The System Research of the Molecular Mechanism of Quyushengxin Capsule in the Treatment of Osteonecrosis of the Femoral Head

Osteonecrosis of the femoral head (ONFH) is a chronic and irreversible disease that has a risk of eventually developing into a joint collapse and resulting in joint dysfunction. Quyushengxin capsule (QYSXC) is an effective and safe traditional Chinese medicine used in the treatment of ONFH. In this present study, an integrated approach was used to investigate the mechanism of QYSXC in the treatment of ONFH, which contained systems pharmacology, molecular docking, and chip experiment. In the systems pharmacology, target fishing, protein-protein interaction (PPI), Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis, and herbs-compounds-targets-pathways (H-C-T-P) network construction were performed to study the mechanism of QYSXC in the treatment of ONFH. The results showed that 15 key compounds, 8 key targets, and 8 key signaling pathways were found for QYSXC in the treatment with ONFH. Then, molecular docking was performed to further explore the interaction between some key compounds and key targets. After that, the chip experiment was performed to verify some target factors, including ICAM-1, IL-6, IL-1α, IL-1β, IL-2, IL-4, IL-10, and TNF-α. The results of this work may provide a theoretical basis for further research on the molecular mechanism of QYSXC in the treatment of ONFH.

target: an R package to predict combined function of transcription factors

Researchers use ChIP binding data to identify potential transcription factor binding sites. Similarly, they use gene expression data from sequencing or microarrays to quantify the effect of the transcription factor overexpression or knockdown on its targets. Therefore, the integration of the binding and expression data can be used to improve the understanding of a transcription factor function. Here, we implemented the binding and expression target analysis (BETA) in an R/Bioconductor package. This algorithm ranks the targets based on the distances of their assigned peaks from the transcription factor ChIP experiment and the signed statistics from gene expression profiling with transcription factor perturbation. We further extend BETA to integrate two sets of data from two transcription factors to predict their targets and their combined functions. In this article, we briefly describe the workings of the algorithm and provide a workflow with a real dataset for using it. The gene targets and the aggregate functions of transcription factors YY1 and YY2 in HeLa cells were identified. Using the same datasets, we identified the shared targets of the two transcription factors, which were found to be, on average, more cooperatively regulated.

An optimized ChIP-Seq framework for profiling of histone modifications in Chromochloris zofingiensis

The eukaryotic green alga Chromochloris zofingiensis is a reference organism for studying carbon partitioning and a promising candidate for the production of biofuel precursors. Recent transcriptome profiling transformed our understanding of its biology and generally algal biology, but epigenetic regulation remains understudied and represents a fundamental gap in our understanding of algal gene expression. Chromatin Immunoprecipitation followed by deep sequencing (ChIP-Seq) is a powerful tool for the discovery of such mechanisms, by identifying genome-wide histone modification patterns and transcription factor-binding sites alike. Here, we established a ChIP-Seq framework for Chr. zofingiensis yielding over 20 million high quality reads per sample. The most critical steps in a ChIP experiment were optimized, including DNA shearing to obtain an average DNA fragment size of 250 bp and assessment of the recommended formaldehyde concentration for optimal DNA-protein crosslinking. We used this ChIP-Seq framework to generate a genome-wide map of the H3K4me3 distribution pattern and to integrate these data with matching RNA-Seq data. In line with observations from other organisms, H3K4me3 marks predominantly transcription start sites of genes. Our H3K4me3 ChIP-Seq data will pave the way for improved genome structural annotation in the emerging reference alga Chr. zofingiensis.

target: an R package to predict combined function of transcription factors

Researchers use ChIP binding data to identify potential transcription factor binding sites. Similarly, they use gene expression data from sequencing or microarrays to quantify the effect of the factor overexpression or knockdown on its targets. Therefore, the integration of the binding and expression data can be used to improve the understanding of a transcription factor function. Here, we implemented the binding and expression target analysis (BETA) in an R/Bioconductor package. This algorithm ranks the targets based on the distances of their assigned peaks from the factor ChIP experiment and the signed statistics from gene expression profiling with factor perturbation. We further extend BETA to integrate two sets of data from two factors to predict their targets and their combined functions. In this article, we briefly describe the workings of the algorithm and provide a workflow with a real dataset for using it. The gene targets and the aggregate functions of transcription factors YY1 and YY2 in HeLa cells were identified. Using the same datasets, we identified the shared targets of the two factors, which were found to be, on average, more cooperatively regulated.

Estimation Algorithm for a Hybrid PDE–ODE Model Inspired by Immunocompetent Cancer-on-Chip Experiment

The present work is motivated by the development of a mathematical model mimicking the mechanisms observed in lab-on-chip experiments, made to reproduce on microfluidic chips the in vivo reality. Here we consider the Cancer-on-Chip experiment where tumor cells are treated with chemotherapy drug and secrete chemical signals in the environment attracting multiple immune cell species. The in silico model here proposed goes towards the construction of a “digital twin” of the experimental immune cells in the chip environment to better understand the complex mechanisms of immunosurveillance. To this aim, we develop a tumor-immune microfluidic hybrid PDE–ODE model to describe the concentration of chemicals in the Cancer-on-Chip environment and immune cells migration. The development of a trustable simulation algorithm, able to reproduce the immunocompetent dynamics observed in the chip, requires an efficient tool for the calibration of the model parameters. In this respect, the present paper represents a first methodological work to test the feasibility and the soundness of the calibration technique here proposed, based on a multidimensional spline interpolation technique for the time-varying velocity field surfaces obtained from cell trajectories.

A Fast and Implantation-Free Sample Production Method for Large Scale Electron-Transparent Metallic Samples Destined for MEMS-Based In Situ S/TEM Experiments

Microelectromechanical systems (MEMS) are currently supporting ground-breaking basic research in materials science and metallurgy as they allow in situ experiments on materials at the nanoscale within electron microscopes in a wide variety of different conditions such as extreme materials dynamics under ultrafast heating and quenching rates as well as in complex electro-chemical environments. Electron-transparent sample preparation for MEMS e-chips remains a challenge for this technology as the existing methodologies can introduce contaminants, thus disrupting the experiments and the analysis of results. Herein we introduce a methodology for simple and fast electron-transparent sample preparation for MEMS e-chips without significant contamination. The quality of the samples as well as their performance during a MEMS e-chip experiment in situ within an electron microscope are evaluated during a heat treatment of a crossover AlMgZn(Cu) alloy.

MiR-204-5p/FOXC1/GDF7 Axis Regulates Osteogenic Differentiation of Human Adipose-Derived Stem Cells Via the AKT and p38 Signaling Pathways

Background: Human adipose-derived stem cells (hADSCs) are stem cells with the potential to differentiate in multiple directions. MiR-204-5p is poorly expressed during osteogenic differentiation of hADSCs, and its specific regulatory mechanism remains unclear. Here, we aimed to explore the function and possible molecular mechanism of miR-204-5p involved in the osteogenic differentiation of hADSCs. Methods: The expression pattern of miR-204-5p, Runx2, Alkaline phosphatase (ALP), Osteocalcin (OCN), and Forkhead box C1(FOXC1) and growth differentiation factor 7(GDF7) in hADSCs during osteogenesis were detected by qRT-PCR. Then, ALP and alizarin red staining (ARS) were used to detect the activity of osteoblasts and mineral deposition. Western blot was conducted to confirm the protein levels. The regulation relationship among miR-204-5p, FOXC1 and GDF7 was verified by double luciferase activity and CHIP experiment.Results: First, miR-204-5p expression was down-regulated and overexpressed miR-204-5p suppressed the osteogenic differentiation. Furthermore, the levels of FOXC1 and GDF7 were decreased in the miR-204-5p mimics group, which indicate that overexpressed miR-204-5p would suppress the expression of FOXC1 and GDF7 through binding the 3’UTR region each. Overexpression of FOXC1 or GDF7 could improve the inhibition of osteogenic differentiation of hADSCs induced by the miR-204-5p mimics. Moreover, FOXC1 could bind to the promoter of miR-204-5p and GDF7, promote the deacetylation of miR-204-5p and reduced the expression of miR-204-5p, thus promoting the expression of GDF7 during osteogenic differentiation. GDF7 could induce hADSCs osteogenesis differentiation by activating the AKT and P38 signaling pathways. Conclusions: Our results demonstrated that miR-204-5p/FOXC1/GDF7 axis regulates osteogenic differentiation of hADSCs via the AKT and p38 signaling pathways. This study further understood the regulatory mechanism of hADSCs differentiation balance from the perspective of miRNAs regulation.

Finite Element Modeling and Critical Plane Analysis of a Cut-and-Chip Experiment for Rubber

ABSTRACT Rubber surfaces exposed to concentrated, sliding impacts carry large normal and shearing stresses that can cause damage and the eventual removal of material from the surface. Understanding this cut-and-chip (CC) effect in rubber is key to developing improved tread compounds for tires used in off-road or poor road conditions. To better understand the mechanics involved in the CC process, an analysis was performed of an experiment conducted on a recently introduced device, the Coesfeld Instrumented Chip and Cut Analyser (ICCA), which repetitively impacts a rigid indenter against a rotating solid rubber wheel. The impact process is carefully controlled and measured on this lab instrument, so that the contact time, normal force, and shear force are all known. The numerical evaluation includes Abaqus finite element analysis (FEA) to determine the stress and strain fields during impact. The FEA results are combined with rubber fracture mechanics characteristics of the material as inputs to the Endurica CL elastomer fatigue solver, which employs critical plane analysis to determine the fatigue response of the specimen surface. The modeling inputs are experimentally determined hyperelastic stress-strain parameters, crack growth rate laws, and crack precursor sizes for carbon black–filled compounds wherein the type of elastomer is varied in order to compare natural rubber (NR), butadiene rubber (BR), and styrene-butadiene rubber (SBR). At the lower impact force, the simulation results were consistent with the relative CC resistances of NR, BR, and SBR measured using the ICCA, which followed the order BR > NR > SBR. Impact-induced temperature increases need to be considered in the fatigue analysis of the higher impact force to provide lifetime predictions that match the experimental CC resistance ranking of NR > SBR > BR.