Showing 19,321 - 19,340 results of 21,342 for search '(( ((significant based) OR (significant changes)) decrease ) OR ( significant decrease decrease ))', query time: 0.65s Refine Results
  1. 19321

    Table12_Unveiling the molecular landscape of PCOS: identifying hub genes and causal relationships through bioinformatics and Mendelian randomization.xlsx by Yifang He (18126257)

    Published 2024
    “…</p>Conclusions<p>Our bioinformatics combined with MR analysis revealed that CD93, CYBB, DOCK8, IRF1, MBOAT1, MYO1F, NLRP1, NOD2, PIK3R1 increase the risk of PCOS, while PTER decreases the risk of PCOS. This discovery has implications for clinical decision-making in terms of disease diagnosis, prognosis, treatment strategies, and opens up novel avenues for drug development.…”
  2. 19322

    Data Sheet 2_Perceived benefits and barriers to the use of long-acting injectable antiretroviral treatment among adolescents and young people living with HIV in Western Kenya: qual... by Shukri A. Hassan (14245301)

    Published 2025
    “…Introduction<p>Adolescents and young people living with HIV (AYPLHIV) face significant hurdles in adhering to daily oral antiretroviral therapy (ART). …”
  3. 19323

    Table3_Unveiling the molecular landscape of PCOS: identifying hub genes and causal relationships through bioinformatics and Mendelian randomization.xlsx by Yifang He (18126257)

    Published 2024
    “…</p>Conclusions<p>Our bioinformatics combined with MR analysis revealed that CD93, CYBB, DOCK8, IRF1, MBOAT1, MYO1F, NLRP1, NOD2, PIK3R1 increase the risk of PCOS, while PTER decreases the risk of PCOS. This discovery has implications for clinical decision-making in terms of disease diagnosis, prognosis, treatment strategies, and opens up novel avenues for drug development.…”
  4. 19324

    Table9_Unveiling the molecular landscape of PCOS: identifying hub genes and causal relationships through bioinformatics and Mendelian randomization.xlsx by Yifang He (18126257)

    Published 2024
    “…</p>Conclusions<p>Our bioinformatics combined with MR analysis revealed that CD93, CYBB, DOCK8, IRF1, MBOAT1, MYO1F, NLRP1, NOD2, PIK3R1 increase the risk of PCOS, while PTER decreases the risk of PCOS. This discovery has implications for clinical decision-making in terms of disease diagnosis, prognosis, treatment strategies, and opens up novel avenues for drug development.…”
  5. 19325

    Image1_Unveiling the molecular landscape of PCOS: identifying hub genes and causal relationships through bioinformatics and Mendelian randomization.tif by Yifang He (18126257)

    Published 2024
    “…</p>Conclusions<p>Our bioinformatics combined with MR analysis revealed that CD93, CYBB, DOCK8, IRF1, MBOAT1, MYO1F, NLRP1, NOD2, PIK3R1 increase the risk of PCOS, while PTER decreases the risk of PCOS. This discovery has implications for clinical decision-making in terms of disease diagnosis, prognosis, treatment strategies, and opens up novel avenues for drug development.…”
  6. 19326

    Table7_Unveiling the molecular landscape of PCOS: identifying hub genes and causal relationships through bioinformatics and Mendelian randomization.xlsx by Yifang He (18126257)

    Published 2024
    “…</p>Conclusions<p>Our bioinformatics combined with MR analysis revealed that CD93, CYBB, DOCK8, IRF1, MBOAT1, MYO1F, NLRP1, NOD2, PIK3R1 increase the risk of PCOS, while PTER decreases the risk of PCOS. This discovery has implications for clinical decision-making in terms of disease diagnosis, prognosis, treatment strategies, and opens up novel avenues for drug development.…”
  7. 19327
  8. 19328

    Table6_Unveiling the molecular landscape of PCOS: identifying hub genes and causal relationships through bioinformatics and Mendelian randomization.xlsx by Yifang He (18126257)

    Published 2024
    “…</p>Conclusions<p>Our bioinformatics combined with MR analysis revealed that CD93, CYBB, DOCK8, IRF1, MBOAT1, MYO1F, NLRP1, NOD2, PIK3R1 increase the risk of PCOS, while PTER decreases the risk of PCOS. This discovery has implications for clinical decision-making in terms of disease diagnosis, prognosis, treatment strategies, and opens up novel avenues for drug development.…”
  9. 19329

    DataSheet1_Effects of mesenchymal stromal cells and human recombinant Nerve Growth Factor delivered by bioengineered human corneal lenticule on an innovative model of diabetic reti... by Letizia Pelusi (9606879)

    Published 2024
    “…In the last years, mesenchymal stromal cells (MSCs) and neurotrophins like Nerve Growth Factor (NGF), have garnered significant attention as innovative therapeutic approaches targeting DR-associated neurodegeneration. …”
  10. 19330
  11. 19331

    Data Sheet 1_Unilateral biportal endoscopic transforaminal lumbar interbody fusion versus minimally invasive transforaminal lumbar interbody fusion for single-level lumbar spondylo... by Yu Zhang (12946)

    Published 2025
    “…Compared with MIS-TLIF, ULIF demonstrated significantly reduced intraoperative blood loss [WMD = −35.71, 95% CI (−51.80, −19.63), p < 0.01], fewer intraoperative fluoroscopy times [WMD = −1.29, 95% CI (−2.56, −0.02), p < 0.05], lower postoperative drainage volume [WMD = −20.64, 95% CI (−37.13, −4.15), p = 0.01], shorter postoperative ambulation time [WMD = −0.30, 95% CI (−0.42, −0.17), p < 0.01], and decreased hospital stay duration [WMD = −1.50, 95% CI (−2.09, −0.90), p < 0.01]. …”
  12. 19332
  13. 19333
  14. 19334

    Data Sheet 2_Unilateral biportal endoscopic transforaminal lumbar interbody fusion versus minimally invasive transforaminal lumbar interbody fusion for single-level lumbar spondylo... by Yu Zhang (12946)

    Published 2025
    “…Compared with MIS-TLIF, ULIF demonstrated significantly reduced intraoperative blood loss [WMD = −35.71, 95% CI (−51.80, −19.63), p < 0.01], fewer intraoperative fluoroscopy times [WMD = −1.29, 95% CI (−2.56, −0.02), p < 0.05], lower postoperative drainage volume [WMD = −20.64, 95% CI (−37.13, −4.15), p = 0.01], shorter postoperative ambulation time [WMD = −0.30, 95% CI (−0.42, −0.17), p < 0.01], and decreased hospital stay duration [WMD = −1.50, 95% CI (−2.09, −0.90), p < 0.01]. …”
  15. 19335

    Table11_Unveiling the molecular landscape of PCOS: identifying hub genes and causal relationships through bioinformatics and Mendelian randomization.xlsx by Yifang He (18126257)

    Published 2024
    “…</p>Conclusions<p>Our bioinformatics combined with MR analysis revealed that CD93, CYBB, DOCK8, IRF1, MBOAT1, MYO1F, NLRP1, NOD2, PIK3R1 increase the risk of PCOS, while PTER decreases the risk of PCOS. This discovery has implications for clinical decision-making in terms of disease diagnosis, prognosis, treatment strategies, and opens up novel avenues for drug development.…”
  16. 19336

    Data Sheet 1_Cross-species analysis of FcγRIIa/b (CD32a/b) polymorphisms at position 131: structural and functional insights into the mechanism of IgG- mediated phagocytosis in hum... by William D. Tolbert (7870697)

    Published 2025
    “…In contrast, allele-specific effects in macaques were highly significant; the macaque P<sup>131</sup> variant showing uniformly reduced IgG affinity. …”
  17. 19337

    DataSheet1_Erlotinib regulates short-term memory, tau/Aβ pathology, and astrogliosis in mouse models of AD.doc by Hyun-ju Lee (7550741)

    Published 2024
    “…Moreover, erlotinib treatment decreased astrogliosis in 6-month-old PS19 mice and reduced proinflammatory responses in primary astrocytes (PACs) from PS19 mice. …”
  18. 19338
  19. 19339

    Data Sheet 1_Metformin upregulates circadian gene PER2 to inhibit growth and enhance the sensitivity of glioblastoma cell lines to radiotherapy via SIRT2/G6PD pathway.docx by Hailiang Li (740080)

    Published 2025
    “…Meanwhile, NADPH+ production and G6PDH enzyme activity significantly decreased. Further study validated that metformin inhibited the cell growth of GBM cell lines through up-regulating PER2 and inhibited SIRT2/G6PD signaling pathway, enhancing radiotherapy(RT) sensitivity. …”
  20. 19340

    Table8_Unveiling the molecular landscape of PCOS: identifying hub genes and causal relationships through bioinformatics and Mendelian randomization.xlsx by Yifang He (18126257)

    Published 2024
    “…</p>Conclusions<p>Our bioinformatics combined with MR analysis revealed that CD93, CYBB, DOCK8, IRF1, MBOAT1, MYO1F, NLRP1, NOD2, PIK3R1 increase the risk of PCOS, while PTER decreases the risk of PCOS. This discovery has implications for clinical decision-making in terms of disease diagnosis, prognosis, treatment strategies, and opens up novel avenues for drug development.…”