Genetically modified non-human primate models for research on neurodegenerative diseases

Neurodegenerative diseases(NDs)are a group of debilitating neurological disorders that primarily affect elderly populations and include Alzheimer's disease(AD),Parkinson's disease(PD),Huntington's disease(HD),and amyotrophic lateral sclerosis(ALS).Currently,there are no therapies available that can delay,stop,or reverse the pathological progression of NDs in clinical settings.As the population ages,NDs are imposing a huge burden on public health systems and affected families.Animal models are important tools for preclinical investigations to understand disease pathogenesis and test potential treatments.While numerous rodent models of NDs have been developed to enhance our understanding of disease mechanisms,the limited success of translating findings from animal models to clinical practice suggests that there is still a need to bridge this translation gap.Old World nonhuman primates(NHPs),such as rhesus,cynomolgus,and vervet monkeys,are phylogenetically,physiologically,biochemically,and behaviorally most relevant to humans.This is particularly evident in the similarity of the structure and function of their central nervous systems,rendering such species uniquely valuable for neuroscience research.Recently,the development of several genetically modified NHP models of NDs has successfully recapitulated key pathologies and revealed novel mechanisms.This review focuses on the efficacy of NHPs in modeling NDs and the novel pathological insights gained,as well as the challenges associated with the generation of such models and the complexities involved in their subsequent analysis.

Predictive model using four ferroptosis-related genes accurately predicts gastric cancer prognosis

BACKGROUND Gastric cancer(GC)is a common malignancy of the digestive system.According to global 2018 cancer data,GC has the fifth-highest incidence and the thirdhighest fatality rate among malignant tumors.More than 60%of GC are linked to infection with Helicobacter pylori(H.pylori),a gram-negative,active,microaerophilic,and helical bacterium.This parasite induces GC by producing toxic factors,such as cytotoxin-related gene A,vacuolar cytotoxin A,and outer membrane proteins.Ferroptosis,or iron-dependent programmed cell death,has been linked to GC,although there has been little research on the link between H.pylori infection-related GC and ferroptosis.AIM To identify coregulated differentially expressed genes among ferroptosis-related genes(FRGs)in GC patients and develop a ferroptosis-related prognostic model with discrimination ability.METHODS Gene expression profiles of GC patients and those with H.pylori-associated GC were obtained from The Cancer Genome Atlas and Gene Expression Omnibus(GEO)databases.The FRGs were acquired from the FerrDb database.A ferroptosis-related gene prognostic index(FRGPI)was created using least absolute shrinkage and selection operator–Cox regression.The predictive ability of the FRGPI was validated in the GEO cohort.Finally,we verified the expression of the hub genes and the activity of the ferroptosis inducer FIN56 in GC cell lines and tissues.RESULTS Four hub genes were identified(NOX4,MTCH1,GABARAPL2,and SLC2A3)and shown to accurately predict GC and H.pylori-associated GC.The FRGPI based on the hub genes could independently predict GC patient survival;GC patients in the high-risk group had considerably worse overall survival than did those in the low-risk group.The FRGPI was a significant predictor of GC prognosis and was strongly correlated with disease progression.Moreover,the gene expression levels of common immune checkpoint proteins dramatically increased in the highrisk subgroup of the FRGPI cohort.The hub genes were also confirmed to be highly overexpressed in GC cell lines and tissues and were found to be primarily localized at the cell membrane.The ferroptosis inducer FIN56 inhibited GC cell proliferation in a dose-dependent manner.CONCLUSION In this study,we developed a predictive model based on four FRGs that can accurately predict the prognosis of GC patients and the efficacy of immunotherapy in this population.

Verify the Function of a Potential Growth-Regulating Gene in Marine Bivalve Using a Candidate Model Organism Mulinia lateralis

A better understanding of genetic bases of growth regulation is essential for bivalve breeding,which is helpful to improve the yield of the commercially important bivalves.While previous studies have identified some candidate genes accounting for variation in growth-related traits through genotype-phenotype association analyses,seldom of them have verified the functions of these putative,growth-related genes beyond the genomic level due to the difficulty of culturing commercial bivalves under laboratory conditions.Fortunately,dwarf surf clam Mulinia lateralis can serve as a model organism for studying marine bivalves given its short generation time,the feasibility of being grown under experimental conditions and the availability of genetic and biological information.Using dwarf surf clam as a model bivalve,we characterize E2F3,a gene that has been found to account for variation in growth in scallops by a previous genome-wide association study,and verify its function in growth regulation through RNA interference(RNAi)experiments.For the first time,E2F3 in dwarf surf clam,which is termed as MulE2F3,is characterized.The results reveal that dwarf surf clams with MulE2F3 knocked down exhibit a reduction in both shell size and soft-tissue weight,indicating the functions of MulE2F3 in positively regulating bivalve growth.More importantly,we demonstrate how dwarf surf clam can be used as a model organism to investigate gene functions in commercial bivalves,shedding light on genetic causes for variation in growth to enhance the efficiency of bivalve farming.

Towards cultivar-oriented gene discovery for better crops

The continued expansion of the world population,increasingly inconsistent climate and shrinking agricultural resources present major challenges to crop breeding.Fortunately,the increasing ability to discover and manipulate genes creates new opportunities to develop more productive and resilient cultivars.Many genes have been described in papers as being beneficial for yield increase.However,few of them have been translated into increased yield on farms.In contrast,commercial breeders are facing gene decidophobia,i.e.,puzzled about which gene to choose for breeding among the many identified,a huge chasm between gene discovery and cultivar innovation.The purpose of this paper is to draw attention to the shortfalls in current gene discovery research and to emphasise the need to align with cultivar innovation.The methodology dictates that genetic studies not only focus on gene discovery but also pay good attention to the genetic backgrounds,experimental validation in relevant environments,appropriate crop management,and data reusability.The close of the gaps should accelerate the application of molecular study in breeding and contribute to future global food security.

A Vertex Network Model of Arabidopsis Leaf Growth

Biology provides many examples of complex systems whose properties allow organisms to develop in a highly reproducible,or robust,manner.One such system is the growth and development of flat leaves in Arabidopsis thaliana.This mechanistically challenging process results from multiple inputs including gene interactions,cellular geometry,growth rates,and coordinated cell divisions.To better understand how this complex genetic and cellular information controls leaf growth,we developed a mathematical model of flat leaf production.This two-dimensional model describes the gene interactions in a vertex network of cells which grow and divide according to physical forces and genetic information.Interestingly,the model predicts the presence of an unknown additional factor required for the formation of biologically realistic gene expression domains and iterative cell division.This two-dimensional model will form the basis for future studies into robustness of adaxial-abaxial patterning.

Identification of immune cell-related prognostic genes characterized by a distinct microenvironment in hepatocellular carcinoma

BACKGROUND The development and progression of hepatocellular carcinoma(HCC)have been reported to be associated with immune-related genes and the tumor microenvir-onment.Nevertheless,there are not enough prognostic biomarkers and models available for clinical use.Based on seven prognostic genes,this study calculated overall survival in patients with HCC using a prognostic survival model and revealed the immune status of the tumor microenvironment(TME).AIM To develop a novel immune cell-related prognostic model of HCC and depict the basic profile of the immune response in HCC.METHODS We obtained clinical information and gene expression data of HCC from The Cancer Genome Atlas(TCGA)and International Cancer Genome Consortium(ICGC)datasets.TCGA and ICGC datasets were used for screening prognostic genes along with developing and validating a seven-gene prognostic survival model by weighted gene coexpression network analysis and least absolute shrinkage and selection operator regression with Cox regression.The relative analysis of tumor mutation burden(TMB),TME cell infiltration,immune check-points,immune therapy,and functional pathways was also performed based on prognostic genes.RESULTS Seven prognostic genes were identified for signature construction.Survival receiver operating characteristic curve analysis showed the good performance of survival prediction.TMB could be regarded as an independent factor in HCC survival prediction.There was a significant difference in stromal score,immune score,and estimate score between the high-risk and low-risk groups stratified based on the risk score derived from the seven-gene prognostic model.Several immune checkpoints,including VTCN1 and TNFSF9,were found to be associated with the seven prognostic genes and risk score.Different combinations of checkpoint blockade targeting inhibitory CTLA4 and PD1 receptors and potential chemotherapy drugs hold great promise for specific HCC therapies.Potential pathways,such as cell cycle regulation and metabolism of some amino acids,were also identified and analyzed.CONCLUSION The novel seven-gene(CYTH3,ENG,HTRA3,PDZD4,SAMD14,PGF,and PLN)prognostic model showed high predictive efficiency.The TMB analysis based on the seven genes could depict the basic profile of the immune response in HCC,which might be worthy of clinical application.

Rapid Prototype Development Approach for Genetic Programming

Genetic Programming (GP) is an important approach to deal with complex problem analysis and modeling, and has been applied in a wide range of areas. The development of GP involves various aspects, including design of genetic operators, evolutionary controls and implementations of heuristic strategy, evaluations and other mechanisms. When designing genetic operators, it is necessary to consider the possible limitations of encoding methods of individuals. And when selecting evolutionary control strategies, it is also necessary to balance search efficiency and diversity based on representation characteristics as well as the problem itself. More importantly, all of these matters, among others, have to be implemented through tedious coding work. Therefore, GP development is both complex and time-consuming. To overcome some of these difficulties that hinder the enhancement of GP development efficiency, we explore the feasibility of mutual assistance among GP variants, and then propose a rapid GP prototyping development method based on πGrammatical Evolution (πGE). It is demonstrated through regression analysis experiments that not only is this method beneficial for the GP developers to get rid of some tedious implementations, but also enables them to concentrate on the essence of the referred problem, such as individual representation, decoding means and evaluation. Additionally, it provides new insights into the roles of individual delineations in phenotypes and semantic research of individuals.

Genetic Analysis of Stripe Disease Resistance in Rice Restorer Line C224 Using Major Gene plus Polygene Mixed Effect Model

The inheritance of stripe disease resistance in a rice restorer line C224 was analyzed using the mixed effect model of major gene plus polygene for quantitative traits.In addition,the resistance was investigated in seven crosses of C224 with maintainer lines.The results showed that the stripe resistance of C224 was controlled by two major genes with additive-dominance-epistasis effects plus polygenes with additive-dominance effects （E-1 model）.These two genes had additive effects of-12.47% and-24.75%,respectively,showing negative dominance effects.There were significant epistasis and interaction effects between the two major genes.The heritability of the two major genes was 92.12%,while that of polygenes was 2.74%,indicating that the stripe resistance had dominant major gene effect.Of the seven crosses,five displayed high or medium resistance to the stripe disease.

Expression Pattern of Testis-specific Expressed Gene 2 in Cryptorchidism Model and Its Role in Apoptosis of Spermatogenic Cells

In our previous study, we identified a novel testis-specific expressed gene 2 （TSEG-2） from mouse testis. To further investigate its functions, 35 male Balb/c mice （8 weeks old） were divided into cryptorchidism group （n=20）, sham group （n=10）, and control group （n=5）. In cryptorchidism group, the right testes were anchored to the inner lateral abdominal wall. In situ hybridization （ISH） was applied to measure the localization of TSEG-2 in mouse testis. Real-time quantitative PCR was performed to detect the expression of TSEG-2 gene. Meanwhile, under the mediation of polyethylenimine （PEI）, the recombinant vector pEGFP-TSEG-2 （n=5） or empty vector （mock, n=5） was transfected into the testis of male mice. The transfection efficiencies were measured under a fluorescence microscope. The apoptosis of spermatogenic cells was detected by terminal deoxynuleotidyl-mediated nick end labeling （TUNEL）. The results showed that TSEG-2 was expressed in convoluted seminiferous tubules, more precisely, in spermatogonia and spermatocytes. As compared with sham and control groups, the TSEG-2 transcription was significantly enhanced （P〈0.05） and was correlated with apoptosis of spermatogenic cells in cryptorchid testes （P〈0.05）. PEI was efficient in mediating transfeetion of TSEG-2 into seminiferous tubules of testis. One week post-transfection, intratesticular injection of TSEG-2 resulted in increased apoptosis of spermatogenic cells in vivo （P〈0.05）. These results indicate that TSEG-2 may participate in the apoptosis of spermatogenic cells and the pathogenesis of cryptorchidism.

Inheritance Analysis of Bolting Associated Traits Using Mixed Major Gene Plus Polygene Model in Brassica rapa

[ Objective ] This study aimed to analyze the inheritance of bolting associated traits in Brassica rapa, which will provide useful information in a breeding program for late-bolting or bolting-resistant cultivars of Chinese cabbage. [ Method] Three phenotypic measurements, bolting index, flowering time, days to 5 cm elongated stalk, respectively were used for inheritance analysis of six generations, P, （bolting resistant inbreed line ）, P2 （vernalization independent type） and their filial generations F1 , B1, B2 and F2, using the mixed major-gene plus polygene inheritance model. [ Result] The two traits, bolting index and days to 5 cm elongated stalk, both were controlled by two major genes with additive-dominant-epistatic effects （ B-1 model） in hybrid. The flowering time was controlled by one major gene with addltive-dominant effects plus additive-dominant-epistatic effects （D model）. The heritability of the major genes in B1, B2 and F2 were 96.22%, 93.33%, 93.55% for bolting index, 70.68%, 70.68%, 70.64% for flowering time, 79.44%, 79.55%, 79.38% for days to 5-cm elongated stalk, respectively, but no polygene heritability was detected in BI, B2 and F2 generation. It indicated that the bolting trait in Brassica rapa was controlled by one or tow major genes. [ Conclusion] This implied that in the genetic improvement for bolting resistant trait major gene was a main factor. It is fit for early selection and environment factor should be mentioned.

Integrated analysis of human influenza A(H1N1)virus infectionrelated genes to construct a suitable diagnostic model

The genome characteristics and structural functions of coding proteins correlate with the genetic diversity of the H1N1 virus,which aids in the understanding of its underlying pathogenic mechanism.In this study,analyses of the characteristic of the H1N1 virus infection-related genes,their biological functions,and infection-related reversal drugs were performed.Additionally,we used multi-dimensional bioinformatics analysis to identify the key genes and then used these to construct a diagnostic model for the H1N1 virus infection.There was a total of 169 differently expressed genes in the samples between 21 h before infection and 77 h after infection.They were used during the protein-protein interaction(PPI)analysis,and we obtained a total of 1725 interacting genes.Then,we performed a weighted gene co-expression network analysis(WGCNA)on these genes,and we identified three modules that showed significant potential for the diagnosis of the H1N1 virus infection.These modules contained 60 genes,and they were used to construct this diagnostic model,which showed an effective prediction value.Besides,these 60 genes were involved in the biological functions of this infectious virus,like the cellular response to type I interferon and in the negative regulation of the viral life cycle.However,20 genes showed an upregulated expression as the infection progressed.Other 36 upregulated genes were used to examine the relationship between genes,human influenza A virus,and infection-related reversal drugs.This study revealed numerous important reversal drug molecules on the H1N1 virus.They included rimantadine,interferons,and shikimic acid.Our study provided a novel method to analyze the characteristic of different genes and explore their corresponding biological function during the infection caused by the H1N1 virus.This diagnostic model,which comprises 60 genes,shows that a significant predictive value can be the potential biomarker for the diagnosis of the H1N1 virus infection.

Genome engineering and disease modeling via programmable nucleases for insulin gene therapy;promises of CRISPR/Cas9 technology

Targeted genome editing is a continually evolving technology employing programmable nucleases to specifically change,insert,or remove a genomic sequence of interest.These advanced molecular tools include meganucleases,zinc finger nucleases,transcription activator-like effector nucleases and RNA-guided engineered nucleases(RGENs),which create double-strand breaks at specific target sites in the genome,and repair DNA either by homologous recombination in the presence of donor DNA or via the error-prone non-homologous end-joining mechanism.A recently discovered group of RGENs known as CRISPR/Cas9 gene-editing systems allowed precise genome manipulation revealing a causal association between disease genotype and phenotype,without the need for the reengineering of the specific enzyme when targeting different sequences.CRISPR/Cas9 has been successfully employed as an ex vivo gene-editing tool in embryonic stem cells and patient-derived stem cells to understand pancreatic beta-cell development and function.RNA-guided nucleases also open the way for the generation of novel animal models for diabetes and allow testing the efficiency of various therapeutic approaches in diabetes,as summarized and exemplified in this manuscript.

CMT1A current gene therapy approaches and promising biomarkers

Charcot-Marie-Tooth neuropathies(CMT)constitute a group of common but highly heterogeneous,non-syndromic genetic disorders affecting predominantly the peripheral nervous system.CMT type 1A(CMT1A)is the most frequent type and accounts for almost~50%of all diagnosed CMT cases.CMT1A results from the duplication of the peripheral myelin protein 22(PMP22)gene.Overexpression of PMP22 protein overloads the protein folding apparatus in Schwann cells and activates the unfolded protein response.This leads to Schwann cell apoptosis,dys-and de-myelination and secondary axonal degeneration,ultimately causing neurological disabilities.During the last decades,several different gene therapies have been developed to treat CMT1A.Almost all of them remain at the pre-clinical stage using CMT1A animal models overexpressing PMP22.The therapeutic goal is to achieve gene silencing,directly or indirectly,thereby reversing the CMT1A genetic mechanism allowing the recovery of myelination and prevention of axonal loss.As promising treatments are rapidly emerging,treatment-responsive and clinically relevant biomarkers are becoming necessary.These biomarkers and sensitive clinical evaluation tools will facilitate the design and successful completion of future clinical trials for CMT1A.

Animal models of genetic causes of male infertility

Introduction In the past 10 years, more than 100 different genetically engineered mice have been developed with an abnormality in spermatogenesis. More than half of these male infertility animal models have been reported in the past three years alone. Spermatogenic defects in these models vary considerably, ranging from the inappropriate migration of primordial germ cells to the inability of mature spermatozoa to bind the zona pellucida. Many of

Hepatocellular carcinoma mouse models:Hepatitis B virusassociatedhepatocarcinogenesis and haploinsufficienttumor suppressor genes

The multifactorial and multistage pathogenesis of hepatocellular carcinoma(HCC)has fascinated a wide spectrum of scientists for decades.While a number of major risk factors have been identified,their mechanistic roles in hepatocarcinogenesis still need to be elucidated.Many tumor suppressor genes(TSGs)have been identified as being involved in HCC.These TSGs can be classified into two groups depending on the situation with respect to allelic mutation/loss in the tumors:the recessive TSGs with two required mutated alleles and the haploinsufficient TSGs with one required mutated allele.Hepatitis B virus(HBV)is one of the most important risk factors associated with HCC.Although mice cannot be infected with HBV due to the narrow host range of HBV and the lack of a proper receptor,one advantage of mouse models for HBV/HCC research is the numerous and powerfulgenetic tools that help investigate the phenotypic effects of viral proteins and allow the dissection of the dose-dependent action of TSGs.Here,we mainly focus on the application of mouse models in relation to HBV-associated HCC and on TSGs that act either in a recessive or in a haploinsufficient manner.Discoveries obtained using mouse models will have a great impact on HCC translational medicine.

High yield reproducible rat model recapitulating human Barrett's carcinogenesis

AIM To efficiently replicate the biology and pathogenesis of human esophageal adenocarcinoma(EAC) using the modified Levrat model of end-to-side esophagojejunostomy. METHODS End-to-side esophagojejunostomy was performed on rats to induce gastroduodenoesophageal reflux to develop EAC. Animals were randomly selected and serially euthanized at 10(n = 6),17(n = 8),24(n = 9),31(n = 6),38(n = 6),and 40(n = 6) wk postoperatively. The esophagi were harvested for downstream histopathology and gene expression. Histological evaluation wascompleted to determine respective rates of carcinogenic development. Quantitative reverse transcriptionpolymerase chain reaction was performed to determine gene expression levels of MUC2,CK19,and CK20,and results were compared to determine significant differences throughout disease progression stages.RESULTS The overall study mortality was 15%. Causes of mortality included anastomotic leak,gastrointestinal hemorrhage,stomach ulcer perforation,respiratory infection secondary to aspiration,and obstruction due to tumor or late anastomotic stricture. 10 wk following surgery,100% of animals presented with esophagitis. Barrett's esophagus(BE) was first observed at 10 wk,and was present in 100% of animals by 17 wk. Dysplasia was confirmed in 87.5% of animals at 17 wk,and increased to 100% by 31 wk. EAC was first observed in 44.4% of animals at 24 wk and increased to 100% by 40 wk. In addition,two animals at 38-40 wk post-surgery had confirmed macro-metastases in the lung/liver and small intestine,respectively. MUC2 gene expression was progressively down-regulated from BE to dysplasia to EAC. Both CK19 and CK20 gene expression significantly increased in a stepwise manner from esophagitis to EAC. CONCLUSION Esophagojejunostomy was successfully replicated in rats with low mortality and a high tumor burden,which may facilitate broader adoption to study EAC development,progression,and therapeutics.

The potential of gene therapies for spinal cord injury repair:a systematic review and meta-analysis of pre-clinical studies

Currently,there is no cure for traumatic spinal co rd injury but one therapeutic approach showing promise is gene therapy.In this systematic review and meta-analysis,we aim to assess the efficacy of gene therapies in pre-clinical models of spinal cord injury and the risk of bias.In this metaanalysis,registe red at PROSPERO(Registration ID:CRD42020185008),we identified relevant controlled in vivo studies published in English by searching the PubMed,Web of Science,and Embase databases.No restrictions of the year of publication were applied and the last literature search was conducted on August 3,2020.We then conducted a random-effects meta-analysis using the restricted maximum likelihood estimator.A total of 71 studies met our inclusion crite ria and were included in the systematic review.Our results showed that overall,gene therapies were associated with improvements in locomotor score(standardized mean difference[SMD]:2.07,95%confidence interval[CI]:1.68-2.47,Tau^(2)=2.13,I^(2)=83.6%)and axonal regrowth(SMD:2.78,95%CI:1.92-3.65,Tau^(2)=4.13,I^(2)=85.5%).There was significant asymmetry in the funnel plots of both outcome measures indicating the presence of publication bias.We used a modified CAMARADES(Collaborative Approach to M eta-Analysis and Review of Animal Data in Experimental Studies)checklist to assess the risk of bias,finding that the median score was 4(IQR:3-5).In particula r,reports of allocation concealment and sample size calculations were lacking.In conclusion,gene therapies are showing promise as therapies for spinal co rd injury repair,but there is no consensus on which gene or genes should be targeted.

The application of hidden markov model in building genetic regulatory network

The research hotspot in post-genomic era is from sequence to function. Building genetic regulatory network (GRN) can help to understand the regulatory mechanism between genes and the function of organisms. Probabilistic GRN has been paid more attention recently. This paper discusses the Hidden Markov Model (HMM) approach served as a tool to build GRN. Different genes with similar expression levels are considered as different states during training HMM. The probable regulatory genes of target genes can be found out through the resulting states transition matrix and the determinate regulatory functions can be predicted using nonlinear regression algorithm. The experiments on artificial and real-life datasets show the effectiveness of HMM in building GRN.

Effect of warm acupuncture on nitric oxide synthase and calcitonin gene-related peptide in a rat model of lumbar nerve root compression

BACKGROUND： Varying degrees of inflammatory responses occur during lumbar nerve root compression. Studies have shown that nitric oxide synthase （NOS） and calcitonin gene-related peptide （CGRP） are involved in secondary disc inflammation. OBJECTIVE： To observe the effects of warm acupuncture on the ultrastructure of inflammatory mediators in a rat model of lumbar nerve root compression, including NOS and CGRP contents. DESIGN, TIME AND SETTING： Randomized, controlled study, with molecular biological analysis, was performed at the Experimental Center, Sixth People＇s Hospital Affiliated to Shanghai Jiao Tong University, between September 2006 and April 2007. MATERIALS： Acupuncture needles and refined Moxa grains were purchased from Shanghai Taicheng Technology Development Co., Ltd., China; Mobic tablets were purchased from Shanghai Boehringer Ingelheim Pharmaceuticals Co., Ltd., China; enzyme linked immunosorbent assay （ELISA） kits for NOS and CGRP were purchased from ADL Biotechnology, Inc., USA. METHODS： A total of 50, healthy, adult Sprague-Dawley rats, were randomly divided into five groups normal, model, warm acupuncture, acupuncture, and drug, with 10 rats in each group. Rats in the four groups, excluding the normal group, were used to establish models of lumbar nerve root compression. After 3 days, Jiaji points were set using reinforcing-reducing manipulation in the warm acupuncture group. Moxa grains were burned on each needle, with 2 grains each daily. The acupuncture group was the same as the warm acupuncture group, with the exception of non-moxibustion. Mobic suspension （3.75 mg/kg） was used in the oral drug group, once a day. Treatment of each group lasted for 14 consecutive days. Modeling and medication were not performed in the normal group. MAIN OUTCOME MEASURES： The ultrastructure of damaged nerve roots was observed with transmission electron microscopy; NOS and CGRP contents were measured using ELISA. RESULTS： The changes of the radicular ultramicrostructure were characterized by Wallerian degeneration; nerve fibers were clearly demyelinated; axons collapsed or degenerated; outer Schwann cell cytoplasm was swollen and its nucleus was compacted. Compared with the normal group, NOS and CGRP contents in the nerve root compression zone in the model group were significantly increased （P 〈 0.01）. Nerve root edema was improved in the drug, acupuncture and the warm acupuncture groups over the model group. NOS and CGRP expressions were also decreased with the warm acupuncture group having the lowest concentration （P 〈 0.01）. CONCLUSION： In comparison to the known effects of Mobic drug and acupuncture treatments, the warm acupuncture significantly decreased NOS and CGRP expression which helped improve the ultrastructure of the compressed nerve root.

A Re-Parametrization-Based Bayesian Differential Analysis Algorithm for Gene Regulatory Networks Modeled with Structural Equation Models

Under different conditions,gene regulatory networks(GRNs)of the same gene set could be similar but different.The differential analysis of GRNs under different conditions is important for understanding condition-specific gene regulatory relationships.In a naive approach,existing GRN inference algorithms can be used to separately estimate two GRNs under different conditions and identify the differences between them.However,in this way,the similarities between the pairwise GRNs are not taken into account.Several joint differential analysis algorithms have been proposed recently,which were proved to outperform the naive approach apparently.In this paper,we model the GRNs under different conditions with structural equation models(SEMs)to integrate gene expression data and genetic perturbations,and re-parameterize the pairwise SEMs to form an integrated model that incorporates the differential structure.Then,a Bayesian inference method is used to make joint differential analysis by solving the integrated model.We evaluated the performance of the proposed re-parametrization-based Bayesian differential analysis(ReBDA)algorithm by running simulations on synthetic data with different settings.The performance of the ReBDA algorithm was demonstrated better than another state-of-the-art joint differential analysis algorithm for SEMs ReDNet obviously.In the end,the ReBDA algorithm was applied to make differential analysis on a real human lung gene data set to illustrate its applicability and practicability.