人体寄生虫学网络课程的应用与评价

目的对郧阳医学院人体寄生虫学网络课程的教学效果进行评价。方法选取2005级临床医学一系和二系分别作为实验组和对照组，对照组的人体寄生虫学采用传统教学方法教学，实验组采用传统教学和本课题组构建的人体寄生虫学网络课程平台进行辅助教学。结果实验组学生的人体寄生虫学理论课程考试成绩和实验课程考试成绩明显优于对照组学生（P〈0．05）。结论人体寄生虫学网络课程能够显著提高教学效果，对突破传统面授教学的局限性和帮助学生网上学习具有重要意义。     

Infrared spectroscopy: A new diagnostic tool in Alzheimer disease

Biological markers play an evolving role in the diagnosis of Alzheimer disease (AD). We compare conventional measurements of cerebrospinal fluid (CSF) tau and β-amyloid_1–42 proteins to a novel approach – Fourier transformed infrared (FT-IR) spectroscopy – a simple technique derived from chemical and physical sciences that characterizes intramolecular bonds. For automatic diagnostic analysis, we developed an artificial neural network (ANN). We examined 71 patients with a clinical diagnosis of AD and 66 controls. β-Amyloid_1–42 was decreased (sensitivity 80% and specificity 78%); tau was elevated (sensitivity 76% and specificity 88%) in CSF of AD patients. The combined tau/β-amyloid_1–42 quotient was able to distinguish healthy from diseased subjects with 99% sensitivity and 86% specificity. The ANN could separate FT-IR spectroscopy data with 88.5% sensitivity and 80% specificity. FT-IR spectroscopy proved to be cost-effective and simple to perform. Diagnostic sensitivity and specificity is in the range of CSF tau and β-amyloid_1–42 protein analysis. Larger sample numbers for ANN training and validation could increase diagnostic accuracy and thus prove to be a useful screening tool.     

利用神经网络集成预测MHC-Ⅰ类分子结合肽

目的：利用神经网络集成（NNE）预测MHC-Ⅰ类分子结合肽。 方法： 基于HLA-A*0201编码的MHC-Ⅰ类分子结合肽数据库（含有628个9聚物）及其结合能力分类，利用NNE分别对具有无、低、中和高4类亲合性的结合肽进行分类预测；同时还进一步利用T细胞真实表位集（含50个表位）评估了NNE的预测性能。 结果： 集成数为12的NNE对上述分类的平均预测命中率可达0.8,而且NNE对潜在T细胞表位的预测能力也较高，约84%的真实表位归于高和中等亲合性的潜在抗原肽一类。 结论： 可以利用神经网络集成预测MHC-Ⅰ类分子结合肽，并进而预测相应的T细胞表位。经适当修改，NNE预测工具可扩展为能涵盖任意长度的Ⅰ类分子结合肽甚至可扩展到Ⅱ类分子结合肽的预测。     

Control of feeding rhythm in the terrestrial slug Incilaria bilineata

A modulatory neuron of feeding rhythm was newly identified in the buccal ganglia of the isolated central nervous system (CNS) of the terrestrial slug Incilaria bilineata. This neuron was termed the “feeding rhythm modulator” (FRM). Its morphological and electrical properties were compared with those of the MGC (metacerebral giant cell, a cerebral modulatory neuron of feeding rhythm). There was no direct connection between FRM and MGC. In order to investigate the control mechanism of the buccal central pattern generator, feeding rhythm was observed by varying the activities of MGC and FRM simultaneously. At a lower level of activity of MGC, feeding rhythm was not only sensitive to the activity of MGC but also to that of FRM. As the level of activity of MGC increased, feeding rhythm was exclusively controlled by the activity of MGC, and became unaffected by the activity of FRM. This indicates that cerebral neurons such as MGC primarily control feeding rhythm and modulate the contribution of FRM in a hierarchical manner.     

The superspreading places of COVID-19 and the associated built-environment and socio-demographic features: A study using a spatial network framework and individual-level activity data

Previous studies observed that most COVID-19 infections were transmitted by a few individuals at a few high-risk places (e.g., bars or social gathering venues). These individuals, often called superspreaders, transmit the virus to an unexpectedly large number of people. Further, a small number of superspreading places (SSPs) where this occurred account for a large number of COVID-19 transmissions. In this study, we propose a spatial network framework for identifying the SSPs that disproportionately spread COVID-19. Using individual-level activity data of the confirmed cases in Hong Kong, we first identify the high-risk places in the first four COVID-19 waves using the space-time kernel density method (STKDE). Then, we identify the SSPs among these high-risk places by constructing spatial networks that integrate the flow intensity of the confirmed cases. We also examine what built-environment and socio-demographic features would make a high-risk place to more likely become an SSP in different waves of COVID-19 by using regression models. The results indicate that some places had very high transmission risk and suffered from repeated COVID-19 outbreaks over the four waves, and some of these high-risk places were SSPs where most (about 80%) of the COVID-19 transmission occurred due to their intense spatial interactions with other places. Further, we find that high-risk places with dense urban renewal buildings and high median monthly household rent-to-income ratio have higher odds of being SSPs. The results also imply that the associations between built-environment and socio-demographic features with the high-risk places and SSPs are dynamic over time. The implications for better policymaking during the COVID-19 pandemic are discussed.     

Antihypertensive Medication Classes and the Risk of Dementia: A Systematic Review and Network Meta-Analysis

ObjectivesTo systematically review and synthesize the evidence on differential associations between antihypertensive medication (AHM) classes and the risk of incident dementia.DesignSystematic review and random effects frequentist network meta-analysis. Embase, MEDLINE, and the Cochrane library were searched from origin to December 2019.Setting and participantsRandomized controlled trials (RCTs) and prospective cohort studies that compared associations of different AHM classes with incident all-cause dementia and/or Alzheimer's disease over at least 1 year of follow-up.MeasuresAll cause dementia and/or Alzheimer's disease.ResultsFifteen observational studies and 7 RCTs were included. Data on AHM classes were available for 649,790 participants and dementia occurred in 19,600 (3.02%). Network meta-analysis showed that in observational studies, treatment with either calcium channel blockers (CCBs) or angiotensin II receptor blockers (ARBs) was associated with lower dementia risks than treatment with other antihypertensives: CCBs vs angiotensin converting enzyme inhibitors (ACE inhibitors) (HR=0.84, 95% CI 0.74-0.95), beta blockers (HR=0.83, 95% CI 0.73-0.95) and diuretics (HR=0.89, 95% CI 0.78-1.01) and ARBs vs ACE inhibitors (HR=0.88, 95% CI 0.81-0.97), beta blockers (HR=0.87, 95% CI 0.77-0.99), and diuretics (HR=0.93, 95% CI 0.83-1.05). There were insufficient RCTs to create a robust network based on randomized data alone.Conclusions and ImplicationsRecommending CCBs or ARBs as preferred first-line antihypertensive treatment may significantly reduce the risk of dementia. If corroborated in a randomized setting, these findings reflect a low-cost and scalable opportunity to reduce dementia incidence worldwide.     

大学生男男性行为者社会网络特征与多性伴的相关性研究

目的 了解长沙市大学生男男性行为人群(men who have sex with men, MSM)的社会网络特征与多性伴之间的相关性,为制定更有针对性的艾滋病防治措施提供科学依据。 方法 运用横断面研究设计,于2017年9月—2018年3月,在长沙市通过连续样本抽样及滚雪球抽样法招募大学生MSM,并进行匿名问卷调查。 结果 有效调查214人,共提名800名社交网络成员和430名性网络成员。多性伴MSM占47.6%。社交网络大小、社交网络密度的中位数和四分位数分别为6(3.75, 6)、0.1(0, 0.5)。性网络大小的中位数和四分位数为2(2,3),性网络密度为0。经多因素logistic回归分析发现,做过HIV检测(OR=2.688, 95%CI:1.336~5.407)、有偶然性伴 (OR=2.409, 95%CI=1.619~3.583)、社交网络大于5人(OR=2.163, 95%CI=1.093~4.280)、性网络与社交网络重合程度高者(OR=0.624, 95%CI=0.412~0.945),有2个或以上性伴的可能性大。 结论 大学生MSM多性伴行为普遍,且与部分社会网络特征相关,建议通过同伴进行社会网络干预,预防大学生MSM群体中HIV传播。     

引文归一化指标RCR与FWCI指标、F1000评分的相关性研究

【目的】 检验引文归一化指标RCR与Scopus的FWCI指标及同行评议指标F1000之间的相关性,为引文归一化学科影响力评价实践提供理论支撑。【方法】 选取国际干细胞研究领域的学术论文为研究样本,采用正态性检验及相关性分析法研究论文的RCR指标、FWCI指标及F1000推荐次数、F1000评分之间的相关关系。【结果】 RCR指标与FWCI指标具有较强的相关性,而RCR指标与F1000推荐次数和F1000评分之间仅低度相关。【结论】 作为学科归一化指标,RCR与FWCI指标在论文影响力评价上具有一致性,但与同行评议指标F1000相关性较弱。未来,RCR指标在我国交叉学科期刊评价、建立我国科技期刊影响力评价基准、构建我国科技期刊动态评价系统方面具有较大借鉴意义。     

Analysis of pharmacological mechanisms of Yinyanghuo as treatment of erectile dysfunction with network pharmacology-based strategy

Erectile dysfunction is considered an important health problem that impacts the quality of life of men. Yinyanghuo, also called Epimedium or Horny Goat Weed, is a frequently used Chinese traditional herbal medicine, commonly used in treating erectile dysfunction in China. A network pharmacology method was performed systematically, at a molecular level, to analyse the pharmacological mechanism of Yinyanghuo as erectile dysfunction therapy. The network pharmacology method used in this study primarily includes prescreening of the active compounds, prediction of targets, network analysis and gene enrichment analysis. This network analysis proved that 4 targets (AR, NR3C2, PDE5A and BMP2) could be the targets of Yinyanghuo therapy on erectile dysfunction. Besides, gene enrichment analysis predicted that Yinyanghuo might have a role in erectile dysfunction by regulating 10 molecular functions, 8 cellular components, 10 biological processes and 36 possible targets related to 10 signalling pathways. Our study demonstrated the molecular and pharmacological mechanisms of Yinyanghuo against erectile dysfunction with a holistic approach and demonstrated a powerful method for analysing pharmacological mechanisms and rational utilisation of Traditional Chinese Medicine clinically.     

Application of network pharmacology and molecular docking to elucidate the potential mechanism of Astragalus–Scorpion against prostate cancer

The present study aimed to investigate the molecular mechanism of the Astragalus–Scorpion drug pair in the treatment of prostate cancer (PCa). We employed network pharmacology and molecular docking technology to retrieving the active ingredients and corresponding targets of Astragalus–Scorpion by using TCMSP, BATMAN-TCM, TCMID and Swiss Target Prediction Databases. The targets related to PCa were retrieved through GeneCards. Cytoscape software was used to construct the ‘active ingredient–target disease’ network, and GO and KEGG enrichment analyses were performed on the common targets. Autodock software was used for molecular docking verification. In total, 26 active ingredients, 340 potential targets related to active ingredients and 122 common targets were screened from Astragalus–Scorpion drug pair. The core targets of the protein–protein interaction (PPI) network were JUN, AKT1, IL6, MAPK1 and RELA, whereas the core active ingredients were quercetin, kaempferol, formononetin, 7-o-methylisomucronulatol and calycosin. Nearly 762 GO entries and 154 pathways were obtained by using the pathway enrichment analysis. Molecular docking results revealed that quercetin and kaempferol bind to AKT1 and formononetin binds to RELA, all of which were found to be stable bounds.