Association Between Educational Status and Mortality According to Diabetes Status Among US Adults.

Objective: To examine differences in the association between educational attainment and mortality by the presence of diabetes and diabetic retinopathy (DR)-a major complication of diabetes. Patients and Methods: We used a nationally representative sample of 54,924 US adults aged 20 years or older with diabetes from the National Health and Nutrition Examination Survey 1999-2018 and its mortality data through 2019. We applied the multivariable Cox proportional hazard models to investigate the associations between educational attainment (low, less than high school; middle, high school; and high, more than high school) and all-cause mortality according to diabetes status: nondiabetes, diabetes without DR, and diabetes with DR. Differences in the survival rate by educational attainment were evaluated using the slope inequality index (SII). Results: Among the 54,924 participants (mean age, 49.9 years), adults in the low educational group reported an increased risk of all-cause mortality compared with those of the high educational group in any diabetes status (nondiabetes-hazard ratio [HR], 1.69; 95% CI, 1.56-1.82; diabetes without DR-HR, 1.61; 95% CI, 1.37-1.90; diabetes with DR-HR, 1.43; 95% CI, 1.10-1.86). SIIs among the diabetes without DR group and diabetes with DR group were 22.17 and 20.87 per 1000 person-years, respectively, which were 2 times greater than those among the nondiabetes group (SII=9.94). Conclusion: The differences in the mortality risks owing to the educational attainment increased by the presence of diabetes regardless of the complication of DR. Our findings indicate that prevention of diabetes itself is critical to mitigate health disparities by socioeconomic status such as education status.

Deconvoluting complex correlates of COVID-19 severity with a multi-omic pandemic tracking strategy.

The SARS-CoV-2 pandemic has differentially impacted populations across race and ethnicity. A multi-omic approach represents a powerful tool to examine risk across multi-ancestry genomes. We leverage a pandemic tracking strategy in which we sequence viral and host genomes and transcriptomes from nasopharyngeal swabs of 1049 individuals (736 SARS-CoV-2 positive and 313 SARS-CoV-2 negative) and integrate them with digital phenotypes from electronic health records from a diverse catchment area in Northern California. Genome-wide association disaggregated by admixture mapping reveals novel COVID-19-severity-associated regions containing previously reported markers of neurologic, pulmonary and viral disease susceptibility. Phylodynamic tracking of consensus viral genomes reveals no association with disease severity or inferred ancestry. Summary data from multiomic investigation reveals metagenomic and HLA associations with severe COVID-19. The wealth of data available from residual nasopharyngeal swabs in combination with clinical data abstracted automatically at scale highlights a powerful strategy for pandemic tracking, and reveals distinct epidemiologic, genetic, and biological associations for those at the highest risk.

Using genomic epidemiology of SARS-CoV-2 to support contact tracing and public health surveillance in rural Humboldt County, California.

BACKGROUND: During the COVID-19 pandemic within the United States, much of the responsibility for diagnostic testing and epidemiologic response has relied on the action of county-level departments of public health. Here we describe the integration of genomic surveillance into epidemiologic response within Humboldt County, a rural county in northwest California. METHODS: Through a collaborative effort, 853 whole SARS-CoV-2 genomes were generated, representing ~58% of the 1,449 SARS-CoV-2-positive cases detected in Humboldt County as of March 12, 2021. Phylogenetic analysis of these data was used to develop a comprehensive understanding of SARS-CoV-2 introductions to the county and to support contact tracing and epidemiologic investigations of all large outbreaks in the county. RESULTS: In the case of an outbreak on a commercial farm, viral genomic data were used to validate reported epidemiologic links and link additional cases within the community who did not report a farm exposure to the outbreak. During a separate outbreak within a skilled nursing facility, genomic surveillance data were used to rule out the putative index case, detect the emergence of an independent Spike:N501Y substitution, and verify that the outbreak had been brought under control. CONCLUSIONS: These use cases demonstrate how developing genomic surveillance capacity within local public health departments can support timely and responsive deployment of genomic epidemiology for surveillance and outbreak response based on local needs and priorities.

Evolution of reproductive traits have no apparent life-history associated cost in populations of Drosophila melanogaster selected for cold shock resistance.

BACKGROUND: In insect species like Drosophila melanogaster, evolution of increased resistance or evolution of particular traits under specific environmental conditions can lead to energy trade-offs with other crucial life-history traits. Adaptation to cold stress can, in principle, involve modification of reproductive traits and physiological responses. Reproductive traits carry a substantial cost; and therefore, the evolution of reproductive traits in response to cold stress could potentially lead to trade-offs with other life-history traits. We have successfully selected replicate populations of Drosophila melanogaster for increased resistance to cold shock for over 33 generations. In these populations, the ability to recover from cold shock, mate, and lay fertile eggs 24 h post cold shock is under selection. These populations have evolved a suite of reproductive traits including increased egg viability, male mating ability, and siring ability post cold shock. These populations also show elevated mating rate both with and without cold shock. In the present study, we quantified a suite of life-history related traits in these populations to assess if evolution of cold shock resistance in these populations comes at a cost of other life-history traits. RESULTS: To assess life-history cost, we measured egg viability, mating frequency, longevity, lifetime fecundity, adult mortality, larva to adult development time, larvae to adults survival, and body weight in the cold shock selected populations and their controls under two treatments (a) post cold chock and (b) without cold shock. Twenty-four hours post cold shock, the selected population had significantly higher egg viability and mating frequency compared to control populations indicating that they have higher cold shock resistance. Selected populations had significantly longer pre-adult development time compared to their control populations. Females from the selected populations had higher body weight compared to their control populations. However, we did not find any significant difference between the selected and control populations in longevity, lifetime fecundity, adult mortality, larvae to adults survival, and male body weight under the cold chock or no cold shock treatments. CONCLUSIONS: These findings suggest that cold shock selected populations have evolved higher mating frequency and egg viability. However, there is no apparent life-history associated cost with the evolution of egg viability and reproductive performances under the cold stress condition.

Urinary Stress Hormones, Hypertension, and Cardiovascular Events: The Multi-Ethnic Study of Atherosclerosis.

[Figure: see text].

Mechanism of morphine addiction by inhibiting the soluble Guanylate Cyclase-Nitric Oxide (sGC-NO) pathway.

Ample evidence has shown that morphine influences learning and memory and thereby causing addiction. Various studies have shown that it decreases the inhibitory GABAergic synaptic transmission (LTPGABA) via the soluble guanylate cyclase (sGC) and nitric oxide (NO) pathway. But still it is unclear on how does morphine inhibit the sGC-NO pathway. In this study, we show the mechanism of LTPGABA inhibition by morphine with the help of a mathematical model. A two step model of sGC activation is used, where morphine inhibits NO during the first step and consequently blocks sGC activation. Here, morphine binding on µ-opioid receptors blocks the binding of retrogradely travelling NO to sGC and hence its activation. As a result, LTPGABA is not produced which increases the chances of addiction manifold. Alongwith the mechanism, the dependence of morphine inhibition on major parameters such as morphine dissociation, morphine concentration, NO removal & rate of inhibition and its effect on addiction is also shown.