Background: We evaluated severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2)-specific humoral and cellular responses for up to 6 months after the 3rd dose of ancestral coronavirus disease 2019 (COVID-19) vaccination in people living with HIV (PLWH) and healthy controls (HCs) who were not infected with COVID-19. Methods: Anti-spike receptor-binding domain IgG (anti-RBD IgG) concentrations using chemiluminescence immunoassay and neutralizing antibodies using focus reduction neutralization test (FRNT) were assessed at 1 week after each dose of vaccination, and 3 and 6 months after the 3rd dose in 62 PLWH and 25 HCs. T-cell responses using intracellular cytokine stain were evaluated at 1 week before, and 1 week and 6 months after the 3rd dose. Results: At 1 week after the 3rd dose, adequate anti-RBD IgG (> 300 binding antibody unit /mL) was elicited in all PLWH except for one patient with 36 CD4 T-cell count/mm3 . The geometric mean titers of 50% FRNT against wild type (WT) and omicron BA.5 strains of SARS-CoV-2 in PLWH with CD4 T-cell count ≥ 500 cells/mm3(high CD4 recovery, HCDR) were comparable to HC, but they were significantly decreased in PLWH with CD4 T-cell count < 500/mm3 (low CD4 recovery, LCDR). After adjusting for age, gender, viral suppression, and number of preexisting comorbidities, CD4 T-cell counts < 500/mm3 significantly predicted a poor magnitude of neutralizing antibodies against WT, omicron BA.5, and XBB 1.5 strains among PLWH. Multivariable linear regression adjusting for age and gender revealed that LCDR was associated with reduced neutralizing activity (P = 0.017) and interferon-γ-producing T-cell responses (P = 0.049 for CD T-cell; P = 0.014 for CD8 T-cell) against WT, and strongly associated with more decreased cross-neutralization against omicron BA.5 strains (P < 0.001). Conclusion HCDR demonstrated robust humoral and cell-mediated immune responses after a booster dose of ancestral SARS-CoV-2 vaccine, whereas LCDR showed diminished immune responses against WT virus and more impaired cross-neutralization against omicron BA.5 strain.

Background: We evaluated severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2)-specific humoral and cellular responses for up to 6 months after the 3rd dose of ancestral coronavirus disease 2019 (COVID-19) vaccination in people living with HIV (PLWH) and healthy controls (HCs) who were not infected with COVID-19. Methods: Anti-spike receptor-binding domain IgG (anti-RBD IgG) concentrations using chemiluminescence immunoassay and neutralizing antibodies using focus reduction neutralization test (FRNT) were assessed at 1 week after each dose of vaccination, and 3 and 6 months after the 3rd dose in 62 PLWH and 25 HCs. T-cell responses using intracellular cytokine stain were evaluated at 1 week before, and 1 week and 6 months after the 3rd dose. Results: At 1 week after the 3rd dose, adequate anti-RBD IgG (> 300 binding antibody unit /mL) was elicited in all PLWH except for one patient with 36 CD4 T-cell count/mm3 . The geometric mean titers of 50% FRNT against wild type (WT) and omicron BA.5 strains of SARS-CoV-2 in PLWH with CD4 T-cell count ≥ 500 cells/mm3(high CD4 recovery, HCDR) were comparable to HC, but they were significantly decreased in PLWH with CD4 T-cell count < 500/mm3 (low CD4 recovery, LCDR). After adjusting for age, gender, viral suppression, and number of preexisting comorbidities, CD4 T-cell counts < 500/mm3 significantly predicted a poor magnitude of neutralizing antibodies against WT, omicron BA.5, and XBB 1.5 strains among PLWH. Multivariable linear regression adjusting for age and gender revealed that LCDR was associated with reduced neutralizing activity (P = 0.017) and interferon-γ-producing T-cell responses (P = 0.049 for CD T-cell; P = 0.014 for CD8 T-cell) against WT, and strongly associated with more decreased cross-neutralization against omicron BA.5 strains (P < 0.001). Conclusion HCDR demonstrated robust humoral and cell-mediated immune responses after a booster dose of ancestral SARS-CoV-2 vaccine, whereas LCDR showed diminished immune responses against WT virus and more impaired cross-neutralization against omicron BA.5 strain.

Background: We evaluated severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2)-specific humoral and cellular responses for up to 6 months after the 3rd dose of ancestral coronavirus disease 2019 (COVID-19) vaccination in people living with HIV (PLWH) and healthy controls (HCs) who were not infected with COVID-19. Methods: Anti-spike receptor-binding domain IgG (anti-RBD IgG) concentrations using chemiluminescence immunoassay and neutralizing antibodies using focus reduction neutralization test (FRNT) were assessed at 1 week after each dose of vaccination, and 3 and 6 months after the 3rd dose in 62 PLWH and 25 HCs. T-cell responses using intracellular cytokine stain were evaluated at 1 week before, and 1 week and 6 months after the 3rd dose. Results: At 1 week after the 3rd dose, adequate anti-RBD IgG (> 300 binding antibody unit /mL) was elicited in all PLWH except for one patient with 36 CD4 T-cell count/mm3 . The geometric mean titers of 50% FRNT against wild type (WT) and omicron BA.5 strains of SARS-CoV-2 in PLWH with CD4 T-cell count ≥ 500 cells/mm3(high CD4 recovery, HCDR) were comparable to HC, but they were significantly decreased in PLWH with CD4 T-cell count < 500/mm3 (low CD4 recovery, LCDR). After adjusting for age, gender, viral suppression, and number of preexisting comorbidities, CD4 T-cell counts < 500/mm3 significantly predicted a poor magnitude of neutralizing antibodies against WT, omicron BA.5, and XBB 1.5 strains among PLWH. Multivariable linear regression adjusting for age and gender revealed that LCDR was associated with reduced neutralizing activity (P = 0.017) and interferon-γ-producing T-cell responses (P = 0.049 for CD T-cell; P = 0.014 for CD8 T-cell) against WT, and strongly associated with more decreased cross-neutralization against omicron BA.5 strains (P < 0.001). Conclusion HCDR demonstrated robust humoral and cell-mediated immune responses after a booster dose of ancestral SARS-CoV-2 vaccine, whereas LCDR showed diminished immune responses against WT virus and more impaired cross-neutralization against omicron BA.5 strain.

Background: We evaluated severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2)-specific humoral and cellular responses for up to 6 months after the 3rd dose of ancestral coronavirus disease 2019 (COVID-19) vaccination in people living with HIV (PLWH) and healthy controls (HCs) who were not infected with COVID-19. Methods: Anti-spike receptor-binding domain IgG (anti-RBD IgG) concentrations using chemiluminescence immunoassay and neutralizing antibodies using focus reduction neutralization test (FRNT) were assessed at 1 week after each dose of vaccination, and 3 and 6 months after the 3rd dose in 62 PLWH and 25 HCs. T-cell responses using intracellular cytokine stain were evaluated at 1 week before, and 1 week and 6 months after the 3rd dose. Results: At 1 week after the 3rd dose, adequate anti-RBD IgG (> 300 binding antibody unit /mL) was elicited in all PLWH except for one patient with 36 CD4 T-cell count/mm3 . The geometric mean titers of 50% FRNT against wild type (WT) and omicron BA.5 strains of SARS-CoV-2 in PLWH with CD4 T-cell count ≥ 500 cells/mm3(high CD4 recovery, HCDR) were comparable to HC, but they were significantly decreased in PLWH with CD4 T-cell count < 500/mm3 (low CD4 recovery, LCDR). After adjusting for age, gender, viral suppression, and number of preexisting comorbidities, CD4 T-cell counts < 500/mm3 significantly predicted a poor magnitude of neutralizing antibodies against WT, omicron BA.5, and XBB 1.5 strains among PLWH. Multivariable linear regression adjusting for age and gender revealed that LCDR was associated with reduced neutralizing activity (P = 0.017) and interferon-γ-producing T-cell responses (P = 0.049 for CD T-cell; P = 0.014 for CD8 T-cell) against WT, and strongly associated with more decreased cross-neutralization against omicron BA.5 strains (P < 0.001). Conclusion HCDR demonstrated robust humoral and cell-mediated immune responses after a booster dose of ancestral SARS-CoV-2 vaccine, whereas LCDR showed diminished immune responses against WT virus and more impaired cross-neutralization against omicron BA.5 strain.

Background and Objectives: Although various cardiac parameters on echocardiography have clinical importance, their measurement by conventional manual methods is time-consuming and subject to variability. We evaluated the feasibility, accuracy, and predictive value of an artificial intelligence (AI)-based automated system for echocardiographic analysis in patients with ST-segment elevation myocardial infarction (STEMI). Methods: The AI-based system was developed using a nationwide echocardiographic dataset from five tertiary hospitals, and automatically identified views, then segmented and tracked the left ventricle (LV) and left atrium (LA) to produce volume and strain values. Both conventional manual measurements and AI-based fully automated measurements of the LV ejection fraction and global longitudinal strain, and LA volume index and reservoir strain were performed in 632 patients with STEMI. Results: The AI-based system accurately identified necessary views (overall accuracy, 98.5%) and successfully measured LV and LA volumes and strains in all cases in which conventional methods were applicable. Inter-method analysis showed strong correlations between measurement methods, with Pearson coefficients ranging 0.81–0.92 and intraclass correlation coefficients ranging 0.74–0.90. For the prediction of clinical outcomes (composite of all-cause death, re-hospitalization due to heart failure, ventricular arrhythmia, and recurrent myocardial infarction), AI-derived measurements showed predictive value independent of clinical risk factors, comparable to those from conventional manual measurements. Conclusions Our fully automated AI-based approach for LV and LA analysis on echocardiography is feasible and provides accurate measurements, comparable to conventional methods, in patients with STEMI, offering a promising solution for comprehensive echocardiographic analysis, reduced workloads, and improved patient care.

Background and Objectives: Although various cardiac parameters on echocardiography have clinical importance, their measurement by conventional manual methods is time-consuming and subject to variability. We evaluated the feasibility, accuracy, and predictive value of an artificial intelligence (AI)-based automated system for echocardiographic analysis in patients with ST-segment elevation myocardial infarction (STEMI). Methods: The AI-based system was developed using a nationwide echocardiographic dataset from five tertiary hospitals, and automatically identified views, then segmented and tracked the left ventricle (LV) and left atrium (LA) to produce volume and strain values. Both conventional manual measurements and AI-based fully automated measurements of the LV ejection fraction and global longitudinal strain, and LA volume index and reservoir strain were performed in 632 patients with STEMI. Results: The AI-based system accurately identified necessary views (overall accuracy, 98.5%) and successfully measured LV and LA volumes and strains in all cases in which conventional methods were applicable. Inter-method analysis showed strong correlations between measurement methods, with Pearson coefficients ranging 0.81–0.92 and intraclass correlation coefficients ranging 0.74–0.90. For the prediction of clinical outcomes (composite of all-cause death, re-hospitalization due to heart failure, ventricular arrhythmia, and recurrent myocardial infarction), AI-derived measurements showed predictive value independent of clinical risk factors, comparable to those from conventional manual measurements. Conclusions Our fully automated AI-based approach for LV and LA analysis on echocardiography is feasible and provides accurate measurements, comparable to conventional methods, in patients with STEMI, offering a promising solution for comprehensive echocardiographic analysis, reduced workloads, and improved patient care.

Background and Objectives: Although various cardiac parameters on echocardiography have clinical importance, their measurement by conventional manual methods is time-consuming and subject to variability. We evaluated the feasibility, accuracy, and predictive value of an artificial intelligence (AI)-based automated system for echocardiographic analysis in patients with ST-segment elevation myocardial infarction (STEMI). Methods: The AI-based system was developed using a nationwide echocardiographic dataset from five tertiary hospitals, and automatically identified views, then segmented and tracked the left ventricle (LV) and left atrium (LA) to produce volume and strain values. Both conventional manual measurements and AI-based fully automated measurements of the LV ejection fraction and global longitudinal strain, and LA volume index and reservoir strain were performed in 632 patients with STEMI. Results: The AI-based system accurately identified necessary views (overall accuracy, 98.5%) and successfully measured LV and LA volumes and strains in all cases in which conventional methods were applicable. Inter-method analysis showed strong correlations between measurement methods, with Pearson coefficients ranging 0.81–0.92 and intraclass correlation coefficients ranging 0.74–0.90. For the prediction of clinical outcomes (composite of all-cause death, re-hospitalization due to heart failure, ventricular arrhythmia, and recurrent myocardial infarction), AI-derived measurements showed predictive value independent of clinical risk factors, comparable to those from conventional manual measurements. Conclusions Our fully automated AI-based approach for LV and LA analysis on echocardiography is feasible and provides accurate measurements, comparable to conventional methods, in patients with STEMI, offering a promising solution for comprehensive echocardiographic analysis, reduced workloads, and improved patient care.

Background and Objectives: Although various cardiac parameters on echocardiography have clinical importance, their measurement by conventional manual methods is time-consuming and subject to variability. We evaluated the feasibility, accuracy, and predictive value of an artificial intelligence (AI)-based automated system for echocardiographic analysis in patients with ST-segment elevation myocardial infarction (STEMI). Methods: The AI-based system was developed using a nationwide echocardiographic dataset from five tertiary hospitals, and automatically identified views, then segmented and tracked the left ventricle (LV) and left atrium (LA) to produce volume and strain values. Both conventional manual measurements and AI-based fully automated measurements of the LV ejection fraction and global longitudinal strain, and LA volume index and reservoir strain were performed in 632 patients with STEMI. Results: The AI-based system accurately identified necessary views (overall accuracy, 98.5%) and successfully measured LV and LA volumes and strains in all cases in which conventional methods were applicable. Inter-method analysis showed strong correlations between measurement methods, with Pearson coefficients ranging 0.81–0.92 and intraclass correlation coefficients ranging 0.74–0.90. For the prediction of clinical outcomes (composite of all-cause death, re-hospitalization due to heart failure, ventricular arrhythmia, and recurrent myocardial infarction), AI-derived measurements showed predictive value independent of clinical risk factors, comparable to those from conventional manual measurements. Conclusions Our fully automated AI-based approach for LV and LA analysis on echocardiography is feasible and provides accurate measurements, comparable to conventional methods, in patients with STEMI, offering a promising solution for comprehensive echocardiographic analysis, reduced workloads, and improved patient care.

Ovarian cancer is a primary global health concern, often diagnosed at advanced stages with limited treatment options and poor prognosis. Natural products have emerged as potential sources of safe and effective therapies. From the seeds of Myristica fragrans Houtt. (nutmeg), 24 compounds, including neolignans and diarylnonanoid derivatives, were isolated and structurally elucidated. The cytotoxic activities of these isolated metabolites against cisplatin-sensitive and resistant human ovarian cancer cell lines were evaluated. In particular, myrifragranone C (23) exhibited cytotoxicity against all test cancer cell lines A2780, TOV-112D, and SK-OV3 with IC50 values of 14.1, 16.9, and 33.4 μM, respectively. Furthermore, compound 23 induced the death of A2780 and SK-OV3 cancer cells via apoptosis. Western blotting revealed that compound 23 significantly increased the expression of cleaved caspase-3 and poly-ADP ribose polymerase and promoted apoptosis via the mitogenactivated protein kinase signaling pathway. Our findings may provide a preliminary understanding of the antiovarian cancer effect of the active compound myrifragranone C as a potential treatment using natural products.