Purpose: Hyperglycemia accelerates the formation of advanced glycation end products (AGEs), a group of compounds formed via non-enzymatic glycation/glycoxidation. Type 2 diabetes mellitus (T2DM) is related to oxidative stress, resulting in some overgeneration of AGEs. The accumulation of AGEs in T2DM patients leads to increased inflammation, DNA damage, tissue damage, progression of diabetic microvascular disease, and nephropathy. Heme oxygenase-1 (HO-1) is an intracellular enzyme that catalyzes the oxidation of heme. Expression of HO-1 in the endothelium and in muscle monocytes/macrophages was upregulated upon exposure to reactive oxygen species or oxidized low-density lipoprotein. Cells activated by oxidative stress are reported to release HO-1 in the serum. In the current study, we discuss the oxidative status according to the level of AGEs and the association of HO-1 with AGEs or urinary DNA damage marker in type 2 diabetic Korean patients. Methods: This study enrolled 36 diabetic patients. Subjects were classified into two groups by serum AGEs level (Low AGEs group: < 0.85 ng/mL serum AGEs; High AGEs group: > 0.85 ng/ mL serum AGEs). Body composition was measured using bioelectrical impedance analysis. Blood and urinary parameters were measured using commercial kits. Results: No significant differences were observed in the general characteristics and body composition between the two groups. Serum HO-1 concentration was significantly higher in the High AGEs group than in the Low AGEs group. After adjustment of age and gender, a correlation was performed to assess the association between serum HO-1 and serum AGEs or urinary 8-hydroxy-2′-deoxyguanosine (8-OHdG). Our results indicate that serum HO-1 is positively correlated with serum AGEs and urinary 8-OHdG. Conclusion Taken together, our results indicate that in diabetes patients, a high level of HO-1 is associated with a high concentration of AGEs and 8-OHdG, probably reflecting a protective response against oxidative stress.

Background: Firefighters inevitably encounter emotionally and physically stressful situations at work. Even firefighters without diagnosed post-traumatic stress disorder receive clinical attention because the nature of the profession exposes them to repetitive trauma and high occupational stress. This study investigated gray matter abnormalities related to high occupational stress in firefighters using voxel-based morphometry (VBM) and surface-based morphometry (SBM). Methods: We assessed 115 subjects (112 males and 3 females) using magnetic resonance imaging and evaluated occupational stress by the Korean Occupational Stress Scale-26 (KOSS-26). Subjects were classified into highly or lowly stressed groups based on the median value of the KOSS-26. Results: In VBM analysis, we found that firefighters with high occupational stress had lower gray matter volume (GMV) in both sides of the insula, the left amygdala, the right medial prefrontal cortex (mPFC), and the anterior cingulate cortex than firefighters with low occupational stress. In SBM analysis based on regions of interest, the GMV of the bilateral insula and right mPFC were also lower in the highly stressed group. Within the highly stressed group, low GMV of the insula was significantly correlated with the length of service (left: r = −0.347, P = 0.009; right: r = −0.333, P = 0.012). Conclusion Our findings suggest that regional GMV abnormalities are related to occupational stress. Regional gray matter abnormalities and related emotional dysregulation may contribute to firefighter susceptibility to burnout.

Background/Aims: Sepsis-3 criteria and quick Sequential Organ Failure Assessment (qSOFA) have been advocated to be used in defining sepsis in the general population. We aimed to compare the Sepsis-3 criteria and Chronic Liver Failure-SOFA (CLIF-SOFA) scores as predictors of in-hospital mortality in cirrhotic patients admitted to the emergency department (ED) for infections. Methods: A total of 1,622 cirrhosis patients admitted at the ED for infections were assessed retrospectively. We analyzed their demographic, laboratory, and microbiological data upon diagnosis of the infection. The primary endpoint was inhospital mortality rate. The predictive performances of baseline CLIF-SOFA, Sepsis-3, and qSOFA scores for in-hospital mortality were evaluated. Results: The CLIF-SOFA score proved to be significantly better in predicting in-hospital mortality (area under the receiver operating characteristic curve [AUROC], 0.80; 95% confidence interval [CI], 0.78–0.82) than the Sepsis-3 (AUROC, 0.75; 95% CI, 0.72–0.77, P<0.001) and qSOFA (AUROC, 0.67; 95% CI, 0.64–0.70; P<0.001) score. The CLIF-SOFA, CLIF-C-AD scores, Sepsis-3 criteria, septic shock, and qSOFA positivity were significantly associated with in-hospital mortality (adjusted hazard ratio [aHR], 1.24; 95% CI, 1.19–1.28; aHR, 1.13; 95% CI, 1.09–1.17; aHR, 1.19; 95% CI, 1.15–1.24; aHR, 1.88; 95% CI, 1.42–2.48; aHR, 2.06; 95% CI, 1.55–2.72; respectively; all P<0.001). For CLIF-SOFA scores ≥6, in-hospital mortality was >10%; this is the cutoff point for the definition of sepsis. Conclusions Among cirrhosis patients presenting with infections at the ED, CLIF-SOFA scores showed a better predictive performance for mortality than both Sepsis-3 criteria and qSOFA scores, and can be a useful tool of risk stratification in cirrhotic patients requiring timely intervention for infection.

This paper describes a community effort to improve earlier versions of the full-text corpus of Genomics & Informatics by semi-automatically detecting and correcting PDF-to-text conversion errors and optical character recognition errors during the first hackathon of Genomics & Informatics Annotation Hackathon (GIAH) event. Extracting text from multi-column biomedical documents such as Genomics & Informatics is known to be notoriously difficult. The hackathon was piloted as part of a coding competition of the ELTEC College of Engineering at Ewha Womans University in order to enable researchers and students to create or annotate their own versions of the Genomics & Informatics corpus, to gain and create knowledge about corpus linguistics, and simultaneously to acquire tangible and transferable skills. The proposed projects during the hackathon harness an internal database containing different versions of the corpus and annotations.

This paper describes a community effort to improve earlier versions of the full-text corpus of Genomics & Informatics by semi-automatically detecting and correcting PDF-to-text conversion errors and optical character recognition errors during the first hackathon of Genomics & Informatics Annotation Hackathon (GIAH) event. Extracting text from multi-column biomedical documents such as Genomics & Informatics is known to be notoriously difficult. The hackathon was piloted as part of a coding competition of the ELTEC College of Engineering at Ewha Womans University in order to enable researchers and students to create or annotate their own versions of the Genomics & Informatics corpus, to gain and create knowledge about corpus linguistics, and simultaneously to acquire tangible and transferable skills. The proposed projects during the hackathon harness an internal database containing different versions of the corpus and annotations.