Showing 161 - 180 results of 21,342 for search '(( significant decrease decrease ) OR ((( significant i decrease ) OR ( significant a decrease ))))', query time: 0.80s Refine Results
  1. 161
  2. 162
  3. 163

    Mechlorethamine gel causes epithelium thinning, epithelium-stroma separation, and decreased total stroma cell count. by Ana M. Sandoval-Castellanos (11611315)

    Published 2025
    “…<p>A) Epithelium thickness decreased, and B) the percentage of epithelium-stroma separation increased after NM exposure. …”
  4. 164
  5. 165
  6. 166
  7. 167
  8. 168

    Decreased childhood asthma hospitalizations linked to hotter, drier climate with lower wind speed in drylands by Klézio Silva Monte (20579829)

    Published 2025
    “…Monthly trends in hospitalizations and climatic variables were calculated. A generalized additive model analyzed the association between these trends, and the Mann-Kendall test determined if trends were increasing, decreasing, or not significant. …”
  9. 169

    Presentation 1_Prehospital tranexamic acid decreases early mortality in trauma patients: a systematic review and meta-analysis.pdf by Yi Li (1144)

    Published 2025
    “…Compared to the control group, the prehospital TXA group exhibited a significant reduction in 24-h mortality with an OR of 0.72 and a 95% CI of 0.54–0.94 (p = 0.02), while no statistically significant difference in the incidence of venous thromboembolism (VTE; OR: 1.14, 95% CI: 0.98–1.33, p = 0.09). …”
  10. 170

    Table_1_FMT intervention decreases urine 5-HIAA levels: a randomized double-blind controlled study.DOCX by Lihong Wang (14991)

    Published 2024
    “…However, in the placebo group, GSRS, CARS, and SRS scores showed no significant changes, while ABC scores decreased from 72 to 58.75 (p = 0.034). …”
  11. 171

    Supplementary Material for: Longitudinal Decrease in Left Ventricular Size with Age: Impact on Mortality and Cardiovascular Hospitalization by figshare admin karger (2628495)

    Published 2025
    “…Sensitivity analysis using annual LVEDD change (>1mm/year) demonstrated a significant association with mortality (HR 1.45, 95% CI 1.26-1.66, p<0.001) and the combined endpoint of death/cardiovascular hospitalization (HR 1.26, 95% CI 1.12-1.41, p<0.001). …”
  12. 172
  13. 173
  14. 174
  15. 175

    Data from: Colony losses of stingless bees increase in agricultural areas, but decrease in forested areas by Malena Sibaja Leyton (18400983)

    Published 2025
    “…</p><p><br></p><p dir="ltr">#METADATA</p><p dir="ltr">#'data.frame': 472 obs. of 28 variables:</p><p dir="ltr"> #$ ID: Factor variable; a unique identity for the response to the survey</p><p dir="ltr"> #$ Year: Factor variable; six factors available (2016, 2017, 2018, 2019, 2020, 2021) representing the year for the response to the survey</p><p dir="ltr"> #$ N_dead_annual: Numeric variable; representing the number of colonies annually lost</p><p dir="ltr">#$ N_alive_annual: Numeric variable; representing the number of colonies annually alive</p><p dir="ltr"> #$ N_dead_dry: Numeric variable; representing the number of colonies lost during the dry season</p><p dir="ltr">#$ N_alive_dry: Numeric variable; representing the number of colonies alive during the dry season</p><p dir="ltr"> #$ N_dead_rainy: Numeric variable; representing the number of colonies lost during the rainy season</p><p dir="ltr">#$ N_alive_rainy: Numeric variable; representing the number of colonies alive during the rainy season</p><p dir="ltr"> #$ Education: Factor variable; four factors are available ("Self-taught","Learned from another melip","Intro training","Formal tech training"), representing the training level in meliponiculture</p><p dir="ltr"> #$ Operation_Size: Numeric variable; representing the number of colonies managed by the participant (in n)</p><p dir="ltr"> #$ propAgri: Numeric variable; representing the percentage of agricultural area surrounding the meliponary (in %)</p><p dir="ltr"> #$ propForest: Numeric variable; representing the percentage of forested area surrounding the meliponary (in %)</p><p dir="ltr">#$ temp.avg_annual: Numeric variable; representing the average annual temperature (in ºC)</p><p dir="ltr">#$ precip_annual_sum: Numeric variable; representing the total accumulated precipitation (in mm)</p><p dir="ltr">#$ precip_Oct_March_sum: Numeric variable; representing the total accumulated precipitation between October to March (in mm)</p><p dir="ltr">#$ precip_Apri_Sept_sum: Numeric variable; representing the total accumulated precipitation between April to September (in mm)</p><p dir="ltr">#$ temp.avg_Oct_March: Numeric variable; representing the total accumulated precipitation between October to March (in ºC)</p><p dir="ltr">#$ temp.avg_Apri_Sept: Numeric variable; representing the total accumulated precipitation between April to September (in ºC)</p><p dir="ltr"> #$ Importance_dead: Factor variable; three factors are available Normal","High","Very high"), representing the perception of the significance of annual colony losses</p><p dir="ltr"> #$ Climatic_environmental: Binary variable; representing if the participant considered climatic and environmental problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr"> #$ Contamination: Binary variable; representing if the participant considered contamination problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr"> #$ Nutritional: Binary variable; representing if the participant considered nutritional problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr">#$ Sanitary: Binary variable; representing if the participant considered sanitary problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr">#$ Queen: Binary variable; representing if the participant considered queen problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr">#$ Time: Binary variable; representing if the participant considered time problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr">#$ Economic: Binary variable; representing if the participant considered economic problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr">#$ Attacks: Binary variable; representing if the participant considered time attacks as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr">#$ Swarming: Binary variable; representing if the participant considered swarming problems as a potential driver (1) or not (0) of their annual colony losses</p><p><br></p>…”
  16. 176

    Decreased synthesis of VCAM-1, tubulin and dynein proteins in the heart of mice stimulated with EVs (green) or ICs (blue). by Alberto Cornet-Gomez (10676133)

    Published 2025
    “…<p>Confocal microscopy images of heart sections incubated with specific antibodies against VCAM-1 <b>(A)</b>, tubulin <b>(B)</b> and dynein <b>(C)</b> showed a decrease in fluorescence signals in samples from the EVs and ICs groups. …”
  17. 177
  18. 178
  19. 179
  20. 180