Search alternatives:
wt decrease » _ decrease (Expand Search), awd decreased (Expand Search), step decrease (Expand Search)
nn decrease » _ decrease (Expand Search), mean decrease (Expand Search), gy decreased (Expand Search)
we decrease » _ decrease (Expand Search), mean decrease (Expand Search), teer decrease (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
wt decrease » _ decrease (Expand Search), awd decreased (Expand Search), step decrease (Expand Search)
nn decrease » _ decrease (Expand Search), mean decrease (Expand Search), gy decreased (Expand Search)
we decrease » _ decrease (Expand Search), mean decrease (Expand Search), teer decrease (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
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145841
Performance of BRSA and other methods on simulated data.
Published 2019“…(<b>C</b>) We multiplied the design matrix of the task in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006299#pcbi.1006299.g001" target="_blank">Fig 1A</a> with the activity pattern simulated according to A and then added this “signal” to voxels in a cubical region of the ROI. …”
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145842
Loss of <i>bmm</i> in the neurons with an independent RNAi line has no effect on triglyceride storage or breakdown in females.
Published 2021“…(H) Whole-body triglyceride levels post-starvation among 5-day-old virgin <i>elav>UAS-bmm;UAS-bmm-RNAi</i> females and control females (<i>elav>+</i> and <i>+>UAS-bmm;UAS-bmm-RNAi</i>) decreased by a similar magnitude between 0 and 12 hours or 12 and 24 hours STV, demonstrating that re-expression of <i>UAS-bmm</i> rescued the effects of <i>bmm</i> loss in neurons STV (<i>p</i> = 0.0023, 0.0012, and 0.0027 for 0–12 hours and 1.0 × 10<sup>−6</sup>, 5.2 × 10<sup>−6</sup>, and 2.9 × 10<sup>−4</sup> for 12–24 hours, respectively; one-way ANOVA followed by Tukey HSD test). …”
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145843
WV phase space projection for QIF model with spike waveform, and convergent iterative theoretical predictions for <i>μ</i> > <i>μ</i>* and <i>μ</i> → 0.
Published 2016“…Inset shows the cyan trajectory in terms of decaying variables <i>x</i>*(<i>t</i>) and <i>C</i>*(<i>t</i>), and how <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0159300#pone.0159300.e084" target="_blank">Eq (22)</a> captures the initial increase and then decrease in the calcium concentration, while <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0159300#pone.0159300.e083" target="_blank">Eq (21)</a> does not. …”
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145844
Example of predicted effects of choice bundling on preference for larger, later rewards (LLRs) over smaller, sooner rewards (SSRs).
Published 2021“…The corresponding graph to the right illustrates how the discounted value (<i>V</i>) of the LLR decreases hyperbolically according to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0259830#pone.0259830.e001" target="_blank">Eq 1</a> (in this example, <i>k</i> = 0.003). …”
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145845
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145846
Table_4_Identification and Characterization of Biomarkers and Their Role in Opioid Addiction by Integrated Bioinformatics Analysis.XLSX
Published 2020“…The importance and originality of this study are provided by two aspects. Firstly, we used a variety of calculation methods to obtain hub genes; secondly, we exploited homology analysis to solve the difficult challenge that addiction-related experiments cannot be carried out in patients or healthy individuals. …”
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145847
Table_6_Identification and Characterization of Biomarkers and Their Role in Opioid Addiction by Integrated Bioinformatics Analysis.XLSX
Published 2020“…The importance and originality of this study are provided by two aspects. Firstly, we used a variety of calculation methods to obtain hub genes; secondly, we exploited homology analysis to solve the difficult challenge that addiction-related experiments cannot be carried out in patients or healthy individuals. …”
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145848
Table_2_Identification and Characterization of Biomarkers and Their Role in Opioid Addiction by Integrated Bioinformatics Analysis.XLSX
Published 2020“…The importance and originality of this study are provided by two aspects. Firstly, we used a variety of calculation methods to obtain hub genes; secondly, we exploited homology analysis to solve the difficult challenge that addiction-related experiments cannot be carried out in patients or healthy individuals. …”
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145849
Table_1_Identification and Characterization of Biomarkers and Their Role in Opioid Addiction by Integrated Bioinformatics Analysis.XLSX
Published 2020“…The importance and originality of this study are provided by two aspects. Firstly, we used a variety of calculation methods to obtain hub genes; secondly, we exploited homology analysis to solve the difficult challenge that addiction-related experiments cannot be carried out in patients or healthy individuals. …”
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145850
Table_5_Identification and Characterization of Biomarkers and Their Role in Opioid Addiction by Integrated Bioinformatics Analysis.XLSX
Published 2020“…The importance and originality of this study are provided by two aspects. Firstly, we used a variety of calculation methods to obtain hub genes; secondly, we exploited homology analysis to solve the difficult challenge that addiction-related experiments cannot be carried out in patients or healthy individuals. …”
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145851
Table_3_Identification and Characterization of Biomarkers and Their Role in Opioid Addiction by Integrated Bioinformatics Analysis.XLSX
Published 2020“…The importance and originality of this study are provided by two aspects. Firstly, we used a variety of calculation methods to obtain hub genes; secondly, we exploited homology analysis to solve the difficult challenge that addiction-related experiments cannot be carried out in patients or healthy individuals. …”
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145852
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145853
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145854
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145855
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145856
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145857
Image_1_Skin Interstitial Fluid and Plasma Multiplex Cytokine Analysis Reveals IFN-γ Signatures and Granzyme B as Useful Biomarker for Activity, Severity and Prognosis Assessment i...
Published 2022“…By way of comparison, no significant changes in IL-1β, IL-13, IL-15, IL-17A, IL-18 were observed. Receiver operating characteristic analysis revealed that IFN-γ is the most sensitive and specific marker in predicting disease activity, followed by CXCL10 and GzmB. …”
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145858
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145859
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145860