The rapid COVID-19 polymerase chain reaction (PCR) test using Xpert Xpress SARS-CoV-2 and the conventional COVID-19 PCR test using Standard M nCoV Detection were compared after matching for sex, age, and hospitalization period. The rapid COVID-19 PCR test group exhibited shorter turnaround time and emergency department stay.

While the coronavirus disease 2019 pandemic is ongoing, monkeypox has been rapidly spreading in non-endemic countries since May 2022. Accurate and rapid laboratory tests are essential for identifying and controlling monkeypox. Korean Society for Laboratory Medicine and the Korea Disease Prevention and Control Agency have proposed guidelines for diagnosing monkeypox in clinical laboratories in Korea. These guidelines cover the type of tests, selection of specimens, collection of specimens, diagnostic methods, interpretation of test results, and biosafety. Molecular tests are recommended as confirmatory tests. Skin lesion specimens are recommended for testing in the symptomatic stage, and the collection of both blood and oropharyngeal swabs is recommended in the presymptomatic or prodromal stage.

Background: National reference standards for anti-HIV-1 antibody are needed to evaluate the performance and maintain the quality control of anti-HIV-1 antibody assays. The aim of this study was to prepare a mixed-titer performance panel and assess its suitability as a national reference standard for anti-HIV-1 antibody according to stability, collaboration, and other studies. Methods: Nineteen serum samples from different HIV patients were obtained, along with 15 units of fresh frozen plasma samples with negative anti-HIV-1 antibody results. Ten anti-HIV-1 antibody-positive candidate standards and two negative candidate standards were prepared based on the reactivity in the Alinity i HIV Ag/Ab combo assay (Abbott Laboratories, Wiesbaden, Germany). A collaborative study was conducted across eight laboratories using five anti-HIV-1 antibody assays. Real-time and accelerated stability were evaluated to assess the long-term stability. Results: In the collaborative study, results of all five anti-HIV-1 antibody assays were positive for all 10 candidate standards prepared using HIV patient samples. The CV of each assay for every candidate standard was within 10%, except for one assay result. No real-time and accelerated stability change trend was observed at −70°C or −20°C, supporting that the reference standards were maintained in a stable state at −70°C for long-term storage. Conclusions The overall results suggest that the 12 candidate standards could serve as national reference standards for anti-HIV-1 antibody.

Background: Due to the COVID-19 pandemic, from 2020, many pharmaceutical companies have developed vaccines. To determine the efficacy of AstraZeneca's and Pfizer's vaccines, which were the first and second vaccines to be approved in Korea, respectively, we developed a method to measure their antibody-generating efficacies using immunology analyzers and a rapid antibody test available in Korea. Methods: The antibody-stimulating efficacies of the Pfizer and AstraZeneca vaccines were evaluated using Centaur® XPT SARS-CoV-2 (Siemens Healthineers, Germany), Elecsys® AntiSARS-CoV-2 S (Roche Diagnostics, Germany), and STANDARD F SARS-CoV-2 nAb FIA (SD Biosensor, Korea). Healthcare workers were enrolled in two groups: the Pfizer (121) and AstraZeneca (117) groups. Antibody levels were measured pre-vaccination, three weeks after vaccination, and 16 weeks after vaccination. Results: The Pfizer group comprised 41 males and 80 females, while the AstraZeneca group comprised 38 males and 79 females. Antibody results were analyzed after excluding four individuals who had recovered from COVID-19. Between weeks 3 and 16, there was no significant difference (P= 0.5, 1.0) between the results of the Roche and Siemens antibody tests in the Pfizer vaccine group. However, the SD biosensor results comparing with the Roche and Siemens antibody tests at three weeks after the initial vaccination showed a significant difference (P < 0.0001). Analysis of the Roche antibody test results before, at three weeks, and at 16 weeks after the administration of the Pfizer and AstraZeneca vaccines revealed a statistically significant difference between before and at three weeks after the first injection (P < 0.0001). Conclusion After two doses of the Pfizer and AstraZeneca vaccines, antibody formation was above the 90 th percentile of the measurement range in all subjects.

In response to the ongoing coronavirus disease 2019 (COVID-19) pandemic, an online laboratory surveillance system was established to monitor severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) real-time reverse transcription-PCR (rRT-PCR) testing capacities and results. SARS-CoV-2 rRT-PCR testing data were collected from 97 clinical laboratories, including 84 medical institutions and 13 independent clinical laboratories in Korea. We assessed the testing capacities to utilize SARS-CoV-2 rRT-PCR based on surveillance data obtained from February 7th to June 4th, 2020 and evaluated positive result characteristics according to the reagents used and sample types. A total of 1,890,319 SARS-CoV-2 rRT-PCR testing were performed, 2.3% of which were positive. Strong correlations were observed between the envelope (E ) gene and RNA-dependent RNA polymerase (RdRp )ucleocapsid (N ) genes threshold cycle (Ct) values for each reagent. No statistically significant differences in gene Ct values were observed between the paired upper and lower respiratory tract samples, except in the N gene for nasopharyngeal swab and sputum samples. Our study showed that clinical laboratories in Korea have rapidly expanded their testing capacities in response to the COVID-19 outbreak, with a peak daily capacity of 34,193 tests. Rapid expansion in testing capacity is a critical component of the national response to the ongoing pandemic.

Objective: To evaluate the association of MRI features with the major genomic profiles and prognosis of World Health Organization grade III (G3) gliomas compared with those of glioblastomas (GBMs). Materials and Methods: We enrolled 76 G3 glioma and 155 GBM patients with pathologically confirmed disease who had pretreatment brain MRI and major genetic information of tumors. Qualitative and quantitative imaging features, including volumetrics and histogram parameters, such as normalized cerebral blood volume (nCBV), cerebral blood flow (nCBF), and apparent diffusion coefficient (nADC) were evaluated. The G3 gliomas were divided into three groups for the analysis: with this isocitrate dehydrogenase (IDH)-mutation, IDH mutation and a chromosome arm 1p/19q-codeleted (IDHmut1p/19qdel), IDH mutation, 1p/19q-nondeleted (IDHmut1p/19qnondel), and IDH wildtype (IDHwt). A prediction model for the genetic profiles of G3 gliomas was developed and validated on a separate cohort. Both the quantitative and qualitative imaging parameters and progression-free survival (PFS) of G3 gliomas were compared and survival analysis was performed. Moreover, the imaging parameters and PFS between IDHwt G3 gliomas and GBMs were compared. Results: IDHmut G3 gliomas showed a larger volume (p = 0.017), lower nCBF (p = 0.048), and higher nADC (p = 0.007) than IDHwt. Between the IDHmut tumors, IDHmut1p/19qdel G3 gliomas had higher nCBV (p = 0.024) and lower nADC (p = 0.002) than IDHmut1p/19qnondel G3 gliomas. Moreover, IDHmut1p/19qdel tumors had the best prognosis and IDHwt tumors had the worst prognosis among G3 gliomas (p < 0.001). PFS was significantly associated with the 95th percentile values of nCBV and nCBF in G3 gliomas. There was no significant difference in neither PFS nor imaging features between IDHwt G3 gliomas and IDHwt GBMs. Conclusion We found significant differences in MRI features, including volumetrics, CBV, and ADC, in G3 gliomas, according to IDH mutation and 1p/19q codeletion status, which can be utilized for the prediction of genomic profiles and the prognosis of G3 glioma patients. The MRI signatures and prognosis of IDHwt G3 gliomas tend to follow those of IDHwt GBMs.

Objective: To evaluate pharmacokinetic variables from contrast-enhancing lesions (CELs) and non-enhancing T2 high signal intensity lesions (NE-T2HSILs) on dynamic contrast-enhanced (DCE) magnetic resonance (MR) imaging for predicting progression-free survival (PFS) in glioblastoma (GBM) patients. Materials and Methods: Sixty-four GBM patients who had undergone preoperative DCE MR imaging and received standard treatment were retrospectively included. We analyzed the pharmacokinetic variables of the volume transfer constant (Ktrans) and volume fraction of extravascular extracellular space within the CEL and NE-T2HSIL of the entire tumor. Univariate and multivariate Cox regression analyses were performed using preoperative clinical characteristics, pharmacokinetic variables of DCE MR imaging, and postoperative molecular biomarkers to predict PFS. Results: The increased mean Ktrans of the CEL, increased 95th percentile Ktrans of the CELs, and absence of methylated O6- methylguanine-DNA methyltransferase promoter were relevant adverse variables for PFS in the univariate analysis (p = 0.041, p = 0.032, and p = 0.083, respectively). The Kaplan-Meier survival curves demonstrated that PFS was significantly shorter in patients with a mean Ktrans of the CEL > 0.068 and 95th percentile Ktrans of the CEL > 0.223 (log-rank p = 0.038 and p = 0.041, respectively). However, only mean Ktrans of the CEL was significantly associated with PFS (p = 0.024; hazard ratio, 553.08; 95% confidence interval, 2.27–134756.74) in the multivariate Cox proportional hazard analysis. None of the pharmacokinetic variables from NE-T2HSILs were significantly related to PFS. Conclusion Among the pharmacokinetic variables extracted from CELs and NE-T2HSILs on preoperative DCE MR imaging, the mean Ktrans of CELs exhibits potential as a useful imaging predictor of PFS in GBM patients.

The explosive growth of next-generation sequencing data has resulted in ultra-large-scale datasets and ensuing computational problems. In Korea, the amount of genomic data has been increasing rapidly in the recent years. Leveraging these big data requires researchers to use large-scale computational resources and analysis pipelines. A promising solution for addressing this computational challenge is cloud computing, where CPUs, memory, storage, and programs are accessible in the form of virtual machines. Here, we present a cloud computing-based system, Bio-Express, that provides user-friendly, cost-effective analysis of massive genomic datasets. Bio-Express is loaded with predefined multi-omics data analysis pipelines, which are divided into genome, transcriptome, epigenome, and metagenome pipelines. Users can employ predefined pipelines or create a new pipeline for analyzing their own omics data. We also developed several web-based services for facilitating downstream analysis of genome data. Bio-Express web service is freely available at https://www.bioexpress.re.kr/.

The explosive growth of next-generation sequencing data has resulted in ultra-large-scale datasets and ensuing computational problems. In Korea, the amount of genomic data has been increasing rapidly in the recent years. Leveraging these big data requires researchers to use large-scale computational resources and analysis pipelines. A promising solution for addressing this computational challenge is cloud computing, where CPUs, memory, storage, and programs are accessible in the form of virtual machines. Here, we present a cloud computing-based system, Bio-Express, that provides user-friendly, cost-effective analysis of massive genomic datasets. Bio-Express is loaded with predefined multi-omics data analysis pipelines, which are divided into genome, transcriptome, epigenome, and metagenome pipelines. Users can employ predefined pipelines or create a new pipeline for analyzing their own omics data. We also developed several web-based services for facilitating downstream analysis of genome data. Bio-Express web service is freely available at https://www.bioexpress.re.kr/.