Label-free discrimination analysis of de-differentiated vascular smooth muscle cells, mesenchymal stem cells and their vascular and osteogenic progeny using vibrational spectroscopy.

The accumulation of vascular smooth muscle (SMC)-like cells and stem cell-derived myogenic and osteogenic progeny contributes significantly to arteriosclerotic disease. This study established whether label-free vibrational spectroscopy can discriminate de-differentiated 'synthetic' SMCs from undifferentiated stem cells and their myogenic and osteogenic progeny in vitro, compared with conventional immunocytochemical and genetic analyses. TGF-ß1- and Jagged1-induced myogenic differentiation of CD44+ mesenchymal stem cells was confirmed in vitro by immunocytochemical analysis of specific SMC differentiation marker expression (α-actin, calponin and myosin heavy chain 11), an epigenetic histone mark (H3K4me2) at the myosin heavy chain 11 locus, promoter transactivation and mRNA transcript levels. Osteogenic differentiation was confirmed by alizarin red staining of calcium deposition. Fourier Transform Infrared (FTIR) maps facilitated initial screening and discrimination while Raman spectroscopy of individual cell nuclei revealed specific spectral signatures of each cell type in vitro, using Principal Components Analysis (PCA). PCA fed Linear Discriminant Analysis (LDA) enabled quantification of this discrimination and the sensitivity and specificity value was determined for all cell populations based on a leave-one-out cross validation method and revealed that de-differentiated SMCs and stem-cell derived myogenic progeny in culture shared the greatest similarity. FTIR and Raman spectroscopy discriminated undifferentiated stem cells from both their myogenic and osteogenic progeny. The ability to detect stem cell-derived myogenic progeny using label-free platforms in situ may facilitate interrogation of these important phenotypes during vascular disease progression.

Growth trajectory of preterm small-for-gestational-age neonates.

AIM: To assess the growth trajectory of preterm small-for-gestational-age (SGA) neonates compared to preterm non-small-for-gestational age neonates in the neonatal intensive care unit and special care nursery. METHODS: We conducted a retrospective cohort study at a large tertiary hospital in Victoria, Australia, examining neonates ≤34 weeks' gestation admitted to the neonatal intensive care unit or special care nursery between 2013 and 2017. We categorized neonates according to their birth weight centile: <10th centile (small-for-gestational age) and ≥10th centile (non-small-for-gestational age). Growth trajectory was tracked based on serial weights obtained in the neonatal intensive care unit and special care nursery, using z-scores derived from Fenton preterm growth charts. Our primary outcome was the change in weight z-score from birth to discharge from neonatal intensive care unit or special care nursery. RESULTS: Of the 910 babies included, 88 were small-for-gestational age and 822 were appropriate-for gestational age. Both groups had a reduction in their weight z-score; however, SGA babies had a significantly smaller reduction (-0.62 SD compared to -0.85 SD, p < .0001). Small-for-gestational-age neonates were four times more likely to experience an increase in their weight z-score across their admission compared to neonates who were not small-for-gestational age (OR 4.04, 95% CI 2.23-7.48, p < .0001). Small-for-gestational-age neonates had an increased median length of stay, increased incidence of necrotizing enterocolitis but a reduced incidence of intraventricular hemorrhage. CONCLUSIONS: Preterm SGA babies experience a smaller reduction in their weight trajectory compared to their appropriately grown counterparts in the neonatal intensive care unit or special care nursery.

Disease-Relevant Single Cell Photonic Signatures Identify S100ß Stem Cells and their Myogenic Progeny in Vascular Lesions.

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, S100ß+ 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- ß1), 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 S100ß+ vSCs and identified the presence of S100ß+vSC-derived myogenic progeny within vascular lesions. We conclude disease-relevant photonic signatures may have predictive value for vascular disease.