Computational fluid dynamic analysis of bioprinted self-supporting perfused tissue models

Natural tissues are incorporated with vasculature, which is further integrated with a cardiovascular system responsible for driving perfusion of nutrient‐rich oxygenated blood through the vasculature to support cell metabolism within most cell‐dense tissues. Since scaffold‐free biofabricated tissues being developed into clinical implants, research models, and pharmaceutical testing platforms should similarly exhibit perfused tissue‐like structures, we generated a generalizable biofabrication method resulting in self‐supporting perfused (SSuPer) tissue constructs incorporated with perfusible microchannels and integrated with the modular FABRICA perfusion bioreactor. As proof of concept, we perfused an MLO‐A5 osteoblast‐based SSuPer tissue in the FABRICA. Although our resulting SSuPer tissue replicated vascularization and perfusion observed in situ, supported its own weight, and stained positively for mineral using Von Kossa staining, our in vitro results indicated that computational fluid dynamics (CFD) should be used to drive future construct design and flow application before further tissue biofabrication and perfusion. We built a CFD model of the SSuPer tissue integrated in the FABRICA and analyzed flow characteristics (net force, pressure distribution, shear stress, and oxygen distribution) through five SSuPer tissue microchannel patterns in two flow directions and at increasing flow rates. Important flow parameters include flow direction, fully developed flow, and tissue microchannel diameters matched and aligned with bioreactor flow channels. We observed that the SSuPer tissue platform is capable of providing direct perfusion to tissue constructs and proper culture conditions (oxygenation, with controllable shear and flow rates), indicating that our approach can be used to biofabricate tissue representing primary tissues and that we can model the system in silico

AGE-modified basement membrane cooperates with Endo180 to promote epithelial cell invasiveness and decrease prostate cancer survival

Biomechanical strain imposed by age-related thickening of the basal lamina and augmented tissue stiffness in the prostate gland coincides with increased cancer risk. Here we hypothesized that the structural alterations in the basal lamina associated with age can induce mechanotransduction pathways in prostate epithelial cells (PECs) to promote invasiveness and cancer progression. To demonstrate this, we developed a 3D model of PEC acini in which thickening and stiffening of basal lamina matrix was induced by advanced glycation end-product (AGE)-dependent non-enzymatic crosslinking of its major components, collagen IV and laminin. We used this model to demonstrate that antibody targeted blockade of CTLD2, the second of eight C-type lectin-like domains in Endo180 (CD280, CLEC13E, KIAA0709, MRC2, TEM9, uPARAP) that can recognize glycosylated collagens, reversed actinomyosin-based contractility [myosin-light chain-2 (MLC2) phosphorylation], loss of cell polarity, loss of cell–cell junctions, luminal infiltration and basal invasion induced by AGE-modified basal lamina matrix in PEC acini. Our in vitro results were concordant with luminal occlusion of acini in the prostate glands of adult Endo180ΔEx2–6/ΔEx2–6 mice, with constitutively exposed CTLD2 and decreased survival of men with early (non-invasive) prostate cancer with high epithelial Endo180 expression and levels of AGE. These findings indicate that AGE-dependent modification of the basal lamina induces invasive behaviour in non-transformed PECs via a molecular mechanism linked to cancer progression. This study provides a rationale for targeting CTLD2 in Endo180 in prostate cancer and other pathologies in which increased basal lamina thickness and tissue stiffness are driving factors

Using reference-free compressed data structures to analyze sequencing reads from thousands of human genomes.

We are rapidly approaching the point where we have sequenced millions of human genomes. There is a pressing need for new data structures to store raw sequencing data and efficient algorithms for population scale analysis. Current reference-based data formats do not fully exploit the redundancy in population sequencing nor take advantage of shared genetic variation. In recent years, the Burrows-Wheeler transform (BWT) and FM-index have been widely employed as a full-text searchable index for read alignment and de novo assembly. We introduce the concept of a population BWT and use it to store and index the sequencing reads of 2705 samples from the 1000 Genomes Project. A key feature is that, as more genomes are added, identical read sequences are increasingly observed, and compression becomes more efficient. We assess the support in the 1000 Genomes read data for every base position of two human reference assembly versions, identifying that 3.2 Mbp with population support was lost in the transition from GRCh37 with 13.7 Mbp added to GRCh38. We show that the vast majority of variant alleles can be uniquely described by overlapping 31-mers and show how rapid and accurate SNP and indel genotyping can be carried out across the genomes in the population BWT. We use the population BWT to carry out nonreference queries to search for the presence of all known viral genomes and discover human T-lymphotropic virus 1 integrations in six samples in a recognized epidemiological distribution

Transparency of Regulatory Data across the European Medicines Agency, Health Canada, and US Food and Drug Administration

Based on an analysis of relevant laws and policies, regulator data portals, and information requests, we find that clinical data, including clinical study reports, submitted to the European Medicines Agency and Health Canada to support approval of medicines are routinely made publicly available

Brain age predicts disability accumulation in multiple sclerosis

OBJECTIVE: Neurodegenerative conditions often manifest radiologically with the appearance of premature aging. Multiple sclerosis (MS) biomarkers related to lesion burden are well developed, but measures of neurodegeneration are less well-developed. The appearance of premature aging quantified by machine learning applied to structural MRI assesses neurodegenerative pathology. We assess the explanatory and predictive power of brain age analysis on disability in MS using a large, real-world dataset. METHODS: Brain age analysis is predicated on the over-estimation of predicted brain age in patients with more advanced pathology. We compared the performance of three brain age algorithms in a large, longitudinal dataset (\u3e13,000 imaging sessions from \u3e6,000 individual MS patients). Effects of MS, MS disease course, disability, lesion burden, and DMT efficacy were assessed using linear mixed effects models. RESULTS: MS was associated with advanced predicted brain age cross-sectionally and accelerated brain aging longitudinally in all techniques. While MS disease course (relapsing vs. progressive) did contribute to advanced brain age, disability was the primary correlate of advanced brain age. We found that advanced brain age at study enrollment predicted more disability accumulation longitudinally. Lastly, a more youthful appearing brain (predicted brain age less than actual age) was associated with decreased disability. INTERPRETATION: Brain age is a technically tractable and clinically relevant biomarker of disease pathology that correlates with and predicts increasing disability in MS. Advanced brain age predicts future disability accumulation

Physiological Differences Between Low Versus High Skeletal Muscle Hypertrophic Responders to Resistance Exercise Training: Current Perspectives and Future Research Directions

Numerous reports suggest there are low and high skeletal muscle hypertrophic responders following weeks to months of structured resistance exercise training (referred to as low and high responders herein). Specifically, divergent alterations in muscle fiber cross sectional area (fCSA), vastus lateralis thickness, and whole body lean tissue mass have been shown to occur in high versus low responders. Differential responses in ribosome biogenesis and subsequent protein synthetic rates during training seemingly explain some of this individual variation in humans, and mechanistic in vitro and rodent studies provide further evidence that ribosome biogenesis is critical for muscle hypertrophy. High responders may experience a greater increase in satellite cell proliferation during training versus low responders. This phenomenon could serve to maintain an adequate myonuclear domain size or assist in extracellular remodeling to support myofiber growth. High responders may also express a muscle microRNA profile during training that enhances insulin-like growth factor-1 (IGF-1) mRNA expression, although more studies are needed to better validate this mechanism. Higher intramuscular androgen receptor protein content has been reported in high versus low responders following training, and this mechanism may enhance the hypertrophic effects of testosterone during training. While high responders likely possess “good genetics,” such evidence has been confined to single gene candidates which typically share marginal variance with hypertrophic outcomes following training (e.g., different myostatin and IGF-1 alleles). Limited evidence also suggests pre-training muscle fiber type composition and self-reported dietary habits (e.g., calorie and protein intake) do not differ between high versus low responders. Only a handful of studies have examined muscle biomarkers that are differentially expressed between low versus high responders. Thus, other molecular and physiological variables which could potentially affect the skeletal muscle hypertrophic response to resistance exercise training are also discussed including rDNA copy number, extracellular matrix and connective tissue properties, the inflammatory response to training, and mitochondrial as well as vascular characteristics

ArborZ: Photometric Redshifts Using Boosted Decision Trees

Precision photometric redshifts will be essential for extracting cosmological parameters from the next generation of wide-area imaging surveys. In this paper we introduce a photometric redshift algorithm, ArborZ, based on the machine-learning technique of Boosted Decision Trees. We study the algorithm using galaxies from the Sloan Digital Sky Survey and from mock catalogs intended to simulate both the SDSS and the upcoming Dark Energy Survey. We show that it improves upon the performance of existing algorithms. Moreover, the method naturally leads to the reconstruction of a full probability density function (PDF) for the photometric redshift of each galaxy, not merely a single "best estimate" and error, and also provides a photo-z quality figure-of-merit for each galaxy that can be used to reject outliers. We show that the stacked PDFs yield a more accurate reconstruction of the redshift distribution N(z). We discuss limitations of the current algorithm and ideas for future work.Comment: 10 pages, 13 figures, submitted to Ap

Arthroscopic rotator cuff repair with a fibrin scaffold containing growth factors and autologous progenitor cells derived from humeral cBMA improves clinical outcomes in high risk patients

PURPOSE: To report the clinical outcomes after biologically augmented rotator cuff repair (RCR) with a fibrin scaffold derived from autologous whole blood and supplemented with concentrated bone marrow aspirate (cBMA) harvested at the proximal humerus. METHODS: Patients who underwent arthroscopic RCR with biologic augmentation using a fibrin clot scaffold (“Mega- Clot”) containing progenitor cells and growth factors from proximal humerus BMA and autologous whole blood between April 2015 and January 2018 were prospectively followed. Only high-risk patients in primary and revision cases that possessed relevant comorbidities or physically demanding occupation were included. Minimum follow-up for inclusion was 1 year. The visual analog score for pain (VAS), American Shoulder and Elbow Surgeons (ASES), Simple Shoulder Test (SST), Single Assessment Numerical Evaluation (SANE), and Constant-Murley scores were collected preoperatively and at final follow-up. In vitro analyses of the cBMA and fibrin clot using nucleated cell count, colony forming units, and live/dead assays were used to quantify the substrates. RESULTS: Thirteen patients (56.9 ± 7.7 years) were included. The mean follow-up was 26.9 ± 17.7 months (n = 13). There were significant improvements in all outcome scores from the preoperative to the postoperative state: VAS (5.6 ± 2.5 to 3.1 ± 3.2; P < .001), ASES (42.0 ± 17.1 to 65.5 ± 30.6; P < .001), SST (3.2 ± 2.8 to 6.5 ± 4.7; P = .002), SANE (11.5 ± 15.6 to 50.3 ± 36.5; P < .001), and Constant-Murley (38.9 ± 17.5 to 58.1 ± 26.3; P < .001). Six patients (46%) had retears on postoperative MRI, despite all having improvements in pain and function except one. All failures were chronic rotator cuff tears, and all were revision cases except one (1.6 ± 0.5 previous RCRs). The representative sample of harvested cBMA showed an average of 28.5 ± 9.1 × 10(6) nucleated cells per mL. CONCLUSIONS: Arthroscopic rotator cuff repairs that are biologically augmented with a fibrin scaffold containing growth factors and autologous progenitor cells derived from autologous whole blood and humeral cBMA can improve clinical outcomes in primary, as well as revision cases in high-risk patients. However, the incidence of retears remains a concern in this population, demanding further improvements in biologic augmentation. LEVEL OF EVIDENCE: IV, therapeutic case series

Cosmological Constraints from Galaxy Clustering and the Mass-to-Number Ratio of Galaxy Clusters

We place constraints on the average density (Omega_m) and clustering amplitude (sigma_8) of matter using a combination of two measurements from the Sloan Digital Sky Survey: the galaxy two-point correlation function, w_p, and the mass-to-galaxy-number ratio within galaxy clusters, M/N, analogous to cluster M/L ratios. Our w_p measurements are obtained from DR7 while the sample of clusters is the maxBCG sample, with cluster masses derived from weak gravitational lensing. We construct non-linear galaxy bias models using the Halo Occupation Distribution (HOD) to fit both w_p and M/N for different cosmological parameters. HOD models that match the same two-point clustering predict different numbers of galaxies in massive halos when Omega_m or sigma_8 is varied, thereby breaking the degeneracy between cosmology and bias. We demonstrate that this technique yields constraints that are consistent and competitive with current results from cluster abundance studies, even though this technique does not use abundance information. Using w_p and M/N alone, we find Omega_m^0.5*sigma_8=0.465+/-0.026, with individual constraints of Omega_m=0.29+/-0.03 and sigma_8=0.85+/-0.06. Combined with current CMB data, these constraints are Omega_m=0.290+/-0.016 and sigma_8=0.826+/-0.020. All errors are 1-sigma. The systematic uncertainties that the M/N technique are most sensitive to are the amplitude of the bias function of dark matter halos and the possibility of redshift evolution between the SDSS Main sample and the maxBCG sample. Our derived constraints are insensitive to the current level of uncertainties in the halo mass function and in the mass-richness relation of clusters and its scatter, making the M/N technique complementary to cluster abundances as a method for constraining cosmology with future galaxy surveys.Comment: 23 pages, submitted to Ap