Pathway clusters of aging genes using data mining techniques

Exploring and identifying novel aging genes has been the current area of interest in Gerontology. A variety of techniques have been proposed to identify the genes that affect the centenarians and the focus is on the study of genes of interest affecting older population. However the study of aging related pathways using computational methods has not been discussed explicitly so far. In this paper, an attempt is made to cluster the aging genes into different biological pathways using data mining techniques. Text mining is used to identify the most relevant keywords from different pathway databases, which is used as one of the feature describing a gene. K-means clustering is done on the aging pathway dataset. The clusters formed are in good agreement with the background knowledge about the aging genes and their pathways. The quality of the K-means clustering is quite promising as it well separates the different aging genes into their respective pathways

Development of a Smartphone-Enabled Hypertension and Diabetes Mellitus Management Package to Facilitate Evidence-Based Care Delivery in Primary Healthcare Facilities in India: The mPower Heart Project.

BACKGROUND: The high burden of undetected and undertreated hypertension and diabetes mellitus is a major health challenge worldwide. The mPower Heart Project aimed to develop and test a feasible and scalable intervention for hypertension and diabetes mellitus by task-sharing with the use of a mobile phone-based clinical decision support system at Community Health Centers in Himachal Pradesh, India. METHODS AND RESULTS: The development of the intervention and mobile phone-based clinical decision support system was carried out using mixed methods in five Community Health Centers. The intervention was subsequently evaluated using pre-post evaluation design. During intervention, a nurse care coordinator screened, examined, and entered patient parameters into mobile phone-based clinical decision support system to generate a prescription, which was vetted by a physician. The change in systolic blood pressure, diastolic blood pressure, and fasting plasma glucose (FPG) over 18 months of intervention was quantified using generalized estimating equations models. During intervention, 6797 participants were enrolled. Six thousand sixteen participants had hypertension (mean systolic blood pressure: 146.1 mm Hg, 95% CI: 145.7, 146.5; diastolic blood pressure: 89.52 mm Hg, 95% CI: 89.33, 89.72), of which 3152 (52%) subjects were newly detected. Similarly, 1516 participants had diabetes mellitus (mean FPG: 177.9 mg/dL, 95% CI: 175.8, 180.0), of which 450 (30%) subjects were newly detected. The changes in systolic blood pressure, diastolic blood pressure, and FPG observed at 18 months of follow-up were -14.6 mm Hg (95% CI: -15.3, -13.8), -7.6 mm Hg (CI: -8.0, -7.2), and -50.0 mg/dL (95% CI: -54.6, -45.5), respectively, and were statistically significant even after adjusting for age, sex, and Community Health Center. CONCLUSIONS: A nurse-facilitated, mobile phone-based clinical decision support system-enabled intervention in primary care was associated with improvements in blood pressure and blood glucose control and has the potential to scale-up in resource poor settings. CLINICAL TRIAL REGISTRATION: URL: https://www.clinicaltrials.gov. Unique identifiers: NCT01794052. Clinical Trial Registry-India: CTRI/2013/02/003412

SEAD: source encrypted authentic data for wireless sensor networks

One of the critical issues in WSNs is providing security for the secret data in military applications. It is necessary to ensure data integrity and authentication for the source data and secure end-to-end path for data transmission. Mobile sinks are suitable for data collection and localization. Mobile sinks and sensor nodes communicate with each other using their public identity, which is prone to security attacks like sink replication and node replication attack. In this work, we have proposed Source Encrypted Authentic Data algorithm (SEAD) that hides the location of mobile sink from malicious nodes. The sensed data is encrypted utilizing symmetric encryption---Advanced Encryption Standards (AES) and tracks the location of the mobile sink. When data encounters a malicious node in a path, then data transmission path is diverted through a secure path. SEAD uses public encryption---Elliptic Curve Cryptography (ECC) to verify the authenticity of the data. Simulation results show that the proposed algorithm ensures data integrity and node authenticity against malicious nodes. Double encryption in the proposed algorithm produces better results in comparison with the existing algorithms

Protocol for the mWellcare trial: a multicentre, cluster randomised, 12-month, controlled trial to compare the effectiveness of mWellcare, an mHealth system for an integrated management of patients with hypertension and diabetes, versus enhanced usual care in India.

INTRODUCTION: Rising burden of cardiovascular disease (CVD) and diabetes is a major challenge to the health system in India. Innovative approaches such as mobile phone technology (mHealth) for electronic decision support in delivering evidence-based and integrated care for hypertension, diabetes and comorbid depression have potential to transform the primary healthcare system. METHODS AND ANALYSIS: mWellcare trial is a multicentre, cluster randomised controlled trial evaluating the clinical and cost-effectiveness of a mHealth system and nurse managed care for people with hypertension and diabetes in rural India. mWellcare system is an Android-based mobile application designed to generate algorithm-based clinical management prompts for treating hypertension and diabetes and also capable of storing health records, sending alerts and reminders for follow-up and adherence to medication. We recruited a total of 3702 participants from 40 Community Health Centres (CHCs), with ≥90 at each of the CHCs in the intervention and control (enhanced care) arms. The primary outcome is the difference in mean change (from baseline to 1 year) in systolic blood pressure and glycated haemoglobin (HbA1c) between the two treatment arms. The secondary outcomes are difference in mean change from baseline to 1 year in fasting plasma glucose, total cholesterol, predicted 10-year risk of CVD, depression, smoking behaviour, body mass index and alcohol use between the two treatment arms and cost-effectiveness. ETHICS AND DISSEMINATION: The study has been approved by the institutional Ethics Committees at Public Health Foundation of India and the London School of Hygiene and Tropical Medicine. Findings will be disseminated widely through peer-reviewed publications, conference presentations and other mechanisms. TRIAL REGISTRATION: mWellcare trial is registered with Clinicaltrial.gov (Registration number NCT02480062; Pre-results) and Clinical Trial Registry of India (Registration number CTRI/2016/02/006641). The current version of the protocol is Version 2 dated 19 October 2015 and the study sponsor is Public Health Foundation of India, Gurgaon, India (www.phfi.org)

Clinically Stable COVID-19 Patients Presenting to Acute Unscheduled Episodic Care Venues Have Increased Risk of Hospitalization: Secondary Analysis of a Randomized Control Trial

BACKGROUND: Assessment for risks associated with acute stable COVID-19 is important to optimize clinical trial enrollment and target patients for scarce therapeutics. To assess whether healthcare system engagement location is an independent predictor of outcomes we performed a secondary analysis of the ACTIV-4B Outpatient Thrombosis Prevention trial. METHODS: A secondary analysis of the ACTIV-4B trial that was conducted at 52 US sites between September 2020 and August 2021. Participants were enrolled through acute unscheduled episodic care (AUEC) enrollment location (emergency department, or urgent care clinic visit) compared to minimal contact (MC) enrollment (electronic contact from test center lists of positive patients).We report the primary composite outcome of cardiopulmonary hospitalizations, symptomatic venous thromboembolism, myocardial infarction, stroke, transient ischemic attack, systemic arterial thromboembolism, or death among stable outpatients stratified by enrollment setting, AUEC versus MC. A propensity score for AUEC enrollment was created, and Cox proportional hazards regression with inverse probability weighting (IPW) was used to compare the primary outcome by enrollment location. RESULTS: Among the 657 ACTIV-4B patients randomized, 533 (81.1%) with known enrollment setting data were included in this analysis, 227 from AUEC settings and 306 from MC settings. In a multivariate logistic regression model, time from COVID test, age, Black race, Hispanic ethnicity, and body mass index were associated with AUEC enrollment. Irrespective of trial treatment allocation, patients enrolled at an AUEC setting were 10-times more likely to suffer from the adjudicated primary outcome, 7.9% vs. 0.7%; p \u3c 0.001, compared with patients enrolled at a MC setting. Upon Cox regression analysis adjustment patients enrolled at an AUEC setting remained at significant risk of the primary composite outcome, HR 3.40 (95% CI 1.46, 7.94). CONCLUSIONS: Patients with clinically stable COVID-19 presenting to an AUEC enrollment setting represent a population at increased risk of arterial and venous thrombosis complications, hospitalization for cardiopulmonary events, or death, when adjusted for other risk factors, compared with patients enrolled at a MC setting. Future outpatient therapeutic trials and clinical therapeutic delivery programs of clinically stable COVID-19 patients may focus on inclusion of higher-risk patient populations from AUEC engagement locations

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

BACKGROUND: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. METHODS: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. FINDINGS: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. INTERPRETATION: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic. FUNDING: Bill & Melinda Gates Foundation

Association between visual acuity and vision related quality of life in patients with non-infectious uveitis

Introduction: Vision related quality of life is often measured as a secondary patient reported outcome (PRO) in clinical trials of treatments for eye disease. The cross-sectional association of this measure with visual acuity (the “gold standard” primary outcome used in clinical studies in ophthalmology) has been studied extensively in patients with and without eye disease. However, the relationships between treatment induced changes in visual acuity and quality of life measures are not well studied. The goal of this dissertation was to study the association between trajectories of visual acuity and vision related quality of life in patients with non-infectious uveitis using three approaches. Specifically, our aims were to (i) to explore how baseline visual acuity predicts the trajectory of vision related quality of life over the course of long-term (three-year) follow up in patients with non-infectious uveitis (ii) to study the association between long-term (three-year) changes in visual acuity and vision related quality of life from baseline to the end of follow up and (iii) to examine the association between short-term (six-month) changes in visual acuity and vision related quality of life. We were also interested in exploring the impact of ocular and systemic events on changes in vision related quality of life scores both in the long-term as well as the short-term. Methods: We used data from the Multicenter Uveitis Steroid Treatment (MUST) trial, a randomized, parallel group, open label comparative effectiveness trial comparing the efficacy of fluocinolone acetonide implant therapy and systemic corticosteroids (supplemented with immunosuppressive therapy, where indicated) in patients with non-infectious uveitis for our analyses. Vision related quality of life was measured using the 25-item National Eye Institute Visual Functioning Questionnaire (VFQ25), a standard and well-validated questionnaire. Visual acuity measurements were taken using the Early Treatment in Diabetic Retinopathy Study (ETDRS) charts. We categorized baseline visual acuity as 20/40 or better and worse than 20/40. For analyses considering change in visual acuity, we defined categories of change as an increase of 5 letters or more, a decrease of 5 letters or more and no change (-4 to 4 letters change). We considered vision in the better-seeing eye for all our primary analyses, and conducted sensitivity analyses to explore the impact of using the worse-seeing eye. We also considered ocular events such as cataract surgery, glaucoma diagnosis, uveitis activity etc. as well as chronic and acute systemic adverse events in our analyses for aims 2 and 3. Results from exploratory analyses were used to inform choice of predictors for the final regression models for all the aims. Results: We found that the trajectories of vision related quality of life scores were different in the systemic and implant groups in the MUST trial. Baseline visual acuity and visual field impairment were predictive of statistically significant differences in vision related quality of life scores at baseline in both the treatment groups, and these differences were sustained throughout follow up. However, baseline visual field impairment did not have any impact on short-term or long-term change in VFQ25 scores after adjusting for the corresponding short-term or long-term change in visual acuity. Regardless of treatment received, a gain of 5 letters or more in visual acuity in the long-term resulted in a statistically significantly larger increases in the VFQ25 scores from baseline to the end of three years compared to no change in visual acuity. A decline in visual acuity was associated with a smaller increase in VFQ25 score over three years compared to no change in visual acuity. These relationships were observed in the short term (six-month intervals) as well, however the magnitude of differences in the change in VFQ25 scores between the visual acuity groups was smaller. Among the ocular and systemic events, cataract surgery was the only ocular event that was associated with changes in VFQ25 scores and led to an improvement in vision related quality of life in both the short-term and long-term. Conclusions: We have shown that both baseline visual acuity and visual field impairment are independently associated with differences in VFQ25 scores over time. We have also shown that the VFQ25 questionnaire is sensitive to changes in visual acuity; however visual acuity did not fully explain all of the variability in the VFQ25 scores. This may be because vision related quality of life captures aspects of visual functioning that visual acuity alone might not capture. The frequent measurement of these complementary aspects of vision is important to consider in the design and implementation of future clinical studies in uveitis. Cataract surgery had an independent positive impact on VFQ25 scores. Further research is needed to explore the sensitivity of generic quality of life instruments to changes in clinical measures of vision and to compare evaluation of cost-effectiveness of treatments using the VFQ25 and other quality of life questionnaires

Parallelized Sequence Comparison of Human and Naked Mole Rat for Aging Studies

A significant increase in the elderly population in the last few decades is expected to rise even more in near future. Inspite of advancement in research on aging; still aging remains unrevealed to a larger extent. Aging is considered to be a major cause for many diseases like cancer, diabetes, Parkinson. The naked mole rat is one of the most promising rodents in aging research. The present work deals with the application of parallel computation to compare the mitochondrial RNA of human with… Expan