RESUMEN
The functional role of procyanidins (PC) in PM2.5-induced cardiovascular diseases (CVD) is largely unexplored. This study aimed to explore the protective effect of PC against PM2.5-induced vascular smooth muscle cells (VSMCs) apoptosis and underlying mechanisms. Sprague Dawley rats were pretreated with three doses of PC (50, 100, and 200 mg/kg) and exposed to 10 mg/kg PM2.5 by intratracheal instillation three times a week. VSMCs were exposed to 5, 10, and 20 µM PC before the addition of 100 µg/mL PM2.5. In vivo, the PM2.5 exposure induced apoptosis in the thoracic aorta of rats. The PM2.5 exposure significantly elevated the reactive oxygen species (ROS) and malondialdehyde (MDA) levels and decreased the superoxide dismutase activity. Also, PC supplementation increased the expression of nuclear factor erythroid 2-related factor 2 (Nrf2), and its downstream antioxidant genes, i.e., NAD(P)H dehydrogenase (quinine) 1 and heme oxygenase 1, attenuated oxidative stress and vascular apoptosis. In vitro, PM2.5 induced cytotoxicity in VSMCs in a dose-dependent manner. Besides, PC abolished the PM2.5-induced cytotoxicity by activating the Nrf2 signal pathway, alleviating oxidative stress, and decreasing apoptosis. In conclusion, this work is the first study to demonstrate that PC can suppress the PM2.5-induced VSMCs apoptosis via the activation of the Nrf2 signal pathway.
Asunto(s)
Factor 2 Relacionado con NF-E2 , Proantocianidinas , Animales , Apoptosis , Músculo Liso Vascular/metabolismo , Factor 2 Relacionado con NF-E2/genética , Factor 2 Relacionado con NF-E2/metabolismo , Estrés Oxidativo , Material Particulado/metabolismo , Material Particulado/toxicidad , Proantocianidinas/farmacología , Ratas , Ratas Sprague-Dawley , Especies Reactivas de Oxígeno/metabolismo , Transducción de SeñalRESUMEN
A tert-butyl hydroperoxide (TBHP)-mediated coupling of sulfonylhydrazides with thiols catalyzed by CuBr2 to afford thiosulfonates via a radical process is described.
RESUMEN
Time-restricted eating (TRE) is known to improve metabolic health, whereas very few studies have compared the effects of early and late TRE (eTRE and lTRE) on metabolic health. Overweight and obese young adults were randomized to 6-h eTRE (eating from 7 a.m. to 1 p.m.) (n = 21), 6-h lTRE (eating from 12 p.m. to 6 p.m.) (n = 20), or a control group (ad libitum intake in a day) (n = 19). After 8 weeks, 6-h eTRE and lTRE produced comparable body weight loss compared with controls. Compared with control, 6-h eTRE reduced systolic blood pressure, mean glucose, fasting insulin, insulin resistance, leptin, and thyroid axis activity, whereas lTRE only reduced leptin. These findings shed light on the promise of 6-h eTRE and lTRE for weight loss. Larger studies are needed to assess the promise of eTRE to yield better thyroid axis modulation and overall cardiometabolic health improvement.
RESUMEN
Since fall is happening with increasing frequency, it has been a major public health problem in an aging society. There are considerable demands to distinguish fall down events of seniors with the characteristics of accurate detection and real-time alarm. However, some daily activities are erroneously signaled as falls and there are too many false alarms in actual application. In order to resolve this problem, this paper designs and implements a comprehensive fall detection framework on the basis of inertial posture sensors and surveillance cameras. In the proposed system framework, data sources representing behavior characteristics to indicate potential fall are derived from wearable triaxial accelerometers and monitoring videos of surveillance cameras. Moreover, the NB-IoT based communication mode is adopted to transmit wearable sensory data to the Internet for subsequent analysis. Furthermore, a Gradient Boosting Decision Tree (GBDT) classifier-based fall detection algorithm (GBDT-FD in short) with comprehensive data fusion of posture sensor and human video skeleton is proposed to improve detection accuracy. Experimental results verify the good performance of the proposed GBDT-FD algorithm compared to six kinds of existing fall detection algorithms, including SVM-based fall detection, NN-based fall detection, etc. Finally, we implement the proposed integrated systems including wearable posture sensors and monitoring software on the Cloud Server.