Showing 21 - 40 results of 103,032 for search '(( 5 ((((we decrease) OR (nn decrease))) OR (a decrease)) ) OR ( 2020 n decrease ))', query time: 1.59s Refine Results
  1. 21
  2. 22
  3. 23
  4. 24
  5. 25
  6. 26
  7. 27
  8. 28
  9. 29
  10. 30
  11. 31

    Image_1_miR-144-5p and miR-451a Inhibit the Growth of Cholangiocarcinoma Cells Through Decreasing the Expression of ST8SIA4.tif by Wan Fu (3681799)

    Published 2021
    “…This study aimed to investigate the action mechanism of miR-144-5p and miR-451a in cholangiocarcinoma. We found that miR-144-5p and miR-451a were significantly decreased in cholangiocarcinoma patient samples compared to the adjacent normal bile duct samples. …”
  12. 32

    Image_4_miR-144-5p and miR-451a Inhibit the Growth of Cholangiocarcinoma Cells Through Decreasing the Expression of ST8SIA4.tif by Wan Fu (3681799)

    Published 2021
    “…This study aimed to investigate the action mechanism of miR-144-5p and miR-451a in cholangiocarcinoma. We found that miR-144-5p and miR-451a were significantly decreased in cholangiocarcinoma patient samples compared to the adjacent normal bile duct samples. …”
  13. 33

    Image_3_miR-144-5p and miR-451a Inhibit the Growth of Cholangiocarcinoma Cells Through Decreasing the Expression of ST8SIA4.tif by Wan Fu (3681799)

    Published 2021
    “…This study aimed to investigate the action mechanism of miR-144-5p and miR-451a in cholangiocarcinoma. We found that miR-144-5p and miR-451a were significantly decreased in cholangiocarcinoma patient samples compared to the adjacent normal bile duct samples. …”
  14. 34

    Image_2_miR-144-5p and miR-451a Inhibit the Growth of Cholangiocarcinoma Cells Through Decreasing the Expression of ST8SIA4.tif by Wan Fu (3681799)

    Published 2021
    “…This study aimed to investigate the action mechanism of miR-144-5p and miR-451a in cholangiocarcinoma. We found that miR-144-5p and miR-451a were significantly decreased in cholangiocarcinoma patient samples compared to the adjacent normal bile duct samples. …”
  15. 35

    Individual data 2020. by Luís-Jorge Amaral (16406704)

    Published 2024
    “…Similarly, pNS incidence per 100,000 person-years decreased from 151.7 (95% CI: 112.7–203.4) to 27.0 (95% CI: 12.5–55.5). …”
  16. 36

    Household data 2020. by Luís-Jorge Amaral (16406704)

    Published 2024
    “…Similarly, pNS incidence per 100,000 person-years decreased from 151.7 (95% CI: 112.7–203.4) to 27.0 (95% CI: 12.5–55.5). …”
  17. 37

    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>…”
  18. 38

    Data_Sheet_2_Hepcidin Decreases Rotenone-Induced α-Synuclein Accumulation via Autophagy in SH-SY5Y Cells.ZIP by Meiqi Li (4169182)

    Published 2020
    “…We demonstrated that SH-SY5Y cell viability was impaired after rotenone treatment in a dose-dependent manner. α-syn expression and iron content increased under a low concentration rotenone (25 nM for 3 days) treatment in SH-SY5Y cells. …”
  19. 39

    Data_Sheet_1_Hepcidin Decreases Rotenone-Induced α-Synuclein Accumulation via Autophagy in SH-SY5Y Cells.PDF by Meiqi Li (4169182)

    Published 2020
    “…We demonstrated that SH-SY5Y cell viability was impaired after rotenone treatment in a dose-dependent manner. α-syn expression and iron content increased under a low concentration rotenone (25 nM for 3 days) treatment in SH-SY5Y cells. …”
  20. 40