Showing 145,841 - 145,860 results of 229,666 for search '(( 5 ((wt decrease) OR (nn decrease)) ) OR ( 10 ((we decrease) OR (a decrease)) ))', query time: 2.23s Refine Results
  1. 145841

    Performance of BRSA and other methods on simulated data. by Ming Bo Cai (6733568)

    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. …”
  2. 145842

    Loss of <i>bmm</i> in the neurons with an independent RNAi line has no effect on triglyceride storage or breakdown in females. by Lianna W. Wat (8339454)

    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). …”
  3. 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. by Adam D. Schneider (148548)

    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. …”
  4. 145844

    Example of predicted effects of choice bundling on preference for larger, later rewards (LLRs) over smaller, sooner rewards (SSRs). by Jeffrey S. Stein (11689918)

    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). …”
  5. 145845
  6. 145846

    Table_4_Identification and Characterization of Biomarkers and Their Role in Opioid Addiction by Integrated Bioinformatics Analysis.XLSX by Xiuning Zhang (9698756)

    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. …”
  7. 145847

    Table_6_Identification and Characterization of Biomarkers and Their Role in Opioid Addiction by Integrated Bioinformatics Analysis.XLSX by Xiuning Zhang (9698756)

    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. …”
  8. 145848

    Table_2_Identification and Characterization of Biomarkers and Their Role in Opioid Addiction by Integrated Bioinformatics Analysis.XLSX by Xiuning Zhang (9698756)

    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. …”
  9. 145849

    Table_1_Identification and Characterization of Biomarkers and Their Role in Opioid Addiction by Integrated Bioinformatics Analysis.XLSX by Xiuning Zhang (9698756)

    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. …”
  10. 145850

    Table_5_Identification and Characterization of Biomarkers and Their Role in Opioid Addiction by Integrated Bioinformatics Analysis.XLSX by Xiuning Zhang (9698756)

    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. …”
  11. 145851

    Table_3_Identification and Characterization of Biomarkers and Their Role in Opioid Addiction by Integrated Bioinformatics Analysis.XLSX by Xiuning Zhang (9698756)

    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. …”
  12. 145852
  13. 145853
  14. 145854
  15. 145855
  16. 145856
  17. 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... by Chau Yee Ng (3953372)

    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. …”
  18. 145858
  19. 145859
  20. 145860