MiR-20a regulates the PRKG1 gene by targeting its coding region in pulmonary arterial smooth muscle cells

AbstractChronic hypoxia triggers pulmonary vascular remodeling, which is associated with de-differentiation of pulmonary artery smooth muscle cells (PASMC). Here, we show that miR-20a expression is up-regulated in response to hypoxia in both mouse and human PASMC. We also observed that miR-20a represses the protein kinase, cGMP-dependent, type I (PRKG1) gene and we identified two crucial miR-20a binding sites within the coding region of PRKG1. Functional studies showed that miR-20a promotes the proliferation and migration of human PASMC, whereas it inhibits their differentiation. In summary, we provided a possible mechanism by which hypoxia results in decreased PRKG1 expression and in the phenotypic switching of PASMC

Trajectory Optimization of Lower Extremity Rehabilitation Robots Based on Cycloid

With the rapid development of modern robotics and medical industry, the use of rehabilitation robots for the treatment of patients with lower limb sports injuries has become one of the research hotspots at home and abroad. In order to achieve better rehabilitation treatment effect, trajectory planning of a three-degree-of-freedom lower limb rehabilitation robot is studied, and the motion law of healthy ankle joint is simulated to optimize the trajectory design of the lower limb rehabilitation robot. Based on the rehabilitation, injury mechanism, and motion form of the ankle joint, a comparative analysis of several low degree of freedom planar symmetric parallel mechanisms is conducted, and a design prototype using a 2UU-UPU mechanism as the rehabilitation actuator is determined; research on trajectory planning for lower limb rehabilitation training of lower limb rehabilitation robots, trajectory planning motion formulas for cycloidal motion laws and superimposed cycloidal motion laws are derived, and the rationality of trajectory under different rehabilitation training conditions is verified. In order to further explore a more reasonable rehabilitation trajectory, the optical motion capture system is used to collect the ankle joint movement trajectory in the sitting position, establish the rehabilitation trajectory constraints, improve the similarity between the planned trajectory and the human movement, and achieve better rehabilitation effect

Applying data mining techniques to address critical process optimization needs in advanced manufacturing

Advanced manufacturing such as aerospace, semi-conductor, and flat display device often involves complex production processes, and generates large volume of production data. In general, the production data comes from products with different levels of quality, assembly line with complex flows and equipments, and processing craft with massive control-ling parameters. The scale and complexity of data is be-yond the analytic power of traditional IT infrastructures. To achieve better manufacturing performance, it is imperative to explore the underlying dependencies of the production data and exploit analytic insights to improve the production process. However, few research and industrial efforts have been reported on providing manufacturers with integrated data analytical solutions to reveal potentials and optimiz

An Advanced Model to Precisely Estimate the Cell-Free Fetal DNA Concentration in Maternal Plasma

<div><p>Background</p><p>With the speedy development of sequencing technologies, noninvasive prenatal testing (NIPT) has been widely applied in clinical practice for testing for fetal aneuploidy. The cell-free fetal DNA (cffDNA) concentration in maternal plasma is the most critical parameter for this technology because it affects the accuracy of NIPT-based sequencing for fetal trisomies 21, 18 and 13. Several approaches have been developed to calculate the cffDNA fraction of the total cell-free DNA in the maternal plasma. However, most approaches depend on specific single nucleotide polymorphism (SNP) allele information or are restricted to male fetuses.</p><p>Methods</p><p>In this study, we present an innovative method to accurately deduce the concentration of the cffDNA fraction using only maternal plasma DNA. SNPs were classified into four maternal-fetal genotype combinations and three boundaries were added to capture effective SNP loci in which the mother was homozygous and the fetus was heterozygous. The median value of the concentration of the fetal DNA fraction was estimated using the effective SNPs. A depth-bias correction was performed using simulated data and corresponding regression equations for adjustments when the depth of the sequencing data was below 100-fold or the cffDNA fraction is less than 10%.</p><p>Results</p><p>Using our approach, the median of the relative bias was 0.4% in 18 maternal plasma samples with a median sequencing depth of 125-fold. There was a significant association (r = 0.935) between our estimations and the estimations inferred from the Y chromosome. Furthermore, this approach could precisely estimate a cffDNA fraction as low as 3%, using only maternal plasma DNA at the targeted region with a sequencing depth of 65-fold. We also used PCR instead of parallel sequencing to calculate the cffDNA fraction. There was a significant association (r = 98.2%) between our estimations and those inferred from the Y chromosome.</p></div

The estimated fractional fetal DNA concentration using capture sequencing data and MT-PCR data.

<p>(a) The x-axis represents the estimated fractional fetal DNA concentration, using polymorphic alleles by capture sequencing. The y-axis represents the estimated fractional fetal DNA concentration, using SNPs from the Y-chromosome with capture sequencing. (b) The x-axis represents the estimated fractional fetal DNA concentration using polymorphic alleles by MT-PCR. The y-axis represents the estimated fractional fetal DNA concentration using URchrY or URchr18 counts by MT-PCR.</p

The workflow to estimate the fractional fetal DNA concentration.

<p>The first step is to extract free DNA from plasma samples from pregnant women. Then, the regions of interest in the extracted DNA fragments are enriched using a crossing system. The next step is to prepare the DNA sequencing library and sequence the samples. After sequencing, these reads are matched to a reference genome (Hg19) using SOAP2. The pileup files of the matching are generated by SAMTOOLS for the covered regions. Each point of the targeted zones is calculated following Formula 1, and the median value is considered the cell-free fetal DNA concentration. If the depth is more than 100-fold and the cff-DNA is larger than 10%, we can obtain the cff-DNA concentration directly. Otherwise, we can fit the result using an equation.</p

The estimated fractional fetal DNA concentration before and after the fitting correction.

<p>The x-axis and y-axis represent the estimated value and standard value of the cell-free fetal DNA concentration in the plasma, respectively. (a) Most estimated values are close to the standard values. However, the estimated value was higher than the standard value when the standard value was less than 8%. (b) The bias was corrected through the equation (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0161928#pone.0161928.s003" target="_blank">S1 Table</a>) generated by the corrected model. Finally, the deviation was reduced to a satisfactory level when most of the estimated values and standards were in the diagonal line.</p