Gemella sanguinis is a gram-positive, facultatively anaerobic coccus bacterium that has rarely been reported as a cause of infective endocarditis. A 41-year-old male patient with mitral valve prolapse visited the outpatient clinic presenting with fever. Transthoracic echocardiography and transesophageal echocardiography revealed myxomatous change and vegetation of the mitral valve. We isolated G. sanguinis from the patient’s blood, cultured it in both aerobic and anaerobic blood culture bottles, and identified it using matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS; bioMérieux, France) and 16s rRNA sequencing. The isolated G. sanguinis was highly susceptible to penicillin and vancomycin and intermediately susceptible to erythromycin, clindamycin, and levofloxacin. Following the American Heart Association recommendations, this highly penicillin-sensitive isolate was eradicated with ceftriaxone and gentamicin, and the patient recovered and was discharged. To the best of our knowledge, this is the first reported case in Korea where G. sanguinis, the causative agent of endocarditis, was identified using MALDI-TOF MS and 16s rRNA sequencing and was treated with only antibiotics and without surgical valve replacement.

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.

Recent evidence has indicated that bacteria-derived extracellular vesicles (EVs) are important for host–microbe communication. The aims of the present study were to evaluate whether bacteria-derived EVs are excreted via the urinary tract and to compare the composition of bacteria-derived EVs in the urine of pregnant and non-pregnant women. Seventy-three non-pregnant and seventy-four pregnant women were enrolled from Dankook University and Ewha Womans University hospitals. DNA was extracted from urine EVs after EV isolation using the differential centrifugation method. 16S ribosomal RNA (16S rRNA) gene sequencing was performed using high-throughput 454 pyrosequencing after amplification of the V1–V3 region of the 16S rDNA. The composition of 13 taxa differed significantly between the pregnant and non-pregnant women. At the genus level, Bacillus spp. EVs were more significantly enriched in the urine of the pregnant women than in that of the non-pregnant women (45.61% vs 0.12%, respectively). However, Pseudomonas spp. EVs were more dominant in non-pregnant women than in pregnant women (13.2% vs 4.09%, respectively). Regarding the compositional difference between pregnant women with normal and preterm delivery, EVs derived from Ureaplasma spp. and the family Veillonellaceae (including Megasphaera spp.) were more abundant in the urine of preterm-delivered women than in that of women with normal deliveries. Taken together, these data showed that Bacillus spp. EVs predominate in the urine of pregnant women, whereas Pseudomonas spp. EVs predominate in the urine of non-pregnant women; this suggests that Bacillus spp. EVs might have an important role in the maintenance of pregnancy.
Bacillus ; Centrifugation ; DNA ; DNA, Ribosomal ; Extracellular Vesicles* ; Female ; Hospitals, University ; Humans ; Megasphaera ; Metagenomics* ; Methods ; Pregnancy ; Pregnant Women ; Pseudomonas ; RNA, Ribosomal, 16S ; Ureaplasma ; Urinary Tract ; Veillonellaceae

Background: The coronavirus disease 2019 (COVID-19) pandemic has caused the death of thousands of patients worldwide. Although age is known to be a risk factor for morbidity and mortality in COVID-19 patients, critical illness or death is occurring even in the younger age group as the epidemic spreads. In early 2022, omicron became the dominant variant of the COVID-19 virus in South Korea, and the epidemic proceeded on a large scale. Accordingly, this study aimed to determine whether young adults (aged ≤ 50 years) with critical COVID-19 infection during the omicron period had different characteristics from older patients and to determine the risk factors for mortality in this specific age group. Methods: We evaluated 213 critical adult patients (high flow nasal cannula or higher respiratory support) hospitalized for polymerase chain reaction-confirmed COVID-19 in nine hospitals in South Korea between February 1, 2022 and April 30, 2022. Demographic characteristics, including body mass index (BMI) and vaccination status; underlying diseases; clinical features and laboratory findings; clinical course; treatment received; and outcomes were collected from electronic medical records (EMRs) and analyzed according to age and mortality. Results: Overall, 71 critically ill patients aged ≤ 50 years were enrolled, and 142 critically ill patients aged over 50 years were selected through 1:2 matching based on the date of diagnosis. The most frequent underlying diseases among those aged ≤ 50 years were diabetes and hypertension, and all 14 patients who died had either a BMI ≥ 25 kg/m 2 or an underlying disease. The total case fatality rate among severe patients (S-CFR) was 31.0%, and the S-CFR differed according to age and was higher than that during the delta period. The S-CFR was 19.7% for those aged ≤ 50 years, 36.6% for those aged > 50 years, and 38.1% for those aged ≥ 65 years. In multivariate analysis, age (odds ratio [OR], 1.084; 95% confidence interval [CI], 1.043–1.127), initial low-density lipoprotein > 600 IU/L (OR, 4.782; 95% CI, 1.584–14.434), initial C-reactive protein > 8 mg/dL (OR, 2.940; 95% CI, 1.042–8.293), highest aspartate aminotransferase > 200 IU/L (OR, 12.931; 95% CI, 1.691–98.908), and mechanical ventilation implementation (OR, 3.671; 95% CI, 1.294–10.420) were significant independent predictors of mortality in critical COVID-19 patients during the omicron wave. A similar pattern was shown when analyzing the data by age group, but most had no statistical significance owing to the small number of deaths in the young critical group. Although the vaccination completion rate of all the patients (31.0%) was higher than that in the delta wave period (13.6%), it was still lower than that of the general population. Further, only 15 (21.1%) critically ill patients aged ≤ 50 years were fully vaccinated. Overall, the severity of hospitalized critical patients was significantly higher than that in the delta period, indicating that it was difficult to find common risk factors in the two periods only with a simple comparison. Conclusion Overall, the S-CFR of critically ill COVID-19 patients in the omicron period was higher than that in the delta period, especially in those aged ≤ 50 years. All of the patients who died had an underlying disease or obesity. In the same population, the vaccination rate was very low compared to that in the delta wave, indicating that non-vaccination significantly affected the progression to critical illness. Notably, there was a lack of prescription for Paxlovid for these patients although they satisfied the prescription criteria. Early diagnosis and active initial treatment was necessary, along with the proven methods of vaccination and personal hygiene. Further studies are needed to determine how each variant affects critically ill patients.

Objective: To describe and molecularly characterize an outbreak of dengue virus (DENV) infection in Cajamarca, an Andean region in Peru. Methods: A total of 359 serum samples from patients with acute febrile illness were assessed for the presence of DENV via RT-PCR, ELISA NS1, IgM and IgG in Cajamarca, Peru from January 2017 to June 2017. The evaluation of the different diagnostic tests and their applicability was performed. Results: Dengue virus was detected in 24.7% of samples by RTPCR. Meanwhile, serological analysis detected 30.3% positive cases via ELISA NS1 antigen, 16.7% via ELISA IgG and 9.7% via ELISA IgM. Most of the cases corresponded to DENV-3 (77.5%). The use of RT-PCR performed better in primary infections (P<0.01), while detection of ELISA IgM performed better in secondary infections (P<0.01). The combination of NS1 and IgM performed better than the other assays in detecting primary (92.5%) and secondary infections (96.6%). The most frequent symptoms associated with fever were headaches, myalgias, and arthralgias across all groups. Conclusions: We report an important outbreak of dengue infection caused by DENV-3 in Cajamarca, Peru. Our findings encourage the use of NS1 antigen and IgM co-detection. These findings demonstrate an increasing expansion of DENV-3 in Peru and highlight the importance of molecular diagnosis and serotype characterization among the clinically defined dengue cases to strengthen the Peruvian epidemiological surveillance.