国外动物智能军事应用情报研究

目的：阐述动物智能在军事学的应用及意义。方法：以学术论文、新闻、报纸、智库报告等作为信息源，综合研究国外动物智能军事应用实例及内在关联，描述动物智能在未来战场应用场景。结果：动物智能军事应用主要是动物特殊能力的军事应用和动物智能的仿生武器应用。结论：动物部队、仿生作战部队和动物战术是未来战争不可忽视的重要组成部分，动物智能的隐匿、灵活、多变等特点正逐渐被广泛应用于战场。     

基于文本挖掘和生物医学数据库的新型冠状病毒肺炎药物发现

目的 基于文本挖掘技术和生物医学数据库对新型冠状病毒肺炎（COVID-19）相关文献进行数据挖掘分析，探究COVID-19及其主要症状发热、咳嗽、呼吸障碍相关基因靶点，筛选潜在有效的化学药和中药。方法 使用GenCLiP 3网站获取COVID-19和其主要症状咳嗽、发热、呼吸障碍共4个关键词的共有靶点，在METASCAPE数据库中对其进行基因本体（GO）和通路富集分析，再利用String数据库和Cytoscape软件构建共有靶点的蛋白质相互作用网络，筛选获得核心基因，运用DGIdb数据库、SymMap数据库针对核心基因进行中西医治疗药物预测。结果 获得COVID-19及其主要症状共有基因靶点28个，其中有IL2、IL1B、CCL2等核心基因16个，使用DGIdb数据库筛选获得与16个关键靶点相互作用的化学药包括沙利度胺、来氟米特、环孢素等28种，中药包括虎杖、黄芪、芦荟等70味。结论 COVID-19及其主要症状的病理机制可能和CD4、KNG1、VEGFA等28个共有基因相关，可能通过介导TNF、IL-17等信号通路参与COVID-19病理过程。潜在有效药物可能通过作用相关靶点通路起到治疗COVID-19的作用。     

Utility of Differential White Cell Count and Cell Population Data for Ruling Out COVID-19 Infection in Patients With Community-Acquired Pneumonia

IntroductionThe main aim of this study was to assess the utility of differential white cell count and cell population data (CPD) for the detection of COVID-19 in patients admitted for community-acquired pneumonia (CAP) of different etiologies.MethodsThis was a multicenter, observational, prospective study of adults aged ≥18 years admitted to three teaching hospitals in Spain from November 2019 to November 2021 with a diagnosis of CAP. At baseline, a Sysmex XN-20 analyzer was used to obtain detailed information related to the activation status and functional activity of white cells.ResultsThe sample was split into derivation and validation cohorts of 1065 and 717 patients, respectively. In the derivation cohort, COVID-19 was confirmed in 791 patients and ruled out in 274 patients, with mean ages of 62.13 (14.37) and 65.42 (16.62) years, respectively (p < 0.001). There were significant differences in all CPD parameters except MO-Y. The multivariate prediction model showed that lower NE-X, NE-WY, LY-Z, LY-WY, MO-WX, MO-WY, and MO-Z values and neutrophil-to-lymphocyte ratio were related to COVID-19 etiology with an AUC of 0.819 (0.790, 0.846). No significant differences were found comparing this model to another including biomarkers (p = 0.18).ConclusionsAbnormalities in white blood cell morphology based on a few cell population data values as well as NLR were able to accurately identify COVID-19 etiology. Moreover, systemic inflammation biomarkers currently used were unable to improve the predictive ability. We conclude that new peripheral blood biomarkers can help determine the etiology of CAP fast and inexpensively.     

红外光谱数据融合对栽培滇重楼产地鉴别*

目的 多样的环境因素使得不同产地栽培滇重楼的化学成分也丰富多样，不同居群栽培滇重楼的甾体皂苷类成分具有很大的差异，多源数据融合分析能更全面的表征药材化学信息，建立一个高效而准确的产地鉴别模型，为其资源合理开发利用提供依据。方法 以来自云南和四川的8个产地（保山、楚雄、大理、红河、丽江、成都、文山、玉溪）共366份栽培滇重楼根茎为实验材料，采集其傅里叶变换近红外光谱（FT-NIR）和衰减全反射-傅里叶变换中红外光谱（ATR-FTMIR）数据。采用Kennard-Stone算法将不同产地的样品分为2/3的训练集和1/3的预测集，基于4种特征变量提取方法（CARS、VIP、SPA、SO-Covsel）结合2种数据融合策略（低级数据融合和中级数据融合），建立偏最小二乘产地判别分析模型。根据模型参数交叉验证均方根误差（RMSECV）和预测均方根误差（RMSEP）评估模型的稳定性，模型训练集和预测集准确率（ACC）评估模型分类性能。结果 近红外光谱和中红外光谱均能反应不同产地栽培滇重楼的化学成分差异，在中级数据融合中，基于VIP和SPA提取的特征变量建立的模型正确率均大于94%。相较于中级数据融合，低级数据融合模型得到了最为满意的结果，其预测集分类正确率达到100%。结论 根据近红外和中红外数据建立的低级数据融合PLS-DA模型，能够用于栽培滇重楼的产地鉴别分析。     

TIC en actividad física y parámetros cardiovasculares en mayores: una revisión

IntroductionAgeing is a period of physical and psychological changes. Inactivity is one of the biggest problems among the older adult population increasing the risk of sarcopenia and chronic diseases. Physical activity is an effective intervention to improve health outcomes. In recent years, there has been an increase in the use of technology, with health technology tools (ICT) appearing as an intervention to increase physical activity and improve associated health problems.ObjectiveIn this review, we evaluated the effectiveness of health technology to increase physical activity and to improve cardiovascular parameters in older adults.MethodologyStudies with a great variety of health technology tools to increase physical activity levels, and that evaluated the effect of that increase on cardiovascular parameters were included by searching the main databases.ResultsEleven studies reporting the use of a variety of ICT tools were included in this review. Despite these differences, the effectiveness of health technology tool interventions has been demonstrated in increasing physical activity and reducing cardiovascular parameters.DiscussionThe lack of adherence of older adults to health technology would be a disadvantage, but it has been shown that younger older adults are more familiar with health technology tools and the number using them is increasing.ConclusionHealth technology tools show effectiveness in increasing physical activity in older adults and improving cardiovascular parameters.     

基于真实世界数据探讨中医药治疗糖尿病肾病用药规律的研究＊

目的 基于临床信息系统分析总结真实世界的数据，采用数据挖掘的方法探讨中医药治疗糖尿病肾病的用药规律。方法 收集2018年1月-2020年12月上海中医药大学附属曙光医院宝山分院健康信息系统确诊的糖尿病肾病的门诊或住院患者的诊疗信息，建立Excel数据库，采用Excel 2010软件统计高频药物的四气、五味、归经及功效；使用SPSS Modeler 18.0软件中的Apriori算法分析关联规则，采用web节点建构药对关联网状图；运用SPSS 25统计软件进行因子分析。结果 本研究最终纳入477例接受中药饮片治疗的DKD患者，在1203条方剂信息中，涉及中药462种；使用频数排名前5位的中药分别是黄芪、黄精、石斛、山茱萸、麦冬；使用频数前5类的中药类别分别是补气药、补阴药、清热燥湿药、活血调经药、息风止痉药；在30味高频药物中，苦、甘、辛药味最为常见；药性寒、温数量接近；归脾经、肝经、肺经、肾经居多；关联规则提示，药物组合中置信度最高的组合为地龙-当归-僵蚕，因子分析共得到5个有效因子，累积贡献率为47.33%。结论 中医药治疗DKD在补益气血阴阳的同时，兼顾对瘀血、湿邪和痰饮的治疗，结合证型，可考虑使用黄芪、黄精、石斛、山茱萸、麦冬、金蝉花等药物的使用，清热燥湿药物如黄连、黄芩、黄柏可适当加入，为使邪有去处，大黄、车前子或可增添疗效。     

下一代诊断病理学

随着人类基因组测序、生物大数据信息分析、分子病理检测和人工智能辅助病理诊断等技术进步及其应用, 临床医学发展迈向精准诊疗时代。这一时代背景下, 传统诊断病理学迎来前所未有的历史机遇, 正在向"下一代诊断病理学(next-generation diagnostic pathology)"迈进。下一代诊断病理学以病理形态和临床信息为诊断基础, 以分子检测与生物信息分析、智慧制样与流程质控、智能诊断与远程会诊、病灶活体可视化与"无创"病理诊断等创新前沿交叉技术为主要特征, 以多组学和跨尺度整合诊断为病理报告内容, 实现对疾病的"最后诊断", 并预测疾病演进和结局、建议治疗方案和评估治疗反应, 形成新的疾病诊断"金标准"。未来, 需要激发病理学科创新活力, 加快下一代诊断病理学成熟和应用, 重塑病理学科理论和技术体系, 发挥诊断病理学在疾病"防、诊、治、养"等过程中的重要作用, 促进临床医学进一步发展, 服务健康中国战略。     

Effects of state reinsurance programs on health insurance exchange premiums and insurer participation

Objective

The aim of the study was to estimate the effect of the state-based reinsurance programs through the section 1332 State Innovation Waivers on health insurance marketplace premiums and insurer participation.

Data Source

2015 to 2022 Robert Wood Johnson Foundation Health Insurance Exchange Compare Datasets.

Study Design

An event study difference-in-differences (DD) model separately for each year of implementation and a synthetic control method (SCM) are used to estimate year-by-year effects following program implementation.

Data Collection/Extraction Methods

Not applicable.

Principal Findings

Reinsurance programs were associated with a decline in premiums in the first year of implementation by 10%–13%, 5%–19%, and 11%–17% for bronze, silver, and gold plans (p < 0.05). There is a trend of sustained declines especially for states that implemented their programs in 2019 and 2020. The SCM analyses suggest some effect heterogeneity across states but also premium declines across most states. There is no evidence that reinsurance programs affected insurer participation.

Conclusion

State-based reinsurance programs have the potential to improve the affordability of health insurance coverage. However, reinsurance programs do not appear to have had an effect on insurer participation, highlighting the need for policy makers to consider complementary strategies to encourage insurer participation.