T cell responses to SARS‐CoV‐2 Omicron spike epitopes with mutations after the third booster dose of an inactivated vaccine

alexandrossfakianakis shared this article with you from Inoreader T cell responses to SARS‐CoV‐2 Omicron spike epitopes with mutations after the third booster dose of an inactivated vaccine Via Journal of Medical Virology Abstract The rapidly spreading SARS-CoV-2 Omicron variant contains more than 30 mutations that mediate escape from antibody responses elicited by prior infection or current vaccines. Fortunately, T cell responses are highly conserved in most individuals, but the impacts of mutations are not clear. Here, we showed that the T cell responses of individuals who underwent booster vaccination with CoronaVac were largely protective against the SARS-CoV-2 Omicron spike protein. To specifically estimate the impact of Omicron mutations on vaccinated participants, 16 peptides derived from the spike protein of the ancestral virus or Omicron strain with mutations were used to stimulate peripheral blood mononuclear cells (PBMCs) from the volunteers. Compared with the administration of two doses of vaccine, booster vaccination substantially enhanced T cell activation in response to both the ancestral and Omicron epitopes, although the enhancement was slightly weakened by the Omicro n mutations. Then, the peptides derived from these spike proteins were used separately to stimulate PBMCs. Interestingly, compared with the ancestral peptides, only the peptides with the G339D or N440K mutation were detected to significantly destabilize the T cell response. Although more participants need to be evaluated to confirm this conclusion, our study nonetheless estimates the impacts of mutations on T cell responses to the SARS-CoV-2 Omicron variant. This article is protected by copyright. All rights reserved. View on the web Inoreader. Take back control of your news feed. Follow us on Twitter and Facebook.

Low Body Mass Index at Treatment Initiation and Rifampicin-Resistant Tuberculosis Treatment Outcomes: An Individual Participant Data Meta-Analysis

alexandrossfakianakis shared this article with you from Inoreader Low Body Mass Index at Treatment Initiation and Rifampicin-Resistant Tuberculosis Treatment Outcomes: An Individual Participant Data Meta-Analysis Via Clinical Infectious Diseases Advance Access Abstract Background The impact of low body-mass-index at treatment initiation on rifampicin-resistant tuberculosis treatment outcomes is uncertain. We evaluated the association between body-mass-index at rifampicin-resistant tuberculosis treatment initiation and end-of-treatment outcomes, and its modifying factors. Methods We did an individual participant data meta-analysis of adults ≥18 years with rifampicin-resistant tuberculosis whose body-mass-index was documented at treatment initiation. We compared odds of any unfavorable treatment outcome, mortality, or failure/recurrence between patients who were underweight (body-mass-index <18.5 kg/m2) and not underweight. Adjusted odds ratios and 95%CI were estimated using logistic regression, with matching on demographic, clinical, and treatment-related factors. We evaluated effect modification by HIV-infection and other variables using likelihood ratio tests. In secondary an alysis, we estimated cumulative incidence of mortality during treatment, stratified by HIV-infection. Results Overall, 5148 patients were included; 1702 (33%) were underweight at treatment initiation. The median (IQR) age was 37 years (29 to 47) and 455 (9%) were living with HIV. Compared to non-underweight patients, the adjusted odds ratio among underweight patients was 1.7 (95%CI 1.4-1.9) for any unfavorable outcome, 3.1 (2.4-3.9) for death, and 1.6 (1.2-2.0) for failure/recurrence. Significant effect modification was observed for WHO region where the participant was treated. Among patients without HIV, cumulative incidence of 24-month mortality 14.8% (95%CI 12.7%-17.3%) for underweight and 5.6% (4.5%-7.0%) for not underweight patients. Among patients living with HIV, corresponding values were 33.0% (25.6%-42.6%) and 20.9% (14.1%-27.6%). Conclusions Low body-mass-index at treatment initiation for rifampicin-resistant tuberculosis is associated with increased odds of unfavorable treatment outcome, particularly mortality. View on the web Inoreader. Take back control of your news feed. Follow us on Twitter and Facebook.

Usability Experience of a Personal Sleep Monitoring Device to Self-manage Sleep Among Persons 65 Years or Older With Self-reported Sleep Disturbances

alexandrossfakianakis shared this article with you from Inoreader Usability Experience of a Personal Sleep Monitoring Device to Self-manage Sleep Among Persons 65 Years or Older With Self-reported Sleep Disturbances Via Computers Informatics Nursing - Published Ahead-of-Print Increasingly, persons with self-reported health symptoms are using mobile health technologies to better understand, validate, and manage their symptoms. These off-the-shelf devices primarily utilize actigraphy to estimate sleep and activity. The purpose of this study was to describe qualitatively the experience of using a personal sleep monitoring device for sleep self-management in adults 65 years or older with self-reported sleep disturbances. This study followed a hybrid qualitative design using deductive and emergent coding derived from open-ended interviews (n = 25) after a period of 4 weeks using a wearable personal sleep monitoring device. Results expanded existing theoretical models on usability with the theme of personal meaning in the interaction between health and self-monitoring technology that were associated with age and technology use, privacy, and capability. Future studies for sleep health self-management and personally tailored interventions using personal sleep monitoring devices should continue to collect qualitative information in extending the understanding of user experience across different symptom clusters, such as sleep disturbances, that manifest more commonly in older age populations. This research is important for application in the use of mobile health technologies for nursing led health self-management interventions. View on the web Inoreader. Take back control of your news feed. Follow us on Twitter and Facebook.