Background: Carbapenem resistance in Pseudomonas aeruginosa is a serious global health problem. We investigated the clonal distribution and its association with the carbapenem resistance mechanisms of carbapenem-non-susceptible P. aeruginosa isolates from three Korean hospitals. Methods: A total of 155 carbapenem-non-susceptible P. aeruginosa isolates collected between 2011 and 2019 were analyzed for sequence types (STs), antimicrobial susceptibility, and carbapenem resistance mechanisms, including carbapenemase production, the presence of resistance genes, OprD mutations, and the hyperproduction of AmpC β-lactamase. Results: Sixty STs were identified in carbapenem-non-susceptible P. aeruginosa isolates.Two high-risk clones, ST235 (N = 41) and ST111 (N = 20), were predominant; however, sporadic STs were more prevalent than high-risk clones. The resistance rate to amikacin was the lowest (49.7%), whereas that to piperacillin was the highest (92.3%). Of the 155 carbapenem-non-susceptible isolates, 43 (27.7%) produced carbapenemases. Three metalloβ-lactamase (MBL) genes, blaIMP-6 (N = 38), blaVIM-2 (N = 3), and blaNDM-1 (N = 2), were detected. blaIMP-6 was detected in clonal complex 235 isolates. Two ST773 isolates carried blaNDM-1 and rmtB. Frameshift mutations in oprD were identified in all isolates tested, regardless of the presence of MBL genes. Hyperproduction of AmpC was detected in MBL gene–negative isolates. Conclusions Frameshift mutations in oprD combined with MBL production or hyperproduction of AmpC are responsible for carbapenem resistance in P. aeruginosa. Further attention is required to curb the emergence and spread of new carbapenem-resistant P. aeruginosa clones.

Background: Carbapenem resistance in Pseudomonas aeruginosa is a serious global health problem. We investigated the clonal distribution and its association with the carbapenem resistance mechanisms of carbapenem-non-susceptible P. aeruginosa isolates from three Korean hospitals. Methods: A total of 155 carbapenem-non-susceptible P. aeruginosa isolates collected between 2011 and 2019 were analyzed for sequence types (STs), antimicrobial susceptibility, and carbapenem resistance mechanisms, including carbapenemase production, the presence of resistance genes, OprD mutations, and the hyperproduction of AmpC β-lactamase. Results: Sixty STs were identified in carbapenem-non-susceptible P. aeruginosa isolates.Two high-risk clones, ST235 (N = 41) and ST111 (N = 20), were predominant; however, sporadic STs were more prevalent than high-risk clones. The resistance rate to amikacin was the lowest (49.7%), whereas that to piperacillin was the highest (92.3%). Of the 155 carbapenem-non-susceptible isolates, 43 (27.7%) produced carbapenemases. Three metalloβ-lactamase (MBL) genes, blaIMP-6 (N = 38), blaVIM-2 (N = 3), and blaNDM-1 (N = 2), were detected. blaIMP-6 was detected in clonal complex 235 isolates. Two ST773 isolates carried blaNDM-1 and rmtB. Frameshift mutations in oprD were identified in all isolates tested, regardless of the presence of MBL genes. Hyperproduction of AmpC was detected in MBL gene–negative isolates. Conclusions Frameshift mutations in oprD combined with MBL production or hyperproduction of AmpC are responsible for carbapenem resistance in P. aeruginosa. Further attention is required to curb the emergence and spread of new carbapenem-resistant P. aeruginosa clones.

Background: Carbapenem resistance in Pseudomonas aeruginosa is a serious global health problem. We investigated the clonal distribution and its association with the carbapenem resistance mechanisms of carbapenem-non-susceptible P. aeruginosa isolates from three Korean hospitals. Methods: A total of 155 carbapenem-non-susceptible P. aeruginosa isolates collected between 2011 and 2019 were analyzed for sequence types (STs), antimicrobial susceptibility, and carbapenem resistance mechanisms, including carbapenemase production, the presence of resistance genes, OprD mutations, and the hyperproduction of AmpC β-lactamase. Results: Sixty STs were identified in carbapenem-non-susceptible P. aeruginosa isolates.Two high-risk clones, ST235 (N = 41) and ST111 (N = 20), were predominant; however, sporadic STs were more prevalent than high-risk clones. The resistance rate to amikacin was the lowest (49.7%), whereas that to piperacillin was the highest (92.3%). Of the 155 carbapenem-non-susceptible isolates, 43 (27.7%) produced carbapenemases. Three metalloβ-lactamase (MBL) genes, blaIMP-6 (N = 38), blaVIM-2 (N = 3), and blaNDM-1 (N = 2), were detected. blaIMP-6 was detected in clonal complex 235 isolates. Two ST773 isolates carried blaNDM-1 and rmtB. Frameshift mutations in oprD were identified in all isolates tested, regardless of the presence of MBL genes. Hyperproduction of AmpC was detected in MBL gene–negative isolates. Conclusions Frameshift mutations in oprD combined with MBL production or hyperproduction of AmpC are responsible for carbapenem resistance in P. aeruginosa. Further attention is required to curb the emergence and spread of new carbapenem-resistant P. aeruginosa clones.

Background: Carbapenem resistance in Pseudomonas aeruginosa is a serious global health problem. We investigated the clonal distribution and its association with the carbapenem resistance mechanisms of carbapenem-non-susceptible P. aeruginosa isolates from three Korean hospitals. Methods: A total of 155 carbapenem-non-susceptible P. aeruginosa isolates collected between 2011 and 2019 were analyzed for sequence types (STs), antimicrobial susceptibility, and carbapenem resistance mechanisms, including carbapenemase production, the presence of resistance genes, OprD mutations, and the hyperproduction of AmpC β-lactamase. Results: Sixty STs were identified in carbapenem-non-susceptible P. aeruginosa isolates.Two high-risk clones, ST235 (N = 41) and ST111 (N = 20), were predominant; however, sporadic STs were more prevalent than high-risk clones. The resistance rate to amikacin was the lowest (49.7%), whereas that to piperacillin was the highest (92.3%). Of the 155 carbapenem-non-susceptible isolates, 43 (27.7%) produced carbapenemases. Three metalloβ-lactamase (MBL) genes, blaIMP-6 (N = 38), blaVIM-2 (N = 3), and blaNDM-1 (N = 2), were detected. blaIMP-6 was detected in clonal complex 235 isolates. Two ST773 isolates carried blaNDM-1 and rmtB. Frameshift mutations in oprD were identified in all isolates tested, regardless of the presence of MBL genes. Hyperproduction of AmpC was detected in MBL gene–negative isolates. Conclusions Frameshift mutations in oprD combined with MBL production or hyperproduction of AmpC are responsible for carbapenem resistance in P. aeruginosa. Further attention is required to curb the emergence and spread of new carbapenem-resistant P. aeruginosa clones.

Since the role of the liver in metabolic dysfunction, including type 2 diabetes mellitus, was demonstrated, studies on non-alcoholic fatty liver disease (NAFLD) and metabolic dysfunction-associated fatty liver disease (MAFLD) have shown associations between fatty liver disease and other metabolic diseases. Unlike the exclusionary diagnostic criteria of NAFLD, MAFLD diagnosis is based on the presence of metabolic dysregulation in fatty liver disease. Renaming NAFLD as MAFLD also introduced simpler diagnostic criteria. In 2023, a new nomenclature, steatotic liver disease (SLD), was proposed. Similar to MAFLD, SLD diagnosis is based on the presence of hepatic steatosis with at least one cardiometabolic dysfunction. SLD is categorized into metabolic dysfunction-associated steatotic liver disease (MASLD), metabolic dysfunction and alcohol-related/-associated liver disease, alcoholrelated liver disease, specific etiology SLD, and cryptogenic SLD. The term MASLD has been adopted by a number of leading national and international societies due to its concise diagnostic criteria, exclusion of other concomitant liver diseases, and lack of stigmatizing terms. This article reviews the diagnostic criteria, clinical relevance, and differences among NAFLD, MAFLD, and MASLD from a diabetologist’s perspective and provides a rationale for adopting SLD/MASLD in the Fatty Liver Research Group of the Korean Diabetes Association.

Since the role of the liver in metabolic dysfunction, including type 2 diabetes mellitus, was demonstrated, studies on non-alcoholic fatty liver disease (NAFLD) and metabolic dysfunction-associated fatty liver disease (MAFLD) have shown associations between fatty liver disease and other metabolic diseases. Unlike the exclusionary diagnostic criteria of NAFLD, MAFLD diagnosis is based on the presence of metabolic dysregulation in fatty liver disease. Renaming NAFLD as MAFLD also introduced simpler diagnostic criteria. In 2023, a new nomenclature, steatotic liver disease (SLD), was proposed. Similar to MAFLD, SLD diagnosis is based on the presence of hepatic steatosis with at least one cardiometabolic dysfunction. SLD is categorized into metabolic dysfunction-associated steatotic liver disease (MASLD), metabolic dysfunction and alcohol-related/-associated liver disease, alcoholrelated liver disease, specific etiology SLD, and cryptogenic SLD. The term MASLD has been adopted by a number of leading national and international societies due to its concise diagnostic criteria, exclusion of other concomitant liver diseases, and lack of stigmatizing terms. This article reviews the diagnostic criteria, clinical relevance, and differences among NAFLD, MAFLD, and MASLD from a diabetologist’s perspective and provides a rationale for adopting SLD/MASLD in the Fatty Liver Research Group of the Korean Diabetes Association.

Since the role of the liver in metabolic dysfunction, including type 2 diabetes mellitus, was demonstrated, studies on non-alcoholic fatty liver disease (NAFLD) and metabolic dysfunction-associated fatty liver disease (MAFLD) have shown associations between fatty liver disease and other metabolic diseases. Unlike the exclusionary diagnostic criteria of NAFLD, MAFLD diagnosis is based on the presence of metabolic dysregulation in fatty liver disease. Renaming NAFLD as MAFLD also introduced simpler diagnostic criteria. In 2023, a new nomenclature, steatotic liver disease (SLD), was proposed. Similar to MAFLD, SLD diagnosis is based on the presence of hepatic steatosis with at least one cardiometabolic dysfunction. SLD is categorized into metabolic dysfunction-associated steatotic liver disease (MASLD), metabolic dysfunction and alcohol-related/-associated liver disease, alcoholrelated liver disease, specific etiology SLD, and cryptogenic SLD. The term MASLD has been adopted by a number of leading national and international societies due to its concise diagnostic criteria, exclusion of other concomitant liver diseases, and lack of stigmatizing terms. This article reviews the diagnostic criteria, clinical relevance, and differences among NAFLD, MAFLD, and MASLD from a diabetologist’s perspective and provides a rationale for adopting SLD/MASLD in the Fatty Liver Research Group of the Korean Diabetes Association.

Since the role of the liver in metabolic dysfunction, including type 2 diabetes mellitus, was demonstrated, studies on non-alcoholic fatty liver disease (NAFLD) and metabolic dysfunction-associated fatty liver disease (MAFLD) have shown associations between fatty liver disease and other metabolic diseases. Unlike the exclusionary diagnostic criteria of NAFLD, MAFLD diagnosis is based on the presence of metabolic dysregulation in fatty liver disease. Renaming NAFLD as MAFLD also introduced simpler diagnostic criteria. In 2023, a new nomenclature, steatotic liver disease (SLD), was proposed. Similar to MAFLD, SLD diagnosis is based on the presence of hepatic steatosis with at least one cardiometabolic dysfunction. SLD is categorized into metabolic dysfunction-associated steatotic liver disease (MASLD), metabolic dysfunction and alcohol-related/-associated liver disease, alcoholrelated liver disease, specific etiology SLD, and cryptogenic SLD. The term MASLD has been adopted by a number of leading national and international societies due to its concise diagnostic criteria, exclusion of other concomitant liver diseases, and lack of stigmatizing terms. This article reviews the diagnostic criteria, clinical relevance, and differences among NAFLD, MAFLD, and MASLD from a diabetologist’s perspective and provides a rationale for adopting SLD/MASLD in the Fatty Liver Research Group of the Korean Diabetes Association.

Viral load and the duration of viral shedding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are important determinants of the transmission of coronavirus disease 2019.In this study, we examined the effects of viral doses on the lung and spleen of K18-hACE2 transgenic mice by temporal histological and transcriptional analyses. Approximately, 1×105 plaque-forming units (PFU) of SARS-CoV-2 induced strong host responses in the lungs from 2 days post inoculation (dpi) which did not recover until the mice died, whereas responses to the virus were obvious at 5 days, recovering to the basal state by 14 dpi at 1×102 PFU. Further, flow cytometry showed that number of CD8+ T cells continuously increased in 1×102 PFU-virusinfected lungs from 2 dpi, but not in 1×105 PFU-virus-infected lungs. In spleens, responses to the virus were prominent from 2 dpi, and number of B cells was significantly decreased at 1×105PFU; however, 1×102 PFU of virus induced very weak responses from 2 dpi which recovered by 10 dpi. Although the defense responses returned to normal and the mice survived, lung histology showed evidence of fibrosis, suggesting sequelae of SARS-CoV-2 infection. Our findings indicate that specific effectors of the immune response in the lung and spleen were either increased or depleted in response to doses of SARS-CoV-2. This study demonstrated that the response of local and systemic immune effectors to a viral infection varies with viral dose, which either exacerbates the severity of the infection or accelerates its elimination.

Background: Atopic dermatitis (AD) is a chronic inflammatory cutaneous disorder, that emerges from intricate interplays among genetic predisposition, immune dysregulation, environmental factors, and compromised skin barrier. Understanding the inflammatory pathway in AD is important due to its fundamental role in the pathogenesis of AD. This study aimed to explore the diverse spectrum of proteins linked to the inflammation of AD and the relationship between systemic biomarkers and clinical severity in AD. Methods: We examined the blood samples from 48 patients with AD and 48 healthy controls (HCs) using the Proximity Extension Assay (Olink). Differentially expressed proteins (DEPs) were identified and Pearson correlation analysis was conducted to determine systemic proteomic biomarkers associated with severity of AD. Results: A total of 29 DEPs were significantly up-regulated and 2 DEPs were significantly down-regulated in AD compared with the HC. The MCP-4, IL-18, MCP-3, TNFRSF9, and IL-17C were the top 5 highest DEPs associated with the severity of AD. Conclusion Our study sheds light on the intricate network of inflammatory proteins in AD and their potential implications for disease severity. Our results indicate that these systemic inflammatory proteins could be valuable for assessing AD severity and enhancing our understanding of the disease's complexity and its potential management strategies.