Predicted <i>cis</i>-acting elements in <i>DpAP2</i> promoter. by Lingru Ruan (18995544)

“…The high concentrations of MeJA (10–100 μM) inhibited the accumulation of carotenoid, and the relative expression of <i>DpAP2</i>, <i>PSY</i>, <i>PDS</i> and <i>GGPS</i> decreased significantly. On the contrary, the relative expression of <i>DpAP2</i>, <i>PDS</i> and <i>GGPS</i> increased significantly when <i>D</i>. …”

ERI Thresholds Between Adjacent Zones. by Mingyue Sun (4638535)

“…The thresholds of the ERI in the oasis zone-transition zone and the transition zone-desert zone were 0.08–0.085 and 0.111–0.118, respectively. (2) Socioeconomic factors, including infrastructure expansion, population density, and GDP, were dominant influences, contributing 64% to the ERI, whereas the influence of natural factors such as climate declined. (3) The low-ERI areas increased by 3.3% under government control, and the transition zones increased significantly, slowing the growth rate of the oasis zone. …”

Location of the study area. by Mingyue Sun (4638535)

“…The thresholds of the ERI in the oasis zone-transition zone and the transition zone-desert zone were 0.08–0.085 and 0.111–0.118, respectively. (2) Socioeconomic factors, including infrastructure expansion, population density, and GDP, were dominant influences, contributing 64% to the ERI, whereas the influence of natural factors such as climate declined. (3) The low-ERI areas increased by 3.3% under government control, and the transition zones increased significantly, slowing the growth rate of the oasis zone. …”

Random Forest structure with cross-validation. by Mingyue Sun (4638535)

“…The thresholds of the ERI in the oasis zone-transition zone and the transition zone-desert zone were 0.08–0.085 and 0.111–0.118, respectively. (2) Socioeconomic factors, including infrastructure expansion, population density, and GDP, were dominant influences, contributing 64% to the ERI, whereas the influence of natural factors such as climate declined. (3) The low-ERI areas increased by 3.3% under government control, and the transition zones increased significantly, slowing the growth rate of the oasis zone. …”

Land use change from 1990 to 2020. by Mingyue Sun (4638535)

“…The thresholds of the ERI in the oasis zone-transition zone and the transition zone-desert zone were 0.08–0.085 and 0.111–0.118, respectively. (2) Socioeconomic factors, including infrastructure expansion, population density, and GDP, were dominant influences, contributing 64% to the ERI, whereas the influence of natural factors such as climate declined. (3) The low-ERI areas increased by 3.3% under government control, and the transition zones increased significantly, slowing the growth rate of the oasis zone. …”

Geographic data. by Mingyue Sun (4638535)

“…The thresholds of the ERI in the oasis zone-transition zone and the transition zone-desert zone were 0.08–0.085 and 0.111–0.118, respectively. (2) Socioeconomic factors, including infrastructure expansion, population density, and GDP, were dominant influences, contributing 64% to the ERI, whereas the influence of natural factors such as climate declined. (3) The low-ERI areas increased by 3.3% under government control, and the transition zones increased significantly, slowing the growth rate of the oasis zone. …”

Classification accuracy. by Mingyue Sun (4638535)

“…The thresholds of the ERI in the oasis zone-transition zone and the transition zone-desert zone were 0.08–0.085 and 0.111–0.118, respectively. (2) Socioeconomic factors, including infrastructure expansion, population density, and GDP, were dominant influences, contributing 64% to the ERI, whereas the influence of natural factors such as climate declined. (3) The low-ERI areas increased by 3.3% under government control, and the transition zones increased significantly, slowing the growth rate of the oasis zone. …”

All measurement data obtained for this study. by Brendan M. Anderson (11234356)

“…One clade increased in size, one decreased, and another exhibited no substantial change. …”

Regional stratigraphic correlation. by Brendan M. Anderson (11234356)

“…One clade increased in size, one decreased, and another exhibited no substantial change. …”

Anthelmintics Derived from the Kinase Inhibitor SGI-1776 for the Treatment of Gastrointestinal Worm Infections by Mostafa A. Elfawal (22430138)

“…The unexpected SAR of compound <b>15</b> can be explained by computational modeling. We demonstrate the efficacy of optimized compound <b>50</b> as a new oral anthelmintic, which demonstrated better gut restriction properties and significantly reduced the fecundity of T. muris whipworm adults in infected mice. …”

Datasets used in the study. by Rajon Banik (12066099)

“…</p><p>Conclusion</p><p>The findings indicate a significant increase in the availability of health facilities offering modern family planning services in Bangladesh; however, a slight decline has been observed in their overall mean readiness score. …”

Flow diagram of participants selection. by Wei Huang (36889)

“…Finally, to assess the robustness of results, we conducted subgroup and sensivity analysis.</p><p>Results</p><p>Each 1-unit BRI increase elevated LMM risk by 73% (OR=1.73, 95%CI = 1.61–1.86, <i><i>p</i></i> < 0.0001). …”

Minimal data set. by Wei Huang (36889)

“…Finally, to assess the robustness of results, we conducted subgroup and sensivity analysis.</p><p>Results</p><p>Each 1-unit BRI increase elevated LMM risk by 73% (OR=1.73, 95%CI = 1.61–1.86, <i><i>p</i></i> < 0.0001). …”

Weighted comparison of baseline characteristics. by Wei Huang (36889)

“…Finally, to assess the robustness of results, we conducted subgroup and sensivity analysis.</p><p>Results</p><p>Each 1-unit BRI increase elevated LMM risk by 73% (OR=1.73, 95%CI = 1.61–1.86, <i><i>p</i></i> < 0.0001). …”

S1 File - by Ingmar Lundquist (46422)

“…Culturing at high glucose increased both nNOS and iNOS activities inducing a marked decrease in GSIS in a following short-term incubation at high glucose. …”

Design of the D-trial. by Torsten Schober (20485754)

“…Empirical models for the relationships between the investigated plant traits and PD/DVP were created using linear regression analysis preceded by a lack-of-fit test. An increase in PD led to a linear decrease in inflorescence yield per plant (<i>p</i> = 0.02), whereas a positive linear relationship was found for inflorescence yield (<i>p</i> = 0.0001) and CBD yield (<i>p</i> = 0.0002) per m². …”

Estimated mean values for light interception. by Torsten Schober (20485754)

“…Empirical models for the relationships between the investigated plant traits and PD/DVP were created using linear regression analysis preceded by a lack-of-fit test. An increase in PD led to a linear decrease in inflorescence yield per plant (<i>p</i> = 0.02), whereas a positive linear relationship was found for inflorescence yield (<i>p</i> = 0.0001) and CBD yield (<i>p</i> = 0.0002) per m². …”

Raw data V-trial. by Torsten Schober (20485754)

“…Empirical models for the relationships between the investigated plant traits and PD/DVP were created using linear regression analysis preceded by a lack-of-fit test. An increase in PD led to a linear decrease in inflorescence yield per plant (<i>p</i> = 0.02), whereas a positive linear relationship was found for inflorescence yield (<i>p</i> = 0.0001) and CBD yield (<i>p</i> = 0.0002) per m². …”

Raw data D-trial. by Torsten Schober (20485754)

“…Empirical models for the relationships between the investigated plant traits and PD/DVP were created using linear regression analysis preceded by a lack-of-fit test. An increase in PD led to a linear decrease in inflorescence yield per plant (<i>p</i> = 0.02), whereas a positive linear relationship was found for inflorescence yield (<i>p</i> = 0.0001) and CBD yield (<i>p</i> = 0.0002) per m². …”

Table 2_Prognostic significance of collagen content in solitary fibrous tumors of the central nervous system.docx by Xiaoling Li (129705)

“…Additionally, the signal intensity of SFTs on T2-weighted imaging (T2WI) decreased with increasing collagen content. Radiomics analysis identified 1,702 features from each patient’s region of interest, with 12 features showing significant differences between the high and low collagen content groups. …”