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ABSTRACT We used a Vitek 2 AST–YS08 (YS08) system and the broth microdilution method (BMD) adopted by the Clinical and Laboratory Standards Institute (CLSI) to compare the susceptibility of 184 isolates of 11 Candida species to fluconazole, voriconazole, micafungin, caspofungin, amphotericin B, and flucytosine. In Candida albicans, the categorical agreement (CA) was 79.2%, 91.7%, 95.8%, and 95.8% for fluconazole, voriconazole, micafungin, and caspofungin, respectively. About 12.5% and 4.2% of very major errors were detected for fluconazole and voriconazole, respectively. C. glabrata showed excellent essential agreements (EAs) (>90%) for azoles but different MIC distributions for fluconazole and caspofungin. The CA between BMD fluconazole MICs and YS08 voriconazole MICs by the method-specific clinical breakpoint (CBP) was 90% in C. glabrata. Over 80% of C. glabrata and C. krusei isolates identified as micafungin–susceptible were labeled intermediate or resistant to caspofungin in YS08. In C. parapsilosis, 5.3% of very major errors and 10.5% of minor errors were found, whereas 33.3% of minor errors were observed in C. tropicalis for fluconazole. For C. tropicalis, 13 (61.9%) non-wild type (WT) isolates of fluconazole and 7 (33.3%) non-WTs of voriconazole were classified in YS08 as WT. For C. auris, the EAs were 93.3%, 100%, 82.2%, 97.8%, and 97.8% for fluconazole, voriconazole, micafungin, caspofungin, and amphotericin B, respectively. YS08 showed comparable results to the BMD. However, considering the lower YS08 fluconazole MIC results compared with BMD in Candida species and YS08 caspofungin results in C. glabrata and C. krusei, improvements are needed. IMPORTANCE The new Vitek 2 AST–YS08 (YS08) card has been updated to reflect the recently revised Clinical and Laboratory Standards Institute (CLSI) guideline. In this study, antifungal drug susceptibility tests were performed using the YS08 card and compared with the CLSI broth microdilution (BMD) method. In conclusion, YS08 showed similar results to BMD, including with C. auris. However, about 12.5% and 4.2% of major errors were detected for fluconazole and voriconazole, respectively, in C. albicans. More than 80% of C. glabrata and C. krusei isolates identified as susceptible to micafungin were labeled moderate or resistant to caspofungin in YS08. The categorical agreement between BMD fluconazole MICs and YS08 voriconazole MICs was 90% by the method-specific CBP of voriconazole, 80% by the current epidemiological cutoff value (ECV) (0.25 μg/mL) of voriconazole, and 85% by the previous ECV (0.5 μg/mL) of voriconazole. Further improvements in YS08 for the detection of fluconazole and echinocandin resistance are thus needed.

Soluble suppression of tumorigenesis-2 (sST2) is an emerging biomarker for sepsis as well as for heart failure. We investigated the prognostic utility of sST2 for predicting clinical outcomes in hospitalized coronavirus disease 2019 (COVID-19) patients. In a total of 52 hospitalized COVID-19 patients, sST2 levels were measured using the ichroma ST2 assay (Boditech Med Inc., Chuncheon-si, Gang-won-do, Republic of Korea). Clinical outcomes included intensive care unit (ICU) admission, ventilator use, extracorporeal membrane oxygenation (ECMO) use, and 30-day mortality. sST2 was analyzed according to clinical outcomes. sST2, sequential organ failure assessment (SOFA) score, critical disease, and 4C mortality score were compared using the receiver operating characteristic (ROC) curve and Kaplan–Meier methods for clinical outcomes. The sST2 level differed significantly according to ICU admission, ventilator use, ECMO use, and 30-day mortality (all p < 0.05). On ROC curve analysis, sST2 predicted ICU admission, ventilator use, ECMO use, and 30-day mortality comparable to SOFA score but significantly better than critical disease. sST2 predicted ICU admission, ventilator use, and ECMO use significantly better than the 4C mortality score. On Kaplan–Meier survival analysis, hazard ratios (95% confidence interval) were 8.4 (2.7–26.8) for sST2, 14.8 (3.0–71.7) for SOFA score, 1.8 (0.5–6.5) for critical disease, and 11.7 (3.4–40.1) for 4C mortality score. This study demonstrated that sST2 could be a useful biomarker to predict ICU admission, ventilator use, ECMO use, and 30-day mortality in hospitalized COVID-19 patients. sST2 may be implemented as a prognostic COVID-19 biomarker in clinical practice.

Background: Krebs von den Lungen 6 (KL-6) is a novel biomarker for interstitial lung disease, and it reflects acute lung injury. We explored the usefulness of KL-6 to predict clinical outcomes in hospitalized coronavirus disease 2019 (COVID-19) patients. Methods: In a total of 48 hospitalized COVID-19 patients, KL-6 levels were measured using the HISCL KL-6 assay (Sysmex, Kobe, Japan) with the HISCL 5000 automated analyzer (Sysmex). Clinical outcomes (intensive care unit [ICU] admission, ventilator use, extracorporeal membrane oxygenation [ECMO] use, and 30-day mortality) were analyzed according to KL-6 percentiles. Age, initial KL-6 level, Charlson comorbidity index (CCI), and critical disease were compared using the receiver operating characteristic (ROC) curve and Kaplan-Meier methods for clinical outcomes. Results: KL-6 quartiles were associated with ICU admission, ventilator use, and ECMO use (all p < 0.05), except 30-day mortality (p = 0.187). On ROC curve analysis, initial KL-6 level predicted ICU admission, ventilator use, and ECMO use significantly better than age, CCI, and critical disease (all p < 0.05); age, initial KL-6 level, CCI, and critical disease predicted 30-day mortality comparably. On Kaplan–Meier survival analysis, hazard ratios (95% confidence interval) were 4.8 (1.2–19.3) for age, 4.7 (1.1–21.6) for initial KL-6 level, 3.9 (0.9–16.2) for CCI, and 2.1 (0.5–10.3) for critical disease. Conclusions: This study demonstrated that KL-6 could be a useful biomarker to predict clinical outcomes in hospitalized COVID-19 patients. KL-6 may contribute to identifying COVID-19 patients requiring critical care, including ICU admission and ventilator and/or ECMO use.

This study provides a comprehensive analysis of global patent trends in battery recycling, focusing on secondary batteries and related technologies across Korea, China, and the United States. The methodology involved collecting data from various patent databases, followed by quantitative analysis to identify technology trends and guide future development. The research employed statistical tools to analyze patent activities, including the frequency and scope of patent filings, and comparative analysis to highlight differences between countries. This study reveals distinct emphases on technologies such as lithium-ion and waste battery recycling, highlighting notable differences in patent activities among key companies and countries. China’s large number of patents in battery manufacturing processes contrasts with the USA’s focus on electrochemical cell construction and storage systems, while Korea shows significant activity in waste battery technology. The novelty of this paper lies in its detailed comparative analysis of patent trends across these three major economies, providing insights into the technological focuses and priorities of each country. The study also identifies key challenges, such as the need for consistent innovation and broader geographic coverage in Korea, enhancing patent influence and international presence in China, and ensuring high patent quality and fostering innovation in lagging sectors in the United States. Addressing these challenges through enhanced collaboration, increased R&D investments, and supportive policies is crucial for strengthening the global position and driving further innovation in the battery recycling sector.

Background: Biomarkers and clinical indices have been investigated for predicting mortality in patients with coronavirus disease (COVID-19). We explored the prognostic utility of procalcitonin (PCT), presepsin, and the Veterans Health Administration COVID-19 (VACO) index for predicting 30-day-mortality in COVID-19 patients. Methods: In total, 54 hospitalized COVID-19 patients were enrolled. PCT and presepsin levels were measured using the Elecsys BRAHMS PCT assay (Roche Diagnostics GmbH, Mannheim, Germany) and HISCL Presepsin assay (Sysmex, Kobe, Japan), respectively. The VACO index was calculated based on age, sex, and comorbidities. PCT and presepsin levels and the VACO index were compared using ROC curve, Kaplan-Meier method, and reclassification analysis for the 30-day mortality. Results: ROC curve analysis was used to measure PCT and presepsin levels and the VACO index to predict 30-day mortality; the optimal cut-off values were 0.138 ng/mL for PCT, 717 pg/mL for presepsin, and 12.1% for the VACO index. On Kaplan-Meier survival analysis, hazard ratios (95% confidence interval) were 15.9 (4.1-61.3) for PCT, 26.3 (6.4-108.0) for presepsin, and 6.0 (1.7-21.1) for the VACO index. On reclassification analysis, PCT and presepsin in addition to the VACO index significantly improved the prognostic value of the index. Conclusions: This study demonstrated the prognostic utility of measuring PCT and presepsin levels and the VACO index in COVID-19 patients. The biomarkers in addition to the clinical index were more useful than the index alone for predicting clinical outcomes in COVID-19 patients. [ABSTRACT FROM AUTHOR]

Background: Non-invasive clinical algorithms for the detection of liver fibrosis (LF) can reduce the need for liver biopsy (LB). We explored the implementation of two serum biomarkers, enhanced liver fibrosis (ELF) and Mac-2 binding protein glycosylation isomer (M2BPGi), in clinical algorithms for LF in chronic hepatitis B (CHB) patients. Methods: Two clinical algorithms were applied to 152 CHB patients: (1) transient elastography (TE) followed by biomarkers (TE/ELF and TE/M2GPGi); (2) biomarker test followed by TE (ELF/TE and M2BPGi/TE). Using the cut-off value or index for the detection of advanced LF (TE≥F3; 9.8 in ELF and 3.0 in M2BPGi), LB was expected to be performed in cases with discordant TE and biomarker results. Results: In both algorithms, the expected number of LBs was lower when using M2BPGi than when using ELF (TE/ELF or ELF/TE, 13.2% [N=20]; TE/M2BPGi or M2BPGi/TE, 9.9% [N=15]), although there was no statistical difference (P=0.398). In the TE low-risk group (TE≤F2), the discordance rate was significantly lower in the TE/M2BPGi approach than in the TE/ELF approach (1.5% [2/136] vs. 11.0% [15/136], P=0.002). In the biomarker low-risk group, there was no significant difference between the ELF/TE and M2BPGi/TE approaches (3.9% [5/126] vs. 8.8% [13/147], P=0.118). Conclusions: Both ELF and M2BPGi can be implemented in non-invasive clinical algorithms for assessing LF in CHB patients. Given the lowest possibility of losing advanced LF cases in the low-risk group when using the TE/M2BPGi approach, this combination seems useful in clinical practice. [ABSTRACT FROM AUTHOR]

Background: Laboratory parameter abnormalities are commonly observed in COVID-19 patients; however, their clinical significance remains controversial. We assessed the prevalence, characteristics, and clinical impact of laboratory parameters in COVID-19 patients hospitalized in Daegu, Korea. Methods: We investigated the clinical and laboratory parameters of 1,952 COVID-19 patients on admission in nine hospitals in Daegu, Korea. The average patient age was 58.1 years, and 700 (35.9%) patients were men. The patients were classified into mild (N=1,612), moderate (N=294), and severe (N=46) disease groups based on clinical severity scores. We used chi-square test, multiple comparison analysis, and multinomial logistic regression to evaluate the correlation between laboratory parameters and disease severity. Results: Laboratory parameters on admission in the three disease groups were significantly different in terms of hematologic (Hb, Hct, white blood cell count, lymphocyte%, and platelet count), coagulation (prothrombin time and activated partial thromboplastin time), biochemical (albumin, aspartate aminotransferase, alanine aminotransferase, lactate, blood urea nitrogen, creatinine, and electrolytes), inflammatory (C-reactive protein and procalcitonin), cardiac (creatinine kinase MB isoenzyme and troponin I), and molecular virologic (Ct value of SARS-CoV-2 RdRP gene) parameters. Relative lymphopenia, prothrombin time prolongation, and hypoalbuminemia were significant indicators of COVID-19 severity. Patients with both hypoalbuminemia and lymphopenia had a higher risk of severe COVID-19. Conclusions: Laboratory parameter abnormalities on admission are common, are significantly associated with clinical severity, and can serve as independent predictors of COVID-19 severity. Monitoring the laboratory parameters, including albumin and lymphocyte count, is crucial for timely treatment of COVID-19. [ABSTRACT FROM AUTHOR]