Showing 1,261 - 1,280 results of 100,776 for search '(( 5 ((ht decrease) OR (we decrease)) ) OR ( 5 ((a decrease) OR (nn decrease)) ))', query time: 1.41s Refine Results
  1. 1261

    Image_6_TRAPS mutations in Tnfrsf1a decrease the responsiveness to TNFα via reduced cell surface expression of TNFR1.tif by Takahiko Akagi (13138338)

    Published 2022
    “…T79M is a known mutation responsible for TRAPS, whereas G87V is a TRAPS mutation that we have reported, and T90I is a variant of unknown significance. …”
  2. 1262

    Image_2_TRAPS mutations in Tnfrsf1a decrease the responsiveness to TNFα via reduced cell surface expression of TNFR1.tif by Takahiko Akagi (13138338)

    Published 2022
    “…T79M is a known mutation responsible for TRAPS, whereas G87V is a TRAPS mutation that we have reported, and T90I is a variant of unknown significance. …”
  3. 1263
  4. 1264

    Deciphering Nonbioavailable Substructures Improves the Bioavailability of Antidepressants by Serotonin Transporter by Zhi-Zheng Wang (6056033)

    Published 2023
    “…A machine learning model was developed to identify nonbioavailable substructures based on their molecular properties and shows the accuracy of 83.5%. …”
  5. 1265

    Deciphering Nonbioavailable Substructures Improves the Bioavailability of Antidepressants by Serotonin Transporter by Zhi-Zheng Wang (6056033)

    Published 2023
    “…A machine learning model was developed to identify nonbioavailable substructures based on their molecular properties and shows the accuracy of 83.5%. …”
  6. 1266

    Deciphering Nonbioavailable Substructures Improves the Bioavailability of Antidepressants by Serotonin Transporter by Zhi-Zheng Wang (6056033)

    Published 2023
    “…A machine learning model was developed to identify nonbioavailable substructures based on their molecular properties and shows the accuracy of 83.5%. …”
  7. 1267

    Deciphering Nonbioavailable Substructures Improves the Bioavailability of Antidepressants by Serotonin Transporter by Zhi-Zheng Wang (6056033)

    Published 2023
    “…A machine learning model was developed to identify nonbioavailable substructures based on their molecular properties and shows the accuracy of 83.5%. …”
  8. 1268

    Deciphering Nonbioavailable Substructures Improves the Bioavailability of Antidepressants by Serotonin Transporter by Zhi-Zheng Wang (6056033)

    Published 2023
    “…A machine learning model was developed to identify nonbioavailable substructures based on their molecular properties and shows the accuracy of 83.5%. …”
  9. 1269
  10. 1270

    Decreased MCM2-6 in Drosophila S2 Cells Does Not Generate Significant DNA Damage or Cause a Marked Increase in Sensitivity to Replication Interference by Isabelle Crevel (119003)

    Published 2011
    “…<div><p>A reduction in the level of some MCM proteins in human cancer cells (MCM5 in U20S cells or MCM3 in Hela cells) causes a rapid increase in the level of DNA damage under normal conditions of cell proliferation and a loss of viability when the cells are subjected to replication interference. …”
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  13. 1273

    Vascular Endothelial Growth Factor (VEGF) Bioavailability Regulates Angiogenesis and Intestinal Stem and Progenitor Cell Proliferation during Postnatal Small Intestinal Development by Christopher R. Schlieve (3179439)

    Published 2016
    “…<div><p>Background</p><p>Vascular endothelial growth factor (VEGF) is a highly conserved, master regulatory molecule required for endothelial cell proliferation, organization, migration and branching morphogenesis. …”
  14. 1274

    Macroalgae Decrease Growth and Alter Microbial Community Structure of the Reef-Building Coral, <em>Porites astreoides</em> by Rebecca Vega Thurber (41633)

    Published 2012
    “…To determine if macroalgae alter the coral microbiome, we conducted a field-based experiment in which the coral <em>Porites astreoides</em> was placed in competition with five species of macroalgae. …”
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  18. 1278

    Decreased antihyperglycemic drug use driven by high out-of-pocket costs despite Medicare coverage gap closure by Mugdha Gokhale (8676201)

    Published 2020
    “…<a><b>Objectives</b></a>: <a>Using the 2016 Medicare part D coverage gap as an example, we explored effects of increased out-of-pocket costs on adherence to branded </a>dipeptidyl peptidase-4 inhibitors (DPP-4i) in patients without financial subsidies, relative to subsidized patients who do not experience increased spending during the gap. …”
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