Showing 3,321 - 3,340 results of 4,838 for search '(( significant decrease decrease ) OR ( significant time decrease ))~', query time: 0.48s Refine Results
  1. 3321

    Image 1_SQLE-mediated squalene metabolism promotes tumor immune evasion in pancreatic cancer.tif by Junchen Pan (19417598)

    Published 2024
    “…</p>Results<p>We show that SQLE is significantly overexpressed in pancreatic cancer, and abrogation of SQLE results in a significant increase in squalene accumulation within tumor cells. …”
  2. 3322

    Supplementary Material for: TRENDS IN HOSPITAL DISCHARGES WITH PRIMARY DIAGNOSIS OF CEREBRAL VENOUS THROMBOSIS BY AGE AND SEX IN SPAIN by figshare admin karger (2628495)

    Published 2025
    “…. +1.4 pre-2016, p = 0.019), and a reversal in younger women from decline to growth (+10.9/year post-2016, p = 0.074). Time series analysis showed a proportional decrease in younger women (p < 0.001) and a rising relative burden in older men (p < 0.001). …”
  3. 3323

    Transcriptomics insight into occupational exposure to engineered nanoparticles by Zuzana Simova (19368296)

    Published 2025
    “…</p> <p>Following PM0.1 exposure, a significant decrease in the expression of <i>DDIT4</i> and <i>FKBP5</i>, genes involved in the stress response, was detected in exposed workers. …”
  4. 3324

    Effectiveness of Self-Help plus and problem management plus interventions in providing psychological support to clients of Opioid Agonist treatment programs in Ukraine by Viktoriia Gorbunova (21728671)

    Published 2025
    “…The GAD-7, PHQ-9, LEC-5, and PCL-5 scales were used for the outcomes’ screening three times (before, immediately after, and three months after the intervention). …”
  5. 3325

    Data Sheet 1_Can posttreatment blood inflammatory markers predict poor survival in gynecologic cancer?: a systematic review and meta-analysis.xlsx by Minyong Choi (22465405)

    Published 2025
    “…Sampling within one month after therapy was significantly associated with prognosis, which may reflect the importance of sampling time in relation to the different recovery times by immune cell compartments. …”
  6. 3326

    Table1_Cognitive performance in ISS astronauts on 6-month low earth orbit missions.docx by Sheena I. Dev (20293434)

    Published 2024
    “…</p>Results<p>Cognitive performance was generally stable over time with some differences observed across mission phases for specific subtests. …”
  7. 3327

    Table 2_Global burden and trends of norovirus-associated diseases from 1990 to 2021 an observational trend study.xlsx by MengLan Zhu (20517257)

    Published 2025
    “…For trend analysis, we employed annual percentage change (EAPC) through linear regression and applied Joinpoint analysis to identify significant changes over time. A comprehensive age-period-cohort model evaluated the key mortality risk factors. …”
  8. 3328

    Data Sheet 1_Effects of continuous cropping on soil metabolomics and rhizosphere bacterial communities in Panax quinquefolius L..docx by Jian Song (4232)

    Published 2025
    “…Time-series analysis revealed a decrease in metabolites classified as lipids and lipid-like molecules and an increase in organic acids, derivatives, phenylpropanoids, and polyketides with continuous cropping. …”
  9. 3329

    Table 5_Global burden and trends of norovirus-associated diseases from 1990 to 2021 an observational trend study.xlsx by MengLan Zhu (20517257)

    Published 2025
    “…For trend analysis, we employed annual percentage change (EAPC) through linear regression and applied Joinpoint analysis to identify significant changes over time. A comprehensive age-period-cohort model evaluated the key mortality risk factors. …”
  10. 3330

    Table 3_Global burden and trends of norovirus-associated diseases from 1990 to 2021 an observational trend study.xlsx by MengLan Zhu (20517257)

    Published 2025
    “…For trend analysis, we employed annual percentage change (EAPC) through linear regression and applied Joinpoint analysis to identify significant changes over time. A comprehensive age-period-cohort model evaluated the key mortality risk factors. …”
  11. 3331

    Image 8_Can posttreatment blood inflammatory markers predict poor survival in gynecologic cancer?: a systematic review and meta-analysis.tiff by Minyong Choi (22465405)

    Published 2025
    “…Sampling within one month after therapy was significantly associated with prognosis, which may reflect the importance of sampling time in relation to the different recovery times by immune cell compartments. …”
  12. 3332

    Data Sheet 2_Effects of continuous cropping on soil metabolomics and rhizosphere bacterial communities in Panax quinquefolius L..docx by Jian Song (4232)

    Published 2025
    “…Time-series analysis revealed a decrease in metabolites classified as lipids and lipid-like molecules and an increase in organic acids, derivatives, phenylpropanoids, and polyketides with continuous cropping. …”
  13. 3333

    Image 1_Can posttreatment blood inflammatory markers predict poor survival in gynecologic cancer?: a systematic review and meta-analysis.tiff by Minyong Choi (22465405)

    Published 2025
    “…Sampling within one month after therapy was significantly associated with prognosis, which may reflect the importance of sampling time in relation to the different recovery times by immune cell compartments. …”
  14. 3334

    Supplementary Material for: Effect of Surface Perturbation Treadmill Training Program on Strategies and Kinematics of Reactive Stepping during Standing in Older Adults: A Single-Bl... by figshare admin karger (2628495)

    Published 2025
    “…Results: Both groups showed a significant decrease in the percentage of multiple-step responses (p=0.013) and a shorter total recovery time to recover balance (p=0.006). …”
  15. 3335

    Image1_Cognitive performance in ISS astronauts on 6-month low earth orbit missions.pdf by Sheena I. Dev (20293434)

    Published 2024
    “…</p>Results<p>Cognitive performance was generally stable over time with some differences observed across mission phases for specific subtests. …”
  16. 3336

    Image 7_Can posttreatment blood inflammatory markers predict poor survival in gynecologic cancer?: a systematic review and meta-analysis.tiff by Minyong Choi (22465405)

    Published 2025
    “…Sampling within one month after therapy was significantly associated with prognosis, which may reflect the importance of sampling time in relation to the different recovery times by immune cell compartments. …”
  17. 3337

    Image 1_Global burden and trends of norovirus-associated diseases from 1990 to 2021 an observational trend study.png by MengLan Zhu (20517257)

    Published 2025
    “…For trend analysis, we employed annual percentage change (EAPC) through linear regression and applied Joinpoint analysis to identify significant changes over time. A comprehensive age-period-cohort model evaluated the key mortality risk factors. …”
  18. 3338

    Table 1_Global burden and trends of norovirus-associated diseases from 1990 to 2021 an observational trend study.xlsx by MengLan Zhu (20517257)

    Published 2025
    “…For trend analysis, we employed annual percentage change (EAPC) through linear regression and applied Joinpoint analysis to identify significant changes over time. A comprehensive age-period-cohort model evaluated the key mortality risk factors. …”
  19. 3339

    Data Sheet 2_Can posttreatment blood inflammatory markers predict poor survival in gynecologic cancer?: a systematic review and meta-analysis.zip by Minyong Choi (22465405)

    Published 2025
    “…Sampling within one month after therapy was significantly associated with prognosis, which may reflect the importance of sampling time in relation to the different recovery times by immune cell compartments. …”
  20. 3340

    Table 1_Can posttreatment blood inflammatory markers predict poor survival in gynecologic cancer?: a systematic review and meta-analysis.docx by Minyong Choi (22465405)

    Published 2025
    “…Sampling within one month after therapy was significantly associated with prognosis, which may reflect the importance of sampling time in relation to the different recovery times by immune cell compartments. …”