The effect of tissue-engineered cartilage biomechanical and biochemical properties on its post-implantation mechanical behavior

The insufficient load-bearing capacity of today’s tissue-engineered (TE) cartilage limits its clinical application. Focus has been on engineering cartilage with enhanced mechanical stiffness by reproducing native biochemical compositions. More recently, depth dependency of the biochemical content and the collagen network architecture has gained interest. However, it is unknown whether the mechanical performance of TE cartilage would benefit more from higher content of biochemical compositions or from achieving an appropriate collagen organization. Furthermore, the relative synthesis rate of collagen and proteoglycans during the TE process may affect implant performance. Such insights would assist tissue engineers to focus on those aspects that are most important. The aim of the present study is therefore to elucidate the relative importance of implant ground substance stiffness, collagen content, and collagen architecture of the implant, as well as the synthesis rate of the biochemical constituents for the post-implantation mechanical behavior of the implant. We approach this by computing the post-implantation mechanical conditions using a composition-based fibril-reinforced poro-viscoelastic swelling model of the medial tibia plateau. Results show that adverse implant composition and ultrastructure may lead to post-implantation excessive mechanical loads, with collagen orientation being the most critical variable. In addition, we predict that a faster synthesis rate of proteoglycans compared to that of collagen during TE culture may result in excessive loads on collagen fibers post-implantation. This indicates that even with similar final contents, constructs may behave differently depending on their development. Considering these aspects may help to engineer TE cartilage implants with improved survival rates.     

A Hybrid Likelihood Model for Sequence-Based Disease Association Studies

In the past few years, case-control studies of common diseases have shifted their focus from single genes to whole exomes. New sequencing technologies now routinely detect hundreds of thousands of sequence variants in a single study, many of which are rare or even novel. The limitation of classical single-marker association analysis for rare variants has been a challenge in such studies. A new generation of statistical methods for case-control association studies has been developed to meet this challenge. A common approach to association analysis of rare variants is the burden-style collapsing methods to combine rare variant data within individuals across or within genes. Here, we propose a new hybrid likelihood model that combines a burden test with a test of the position distribution of variants. In extensive simulations and on empirical data from the Dallas Heart Study, the new model demonstrates consistently good power, in particular when applied to a gene set (e.g., multiple candidate genes with shared biological function or pathway), when rare variants cluster in key functional regions of a gene, and when protective variants are present. When applied to data from an ongoing sequencing study of bipolar disorder (191 cases, 107 controls), the model identifies seven gene sets with nominal p-values0.05, of which one MAPK signaling pathway (KEGG) reaches trend-level significance after correcting for multiple testing.     

Evolutionarily conserved motifs and modules in mitochondrial protein–protein interaction networks

Advances in organelle interactomics have led to new insights into organelle functions. In this study, we considered the common mitochondrial PIN of four evolutionarily distant eukaryotic species, namely Homo sapiens, Mus musculus, Drosophila melanogaster and Caenorhabditis elegans. By comparative interactomics analysis of mitochondrial PINs in these organisms, five conserved modules were identified. Modules comprise the main mitochondrial tasks, including proteins involved in translation process, mitochondrial import inner membrane proteins, TCA cycle enzymes, mitochondrial electron transport chain, and metabolic enzymes. Furthermore, we reemphasize that subgraphs of network, i.e., motifs and themes, may represent evolutionarily conserved topological units which are biologically significant.     

Retinoic acid and/or progesterone differentiate mouse induced pluripotent stem cells into male germ cells in vitro

Numerous reagents were employed for differentiating induced pluripotent stem cells (iPSCs) into male germ cells; however, the induction procedure was ineffective. The aim of this study was to improve the in vitro differentiation of mice iPSCs (miPSCs) into male germ cells with retinoic acid (RA) and progesterone (P). miPSCs were differentiated to embryoid bodies (EBs) in suspension with RA with or without progesterone for 0, 4, and 7 days. Then, the expression of certain genes at different stages of male germ cell development including Ddx4 (pre meiosis), Stra8 (meiosis), AKAP3 (post meiosis), and Mvh protein was examined in RNA and/or protein levels by real-time polymerase chain reaction or flow cytometry, respectively. The Stra8 gene expression increased in the RA groups on all days. But, expression of this gene declined in RA + P groups. In addition, an increased expression of Ddx4 gene was observed on day 0 in the P group. Also, a significant upregulation was observed in the expression of AKAP3 gene in the RA + P group on days 0 and 4. However, gene expression decreased in P and RA groups on day 7. The expression of Mvh protein significantly increased in the RA group on day 7. The Mvh expression was also enhanced in the P group on day 4, but it decreased on day 7, while this protein upregulated on day 0 and 7 in the RA + P group. The miPSCs have the capacity for in vitro differentiation into male germ cells by RA and/or progesterone. However, the effects of these inducers depend on the type of combination and an effective time.     

Bovine serum albumin/gold nanoparticles as a drug delivery system for Curcumin: experimental and computational studies

Abstract

Communicated by Ramaswamy H. Sarma     

Simultaneous impact of atorvastatin and mesenchymal stem cells for glioblastoma multiform suppression in rat glioblastoma multiform model

Glioblastoma multiform (GBM) is known as an aggressive glial neoplasm. Recently incorporation of mesenchymal stem cells with anti-tumor drugs have been used due to lack of immunological responses and their easy accessibility. In this study, we have investigated the anti-proliferative and apoptotic activity of atorvastatin (Ator) in combination of mesenchymal stem cells (MSCs) on GBM cells in vitro and in vivo. The MSCs isolated from rats and characterized for their multi-potency features. The anti-proliferative and migration inhibition of Ator and MSCs were evaluated by MTT and scratch migration assays. The annexin/PI percentage and cell cycle arrest of treated C6 cells were evaluated until 72 h incubation. The animal model was established via injection of C6 cells in the brain of rats and subsequent injection of Ator each 3 days and single injection of MSCs until 12 days. The growth rate, migrational phenotype and cell cycle progression of C6 cells decreased and inhibited by the interplay of different factors in the presence of Ator and MSCs. The effect of Ator and MSCs on animal models displayed a significant reduction in tumor size and weight. Furthermore, histopathology evaluation proved low hypercellularity and mitosis index as well as mild invasive tumor cells for perivascular cuffing without pseudopalisading necrosis and small delicate vessels in Ator?+?MSCs condition. In summary, Ator and MSCs delivery to GBM model provides an effective strategy for targeted therapy of brain tumor.

     

Rational MD simulations for improvement the affinity of nanobody against PlGF (placenta growth factor): mutagenesis based on electrostatic interactions

Abbreviations COM center of mass distance

MD molecular dynamics

MM-PBSA Molecular Mechanics Poisson–Boltzmann Surface Area

Nb nanobody

PlGF placenta growth factor

Rg radius of gyration

RMSD root mean-square deviation

SASA solvent-accessible surface area

VEGF vascular endothelial growth factor

     

Dissolved oxygen concentration regulates human hepatic organoid formation from pluripotent stem cells in a fully controlled bioreactor

Developing technologies for scalable production of human organoids has gained increased attention for “organoid medicine” and drug discovery. We developed a scalable and integrated differentiation process for generation of hepatic organoid from human pluripotent stem cells (hPSCs) in a fully controlled stirred tank bioreactor with 150 ml working volume by application of physiological oxygen concentrations in different liver tissue zones. We found that the 20–40% dissolved oxygen concentration [DO] (corresponded to 30–60 mmHg pO₂ within the liver tissue) significantly influences the process outcome via regulating the differentiation fate of hPSC aggregates by enhancing mesoderm induction. Regulation of the [DO] at 30% DO resulted in efficient generation of human fetal-like hepatic organoids that had a uniform size distribution and were comprised of red blood cells and functional hepatocytes, which exhibited improved liver-specific marker gene expressions, key liver metabolic functions, and, more important, higher inducible cytochrome P450 activity compared to the other trials. These hepatic organoids were successfully engrafted in an acute liver injury mouse model and produced albumin after implantation. These results demonstrated the significant impact of the dissolved oxygen concentration on hPSC hepatic differentiation fate and differentiation efficacy that should be considered ascritical translational aspect of established scalable liver organoid generation protocols for potential clinical and drug discovery applications.