Hydrogen peroxide emissions from surface cleaning in a single-family residence.

High levels of reactive chemicals may be emitted to the indoor air during household surface cleaning, leading to poorer air quality and potential health hazards. Hydrogen peroxide (H2O2)-based cleaners have gained popularity in recent years, especially in times of COVID-19. Still, little is known regarding the effects of H2O2 cleaning on indoor air composition. In this work we monitored time-resolved H2O2 concentrations during a cleaning campaign in an occupied single-family residence using a cavity ring-down spectroscopy (CRDS) H2O2 analyzer. During the cleaning experiments, we investigated how unconstrained (i.e., "real-life") surface cleaning with a hydrogen peroxide solution influenced the indoor air quality of the house, and performed controlled experiments to investigate factors that could influence H2O2 levels including surface area and surface material, ventilation, and dwell time of the cleaning solution. Mean peak H2O2 concentrations observed following all surface cleaning events were 135 ppbv. The factors with the greatest effect on H2O2 levels were distance of the cleaned surface from the detector inlet, type of surface cleaned, and solution dwell time.

Treating asthma in the time of COVID.

The Precision Interventions for Severe and/or Exacerbation-Prone Asthma clinical trials network is actively assessing novel treatments for severe asthma during the coronavirus disease (COVID-19) pandemic and has needed to adapt to various clinical dilemmas posed by the COVID-19 pandemic. Pharmacologic interactions between established asthma therapies and novel drug interventions for COVID-19 infection, including antivirals, biologics, and vaccines, have emerged as a critical and unanticipated issue in the clinical care of asthma. In particular, impaired metabolism of some long-acting beta-2 agonists by the cytochrome P4503A4 enzyme in the setting of antiviral treatment using ritonavir-boosted nirmatrelvir (NVM/r, brand name Paxlovid) may increase risk for adverse cardiovascular events. Although available data have documented the potential for such interactions, these issues are largely unappreciated by clinicians who treat asthma, or those dispensing COVID-19 interventions in patients who happen to have asthma. Because these drug-drug interactions have not previously been relevant to patient care, clinicians have had no guidance on management strategies to reduce potentially serious interactions between treatments for asthma and COVID-19. The Precision Interventions for Severe and/or Exacerbation-Prone Asthma network considered the available literature and product information, and herein share our considerations and plans for treating asthma within the context of these novel COVID-19-related therapies.

COVID-19 Mimicking Hemolysis, Elevated Liver Enzymes and Low Platelets (HELLP) Syndrome: A Case Report

Background & aim: Hemolysis, elevated liver enzymes, and low platelets syndrome (HELLP) was mimicked by several infectious conditions. It is critically important to distinguish these two, since their management and course differs, substantially. Case report: The case was a 27-year-old gravid patient with gestational age of 30 weeks who initially presented with headache and lower limb pain as well as leukopenia (and lymphopenia), normochromic normocytic anemia, thrombocytopenia, abnormal liver enzymes, increased lactate dehydrogenase enzyme and C-reactive protein. The patient was initially managed for HELLP syndrome, but due to the atypical presentation (low blood pressure and an episode of delirium when admitted), the novel coronavirus disease 2019 (COVID-19), realtime reverse transcription polymerase chain reaction (rRT-PCR) was requested for the patient that was positive. The spiral lung high-resolution computed tomography scan revealed changes compatible with COVID-19 diagnosis. Finally, the patient underwent uncomplicated normal vaginal delivery at 39th gestational week. Conclusion: It is important to consider the COVID-19 in differential diagnosis of patients suspected to HELLP syndrome, as the isolation and treatment of the patient is different and time-sensitive. © Journal of Midwifery and Reproductive Health.All rights reserved.

Bayesian quantile forecasting via the realized hysteretic GARCH model

This research introduces a new model, a realized hysteretic GARCH, that is similar to a three-regime nonlinear framework combined with daily returns and realized volatility. The setup allows the mean and volatility switching in a regime to be delayed when the hysteresis variable lies in a hysteresis zone. This nonlinear model presents explosive persistence and high volatility in Regime 1 in order to capture extreme cases. We employ the Bayesian Markov chain Monte Carlo (MCMC) procedure to estimate model parameters and to forecast volatility, value at risk (VaR), and expected shortfall (ES). A simulation study highlights the properties of the proposed MCMC methods, as well as their accuracy and satisfactory performance as quantile forecasting tools. We also consider two competing models, the realized GARCH and the realized threshold GARCH, for comparison and carry out Bayesian risk forecasting via predictive distributions on four stock markets. The out-of-sample period covers the recent 4 years by a rolling window approach and includes the COVID-19 pandemic period. Among the realized models, the realized hysteretic GARCH model outperforms at the 1% level in terms of violation rates and backtests.

Group IIA secreted phospholipase A2 is associated with the pathobiology leading to COVID-19 mortality.

There is an urgent need to identify the cellular and molecular mechanisms responsible for severe COVID-19 that results in death. We initially performed both untargeted and targeted lipidomics as well as focused biochemical analyses of 127 plasma samples and found elevated metabolites associated with secreted phospholipase A2 (sPLA2) activity and mitochondrial dysfunction in patients with severe COVID-19. Deceased COVID-19 patients had higher levels of circulating, catalytically active sPLA2 group IIA (sPLA2-IIA), with a median value that was 9.6-fold higher than that for patients with mild disease and 5.0-fold higher than the median value for survivors of severe COVID-19. Elevated sPLA2-IIA levels paralleled several indices of COVID-19 disease severity (e.g., kidney dysfunction, hypoxia, multiple organ dysfunction). A decision tree generated by machine learning identified sPLA2-IIA levels as a central node in the stratification of patients who died from COVID-19. Random forest analysis and least absolute shrinkage and selection operator-based (LASSO-based) regression analysis additionally identified sPLA2-IIA and blood urea nitrogen (BUN) as the key variables among 80 clinical indices in predicting COVID-19 mortality. The combined PLA-BUN index performed significantly better than did either one alone. An independent cohort (n = 154) confirmed higher plasma sPLA2-IIA levels in deceased patients compared with levels in plasma from patients with severe or mild COVID-19, with the PLA-BUN index-based decision tree satisfactorily stratifying patients with mild, severe, or fatal COVID-19. With clinically tested inhibitors available, this study identifies sPLA2-IIA as a therapeutic target to reduce COVID-19 mortality.

Comparative analysis of antibodies to SARS-CoV-2 between asymptomatic and convalescent patients.

The SARS-CoV-2 viral pandemic has induced a global health crisis, which requires more in-depth investigation into immunological responses to develop effective treatments and vaccines. To understand protective immunity against COVID-19, we screened over 60,000 asymptomatic individuals in the Southeastern United States for IgG antibody positivity against the viral Spike protein, and approximately 3% were positive. Of these 3%, individuals with the highest anti-S or anti-RBD IgG level showed a strong correlation with inhibition of ACE2 binding and cross-reactivity against non-SARS-CoV-2 coronavirus S-proteins. We also analyzed samples from 94 SARS-CoV-2 patients and compared them with those of asymptomatic individuals. SARS-CoV-2 symptomatic patients had decreased antibody responses, ACE2 binding inhibition, and antibody cross-reactivity. Our study shows that healthy individuals can mount robust immune responses against SARS-CoV-2 without symptoms. Furthermore, IgG antibody responses against S and RBD may correlate with high inhibition of ACE2 binding in individuals tested for SARS-CoV-2 infection or post vaccination.