التفاصيل البيبلوغرافية
| العنوان: |
Disease-relevant single cell photonic signatures identify S100β stem cells and their myogenic progeny in vascular lesions |
| المؤلفون: |
Molony, Claire, King, Damien, Di Luca, Mariana, Kitching, Michael, Olayinka, Abidemi, Hakimjavadi, Roya, Julius, Lourdes A.N., Fitzpatrick, Emma, Gusti, Yusof, Burtenshaw, Denise, Healy, Killian, Finlay, Emma K., Kernan, David, Llobera, Andreu, Liu, Weimin, Morrow, David, Redmond, Eileen M., Ducrée, Jens, Paul, Cahill |
| المصدر: |
Molony, Claire, King, Damien, Di Luca, Mariana, Kitching, Michael orcid:0000-0002-9884-0790 , Olayinka, Abidemi, Hakimjavadi, Roya, Julius, Lourdes A.N., Fitzpatrick, Emma, Gusti, Yusof, Burtenshaw, Denise orcid:0000-0002-5958-1773 , Healy, Killian, Finlay, Emma K. orcid:0000-0003-0621-2744 , Kernan, David, Llobera, Andreu orcid:0000-0002-2941-478X , Liu, Weimin, Morrow, David, Redmond, Eileen M. orcid:0000-0001-8642-4418 , Ducrée, Jens orcid:0000-0002-0366-1897 and Paul, Cahill orcid:0000-0002-5385-6502 (2021) Disease-relevant single cell photonic signatures identify S100β stem cells and their myogenic progeny in vascular lesions. Stem Cell Reviews and Reports, 17 . pp. 1713-1740. ISSN 2629-3269 |
| بيانات النشر: |
Springer |
| سنة النشر: |
2021 |
| المجموعة: |
Dublin City University: DCU Online Research Access Service (DORAS) |
| مصطلحات موضوعية: |
Photonics, Autofluorescence imaging, S100β vascular stem cells, Carotid artery ligation, Lineage tracing, arteriosclerosis, Smooth muscle differentiation, Multivariate analysis, Supervised machine learning |
| الوصف: |
A hallmark of subclinical atherosclerosis is the accumulation of vascular smooth muscle cell (SMC)-like cells leading to intimal thickening and lesion formation. While medial SMCs contribute to vascular lesions, the involvement of resident vascular stem cells (vSCs) remains unclear. We evaluated single cell photonics as a discriminator of cell phenotype in vitro before the presence of vSC within vascular lesions was assessed ex vivo using supervised machine learning and further validated using lineage tracing analysis. Using a novel lab-on-a-Disk(Load) platform, label-free single cell photonic emissions from normal and injured vessels ex vivo were interrogated and compared to freshly isolated aortic SMCs, cultured Movas SMCs, macrophages, B-cells, S100β+ mVSc, bone marrow derived mesenchymal stem cells (MSC) and their respective myogenic progeny across five broadband light wavelengths (λ465- λ670 ± 20 nm). We found that profiles were of sufficient coverage, specificity, and quality to clearly distinguish medial SMCs from different vascular beds (carotid vs aorta), discriminate normal carotid medial SMCs from lesional SMC-like cells ex vivo following flow restriction, and identify SMC differentiation of a series of multipotent stem cells following treatment with transforming growth factor beta 1 (TGF- β1), the Notch ligand Jagged1, and Sonic Hedgehog using multivariate analysis, in part, due to photonic emissions from enhanced collagen III and elastin expression. Supervised machine learning supported genetic lineage tracing analysis of S100β+ vSCs and identified the presence of S100β+vSC-derived myogenic progeny within vascular lesions. We conclude disease-relevant photonic signatures may have predictive value for vascular disease. |
| نوع الوثيقة: |
article in journal/newspaper |
| وصف الملف: |
application/pdf |
| اللغة: |
English |
| Relation: |
http://doras.dcu.ie/27470/1/s12015-021-10125-x.pdf; https://dx.doi.org/10.1007/s12015-021-10125-x; http://doras.dcu.ie/27470/ |
| الاتاحة: |
http://doras.dcu.ie/27470/ |
| Rights: |
© 2021 The Authors. Open Access (CC BY 4.0) |
| رقم الانضمام: |
edsbas.FDCBA462 |
| قاعدة البيانات: |
BASE |