Inhibition of Stimulator of Interferon Genes Protects Against Myocardial Ischemia-Reperfusion Injury in Diabetic Mice

Background: Although the past decade has witnessed substantial scientific progress with the advent of cardioprotective pharmacological agents, most have failed to protect against myocardial ischemia/reperfusion (I/R) injury in diabetic hearts. This study was aimed at investigating the role of stimulator of interferon genes (STING) in I/R injury in diabetic mice and further exploring the underlying mechanisms. Methods: Type 2 diabetic mice were subjected to I/R or sham operation to investigate the role of STING. STING knockout mice were subjected to 30 minutes of ischemia followed by reperfusion for 24 hours. Finally, myocardial injury, cardiac function, and inflammation levels were assessed. Results: STING pathway activation was observed in diabetic I/R hearts, as evidenced by increased p-TBK and p-IRF3 expression. STING knockout significantly decreased the ischemic area and improved cardiac function after I/R in diabetic mice. STING knockout also elicited cardio-protective effects by decreasing serum cardiac troponin T and lactate dehydrogenase levels, thus diminishing the inflammatory response in the heart after I/R in diabetic mice. In vitro , STING inhibition decreased the expression of hypoxia-re-oxygenation-induced inflammatory cytokines. Conclusions: Targeting STING inhibits inflammation and prevents I/R injury in diabetic mice. Thus, STING may be a potential novel therapeutic target against myocardial I/R injury in diabetes

Mitotic Spindle Proteomics in Chinese Hamster Ovary Cells

Mitosis is a fundamental process in the development of all organisms. The mitotic spindle guides the cell through mitosis as it mediates the segregation of chromosomes, the orientation of the cleavage furrow, and the progression of cell division. Birth defects and tissue-specific cancers often result from abnormalities in mitotic events. Here, we report a proteomic study of the mitotic spindle from Chinese Hamster Ovary (CHO) cells. Four different isolations of metaphase spindles were subjected to Multi-dimensional Protein Identification Technology (MudPIT) analysis and tandem mass spectrometry. We identified 1155 proteins and used Gene Ontology (GO) analysis to categorize proteins into cellular component groups. We then compared our data to the previously published CHO midbody proteome and identified proteins that are unique to the CHO spindle. Our data represent the first mitotic spindle proteome in CHO cells, which augments the list of mitotic spindle components from mammalian cells

Internet of Things for Sustainable Human Health

The sustainable health IoT has the strong potential to bring tremendous improvements in human health and well-being through sensing, and monitoring of health impacts across the whole spectrum of climate change. The sustainable health IoT enables development of a systems approach in the area of human health and ecosystem. It allows integration of broader health sub-areas in a bigger archetype for improving sustainability in health in the realm of social, economic, and environmental sectors. This integration provides a powerful health IoT framework for sustainable health and community goals in the wake of changing climate. In this chapter, a detailed description of climate-related health impacts on human health is provided. The sensing, communications, and monitoring technologies are discussed. The impact of key environmental and human health factors on the development of new IoT technologies also analyzed

Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation: As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and developm nt investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens

LncRNA GAS5 downregulates NLRP3 inflammasome activation-mediated pyroptosis in sepsis-induced myocardial injury by targeting SIRT3/AMPKα

An increasing body of studies has demonstrated the significance of long non-coding RNA (lncRNA) growth arrest specific 5 (GAS5) in inflammation and myocardial injury in septic shock. This research aims to determine whether GAS5 contributes to the pathological development of sepsis-induced cardiac damage and NLRP3 inflammasome-mediated myocardial cell pyroptosis. Cecal ligation and puncture (CLP) surgery was used to cause septic shock in C57BL/6 wild-type mice. After CLP, inflammatory, pyroptosis parameters of myocardial tissue, survival rate, and Murine Sepsis Score (MSS) were assessed to evaluate the involvement of GAS5 in the mouse myocardial depression. To investigate GAS5's function in lipopolysaccharide (LPS) induced myocardial cell pyroptosis, gain- and loss-of-function experiments were conducted in vitro on HL-1 cells. Our findings indicated that CLP dramatically reduced survival rates, MSS, SIRT3 and p-AMPK expression, and activated the Nuclear factor-κB (NF-κB) pathway and NLRP3 inflammasome-mediated pyroptosis. The NF-κB and pyroptosis pathways were greatly elevated while SIRT3/p-AMPKα was dramatically decreased as a result of GAS5 being downregulated. Meanwhile, the regulatory effect could be suppressed by SIRT3 and AMPKα activator. Our observations supported the idea that GAS5 has a crucial protective impact against myocardial inflammation and pyroptosis in sepsis

Monitoring of physiological parameters from multiple patients using wireless sensor network

This paper presents a wireless sensor network system that has the capability to monitor physiological parameters from multiple patient bodies. The system uses the Medical Implant Communication Service band between the sensor nodes and a remote central control unit (CCU) that behaves as a base station. The CCU communicates with another network standard (the internet or a mobile network) for a long distance data transfer. The proposed system offers mobility to patients and flexibility to medical staff to obtain patient’s physiological data on demand basis via Internet. A prototype sensor network including hardware, firmware and software designs has been implemented and tested. The developed system has been optimized for power consumption by having the nodes sleep when there is no communication via a bidirectional communication