Objective: To identify the adherence rate to poly (ADP-ribose) polymerase (PARP) inhibitors and identify factors contributing to the deterioration of adherence at our institution. Methods: The adherence rate to PARP inhibitors was calculated using self-reported Adherence to Refills and Medications Scale questionnaires from a cross-sectional survey. Multivariable logistic regression analysis was performed to identify the factors that affected adherence. Results: Of the 131 respondents, 32 (24.4%) showed non-adherence to PARP inhibitors.In the multivariable logistic regression analysis, unemployed or retired status (odds ratio [OR]=4.878; 95% confidence interval [CI]=1.528–15.572; p=0.008), patients receiving niraparib (OR=3.387; 95% CI=1.283–8.940; p=0.014), and a lower score on the quality-oflife assessment (EORTC-QLQ-OV28), which reflects a better quality of life (QOC) with a lower symptom burden (OR=1.056; 95% CI=1.027–1.086; p<0.001) were associated with high adherence to PARP inhibitors. Conclusion Approximately one-fourth of patients with ovarian cancer are non-adherent to PARP inhibitors as maintenance treatment for newly diagnosed advanced ovarian cancer. The occupational status, type of PARP inhibitor, and QOC may affect adherence to PARP inhibitors.

Objective: To identify the adherence rate to poly (ADP-ribose) polymerase (PARP) inhibitors and identify factors contributing to the deterioration of adherence at our institution. Methods: The adherence rate to PARP inhibitors was calculated using self-reported Adherence to Refills and Medications Scale questionnaires from a cross-sectional survey. Multivariable logistic regression analysis was performed to identify the factors that affected adherence. Results: Of the 131 respondents, 32 (24.4%) showed non-adherence to PARP inhibitors.In the multivariable logistic regression analysis, unemployed or retired status (odds ratio [OR]=4.878; 95% confidence interval [CI]=1.528–15.572; p=0.008), patients receiving niraparib (OR=3.387; 95% CI=1.283–8.940; p=0.014), and a lower score on the quality-oflife assessment (EORTC-QLQ-OV28), which reflects a better quality of life (QOC) with a lower symptom burden (OR=1.056; 95% CI=1.027–1.086; p<0.001) were associated with high adherence to PARP inhibitors. Conclusion Approximately one-fourth of patients with ovarian cancer are non-adherent to PARP inhibitors as maintenance treatment for newly diagnosed advanced ovarian cancer. The occupational status, type of PARP inhibitor, and QOC may affect adherence to PARP inhibitors.

Objective: To identify the adherence rate to poly (ADP-ribose) polymerase (PARP) inhibitors and identify factors contributing to the deterioration of adherence at our institution. Methods: The adherence rate to PARP inhibitors was calculated using self-reported Adherence to Refills and Medications Scale questionnaires from a cross-sectional survey. Multivariable logistic regression analysis was performed to identify the factors that affected adherence. Results: Of the 131 respondents, 32 (24.4%) showed non-adherence to PARP inhibitors.In the multivariable logistic regression analysis, unemployed or retired status (odds ratio [OR]=4.878; 95% confidence interval [CI]=1.528–15.572; p=0.008), patients receiving niraparib (OR=3.387; 95% CI=1.283–8.940; p=0.014), and a lower score on the quality-oflife assessment (EORTC-QLQ-OV28), which reflects a better quality of life (QOC) with a lower symptom burden (OR=1.056; 95% CI=1.027–1.086; p<0.001) were associated with high adherence to PARP inhibitors. Conclusion Approximately one-fourth of patients with ovarian cancer are non-adherent to PARP inhibitors as maintenance treatment for newly diagnosed advanced ovarian cancer. The occupational status, type of PARP inhibitor, and QOC may affect adherence to PARP inhibitors.

Background: Worldwide, sepsis is the leading cause of death in hospitals. If mortality rates in patients with sepsis can be predicted early, medical resources can be allocated efficiently. We constructed machine learning (ML) models to predict the mortality of patients with sepsis in a hospital emergency department. Methods: This study prospectively collected nationwide data from an ongoing multicenter cohort of patients with sepsis identified in the emergency department. Patients were enrolled from 19 hospitals between September 2019 and December 2020. For acquired data from 3,657 survivors and 1,455 deaths, six ML models (logistic regression, support vector machine, random forest, extreme gradient boosting [XGBoost], light gradient boosting machine, and categorical boosting [CatBoost]) were constructed using fivefold cross-validation to predict mortality. Through these models, 44 clinical variables measured on the day of admission were compared with six sequential organ failure assessment (SOFA) components (PaO 2 /FIO 2 [PF], platelets (PLT), bilirubin, cardiovascular, Glasgow Coma Scale score, and creatinine).The confidence interval (CI) was obtained by performing 10,000 repeated measurements via random sampling of the test dataset. All results were explained and interpreted using Shapley’s additive explanations (SHAP). Results: Of the 5,112 participants, CatBoost exhibited the highest area under the curve (AUC) of 0.800 (95% CI, 0.756–0.840) using clinical variables. Using the SOFA components for the same patient, XGBoost exhibited the highest AUC of 0.678 (95% CI, 0.626–0.730). As interpreted by SHAP, albumin, lactate, blood urea nitrogen, and international normalization ratio were determined to significantly affect the results. Additionally, PF and PLTs in the SOFA component significantly influenced the prediction results. Conclusion Newly established ML-based models achieved good prediction of mortality in patients with sepsis. Using several clinical variables acquired at the baseline can provide more accurate results for early predictions than using SOFA components. Additionally, the impact of each variable was identified.

Purpose: In the present study, we determined the prevalence of obstructive meibomian gland dysfunction (MGD), hyposecretory MGD, grossly normal MG, and hypersecretory MGD in patients with dry eye syndrome using lipid layer thickness (LLT) and MG dropout. Methods: Eighty-eight patients with dry eye syndrome were included in the study. Patients were categorized into four groups according to the LLT and weighted total meiboscore. The proportion of patients in each group was calculated. The age, sex, Ocular Surface Disease Index, LLT, Schirmer, tear film breakup time, cornea stain, weighted total meiboscore, expressibility, and quality of meibum were compared between the four groups. Results: Fifteen eyes (17.0%) had obstructive MGD, two eyes (2.3%) had hyposecretory MGD, 40 eyes (45.5%) had grossly normal MG, and 17 eyes (19.3%) had hypersecretory MGD. The obstructive MGD group was younger than the grossly normal MG group. In obstructive MGD, the ratio of men to women was higher than that of the other groups. However, Ocular Surface Disease Index, Schirmer, tear film breakup time, and corneal stain did not show statistically significant differences between the four groups. The meibum expressibility of the hyposecretoy MGD group was worse than those of the other groups. The meibum expressibility of the hyposecretoy MGD group was poor than those of the obstructive and hypersecretory MGD group. Conclusions This categorization was expected to help determine the best treatment method for dry eye syndrome, according to the MG status.

The hepatitis A virus (HAV) induces severe acute liver injury and is adapted to human and monkey cell lines but not other cells. In this study, the HAV was inoculated into porcine kidney (PK-15) cells to determine its infectivity in porcine cells. The growth pattern of the HAV in PK-15 cells was compared with its growth pattern in fetal rhesus kidney (FRhK-4) cells. The growth of HAV was less efficient in PK-15 cells. In conclusion, HAV replication was verified in PK-15 cells for the first time. Further investigations will be needed to identify the HAV-restrictive mechanisms in PK-15 cells.

Gastroesophageal reflux disease (GERD) is a condition in which gastric contents regurgitate into the esophagus or beyond, resulting in either troublesome symptoms or complications. GERD is heterogeneous in terms of varied manifestations, test findings, and treatment responsiveness. GERD diagnosis can be established with symptomatology, pathology, or physiology. Recently the Lyon consensus defined the “proven GERD” with concrete evidence for reflux, including advanced grade erosive esophagitis (Los Angeles classification grades C and or D esophagitis), long-segment Barrett’s mucosa or peptic strictures on endoscopy or distal esophageal acid exposure time > 6% on 24-hour ambulatory pH-impedance monitoring. However, some Asian researchers have different opinions on whether the same standards should be applied to the Asian population. The prevalence of GERD is increasing in Asia. The present evidence-based guidelines were developed using a systematic review and meta-analysis approach. In GERD with typical symptoms, a proton pump inhibitor test can be recommended as a sensitive, cost-effective, and practical test for GERD diagnosis. Based on a meta-analysis of 19 estimated acid-exposure time values in Asians, the reference range upper limit for esophageal acid exposure time was 3.2% (95% confidence interval 2.7-3.9%) in the Asian countries. Esophageal manometry and novel impedance measurements, including mucosal impedance and a post-reflux swallow-induced peristaltic wave, are promising in discrimination of GERD among different reflux phenotypes, thus increasing its diagnostic yield. We also propose a long-term strategy of evidence-based GERD treatment with proton pump inhibitors and other drugs.

Purpose: Identification of type I protein arginine methyltransferase (PRMT) substrates and their functional significance during tumorigenesis is becoming more important. The present study aimed to identify target substrates for type I PRMT using 2-dimensional (2D) gel electrophoresis (GE) and 2D Western blotting (WB). Methods: Using immunoblot analysis, we compared the expression of type I PRMTs and endogenous levels of arginine methylation between the primary colorectal cancer (CRC) and adjacent noncancerous tissues paired from the same patient. To identify arginine-methylated proteins in HCT116 cells, we carried out 2D-GE and 2D-WB with a type I PRMT product-specific antibody (anti-dimethyl-arginine antibody, asymmetric [ASYM24]). Arginine-methylated protein spots were identified by mass spectrometry, and messenger RNA (mRNA) levels corresponding to the identified proteins were analyzed using National Center for Biotechnology Information (NCBI) microarray datasets between the primary CRC and noncancerous tissues. Results: Type I PRMTs and methylarginine-containing proteins were highly maintained in CRC tissues compared to noncancerous tissues. We matched 142 spots using spot analysis software between a Coomassie blue (CBB)-stained 2D gel and 2D-WB, and we successfully identified 7 proteins that reacted with the ASYM24 antibody: CACYBP, GLOD4, MAPRE1, CCT7, TKT, CK8, and HSPA8. Among these proteins, the levels of 4 mRNAs including MAPRE1, CCT7, TKT, and HSPA8 in CRC tissues showed a statistically significant increase compared to noncancerous tissues from patients using the NCBI microarray datasets. Conclusion Our results indicate that the method shown here is useful in identifying arginine-methylated proteins, and significance of arginine modification in the proteins identified here should be further identified during CRC development.

Background/Aims: Coronavirus disease 2019 (COVID-19) is associated with acute respiratory syndrome. The mechanisms underlying the different degrees of pneumonia severity in patients with COVID-19 remain elusive. This study provides evidence that COVID-19 is associated with eosinophil-mediated inflammation. Methods: We performed a retrospective case series of three patients with laboratory and radiologically confirmed COVID-19 pneumonia admitted to Chosun University Hospital. Demographic and clinical data on inflammatory cell lung infiltration and cytokine levels in patients with COVID-19 were collected. Results: Cytological analysis of sputum, tracheal aspirates, and bronchoalveolar lavage fluid (BALF) samples from all three patients revealed massive infiltration of polymorphonuclear cells (PMNs), such as eosinophils and neutrophils. All sputum and BALF specimens contained high levels of eosinophil cationic proteins. The infiltration of PMNs into the lungs, together with elevated levels of natural killer T (NKT) cells in BALF and peripheral blood samples from patients with severe pneumonia in the acute phase was confirmed by flow cytometry. Conclusions These results suggest that the lungs of COVID-19 patients can exhibit eosinophil-mediated inflammation, together with an elevated NKT cell response, which is associated with COVID-19 pneumonia.