穴位按摩腹带联合中药贴敷的应用对维持性血透病人便秘疗效的观察

目的 探讨利用穴位按摩腹带进行穴位按摩联合中药贴敷对维持性血透便秘病人的效果。方法 将60例长期维持性血液透析的便秘病人按透析日期的单双号分成两组,观察组用穴位按摩腹带联合中药贴敷,对照组服用大黄粉,两组其余治疗方法相同。观察两组便秘治疗的有效率和首次排便时间并进行比较。结果 观察组总有效率93.33%,对照组总有效率66.67%;观察组首次排便时间（4.83±2.67）h,对照组首次排便时间（8.15±5.67）h,两组比较差异有统计学意义（P〈0.05）。结论 穴位按摩腹带的应用联合中药贴敷可以使维持性血液透析病人保持大便通畅,减少因便秘引起的不适,提高生活质量,且使用简单方便,患者能自行操作。     

基于全生命周期理念的中药新药监管科学研究

中药是我国具有原创性优势的健康资源,近年来,国家高度重视中医药的价值,强调"传承精华,守正创新"以推动中医药行业的健康发展。但目前中药仍面临创新能力不足、中药新药发展缓慢的问题,严重制约中药产业的发展。中药新药研发具有政策导向性,全生命周期管理理念的运用和监管科学的兴起,将会促进中药监管体系与治理能力的发展,为中药研发提供政策指导。对中药全生命周期各阶段的特殊性及监管情况进行分析,探索中药监管科学建设思路,以期为改善中药新药监管效果提供参考。     

通阳中药葱白提取物抑制低压低氧诱导促凝血反应的机制研究

目的研究通阳中药葱白提取物(AYMOE)对低压低氧诱导的血小板激活和促凝状态的影响。方法将42只成年雄性SD大鼠随机分为对照组(暴露于常压常氧环境)、低压低氧组(Hyp组,暴露于低压低氧环境)、Hyp+AYMOE-100组(暴露于低压低氧环境并口服AYMOE 100 mg/kg)、Hyp+AYMOE-200组(暴露于低压低氧环境并口服AYMOE 200 mg/kg)、Hyp+AYMOE-300组(暴露于低压低氧环境并口服AYMOE 300 mg/kg)、Hyp+anti-CD42c组(暴露于低压低氧环境并尾静脉注射antiCD42c 5 mg/kg)、Hyp+AYMOE-200+rh Lyn组[暴露于低压低氧环境并口服AYMOE 200 mg/kg联合尾静脉注射重组人酪氨酸蛋白激酶Lyn(rh Lyn) 4.8 mg/kg],每组6只。低压低氧暴露7 d后,ELISA检测各组大鼠血清血栓素A2(TXA2)以及血小板激活因子(PAF)含量,检测大鼠血小板的凝集率,HE染色观察大鼠肺组织病理变化,Western blot检测GPIb-Ⅸ-Ⅴ、Lyn、磷酸化的Lyn(p-Lyn)的表达。结果与对照组比较,暴露于低压低氧的各组大鼠血清TXA2、PAF水平及血小板凝集率升高,GPIb-Ⅸ-Ⅴ、Lyn、p-Lyn蛋白表达上调(P <0.05)。与Hyp组相比,Hyp+AYMOE-100组、Hyp+AYMOE-200组、Hyp+AYMOE-300组的血小板凝集率、血清TXA2、PAF的水平降低,差异均有统计学意义(P <0.05),其中以Hyp+AYMOE-200组抑制效果最明显(P <0.05)。与对照组比较,Hyp组大鼠因低氧而发生血管堵塞,肺静脉血管腔空间狭小;与Hyp组相比,Hyp+AYMOE-200组大鼠肺静脉血管栓塞明显缓解。与Hyp组相比,Hyp+anti-CD42c组和Hyp+AYMOE-200组GPIb-Ⅸ-Ⅴ、Lyn、p-Lyn蛋白表达下调,差异均有统计学意义(P <0.05)。与Hyp+AYMOE-200组比较,Hyp+AYMOE-200+rh Lyn组血小板凝集率、血清TXA2和PAF水平均较高,Lyn和p-Lyn蛋白表达均增加,差异均有统计学意义(P <0.05)。结论 AYMOE可通过抑制GPIb-Ⅸ-Ⅴ和Lyn减少低压低氧诱导的血小板激活并改善促凝状态。     

Qingre Quyu Granule(清热祛瘀颗粒)Stabilizes Plaques through Inhibiting the Expression of Tenascin-C in Patients with Severe Carotid Stenosis

Objective:To investigate the therapeutic effects of Qingre Quyu Granule(清热祛瘀颗粒,QQG)on the patients with severe carotid stenosis,and to explore the mechanism of it.Methods:Ninety-six patients with severe carotid stenosis were enrolled in the study and were classified into a QQG group(n=48) and a control group(n=48) randomly using consecutively numbered envelopes.The patients in the QQG group were given QQG and Western medicine,those in the control group were given Western medicine merely,the course of treatment was 16 weeks.All patients went through endarterectomy after treatment.Plaques were subjected to the analysis of CD3,CD68,soluble intercellular adhesion molecule 1(ICAM-1),matrix metalloprotease-9(MMP-9),CD40 L,tenascin-C,and collagen content lipid content by immunohistochemistry or polarized light analysis.Results:By the end of experiment,the expressions of CD3,CD68,ICAM-1,MMP9,CD40 L and tenascin-C on the plaques were statistically significant lower in the QQG group compared with the control group(P0.01).The lipid content of the plaque was also significantly lower in the QQG group compared with the control group(P0.01).The interstitial collagen in the tissue sections of the plaques was also significantly higher in the QQG group in comparison with the control group(P0.01).Conclusion:QQG could stabilize carotid artery plaques through inhibiting pro-inflammation factors and restraining the tenascin-C and MMP9 pathway.     

Deep learning for intelligent diagnosis in thyroid scintigraphy

ObjectiveTo construct deep learning (DL) models to improve the accuracy and efficiency of thyroid disease diagnosis by thyroid scintigraphy.MethodsWe constructed DL models with AlexNet, VGGNet, and ResNet. The models were trained separately with transfer learning. We measured each model’s performance with six indicators: recall, precision, negative predictive value (NPV), specificity, accuracy, and F1-score. We also compared the diagnostic performances of first- and third-year nuclear medicine (NM) residents with assistance from the best-performing DL-based model. The Kappa coefficient and average classification time of each model were compared with those of two NM residents.ResultsThe recall, precision, NPV, specificity, accuracy, and F1-score of the three models ranged from 73.33% to 97.00%. The Kappa coefficient of all three models was >0.710. All models performed better than the first-year NM resident but not as well as the third-year NM resident in terms of diagnostic ability. However, the ResNet model provided “diagnostic assistance” to the NM residents. The models provided results at speeds 400 to 600 times faster than the NM residents.ConclusionDL-based models perform well in diagnostic assessment by thyroid scintigraphy. These models may serve as tools for NM residents in the diagnosis of Graves’ disease and subacute thyroiditis.     

中医人工智能辨证研究现状与发展＊

目的 总结中医人工智能辨证领域的研究历史与现状、应用状况、所面临的挑战，为中医辨证智能发展提供帮助。方法 检索中国知网（China National Knowledge Infrastructure，CNKI）总库1980年-2020年人工智能与中医辨证相关文献，筛选出301篇，以时间为线索，从专家系统、机器学习、深度学习和知识图谱，对中医辨证算法研究进行分类；以地域为线索，结合文献计量学可视化分析，梳理出中医辨证人工智能地域发展态势。结果 通过三个阶段中医辨证算法的比较，机器学习的神经网络、决策树和贝叶斯等算法模型辨证准确率均值在90%以上，适用于中医辨证，未来深度学习与知识图谱在中医辨证方面极具潜力。结论 中医辨证信息化迅猛发展并处于持续深入的状态，但中医文本数据的处理和结构化工作滞后，缺乏评价系统来评判人工智能算法在辨证上的效果，需予以重视。