Immunosenescence, an age-associated decline in immune function, is increasingly recognized as a central determinant of health and disease in older adults. Characterized by thymic involution, loss of naïve T cells, contraction of T cell receptor diversity, accumulation of senescent and exhausted lymphocytes, and a chronic inflammatory state known as inflammaging, immunosenescence compromises both innate and adaptive immune responses. Immunosenescence contributes to the pathogenesis of diverse age-related diseases. In autoimmune and metabolic diseases, premature accumulation of senescent T cells and impaired regulatory T cell function drive chronic inflammation and tissue damage, while in neurodegenerative diseases, microglial aging and sustained neuroinflammation exacerbate neuronal loss. These findings highlight immunosenescence as a unifying mechanism linking aging to systemic and organ-specific pathologies. Advances in biomarker discovery, including phenotypic markers, telomere attrition, and epigenetic signatures, have enabled the quantitative assessment of immune aging, while emerging therapeutic strategies, such as cytokine modulation, mTOR inhibition, senolytics, and epigenetic reprogramming, show promise in restoring immune competence. Here, we summarize recent research on immunosenescence in various diseases, particularly chronic inflammatory, metabolic, and neurodegenerative diseases, and suggest novel strategies for the development of senolytic drugs.

Purpose: This study aimed to develop a digital multimedia-based educational intervention for hematopoietic stem cell (HSC) donors and to evaluate its effects on anxiety, knowledge, attitudes toward hematopoietic stem cell donation, and educational satisfaction. Methods: This quasi-experimental study employed a nonequivalent control group non-synchronized pretest-posttest design. Participants were 60 HSC donors admitted to a general hospital in Seoul, Republic of Korea, between April and December 2024. The participants were assigned to an experimental group (n=30) and a control group (n=30). The experimental group received a digital multimediabased educational intervention in addition to the usual education using a standardized handout, whereas the control group received the usual education only. The intervention was provided in three sessions: on the day of admission (20 minutes), on the day of stem cell collection (10 minutes), and on the day of discharge (10 minutes). Data were collected at admission and discharge using structured questionnaires. Anxiety was analyzed using generalized estimating equations (GEE), knowledge and attitudes using mixed ANOVA, and educational satisfaction using an independent t-test. Results: The experimental group showed significantly lower anxiety (p=.048) and higher knowledge levels (p=.005) than the control group. No significant differences were found between the groups in attitudes toward donation or educational satisfaction. Conclusion The digital multimedia-based educational intervention was effective in reducing anxiety and improving knowledge among HSC donors. This intervention may enhance donors’ understanding of the donation process and support a more positive donation experience. Further multicenter studies with larger samples and longitudinal follow-up measurements are needed to verify the long-term effects and generalizability of the intervention.

Objective: This study aimed to evaluate the survival of removable partial dentures (RPDs) abutment teeth that had undergone root canal treatment (RCT) and to identify the factors influencing survival. Materials and Methods: Records from the Veterans Health Service Medical Center were reviewed to identify patients who received RPDs between 2014 and 2015 and had root canal-treated abutment teeth. Preoperative variables included patient demographics, tooth location, and periapical radiolucency, while postoperative variables included RPD classification, opposing dentition, crown-root ratio (CRR), root canal filling quality, post placement, and restoration type. Statistical analysis was performed using the Kaplan-Meier method and Cox proportional hazards models. Results: A total of 776 root canal-treated abutment teeth from 341 patients using RPDs (mean age, 72.03 years) were included. In the multivariate analysis, tooth-related conditions such as arch type and tooth location, presence of a periapical lesion, and presence of a core were significantly associated with poor prognosis. Kaplan-Meier survival analysis revealed that the 3-, 5-, 7-, and 10-year survival rates for all teeth were 93.5%, 84.4%, 77.1%, and 60.0%, respectively. Conclusion Arch type and tooth position, preoperative periapical radiolucency, and type of restoration are significantly associated with prognosis in patients with RPDs in whom the abutment teeth have previously undergone RCT.

Objective: To test the performance of an artificial intelligence-based computer-aided diagnosis (AI-CAD) designed for fullfield digital mammography (FFDM) when applied to synthetic mammography (SM). Materials and Methods: We analyzed 501 women (mean age, 57 ± 11 years) who underwent preoperative mammography and breast cancer surgery. This cohort consisted of 1002 breasts, comprising 517 with cancer and 485 without. All patients underwent digital breast tomosynthesis (DBT) and FFDM during the preoperative workup. The SM is routinely reconstructed using DBT. Commercial AI-CAD (Lunit Insight MMG, version 1.1.7.2) was retrospectively applied to SM and FFDM to calculate the abnormality scores for each breast. The median abnormality scores were compared for the 517 breasts with cancer using the Wilcoxon signed-rank test. Calibration curves of abnormality scores were evaluated. The discrimination performance was analyzed using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity using a 10% preset threshold. Sensitivity and specificity were further analyzed according to the mammographic and pathological characteristics.The results of SM and FFDM were compared. Results: AI-CAD demonstrated a significantly lower median abnormality score (71% vs. 96%, P < 0.001) and poorer calibration performance for SM than for FFDM. SM exhibited lower sensitivity (76.2% vs. 82.8%, P < 0.001), higher specificity (95.5% vs.91.8%, P < 0.001), and comparable AUC (0.86 vs. 0.87, P = 0.127) than FFDM. SM showed lower sensitivity than FFDM in asymptomatic breasts, dense breasts, ductal carcinoma in situ, T1, N0, and hormone receptor-positive/human epidermal growth factor receptor 2-negative cancers but showed higher specificity in non-cancerous dense breasts. Conclusion AI-CAD showed lower abnormality scores and reduced calibration performance for SM than for FFDM.Furthermore, the 10% preset threshold resulted in different discrimination performances for the SM. Given these limitations, off-label application of the current AI-CAD to SM should be avoided.

Background: Kelch-like ECH-associated protein 1 (KEAP1)–nuclear factor erythroid- 2-related factor 2 (NRF2) pathway is a major regulator protecting cells from oxidative and metabolic stress. Studies have revealed that this pathway is involved in mediating resistance to cytotoxic chemotherapy and immunotherapy; however, its implications in oncogene-addicted tumors are largely unknown. This study aimed to elucidate whether this pathway could be a potential therapeutic target for epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer. Methods: We measured the baseline expression of NRF2 using EGFR-mutant parental cells and acquired gefitinib resistant cells. We investigated whether NRF2 inhibition affected cell death in vitro and tumor growth in vivo using a xenograft mouse model, and compared the transcriptional changes before and after NRF2 inhibition. Results: Baseline NRF2 expression was enhanced in PC9 and PC9 with gefitinib resistance (PC9/GR) cells than in other cell lines, with a more prominent expression in PC9/ GR. The NRF2 inhibitor induced NRF2 downregulation and cell death in a dose-dependent manner. Cotreatment with an NRF2 inhibitor enhanced osimertinib-induced cell death in vitro, and potentiated tumor growth inhibition in a PC9/GR xenograft model. Finally, RNA sequencing revealed that NRF2 inhibition resulted in the altered expression of multiple genes involved in various signaling pathways. Conclusion We identified that NRF2 inhibition enhanced cell death and inhibited tumor growth in tyrosine kinase inhibitor (TKI)-resistant lung cancer with EGFR-mutation. Thus, NRF2 modulation may be a novel therapeutic strategy to overcome the resistance to EGFR-TKIs.

Objective: To test the performance of an artificial intelligence-based computer-aided diagnosis (AI-CAD) designed for fullfield digital mammography (FFDM) when applied to synthetic mammography (SM). Materials and Methods: We analyzed 501 women (mean age, 57 ± 11 years) who underwent preoperative mammography and breast cancer surgery. This cohort consisted of 1002 breasts, comprising 517 with cancer and 485 without. All patients underwent digital breast tomosynthesis (DBT) and FFDM during the preoperative workup. The SM is routinely reconstructed using DBT. Commercial AI-CAD (Lunit Insight MMG, version 1.1.7.2) was retrospectively applied to SM and FFDM to calculate the abnormality scores for each breast. The median abnormality scores were compared for the 517 breasts with cancer using the Wilcoxon signed-rank test. Calibration curves of abnormality scores were evaluated. The discrimination performance was analyzed using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity using a 10% preset threshold. Sensitivity and specificity were further analyzed according to the mammographic and pathological characteristics.The results of SM and FFDM were compared. Results: AI-CAD demonstrated a significantly lower median abnormality score (71% vs. 96%, P < 0.001) and poorer calibration performance for SM than for FFDM. SM exhibited lower sensitivity (76.2% vs. 82.8%, P < 0.001), higher specificity (95.5% vs.91.8%, P < 0.001), and comparable AUC (0.86 vs. 0.87, P = 0.127) than FFDM. SM showed lower sensitivity than FFDM in asymptomatic breasts, dense breasts, ductal carcinoma in situ, T1, N0, and hormone receptor-positive/human epidermal growth factor receptor 2-negative cancers but showed higher specificity in non-cancerous dense breasts. Conclusion AI-CAD showed lower abnormality scores and reduced calibration performance for SM than for FFDM.Furthermore, the 10% preset threshold resulted in different discrimination performances for the SM. Given these limitations, off-label application of the current AI-CAD to SM should be avoided.

Background: Healthcare-associated infections impose a significant burden on antibiotic usage, healthcare expenditures, and morbidity. Therefore, it is crucial to revise policies to minimize such losses. This nationwide survey aimed to evaluate infection prevention and control (IPC) components in healthcare facilities and encourage improvements in acute care hospitals with inadequate infection prevention settings. This study aims to enhance the infection control capabilities of healthcare facilities. Methods: From December 27, 2021, to May 13, 2022, we conducted a survey of 1,767 acute care hospitals in the Republic of Korea. A survey was conducted to evaluate the infection control components in 1,767 acute care hospitals. Infection control officers provided direct responses to a systematically developed questionnaire. Subsequently, 10% of the respondents were randomly selected for the site investigation. Results: Overall, 1,197 (67.7%) hospitals responded to the online survey. On-site investigations were conducted at 125 hospitals. Hospitals with ≥ 150 beds are advised to have an IPC team under Article 3 of the Medical Service Act; however, only 87.0% (598/687) of hospitals with ≥ 100 beds had one. Conversely, 22.7% (116/510) of hospitals with < 100 beds had an IPC team. Regulations for hand hygiene, waste management, healthcare worker protection and safety, environmental cleaning, standard precautions, and prevention of the transmission of multidrug-resistant pathogens were present in 84.2%, 80.1%, 77.4%, 76.2%, 75.8%, and 63.5% of the hospitals, respectively. Hospitals with < 100 beds had low availability of all categories of standard operating procedures. Conclusion This study is the first national survey of acute care hospitals in the Republic of Korea. The data presented in the current study will improve the understanding of IPC status and will help establish a survey system. Our survey provides a basis for improving policies related to IPC in healthcare facilities.