Circulating exosomal lncRNA contributes to the pathogenesis of spinal cord injury in rats

Exosome-derived long non-coding RNAs(lncRNAs)are extensively engaged in recovery and repair of the injured spinal cord,through different mechanisms.However,to date no study has systematically evaluated the differentially expressed lncRNAs involved in the development of spinal cord injury.Thus,the aim of this study was to identify key circulating exosome-derived lncRNAs in a rat model of spinal cord injury and investigate their potential actions.To this end,we established a rat model of spinal cord hemisection.Circulating exosomes were extracted from blood samples from spinal cord injury and control(sham)rats and further identified through Western blotting and electron microscopy.RNA was isolated from the exosomes and sequenced.The enrichment analysis demonstrated that there were distinctively different lncRNA and mRNA expression patterns between the two groups.Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analysis and Gene Ontology(GO)functional analysis were performed to determine the possible involvements of upregulated and downregulated lncRNAs in various pathways and different biological processes,as well as their cellular locations and molecular functions.Furthermore,quantitative reverse transcription-polymerase chain reaction showed that the expression of five lncRNAs––ENSRN0T00000067908,XR_590093,XR_591455,XR_360081,and XR_346933––was increased,whereas the expression of XR_351404,XR_591426,XR_353833,XR_590076,and XR_590719 was decreased.Of note,these 10 lncRNAs were at the center of the lncRNA-miRNA-mRNA coexpression network,which also included 198 mRNAs and 41 miRNAs.Taken together,our findings show that several circulating exosomal lncRNAs are differentially expressed after spinal cord injury,suggesting that they may be involved in spinal cord injury pathology and pathogenesis.These lncRNAs could potentially serve as targets for the clinical diagnosis and treatment of spinal cord injury.

Fast prediction of the mechanical response for layered pavement under instantaneous large impact based on random forest regression

The layered pavements usually exhibit complicated mechanical properties with the effect of complex material properties under external environment.In some cases,such as launching missiles or rockets,layered pavements are required to bear large impulse load.However,traditional methods cannot non-destructively and quickly detect the internal structural of pavements.Thus,accurate and fast prediction of the mechanical properties of layered pavements is of great importance and necessity.In recent years,machine learning has shown great superiority in solving nonlinear problems.In this work,we present a method of predicting the maximum deflection and damage factor of layered pavements under instantaneous large impact based on random forest regression with the deflection basin parameters obtained from falling weight deflection testing.The regression coefficient R^(2)of testing datasets are above 0.94 in the process of predicting the elastic moduli of structural layers and mechanical responses,which indicates that the prediction results have great consistency with finite element simulation results.This paper provides a novel method for fast and accurate prediction of pavement mechanical responses under instantaneous large impact load using partial structural parameters of pavements,and has application potential in non-destructive evaluation of pavement structure.

New insight into the adsorption of ruthenium,rhodium,and palladium from nitric acid solution by a silica-polymer adsorbent

A porous silica-polymer-based adsorbent,isoBuBTP/Si O2-P,was prepared by a vacuum impregnation method and used for the recovery of ruthenium,rhodium,and palladium from nitric acid solution.The experimental results revealed that iso Bu-BTP/SiO2-P exhibited unique adsorption properties such as high saturation adsorption capacity(Ru:0.35 mmol g^-1,Rh:0.32 mmol g^-1,Pd:1.05 mmol g^-1)and excellent selectivity over other metal ions,such as lanthanides(SF(PGM/M)>40)in 1 M HNO3 solution.The adsorption process conformed to the pseudosecond-order model and Langmuir model.From the UV,FTIR,and XPS analyses,it can be concluded that the strong affinity between functional groups(C–N=C)and metal ions as well as NO3-played a role in coordination during the adsorption process.Furthermore,the desorption behavior was studied,and it was found that the adsorbed Pd,Rh,and Ru could be eluted with a 0.01 M nitric acid–0.1M thiocarbamide solution,5M hydrochloric acid,and sodium hypochlorite(CP)solution,respectively.Finally,based on those findings,a simple process for the separation and recovery of Pd,Rh,and Ru from high-level liquid waste using iso Bu-BTP/SiO2-P was designed and proposed.

Lasing-enhanced surface plasmon resonance spectroscopy and sensing

Surface plasmon resonance(SPR)sensors are a prominent means to detect biological and chemical analytes and to investigate biomolecular interactions in various fields.However,the performance of SPR sensors is ultimately limited by ohmic loss,which substantially weakens the resonance signal and broadens the response linewidth.Recent studies have shown that ohmic loss can be fully compensated in plasmonic nanolasers,which leads to a novel class of lasing-enhanced surface plasmon resonance(LESPR)sensors with improved sensing performance.In this paper,we detail the underlying physical mechanisms of LESPR sensors and present their implementation in various sensing devices.We review recent progress on their applications,particularly for refractive index sensing,gas detection and biological imaging,labeling,tracking,and diagnosis.We then summarize the review and highlight remaining challenges of LESPR sensing technology.