يعرض 1,741 - 1,746 نتائج من 1,746 نتيجة بحث عن '(( significant ((shape based) OR (target based)) ) OR ( significant decrease decrease ))', وقت الاستعلام: 0.09s تنقيح النتائج
  1. 1741

    Proteomics Analysis of Human Obesity Reveals the Epigenetic Factor HDAC4 as a Potential Target for Obesity حسب Mohamed Abu-Farha (18535590)

    منشور في 2013
    "…In functional assays, our data indicated that ectopic expression of HDAC4 significantly impaired TNF-α-dependent activation of NF-κB, establishing thus a link between HDAC4 and regulation of the immune system. …"
  2. 1742
  3. 1743

    The impact of metformin therapy for gestational diabetes on fetal growth in women with risk factors for fetal growth restriction- a registry-based study from Qatar حسب Komal Rafique (17075074)

    منشور في 2023
    "…</p> <h3>Conclusion</h3> <p>The results of this study suggest that in women with additional risk factors for FGR, the concurrent use of metformin significantly decreases the birthweight and increases the risk for LBW, SFD, PTB and admission to NICU. …"
  4. 1744

    Theoretical insight into effect of cation–anion pairs on CO<sub>2</sub> reduction on bismuth electrocatalysts حسب Sun Hee Yoon (7179263)

    منشور في 2020
    "…The adsorption energy (Eads) and work function (Wf) of the anions increases with decreasing anion size (i.e., Cl<sup>−</sup> > Br<sup>−</sup> > I<sup>−</sup>). …"
  5. 1745

    Exergames versus self-regulated exercises with instruction leaflets to improve adherence during geriatric rehabilitation: a randomized controlled trial حسب Peter Oesch (3572426)

    منشور في 2017
    "…Adherence was comparable at day one (38 min. in the EG and 42 min. in the CG) and significantly higher in the CG at day 10 (54 min. in the CG while decreasing to 28 min. in the EG, <i>p</i> = 0.007, ES 0.94, 0.39–0.151). …"
  6. 1746

    Artificial Intelligence Frameworks for Sentiment Variations’ Reasoning and Emerging Topic Detection حسب ALATTAR, FUAD ABDELWAHAB ABDELQADER

    منشور في 2021
    "…Many studies were conducted during the last two decades to help users tracking public sentiments about entities, products, events, or other targets. However, these techniques focus on extracting overall positive/negative/neutral polarity of texts without identifying the main reasons for extracted sentiments. …"
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