As with any machine learning algorithm, the inputs to a sleep scoring classifier are typically standardized in order to remove distributional shift caused by variability in the signal collection process. However, in scientific data, experimental manipulations introduce variability that should not be removed. For example, in sleep scoring, the fraction of time spent in each arousal state can vary between control and experimental subjects. We introduce a standardization method, mixture z-scoring, that preserves this crucial form of distributional shift. Using both a simulated experiment and mouse in vivo data, we demonstrate that a common standardization method used by state-of-the-art sleep scoring algorithms introduces systematic bias, but that mixture z-scoring does not. We present a free, open-source user interface that uses a compact neural network and mixture z-scoring to allow for rapid sleep scoring with accuracy that compares well to contemporary methods. This work provides a set of computational tools for the robust automation of sleep scoring.