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. …”

Summary of subgroup analysis results. by Yongki Welliam (21030005)

“…Subgroup analysis showed that increased KIM-1 in urine or blood was strongly associated with ESRD, and decreased Fetuin-A levels in Asians had a significant association with the incidence of ESRD.…”

PRISMA Flow Chart 2020. by Yongki Welliam (21030005)

“…Subgroup analysis showed that increased KIM-1 in urine or blood was strongly associated with ESRD, and decreased Fetuin-A levels in Asians had a significant association with the incidence of ESRD.…”

Included and excluded studies. by Yongki Welliam (21030005)

“…Subgroup analysis showed that increased KIM-1 in urine or blood was strongly associated with ESRD, and decreased Fetuin-A levels in Asians had a significant association with the incidence of ESRD.…”

Characteristics of included studies. by Yongki Welliam (21030005)

“…Subgroup analysis showed that increased KIM-1 in urine or blood was strongly associated with ESRD, and decreased Fetuin-A levels in Asians had a significant association with the incidence of ESRD.…”

Extraction data table. by Yongki Welliam (21030005)

“…Subgroup analysis showed that increased KIM-1 in urine or blood was strongly associated with ESRD, and decreased Fetuin-A levels in Asians had a significant association with the incidence of ESRD.…”

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. …”

Micelle and Inverse Micelle Structure Driven Viscoelasticity and Phase Separation in 2‑Isobutoxyethanol–Water Mixtures: Insights from All-Atom Simulations by Mayank Dixit (7879364)

“…We observed the presence of the inverse micelle structure in <i>x</i>_IBE = 0.5 and micelle structures in <i>x</i>_IBE = 0.1. …”

Micelle and Inverse Micelle Structure Driven Viscoelasticity and Phase Separation in 2‑Isobutoxyethanol–Water Mixtures: Insights from All-Atom Simulations by Mayank Dixit (7879364)

“…We observed the presence of the inverse micelle structure in <i>x</i>_IBE = 0.5 and micelle structures in <i>x</i>_IBE = 0.1. …”

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. …”

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. …”

MIT-BIH dataset proportion analysis chart. 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. …”

Wavelet transform preprocessing results. 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. …”

PCAECG_GAN. 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. …”

MIT dataset expansion quantities and Proportions. 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. …”

Experimental hardware and software environment. 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. …”

PCA-CGAN K-fold experiment table. 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. …”