Proteoglycan 4 modulates osteogenic smooth muscle cell differentiation during vascular remodeling and intimal calcification

Calcification is a prominent feature of late-stage atherosclerosis, but the mechanisms driving this process are unclear. Using a biobank of carotid endarterectomies, we recently showed that Proteoglycan 4 (PRG4) is a key molecular signature of calcified plaques, expressed in smooth muscle cell (SMC) rich regions. Here, we aimed to unravel the PRG4 role in vascular remodeling and intimal calcification. PRG4 expression in human carotid endarterectomies correlated with calcification assessed by preoperative computed tomographies. PRG4 localized to SMCs in early intimal thickening, while in advanced lesions it was found in the extracellular matrix, surrounding macro-calcifications. In experimental models, Prg4 was upregulated in SMCs from partially ligated ApoE(-/-) mice and rat carotid intimal hyperplasia, correlating with osteogenic markers and TGFb1. Furthermore, PRG4 was enriched in cells positive for chondrogenic marker SOX9 and around plaque calcifications in ApoE(-/-) mice on warfarin. In vitro, PRG4 was induced in SMCs by IFNg, TGFb1 and calcifying medium, while SMC markers were repressed under calcifying conditions. Silencing experiments showed that PRG4 expression was driven by transcription factors SMAD3 and SOX9. Functionally, the addition of recombinant human PRG4 increased ectopic SMC calcification, while arresting cell migration and proliferation. Mechanistically, it suppressed endogenous PRG4, SMAD3 and SOX9, and restored SMC markers' expression. PRG4 modulates SMC function and osteogenic phenotype during intimal remodeling and macro-calcification in response to TGFb1 signaling, SMAD3 and SOX9 activation. The effects of PRG4 on SMC phenotype and calcification suggest its role in atherosclerotic plaque stability, warranting further investigations.Vascular Surger

Algorithm variability in the estimation of lung nodule volume from phantom CT scans: Results of the QIBA 3A public challenge

Rationale and Objectives Quantifying changes in lung tumor volume is important for diagnosis, therapy planning, and evaluation of response to therapy. The aim of this study was to assess the performance of multiple algorithms on a reference data set. The study was organized by the Quantitative Imaging Biomarker Alliance (QIBA). Materials and Methods The study was organized as a public challenge. Computed tomography scans of synthetic lung tumors in an anthropomorphic phantom were acquired by the Food and Drug Administration. Tumors varied in size, shape, and radiodensity. Participants applied their own semi-automated volume estimation algorithms that either did not allow or allowed post-segmentation correction (type 1 or 2, respectively). Statistical analysis of accuracy (percent bias) and precision (repeatability and reproducibility) was conducted across algorithms, as well as across nodule characteristics, slice thickness, and algorithm type. Results Eighty-four percent of volume measurements of QIBA-compliant tumors were within 15% of the true volume, ranging from 66% to 93% across algorithms, compared to 61% of volume measurements for all tumors (ranging from 37% to 84%). Algorithm type did not affect bias substantially; however, it was an important factor in measurement precision. Algorithm precision was notably better as tumor size increased, worse for irregularly shaped tumors, and on the average better for type 1 algorithms. Over all nodules meeting the QIBA Profile, precision, as measured by the repeatability coefficient, was 9.0% compared to 18.4% overall. Conclusion The results achieved in this study, using a heterogeneous set of measurement algorithms, support QIBA quantitative performance claims in terms of volume measurement repeatability for nodules meeting the QIBA Profile criteria

The implementation of novel collaborative structures for the identification and resolution of barriers to pluripotent stem cell translation.

Increased global connectivity has catalyzed technological development in almost all industries, in part through the facilitation of novel collaborative structures. Notably, open innovation and crowd-sourcing-of expertise and/or funding-has tremendous potential to increase the efficiency with which biomedical ecosystems interact to deliver safe, efficacious and affordable therapies to patients. Consequently, such practices offer tremendous potential in advancing development of cellular therapies. In this vein, the CASMI Translational Stem Cell Consortium (CTSCC) was formed to unite global thought-leaders, producing academically rigorous and commercially practicable solutions to a range of challenges in pluripotent stem cell translation. Critically, the CTSCC research agenda is defined through continuous consultation with its international funding and research partners. Herein, initial findings for all research focus areas are presented to inform global product development strategies, and to stimulate continued industry interaction around biomanufacturing, strategic partnerships, standards, regulation and intellectual property and clinical adoption