Semi-parametric modeling of SARS-CoV-2 transmission in Orange County, California using tests, cases, deaths, and seroprevalence data

Mechanistic modeling of SARS-CoV-2 transmission dynamics and frequently estimating model parameters using streaming surveillance data are important components of the pandemic response toolbox. However, transmission model parameter estimation can be imprecise, and sometimes even impossible, because surveillance data are noisy and not informative about all aspects of the mechanistic model. To partially overcome this obstacle, we propose a Bayesian modeling framework that integrates multiple surveillance data streams. Our model uses both SARS-CoV-2 diagnostics test and mortality time series to estimate our model parameters, while also explicitly integrating seroprevalence data from cross-sectional studies. Importantly, our data generating model for incidence data takes into account changes in the total number of tests performed. We model transmission rate, infection-to-fatality ratio, and a parameter controlling a functional relationship between the true case incidence and the fraction of positive tests as time-varying quantities and estimate changes of these parameters nonparameterically. We apply our Bayesian data integration method to COVID-19 surveillance data collected in Orange County, California between March, 2020 and March, 2021 and find that 33-62% of the Orange County residents experienced SARS-CoV-2 infection by the end of February, 2021. Despite this high number of infections, our results show that the abrupt end of the winter surge in January, 2021, was due to both behavioral changes and a high level of accumulated natural immunity.Comment: 37 pages, 16 pages of main text, including 5 figures, 1 tabl

Domino Mukaiyama-Michael reactions in the synthesis of polycyclic systems

Good results were obtained in the Mukaiyama-Michael reaction of the silyl enol ether of cyclohexanone with 2-methyl-2cyclopentenone and carvone, with transfer of the silyl group to the receiving enone and with TrSbCl6 as catalyst. A second Mukaiyama-Michael reaction of this new silyl enol ether with methyl vinyl ketone and cyclization of the resulting adduct leads to tricyclic compounds in one-pot domino sequences. The scope and limitations of this domino reaction have been investigated

Domino Mukaiyama-Michael reactions in the synthesis of polycyclic systems

Good results were obtained in the Mukaiyama-Michael reaction of the silyl enol ether of cyclohexanone with 2-methyl-2cyclopentenone and carvone, with transfer of the silyl group to the receiving enone and with TrSbCl6 as catalyst. A second Mukaiyama-Michael reaction of this new silyl enol ether with methyl vinyl ketone and cyclization of the resulting adduct leads to tricyclic compounds in one-pot domino sequences. The scope and limitations of this domino reaction have been investigated

A new approach toward the synthesis of C,D-cis coupled steroid and C,D-cis coupled D-homosteroid skeletons

A short and efficient procedure has been developed for the synthesis of C,D-cis coupled steroid and D-homo steroid skeletons. A Mukaiyama reaction with transfer of the silyl group of the starting silyl enol ether to the enol of the adduct followed by addition of vinyl magnesium bromide to the unprotected carbonyl group leads to adducts which can be cyclized with ZnBr2. The synthesis of functionalized steroid skeletons in overall yields of about 50% in four steps can be achieved in this way. (C) 2003 Elsevier Science Ltd. All rights reserved

Heterotopic pancreas: gastric outlet obstruction secondary to pancreatitis and pancreatic pseudocyst

Heterotopic pancreas, usually a silent gastrointestinal anomaly, may become clinically evident when complicated by a pathologic process. We report a unique case in which pancreatitis and pseudocyst formation in an antral lesion produced gastric outlet obstruction. The nature of heterotopic pancreas, its diagnosis, and management are discussed

Molecular Genetic Identification of a Mexican Onza Speciment as a Puma (Puma concolor)

Tissue samples from an alleged Mexican Onza, shot in the western Sierra Madre in 1986, were subjected to several biochemical assays in an attempt to determine the specimen\u27s relationship to felid species of North America. Protein analyses included isoenzyme electrophoresis and albumin isoelectric focusing. Mitochondrial DNA was assayed for restriction fragment lengths with 28 restriction enzymes, and the ND5 gene was sequences. The resulting protein and mitochondrial DNA characteristics of the Onza were indistinguishable from those of North American pumas

The Importance of Offering Exome or Genome Sequencing in Adult Neuromuscular Clinics

Advances in gene-specific therapeutics for patients with neuromuscular disorders (NMDs) have brought increased attention to the importance of genetic diagnosis. Genetic testing practices vary among adult neuromuscular clinics, with multi-gene panel testing currently being the most common approach; follow-up testing using broad-based methods, such as exome or genome sequencing, is less consistently offered. Here, we use five case examples to illustrate the unique ability of broad-based testing to improve diagnostic yield, resulting in identification of SORD-neuropathy, HADHB-related disease, ATXN2-ALS, MECP2 related progressive gait decline and spasticity, and DNMT1-related cerebellar ataxia, deafness, narcolepsy, and hereditary sensory neuropathy type 1E. We describe in each case the technological advantages that enabled identification of the causal gene, and the resultant clinical and personal implications for the patient, demonstrating the importance of offering exome or genome sequencing to adults with NMDs

Semi-parametric modeling of SARS-CoV-2 transmission in Orange County, California using tests, cases, deaths, and seroprevalence data.

Mechanistic modeling of SARS-CoV-2 transmission dynamics and frequently estimating model parameters using streaming surveillance data are important components of the pandemic response toolbox. However, transmission model parameter estimation can be imprecise, and sometimes even impossible, because surveillance data are noisy and not informative about all aspects of the mechanistic model. To partially overcome this obstacle, we propose a Bayesian modeling framework that integrates multiple surveillance data streams. Our model uses both SARS-CoV-2 diagnostics test and mortality time series to estimate our model parameters, while also explicitly integrating seroprevalence data from cross-sectional studies. Importantly, our data generating model for incidence data takes into account changes in the total number of tests performed. We model transmission rate, infection-to-fatality ratio, and a parameter controlling a functional relationship between the true case incidence and the fraction of positive tests as time-varying quantities and estimate changes of these parameters nonparameterically. We apply our Bayesian data integration method to COVID-19 surveillance data collected in Orange County, California between March, 2020 and March, 2021 and find that 33-62% of the Orange County residents experienced SARS-CoV-2 infection by the end of February, 2021. Despite this high number of infections, our results show that the abrupt end of the winter surge in January, 2021, was due to both behavioral changes and a high level of accumulated natural immunity