Raw data 16–20. by Fateme Khorramroo (18086501)

“…Wide running significantly decreased the coordination variability in the ankle-knee sagittal during LR (p<0.001) and knee-hip sagittal during LR (p=0.007) and push-off (p=0.016). …”

Demographics, SD= Standard Deviation. by Fateme Khorramroo (18086501)

“…Wide running significantly decreased the coordination variability in the ankle-knee sagittal during LR (p<0.001) and knee-hip sagittal during LR (p=0.007) and push-off (p=0.016). …”

Raw data 6–9 and 15. by Fateme Khorramroo (18086501)

“…Wide running significantly decreased the coordination variability in the ankle-knee sagittal during LR (p<0.001) and knee-hip sagittal during LR (p=0.007) and push-off (p=0.016). …”

Raw data 1–5. by Fateme Khorramroo (18086501)

“…Wide running significantly decreased the coordination variability in the ankle-knee sagittal during LR (p<0.001) and knee-hip sagittal during LR (p=0.007) and push-off (p=0.016). …”

Raw data 10–14. by Fateme Khorramroo (18086501)

“…Wide running significantly decreased the coordination variability in the ankle-knee sagittal during LR (p<0.001) and knee-hip sagittal during LR (p=0.007) and push-off (p=0.016). …”

Coordination angle during running. by Fateme Khorramroo (18086501)

“…Wide running significantly decreased the coordination variability in the ankle-knee sagittal during LR (p<0.001) and knee-hip sagittal during LR (p=0.007) and push-off (p=0.016). …”

Gait retraining with biofeedback. by Fateme Khorramroo (18086501)

“…Wide running significantly decreased the coordination variability in the ankle-knee sagittal during LR (p<0.001) and knee-hip sagittal during LR (p=0.007) and push-off (p=0.016). …”

Coordination angle during walking. by Fateme Khorramroo (18086501)

“…Wide running significantly decreased the coordination variability in the ankle-knee sagittal during LR (p<0.001) and knee-hip sagittal during LR (p=0.007) and push-off (p=0.016). …”

Primers for qPCR. by Xiaoyi Shi (3825754)

“…Our results indicated that PGAM5 was significantly elevated by I/R injury, and predominantly localized in the necrosis area. …”

Making Cells as a “Nirvana Phoenix”: Precise Coupling of Precursors Prior to ROS Bursts for Intracellular Synthesis of Quantum Dots by Juan Kong (2230867)

“…However, the introduced exogenous reactants and intracellularly produced species, e.g., reactive oxygen species (ROS), often cause cell damage, decreasing the fluorescence of the QDs. Herein, we have found that cell-adaptable selenocystine ((Cys-Se)₂) can be reduced to biocompatible low-valence Se precursors, which could be subsequently hijacked by timely added Ag-glutathione (AgSG) to be transformed into NIR Ag₂Se QDs. …”

Making Cells as a “Nirvana Phoenix”: Precise Coupling of Precursors Prior to ROS Bursts for Intracellular Synthesis of Quantum Dots by Juan Kong (2230867)

“…However, the introduced exogenous reactants and intracellularly produced species, e.g., reactive oxygen species (ROS), often cause cell damage, decreasing the fluorescence of the QDs. Herein, we have found that cell-adaptable selenocystine ((Cys-Se)₂) can be reduced to biocompatible low-valence Se precursors, which could be subsequently hijacked by timely added Ag-glutathione (AgSG) to be transformed into NIR Ag₂Se QDs. …”

S1 Raw data - by Xiaoyi Shi (3825754)

“…Our results indicated that PGAM5 was significantly elevated by I/R injury, and predominantly localized in the necrosis area. …”

Minimal data set. by Fu-Lin Yu (21446056)

“…However, the metabolic mechanisms underlying arsenic’s effects on muscle function and pathogenesis remain incompletely understood. In this study, we investigated the role of mitochondrial fatty acid oxidation in arsenic-induced muscular damage using mouse skeletal muscle C2C12 cells. …”

Making Cells as a “Nirvana Phoenix”: Precise Coupling of Precursors Prior to ROS Bursts for Intracellular Synthesis of Quantum Dots by Juan Kong (2230867)

“…However, the introduced exogenous reactants and intracellularly produced species, e.g., reactive oxygen species (ROS), often cause cell damage, decreasing the fluorescence of the QDs. Herein, we have found that cell-adaptable selenocystine ((Cys-Se)₂) can be reduced to biocompatible low-valence Se precursors, which could be subsequently hijacked by timely added Ag-glutathione (AgSG) to be transformed into NIR Ag₂Se QDs. …”

Making Cells as a “Nirvana Phoenix”: Precise Coupling of Precursors Prior to ROS Bursts for Intracellular Synthesis of Quantum Dots by Juan Kong (2230867)

“…However, the introduced exogenous reactants and intracellularly produced species, e.g., reactive oxygen species (ROS), often cause cell damage, decreasing the fluorescence of the QDs. Herein, we have found that cell-adaptable selenocystine ((Cys-Se)₂) can be reduced to biocompatible low-valence Se precursors, which could be subsequently hijacked by timely added Ag-glutathione (AgSG) to be transformed into NIR Ag₂Se QDs. …”

The chemical structure of melatonin. by Xiaoyi Shi (3825754)

“…Our results indicated that PGAM5 was significantly elevated by I/R injury, and predominantly localized in the necrosis area. …”

Regulation of Rice Grain Weight by Fatty Acid Composition: Unveiling the Mechanistic Roles of <i>OsLIN6</i> by OsARF12 by Haoran Tian (6706925)

“…However, the inner mechanism is still unclear and needs to be further studied. In this study, we identified that oleic acid (C18:1) negatively correlates while linoleic acid (C18:2) positively correlates with rice grain weight. …”

Modulating the Coordination Environment of Cu-Embedded Mo<i>X</i>₂ (<i>X</i> = S, Se, and Te) Monolayers for Electrocatalytic Reduction of CO₂ to CH<sub>4</su... by Thamarainathan Doulassiramane (17382128)

“…We found that the catalytic activity is mainly due to the level of antibonding states filling between the Cu atom and *OCHOH intermediate. …”

Analysis of differential microbiome and classification prediction model between case and control groups. by Chuan Zhang (187157)

“…The relative importance of each genus in the predictive model was evaluated using the mean decreasing accuracy and the Gini coefficient.…”

PCA-CGAN model parameter settings. by Chao Tang (10925)

“…Experiments demonstrate that PCA-CGAN not only achieves stable convergence on a large-scale heterogeneous dataset comprising 43 patients for the first time but also resolves the “dilution effect” problem in data augmentation, avoiding the asymmetric phenomenon where Precision increases while Recall decreases. After data augmentation, the ResNet model’s average F1 score improved significantly, with particularly outstanding performance on rare categories such as atrial premature beats, far surpassing traditional methods like SigCWGAN and TD-GAN. …”