Background: We evaluated severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2)-specific humoral and cellular responses for up to 6 months after the 3rd dose of ancestral coronavirus disease 2019 (COVID-19) vaccination in people living with HIV (PLWH) and healthy controls (HCs) who were not infected with COVID-19. Methods: Anti-spike receptor-binding domain IgG (anti-RBD IgG) concentrations using chemiluminescence immunoassay and neutralizing antibodies using focus reduction neutralization test (FRNT) were assessed at 1 week after each dose of vaccination, and 3 and 6 months after the 3rd dose in 62 PLWH and 25 HCs. T-cell responses using intracellular cytokine stain were evaluated at 1 week before, and 1 week and 6 months after the 3rd dose. Results: At 1 week after the 3rd dose, adequate anti-RBD IgG (> 300 binding antibody unit /mL) was elicited in all PLWH except for one patient with 36 CD4 T-cell count/mm3 . The geometric mean titers of 50% FRNT against wild type (WT) and omicron BA.5 strains of SARS-CoV-2 in PLWH with CD4 T-cell count ≥ 500 cells/mm3(high CD4 recovery, HCDR) were comparable to HC, but they were significantly decreased in PLWH with CD4 T-cell count < 500/mm3 (low CD4 recovery, LCDR). After adjusting for age, gender, viral suppression, and number of preexisting comorbidities, CD4 T-cell counts < 500/mm3 significantly predicted a poor magnitude of neutralizing antibodies against WT, omicron BA.5, and XBB 1.5 strains among PLWH. Multivariable linear regression adjusting for age and gender revealed that LCDR was associated with reduced neutralizing activity (P = 0.017) and interferon-γ-producing T-cell responses (P = 0.049 for CD T-cell; P = 0.014 for CD8 T-cell) against WT, and strongly associated with more decreased cross-neutralization against omicron BA.5 strains (P < 0.001). Conclusion HCDR demonstrated robust humoral and cell-mediated immune responses after a booster dose of ancestral SARS-CoV-2 vaccine, whereas LCDR showed diminished immune responses against WT virus and more impaired cross-neutralization against omicron BA.5 strain.

Background: We evaluated severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2)-specific humoral and cellular responses for up to 6 months after the 3rd dose of ancestral coronavirus disease 2019 (COVID-19) vaccination in people living with HIV (PLWH) and healthy controls (HCs) who were not infected with COVID-19. Methods: Anti-spike receptor-binding domain IgG (anti-RBD IgG) concentrations using chemiluminescence immunoassay and neutralizing antibodies using focus reduction neutralization test (FRNT) were assessed at 1 week after each dose of vaccination, and 3 and 6 months after the 3rd dose in 62 PLWH and 25 HCs. T-cell responses using intracellular cytokine stain were evaluated at 1 week before, and 1 week and 6 months after the 3rd dose. Results: At 1 week after the 3rd dose, adequate anti-RBD IgG (> 300 binding antibody unit /mL) was elicited in all PLWH except for one patient with 36 CD4 T-cell count/mm3 . The geometric mean titers of 50% FRNT against wild type (WT) and omicron BA.5 strains of SARS-CoV-2 in PLWH with CD4 T-cell count ≥ 500 cells/mm3(high CD4 recovery, HCDR) were comparable to HC, but they were significantly decreased in PLWH with CD4 T-cell count < 500/mm3 (low CD4 recovery, LCDR). After adjusting for age, gender, viral suppression, and number of preexisting comorbidities, CD4 T-cell counts < 500/mm3 significantly predicted a poor magnitude of neutralizing antibodies against WT, omicron BA.5, and XBB 1.5 strains among PLWH. Multivariable linear regression adjusting for age and gender revealed that LCDR was associated with reduced neutralizing activity (P = 0.017) and interferon-γ-producing T-cell responses (P = 0.049 for CD T-cell; P = 0.014 for CD8 T-cell) against WT, and strongly associated with more decreased cross-neutralization against omicron BA.5 strains (P < 0.001). Conclusion HCDR demonstrated robust humoral and cell-mediated immune responses after a booster dose of ancestral SARS-CoV-2 vaccine, whereas LCDR showed diminished immune responses against WT virus and more impaired cross-neutralization against omicron BA.5 strain.

Background: We evaluated severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2)-specific humoral and cellular responses for up to 6 months after the 3rd dose of ancestral coronavirus disease 2019 (COVID-19) vaccination in people living with HIV (PLWH) and healthy controls (HCs) who were not infected with COVID-19. Methods: Anti-spike receptor-binding domain IgG (anti-RBD IgG) concentrations using chemiluminescence immunoassay and neutralizing antibodies using focus reduction neutralization test (FRNT) were assessed at 1 week after each dose of vaccination, and 3 and 6 months after the 3rd dose in 62 PLWH and 25 HCs. T-cell responses using intracellular cytokine stain were evaluated at 1 week before, and 1 week and 6 months after the 3rd dose. Results: At 1 week after the 3rd dose, adequate anti-RBD IgG (> 300 binding antibody unit /mL) was elicited in all PLWH except for one patient with 36 CD4 T-cell count/mm3 . The geometric mean titers of 50% FRNT against wild type (WT) and omicron BA.5 strains of SARS-CoV-2 in PLWH with CD4 T-cell count ≥ 500 cells/mm3(high CD4 recovery, HCDR) were comparable to HC, but they were significantly decreased in PLWH with CD4 T-cell count < 500/mm3 (low CD4 recovery, LCDR). After adjusting for age, gender, viral suppression, and number of preexisting comorbidities, CD4 T-cell counts < 500/mm3 significantly predicted a poor magnitude of neutralizing antibodies against WT, omicron BA.5, and XBB 1.5 strains among PLWH. Multivariable linear regression adjusting for age and gender revealed that LCDR was associated with reduced neutralizing activity (P = 0.017) and interferon-γ-producing T-cell responses (P = 0.049 for CD T-cell; P = 0.014 for CD8 T-cell) against WT, and strongly associated with more decreased cross-neutralization against omicron BA.5 strains (P < 0.001). Conclusion HCDR demonstrated robust humoral and cell-mediated immune responses after a booster dose of ancestral SARS-CoV-2 vaccine, whereas LCDR showed diminished immune responses against WT virus and more impaired cross-neutralization against omicron BA.5 strain.

Background: We evaluated severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2)-specific humoral and cellular responses for up to 6 months after the 3rd dose of ancestral coronavirus disease 2019 (COVID-19) vaccination in people living with HIV (PLWH) and healthy controls (HCs) who were not infected with COVID-19. Methods: Anti-spike receptor-binding domain IgG (anti-RBD IgG) concentrations using chemiluminescence immunoassay and neutralizing antibodies using focus reduction neutralization test (FRNT) were assessed at 1 week after each dose of vaccination, and 3 and 6 months after the 3rd dose in 62 PLWH and 25 HCs. T-cell responses using intracellular cytokine stain were evaluated at 1 week before, and 1 week and 6 months after the 3rd dose. Results: At 1 week after the 3rd dose, adequate anti-RBD IgG (> 300 binding antibody unit /mL) was elicited in all PLWH except for one patient with 36 CD4 T-cell count/mm3 . The geometric mean titers of 50% FRNT against wild type (WT) and omicron BA.5 strains of SARS-CoV-2 in PLWH with CD4 T-cell count ≥ 500 cells/mm3(high CD4 recovery, HCDR) were comparable to HC, but they were significantly decreased in PLWH with CD4 T-cell count < 500/mm3 (low CD4 recovery, LCDR). After adjusting for age, gender, viral suppression, and number of preexisting comorbidities, CD4 T-cell counts < 500/mm3 significantly predicted a poor magnitude of neutralizing antibodies against WT, omicron BA.5, and XBB 1.5 strains among PLWH. Multivariable linear regression adjusting for age and gender revealed that LCDR was associated with reduced neutralizing activity (P = 0.017) and interferon-γ-producing T-cell responses (P = 0.049 for CD T-cell; P = 0.014 for CD8 T-cell) against WT, and strongly associated with more decreased cross-neutralization against omicron BA.5 strains (P < 0.001). Conclusion HCDR demonstrated robust humoral and cell-mediated immune responses after a booster dose of ancestral SARS-CoV-2 vaccine, whereas LCDR showed diminished immune responses against WT virus and more impaired cross-neutralization against omicron BA.5 strain.

Mucormycosis encompasses a range of fungal infections that can impact various organs. Although pulmonary mucormycosis is relatively rare, it poses a significant threat, particularly to individuals with compromised immune systems. Pulmonary mucormycosis presents with various radiological manifestations. Notably, the involvement of the angioinvasive pulmonary artery in pulmonary mucormycosis cases has seldom been documented. In this report, we showcase the radiological characteristics of angioinvasive mucormycosis, which can mimic pulmonary thromboembolism or a pulmonary artery tumor, in a patient diagnosed with myelodysplastic syndrome.

Mucormycosis encompasses a range of fungal infections that can impact various organs. Although pulmonary mucormycosis is relatively rare, it poses a significant threat, particularly to individuals with compromised immune systems. Pulmonary mucormycosis presents with various radiological manifestations. Notably, the involvement of the angioinvasive pulmonary artery in pulmonary mucormycosis cases has seldom been documented. In this report, we showcase the radiological characteristics of angioinvasive mucormycosis, which can mimic pulmonary thromboembolism or a pulmonary artery tumor, in a patient diagnosed with myelodysplastic syndrome.

Mucormycosis encompasses a range of fungal infections that can impact various organs. Although pulmonary mucormycosis is relatively rare, it poses a significant threat, particularly to individuals with compromised immune systems. Pulmonary mucormycosis presents with various radiological manifestations. Notably, the involvement of the angioinvasive pulmonary artery in pulmonary mucormycosis cases has seldom been documented. In this report, we showcase the radiological characteristics of angioinvasive mucormycosis, which can mimic pulmonary thromboembolism or a pulmonary artery tumor, in a patient diagnosed with myelodysplastic syndrome.

Background: Numerous patients around the globe are dying from coronavirus disease 2019 (COVID-19). While age is a known risk factor, risk analysis in the young generation is lacking. The present study aimed to evaluate the clinical features and mortality risk factors in younger patients (≤ 50 years) with a critical case of COVID-19 in comparison with those among older patients (> 50 years) in Korea. Methods: We analyzed the data of adult patients only in critical condition (requiring high flow nasal cannula oxygen therapy or higher respiratory support) hospitalized with PCR-confirmed COVID-19 at 11 hospitals in Korea from July 1, 2021 to November 30, 2021 when the delta variant was a dominant strain. Patients’ electronic medical records were reviewed to identify clinical characteristics. Results: During the study period, 448 patients were enrolled. One hundred and forty-two were aged 50 years or younger (the younger group), while 306 were above 50 years of age (the older group). The most common pre-existing conditions in the younger group were diabetes mellitus and hypertension, and 69.7% of the patients had a body mass index (BMI) > 25 kg/m 2 .Of 142 younger patients, 31 of 142 patients (21.8%, 19 women) did not have these pre-existing conditions. The overall case fatality rate among severity cases was 21.0%, and it differed according to age: 5.6% (n = 8/142) in the younger group, 28.1% in the older group, and 38% in the ≥ 65 years group. Age (odds ratio [OR], 7.902; 95% confidence interval [CI], 2.754–18.181), mechanical ventilation therapy (OR, 17.233; 95% CI, 8.439–35.192), highest creatinine > 1.5 mg/dL (OR, 17.631; 95% CI, 8.321–37.357), and combined blood stream infection (OR, 7.092;95% CI, 1.061–18.181) were identified as independent predictors of mortality in total patients.Similar patterns were observed in age-specific analyses, but most results were statistically insignificant in multivariate analysis due to the low number of deaths in the younger group.The full vaccination rate was very low among study population (13.6%), and only three patients were fully vaccinated, with none of the patients who died having been fully vaccinated in the younger group. Seven of eight patients who died had a pre-existing condition or were obese (BMI > 25 kg/m 2 ), and the one remaining patient died from a secondary infection. Conclusion About 22% of the patients in the young critical group did not have an underlying disease or obesity, but the rate of obesity (BMI > 25 kg/m2 ) was high, with a fatality rate of 5.6%. The full vaccination rate was extremely low compared to the general population of the same age group, showing that non-vaccination has a grave impact on the progression of COVID-19 to a critical condition. The findings of this study highlight the need for measures to prevent critical progression of COVID-19, such as vaccinations and targeting young adults especially having risk factors.

Background: A pooling test is a useful tool for mass screening of coronavirus disease 2019 (COVID-19) in the pandemic era. We aimed to optimize a simple two-step pooling test by estimating the optimal pool size using experimental and mathematical validation. Materials and Methods: Experimental pools were created by mixing one positive respiratory sample with various numbers of negative samples. We selected positive samples with cycle threshold (Ct) values greater than 32 to validate the efficiency of the pooling test assuming a high likelihood of false-negative results due to low viral loads. The positivities of the experimental pools were investigated with a single reverse-transcription polymerase chain reaction (RT-PCR) using the U-TOP™ COVID-19 Detection Kit Plus (Seasun Biomaterials, Daejeon, Korea). We used the Dorfman equation to calculate the optimal size of a pooling test mathematically. Results: Viral RNA could be detected in a pool with a size up to 11, even if the Ct value of a positive sample was about 35. The Dorfman equation showed that the optimal number of samples in a pool was 11 when the prevalence was assumed to be 0.66% based on the test positivity in Daejeon, Korea from April 1, 2020 to November 10, 2020. The efficiency of the pooling test was 6.2, which can save 83.9 of 100 individual tests. Conclusion Eleven samples in a pool were validated optimal experimentally assuming a prevalence of 0.66%. The pool size needs modification as the pandemic progresses; thus, the prevalence should be carefully estimated before pooling tests are conducted.

Background: A pooling test is a useful tool for mass screening of coronavirus disease 2019 (COVID-19) in the pandemic era. We aimed to optimize a simple two-step pooling test by estimating the optimal pool size using experimental and mathematical validation. Materials and Methods: Experimental pools were created by mixing one positive respiratory sample with various numbers of negative samples. We selected positive samples with cycle threshold (Ct) values greater than 32 to validate the efficiency of the pooling test assuming a high likelihood of false-negative results due to low viral loads. The positivities of the experimental pools were investigated with a single reverse-transcription polymerase chain reaction (RT-PCR) using the U-TOP™ COVID-19 Detection Kit Plus (Seasun Biomaterials, Daejeon, Korea). We used the Dorfman equation to calculate the optimal size of a pooling test mathematically. Results: Viral RNA could be detected in a pool with a size up to 11, even if the Ct value of a positive sample was about 35. The Dorfman equation showed that the optimal number of samples in a pool was 11 when the prevalence was assumed to be 0.66% based on the test positivity in Daejeon, Korea from April 1, 2020 to November 10, 2020. The efficiency of the pooling test was 6.2, which can save 83.9 of 100 individual tests. Conclusion Eleven samples in a pool were validated optimal experimentally assuming a prevalence of 0.66%. The pool size needs modification as the pandemic progresses; thus, the prevalence should be carefully estimated before pooling tests are conducted.