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.

Background: Sarcopenia, a multifactorial disorder involving metabolic disturbance, suggests potential for metabolite biomarkers. Carnitine (CN), essential for skeletal muscle energy metabolism, may be a candidate biomarker. We investigated whether CN metabolites are biomarkers for sarcopenia. Methods: Associations between the CN metabolites identified from an animal model of sarcopenia and muscle cells and sarcopenia status were evaluated in men from an age-matched discovery (72 cases, 72 controls) and a validation (21 cases, 47 controls) cohort. Results: An association between CN metabolites and sarcopenia showed in mouse and cell studies. In the discovery cohort, plasma C5-CN levels were lower in sarcopenic men (P=0.005). C5-CN levels in men tended to be associated with handgrip strength (HGS) (P=0.098) and were significantly associated with skeletal muscle mass (P=0.003). Each standard deviation increase in C5-CN levels reduced the odds of low muscle mass (odd ratio, 0.61; 95% confidence interval [CI], 0.42 to 0.89). The area under the receiver operating characteristic curve (AUROC) of CN score using a regression equation of C5-CN levels, for sarcopenia was 0.635 (95% CI, 0.544 to 0.726). In the discovery cohort, addition of CN score to HGS significantly improved AUROC from 0.646 (95% CI, 0.575 to 0.717; HGS only) to 0.727 (95% CI, 0.643 to 0.810; P=0.006; HGS+CN score). The improvement was confirmed in the validation cohort (AUROC=0.563; 95% CI, 0.470 to 0.656 for HGS; and AUROC=0.712; 95% CI, 0.569 to 0.855 for HGS+CN score; P=0.027). Conclusion C5-CN, indicative of low muscle mass, is a potential circulating biomarker for sarcopenia in men. Further studies are required to confirm these results and explore sarcopenia-related metabolomic changes.

Human rhinovirus (HRV) causes the common cold and exacerbates chronic respiratory diseases, such as asthma and chronic obstructive pulmonary disease. Despite its significant impact on public health, there are currently no approved vaccines or antiviral treatments for HRV infection. Apoptosis is the process through which cells eliminate themselves through the systematic activation of intrinsic death pathways in response to various stimuli. It plays an important role in viral infections and serves as a key immune defense mechanism in the interactions between viruses and the host. In the present study, we investigated the antiviral effects of quercetin-3-methyl ether, a flavonoid isolated from Serratula coronata, on human rhinovirus 1B (HRV1B). Quercetin-3-methyl ether significantly inhibited HRV1B replication in HeLa cells in a concentration-dependent manner, thereby reducing cytopathic effects and viral RNA levels. Time-course and time-of-addition analyses confirmed that quercetin-3-methyl ether exhibited antiviral activity during the early stages of viral infection, potentially targeting the replication and translation phases. Gene expression analysis using microarrays revealed that pro-apoptotic genes were upregulated in quercetin-3-methyl ether-treated cells, suggesting that quercetin-3-methyl ether enhances early apoptosis to counteract HRV1B-induced immune evasion. In vivo administration of quercetin-3-methyl ether to HRV1B-infected mice significantly reduced viral RNA levels and inflammatory cytokine production in the lung tissues. Our findings demonstrated the potential of quercetin-3-methyl ether as a novel antiviral agent against HRV1B, thereby providing a promising therapeutic strategy for the management of HRV1B infections and related complications.

Acute Respiratory Distress Syndrome (ARDS) is a severe condition characterized by extensive lung inflammation and increased alveolar-capillary permeability, often triggered by infections or systemic inflammatory responses. Mesenchymal stem cells (MSCs)-based therapy holds promise for treating ARDS, as MSCs manifest immunomodulatory and regenerative properties that mitigate inflammation and enhance tissue repair. Primed MSCs, modified to augment specific functionalities, demonstrate superior therapeutic efficacy in targeted therapies compared to naive MSCs. This study explored the immunomodulatory potential of MSCs using mixed lymphocyte reaction (MLR) assays and co-culture experiments with M1/M2 macrophages. Additionally, RNA sequencing was employed to identify alterations in immune and inflammation-related factors in primed MSCs. The therapeutic effects of primed MSCs were assessed in an LPS-induced ARDS mouse model, and the underlying mechanisms were investigated through spatial transcriptomics analysis. The study revealed that MSCs primed with IFN-γ and IL-1β significantly enhanced the suppression of T cell activity compared to naive MSCs, concurrently inhibiting TNF-α while increasing IL-10 production in macrophages. Notably, combined treatment with these two cytokines resulted in a significant upregulation of immune and inflammation-regulating factors. Furthermore, our analyses elucidated the mechanisms behind the therapeutic effects of primed MSCs, including the inhibition of inflammatory cell infiltration in lung tissue, modulation of immune and inflammatory responses, and enhancement of elastin fiber formation. Signaling pathway analysis confirmed that efficacy could be enhanced by modulating NFκB and TNF-α signaling. In conclusion, in early-phase ARDS, primed MSCs displayed enhanced homing capabilities, improved lung function, and reduced inflammation.

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: 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.

Purpose: This study evaluated the postoperative quality of life (QoL) after various types of gastrectomy for gastric cancer. Materials and Methods: A multicenter prospective observational study was conducted in Korea using the Korean Quality of Life in Stomach Cancer Patients Study (KOQUSS)-40, a new QoL assessment tool focusing on postgastrectomy syndrome. Overall, 496 patients with gastric cancer were enrolled, and QoL was assessed at 5 time points: preoperatively and at 1, 3, 6, and 12 months after surgery. Results: Distal gastrectomy (DG) and pylorus-preserving gastrectomy (PPG) showed significantly better outcomes than total gastrectomy (TG) and proximal gastrectomy (PG) with regard to total score, indigestion, and dysphagia. DG, PPG, and TG also showed significantly better outcomes than PG in terms of dumping syndrome and worry about cancer. Postoperative QoL did not differ significantly according to anastomosis type in DG, except for Billroth I anastomosis, which achieved better bowel habit change scores than the others. No domains differed significantly when comparing double tract reconstruction and esophagogastrostomy after PG. The total QoL score correlated significantly with postoperative body weight loss (more than 10%) and extent of resection (P<0.05 for both).Reflux as assessed by KOQUSS-40 did not correlate significantly with reflux observed on gastroscopy 1 year postoperatively (P=0.064). Conclusions Our prospective observation using KOQUSS-40 revealed that DG and PPG lead to better QoL than TG and PG. Further study is needed to compare postoperative QoL according to anastomosis type in DG and PG.