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Lattice oxygen redox offers an unexplored way to access superior electrochemical properties of transition metal oxides (TMOs) for rechargeable batteries. However, the reaction is often accompanied by unfavourable structural transformations and persistent electrochemical degradation, thereby precluding the practical application of this strategy. Here we explore the close interplay between the local structural change and oxygen electrochemistry during short- and long-term battery operation for layered TMOs. The substantially distinct evolution of the oxygen-redox activity and reversibility are demonstrated to stem from the different cation-migration mechanisms during the dynamic de/intercalation process. We show that the π stabilization on the oxygen oxidation initially aids in the reversibility of the oxygen redox and is predominant in the absence of cation migrations; however, the π-interacting oxygen is gradually replaced by σ-interacting oxygen that triggers the formation of O–O dimers and structural destabilization as cycling progresses. More importantly, it is revealed that the distinct cation-migration paths available in the layered TMOs govern the conversion kinetics from π to σ interactions. These findings constitute a step forward in unravelling the correlation between the local structural evolution and the reversibility of oxygen electrochemistry and provide guidance for further development of oxygen-redox layered electrode materials. Transition metal oxide electrodes are promising for rechargeable batteries but are subject to suffer from structural transformations and electrochemical degradation. The evolution of oxygen-redox activity and reversibility in layered electrodes are shown to arise from cation-migration mechanisms during de/intercalation.

Depression, one of the most costly and common mental disorders, is reported to be associated with lower quality of life (QoL) in several studies. Improved understanding of the associated factors with QoL is necessary to optimize long-term outcomes and reduce disability in patients with depression. Therefore, the aim of this study was to identify factors that are associated with lower QoL among patients with depression. The study was based on the Korea National Health and Nutrition Examination Survey, a cross-sectional health examination, years 2008 to 2014. The final analyzed sample consisted of a total of 1,502 study subjects who had been diagnosed by clinicians as having depression. A multivariate logistic regression model was performed to exam the association between the clinical characteristics (age, sex, demographic and health-related characteristics) and QoL. Analysis of covariance was also used to analyze EQ-5D according to mental health. Older age, lower level of education, lower income, worse subjective perception of health, unemployment, obesity and mental health struggles were found to be significantly associated with low QoL in depressive individuals after adjustment for multiple covariates. This study has outlined grounding data in identifying patients who are at risk of QoL impairment. Policy makers should direct their interests to these individuals and provide appropriate management.

Background We developed a model to predict remissions in patients treated with biologic disease-modifying anti-rheumatic drugs (bDMARDs) and to identify important clinical features associated with remission using explainable artificial intelligence (XAI). Methods We gathered the follow-up data of 1204 patients treated with bDMARDs (etanercept, adalimumab, golimumab, infliximab, abatacept, and tocilizumab) from the Korean College of Rheumatology Biologics and Targeted Therapy Registry. Remission was predicted at 1-year follow-up using baseline clinical data obtained at the time of enrollment. Machine learning methods (e.g., lasso, ridge, support vector machine, random forest, and XGBoost) were used for the predictions. The Shapley additive explanation (SHAP) value was used for interpretability of the predictions. Results The ranges for accuracy and area under the receiver operating characteristic of the newly developed machine learning model for predicting remission were 52.8–72.9% and 0.511–0.694, respectively. The Shapley plot in XAI showed that the impacts of the variables on predicting remission differed for each bDMARD. The most important features were age for adalimumab, rheumatoid factor for etanercept, erythrocyte sedimentation rate for infliximab and golimumab, disease duration for abatacept, and C-reactive protein for tocilizumab, with mean SHAP values of − 0.250, − 0.234, − 0.514, − 0.227, − 0.804, and 0.135, respectively. Conclusions Our proposed machine learning model successfully identified clinical features that were predictive of remission in each of the bDMARDs. This approach may be useful for improving treatment outcomes by identifying clinical information related to remissions in patients with rheumatoid arthritis.

O2-type lithium-rich layered oxides, known for mitigating irreversible transition metal migration and voltage decay, provide suitable framework for exploring the inherent properties of oxygen redox. Here, we present a series of O2-type lithium-rich layered oxides exhibiting minimal structural disordering and stable voltage retention even with high anionic redox participation based on the nominal composition. Notably, we observe a distinct asymmetric lattice breathing phenomenon within the layered framework driven by excessive oxygen redox, which includes substantial particle-level mechanical stress and the microcracks formation during cycling. This chemo-mechanical degradation can be effectively mitigated by balancing the anionic and cationic redox capabilities, securing both high discharge voltage (~ 3.43 V vs . Li/Li + ) and capacity (~ 200 mAh g −1 ) over extended cycles. The observed correlation between the oxygen redox capability and the structural evolution of the layered framework suggests the distinct intrinsic capacity fading mechanism that differs from the previously proposed voltage fading mode. O2-type Li-rich layered cathodes suppress voltage decay and aid in oxygen redox research. Here, the authors report trilateral relationship among anionic redox utilization, bulk chemo-mechanical degradation, and electrochemical fading, which can be mitigated by balancing the redox center capabilities.

This study aimed to investigate deep convolutional neural network- (DCNN-) based artificial intelligence (AI) model using cephalometric images for the classification of sagittal skeletal relationships and compare the performance of the newly developed DCNN-based AI model with that of the automated-tracing AI software. A total of 1574 cephalometric images were included and classified based on the A-point-Nasion- (N-) point-B-point (ANB) angle (Class I being 0–4°, Class II > 4°, and Class III < 0°). The DCNN-based AI model was developed using training (1334 images) and validation (120 images) sets with a standard classification label for the individual images. A test set of 120 images was used to compare the AI models. The agreement of the DCNN-based AI model or the automated-tracing AI software with a standard classification label was measured using Cohen’s kappa coefficient (0.913 for the DCNN-based AI model; 0.775 for the automated-tracing AI software). In terms of their performances, the micro-average values of the DCNN-based AI model (sensitivity, 0.94; specificity, 0.97; precision, 0.94; accuracy, 0.96) were higher than those of the automated-tracing AI software (sensitivity, 0.85; specificity, 0.93; precision, 0.85; accuracy, 0.90). With regard to the sagittal skeletal classification using cephalometric images, the DCNN-based AI model outperformed the automated-tracing AI software.

Background The lack of adequate and detailed epidemiological data of Parkinson’s disease (PD), especially in Asia, is a barrier to future disease burdens and the prospect of effective public health plans. This study aimed to investigate temporal trends in the incidence and prevalence of PD in South Korea from 2010 to 2015, based on uniform diagnostic criteria. Methods This study examined all PD patients registered in a South Korean national registry database of more than 50 million individuals. We analyzed the incidence and prevalence of PD according to age, gender, and region. Results The annual incidence of PD was between 22.4–27.8 cases per 100,000 individuals. During the 6-year study period, there were 73,726 new PD patients, 42.3% of whom were men. The standardized incidence of PD increased over time in men but remained constant in women until 2013 but began to increase in 2014. The female-to-male ratio in the incidence of PD was 1.4:1 while the female-to-male ratio in the prevalence of PD was 1.6:1. The age- and gender-standardized prevalence of PD increased from 115.9 cases per 100,000 individuals in 2010 to 139.8 cases per 100,000 individuals in 2015. From 2014, the incidence and prevalence of PD peaked in individuals aged between 80 and 89 years in both men and women. Regional analysis also showed an increased prevalence of PD in all regions of Korea. Conclusions The incidence and prevalence of PD in Korea were higher in women and increased gradually from 2010 to 2015. The findings may contribute to epidemiological studies of PD in Asia, and may provide clues on risk factors for PD.

Moutan Cortex, Paeonia suffruticosa root, has long been used as a medicine for the treatment of inflammatory diseases. The aim of this study was to evaluate the modulative properties of Moutan Cortex water extract (CP) on endoplasmic reticulum (ER) stress-related macrophage activation via the calcium-CHOP pathway. RAW 264.7 mouse macrophages were activated by lipopolysaccharide (LPS), and the levels of various inflammatory mediators from RAW 264.7 were evaluated. The multiplex cytokine assay was used to investigate both cytokines and growth factors, and RT-PCR was used to investigate the expressions of inflammation-related genes, such as CHOP. Data represent the levels of NO and cytosolic calcium in LPS-stimulated RAW 264.7 were significantly inhibited by CP as well as hydrogen peroxide (p < 0.05). Minutely, NO production in LPS-stimulated RAW 264.7 incubated with CP at concentrations of 25, 50, 100, and 200 µg/mL for 24 h was 97.32 ± 1.55%, 95.86 ± 2.26%, 94.64 ± 1.83%, and 92.69 ± 2.31% of the control value (LPS only), respectively (p < 0.05). Calcium release in LPS-stimulated RAW 264.7 incubated with CP at concentrations of 25, 50, 100, and 200 µg/mL for 18 h was 95.78 ± 1.64%, 95.41 ± 1.14%, 94.54 ± 2.76%, and 90.89 ± 3.34% of the control value, respectively (p < 0.05). Hydrogen peroxide production in LPS-stimulated RAW 264.7 incubated with CP at concentrations of 25, 50, 100, and 200 µg/mL for 24 h was 79.15 ± 7.16%, 63.83 ± 4.03%, 46.27 ± 4.38%, and 40.66 ± 4.03% of the control value, respectively (p < 0.05). It is interesting that the production of IL-6, TNF-α, G-CSF, MIP-1α, MIP-2, and M-CSF in LPS-stimulated RAW 264.7 were significantly inhibited by CP (p < 0.05), while the production of LIX, LIF, RANTES, and MIP-1β showed a meaningful decrease. CP at concentrations of 25, 50, 100, and 200 µg/mL significantly reduced the transcription of Chop, Camk2α, NOS, STAT1, STAT3, Ptgs2, Jak2, c-Jun, Fas, c-Fos, TLR3, and TLR9 in LPS-stimulated RAW 264.7 (p < 0.05). CP at concentrations of 25, 50, and 100 µg/mL significantly reduced the phosphorylation of STAT3, p38 MAPK, and IκB-α in LPS-stimulated RAW 264.7 (p < 0.05). These results suggest that CP might modulate macrophage activation via LPS-induced calcium signaling and the ER stress-CHOP pathway.

Global warming, driven by greenhouse gas (GHG) emissions, is accelerating globally and highlights the need for effective mitigation strategies. This study assesses the economic feasibility of rainbow trout aquaculture by incorporating GHG emissions into its analysis, thereby contributing to mitigation efforts in the fisheries sector. Focusing on two farming systems—recirculating aquaculture systems (RAS) and flow-through systems (FTS)—we estimated GHG emissions and conducted an economic evaluation using data collected through field surveys. The average GHG emission was 7.14 kg CO2 eq per kilogram of trout produced, with RAS showing lower emissions than FTS. Electricity and feed were identified as the primary emission sources. The economic analysis revealed an average net present value (NPV) of USD 987,609 and an internal rate of return (IRR) of 18%, with RAS outperforming FTS in profitability. A sensitivity analysis under carbon pricing showed that economic feasibility was maintained, but the NPV declined by about 24% under the carbon tax scenario. Overall, these findings underscore the importance of balancing profitability and emission reduction for sustainable aquaculture management.

This study aims to examine the factors influencing the acceptance of extruded pellet (EP) usage among Korea’s olive flounder farming households by analyzing their acceptance factors to provide recommendations for its wider adoption. A survey was conducted among olive flounder farming households, and 188 valid questionnaires were collected. To examine the factors influencing EP acceptance intention, the UTAUT2 (extended unified theory of acceptance and use of technology) model was used. The independent variables were categorized into performance expectancy, effort expectancy, facilitating conditions, social influence, price value, and reliability as independent variables, while acceptance intention was considered as the dependent variable, to derive measurement items. In addition, the differences between the two groups were analyzed by using the aquaculture region and the manager’s experience as moderating variables. The hypothesis testing showed that performance expectancy, effort expectancy, social influence, price value, and reliability factors had a positive effect on acceptance intention, while facilitating conditions did not show a significant effect. The analysis of the moderating effect of the aquaculture region indicated a significant difference between the Jeju-do and Jeollanam-do groups. Conversely, the moderating effect of experience showed no significant difference between those with more experience (≥10 years) and those with less (<10 years).