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Diverse cases regarding the impact, with its related factors, of the COVID-19 pandemic on mental health have been reported in previous studies. In this study, multivariable datasets were collected from 751 college students who could be easily affected by pandemics based on the complex relationships between various mental health factors. We utilized quantum annealing (QA)-based feature selection algorithms that were executed by commercial D-Wave quantum computers to determine the changes in the relative importance of the associated factors before and after the pandemic. Multivariable linear regression (MLR) and XGBoost models were also applied to validate the QA-based algorithms. Based on the experimental results, we confirm that QA-based algorithms have comparable capabilities in factor analysis research to the MLR models that have been widely used in previous studies. Furthermore, the performance of the QA-based algorithms was validated through the important factor results from the algorithms. Pandemic-related factors (e.g., confidence in the social system) and psychological factors (e.g. decision-making in uncertain situations) were more important in post-pandemic conditions. Although the results should be validated using other mental health variables or national datasets, this study will serve as a reference for researchers regarding the use of the quantum annealing approach in factor analysis with validation through real-world survey dataset analysis. [ABSTRACT FROM AUTHOR]

Diverse cases regarding the impact, with its related factors, of the COVID-19 pandemic on mental health have been reported in previous studies. In this study, multivariable datasets were collected from 751 college students who could be easily affected by pandemics based on the complex relationships between various mental health factors. We utilized quantum annealing (QA)-based feature selection algorithms that were executed by commercial D-Wave quantum computers to determine the changes in the relative importance of the associated factors before and after the pandemic. Multivariable linear regression (MLR) and XGBoost models were also applied to validate the QA-based algorithms. Based on the experimental results, we confirm that QA-based algorithms have comparable capabilities in factor analysis research to the MLR models that have been widely used in previous studies. Furthermore, the performance of the QA-based algorithms was validated through the important factor results from the algorithms. Pandemic-related factors (e.g., confidence in the social system) and psychological factors (e.g. decision-making in uncertain situations) were more important in post-pandemic conditions. Although the results should be validated using other mental health variables or national datasets, this study will serve as a reference for researchers regarding the use of the quantum annealing approach in factor analysis with validation through real-world survey dataset analysis. [ABSTRACT FROM AUTHOR]

Inadequate cerebral perfusion is a risk factor for cerebral ischemia in patients with large artery steno-occlusion. We investigated whether prefrontal oxyhemoglobin oscillation (ΔHbO2, 0.6–2 Hz) was associated with decreased vascular reserve in patients with steno-occlusion in the large anterior circulation arteries. Thirty-six patients with steno-occlusion in the anterior circulation arteries (anterior cerebral artery, middle cerebral artery, and internal carotid artery) were included and compared to thirty-six control subjects. Patients were categorized into two groups (deteriorated vascular reserve vs. preserved vascular reserve) based on the results of Diamox single- photon emission computed tomography imaging. HbO2 data were collected using functional near-infrared spectroscopy. The slope of ΔHbO2 and the ipsilateral/contralateral slope ratio of ΔHbO2 were analyzed. Among the included patients (n = 36), 25 (69.4%) had deteriorated vascular reserve. Patients with deteriorated vascular reserve had a significantly higher average slope of ΔHbO2 on the ipsilateral side (5.01 ± 2.14) and a higher ipsilateral/contralateral ratio (1.44 ± 0.62) compared to those with preserved vascular reserve (3.17 ± 1.36, P = 0.014; 0.93 ± 0.33, P = 0.016, respectively) or the controls (3.82 ± 1.69, P = 0.019; 0.94 ± 0.29, P = 0.001). The ipsilateral/contralateral ΔHbO2 ratio could be used as a surrogate for vascular reserve in patients with severe steno-occlusion in the anterior circulation arteries. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via a link at the top of the paper. [ABSTRACT FROM AUTHOR]

Metformin increased cellular ROS levels in AsPC-1 pancreatic cancer cells, with minimal effect in HDF, human primary dermal fibroblasts. Metformin reduced cellular ATP levels in HDF, but not in AsPC-1 cells. Metformin increased AMPK, p-AMPK (Thr172), FOXO3a, p-FOXO3a (Ser413), and MnSOD levels in HDF, but not in AsPC-1 cells. p-AMPK and p-FOXO3a also translocated from the cytosol to the nucleus by metformin in HDF, but not in AsPC-1 cells. Transfection of si-FOXO3a in HDF increased ROS levels, while wt-FOXO3a-transfected AsPC-1 cells decreased ROS levels. Metformin combined with apigenin increased ROS levels dramatically and decreased cell viability in various cancer cells including AsPC-1 cells, with each drug used singly having a minimal effect. Metformin/apigenin combination synergistically decreased mitochondrial membrane potential in AsPC-1 cells but to a lesser extent in HDF cells. Metformin/apigenin combination in AsPC-1 cells increased DNA damage-, apoptosis-, autophagy- and necroptosis-related factors, but not in HDF cells. Oral administration with metformin/apigenin caused dramatic blocks tumor size in AsPC-1-xenografted nude mice. Our results suggest that metformin in cancer cells differentially regulates cellular ROS levels via AMPK-FOXO3a-MnSOD pathway and combination of metformin/apigenin exerts anticancer activity through DNA damage-induced apoptosis, autophagy and necroptosis by cancer cell-specific ROS amplification. [ABSTRACT FROM AUTHOR]