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). …”

Primer sequences. by Min Young Park (2886017)

“…Moreover, we used two mouse models of hypophosphatemia—induced either by dietary intervention in the form of a low phosphorus (LP) diet (0.02% of Pi) or genetically in a mouse model of X-linked hypophosphatemia (XLH)–that had opposite FGF23 levels. …”

BAI as a percent release at pH 4.5. by Ruchika Kishor Jain (19704102)

“…After BAI-RCD treatment, both cell lines showed a decrease in antioxidant stress measures (SOD, CAT, and GSH) and a significant (<i>p</i> < 0.001) increase in oxidative stress parameters (NADPH, MPO, LPO, and PC). …”

Major hyperparameters of RF-SVR. by Jintao Li (448681)

“…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R² value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”

Pseudo code for coupling model execution process. by Jintao Li (448681)

“…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R² value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”

Major hyperparameters of RF-MLPR. by Jintao Li (448681)

“…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R² value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”

Results of RF algorithm screening factors. by Jintao Li (448681)

“…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R² value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”

Schematic diagram of the basic principles of SVR. by Jintao Li (448681)

“…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R² value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”

Renal outcomes of both treatment groups. by Marwan El-Deyarbi (21688492)

“…</p><p>Conclusions</p><p>Implementing multifactorial interventions by a multidisciplinary team improved several clinical manifestations, including HbA1c, SBP, and eGFR, and decreased cardiovascular risk factors despite the decreased diabetes medication use.…”

Down-Regulation of Annexin A Proteins in Human Mesangial Cells by TEGDMA and Bis-GMA Treatment Disrupts Proteins Involved in Cellular Function by Ayse Nur Dogan (21015836)

“…Transient knockdown of annexin A2 protein expression using annexin A2 siRNA resulted in a significant decrease in alpha smooth muscle actin and non-muscle myosin protein expression in human mesangial cells when compared to cells transfected with non-targeting control siRNA. …”

Ferroptosis Induction by a New Pyrrole Derivative in Triple Negative Breast Cancer and Colorectal Cancer by Domiziana Masci (4224451)

“…Furthermore, lactoperoxidase, malondialdehyde, and Fe­(II) levels significantly increased in <b>12</b>-treated tissues, whereas superoxide dismutase concentrations decreased. …”

Ferroptosis Induction by a New Pyrrole Derivative in Triple Negative Breast Cancer and Colorectal Cancer by Domiziana Masci (4224451)

“…Furthermore, lactoperoxidase, malondialdehyde, and Fe­(II) levels significantly increased in <b>12</b>-treated tissues, whereas superoxide dismutase concentrations decreased. …”

Development of Novel PRMT7 Inhibitors for the Treatment of Prostate Cancer by Jiaxing Li (113609)

“…Herein, we reported an effective and selective PRMT7 inhibitor, <b>A33</b>, which was obtained through structural optimization and exhibited potent anti-PCa efficacy in vitro and in vivo. …”

Development of Novel PRMT7 Inhibitors for the Treatment of Prostate Cancer by Jiaxing Li (113609)

“…Herein, we reported an effective and selective PRMT7 inhibitor, <b>A33</b>, which was obtained through structural optimization and exhibited potent anti-PCa efficacy in vitro and in vivo. …”

Development of Novel PRMT7 Inhibitors for the Treatment of Prostate Cancer by Jiaxing Li (113609)

“…Herein, we reported an effective and selective PRMT7 inhibitor, <b>A33</b>, which was obtained through structural optimization and exhibited potent anti-PCa efficacy in vitro and in vivo. …”

Development of Novel PRMT7 Inhibitors for the Treatment of Prostate Cancer by Jiaxing Li (113609)

“…Herein, we reported an effective and selective PRMT7 inhibitor, <b>A33</b>, which was obtained through structural optimization and exhibited potent anti-PCa efficacy in vitro and in vivo. …”

Table 1_DYRK1A roles in human neural progenitors.xlsx by Jeremie Courraud (20871932)

“…</p>Methods<p>For the first time, we have characterized the DYRK1A interactome and study the consequences of DYRK1A depletion in human neural stem cells (hNSCs).…”