Showing 2,641 - 2,660 results of 106,807 for search '(( a de decrease ) OR ( 5 ((((nn decrease) OR (point decrease))) OR (a decrease)) ))', query time: 1.31s Refine Results
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    Image_1_The prevalence of diabetes and thyroid related autoantibodies in Sri Lankan children with type 1 diabetes and their unaffected siblings – The utility of a new screening ass... by Navoda Atapattu (14570081)

    Published 2023
    “…</p>Results<p>The median age (IQR) of 235 T1D children and 252 unaffected siblings was 11 (8.4, 13.2) and 9 (5.4, 14.9) years respectively, and the duration of T1D was 23 (7, 54) months. (1) T1D children (a) 79.1% were 3-Screen positive; (b) all 3-Screen positives were individual antibody positive (GADA in 74%; IA-2A 31.1%; ZnT8A 38.7%); (c) and were younger (p=0.01 vs 3-Screen negatives); (d) multiple autoantibodies were present in 45.1%; (e) IA-2A (p=0.002) and ZnT8A (p=0.006) prevalence decreased with T1D duration. …”
  3. 2643

    DataSheet_1_The prevalence of diabetes and thyroid related autoantibodies in Sri Lankan children with type 1 diabetes and their unaffected siblings – The utility of a new screening... by Navoda Atapattu (14570081)

    Published 2023
    “…</p>Results<p>The median age (IQR) of 235 T1D children and 252 unaffected siblings was 11 (8.4, 13.2) and 9 (5.4, 14.9) years respectively, and the duration of T1D was 23 (7, 54) months. (1) T1D children (a) 79.1% were 3-Screen positive; (b) all 3-Screen positives were individual antibody positive (GADA in 74%; IA-2A 31.1%; ZnT8A 38.7%); (c) and were younger (p=0.01 vs 3-Screen negatives); (d) multiple autoantibodies were present in 45.1%; (e) IA-2A (p=0.002) and ZnT8A (p=0.006) prevalence decreased with T1D duration. …”
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    Disruptive Effects of Resveratrol on a Bacterial Pathogen of Beans by Bret Cooper (1677646)

    Published 2022
    “…A motility assay confirmed a reduction in R5 flagellar movement in resveratrol, and mass spectrometry of metabolite extracts confirmed decreased pools of guanosine 5′-monophosphate and adenosine 5′-monophosphate. …”
  8. 2648

    Disruptive Effects of Resveratrol on a Bacterial Pathogen of Beans by Bret Cooper (1677646)

    Published 2022
    “…A motility assay confirmed a reduction in R5 flagellar movement in resveratrol, and mass spectrometry of metabolite extracts confirmed decreased pools of guanosine 5′-monophosphate and adenosine 5′-monophosphate. …”
  9. 2649

    Disruptive Effects of Resveratrol on a Bacterial Pathogen of Beans by Bret Cooper (1677646)

    Published 2022
    “…A motility assay confirmed a reduction in R5 flagellar movement in resveratrol, and mass spectrometry of metabolite extracts confirmed decreased pools of guanosine 5′-monophosphate and adenosine 5′-monophosphate. …”
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  18. 2658

    Trypanosome locomotion with a decreased body stiffness of , which leads to an increase in both the swimming velocity and rotation frequency when compared to the reference case in S1V. by Florian A. Overberg (21402904)

    Published 2025
    “…<p>Trypanosome locomotion with a decreased body stiffness of , which leads to an increase in both the swimming velocity and rotation frequency when compared to the reference case in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1013111#pcbi.1013111.s003" target="_blank">S1V</a>.…”
  19. 2659

    The prediction result is displayed on the hotel dataset, which includes the training procedure when the loss function is decreased and the model saved with training rounds as a multiple of five. by Hongxia Wang (241142)

    Published 2025
    “…<p>The prediction result is displayed on the hotel dataset, which includes the training procedure when the loss function is decreased and the model saved with training rounds as a multiple of five.…”
  20. 2660

    Image5_Repression of enhancer RNA PHLDA1 promotes tumorigenesis and progression of Ewing sarcoma via decreasing infiltrating T‐lymphocytes: A bioinformatic analysis.TIF by Runzhi Huang (7428713)

    Published 2022
    “…External validation based on multidimensional online databases and scRNA-seq analysis were used to verify our key findings.</p><p>Results: A six-different-dimension regulatory network was constructed based on 17 DEeRNAs, 29 DETFs, 9 DETGs, 5 immune cells, 24 immune gene sets, and 8 hallmarks of cancer. …”