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Objectives: The CoV2-001 phase I randomized trial evaluated the safety and immunogenicity of the GLS-5310 bi-cistronic DNA vaccine through 48 weeks of follow-up. Design: A total of 45 vaccine-naïve participants were recruited between December 31, 2020, and March 30, 2021. GLS-5310, encoding for the SARS-CoV-2 spike and open reading frame 3a (ORF3a) proteins, was administered intradermally at 0.6 mg or 1.2 mg per dose, followed by application of the GeneDerm suction device as part of a two-dose regimen spaced either 8 or 12 weeks between vaccinations. Results: GLS-5310 was well tolerated with no serious adverse events reported. Antibody and T cell responses were dose-independent. Anti-spike antibodies were induced in 95.5% of participants with an average geometric mean titer of ∼480 four weeks after vaccination and declined minimally through 48 weeks. Neutralizing antibodies were induced in 55.5% of participants with post-vaccination geometric mean titer of 28.4. T cell responses were induced in 97.8% of participants, averaging 716 site forming units/106 cells four weeks after vaccination, increasing to 1248 at week 24, and remaining greater than 1000 through 48 weeks. Conclusion: GLS-5310 administered with the GeneDerm suction device was well tolerated and induced high levels of binding antibodies and T-cell responses. Antibody responses were similar to other DNA vaccines, whereas T cell responses were many-fold greater than DNA and non-DNA vaccines.

Bivalent COVID-19 vaccines that contain BA.1 or BA.4/BA.5 have been introduced worldwide in response to pandemic waves of Omicron subvariants. This prospective cohort study was aimed to compare neutralizing antibodies (Nabs) against Omicron subvariants (BA.1, BA.5, BQ.1.1, BN.1, and XBB.1) before and 3–4 weeks after bivalent booster by the types of SARS-CoV-2 variants in prior infections and bivalent vaccine formulations. A total of 21 participants were included. Prior BA.1/BA.2-infected, and BA.5-infected participants showed significantly higher geometric mean titers of Nab compared to SARS-CoV-2-non-infected participants after bivalent booster (BA.1, 8156 vs. 4861 vs. 1636; BA.5, 6515 vs. 4861 vs. 915; BQ.1.1, 697 vs. 628 vs. 115; BN.1, 1402 vs. 1289 vs. 490; XBB.1, 434 vs. 355 vs. 144). When compared by bivalent vaccine formulations, Nab titers against studied subvariants after bivalent booster did not differ between BA.1 and BA.4/BA.5 bivalent vaccine (BA.1, 4886 vs. 5285; BA.5, 3320 vs. 4118; BQ.1.1, 311 vs. 572; BN.1, 1028 vs. 1095; XBB.1, 262 vs. 362). Both BA.1 and BA.4/BA.5 bivalent vaccines are immunogenic and provide enhanced neutralizing activities against Omicron subvariants. However, even after the bivalent booster, neutralizing activities against the later Omicron strains (BQ.1.1, BN.1, and XBB.1) would be insufficient to provide protection.

Objectives: To compare epidemiologic features of the second and third waves of the coronavirus disease 2019 (COVID-19) pandemic in South Korea. Methods: Nationwide COVID-19 data were collected between 6 May and 30 December 2020. The degree of social activity was estimated using an Internet search trend analysis program for leisure-related keywords, including ‘eating-out’, ‘trip’ and ‘get directions’ (transportation). Demographics, transmission chains, case fatality rates, social activity levels and public health responses were compared between the second (13 August–18 September 2020) and third (4 November 2020–present) waves. Results: In comparison with the second wave, the third wave was characterized by delayed strengthening of social distancing policies (3 vs. 15 days), longer duration (36 vs. >56 days) and a higher case fatality rate (0.91% vs. 1.26%). There were significant differences in transmission chains between the second and third waves (P < 0.01). In comparison with the second wave, the proportion of local clusters (24.8% vs. 45.7%) was lower in the third wave, and personal contact transmission (38.5% vs. 25.9%) and unknown routes of transmission (23.5% vs. 20.8%) were higher in the third wave. Conclusion: Early and timely interventions with strengthened social distancing policies should be implemented to suppress and control the COVID-19 pandemic effectively.

Background: Prophylactic immunization is important for human immunodeficiency virus (HIV)-infected patients; however, there are insufficient data on the burden of vaccine-preventable diseases (VPDs), vaccination rates, and factors influencing vaccination. Materials and Methods: The incidence and prevalence of VPDs in HIV-infected patients between 2006 and 2017 were estimated using the Korean HIV/acquired immune deficiency syndrome (AIDS) cohort database. In addition, we evaluated the vaccination rates and influencing factors for vaccination in HIV-infected patients through multilevel analysis of clinico-epidemiological factors, immune status, and psychological status. A questionnaire survey was conducted among experts to determine whether they recommend vaccination for HIV-infected patients. Results: The incidence rates of hepatitis B virus (HBV) infection, herpes zoster, and anogenital warts were 1.74, 7.38, and 10.85 per 1,000 person-years, respectively. The prevalence of HBV infection and anogenital warts at enrollment was 4.8% and 8.6%, respectively, which increased to 5.3% and 12.0%, respectively, by 2017. In HIV-infected patients, HBV (21.7% in 2008, 56.3% in 2013, and 75.4% in 2017) and pneumococcal vaccination rates (3.0% in 2015, 7.6% in 2016, and 9.6% in 2017) increased annually, whereas the influenza vaccination rate remained similar by season (32.7 - 35.6%). In the multilevel analysis, peak HIV viral load (≥50 copies/mL: odds ratio [OR] = 0.64, 95% confidence interval [CI]: 0.44 - 0.93; reference, <50 copies/mL) was an influencing factor for pneumococcal vaccination, while nadir CD4 T-cell counts (200 - 350 cells/mm3 : OR = 0.54, 95% CI: 0.38 - 0.76; <200 cells/mm3 : OR = 0.89, 95% CI: 0.62 - 1.28; reference, ≥350 cells/mm3 ) was an influencing factor for HBV vaccination. Influenza vaccination was associated with male sex (OR = 1.94) and the number of antiretroviral therapy (ART) regimen change (OR = 1.16), but was not significantly associated with HIV viral load or CD4 T-cell counts. Most experts responded that they administer hepatitis A virus, HBV, pneumococcal, and influenza vaccines routinely, but not human papillomavirus (12.9%) or herpes zoster vaccines (27.1%). Conclusion: The burden of vaccine-preventable diseases was quite high in HIV-infected patients. Nadir CD4 T-cell counts, peak HIV viral loads, and the number of ART regimen change are significant factors related to vaccination. Considering the low vaccination rates for VPDs, there was a discordance between experts' opinions and real clinical practice in the medical field. [ABSTRACT FROM AUTHOR]

배경 Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infects luminal cells in the gastrointestinal tract through ACE2 receptors. When SARS-CoV-2 penetrates the ACE2 receptor, which acts as the amino acid transporter, it may cause imbalances in the gut flora (microbiome). The microbiome regulates the human immune response through innate immunity and adaptive immunity. Therefore, we investigated whether the microbiome in the early stage of SARS-CoV-2 infection is associated with the prognosis of coronavirus disease-19 (COVID-19). 방법 Thirty COVID-19 patients and sixteen healthy controls participated in this two-hospital cohort study. We collected blood, stool, and clinical records on day 0 (enrollment), day 7, day 14, and 28. Patients were categorized into four groups, according to their clinical course: improvement from mild (A), im- provement from moderate (B), improvement from severe (C), or deterioration (D). 결과 When comparing the microbial patterns, there was a significant difference in beta diversity according to the clinical course (P = 0.003). During early periods, the change of beta diversity was not remarkable within the first 7 days after the symptom onset (P = 0.218). However, as time progressed, the inter- group difference became apparent at days 8-14 (P = 0.017). After the 15th day of symptom onset, the difference between groups disappeared again (P = 0.116, at days 15-28; P = 0.133, at days 29 and lat- er). With respect to the microbial composition, the groups with clinical improvement (group B and C) and control groups got closer at the convalescent stage, while group D, whose clinical course wors- ened, was still far from the control group. In group A, the intergroup distance maintained far from the control group despite the clinical improvement, which might be due to the underlying medical conditions. The microbial beta diversity was significantly distinguished by the Charlson comorbidity in- dex also (P = 0.001). 결론 In patients with COVID-19, the microbiome composition might be affected by the clinical course and comorbidities. [ABSTRACT FROM AUTHOR]

Campylobacter infection causes gastrointestinal symptoms such as abdominal pain or diarrhea. Occasionally, Campylobacter bacteremia affects immunocompromised patients; however, serious outcomes are known to be rare. Here, we present a case of a patient with Campylobacter bacteremia who had underlying liver cirrhosis. The patient had fever and diarrhea. These symptoms subsided after treatment with cefotaxime. Campylobacter jejuni was isolated in the blood culture after 10 days. In addition, previously reported cases of Campylobacter bacteremia in Asian countries were reviewed with respect to antimicrobial sensitivities. [ABSTRACT FROM AUTHOR]