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  • 1
    In: Pediatric Pulmonology, Wiley, Vol. 56, No. 10 ( 2021-10), p. 3200-3208
    Abstract: Bronchial challenge test (BCT) measures current airways‐hyperreactivity, however, its predictive role in pre‐school children ( 〈 6 years) for the diagnosis of asthma at school age is still debatable. We aimed to find whether preschool children with a positive adenosine or methacholine BCT are more prone to asthma at school age. Methods We included children aged 6–13 years with respiratory symptoms that were previously referred to our pulmonary function laboratory for BCT (methacholine or adenosine, depending on the question asked) at age 10 months to 6 years (baseline). BCT was considered positive based on spirometry results or wheezing, desaturation, and tachypnea reactions. The primary outcome measure was asthma diagnosis at school age using the well‐validated International Study of Asthma and Allergies in Childhood (ISAAC) questionnaire. We used logistic regression analysis to explore whether positive BCT could predict school‐age asthma while including age and collected modified asthma predictive index in the model. Results One hundred and fifty‐one of 189 children (53% males), completed the ISAAC questionnaire (response rate = 80%). Mean ages at BCT and at follow‐up were 3.9 ± 1.28 and 9.4 ± 1.85 years, respectively. At baseline, 40 of 67 had a positive adenosine test and 73 of 84 had a positive methacholine BCT. Thirty‐nine children were diagnosed with asthma at school age. Logistic regression analysis showed that a positive adenosine test at pre‐school age was the best predictor, significantly increasing the odds of asthma at school age by 6.34 (95% CI: 1.23–32.81, p  = .028), while methacholine did not show significance ( p  = .69). Conclusion Choosing the relevant BCT for the question asked, positive adenosine, but not methacholine test, at pre‐school, may predict asthma at school age.
    Type of Medium: Online Resource
    ISSN: 8755-6863 , 1099-0496
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2021
    detail.hit.zdb_id: 1491904-7
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  • 2
    In: Journal of Molecular and Cellular Cardiology, Elsevier BV, Vol. 116 ( 2018-03), p. 91-105
    Type of Medium: Online Resource
    ISSN: 0022-2828
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2018
    detail.hit.zdb_id: 1469767-1
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  • 3
    Online Resource
    Online Resource
    Ovid Technologies (Wolters Kluwer Health) ; 2017
    In:  Circulation Research Vol. 121, No. suppl_1 ( 2017-07-21)
    In: Circulation Research, Ovid Technologies (Wolters Kluwer Health), Vol. 121, No. suppl_1 ( 2017-07-21)
    Abstract: The mammalian body contains several hundred cell types that share the same genome, but can express distinct gene signatures. This specification of gene expression is achieved through the activity of cis-regulatory genomic elements (CRE), such as enhancers, promoters, and silencers. The Assay for Transposase-Accessible Chromatin followed by sequencing (ATAC-seq) can identify nucleosome evicted open chromatin, an established marker of regulatory regions. Using a differential ATAC-seq approach, coupled with RNA-seq, H3K27ac ChiP-seq, and computational transcription factor (TFs) binding analysis we comprehensively mapped cell-type and condition specific cis regulatory elements for cardiac fibroblasts and cardiomyocytes, and outlined the TFs that control them. We show that in cardiomyocytes six main transcription factor groups, that control their own and each other’s expression, cooperatively bind discrete distal enhancers that are located at a variable distance from the transcription start site of their target genes. None of these factors is entirely tissue specific in expression, yet various combination of binding sites for these factors, densely clustered within a nucleosome length of genomic stretch make these CREs tissue specific. Multiple tissue specific CREs in turn, are clustered around highly tissue specific genes, and multiple factors, acting from the same and from different CREs can converge on these genes to control their tissue specific expression. Together our data puts forward a mechanistic multi-level combinatorial model for cardiac specific genes expression
    Type of Medium: Online Resource
    ISSN: 0009-7330 , 1524-4571
    RVK:
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2017
    detail.hit.zdb_id: 1467838-X
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