Treatment strategies for hypertension in patients with type 1 diabetes

ABSTRACT

Introduction

Type 1 diabetes mellitus (T1DM) is a chronic, autoimmune disease that is characterized by total absence of insulin production. Hypertension is a common comorbidity in T1DM with complex pathophysiology, while it is also a well-recognized risk factor for the development of cardiovascular disease (CVD), as well as other microvascular diabetic complications.     

冠状病毒感染对心血管系统的损伤及可能机制

冠状病毒(coronavirus,CoVs)感染主要累及肺部,但对心血管系统损伤作用也不容忽视。CoVs感染引起的心脏损伤并非罕见,其发生与病情的严重程度密切相关。本文首先从CoVs引起心血管损伤的证据入手,进一步探讨了CoVs对心肌的直接损伤,以及肾素血管紧张素(RAS)系统激活和细胞因子风暴与炎症反应对心血管损伤的可能作用机制。相关心血管损伤的可能机制包括,(1)病毒直接作用:CoVs在心肌细胞复制,损伤心肌;(2)RAS系统激活:感染CoVs后,心脏血管紧张素转化酶2(angiotensin-converting enzyme 2,ACE2)的表达下调,激活RAS系统,使得血管紧张素Ⅱ(AngiotensinⅡ,AngⅡ)收缩血管功能增强,Ang1-7保护心脏效应减弱;(3)诱发细胞因子风暴:循环细胞因子和全身炎症反应引起心脏损伤;(4)其他:包括低氧血症和儿茶酚胺心脏毒性。本文就相关内容作一综述,为后续的详尽机制和治疗策略研究提供思路。     

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.     

Computational and experimental studies on the interaction between butyrylcholinesterase and fluoxetine: implications in health and disease

1. Butyrylcholinesterase (BChE) is a serine esterase that plays a role in the detoxification of natural as well as synthetic ester-bond-containing compounds. Alterations in BChE activity are associated with a number of diseases. Cholinergic system abnormalities in particular are correlated with the formation of senile plaques in Alzheimer’s disease (AD), and administration of cholinesterase inhibitors is a common therapeutic approach used to treat AD.

2. Here, our aim was to study the interaction between BChE and fluoxetine.

3. Molecular docking simulations revealed that fluoxetine penetrated deep into the active-site gorge of BChE and that it was engaged in stabilizing noncovalent interactions with multiple subsites. In substrate kinetic studies, the V_m, K_m, k_cat and k_cat/K_m values were found to be 20.59?±?0.36?U mg^?1 protein, 194?±?14?µM, 1.3?×?10⁸?s^?1 and 6.7?×?10⁵?µM^?1s^?1, respectively. Based on inhibitory studies, fluoxetine appeared to inhibit BChE competitively, with an IC₅₀ value of 104?µM and a K_i value of 36.3?±?4.7?µM.

4. Overall, both the low K_i value and the high number of BChE–fluoxetine interactions suggest that fluoxetine is a potent inhibitor of BChE, although in vivo mechanisms for the direct effects of BChE inhibition on various pathologies remain to be further investigated.

     

血管紧张素转换酶2对儿童2019冠状病毒病的作用研究进展

随着严重急性呼吸综合征冠状病毒2（SARS-CoV-2）在全球的肆虐，儿童感染者人数也越来越多。血管紧张素转换酶2（ACE2）是SARS-CoV-2感染人体的结合位点之一，可以与病毒尖峰蛋白结合，使得跨膜丝氨酸蛋白酶（TMPRSS2）启动S蛋白触发感染，引起白细胞介素-1、干扰素-γ、肿瘤坏死因子等多种炎性因子的产生。与成人相比，儿童的ACE2及TMPRSS2的表达水平较低，推测儿童症状较成人轻，发病人数较成人少均与此有关。该综述对SARS-CoV-2感染过程中ACE2的作用研究进展进行总结，有助于了解SARS-CoV-2的致病机制，为更好地开发药物及疫苗，防治儿童2019冠状病毒病提供参考。     

中国优秀马拉松运动员ACE基因I/D多态性频率分布特征

通过分析中国马拉松运动员ACE基因I/D多态频率分布特征,探讨其作为杰出耐力基因标记的可行性。选择我国马拉松健将、国际健将级运动员26名作为马拉松运动员组,汉族学生216名作为对照组。对两组受试者进行ACE基因I/D多态性测定。结果显示:我国马拉松运动员组的等位基因频率和基因型频率与对照组比较无显著差异,其中15名国际健将中无一DD型纯合子,提示我国优秀马拉松运动员的纯合子DD型频率低下是其ACE基因多态频率分布的主要特征。     

碳、氮源对PVA降解混合体系降解能力的影响及PVA降解机理初探

以能完全降解1g／LPVA的一个混合体系为研究对象，研究了碳、氮源对该混合体系降解PVA的影响。实验表明，补充有机氮源有利于混合体系菌体的生长，并且能提高混合体系对PVA的降解能力。进一步的研究发现，其它碳源的补充有利于菌体的生长，但对混合体系降解PVA产生一定的抑制作用。根据初步研究结果推断，该混合体系所产的PVA降解酶主要结合在细胞膜上，部分PVA进入细胞后被降解。     

人血清白蛋白修饰的尿激酶与天然尿激酶的家兔体内过程比较

家兔静注人血清白蛋白修饰的尿激酶(MUK)和天然尿激酶(NUK)40000IU后,MUK 的体内过程符合零级速率过程,NUK 则符合一级速率过程,血纤溶活性 MUK 持续100min,而 NUK 仅20～25min。在“功能性”去除肝肾的家兔,NUK 血浓度半衰期延长3～4倍,而 MUK 血浓度下降与正常家兔相似。MUK 及 NUK 在去除纤溶抑制物的优球蛋白成份中纤溶活性相似,但在血浆中 NUK 仅存24～35%的纤溶活性,MUK 则保留了64～85%的纤溶活性。提示肝肾的摄取、代谢和消除能力降低及对血浆纤溶抑制物抵抗力增强,是 MUK 血纤溶活性长时间维持高水平的主要原因。