Developmental self-reactivity determines pathogenic Tc17 differentiation potential of naive CD8+ T cells in murine models of inflammation.

The differentiation of naive CD8+ T cells into effector cells is important for establishing immunity. However, the effect of heterogeneous naive CD8+ T cell populations is not fully understood. Here, we demonstrate that steady-state naive CD8+ T cells are composed of functionally heterogeneous subpopulations that differ in their ability to differentiate into type 17 cytotoxic effector cells (Tc17) in a context of murine inflammatory disease models, such as inflammatory bowel disease and graft-versus-host disease. The differential ability of Tc17 differentiation is not related to T-cell receptor (TCR) diversity and antigen specificity but is inversely correlated with self-reactivity acquired during development. Mechanistically, this phenomenon is linked to differential levels of intrinsic TCR sensitivity and basal Suppressor of Mothers Against Decapentaplegic 3 (SMAD3) expression, generating a wide spectrum of Tc17 differentiation potential within naive CD8+ T cell populations. These findings suggest that developmental self-reactivity can determine the fate of naive CD8+ T cells to generate functionally distinct effector populations and achieve immense diversity and complexity in antigen-specific T-cell immune responses.

Prognostic factors for clinical outcomes after arthroscopic treatment of traumatic central tears of the triangular fibrocartilage complex.

Aims: The study aimed to assess the clinical outcomes of arthroscopic debridement and partial excision in patients with traumatic central tears of the triangular fibrocartilage complex (TFCC), and to identify prognostic factors associated with unfavourable clinical outcomes. Methods: A retrospective analysis was conducted on patients arthroscopically diagnosed with Palmer 1 A lesions who underwent arthroscopic debridement and partial excision from March 2009 to February 2021, with a minimum follow-up of 24 months. Patients were assessed using the Disabilities of the Arm, Shoulder and Hand (DASH) questionnaire, Mayo Wrist Score (MWS), and visual analogue scale (VAS) for pain. The poor outcome group was defined as patients whose preoperative and last follow-up clinical score difference was less than the minimal clinically important difference of the DASH score (10.83). Baseline characteristics, arthroscopic findings, and radiological factors (ulnar variance, MRI, or arthrography) were evaluated to predict poor clinical outcomes. Results: A total of 114 patients were enrolled in this study, with a mean follow-up period of 29.8 months (SD 14.4). The mean DASH score improved from 36.5 (SD 21.5) to 16.7 (SD 14.3), the mean MWS from 59.7 (SD 17.9) to 79.3 (SD 14.3), and the mean VAS pain score improved from 5.9 (SD 1.8) to 2.2 (SD 2.0) at the last follow-up (all p < 0.001). Among the 114 patients, 16 (14%) experienced poor clinical outcomes and ten (8.8%) required secondary ulnar shortening osteotomy. Positive ulnar variance was the only factor significantly associated with poor clinical outcomes (p < 0.001). Positive ulnar variance was present in 38 patients (33%); among them, eight patients (21%) required additional operations. Conclusion: Arthroscopic debridement alone appears to be an effective and safe initial treatment for patients with traumatic central TFCC tears. The presence of positive ulnar variance was associated with poor clinical outcomes, but close observation after arthroscopic debridement is more likely to be recommended than ulnar shortening osteotomy as a primary treatment.

Prediction of xerostomia in elderly based on clinical characteristics and salivary flow rate with machine learning.

Xerostomia may be accompanied by changes in salivary flow rate and the incidence increases in elderly. We aimed to use machine learning algorithms, to identify significant predictors for the presence of xerostomia. This study is the first to predict xerostomia with salivary flow rate in elderly based on artificial intelligence. In a cross-sectional study, 829 patients with oral discomfort were enrolled, and six features (sex, age, unstimulated and stimulated salivary flow rates (UFR and SFR, respectively), number of systemic diseases, and medication usage) were used in four machine learning algorithms to predict the presence of xerostomia. The incidence of xerostomia increased with age. The SFR was significantly higher than the UFR, and the UFR and SFR were significantly correlated. The UFR, but not SFR, decreased with age significantly. In patients more than 60 years of age, the UFR had a significantly higher predictive accuracy for xerostomia than the SFR. Using machine learning algorithms with tenfold cross-validation, the prediction accuracy increased significantly. In particular, the prediction accuracy of the multilayer perceptron (MLP) algorithm that combined UFR and SFR data was significantly better than either UFR or SFR individually. Moreover, when sex, age, number of systemic diseases, and number of medications were added to the MLP model, the prediction accuracy increased from 56 to 68%.

Comparison of the new-Poisoning Mortality Score and the Modified Early Warning Score for predicting in-hospital mortality in patients with acute poisoning.

INTRODUCTION: The evaluation of acute poisoning is challenging due to varied toxic substances and clinical presentations. The new-Poisoning Mortality Score was recently developed to assess patients with acute poisoning and showed good performance in predicting in-hospital mortality. The objective of this study is to externally validate the performance of the new-Poisoning Mortality Score and to compare it with the Modified Early Warning Score. METHODS: This retrospective analysis used data from the 2019-2020 Injury Surveillance Cohort, established by the Korea Center for Disease Control and Prevention, to perform external validation of the new-Poisoning Mortality Score. The statistical performances of the new-Poisoning Mortality and Modified Early Warning Scores were assessed and compared in terms of discrimination and calibration. Discrimination analysis involved metrics such as sensitivity, specificity, accuracy, and the area under the receiver operating characteristic curve. For calibration analysis, the Hosmer-Lemeshow goodness-of-fit test was utilized and calibration curves for each score were generated to elucidate the relationship between observed and predicted mortalities. RESULTS: This study analysed 16,570 patients with acute poisoning. Significant differences were observed between survivors and those who died in-hospital, including age, sex, and vital signs. The new-Poisoning Mortality Score showed better performance over the Modified Early Warning Score in predicting in-hospital mortality, in terms of the area under the receiver operating characteristic curve (0.947 versus 0.800), sensitivity (0.863 versus 0.667), specificity (0.912 versus 0.817), and accuracy (0.911 versus 0.814). When evaluated through calibration curves, the new-Poisoning Mortality Score showed better concordance between predicted and observed mortalities. In subgroup analyses, the score system consistently showed strong performance, excelling particularly in substances with high mortality indices and remaining superior in all substances as a group. CONCLUSIONS: Our study has helped to validate the new-Poisoning Mortality Score as an effective tool for predicting in-hospital mortality in patients with acute poisoning in the emergency department. The score system demonstrated superior performance over the Modified Early Warning Score in various metrics. Our findings suggest that the new-Poisoning Mortality Score can contribute to the enhancement of clinical decision-making and patient management.

Relationship between urinary potassium excretion, serum potassium levels and cardiac injury in non-dialysis chronic kidney disease: KoreaN cohort study for Outcome in patients With Chronic Kidney Disease (KNOW-CKD).

Although the cardiovascular benefits of an increased urinary potassium excretion have been suggested, little is known about the potential cardiac association of urinary potassium excretion in patients with chronic kidney disease. In addition, whether the cardiac association of urinary potassium excretion was mediated by serum potassium levels has not been studied yet. We reviewed the data of 1633 patients from a large-scale multicentre prospective Korean study (2011-2016). Spot urinary potassium to creatinine ratio was used as a surrogate for urinary potassium excretion. Cardiac injury was defined as a high-sensitivity troponin T ≥ 14 ng/l. OR and 95 % (CI for cardiac injury were calculated using logistic regression analyses. Of 1633 patients, the mean spot urinary potassium to creatinine ratio was 49·5 (sd 22·6) mmol/g Cr and the overall prevalence of cardiac injury was 33·9 %. Although serum potassium levels were not associated with cardiac injury, per 10 mmol/g Cr increase in the spot urinary potassium to creatinine ratio was associated with decreased odds of cardiac injury: OR 0·917 (95 % CI 0·841, 0·998), P = 0·047) in multivariate logistic regression analysis. In mediation analysis, approximately 6·4 % of the relationship between spot urinary potassium to creatinine ratio and cardiac injury was mediated by serum potassium levels, which was not statistically significant (P = 0·368). Higher urinary potassium excretion was associated with lower odds of cardiac injury, which was not mediated by serum potassium levels.

A deep learning segmentation method to assess dose to organs at risk during breast radiotherapy.

Background and purpose: Contouring of organs at risk is important for studying health effects following breast radiotherapy. However, manual contouring is time-consuming and subject to variability. The purpose of this study was to develop a deep learning-based method to automatically segment multiple structures on breast radiotherapy planning computed tomography (CT) images. Materials and methods: We used data from 118 patients, including 90 diagnostic CT scans with expert structure delineations for training and 28 breast radiotherapy planning CT images for testing. The radiotherapy CT images also had expert delineations for evaluating performance. We targeted a total of eleven organs at risk including five heart substructures. Segmentation performance was evaluated using the metrics of Dice similarity coefficient (DSC), overlap fraction, volume similarity, Hausdorff distance, mean surface distance, and dose. Results: The average DSC achieved on the radiotherapy planning images was 0.94 ± 0.02 for the whole heart, 0.96 ± 0.02 and 0.97 ± 0.01 for the left and right lung, 0.61 ± 0.10 for the esophagus, 0.81 ± 0.04 and 0.86 ± 0.04 for left and right atrium, 0.91 ± 0.02 and 0.84 ± 0.04 for left and right ventricle, and 0.21 ± 0.11 for the left anterior descending artery (LAD), respectively. Except for the LAD, the median difference in mean dose to these structures was small with absolute (relative) differences < 0.1 Gy (6 %). Conclusions: Except for the LAD, our method demonstrated excellent performance and can be generalized to segment additional structures of interest.

The impact of C-reactive protein-to-albumin ratio on mortality in patients with acute kidney injury requiring continuous renal replacement therapy: A multicenter retrospective study.

INTRODUCTION: C-reactive protein-to-albumin ratio (CAR) is a prognostic marker in various diseases that represents patients' inflammation and nutritional status. Here, we aimed to investigate the prognostic value of CAR in critically ill patients with severe acute kidney injury (AKI) requiring continuous renal replacement therapy (CRRT). METHODS: We retrospectively collected data from eight tertiary hospitals in Korea from 2006-2021. The patients were divided into quartiles according to CAR levels at the time of CRRT initiation. Cox regression analyses were performed to investigate the effect of CAR on in-hospital mortality. The mortality prediction performance of CAR was evaluated using the area under the curve (AUC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI). RESULTS: In total, 3995 patients who underwent CRRT were included, and the in-hospital mortality rate was 67.3% during the follow-up period. The 7-day, 30-day, and in-hospital mortality rates increased toward higher CAR quartiles (all P < 0.001). After adjusting for confounding variables, the higher quartile groups had an increased risk of in-hospital mortality (quartile 3: adjusted hazard ratio [aHR], 1.26, 95% confidence interval [CI], 1.10-1.43, P < 0.001; quartile 4: aHR, 1.22, 95% CI, 1.07-1.40, P = 0.003). CAR combined with APACHE II or SOFA scores significantly increased the predictive power compared to each severity score alone for the AUC, NRI, and IDI (all P < 0.05). CONCLUSIONS: A high CAR is associated with increased in-hospital mortality in critically ill patients requiring CRRT. The combined use of CAR and severity scores provides better predictive performance for mortality than the severity score alone.

CD5 Expression Dynamically Changes During the Differentiation of Human CD8+ T Cells Predicting Clinical Response to Immunotherapy.

Defining the molecular dynamics associated with T cell differentiation enhances our understanding of T cell biology and opens up new possibilities for clinical implications. In this study, we investigated the dynamics of CD5 expression in CD8+ T cell differentiation and explored its potential clinical uses. Using PBMCs from 29 healthy donors, we observed a stepwise decrease in CD5 expression as CD8+ T cells progressed through the differentiation stages. Interestingly, we found that CD5 expression was initially upregulated in response to T cell receptor stimulation, but diminished as the cells underwent proliferation, potentially explaining the differentiation-associated CD5 downregulation. Based on the proliferation-dependent downregulation of CD5, we hypothesized that relative CD5 expression could serve as a marker to distinguish the heterogeneous CD8+ T cell population based on their proliferation history. In support of this, we demonstrated that effector memory CD8+ T cells with higher CD5 expression exhibited phenotypic and functional characteristics resembling less differentiated cells compared to those with lower CD5 expression. Furthermore, in the retrospective analysis of PBMCs from 30 non-small cell lung cancer patients, we found that patients with higher CD5 expression in effector memory T cells displayed CD8+ T cells with a phenotype closer to the less differentiated cells, leading to favorable clinical outcomes in response to immune checkpoint inhibitor (ICI) therapy. These findings highlight the dynamics of CD5 expression as an indicator of CD8+ T cell differentiation status, and have implications for the development of predictive biomarker for ICI therapy.

Modeling and investigation of swelling kinetics of sodium carboxymethyl cellulose/starch/citric acid superabsorbent polymer.

Crosslinked hydrophilic polymers with high water absorption rates are known as superabsorbent polymers (SAPs). Most commercial superabsorbent polymers are made with acrylic acid, which is difficult to biodegrade. So, in this investigation, carboxymethyl cellulose (CMC) was utilized as a significant component in the synthesis of polysaccharide-based SAPs. Citric acid (CA) and starch were chosen as crosslinking agents because they are more eco-friendly, non-toxic, and biodegradable than traditional crosslinking agents. FTIR analysis revealed that the superabsorbent polymer product contains a crosslinked structure of CMC and starch with side chains that carry carboxylate functional groups. Superabsorbent weight loss and grafting data were satisfactorily studied using the TGA approach. Under optimum circumstances, the SAP2 water absorbency capacity in distilled water was 287.37 g.g-1 and SAP1 absorbency capacity in a solution containing 0.9 wt% NaCl was 52.18 g.g-1. Moreover, Schott's pseudo-second-order model was used to determine the kinetic swelling of the superabsorbent. The initial swelling rate of SAPs can be calculated using the Q∞ data acquired in the following order: SAP2 > SAP1 > SAP3 > SAP4 in distilled water and SAP1 > SAP2 > SAP3 > SAP4 in 0.9 wt% NaCl solution, respectively. The findings suggested that a small amount of citric acid introduced into the SAPs matrix could enhance the swelling rate of SAPs. The results of the cytotoxicity tests show that the extraction liquid of composite hydrogel fibers is less cytotoxic than the positive control. As well, SAP underwent in silico docking investigations on the DNA Gyrase enzyme. As the ligand is a monomer of SAP, it was a long chain of carbohydrate molecules with alcoholic groups, esters groups, and keto groups forms a strong binding interaction with DNA gyrase.

Machine Learning-Based Models for Prediction of Critical Illness at Community, Paramedic, and Hospital Stages.

Overcrowding of emergency department (ED) has put a strain on national healthcare systems and adversely affected the clinical outcomes of critically ill patients. Early identification of critically ill patients prior to ED visits can help induce optimal patient flow and allocate medical resources effectively. This study aims to develop ML-based models for predicting critical illness in the community, paramedic, and hospital stages using Korean National Emergency Department Information System (NEDIS) data. Random forest and light gradient boosting machine (LightGBM) were applied to develop predictive models. The predictive model performance based on AUROC in community stage, paramedic stage, and hospital stage was estimated to be 0.870 (95% CI: 0.869-0.871), 0.897 (95% CI: 0.896-0.898), and 0.950 (95% CI: 0.949-0.950) in random forest and 0.877 (95% CI: 0.876-0.878), 0.899 (95% CI: 0.898-0.900), and 0.950 (95% CI: 0.950-0.951) in LightGBM, respectively. The ML models showed high performance in predicting critical illness using variables available at each stage, which can be helpful in guiding patients to appropriate hospitals according to their severity of illness. Furthermore, a simulation model can be developed for proper allocation of limited medical resources.

ATF6 is a critical regulator of cadmium-mediated apoptosis in spermatocytes.

In this study, we examined the mechanisms of cadmium exposure-induced endoplasmic reticulum (ER) stress response and apoptosis in spermatocytes. Responses to cadmium toxicity were investigated using spermatocytes overexpressing p50ATF6, ATF4, and spliced XBP1s, belonging to the 3 unfolded protein response pathways. The ER stress and apoptosis response to cadmium were most strongly stimulated through the activating transcription factor 6 (ATF6) pathway; in contrast, siRNA-induced inhibition of protein expression could reduce apoptosis under stressful conditions. An in vivo experiment using mice confirmed that upregulation of p50ATF6 in the testis increased apoptosis in response to cadmium exposure. Further, when confirming the correlation between ER stress and MAPK in cadmium toxicity, p38 MAPK phosphorylation was strongly regulated by p50ATF6; p-p38 also mediated the activity of p50ATF6. Overall, these findings suggest that modulating the activity of p38 MAPK and p50ATF6 in cadmium exposure-induced toxicity can be considered a potential strategy to treat infertility.

Effects of Ni/Al2O3 catalyst treatment condition on thermocatalytic conversion of spent disposable wipes.

Municipal solid waste (MSW) management is an essential municipal service. Proper waste treatment is an important part of the waste management. Thermocatalytic waste upcycling has recently gained great interest and attention as a method to extract value from waste, which potentially substitutes traditional waste treatment methods. This study aims at demonstrating the potential for thermocatalytic waste upcycling using spent disposable wipes as an MSW surrogate. Two different Ni/Al2O3 catalysts were prepared, treated under two different atmospheres (N2 and CO2). The catalyst treated in N2 (Ni/Al2O3-N2) exhibited a higher surface metallic Ni site than the catalyst treated in CO2 (Ni/Al2O3-CO2). The use of the Ni/Al2O3-N2 increased the yield of gas pyrolysate and decreased the yield of byproduct (e.g., wax), compared with no catalyst and the Ni/Al2O3-CO2. In particular, the Ni/Al2O3-N2 catalyst affected the generation of gaseous hydrogen (H2) by increasing the H2 yield by up to 102% in comparison with the other thermocatalytic systems. The highest H2 yield obtained with the Ni/Al2O3-N2 was attributed to the most surface metallic Ni sites. However, the Ni/Al2O3-N2 catalyst led to char having a lower higher heating value than the other catalysts due to its lowest carbon content. The results indicated that the reduction treatment environment for Ni/Al2O3 catalyst influences thermocatalytic conversion product yields of spent disposable wipes, including enhanced H2 production. Electronic Supplementary Material: Supplementary material is available in the online version of this article at 10.1007/s11814-023-1461-8.

The effects of muscle mass and quality on mortality of patients with acute kidney injury requiring continuous renal replacement therapy.

This study examined the effects of muscle mass on mortality in patients with acute kidney injury requiring continuous renal replacement therapy. It was conducted in eight medical centers between 2006 and 2021. The data of 2200 patients over the age of 18 years with acute kidney injury who required continuous renal replacement therapy were retrospectively collected. Skeletal muscle areas, categorized into normal and low attenuation muscle areas, were obtained from computed tomography images at the level of the third lumbar vertebra. Cox proportional hazards models were used to investigate the association between mortality within 1, 3, and 30 days and skeletal muscle index. Sixty percent of patients were male, and the 30-day mortality rate was 52%. Increased skeletal muscle areas/body mass index was associated with decreased mortality risk. We also identified a 26% decreased risk of low attenuation muscle area/body mass index on mortality. We established that muscle mass had protective effects on the mortality of patients with acute kidney injury requiring continuous renal replacement therapy. This study showed that muscle mass is a significant determinant of mortality, even if the density is low.

Mitochondrial peroxiredoxin 5 overexpression suppresses insulin-induced adipogenesis by downregulating the phosphorylation of p38.

Obesity is caused by the accumulation of excess lipids due to an energy imbalance. Differentiation of pre-adipocytes induces abnormal lipid accumulation, and reactive oxygen species (ROS) generated in this process promote the differentiation of pre-adipocytes through mitogen-activated protein kinase (MAPK) signaling. Peroxiredoxin (Prx) is a potent antioxidant enzyme, and peroxiredoxin 5 (Prx5), which is mainly expressed in cytosol and mitochondria, inhibits adipogenesis by regulating ROS levels. Based on previous findings, the present study was performed to investigate whether cytosolic Prx5 (CytPrx5) or mitochondrial Prx5 (MtPrx5) has a greater effect on the inhibition of adipogenesis. In this study, MtPrx5 decreased insulin-mediated ROS levels to reduce adipogenic gene expression and lipid accumulation more effectively than CytPrx5. In addition, we found that p38 MAPK mainly participates in adipogenesis. Furthermore, we verified that MtPrx5 overexpression suppressed the phosphorylation of p38 during adipogenesis. Thus, we suggest that MtPrx5 inhibits insulin-induced adipogenesis more effectively than CytPrx5.

Selective recovery of caprolactam from the thermo-catalytic conversion of textile waste over γ-Al2O3 supported metal catalysts.

The massive generation of synthetic textile waste has drawn considerable attention. Landfilling/incineration of textile waste has been widely made. To abate the environmental burdensome from the conventional management processes, a thermo-catalytic conversion was used for rapid volume reduction of textile waste and simultaneous valorization by recovering textile monomer in this study. Stockings were chosen as a model feedstock. Because stockings consisted of nylon with other contents, different products (caprolactam (nylon monomer), imines, cyclic dimers, and azepines) were recovered. The yield of caprolactam from the thermal conversion at 500 °C was 53.6 wt%. To selectively enhance the caprolactam yield, catalytic pyrolysis was done using γ-Al2O3 supported metal catalysts (Ni, Cu, Fe, or Co). γ-Al2O3 itself increased the caprolactam yield up to 69.0 wt% via a based-catalyzed reaction of nylon depolymerization and intramolecular cyclization. Under the presence of metal catalysts, the caprolactam yield increased up to 73.3 wt%. To offer desired feature of green chemistry, CO2 was adopted as reactive gas. Under the CO2-mediated catalytic pyrolysis, caprolactam yield was enhanced up to 77.1 wt% over Cu/Al2O3 (basis: stocking mass). Based on the net content of nylon in the stockings, the yield of caprolactam was deemed 95.3 wt%. This study proves that textile waste (stocking) and CO2 are useful resources for recovery of nylon monomer, which can reduce the waste generation with simultaneous recovery of value-added product.

Building of Pediatric COVID-19 Module Clinic: A Novel Operation Model in Response to COVID-19 Pandemic.

In mid-2022, as the wave of pediatric coronavirus disease 2019 (COVID-19) cases escalated in South Korea, a public-private partnership was made to establish a Pediatric COVID-19 Module Clinic (PMC). We describe the utilization of the first prototype children's modular clinic in Korea University Anam Hospital functioning as the COVID-19 PMC. Between August 1 and September 30, 2022, a total of 766 children visited COVID-19 PMC. Daily number of patient visits to the COVID-19 PMC ranged between 10 and 47 in August; and less than 13 patients per day in September 2022. Not only the model provided timely care for the COVID-19 pediatric patients, but it also enabled safe and efficacious care for the non-COVID-19 patients in the main hospital building while minimizing exposure risk to severe acute respiratory syndrome coronavirus 2 transmission. Current description highlights the importance of spatial measures for mitigating in-hospital transmission of COVID-19, in specifically on pediatric care.

Dynamic nature and prognostic value of the neutrophil-to-lymphocyte ratio in critically ill patients with acute kidney injury on continuous renal replacement therapy: A multicenter cohort study.

Introduction: Patients with acute kidney injury (AKI) receiving renal replacement therapy constitute the subgroup of AKI with the highest risk of mortality. Despite recent promising findings on the neutrophil-to-lymphocyte ratio (NLR) in AKI, studies have not yet addressed the clinical implication of the NLR in this population. Therefore, we aimed to examine the prognostic value of NLR in critically ill patients requiring continuous renal replacement therapy (CRRT), especially focusing on temporal changes in NLR. Methods: We enrolled 1,494 patients with AKI who received CRRT in five university hospitals in Korea between 2006 and 2021. NLR fold changes were calculated as the NLR on each day divided by the NLR value on the first day. We performed a multivariable Cox proportional hazard analysis to assess the association between the NLR fold change and 30-day mortality. Results: The NLR on day 1 did not differ between survivors and non-survivors; however, the NLR fold change on day 5 was significantly different. The highest quartile of NLR fold change during the first 5 days after CRRT initiation showed a significantly increased risk of death (hazard ratio [HR], 1.65; 95% confidence intervals (CI), 1.27-2.15) compared to the lowest quartile. NLR fold change as a continuous variable was an independent predictor of 30-day mortality (HR, 1.14; 95% CI, 1.05-1.23). Conclusion: In this study, we demonstrated an independent association between changes in NLR and mortality during the initial phase of CRRT in AKI patients receiving CRRT. Our findings provide evidence for the predictive role of changes in the NLR in this high-risk subgroup of AKI.

Shaping Heterogeneity of Naive CD8+ T Cell Pools.

Immune diversification helps protect the host against a myriad of pathogens. CD8+ T cells are essential adaptive immune cells that inhibit the spread of pathogens by inducing apoptosis in infected host cells, ultimately ensuring complete elimination of infectious pathogens and suppressing disease development. Accordingly, numerous studies have been conducted to elucidate the mechanisms underlying CD8+ T cell activation, proliferation, and differentiation into effector and memory cells, and to identify various intrinsic and extrinsic factors regulating these processes. The current knowledge accumulated through these studies has led to a huge breakthrough in understanding the existence of heterogeneity in CD8+ T cell populations during immune response and the principles underlying this heterogeneity. As the heterogeneity in effector/memory phases has been extensively reviewed elsewhere, in the current review, we focus on CD8+ T cells in a "naïve" state, introducing recent studies dealing with the heterogeneity of naive CD8+ T cells and discussing the factors that contribute to such heterogeneity. We also discuss how this heterogeneity contributes to establishing the immense complexity of antigen-specific CD8+ T cell response.

Blood-Based Biomarker Analysis for Predicting Efficacy of Chemoradiotherapy and Durvalumab in Patients with Unresectable Stage III Non-Small Cell Lung Cancer.

We recruited 50 patients with unresectable stage III NSCLC who received CCRT between March 2020 and March 2021. Durvalumab consolidation (DC) was administered to patients (n = 23) without progression after CCRT and programmed death-ligand 1 (PD-L1) ≥ 1%. Blood samples were collected before (C0) and after CCRT (C1) to calculate PBC counts and analyze CTCs. CTCs, isolated by the CD-PRIMETM system, exhibited EpCAM/CK+/CD45- phenotype in BioViewCCBSTM. At median follow-up of 27.4 months, patients with residual CTC clusters at C1 had worse median PFS than those without a detectable CTC cluster (11.0 vs. 27.8 months, p = 0.032), and this trend was noted only in the DC group (p = 0.034). Patients with high platelets at C1 (PLThi, >252 × 103/µL) had worse median PFS than those with low platelets (PLTlo) (5.9 vs. 17.1 months, p < 0.001). In multivariable analysis, PLThi and residual CTC clusters at C1 were independent risk factors for PFS, and DC group with PLThi and residual CTC clusters at C1 showed the worst median PFS (2.6 months, HR 45.16, p = 0.001), even worse than that of the CCRT alone group with PLThi (5.9 months, HR 15.39, p = 0.001). The comprehensive analysis of CTCs and PBCs before and after CCRT revealed that the clearance of CTC clusters and platelet counts at C1 might be potential biomarkers for predicting survival.

Self-rated health and the risk of incident chronic kidney disease: a community-based Korean study.

BACKGROUND: The relationship between self-rated health (SRH) and the development of incident chronic kidney disease (CKD) has not been explored in the general population. METHODS: We reviewed the data of 7027 participants in the Ansung-Ansan cohort study. SRH was categorized as poor, fair, or good, and the outcome was the development of CKD, defined as the first event of an estimated glomerular filtration rate < 60 mL/min/1.73 m2, at least twice during the follow-up period. Hazard ratios (HRs) and confidence intervals (CIs) were calculated using Cox proportional hazards regression analysis. RESULTS: Over a mean follow-up duration of 11.9 years, 951 participants (13.5%) developed CKD. Compared with poor self-rated health, the HR (95% CI) of fair self-rated health for incident CKD development was 0.771 (0.657-0.905; P = 0.001), whereas that of good self-rated health was 0.795 (0.676-0.935; P = 0.006). However, the renal hazard of good self-rated health did not differ from that of fair self-rated health. In the fully adjusted model, the HR (95% CI) of poor self-rated health compared to non-poor self-rated health for incident CKD was 1.278 (1.114-1.465, P < 0.001). Old age, smoking, cardiovascular disease, diabetes, hypertension, impaired sleep, and high levels of C-reactive protein and white blood cell counts were associated with increased odds of poor self-rated health, whereas male sex, college graduate level of education, and alcohol consumption were associated with decreased odds of poor self-rated health. CONCLUSION: Poor self-rated health is independently associated with CKD development. Therefore, the early detection of potential CKD patients through a brief questionnaire assessment may help control the incidence of CKD.