COVID-19 in People with Diabetes: Urgently Needed Lessons from Early Reports

Epidemic infections have frightened and harmed people for millennia. Plague and typhus, bacterial infections associated with poor sanitation and high mortality, have devastated populations. Both still reappear intermittently, but they are generally contained with better sanitation and control of rodent and insect vectors along with antibiotics. In contrast, viral epidemics persist. A unique strain of influenza caused a global epidemic (pandemic) in 1918 resulting in millions of deaths. Among recent outbreaks of viral infections, several have been caused by coronaviruses. One of these, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is now causing a pandemic illness termed coronavirus disease 2019 (COVID-19) that poses unique challenges. This novel coronavirus is readily transmitted from person-to-person, even by thosewho are infected but without symptoms. In susceptible people it causes severe illness and often death from pulmonary and systemic injuries. At present, we have neither a preventive vaccine nor well-studied pharmacotherapy, although work to develop these is vigorously underway

Study of a Depolarizing Resonance at the IUCF Cooler Ring

This research was sponsored by the National Science Foundation Grant NSF PHY-931478

Green function techniques in the treatment of quantum transport at the molecular scale

The theoretical investigation of charge (and spin) transport at nanometer length scales requires the use of advanced and powerful techniques able to deal with the dynamical properties of the relevant physical systems, to explicitly include out-of-equilibrium situations typical for electrical/heat transport as well as to take into account interaction effects in a systematic way. Equilibrium Green function techniques and their extension to non-equilibrium situations via the Keldysh formalism build one of the pillars of current state-of-the-art approaches to quantum transport which have been implemented in both model Hamiltonian formulations and first-principle methodologies. We offer a tutorial overview of the applications of Green functions to deal with some fundamental aspects of charge transport at the nanoscale, mainly focusing on applications to model Hamiltonian formulations.Comment: Tutorial review, LaTeX, 129 pages, 41 figures, 300 references, submitted to Springer series "Lecture Notes in Physics

A 24-week, multicenter, open-label, randomized study to compare changes in glucose metabolism in patients with schizophrenia receiving treatment with olanzapine, quetiapine, or risperidone

Objective: This randomized, 24-week, flexible-dose study compared changes in glucose metabolism in patients with DSM-IV schizophrenia receiving initial exposure to olanzapine, quetiapine, or risperidone. Method: The hypothesized primary endpoint was change (baseline to week 24) in area under the curve (AUC) 0- to 2-hour plasma glucose values during an oral glucose tolerance test (OGTT); primary analysis: olanzapine versus quetiapine. Secondary endpoints included mean change in AUC 0- to 2-hour plasma insulin values, insulin sensitivity index, and fasting lipids. The first patient enrolled on April 29, 2004, and the last patient completed the study on October 24, 2005. Results: Mean weight change (kg) over 24 weeks was +3.7 (quetiapine), +4.6 (olanzapine), and +3.6 (risperidone). Based on data from 395 patients (quetiapine, N = 115 [mean dose = 607.0 mg/day], olanzapine, N = 146 [mean dose = 15.2 mg/day], and risperidone, N = 134 [mean dose = 5.2 mg/day]), mean change in AUC 0- to 2-hour glucose value (mg/dL x h) at week 24 was significantly lower for quetiapine versus olanzapine (t = 1.98, df = 377, p = .048). Increases in AUC 0- to 2-hour glucose values were statistically significant with olanzapine (+21.9 mg/dL x h, 95% CI = 11.5 to 32.4 mg/dL x h) and risperidone (+18.8 mg/dL x h, 95% CI = 8.1 to 29.4 mg/dL x h), but not quetiapine (+9.1 mg/dL x h, 95% CI = -2.3 to 20.5 mg/dL x h). AUC 0- to 2-hour insulin values increased statistically significantly with olanzapine (+24.5%, 95% CI = 11.5% to 39.0%), but not with quetiapine or risperidone. Reductions in insulin sensitivity index were statistically significant with olanzapine (-19.1%, 95% CI = -27.9% to -9.3%) and risperidone (-15.8%, 95% CI = -25.1% to -5.4%), but not quetiapine. Total cholesterol and low-density lipoprotein levels increased statistically significantly with olanzapine (+21.1 mg/dL, 95% CI = 13.0 to 29.2 mg/dL, and +20.5 mg/dL, 95% CI = 13.8 to 27.1 mg/dL, respectively) and quetiapine (+13.1 mg/dL, 95% CI = 4.3 to 21.9 mg/dL, and +13.3 mg/dL, 95% CI = 6.1 to 20.5 mg/dL, respectively), but not risperidone. Statistically significant increases in triglycerides (+30.9 mg/dL, 95% CI = 10.9 to 51.0 mg/dL), total cholesterol/high-density lipoprotein (HDL) ratio (0.5, 95% CI = 0.2 to 0.8), and triglyceride/HDL ratio (0.3, 95% CI = 0.0 to 0.6) were observed with olanzapine only. Conclusion: The results indicate a significant difference in the change in glucose tolerance during 6 months' treatment with olanzapine versus quetiapine, with significant reductions on olanzapine and risperidone, but not quetiapine; these differential changes were largely explained by changes in insulin sensitivity. Trial Registration: clinicaltrials.gov Identifier: NCT00214578. © Copyright 2009 Physicians Postgraduate Press, Inc.Articl

Staging presymptomatic type 1 diabetes: A scientific statement of JDRF, the Endocrine Society, and the American Diabetes Association.

Insights from prospective, longitudinal studies of individuals at risk for developing type 1 diabetes have demonstrated that the disease is a continuum that progresses sequentially at variable but predictable rates through distinct identifiable stages prior to the onset of symptoms. Stage 1 is defined as the presence of β-cell autoimmunity as evidenced by the presence of two or more islet autoantibodies with normoglycemia and is presymptomatic, stage 2 as the presence of β-cell autoimmunity with dysglycemia and is presymptomatic, and stage 3 as onset of symptomatic disease. Adoption of this staging classification provides a standardized taxonomy for type 1 diabetes and will aid the development of therapies and the design of clinical trials to prevent symptomatic disease, promote precision medicine, and provide a framework for an optimized benefit/risk ratio that will impact regulatory approval, reimbursement, and adoption of interventions in the early stages of type 1 diabetes to prevent symptomatic disease