Silencing KLF16 inhibits oral squamous cell carcinoma cell proliferation by arresting the cell cycle and inducing apoptosis

Krüppel-like factor 16 (KLF16), a member of the Krüppel-like factor (KLF) family, has been extensively investigated in multiple cancer types. However, the role of KLF16 in oral squamous cell carcinoma (OSCC) remains unknown. Thus, we conducted this study to investigate its related mechanism. KLF16 expression in OSCC cell lines was quantified by western blotting. Then, OECM1 and OC3 cells were divided into Blank, siCtrl, siKLF16#1 and siKLF16#2 groups. Subsequently, cell proliferation was detected using 3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide (MTT) assays, cell migration and invasion were detected with wound healing and Transwell assays, and cell cycle distribution and cell apoptosis were detected via flow cytometry. KLF16, p21, CDK4, Cyclin D1 and p-Rb expression was detected by western blotting. Finally, xenograft models were established in nude mice to observe the in vivo effects of KLF16 on OSCC. KLF16 protein expression was upregulated in OSCC cells. Compared to the cells in the Blank group, the OECM1 and OC3 cells in the siKLF16#1 group and siKLF16#2 group exhibited a sharp decrease in proliferation but a remarkable increase in apoptosis. Moreover, the proportion of cells in the G0/G1 phase notably increased and that in the S phase decreased, with evident decreases in cell invasion and migration. Moreover, KLF16, cyclin-dependent kinase 4 (CDK4), Cyclin D1 and p-Rb protein expression was upregulated, but p21 expression was downregulated. The mice in the siKLF16#1 and siKLF16#2 xenograft model groups exhibited slower tumour growth and smaller tumours with evident downregulation of Ki67 expression compared to the mice in the Blank group. KLF16 expression was upregulated in OSCC cells, and interfering with KLF16 led to cell cycle arrest, inhibited OSCC cell growth and promoted cell apoptosis.     

Effects of age,gender and menstrual cycle on platelet function assessed by impedance aggregometry

Platelets are needed to prevent or arrest bleeding and aggregate at the site of injury upon vascular damage. Platelets express receptors for estrogens which might affect the function of the platelets and their hemostatic ability. The aim was to identify possible differences in platelet function related to age, gender, and phases of the menstrual cycle by use of impedance aggregometry with Multiplate. In the first part of the study, platelet function was assessed in 60 healthy individuals (30 men and 30 women) in each of three age groups (20–25, 40–45, and 60–65 years). In the second part of the study, the platelet function was analyzed on four occasions during the menstrual cycle in women without oral contraceptives (OCs) (n = 17) and compared to 19 women on OCs and 18 men of similar age (20–40 years). For the women on OCs, aggregation was analyzed once during the tablet-free week and once late during the period with OCs. The men were sampled once. Women of younger age (<45 years) had significantly higher agonist-induced aggregation response than both men and post-menopausal women (60–65 years). The agonist-induced aggregation response did not differ between phases of the menstrual cycle or OC use. The results suggest that estradiol and/or progesterone affect spontaneous aggregation since it was found to be lowest in the mid-luteal phase. Spontaneous aggregation was significantly lower in women on OCs than in both men and women without OCs. Our findings indicate that fertile age is associated with higher aggregation response capacity of the platelets, possibly to prevent excessive bleeding during menstruation, but this response capacity is not altered during the menstrual cycle or by use of OCs.     

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.     

运用PDCA循环改进居家养老护理文件书写质量

目的运用PDCA循环的质量管理方法,改进居家养老护理文件书写质量。方法对现存的护理质量不合格项目进行原因分析、制定改进计划、组织实施、效果评价。结果改进后的居家养老护理文件书写合格率达到98%。结论通过应用PDCA循环质量管理工具进行护理质量管理,使该中心居家养老护理文件书写水平得到大幅度提高,同时促进了该中心护理管理质量的提升。     

PDCA循环在消化道肿瘤伴糖尿病患者营养全程管理中的效果观察

目的 探讨PDCA 循环在消化道肿瘤伴糖尿病患者营养全程管理中的效果观察。方法 运用PDCA循环对80例不同程度营养不良的消化道肿瘤伴糖尿病患者实施营养全程管理,比较干预前后患者的体重、BMI指数、糖化血红蛋白、血红蛋白、总蛋白、白蛋白及球蛋白水平。结果 患者血红蛋白、总蛋白、白蛋白及球蛋白水平均有提高,比较差异均有统计学意义(P＜0.05)。结论 PDCA循环管理在消化道肿瘤伴糖尿病患者营养全程管理中有较大的优势, 值得推广。     

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.