Machine Learning Model for Classifying the Results of Fetal Cardiotocography Conducted in High-Risk Pregnancies

PurposeFetal well-being is usually assessed via fetal heart rate (FHR) monitoring during the antepartum period. However, the interpretation of FHR is a complex and subjective process with low reliability. This study developed a machine learning model that can classify fetal cardiotocography results as normal or abnormal.Materials and MethodsIn total, 17492 fetal cardiotocography results were obtained from Ajou University Hospital and 100 fetal cardiotocography results from Czech Technical University and University Hospital in Brno. Board-certified physicians then reviewed the fetal cardiotocography results and labeled 1456 of them as gold-standard; these results were used to train and validate the model. The remaining results were used to validate the clinical effectiveness of the model with the actual outcome.ResultsIn a test dataset, our model achieved an area under the receiver operating characteristic curve (AUROC) of 0.89 and area under the precision-recall curve (AUPRC) of 0.73 in an internal validation dataset. An average AUROC of 0.73 and average AUPRC of 0.40 were achieved in the external validation dataset. Fetus abnormality score, as calculated from the continuous fetal cardiotocography results, was significantly associated with actual clinical outcomes [intrauterine growth restriction: odds ratio, 3.626 (p=0.031); Apgar score 1 min: odds ratio, 9.523 (p<0.001), Apgar score 5 min: odds ratio, 11.49 (p=0.001), and fetal distress: odds ratio, 23.09 (p<0.001)].ConclusionThe machine learning model developed in this study showed precision in classifying FHR signals. This suggests that the model can be applied to medical devices as a screening tool for monitoring fetal status.     

Ferroptosis‐based molecular prognostic model for adrenocortical carcinoma based on least absolute shrinkage and selection operator regression

BackgroundThis study aimed to find ferroptosis‐related genes linked to clinical outcomes of adrenocortical carcinoma (ACC) and assess the prognostic value of the model.MethodsWe downloaded the mRNA sequencing data and patient clinical data of 78 ACC patients from the TCGA data portal. Candidate ferroptosis‐related genes were screened by univariate regression analysis, machine‐learning least absolute shrinkage, and selection operator (LASSO). A ferroptosis‐related gene‐based prognostic model was constructed. The effectiveness of the prediction model was accessed by KM and ROC analysis. External validation was done using the {"type":"entrez-geo","attrs":{"text":"GSE19750","term_id":"19750"}}GSE19750 cohort. A nomogram was generated. The prognostic accuracy was measured and compared with conventional staging systems (TNM stage). Functional analysis was conducted to identify biological characterization of survival‐associated ferroptosis‐related genes.ResultsSeventy genes were identified as survival‐associated ferroptosis‐related genes. The prognostic model was constructed with 17 ferroptosis‐related genes including STMN1, RRM2, HELLS, FANCD2, AURKA, GABARAPL2, SLC7A11, KRAS, ACSL4, MAPK3, HMGB1, CXCL2, ATG7, DDIT4, NOX1, PLIN4, and STEAP3. A RiskScore was calculated for each patient. KM curve indicated good prognostic performance. The AUC of the ROC curve for predicting 1‐, 3‐, and 5‐ year(s) survival time was 0.975, 0.913, and 0.915 respectively. The nomogram prognostic evaluation model showed better predictive ability than conventional staging systems.ConclusionWe constructed a prognosis model of ACC based on ferroptosis‐related genes with better predictive value than the conventional staging system. These efforts provided candidate targets for revealing the molecular basis of ACC, as well as novel targets for drug development.     

停课不停学背景下对机能学实验虚拟实验平台建设的思考

北京中医药大学积极响应教育部"停课不停学"的要求,借助机能学实验虚拟实验平台切实保障机能学实验教学工作的顺利开展。此文通过对"停课不停学"背景下的机能学实验课程以及机能学实验虚拟实验平台进行系统思考,并且结合问卷调查、教师走访、纵向比较等方法,分析"停课不停学"背景下机能学实验虚拟实验平台的使用效果和不足之处,旨在为虚拟实验"金"平台的建设提供参考和思路。     

非酒精性脂肪性肝病及动脉粥样硬化的基因串扰综合分析

目的]使用生物信息学的方法寻找非酒精性脂肪性肝病(NAFLD)和动脉粥样硬化(As)的共同转录特征,通过两种疾病的基因串扰分析,挖掘NAFLD相关As新的潜在机制和关键靶点,并进一步在动物组织和人血清样本中验证关键靶点的表达水平。 [方法]GEO数据库下载NAFLD(数据集GSE89632)和As(数据集GSE43292)的基因表达谱,进行差异基因分析和加权基因共表达网络分析,筛选两种疾病的共享基因。通过String数据库、蛋白质互作分析和R软件等工具对共享基因进行富集分析。利用Cytoscape软件计算、外部数据集(GSE100927)验证及机器学习方法(LASSO回归)筛选出核心基因。最后,通过构建高脂饮食非酒精脂肪肝和As小鼠模型以及收集NAFLD合并冠心病患者的外周血清,验证重要的核心基因。 [结果]识别出两种疾病的75个共享基因,发现共享基因的主要富集通路,包括细胞因子-细胞因子受体相互作用、IL-17信号通路、脂质和As、NF-κB信号通路等。综合多种生物信息学方法,最终筛选出2个重要的核心基因(MMP-9和CCL3)。动物实验验证结果表明,高脂饮食组小鼠肝脏和主动脉窦组织的MMP-9和CCL3含量都明显升高,高脂饮食组小鼠肝脏组织的MMP-9和CCL3含量分别为对照组的2.43倍(P＜0.001)和1.35倍(P＜0.01),高脂饮食组小鼠主动脉窦组织的MMP-9和CCL3含量分别为对照组的2.10倍(P＜0.001)和1.58倍(P＜0.01)。人血清样本验证结果表明,NAFLD合并冠心病患者血清中的MMP-9和CCL3含量分别为单纯冠心病患者的1.21倍(P＜0.01)和1.29倍(P＜0.01)。 [结论]本研究基于生物信息学分析发现MMP-9和CCL3可能是NAFLD相关As中发挥关键作用的核心基因,为研究NAFLD相关As提供一定的靶点参考。     

外源性N-甲基-D-天冬氨酸对成年大鼠被动回避学习记忆的影响

目的 探讨脑内植入外源性N-甲基-D-天冬氨酸(NMDA)对成年大鼠被动回避学习记忆的影响. 方法 在大鼠脑内植入不同浓度的NMDA缓释膜片后,比较各组大鼠被动同避学习记忆(避暗实验)的能力以及额前腹内侧皮质(vMPFC)及扣带同前皮质(ACC)区域NMDA受体活性的区别. 结果 避暗实验中各组大鼠潜伏期和错误次数间差异无统计学意义(P=0.846,P=0.792).各组大鼠vMPFC及ACC区域的NMDA受体活性之间差异无统计学意义(P=0.546),但随着所植入的缓释膜片中NMDA浓度增加.这些区域NMDA受体活性有降低的趋势. 结论 外源性植入NMDA对成年大鼠被动回避学习记忆无明显影响,但本实验为进一步研究NMDA改变受损脑组织的神经可塑性奠定了一定的基础.     

The New Associationism: A Neural Explanation for the Predictive Powers of Cerebral Cortex

The ability to predict is the most importantability of the brain. Somehow, the cortex isable to extract regularities from theenvironment and use those regularities as abasis for prediction. This is a most remarkableskill, considering that behaviourallysignificant environmental regularities are noteasy to discern: they operate not only betweenpairs of simple environmental conditions, astraditional associationism has assumed, butamong complex functions of conditions that areorders of complexity removed from raw sensoryinputs. We propose that the brain's basicmechanism for discovering such complexregularities is implemented in the dendritictrees of individual pyramidal cells in thecerebral cortex. Pyramidal cells have 5–8principal dendrites, each of which is capableof learning nonlinear input-to-outputtransfer functions. We propose that eachdendrite is trained, in learning its transferfunction, by all the other principal dendritesof the same cell. These dendrites teach eachother to respond to their separate inputs withmatching outputs. Exposed to differentbut related information about the sensoryenvironment, principal dendrites of the samecell tune to functions over environmentalconditions that, while different, arecorrelated. As a result, the cell as awhole tunes to the source of the regularitiesdiscovered by the cooperating dendrites,creating a new representation. When organizedinto feed-forward/feedback layers, pyramidalcells can build their discoveries on thediscoveries of other cells, graduallyuncovering nature's hidden order. Theresulting associative network is powerfulenough to meet a troubling traditionalobjection to associationism: that it is toosimple an architecture to implement rationalprocesses.     

BrainAGE and regional volumetric analysis of a Buddhist monk: a longitudinal MRI case study

ABSTRACT

Yongey Mingyur Rinpoche (YMR) is a Tibetan Buddhist monk, and renowned meditation practitioner and teacher who has spent an extraordinary number of hours of his life meditating. The brain-aging profile of this expert meditator in comparison to a control population was examined using a machine learning framework, which estimates “brain-age” from brain imaging. YMR’s brain-aging rate appeared slower than that of controls suggesting early maturation and delayed aging. At 41 years, his brain resembled that of a 33-year-old. Specific regional changes did not differentiate YMR from controls, suggesting that the brain-aging differences may arise from coordinated changes spread throughout the gray matter.     

模式动物线虫的学习与学习抉择行为

线虫因为其简单的体系和对于诸如接触、味道、气味和温度等外界刺激的敏感反映能力,日益成为受人瞩目的研究行为可塑性的模式动物。目前认为,线虫中的学习包括非联想与联想学习两大类,且存在至少6种形式化学趋向性介导的联想学习。同时,三种研究体系已经被开发出来用于学习抉择的研究。本文讨论了线虫中学习与学习抉择的形式、研究模型及其遗传与分子调控机制。     

PBL教学法在儿内科教学中的实践与探索

目的 探索新的高等医学教育的教学方式，以适应医学科学的发展及医学模式的转变。方法 在临床医学院三个大班共182名本科生的《儿内科学》教学中，开展以问题为基础的学习(PBL)教学法尝试，每班分成三个小组，在三位教师辅导下，“以问题为基础”对病例进行讨论学习，要求学生课前阅读教科书和有关参考文献。结果 PBL教学法使学生掌握有关该疾病的更多知识，并在期终考试的成绩及不定期的临床测验中得到证实。结论 PBL教学法有利于调动学生的学习积极性、主动性，有利于培养学生的自学能力和创新精神，在教与学两方面促进了教学质量的提高，受到学生和教师的普遍认可，值得进一步实践和推广。     

两种电子教材开发方式的对比研究

介绍了移动学习领域以iBook Author为依托和基于Web的两种电子教材开发方式,并将两种开发方式进行对比、总结出各自的优缺点,为今后的电子教材开发人员提供参考。