Dietary Habit Is Associated with Depression and Intelligence: An Observational and Genome-Wide Environmental Interaction Analysis in the UK Biobank Cohort

Dietary habits have considerable impact on brain development and mental health. Despite long-standing interest in the association of dietary habits with mental health, few population-based studies of dietary habits have assessed depression and fluid intelligence. Our aim is to investigate the association of dietary habits with depression and fluid intelligence. In total, 814 independent loci were utilized to calculate the individual polygenic risk score (PRS) for 143 dietary habit-related traits. The individual genotype data were obtained from the UK Biobank cohort. Regression analyses were then conducted to evaluate the association of dietary habits with depression and fluid intelligence, respectively. PLINK 2.0 was utilized to detect the single nucleotide polymorphism (SNP) × dietary habit interaction effect on the risks of depression and fluid intelligence. We detected 22 common dietary habit-related traits shared by depression and fluid intelligence, such as red wine glasses per month, and overall alcohol intake. For interaction analysis, we detected that OLFM1 interacted with champagne/white wine in depression, while SYNPO2 interacted with coffee type in fluid intelligence. Our study results provide novel useful information for understanding how eating habits affect the fluid intelligence and depression.     

新生儿个体化发育支持对极低出生体重儿智力和全身运动发育的影响

目的 分析探讨新生儿个体化发育支持对极低出生体重儿智力和全身运动发育的应用效果和作用。 方法 选取2018年12月1日—2019年7月1日期间在湖南省妇幼保健院出生且符合入选标准的极低出生体重儿90例为研究对象,并随机将其分为对照组(n=37)和观察组(即个体化发育支持组,n=53)。收集所有患儿的基本资料,比较两组体质量恢复时间、完全经口喂养时间及胎粪排尽时间,以及两组患儿的全身运动(general movements,GMs)、患儿智力(mental development index,MDI)、心理运动指数(psychomotor development index,PDI)及发育商(development quotient,DQ)情况,评估两组全身运动及智力发育情况。 结果 观察组的体质量恢复时间为(7.86±2.66)d、完全经口喂养时间为(11.77±3.52)d,胎粪排尽时间为(12.19±4.22)d,时间均短于对照组(均P<0.05);观察组体格变化速度情况高于对照组(P<0.05);随访至矫正胎龄12个月后,观察组全身运动情况、智力发育、心理运动发育指数以及发育商评分均优于对照组(均P<0.001)。 结论 新生儿个体化发育支持可以促进极低出生体重儿智力及全身运动的发育,减少异常GMs发生率,可推广应用。     

人工智能辅助学术同行评议的应用及分类

【目的】 分析人工智能(Artificial Intelligence, AI)作为辅助工具在学术同行评议中的创新应用,提出未来发展建议。【方法】 首先通过文献调研法和案例分析法,比较国内外AI辅助学术同行评议的应用实践;其次按功能对其进行分类,并阐述其主要支撑算法;最后展望AI在学术同行评议领域的未来发展方向。【结果】 国内方面,AI推荐审稿人功能被应用于基金评审,但AI学术影响力预测功能尚停留在研发阶段;国外方面,除学术不端检测功能外,其他功能的应用均处于起步阶段。按功能不同,AI辅助同行评议可分为投稿审查、审稿人推荐和学术影响力预测3类。其未来发展方向为:评议流程和文本结构的标准化、智能算法的通用化、评议专家库和已发表学术论文数据库的集成化;最终AI将发挥评议主体功能。【结论】 科研机构与学术期刊应积极参与全文文献数据库与全球审稿人数据库等相关数字基础设施建设,加快AI在学术同行评议中的应用,进一步推进该领域的数字化和智能化。     

缺铁性贫血婴幼儿智能行为发育研究

目的 探讨缺铁性贫血对婴幼儿智能行为发育的影响。方法 对264名儿童进行0－36个月的生长发育纵向监测,定期对其智力发育指数（MDI）、精神运动发育指数（PDI）以及行为进行测试,根据2岁时有无缺铁性贫血分为两组：①贫血组（96名）,②非贫血组（168名）,建立数据库,用SPSS软件进行统计学分析。结果 2岁时贫血组MDI、PDI均低于对照组,且这种改变在2．5岁贫血完全被纠正时仍未安全消除;2岁缺铁性贫血患儿血红蛋白水平与其MDI和PDI分值呈正相关;缺铁性贫血组儿童2－3岁期间行为问题发生率明显高于对照组,突出表现在社交退缩和躯体诉述两个行为因子上。结论 缺铁性贫血对婴幼儿智能行为发育均产生重要影响,鉴于对智能发育的不利影响是长期的,积极防治婴幼儿期缺铁性贫血对于保证儿童正常生长发育具有重要意义。     

儿童注意缺陷多动障碍个性及智力特征探讨

目的 :了解注意缺陷多动障碍 (ADHD)儿童的个性及智力特点。方法 :采用艾森克个性问卷 (EPQ)和韦氏儿童智力量表 (WISC R)对 40例ADHD患儿进行测试。结果 :ADHD组EPQ测验中神经质和精神质量表T分高于正常对照组 ,掩饰性量表T分低于正常对照组。WISC R测验中 ,ADHD组总智商 (FIQ)在正常范围 ,但与正常对照组比较有显著性差异(P <0 .0 5 )。在言语智商 (VIQ)与操作智商 (PIQ)平衡上 ,ADHD组的算术、理解、译码分测验量表分较正常组低 ,两组比较有显著性差异。结论 :ADHD儿童情绪稳定性差 ,心理成熟能力延迟 ,同时可能存在言语理解、记忆 /不分心因子缺陷     

The use of artificial intelligence and robotics in regional anaesthesia

The current fourth industrial revolution is a distinct technological era characterised by the blurring of physics, computing and biology. The driver of change is data, powered by artificial intelligence. The UK National Health Service Topol Report embraced this digital revolution and emphasised the importance of artificial intelligence to the health service. Application of artificial intelligence within regional anaesthesia, however, remains limited. An example of the use of a convoluted neural network applied to visual detection of nerves on ultrasound images is described. New technologies that may impact on regional anaesthesia include robotics and artificial sensing. Robotics in anaesthesia falls into three categories. The first, used commonly, is pharmaceutical, typified by target-controlled anaesthesia using electroencephalography within a feedback loop. Other types include mechanical robots that provide precision and dexterity better than humans, and cognitive robots that act as decision support systems. It is likely that the latter technology will expand considerably over the next decades and provide an autopilot for anaesthesia. Technical robotics will focus on the development of accurate sensors for training that incorporate visual and motion metrics. These will be incorporated into augmented reality and visual reality environments that will provide training at home or the office on life-like simulators. Real-time feedback will be offered that stimulates and rewards performance. In discussing the scope, applications, limitations and barriers to adoption of these technologies, we aimed to stimulate discussion towards a framework for the optimal application of current and emerging technologies in regional anaesthesia.     

数据挖掘在名老中医经验传承的应用现状与智能化趋势

现在,数据挖掘技术正朝着智能化的趋势快速发展,人工智能（AI）在西医学的广泛应用,尤其是AI分析方法在疾病早期诊断与评估、疾病的治疗策略与医疗资源管理这几个方面突出的使用效果,为AI与中医药的结合提供了有价值的参考,尤其在名老中医经验的学习与传承方面。近十余年来,名老中医经验学习与传承领域数据挖掘技术的研究成果颇多,在梳理常用数据挖掘工具与分析方法的基础上,结合AI分析方法在西医学的应用,可以对中医药领域数据挖掘的智能化学习发展方向进行预测与展望,为继承与发展名老中医经验提供更高效的途径,加快中医现代化研究。     

人工智能在军事医学中的应用现状及展望

介绍了人工智能(artificial intelligence,AI)在伤员搜救和管理、伤员救治、军事医学培训、医疗数据管理等军事医学领域中的应用现状,分析了AI在军事医学应用中存在的问题,指出了向强AI系统迈进、突出环境自适应性,紧跟AI技术发展、系统高度综合集成,大力发展数据库技术、确保产品应用价值是未来AI在军事医学中的发展方向。