Showing 18,481 - 18,500 results of 21,342 for search '(( significant ((time decrease) OR (greatest decrease)) ) OR ( significant decrease decrease ))', query time: 0.72s Refine Results
  1. 18481

    Data Sheet 1_Impact of mini-dose dexmedetomidine supplemented analgesia on sleep structure in patients at high risk of obstructive sleep apnea: a pilot trial.docx by Pei Sun (115160)

    Published 2024
    “…Other sleep structure and sleep-respiratory parameters did not differ significantly between the two groups. Subjective sleep quality was slightly improved with dexmedetomidine on the night of surgery, but not statistically significant (median difference, 6; 95% CI, 0 to 13; p = 0.060). …”
  2. 18482

    Table 1_Protocatechuic aldehyde ameliorates high glucose-induced podocyte injury by attenuating inflammation, oxidative stress, and apoptosis via suppression of endoplasmic reticul... by Yishu Wang (845334)

    Published 2025
    “…PCA significantly reduced the secretion of inflammatory cytokines (TNF-α, IL-1β, IL-6), restored the activities of SOD and GSH-Px, decreased MDA content, and downregulated the expression of Cox-2, iNOS, Nox2, and Nox4 proteins, thereby suppressing HG-induced podocyte inflammation and oxidative stress. …”
  3. 18483

    Image 1_Automated radiosynthesis and clinical experience of [18F]SMBT-1 PET imaging for in vivo evaluation of reactive astrocyte in Parkinson's disease: a pilot study.tiff by Peerapon Kiatkittikul (22801874)

    Published 2025
    “…Healthy control also showed globally increased [<sup>18</sup>F]SMBT-1 uptake. There was no significant correlation between the degree of [<sup>18</sup>F]FDOPA uptake and [<sup>18</sup>F]SMBT-1 uptake in any brain region.…”
  4. 18484

    Internal states adjust the Brp compartmental heterogeneity through octopamine. by Hongyang Wu (8856740)

    Published 2025
    “…*<i>P</i> < 0.05 and ns = not significant. The data underlying this Figure can be found in S1 Data.…”
  5. 18485

    Evolutionarily conserved and functionally important amino acids in Artemis. by Ziwen Huang (17562948)

    Published 2025
    “…<i>P</i> values were analyzed with Student <i>t</i> test. ns, not significant.</p>…”
  6. 18486

    FLEXI interactions with RNA-binding proteins. by Jun Yao (9646)

    Published 2024
    “…RNA-binding sites: I, within introns corresponding to FLEXIs; SS-I and SS-E, bimodally enriched across the 5’- and 3’ splice sites in unspliced pre-mRNAs with the midpoints in the intron or flanking exon (SS-I and SS-E, respectively; Figs <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1011416#pgen.1011416.g004" target="_blank">4A</a> and <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1011416#pgen.1011416.s011" target="_blank">S11</a>). mRNA levels, RBPs whose knockdown resulted in significant difference in mRNA levels (increased or decreased, DESeq2 |LFC|≥1, adjusted p≤0.05) from host gene of FLEXIs with a binding site for that RBP compared to those genes whose transcripts lacked a binding site for the same RBPs based on ENCODE RBP-knockdown datasets (p≤0.05 calculated by Fisher’s exact test; <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1011416#pgen.1011416.s013" target="_blank">S13 Fig</a>). …”
  7. 18487

    Ybx1 regulation of its target mRNAs is m<sup>5</sup>C-depdendent (Related to Fig 5). by Jian Zhang (1682)

    Published 2025
    “…<p><b>(A)</b> RT-qPCR confirmed the decreased expression levels of Ybx1 target mRNAs in neural stem cells with Ybx1 knockdown using siRNA. …”
  8. 18488

    Table2_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. 18489

    Table13_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.…”
  10. 18490

    Data Sheet 1_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). …”
  11. 18491

    Table 2_Kidney sparing surgery versus radical nephroureterectomy in upper tract urothelial carcinoma: a meta-analysis and systematic review.docx by Leqing Zhou (20981021)

    Published 2025
    “…In the comparison between the endoscopic management (EM) and RNU groups, EM was associated with worse overall survival outcomes (HR,1.40; 95%CI,1.08-1.82; P=0.01) based on multivariable Cox regression analysis, and the upper tract recurrence rate (OR,39.06; 95%CI, 14.55-104.85; P<0.00001) was significantly higher in the EM group. On the other hand, in patients treated with KSS, postoperative renal function as measured by eGFR increased by 0.4ml/min/1.73 m<sup>2</sup>, while it decreased by 11.4ml/min/1.73 m<sup>2</sup> in the RNU group (WMD, 11.81 ml/min/1.73 m<sup>2</sup>; 95%CI,9.06-14.56; P<0.0001).…”
  12. 18492

    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.…”
  13. 18493

    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). …”
  14. 18494

    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.…”
  15. 18495

    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.…”
  16. 18496

    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.…”
  17. 18497

    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.…”
  18. 18498

    DataSheet_1_FCGR2/3 polymorphisms are associated with susceptibility to Kawasaki disease but do not predict intravenous immunoglobulin resistance and coronary artery aneurysms.docx by Paula Uittenbogaard (19691794)

    Published 2024
    “…Treatment with intravenous immunoglobulin (IVIg) significantly decreases the risk of CAA, possibly through competitive binding to Fc-gamma receptors (FcγRs), which reduces the binding of pathological immune complexes. …”
  19. 18499
  20. 18500

    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.…”