Original data1. by Lan Zeng (638254)

“…The proliferative activity, migration count, and tube formation ability of HG-treated HRMECs were significantly higher than those of the control group. …”

The raw data for S2 Fig. by Hongjoo An (21703199)

“…Luciferase assay and human and mouse brain multi-omics data show that, during the differentiation of OL precursor cells (OPCs) into OLs, the enhancer activity of Sox10-E1 does not change while that of Sox10-E2 decreases significantly. Chromatin interaction data indicate that the two <i>Sox10</i> enhancers lie close to the border of the <i>Sox10</i> topologically associating domain (TAD). …”

The raw data for Fig 6. by Hongjoo An (21703199)

“…Luciferase assay and human and mouse brain multi-omics data show that, during the differentiation of OL precursor cells (OPCs) into OLs, the enhancer activity of Sox10-E1 does not change while that of Sox10-E2 decreases significantly. Chromatin interaction data indicate that the two <i>Sox10</i> enhancers lie close to the border of the <i>Sox10</i> topologically associating domain (TAD). …”

The raw data for S4 Fig. by Hongjoo An (21703199)

“…Luciferase assay and human and mouse brain multi-omics data show that, during the differentiation of OL precursor cells (OPCs) into OLs, the enhancer activity of Sox10-E1 does not change while that of Sox10-E2 decreases significantly. Chromatin interaction data indicate that the two <i>Sox10</i> enhancers lie close to the border of the <i>Sox10</i> topologically associating domain (TAD). …”

The raw data for Fig 5B. by Hongjoo An (21703199)

“…Luciferase assay and human and mouse brain multi-omics data show that, during the differentiation of OL precursor cells (OPCs) into OLs, the enhancer activity of Sox10-E1 does not change while that of Sox10-E2 decreases significantly. Chromatin interaction data indicate that the two <i>Sox10</i> enhancers lie close to the border of the <i>Sox10</i> topologically associating domain (TAD). …”

The raw data for Fig 8A. by Hongjoo An (21703199)

“…Luciferase assay and human and mouse brain multi-omics data show that, during the differentiation of OL precursor cells (OPCs) into OLs, the enhancer activity of Sox10-E1 does not change while that of Sox10-E2 decreases significantly. Chromatin interaction data indicate that the two <i>Sox10</i> enhancers lie close to the border of the <i>Sox10</i> topologically associating domain (TAD). …”

Establishment of a diabetic rat model. by Lan Zeng (638254)

“…. * p < 0.05.VEGF is a key factor in the pathogenesis of DR [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0312791#pone.0312791.ref019" target="_blank">19</a>]. …”

Definitions of the key terms used in this study. by Eriko Takahashi (22608061)

“…A comparison of self-compassion models indicated that both one-factor and two-factor structures were valid, with the one-factor model and the negative component of the two-factor model significantly predicting well-being and appearance schemas, which in turn predicted body image concerns and abnormal eating behaviors. …”

SHAP interpretation of the optimal machine learning model. by Wentao Yang (205781)

Summary of non-randomized studies. by Solima Sabeel (9545738)

Excluded skewed studies. by Solima Sabeel (9545738)

Summary table showing analysis of randomized controlled trials stratified based on age groups. by Solima Sabeel (9545738)

Effects of cell culture patterns on injury and inflammation induced by the S1 protein. by Yanru Liu (1662463)

Effects of S1 protein and exposure duration on co-cultures of HPAEpics and AMs. by Yanru Liu (1662463)

Distribution of samples according to the geographic origin of the infection, <i>Leishmania</i> species, and LRV1 statutes. by Fredy A. Pazmiño (20613765)

Illustrative diagram of the three crash types. by Chun-Chieh Chao (2681722)

“…</p><p>Results</p><p>Significant risk factors for overtaking crashes included heavy goods vehicles (HGVs) as crash partners (AOR = 1.30, 95% CI 1.27–1.33), and elderly crash partners (AOR = 2.01, 95% CI = 1.94–2.09), and decreased risk in rural area with speed limits of 20–30 miles per hour (AOR = 0.45, 95% CI = 0.43–0.47). …”

Multivariate logistic regression results. by Chun-Chieh Chao (2681722)

“…</p><p>Results</p><p>Significant risk factors for overtaking crashes included heavy goods vehicles (HGVs) as crash partners (AOR = 1.30, 95% CI 1.27–1.33), and elderly crash partners (AOR = 2.01, 95% CI = 1.94–2.09), and decreased risk in rural area with speed limits of 20–30 miles per hour (AOR = 0.45, 95% CI = 0.43–0.47). …”

Univariate logistic regression results. by Chun-Chieh Chao (2681722)

“…</p><p>Results</p><p>Significant risk factors for overtaking crashes included heavy goods vehicles (HGVs) as crash partners (AOR = 1.30, 95% CI 1.27–1.33), and elderly crash partners (AOR = 2.01, 95% CI = 1.94–2.09), and decreased risk in rural area with speed limits of 20–30 miles per hour (AOR = 0.45, 95% CI = 0.43–0.47). …”

Fig 6 - by Takafumi Kabuto (14797727)

Subjects:

Study design. by Moazzam Tanveer (20775814)

Subjects: