刘晓鹰教授“扶中”外治法治疗儿科疾病临床经验浅析

小儿"脾常不足",脾胃之体成而未全,脾胃之气全而未壮,脾胃不足在儿科疾病发生发展、病机转归中占有相当重要的地位。刘晓鹰教授在继承全国名老中医倪珠英学术思想基础上,提出"扶中"外治法,立法取穴方面强调时时顾护小儿中焦脾胃,采用小儿推拿、扶阳罐(含温推、温灸和温刮痧)、针刺(含腹针、揿针)等外治手段治疗儿科脾、肺、肾等系列疾病,取得满意疗效。     

Risk factors related to the severity of COVID-19 in Wuhan

Objective: To evaluate the characteristics at admission of patients with moderate COVID-19 in Wuhan and to explore risk factors associated with the severe prognosis of the disease for prognostic prediction.Methods: In this retrospective study, moderate and severe disease was defined according to the report of the WHO-China Joint Mission on COVID-19. Clinical characteristics and laboratory findings of 172 patients with laboratory-confirmed moderate COVID-19 were collected when they were admitted to the Cancer Center of Wuhan Union Hospital between February 13, 2020 and February 25, 2020. This cohort was followed to March 14, 2020. The outcomes, being discharged as mild cases or developing into severe cases, were categorized into two groups. The data were compared and analyzed with univariate logistic regression to identify the features that differed significantly between the two groups. Based on machine learning algorithms, a further feature selection procedure was performed to identify the features that can contribute the most to the prediction of disease severity.Results: Of the 172 patients, 112 were discharged as mild cases, and 60 developed into severe cases. Four clinical characteristics and 18 laboratory findings showed significant differences between the two groups in the statistical test (P<0.01) and univariate logistic regression analysis (P<0.01). In the further feature selection procedure, six features were chosen to obtain the best performance in discriminating the two groups with a linear kernel support vector machine. The mean accuracy was 91.38%, with a sensitivity of 0.90 and a specificity of 0.94. The six features included interleukin-6, high-sensitivity cardiac troponin I, procalcitonin, high-sensitivity C-reactive protein, chest distress and calcium level.Conclusions: With the data collected at admission, the combination of one clinical characteristic and five laboratory findings contributed the most to the discrimination between the two groups with a linear kernel support vector machine classifier. These factors may be risk factors that can be used to perform a prognostic prediction regarding the severity of the disease for patients with moderate COVID-19 in the early stage of the disease.     

冠心病心绞痛患者健康教育和心理护理效果

目的探讨对冠心病心绞痛患者给予健康教育联合心理护理干预后对其生活质量等方面产生的影响。方法选择我院2017年4月-2019年2月收治的100例冠心病心绞痛患者作为实验对象;抽签法分组后探究每组患者护理方式;对照组(50例):选择基础护理方式展开疾病护理;试验组(50例):选择基础护理+健康教育+心理护理方式展开疾病护理;对比各组患者表现出的护理工作满意度以及生活质量评定差异。结果试验组冠心病心绞痛患者护理工作总满意度(98.00%)高于对照组(82.00%)明显(P<0.05);试验组冠心病心绞痛患者睡眠情感、社会生活、精力以及躯体活动评分均高于对照组(P<0.05)。结论冠心病心绞痛患者在接受临床护理工作期间,对于护理工作满意度的提升,各项生活质量指标(睡眠情感、社会生活、精力以及躯体活动)评分结果的提升,均获得明显作用效果,最终对于冠心病心绞痛患者生活质量以及康复状态的显著提升,奠定基础。     

The effect of sleep impairment on gestational diabetes mellitus: a systematic review and meta-analysis of cohort studies

ObjectiveThis systematic review and meta-analysis evaluated the influence of sleep duration or impairment (poor sleep quality, snoring, and obstructive sleep apnea [OSA]) on gestational diabetes mellitus (GDM) risk.MethodsPubMed, Embase, EBSCO, and WOS databases were searched up to March 4th, 2019. Cohort studies were included and relative risk (RR) with 95% confidence interval (CI) were used as the measure of effects. Heterogeneity was assessed by the Chi-squared and I² tests. Subgroup analyses, sensitivity analysis, and dose-response analysis were performed. The overall quality of the evidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach.ResultsA total of 16 studies with 2,551,017 pregnant women and 142,103 GDM cases were included in this study. Both short and long sleep duration were associated with increased risk of GDM. There was a U-shaped relationship between sleep duration and GDM risk (P_{-nonlinearity} < 0.001), and pregnant women with 8 h of sleep presented lower GDM risk. Poor sleep quality, snoring and OSA also increased the subsequent risk of GDM.ConclusionsPregnant women should be made aware of the benefits of proper sleep, and those with poor sleep quality, snoring, and OSA should be screened for GDM.     

A Broad Learning System with Ensemble and Classification Methods for Multi-step-ahead Wind Speed Prediction

Cognitive Computation - Short-term wind speed prediction plays a significant role in the management of large-scale wind power plants. However, wind speed prediction is extremely complex and...     

Semi-supervised mp-MRI data synthesis with StitchLayer and auxiliary distance maximization

The availability of a large amount of annotated data is critical for many medical image analysis applications, in particular for those relying on deep learning methods which are known to be data-hungry. However, annotated medical data, especially multimodal data, is often scarce and costly to obtain. In this paper, we address the problem of synthesizing multi-parameter magnetic resonance imaging data (i.e. mp-MRI), which typically consists of Apparent Diffusion Coefficient (ADC) and T2-weighted (T2w) images, containing clinically significant (CS) prostate cancer (PCa) via semi-supervised learning and adversarial learning. Specifically, our synthesizer generates mp-MRI data in a sequential manner: first utilizing a decoder to generate an ADC map from a 128-d latent vector, followed by translating the ADC to the T2w image via U-Net. The synthesizer is trained in a semi-supervised manner. In the supervised training process, a limited amount of paired ADC-T2w images and the corresponding ADC encodings are provided and the synthesizer learns the paired relationship by explicitly minimizing the reconstruction losses between synthetic and real images. To avoid overfitting limited ADC encodings, an unlimited amount of random latent vectors and unpaired ADC-T2w Images are utilized in the unsupervised training process for learning the marginal image distributions of real images. To improve the robustness for training the synthesizer, we decompose the difficult task of generating full-size images into several simpler tasks which generate sub-images only. A StitchLayer is then employed to seamlessly fuse sub-images together in an interlaced manner into a full-size image. In addition, to enforce the synthetic images to indeed contain distinguishable CS PCa lesions, we propose to also maximize an auxiliary distance of Jensen-Shannon divergence (JSD) between CS and nonCS images. Experimental results show that our method can effectively synthesize a large variety of mp-MRI images which contain meaningful CS PCa lesions, display a good visual quality and have the correct paired relationship between the two modalities of a pair. Compared to the state-of-the-art methods based on adversarial learning (Liu and Tuzel, 2016; Costa et al., 2017), our method achieves a significant improvement in terms of both visual quality and several popular quantitative evaluation metrics.     

气象因素对钉螺密度变化的影响分析

目的 研究自然条件下气象因素对钉螺密度变化的影响,为控制血吸虫病及其钉螺扩散提供科学依据。方法 收集1990－2014年湖北省潜江市春季查螺资料及地面气象观测数据,采用一阶自回归分析方法对实际钉螺密度进行趋势拟合与分解,利用相关分析法对钉螺密度变化率与不同时段、不同气象要素进行相关性分析。结果 对钉螺密度影响最大的气象因子是温度,其次为降水;其中1月平均最低气温和冬季平均最低气温分别是钉螺密度变化率、活螺框变化率影响最大的温度因子;1月平均最低温度升高(或降低)1 ℃,将会导致钉螺密度上升(或下降) 5.080%～6.710%;冬季平均最低温度升高(或降低)1 ℃,活螺框变化率上升(或下降)15.521%～15.928%。降水对钉螺密度影响最大的时段是上年11月至当年4月,该时段内降水偏少20%以上,有利于降低钉螺密度。9－11月日照与钉螺密度变化率、活螺框变化率存在一定相关性。在相关分析基础上分别建立了钉螺密度变化率、活螺框变化率与气象因子的统计回归模型。结论 在12月到来之前清除有螺区杂草有利于降低地表温度和土壤水分含量,能取得一定的灭螺效果。伴随全球气候变化湖北省冬季温度升高趋势明显,可能引发钉螺密度升高。     

Sex estimation of the tibia in modern Turkish: A computed tomography study

The utilization of computed tomography is beneficial for the analysis of skeletal remains and it has important advantages for anthropometric studies. The present study investigated morphometry of left tibia using CT images of a contemporary Turkish population. Seven parameters were measured on 203 individuals (124 males and 79 females) within the 19–92-years age group. The first objective of this study was to provide population-specific sex estimation equations for the contemporary Turkish population based on CT images. A second objective was to test the sex estimation formulae on Southern Europeans by Kranioti and Apostol (2015). Univariate discriminant functions resulted in classification accuracy that ranged from 66 to 86%. The best single variable was found to be upper epiphyseal breadth (86%) followed by lower epiphyseal breadth (85%). Multivariate discriminant functions resulted in classification accuracy for cross-validated data ranged from 79 to 86%. Applying the multivariate sex estimation formulae on Southern Europeans (SE) by Kranioti and Apostol in our sample resulted in very high classification accuracy ranging from 81 to 88%. In addition, 35.5–47% of the total Turkish sample is correctly classified with over 95% posterior probability, which is actually higher than the one reported for the original sample (25–43%). We conclude that the tibia is a very useful bone for sex estimation in the contemporary Turkish population. Moreover, our test results support the hypothesis that the SE formulae are sufficient for the contemporary Turkish population and they can be used safely for criminal investigations when posterior probabilities are over 95%.     

环境条件对蕲艾叶品质影响的研究＊

目的 研究环境条件对蕲艾叶有效物质含量以及出绒率的影响。方法 采用国家行业标准分别测定土壤水分、pH值及有机质的含量；采用紫外-可见分光光度法测定蕲艾叶总黄酮含量；参照中国药典（2015年版）方法测定蕲艾叶挥发油和鞣质含量；采用HPLC法比较样品70%甲醇提取液的峰谱特征；采用自拟的经过方法学验证的方法检测蕲艾叶出绒率。结果 蕲艾叶品质与土壤水分、pH、日照长短及施化肥与否有关。施用化肥（含N、P、K）后所产蕲艾叶的挥发油平均含量比未施化肥的高17.6%，而总黄酮和鞣质的平均含量分别降低28.5%、30.5%，且施用化肥者5种有机酸的总含量显著降低；日照时数较短的蕲艾叶的挥发油的平均含量比日照时数长的高12.6%，但总黄酮和鞣质的平均含量分别降低23.5%、19.1%，5种有机酸的含量也显著降低，且出绒率整体较低；土壤水分较少的蕲艾叶的挥发油的平均含量比土壤水分充足的高5.5%，但总黄酮和鞣质的平均含量分别降低21.4%、34.6%，5种有机酸的含量也显著降低。蕲艾叶总黄酮和鞣质的含量在土壤酸性范围内随pH的升高而升高。结论 蕲艾的栽培应选择日照充分、土壤偏酸性且水分较充足的环境，避免施用化学肥料。