Introduction Safe vaccination worldwide is critical to end the coronavirus disease 2019 (COVID-19) pandemic. We aimed to evaluate adverse reactions to vaccination using a web-based questionnaire and examine the risk factors for the occurrence of immunisation stress-related response (ISRR). Methods We conducted a questionnaire survey using Google Form® among the employees of St. Marianna University Hospital who had received the COVID-19 vaccine between April 2021 and May 2021, 1 week after the first and second vaccinations. We developed and used a questionnaire to identify individuals with ISRR according to the World Health Organization diagnostic criteria. A generalised linear mixed model was constructed with ISRR onset as the dependent variable, subjects as the random factor, and each parameter as a fixed factor. A multivariate model was constructed using the forced imputation method with factors that were significant in the univariate analysis. Results We enrolled 2,073 and 1,856 respondents in the first and second questionnaire surveys, respectively. Fifty-five and 33 ISRR cases were identified in the first and second vaccinations, respectively. In the univariate analysis, strong pre-vaccination anxiety (odds ratio [OR], 2.3; 95% confidence interval [CI], 1.30–4.12, p = 0·004) and history of allergy (OR, 1.6; 95% CI, 1.14–2.24, p = 0·007) were significant risk factors. Multivariate analysis also showed that strong pre-vaccination anxiety (OR, 2.1; 95% CI, 1.15–3.80, p = 0.016) and history of allergy (OR, 1.5; 95% CI, 1.09–2.15, p = 0.014) were significant risk factors. Conclusions Confirmation of allergy prior to vaccination and subsequent action are essential for addressing ISRR.

of FDE assisted in the safe continuation of PD-1i. Besides autoimmune skin blistering disorders, worsening of FDE can also be a differential diagnosis in patients with bulla formation.

Antifungal agents are not always efficient in resolving vulvovaginal candidiasis (VVC), a common genital infection caused by overgrowth of Candida spp., including Candida albicans, or preventing recurrent infections. Although lactobacilli (which are dominant microorganisms constituting healthy human vaginal microbiota) are important barriers against VVC, the Lactobacillus metabolite concentration needed to suppress VVC is unknown. Therefore, we quantitatively evaluated Lactobacillus metabolite concentrations to determine their effect on Candida spp., including 27 vaginal strains of Lactobacillus crispatus, Lactobacillus jensenii, Lactobacillus gasseri, Lacticaseibacillus rhamnosus, and Limosilactobacillus vaginalis, with inhibitory abilities against biofilms of Candida clinical isolates. Lactobacillus culture supernatants suppressed viable bacteria by approximately 24%-92% relative to preformed Candida biofilms, but their suppression differed between strains, not species. Lactate production was necessary to suppress preformed biofilms and hyphal elongation of C. albicans, whereas hydrogen peroxide was not always essential. Both lactic acid and hydrogen peroxide were required to suppress Candida planktonic cell growth. Lactobacillus strains that significantly inhibited biofilm formation in culture supernatant also inhibited Candida adhesion to epithelial cells in an actual live bacterial adhesion competition test. Healthy human microflora and their metabolites may play important roles in the development of new antifungal agent against VVC caused by C. albicans.

Presently, coronavirus disease-19 (COVID-19) is spreading worldwide without an effective treatment method. For COVID-19, which is often asymptomatic, it is essential to adopt a method that does not cause aggravation, as well as a method to prevent infection. Whether aggravation can be predicted by analyzing the extent of lung damage on chest computed tomography (CT) scans was examined. The extent of lung damage on pre-intubation chest CT scans of 277 patients with COVID-19 was assessed. It was observed that aggravation occurred when the CT scan showed extensive damage associated with ground-glass opacification and/or consolidation (p < 0.0001). The extent of lung damage was similar across the upper, middle, and lower fields. Furthermore, upon comparing the extent of lung damage based on the number of days after onset, a significant difference was found between the severe pneumonia group (SPG) with intubation or those who died and non-severe pneumonia group (NSPG) ≥3 days after onset, with aggravation observed when ≥14.5% of the lungs exhibited damage at 3–5 days (sensitivity: 88.2%, specificity: 72.4%) and when ≥20.1% of the lungs exhibited damage at 6–8 days (sensitivity: 88.2%, specificity: 69.4%). Patients with aggravation suddenly developed hypoxemia after 7 days from the onset; however, chest CT scans obtained in the paucisymptomatic phase without hypoxemia indicated that subsequent aggravation could be predicted based on the degree of lung damage. Furthermore, in subjects aged ≥65 years, a significant difference between the SPG and NSPG was observed in the extent of lung damage early beginning from 3 days after onset, and it was found that the degree of lung damage could serve as a predictor of aggravation. Therefore, to predict and improve prognosis through rapid and appropriate management, evaluating patients with factors indicating poor prognosis using chest CT is essential.

Nucleic-acid amplification test (NAT), routinely used for diagnosing coronavirus disease 2019 , is associated with false negative results. Alternatively, serological tests detect antibodies produced against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19. Here, we evaluated the diagnostic accuracy of a single quantum dot immunoassay and three lateral flow immunoassays for COVID-19. We also assessed differences in the antibody positivity rates between patients receiving and not receiving ventilator support and between those treated and not treated with antiviral agents and/or corticosteroids. Test accuracy was estimated by measuring the sensitivity and specificity using receiver operating characteristic curves, along with NAT; sensitivity of NAT was 68.0% (95% confidence interval [CI]: 46.5-85.1%). IgM and IgG serological test sensitivities varied from 20.0% (95% CI: 6.83-40.7%) to 100% (95% CI: 86.3-100%) and from 84% (95% CI: 63.9-95.5%) to 100% (95% CI: 86.3-100%), respectively. The nucleocapsid protein-based serological test sensitivity was up to 100% for IgM and IgG. Serological test positivity rates were higher in patients receiving ventilator support and treatment than in patients not receiving ventilator support and treatment; the positivity rates were significantly higher for IgM than for IgG with the quantum dot immunoassay (Mokobio Biotechnology; 58.3% vs. 15.5%, P<0.05) and one of the lateral flow immunoassays (Kurabo: 83.3% vs. 30.8%, P<0.05). Thus, accuracy of serological tests varied depending on the test kit used; nonetheless, some serological test kits might be helpful as a complementary tool in COVID-19 diagnosis. And quantitative assessment of IgM levels may be useful in predicting the severity of the disease and in determining the course of treatment.