Notes

Impact involving Nutritional Sea Decline for the Growth and development of Obesity and design Only two Diabetes mellitus within db/db Rodents.
and D. Alfandari was supported by grants from the USPHS (RO1DE016289 and R24OD021485).
UMass Faculty Fund (A Lover); UMass Faculty Discretionary Funds (N Reich); UMass Institute for Applied Life Science "Midigrant" (#169076; A. Lover); and D. Alfandari was supported by grants from the USPHS (RO1DE016289 and R24OD021485).
Characterizing the kinetics of the antibody response to SARS□CoV□2 is of critical importance to developing strategies that may mitigate the public health burden of COVID-19. We sought to determine how circulating antibody levels change over time following natural infection.

We conducted a prospective, longitudinal analysis of COVID-19 convalescent plasma (CCP) donors at multiple time points over a 9-month period. At each study visit, subjects either donated plasma or only had study samples drawn. In all cases, anti-SARS-CoV-2 donor testing was performed using semi-quantitative chemiluminescent immunoassays (ChLIA) targeting subunit 1 (S1) of the SARS-CoV-2 spike (S) protein, and an in-house fluorescence reduction neutralization assay (FRNA).

From April to November 2020 we enrolled 202 donors, mean age 47.3 ±14.7 years, 55% female, 75% Caucasian. Most donors reported a mild clinical course (91%, n=171) without hospitalization. One hundred and five (105) (52%) donors presented for repeat visits with a medss demographics, with the exception of age, BMI and clinical severity.
COVID-19 symptoms are increasingly recognized to persist among a subset of individual following acute infection, but features associated with this persistence are not well-understood.

We aimed to identify individual features that predicted persistence of symptoms over at least 2 months at the time of survey completion.Design Non-probability internet survey. Participants were asked to identify features of acute illness as well as persistence of symptoms at time of study completion. We used logistic regression models to examine association between sociodemographic and clinical features and persistence of symptoms at or beyond 2 months.

Ten waves of a fifty-state survey between June 13, 2020 and January 13, 2021.

6,211 individuals who reported symptomatic COVID-19 illness confirmed by positive test or clinician diagnosis.

symptomatic COVID-19 illness.

Among 6,211 survey respondents reporting COVID-19 illness, with a mean age of 37.8 (SD 12.2) years and 45.1% female, 73.9% white, 10.0% Black, 9.9% Hisvelopment of targeted interventions.
As the coronavirus disease 2019 (COVID-19) pandemic continues and millions remain vulnerable to infection with severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2), attention has turned to characterizing post-acute sequelae of SARS-CoV-2 infection (PASC).

From April 21 to December 31, 2020, we assembled a cohort of consecutive volunteers who a) had documented history of SARS-CoV-2 RNA-positivity; b) were ≥ 2 weeks past onset of COVID-19 symptoms or, if asymptomatic, first test for SARS-CoV-2; and c) were able to travel to our site in San Francisco. Participants learned about the study by being identified on medical center-based registries and being notified or by responding to advertisements. At 4-month intervals, we asked participants about physical symptoms that were new or worse compared to the period prior to COVID-19, mental health symptoms and quality of life. We described 4 time periods 1) acute illness (0-3 weeks), 2) early recovery (3-10 weeks), 3) late recovery 1 (12-20 weeks), and 4) lamong a cohort of participants enrolled in the post-acute phase of SARS-CoV-2 infection, we found many with persistent physical symptoms through 8 months following onset of COVID-19 with an impact on self-rated overall health. The presence of participants with and without symptoms and ample biological specimens will facilitate study of PASC pathogenesis. Similar evaluations in a population-representative sample will be needed to estimate the population-level prevalence of PASC.
Among a cohort of participants enrolled in the post-acute phase of SARS-CoV-2 infection, we found many with persistent physical symptoms through 8 months following onset of COVID-19 with an impact on self-rated overall health. The presence of participants with and without symptoms and ample biological specimens will facilitate study of PASC pathogenesis. Similar evaluations in a population-representative sample will be needed to estimate the population-level prevalence of PASC.We analyzed the plasma levels of interferons and cytokines, and the expression of interferon-stimulated genes in peripheral blood mononuclear cells in COVID-19 patients with different disease severity. Mild patients exhibited transient type I interferon responses, while ICU patients had prolonged type I interferon responses with hyper-inflammation mediated by interferon regulatory factor 1. Type II interferon responses were compromised in ICU patients. Type III interferon responses were induced in the early phase of SARS-CoV-2 infection, even in convalescent patients. These results highlight the importance of type I and III interferon responses during the early phase of infection in controlling COVID-19 progression.Timely, high-resolution forecasts of infectious disease incidence are useful for policy makers in deciding intervention measures and estimating healthcare resource burden. In this paper, we consider the task of forecasting COVID-19 confirmed cases at the county level for the United States. Although multiple methods have been explored for this task, their performance has varied across space and time due to noisy data and the inherent dynamic nature of the pandemic. We present a forecasting pipeline which incorporates probabilistic forecasts from multiple statistical, machine learning and mechanistic methods through a Bayesian ensembling scheme, and has been operational for nearly 6 months serving local, state and federal policymakers in the United States. While showing that the Bayesian ensemble is at least as good as the individual methods, we also show that each individual method contributes significantly for different spatial regions and time points. We compare our model's performance with other similar modrence (Conference'17) . ACM, New York, NY, USA, 9 pages. https//doi.org/10.1145/nnnnnnn.nnnnnnn.
The emergence of more transmissible SARS-CoV-2 variants in the United Kingdom (B.1.1.7), South Africa (B1.351) and Brazil (P.1) requires a vigorous public health response, including real time strain surveillance on a global scale. Although new SARS-CoV-2 variants can be most accurately identified by genomic sequencing, this approach is time consuming and expensive. A simple and more rapid screen for the key SARS-CoV-2 mutations that define variant strains is needed. We developed a simple, rapid and high-throughput reverse-transcriptase PCR (RT-PCR) melting temperature assay that identifies the SARS-CoV-2 N501Y mutation, a key mutation which is present in all three known variant strains of concern.

RT-PCR primers and two sloppy molecular beacon (SMB) probes were designed to amplify and detect the SARS-CoV-2 N501Y (A23063T) mutation. One SMB was designed with a probe region that was complementary to the wild type sequence (WT) and a second SMB was designed with a probe region that was complementary to the mrning for the emergence and spread of these strains of concern.
We have developed a rapid screening test for the SARS-CoV-2 N501Y mutation, which is a characteristic of all three SARS-CoV-2 stains of global concern. This assay can be used to rapidly screen large numbers of patient samples for these variants, providing an early warning for the emergence and spread of these strains of concern.The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) is a national prospective study of adults at risk for coronavirus disease 2019 (COVID-19) comprising 14 established United States (US) prospective cohort studies. For decades, C4R cohorts have collected extensive data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health. C4R will link this pre-COVID phenotyping to information on SARS-CoV-2 infection and acute and post-acute COVID-related illness. C4R is largely population-based, has an age range of 18-108 years, and broadly reflects the racial, ethnic, socioeconomic, and geographic diversity of the US. C4R is ascertaining severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and COVID-19 illness using standardized questionnaires, ascertainment of COVID-related hospitalizations and deaths, and a SARS-CoV-2 serosurvey via dried blood spots. Master protocols leverage existing robust retention rates for telephone and in-person examinations, and high-quality events surveillance. Extensive pre-pandemic data minimize referral, survival, and recall bias. Data are being harmonized with research-quality phenotyping unmatched by clinical and survey-based studies; these will be pooled and shared widely to expedite collaboration and scientific findings. This unique resource will allow evaluation of risk and resilience factors for COVID-19 severity and outcomes, including post-acute sequelae, and assessment of the social and behavioral impact of the pandemic on long-term trajectories of health and aging.
COVID-19 Convalescent plasma (CCP) is safe and effective, particularly if given at an early stage of the disease. Our study aimed to identify an association between survival and specific antibodies found in CCP.

Patients ≥18 years of age who were hospitalized with moderate to severe COVID-19 infection and received CCP at the MD Anderson Cancer Center between 4/30/2020 and 8/20/2020 were included in the study. We quantified the levels of anti-SARS-CoV-2 antibodies, as well as antibodies against antigens of other coronavirus strains, in the CCP units and compared antibody levels with patient outcomes. For each antibody, a Bayesian exponential survival time regression model including prognostic variables was fit, and the posterior probability of a beneficial effect (PBE) of higher antibody level on survival time was computed.

CCP was administered to 44 cancer patients. The median age was 60 years (range 37-84) and 19 (43%) were female. Twelve patients (27%) died of COVID-19-related complications. Higher levels of two non-SARS-CoV-2-specific antibodies, anti-HCoV-OC43 spike IgG and anti-HCoV-HKU1 spike IgG, had PBE = 1.00, and 4 SARS-CoV-2-specific antibodies had PBEs between 0.90 and 0.95. Other factors associated with better survival were shorter time to CCP administration, younger age, and female sex.

Common cold coronavirus spike IgG antibodies anti-HCoV-OC43 and anti-HCoV-HKU1 may target a common domain for SARS-CoV-2 and other coronaviruses. They provide a promising therapeutic target for monoclonal antibody production.
Common cold coronavirus spike IgG antibodies anti-HCoV-OC43 and anti-HCoV-HKU1 may target a common domain for SARS-CoV-2 and other coronaviruses. They provide a promising therapeutic target for monoclonal antibody production.
Pregnant and lactating women were excluded from initial COVID-19 vaccine trials; thus, data to guide vaccine decision-making are lacking. We sought to evaluate the immunogenicity and reactogenicity of COVID-19 mRNA vaccination in pregnant and lactating women.

131 reproductive-age vaccine recipients (84 pregnant, 31 lactating, and 16 non-pregnant) were enrolled in a prospective cohort study at two academic medical centers. Titers of SARS-CoV-2 Spike and RBD IgG, IgA and IgM were quantified in participant sera (N=131), umbilical cord sera (N=10), and breastmilk (N=31) at baseline, 2nd vaccine dose, 2-6 weeks post 2nd vaccine, and delivery by Luminex, and confirmed by ELISA. Titers were compared to pregnant women 4-12 weeks from native infection (N=37). Post-vaccination symptoms were assessed. Laduviglusib Kruskal-Wallis tests and a mixed effects model, with correction for multiple comparisons, were used to assess differences between groups.

Vaccine-induced immune responses were equivalent in pregnant and lactating vs non-pregnant women.
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