Background: Posterior reversible encephalopathy syndrome (PRES) is a rare complication of lung transplantation with poorly understood risk factors and clinical characteristics. This study aimed to examine the occurrence, risk factors, and clinical data of patients who developed PRES following lung transplantation. Methods: A retrospective analysis was conducted on 147 patients who underwent lung transplantation between February 2013 and December 2023. The patients were diagnosed with PRES based on the clinical symptoms and radiological findings. We compared the baseline characteristics and clinical information, including primary lung diseases and immunosuppressive therapy related to lung transplantation operations, between the PRES and non-PRES groups. Results: PRES manifested in 7.5% (n=11) of the patients who underwent lung transplantation, with a median onset of 15 days after operation. Seizures were identified as the predominant clinical manifestation (81.8%, n=9) in the group diagnosed with PRES. All patients diagnosed with PRES recovered fully. Patients with PRES were significantly associated with connective tissue disease-associated interstitial lung disease (45.5% vs. 18.4%, P=0.019, odds ratio=9.808; 95% CI, 1.064–90.386; P=0.044). Nonetheless, no significant variance was observed in the type of immunotherapy, such as the use of calcineurin inhibitors, blood pressure, or acute renal failure subsequent to lung transplantation. Conclusions PRES typically manifests shortly after lung transplantation, with seizures being the predominant initial symptom. The presence of preexisting connective tissue disease as the primary lung disease represents a significant risk factor for PRES following lung transplantation.

Background: The mortality of sepsis without direct drugs is high. The association between prediabetes, based on a single fasting glucose (FG), or long-term type 2 diabetes mellitus (T2DM) and sepsis remains unclear. Methods: Of the adults aged ≥20 years who were included in the National Health Screening Program (NHSP) in 2009, 40% were randomly sampled. After excluding patients with type 1 diabetes mellitus, with missing information, and who were diagnosed with sepsis during the wash-out (between 2001 and the NHSP) or 1-year lag period, a cohort comprised of 3,863,323 examinees. Body mass index (BMI) measurements, FG tests, and self-reported questionnaires on health-related behaviors were conducted. Individual information was followed up until 2020 and censored upon the first occurrence of sepsis or death. The incidence of sepsis was compared using a multivariable regression adjusted for age, sex, income, BMI, smoking, drinking, physical activity levels, and chronic diseases. Results: The cohort was divided into those with normal FG (n=2,675,476), impaired fasting glucose (IFG) (n=890,402, 23.0%), T2DM <5 years (n=212,391, 5.5%), or T2DM for ≥5 years (n=85,054, 2.2%). The groups with IFG (adjusted hazard ratio [aHR], 1.03; 95% confidence interval [CI], 1.01 to 1.05), T2DM <5 years (aHR, 1.43; 95% CI, 1.40 to 1.47), and T2DM for ≥5 years (aHR, 1.82; 95% CI, 1.77 to 1.87) exhibited significantly higher incidence of sepsis (P<0.001), with the greatest risk in patients with T2DM aged <40 years (aHR, 1.96; 95% CI, 1.71 to 2.25). Conclusion Patients with long-standing and young-onset T2DM show a substantially high risk of sepsis, emphasizing the need for infection prevention and vaccination.

Background: The mortality of sepsis without direct drugs is high. The association between prediabetes, based on a single fasting glucose (FG), or long-term type 2 diabetes mellitus (T2DM) and sepsis remains unclear. Methods: Of the adults aged ≥20 years who were included in the National Health Screening Program (NHSP) in 2009, 40% were randomly sampled. After excluding patients with type 1 diabetes mellitus, with missing information, and who were diagnosed with sepsis during the wash-out (between 2001 and the NHSP) or 1-year lag period, a cohort comprised of 3,863,323 examinees. Body mass index (BMI) measurements, FG tests, and self-reported questionnaires on health-related behaviors were conducted. Individual information was followed up until 2020 and censored upon the first occurrence of sepsis or death. The incidence of sepsis was compared using a multivariable regression adjusted for age, sex, income, BMI, smoking, drinking, physical activity levels, and chronic diseases. Results: The cohort was divided into those with normal FG (n=2,675,476), impaired fasting glucose (IFG) (n=890,402, 23.0%), T2DM <5 years (n=212,391, 5.5%), or T2DM for ≥5 years (n=85,054, 2.2%). The groups with IFG (adjusted hazard ratio [aHR], 1.03; 95% confidence interval [CI], 1.01 to 1.05), T2DM <5 years (aHR, 1.43; 95% CI, 1.40 to 1.47), and T2DM for ≥5 years (aHR, 1.82; 95% CI, 1.77 to 1.87) exhibited significantly higher incidence of sepsis (P<0.001), with the greatest risk in patients with T2DM aged <40 years (aHR, 1.96; 95% CI, 1.71 to 2.25). Conclusion Patients with long-standing and young-onset T2DM show a substantially high risk of sepsis, emphasizing the need for infection prevention and vaccination.

Background: The mortality of sepsis without direct drugs is high. The association between prediabetes, based on a single fasting glucose (FG), or long-term type 2 diabetes mellitus (T2DM) and sepsis remains unclear. Methods: Of the adults aged ≥20 years who were included in the National Health Screening Program (NHSP) in 2009, 40% were randomly sampled. After excluding patients with type 1 diabetes mellitus, with missing information, and who were diagnosed with sepsis during the wash-out (between 2001 and the NHSP) or 1-year lag period, a cohort comprised of 3,863,323 examinees. Body mass index (BMI) measurements, FG tests, and self-reported questionnaires on health-related behaviors were conducted. Individual information was followed up until 2020 and censored upon the first occurrence of sepsis or death. The incidence of sepsis was compared using a multivariable regression adjusted for age, sex, income, BMI, smoking, drinking, physical activity levels, and chronic diseases. Results: The cohort was divided into those with normal FG (n=2,675,476), impaired fasting glucose (IFG) (n=890,402, 23.0%), T2DM <5 years (n=212,391, 5.5%), or T2DM for ≥5 years (n=85,054, 2.2%). The groups with IFG (adjusted hazard ratio [aHR], 1.03; 95% confidence interval [CI], 1.01 to 1.05), T2DM <5 years (aHR, 1.43; 95% CI, 1.40 to 1.47), and T2DM for ≥5 years (aHR, 1.82; 95% CI, 1.77 to 1.87) exhibited significantly higher incidence of sepsis (P<0.001), with the greatest risk in patients with T2DM aged <40 years (aHR, 1.96; 95% CI, 1.71 to 2.25). Conclusion Patients with long-standing and young-onset T2DM show a substantially high risk of sepsis, emphasizing the need for infection prevention and vaccination.

Background: The mortality of sepsis without direct drugs is high. The association between prediabetes, based on a single fasting glucose (FG), or long-term type 2 diabetes mellitus (T2DM) and sepsis remains unclear. Methods: Of the adults aged ≥20 years who were included in the National Health Screening Program (NHSP) in 2009, 40% were randomly sampled. After excluding patients with type 1 diabetes mellitus, with missing information, and who were diagnosed with sepsis during the wash-out (between 2001 and the NHSP) or 1-year lag period, a cohort comprised of 3,863,323 examinees. Body mass index (BMI) measurements, FG tests, and self-reported questionnaires on health-related behaviors were conducted. Individual information was followed up until 2020 and censored upon the first occurrence of sepsis or death. The incidence of sepsis was compared using a multivariable regression adjusted for age, sex, income, BMI, smoking, drinking, physical activity levels, and chronic diseases. Results: The cohort was divided into those with normal FG (n=2,675,476), impaired fasting glucose (IFG) (n=890,402, 23.0%), T2DM <5 years (n=212,391, 5.5%), or T2DM for ≥5 years (n=85,054, 2.2%). The groups with IFG (adjusted hazard ratio [aHR], 1.03; 95% confidence interval [CI], 1.01 to 1.05), T2DM <5 years (aHR, 1.43; 95% CI, 1.40 to 1.47), and T2DM for ≥5 years (aHR, 1.82; 95% CI, 1.77 to 1.87) exhibited significantly higher incidence of sepsis (P<0.001), with the greatest risk in patients with T2DM aged <40 years (aHR, 1.96; 95% CI, 1.71 to 2.25). Conclusion Patients with long-standing and young-onset T2DM show a substantially high risk of sepsis, emphasizing the need for infection prevention and vaccination.

Purpose: We aimed to comprehensively analyze the immune cell and stromal components of tumor microenvironment at the single-cell level and identify tumor heterogeneity among the major top-derived oncogene mutations in non-small cell lung cancer (NSCLC) using single-cell RNA sequencing (scRNA-seq) data. Materials and Methods: The scRNA-seq dataset utilized in this study comprised 64369 primary tumor tissue cells from 21 NSCLC patients, focusing on mutations in EGFR, ALK, BRAF, KRAS, TP53, and the wild-type. Results: Tumor immune microenvironment (TIM) analysis revealed differential immune responses across NSCLC mutation subtypes. TIM analysis revealed different immune responses across the mutation subtypes. Two mutation clusters emerged: KRAS, TP53, and EGFR+TP53 mutations (MC1); and EGFR, BRAF, and ALK mutations (MC2). MC1 showed higher tertiary lymphoid structures signature scores and enriched populations of C2-T-IL7R, C3-T/NK-CXCL4, C9-T/NK-NKG, and C1-B-MS4A1 clusters than cluster 2. Conversely, MC2 cells exhibited higher expression levels of TNF, IL1B, and chemokines linked to alternative immune pathways. Remarkably, co-occurring EGFR and TP53 mutations were grouped as MC1. EGFR+TP53 mutations showed upregulation of peptide synthesis and higher synthetic processes, as well as differences in myeloid and T/NK cells compared to EGFR mutations. In T/NK cells, EGFR+TP53 mutations showed a higher expression of features related to cell activity and differentiation, whereas EGFR mutations showed the opposite. Conclusion Our research indicates a close association between mutation types and tumor microenvironment in NSCLC, offering insights into personalized approaches for cancer diagnosis and treatment.

Purpose: We aimed to comprehensively analyze the immune cell and stromal components of tumor microenvironment at the single-cell level and identify tumor heterogeneity among the major top-derived oncogene mutations in non-small cell lung cancer (NSCLC) using single-cell RNA sequencing (scRNA-seq) data. Materials and Methods: The scRNA-seq dataset utilized in this study comprised 64369 primary tumor tissue cells from 21 NSCLC patients, focusing on mutations in EGFR, ALK, BRAF, KRAS, TP53, and the wild-type. Results: Tumor immune microenvironment (TIM) analysis revealed differential immune responses across NSCLC mutation subtypes. TIM analysis revealed different immune responses across the mutation subtypes. Two mutation clusters emerged: KRAS, TP53, and EGFR+TP53 mutations (MC1); and EGFR, BRAF, and ALK mutations (MC2). MC1 showed higher tertiary lymphoid structures signature scores and enriched populations of C2-T-IL7R, C3-T/NK-CXCL4, C9-T/NK-NKG, and C1-B-MS4A1 clusters than cluster 2. Conversely, MC2 cells exhibited higher expression levels of TNF, IL1B, and chemokines linked to alternative immune pathways. Remarkably, co-occurring EGFR and TP53 mutations were grouped as MC1. EGFR+TP53 mutations showed upregulation of peptide synthesis and higher synthetic processes, as well as differences in myeloid and T/NK cells compared to EGFR mutations. In T/NK cells, EGFR+TP53 mutations showed a higher expression of features related to cell activity and differentiation, whereas EGFR mutations showed the opposite. Conclusion Our research indicates a close association between mutation types and tumor microenvironment in NSCLC, offering insights into personalized approaches for cancer diagnosis and treatment.

Background: We aimed to identify the risk of incident depression according to cumulative exposure to a low-household income status in individuals with type 2 diabetes mellitus (T2DM). Methods: For this retrospective longitudinal population-based cohort study, we used Korean National Health Insurance Service data from 2002 to 2018. Risk of depression was assessed according to cumulative exposure to low-household income status (defined as Medical Aid registration) during the previous 5 years among adults (aged ≥20 years) with T2DM and without baseline depression who underwent health examinations from 2009 to 2012 (n=2,027,317). Results: During an average 6.23 years of follow-up, 401,175 incident depression cases occurred. Advance in cumulative number of years registered for medical aid during the previous 5 years from baseline was associated with an increased risk of depression in a dose-dependent manner (hazard ratio [HR], 1.44 [95% confidence interval (CI), 1.38 to 1.50]; HR, 1.40 [95% CI, 1.35 to 1.46]; HR, 1.42, [95% CI, 1.37 to 1.48]; HR, 1.46, [95% CI, 1.40 to 1.53]; HR, 1.69, [95% CI, 1.63 to 1.74] in groups with 1 to 5 exposed years, respectively). Insulin users exposed for 5 years to a low-household income state had the highest risk of depression among groups categorized by insulin use and duration of low-household income status. Conclusion Cumulative duration of low-household income status, defined as medical aid registration, was associated with an increased risk of depression in a dose-response manner in individuals with T2DM.

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: Alzheimer’s disease (AD) dementia may not be a single disease entity. Early-onset AD (EOAD) and late-onset AD (LOAD) have been united under the same eponym of AD until now, but disentangling the heterogeneity according to the age of sonset has been a major tenet in the field of AD research. Materials and Methods: Ninety-nine patients with AD (EOAD, n=54; LOAD, n=45) and 66 cognitively normal controls completed both [18F]THK5351 and [18F]flutemetamol (FLUTE) positron emission tomography scans along with structural magnetic resonance imaging and detailed neuropsychological tests. Results: EOAD patients had higher THK retention in the precuneus, parietal, and frontal lobe, while LOAD patients had higher THK retention in the medial temporal lobe. Intravoxel correlation analyses revealed that EOAD presented narrower territory of local FLUTE-THK correlation, while LOAD presented broader territory of correlation extending to overall parieto-occipito-temporal regions. EOAD patients had broader brain areas which showed significant negative correlations between cortical thickness and THK retention, whereas in LOAD, only limited brain areas showed significant correlation with THK retention. In EOAD, most of the cognitive test results were correlated with THK retention. However, a few cognitive test results were correlated with THK retention in LOAD. Conclusion LOAD seemed to show gradual increase in tau and amyloid, and those two pathologies have association to each other. On the other hand, in EOAD, tau and amyloid may develop more abruptly and independently. These findings suggest LOAD and EOAD may have different courses of pathomechanism.