Search alternatives:
significantly predicted » significantly reduced (Expand Search), significantly reduce (Expand Search), significant predictor (Expand Search)
predicted decrease » predicted secreted (Expand Search), reported decrease (Expand Search)
linear decrease » linear increase (Expand Search)
significantly predicted » significantly reduced (Expand Search), significantly reduce (Expand Search), significant predictor (Expand Search)
predicted decrease » predicted secreted (Expand Search), reported decrease (Expand Search)
linear decrease » linear increase (Expand Search)
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Nineteen SNPs with significant association (<i>P < </i>5 × 10<sup>−8</sup>) with risk on minJSW decrease in knee OA.
Published 2025“…<p>Nineteen SNPs with significant association (<i>P < </i>5 × 10<sup>−8</sup>) with risk on minJSW decrease in knee OA.…”
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Statistically significant linear increase in use of antidepressants during the observed time period.
Published 2025Subjects: -
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The figure shows that <i>R</i><sub>0</sub> decreases significantly under control strategies, particularly at temperatures near the peak transmission range, indicating the effectiveness of control mechanisms applied.
Published 2025“…<p>The figure shows that <i>R</i><sub>0</sub> decreases significantly under control strategies, particularly at temperatures near the peak transmission range, indicating the effectiveness of control mechanisms applied.…”
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The flexural lumber properties of Pinus patula Schiede ex Schltdl. & Cham. improve with decreasing initial tree spacing
Published 2025“…After accounting for ring width differences, there remained a significant effect of initial spacing on the parameters of models predicting microfibril angle and wood density.…”
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Validation of genetic markers for risk of OA or knee OA for decrease in minJSW.
Published 2025“…The red line represents the significance threshold (<i>P < </i>5 × 10<sup>−8</sup>). …”
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STL Linear Combination Forecast Graph.
Published 2025“…<div><p>This study constructs a multi-stage hybrid forecasting model using hog price time series data and its influencing factors to improve prediction accuracy. First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. …”