皮肤鳞状细胞癌的中医药治疗进展

皮肤鳞状细胞癌是具有发病率高、发展快、可转移、易误诊等特点的一种恶性肿瘤，对人类的健康造成威胁。随着中医的发展和现代医学实验研究技术的进步，中医药在皮肤鳞状细胞癌的现代研究方面也取得一定成果。目前临床上治疗鳞状细胞癌多采取手术及药物化疗等，因不良反应的存在，患者接受度低。中药具有多靶点、安全性高、不良反应少等优势，在治疗皮肤鳞状细胞癌中中医具有一定优势，本文将围绕中药单体、中药复方，以及针灸在治疗皮肤鳞状细胞癌的研究进展展开论述和思考。     

糖尿病前期中医证型及证素特点分析＊

目的 探讨糖尿病前期的中医证型及证素分布特点。方法 检索中国知网、万方及维普三大数据库中收录的自建库以来有关糖尿病前期证型的临床研究文献，对中医证型进行规范整理，建立数据库，提取证素，运用数据挖掘技术中的关联分析、聚类分析探究证素分布规律。结果 共纳入10篇文献，总有效病例1620例，证型经规范处理后整理为18个，主要证型为脾虚痰湿证。共提取证素13个，主要病位证素为脾，主要病性证素为气虚、湿和痰，关联分析显示脾—湿支持度和置信度最高，聚类分析结果可得到3个聚类组。结论 糖尿病前期病位在脾，气虚、脾、痰、湿是常见证素，临床诊治糖尿病前期应注重从脾论治，需辨证施治。     

疏肝健脾法治疗腹泻型肠易激综合征1例

肠易激综合征（IBS）是一种常见的功能性疾病，中医病名为"肠郁"。郭朋教授根据IBS生理、病理特点，以疏肝健脾法调和肝脾，辨证施治，取得良好疗效。文章从病因病机、辨证论治及经典案例介绍等几个方面对郭教授治疗IBS经验进行系统阐述，以期为中医药治疗IBS提供理论和方法学参考。     

Machine learning models for Parkinson’s disease detection and stage classification based on spatial-temporal gait parameters

BackgroundParkinson’s disease (PD) is a chronic and progressive neurodegenerative disease with no cure, presenting a challenging diagnosis and management. However, despite a significant number of criteria and guidelines have been proposed to improve the diagnosis of PD and to determine the PD stage, the gold standard for diagnosis and symptoms monitoring of PD is still mainly based on clinical evaluation, which includes several subjective factors. The use of machine learning (ML) algorithms in spatial-temporal gait parameters is an interesting advance with easy interpretation and objective factors that may assist in PD diagnostic and follow up.Research questionThis article studies ML algorithms for: i) distinguish people with PD vs. matched-healthy individuals; and ii) to discriminate PD stages, based on selected spatial-temporal parameters, including variability and asymmetry.MethodsGait data acquired from 63 people with PD with different levels of PD motor symptoms severity, and 63 matched-control group individuals, during self-selected walking speed, was study in the experiments.ResultsIn the PD diagnosis, a classification accuracy of 84.6 %, with a precision of 0.923 and a recall of 0.800, was achieved by the Naïve Bayes algorithm. We found four significant gait features in PD diagnosis: step length, velocity and width, and step width variability. As to the PD stage identification, the Random Forest outperformed the other studied ML algorithms, by reaching an Area Under the ROC curve of 0.786. We found two relevant gait features in identifying the PD stage: stride width variability and step double support time variability.SignificanceThe results showed that the studied ML algorithms have potential both to PD diagnosis and stage identification by analysing gait parameters.     

From the "what" to the "how": Teaching integrative medicine-related skills to medical students during COVID-19

ObjectiveTo examine the impact of an integrative medicine (IM) course on self-perceived IM-related communication and research skills.MethodsA 3-day mandatory "hybrid" (online and in-person) IM course was held within COVID-19 restrictions for 161 pre-clerkship medical students, with workshops facilitated by mentor healthcare professionals (IM and non-IM) and student-directed tasks. Self-perceived levels of 6 IM-related skills were scored (from 1 to 5) for history-taking; communicating with patients with "alternative" health-beliefs; referral to IM consultations; assessing risks/benefits; and working with non-medical IM practitioners.Results137 students (85.1%) completed pre-/post-course questionnaires, with overall scores improving from pre-course (1.98 ± 0.92) to post-course (3.31 ± 0.63; p < 0.0001), for the entire group and student subgroups (with vs. without prior IM experience). Multivariate analysis found no association between age, gender, primary language or prior experience with IM and improvement in skill scores.ConclusionsThe IM course increased self-perceived skill levels, reflecting the course curriculum and workshops. Further research needs to explore the application of these skills during clinical training.Practice implicationsTeaching medical students about IM in a course comprising communication and research skills was shown to be feasible and effective. The application of IM-related skills needs to be evaluated during the clinical clerkship.     

肿瘤的数字治疗北大核心

肿瘤治疗已经进入数字治疗时代。数字治疗是数字健康的重要部分,它是应用数字技术预防、控制和治疗疾病。人工智能分析由生物传感器发来的数据资料,远距离控制肿瘤患者进行虚拟治疗和数字临床试验,模拟现实在线治疗帮助肿瘤患者采取健康行为,这些技术正在改变现有的医学模式。     

薄层色谱法在当前中药质量标准中的应用探讨

薄层色谱鉴别在历版《中国药典》中的应用经历了从无到有、从少到多的过程；而薄层扫描含量测定在最近几版《中国药典》中的应用比例逐渐降低。随着对中药质量标准体系要求的进一步提高，薄层色谱法的不足之处陆续显现，如仪器普及率低、设备并不简单、结果重复性和稳定性较差、鉴别速度及准确性不及高效液相色谱法、展开剂毒性大等，逐渐不合时宜。在制定中药质量标准时，研究者不应该墨守成规，薄层色谱鉴别也不应该是雷打不动的定性鉴别必备选项。高效液相色谱法具备完全取代薄层色谱法的可行性，薄层色谱法可作为高效液相色谱法的补充。为充分降低检测成本、缩短检测周期、提高鉴别效率，笔者建议中药质量标准体系应该大幅减少薄层色谱鉴别方法的应用，增加高效液相特征图谱鉴定，尽量做到“一个条件，一张图谱”；除非确有必要，《中国药典》等国家质量标准体系应将薄层色谱鉴别作为推荐方法，而非强制标准。