Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Synthesis of mimics of pramanicin from pyroglutamic acid and their antibacterial activity

10.1021/jo502810bJournal of Organic Chemistry8052661-267

Synthesis of Mimics of Pramanicin from Pyroglutamic Acid and Their Antibacterial Activity

Epoxypyrrolidinones are available by epoxidation of carboxamide-activated bicyclic lactam substrates derived from pyroglutamate using aqueous hydrogen peroxide and tertiary amine catalysis. In the case of an activating Weinreb carboxamide, further chemoselective elaboration leads to the efficient formation of libraries of epoxyketones. Deprotection may be achieved under acidic conditions to give epoxypyroglutaminols, although the ease of this process can be ameliorated by the presence of internal hydrogen bonding. Bioassay against <i>S. aureus</i> and <i>E. coli</i> indicated that some compounds exhibit antibacterial activity. These libraries may be considered to be structural mimics of the natural products pramanicin and epolactaene. More generally, this outcome suggests that interrogation of bioactive natural products is likely to permit the identification of “privileged” structural scaffolds, providing frameworks suitable for optimization in a short series of chemical steps that may accelerate the discovery of new antibiotic chemotypes. Further optimization of such systems may permit the rapid identification of novel systems suitable for antibacterial drug development

Analysis of spinal and muscle pathology in transgenic mice overexpressing wild-type and ALS-linked mutant MATR3

Abstract Mutations in MATR3 have been associated with amyotrophic lateral sclerosis (ALS) as well as a form of distal myopathy termed vocal cord pharyngeal distal myopathy (VCPDM). To begin to understand how mutations in MATR3 may cause disease, here we provide initial characterization of transgenic (Tg) mice expressing human wild-type (WT) MATR3 (MATR3WT) and ALS-mutant F115C MATR3 (MATR3F115C) proteins under the control of the mouse prion promoter (MoPrP). For each construct, we established multiple independent lines of mice that stably transmitted the transgene. Unexpectedly, for all stably-transmitting lines examined, MATR3 transgenic mRNA expression was more robust in muscle, with minimal expression in spinal cord. The levels of transgenic mRNA in muscle did not differ between mice from our lead MATR3F115C line and lead MATR3WT line, but mice from the lead MATR3F115C line had significantly higher levels of MATR3 protein in muscle over the lead MATR3WT line. Mice from the three independent, established lines of MATR3F115C mice developed weakness in both fore- and hind-limbs as early as  20 months were not overtly distinguishable from non-transgenic (NT) littermates based on basic motor phenotype. Muscle of both MATR3WT and MATR3F115C mice showed vacuoles by 2 months of age which worsened by ~ 10 months, but vacuolation was noticeably more severe in MATR3F115C mice. Overall, our results indicate that increasing the levels of MATR3 in muscle can cause pathologic changes associated with myopathy, with MATR3F115C expression causing overt muscle atrophy and a profound motor phenotype. The findings suggest that analysis of muscle pathology in individuals harboring ALS-linked MATR3 mutations should be routinely considered

Retraction Note: Transgenic mice overexpressing the ALS-linked protein Matrin 3 develop a profound muscle phenotype

Abstract The authors are retracting this article. The article describes mice expressing wild-type human MATR3. However, since publication the authors have become aware that all of the lines of mice described express human MATR3 containing the F115C mutation. Transgenic mice expressing wild-type and mutant Matrin were created simultaneously in their laboratory and, at a crucial stage of generating the DNA for embryo injection, as confirmed by an investigation by the University of Florida, the DNA preparations were accidentally mislabelled. All of the founders created were mosaic, requiring extensive breeding to isolate stable lines. Mice mislabelled as expressing wild-type MATR3 were the first to produce lines that stably transmitted the transgene and thus were the first to be characterized. However, as lines of mice that were mislabelled as expressing the mutant (F115C) MATR3 were ultimately established, the data began to suggest that an error had been made. Sequence analysis of amplified tail DNA from mice descended from the lines reported in the article have revealed that they express the F115C variant. The data described are therefore an accurate description of the pathology of mice that express the F115C variant of MATR3, but not of mice expressing wild-type MATR3. The authors are preparing a new manuscript reporting data from both mice expressing the F115C variant of MATR3 and mice expressing wild-type MATR3

Synthesis of 3-acyltetramates by side chain manipulation and their antibacterial activity

10.1039/c4ob00095aOrganic and Biomolecular Chemistry12111711-1716OBCR

Global neuropathologic severity of Alzheimer’s disease and locus coeruleus vulnerability influences plasma phosphorylated tau levels

Abstract Background Advances in ultrasensitive detection of phosphorylated tau (p-tau) in plasma has enabled the use of blood tests to measure Alzheimer’s disease (AD) biomarker changes. Examination of postmortem brains of participants with antemortem plasma p-tau levels remains critical to understanding comorbid and AD-specific contribution to these biomarker changes. Methods We analyzed 35 population-based Mayo Clinic Study of Aging participants with plasma p-tau at threonine 181 and threonine 217 (p-tau181, p-tau217) available within 3 years of death. Autopsied participants included cognitively unimpaired, mild cognitive impairment, AD dementia, and non-AD neurodegenerative disorders. Global neuropathologic scales of tau, amyloid-β, TDP-43, and cerebrovascular disease were examined. Regional digital pathology measures of tau (phosphorylated threonine 181 and 217 [pT181, pT217]) and amyloid-β (6F/3D) were quantified in hippocampus and parietal cortex. Neurotransmitter hubs reported to influence development of tangles (nucleus basalis of Meynert) and amyloid-β plaques (locus coeruleus) were evaluated. Results The strongest regional associations were with parietal cortex for tau burden (p-tau181 R = 0.55, p = 0.003; p-tau217 R = 0.66, p < 0.001) and amyloid-β burden (p-tau181 R = 0.59, p < 0.001; p-tau217 R = 0.71, p < 0.001). Linear regression analysis of global neuropathologic scales explained 31% of variability in plasma p-tau181 (Adj. R2 = 0.31) and 59% in plasma p-tau217 (Adj. R2 = 0.59). Neither TDP-43 nor cerebrovascular disease global scales independently contributed to variability. Global scales of tau pathology (β-coefficient = 0.060, p = 0.016) and amyloid-β pathology (β-coefficient = 0.080, p < 0.001) independently predicted plasma p-tau217 when modeled together with co-pathologies, but only amyloid-β (β-coefficient = 0.33, p = 0.021) significantly predicted plasma p-tau181. While nucleus basalis of Meynert neuron count/mm2 was not associated with plasma p-tau levels, a lower locus coeruleus neuron count/mm2 was associated with higher plasma p-tau181 (R = -0.50, p = 0.007) and higher plasma p-tau217 (R = -0.55, p = 0.002). Cognitive scores (Adj. R2 = 0.25–0.32) were predicted by the global tau scale, but not by the global amyloid-β scale or plasma p-tau when modeled simultaneously. Conclusions Higher soluble plasma p-tau levels may be the result of an intersection between insoluble deposits of amyloid-β and tau accumulation in brain, and may be associated with locus coeruleus degeneration