Showing 18,901 - 18,920 results of 21,342 for search '(( significant decrease decrease ) OR ( significantly improve decrease ))', query time: 0.38s Refine Results
  1. 18901

    Summertime bedroom overheating in un-airconditioned UK urban apartments: factors influencing subjective and objective sleep outcomes by Iuliana Hartescu (1249374)

    Published 2025
    “…</p><p dir="ltr">Results: Night-time (22.00-07.00) bedroom temperatures rose significantly during HN (range BL = 17.5-26.4°C; HN = 22.0-29.3°C, p<0.001) with thermal comfort (p<0.001), ‘restfulness’ (p<0.001) and TST (p<0.05) significantly decreasing, while heat-related sleep disturbance significantly increased (p<0.001). …”
  2. 18902

    Video 7_Loss of two-pore channel 2 enhances CD8+ T cell cytotoxicity and directly impairs tumour growth via MAPK axis in HCC.mp4 by Lina Ouologuem (22489549)

    Published 2025
    “…These metabolic and signalling alterations were associated with decreased tumour proliferation and increased MHC-I surface expression.…”
  3. 18903

    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. …”
  4. 18904

    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.…”
  5. 18905

    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.…”
  6. 18906

    Data Sheet 2_Comparison of percutaneous vs. cutdown access for endovascular aortic repair in the treatment of type B aortic dissection: a meta-analysis.pdf by Zhongyou Liang (22617608)

    Published 2025
    “…No statistically significant differences were observed between the two groups concerning estimated blood loss, ICU admissions, hematoma, acute kidney injury, lower extremity revascularization, ischemic colitis, and deep venous thrombosis.…”
  7. 18907

    Figure 5 from Functional Profiling of p53 and RB Cell Cycle Regulatory Proficiency Suggests Mechanism-Driven Molecular Stratification in Endometrial Carcinoma by Zelei Yang (18491142)

    Published 2025
    “…<p>Aurora kinase B inhibitor sensitive endometrial carcinoma cells show more rapidly decreasing percentages of mitotic cells than resistant models in the setting of nocodazole-induced microtubule instability. …”
  8. 18908

    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>). …”
  9. 18909

    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. …”
  10. 18910

    Table 1_COVID-19 pandemic increased ESKAPEEc bloodstream infections and amplified carbapenem resistance in Chinese children: a multicenter surveillance study (2016–2023).xls by Xiaoqiang Li (612879)

    Published 2025
    “…Between 2016–2019 and 2020–2023, resistance to ceftazidime and gentamicin decreased in Escherichia coli and Klebsiella pneumoniae while resistance to imipenem and meropenem increased. …”
  11. 18911

    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.…”
  12. 18912

    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.…”
  13. 18913

    Minimal test data set by Wenshun Sheng (21485393)

    Published 2025
    “…OSA is highly sensitive to information of different scales, and its one-time aggregation property substantially decreases the computational overhead of the model. …”
  14. 18914

    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).…”
  15. 18915

    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.…”
  16. 18916

    OSNet network structure. by Wenshun Sheng (21485393)

    Published 2025
    “…OSA is highly sensitive to information of different scales, and its one-time aggregation property substantially decreases the computational overhead of the model. …”
  17. 18917

    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.…”
  18. 18918

    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.…”
  19. 18919

    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.…”
  20. 18920

    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.…”