Working condition recognition of sucker rod pumping system based on 4-segment time-frequency signature matrix and deep learning

High-precision and real-time diagnosis of sucker rod pumping system(SRPS)is important for quickly mastering oil well operations.Deep learning-based method for classifying the dynamometer card(DC)of oil wells is an efficient diagnosis method.However,the input of the DC as a two-dimensional image into the deep learning framework suffers from low feature utilization and high computational effort.Additionally,different SRPSs in an oil field have various system parameters,and the same SRPS generates different DCs at different moments.Thus,there is heterogeneity in field data,which can dramatically impair the diagnostic accuracy.To solve the above problems,a working condition recognition method based on 4-segment time-frequency signature matrix(4S-TFSM)and deep learning is presented in this paper.First,the 4-segment time-frequency signature(4S-TFS)method that can reduce the computing power requirements is proposed for feature extraction of DC data.Subsequently,the 4S-TFSM is constructed by relative normalization and matrix calculation to synthesize the features of multiple data and solve the problem of data heterogeneity.Finally,a convolutional neural network(CNN),one of the deep learning frameworks,is used to determine the functioning conditions based on the 4S-TFSM.Experiments on field data verify that the proposed diagnostic method based on 4S-TFSM and CNN(4S-TFSM-CNN)can significantly improve the accuracy of working condition recognition with lower computational cost.To the best of our knowledge,this is the first work to discuss the effect of data heterogeneity on the working condition recognition performance of SRPS.

The W transform and its improved methods for time-frequency analysis of seismic data

The conventional linear time-frequency analysis method cannot achieve high resolution and energy focusing in the time and frequency dimensions at the same time,especially in the low frequency region.In order to improve the resolution of the linear time-frequency analysis method in the low-frequency region,we have proposed a W transform method,in which the instantaneous frequency is introduced as a parameter into the linear transformation,and the analysis time window is constructed which matches the instantaneous frequency of the seismic data.In this paper,the W transform method is compared with the Wigner-Ville distribution(WVD),a typical nonlinear time-frequency analysis method.The WVD method that shows the energy distribution in the time-frequency domain clearly indicates the gravitational center of time and the gravitational center of frequency of a wavelet,while the time-frequency spectrum of the W transform also has a clear gravitational center of energy focusing,because the instantaneous frequency corresponding to any time position is introduced as the transformation parameter.Therefore,the W transform can be benchmarked directly by the WVD method.We summarize the development of the W transform and three improved methods in recent years,and elaborate on the evolution of the standard W transform,the chirp-modulated W transform,the fractional-order W transform,and the linear canonical W transform.Through three application examples of W transform in fluvial sand body identification and reservoir prediction,it is verified that W transform can improve the resolution and energy focusing of time-frequency spectra.

Leveraging ROTI map derived from Indonesian GNSS receiver network for advancing study of Equatorial Plasma Bubble in Southeast/East Asia

This paper highlights the crucial role of Indonesia’s GNSS receiver network in advancing Equatorial Plasma Bubble(EPB)studies in Southeast and East Asia,as ionospheric irregularities within EPB can disrupt GNSS signals and degrade positioning accuracy.Managed by the Indonesian Geospatial Information Agency(BIG),the Indonesia Continuously Operating Reference Station(Ina-CORS)network comprises over 300 GNSS receivers spanning equatorial to southern low-latitude regions.Ina-CORS is uniquely situated to monitor EPB generation,zonal drift,and dissipation across Southeast Asia.We provide a practical tool for EPB research,by sharing two-dimensional rate of Total Electron Content(TEC)change index(ROTI)derived from this network.We generate ROTI maps with a 10-minute resolution,and samples from May 2024 are publicly available for further scientific research.Two preliminary findings from the ROTI maps of Ina-CORS are noteworthy.First,the Ina-CORS ROTI maps reveal that the irregularities within a broader EPB structure persist longer,increasing the potential for these irregularities to migrate farther eastward.Second,we demonstrate that combined ROTI maps from Ina-CORS and GNSS receivers in East Asia and Australia can be used to monitor the development of ionospheric irregularities in Southeast and East Asia.We have demonstrated the combined ROTI maps to capture the development of ionospheric irregularities in the Southeast/East Asian sector during the G5 Geomagnetic Storm on May 11,2024.We observed simultaneous ionospheric irregularities in Japan and Australia,respectively propagating northwestward and southwestward,before midnight,whereas Southeast Asia’s equatorial and low-latitude regions exhibited irregularities post-midnight.By sharing ROTI maps from Indonesia and integrating them with regional GNSS networks,researchers can conduct comprehensive EPB studies,enhancing the understanding of EPB behavior across Southeast and East Asia and contributing significantly to ionospheric research.

High-resolution seismic inversion method based on joint data-driven in the time-frequency domain

Seismic inversion can be divided into time-domain inversion and frequency-domain inversion based on different transform domains.Time-domain inversion has stronger stability and noise resistance compared to frequencydomain inversion.Frequency domain inversion has stronger ability to identify small-scale bodies and higher inversion resolution.Therefore,the research on the joint inversion method in the time-frequency domain is of great significance for improving the inversion resolution,stability,and noise resistance.The introduction of prior information constraints can effectively reduce ambiguity in the inversion process.However,the existing modeldriven time-frequency joint inversion assumes a specific prior distribution of the reservoir.These methods do not consider the original features of the data and are difficult to describe the relationship between time-domain features and frequency-domain features.Therefore,this paper proposes a high-resolution seismic inversion method based on joint data-driven in the time-frequency domain.The method is based on the impedance and reflectivity samples from logging,using joint dictionary learning to obtain adaptive feature information of the reservoir,and using sparse coefficients to capture the intrinsic relationship between impedance and reflectivity.The optimization result of the inversion is achieved through the regularization term of the joint dictionary sparse representation.We have finally achieved an inversion method that combines constraints on time-domain features and frequency features.By testing the model data and field data,the method has higher resolution in the inversion results and good noise resistance.

Landslide Susceptibility Mapping Using RBFN-Based Ensemble Machine Learning Models

This study was aimed to prepare landslide susceptibility maps for the Pithoragarh district in Uttarakhand,India,using advanced ensemble models that combined Radial Basis Function Networks(RBFN)with three ensemble learning techniques:DAGGING(DG),MULTIBOOST(MB),and ADABOOST(AB).This combination resulted in three distinct ensemble models:DG-RBFN,MB-RBFN,and AB-RBFN.Additionally,a traditional weighted method,Information Value(IV),and a benchmark machine learning(ML)model,Multilayer Perceptron Neural Network(MLP),were employed for comparison and validation.The models were developed using ten landslide conditioning factors,which included slope,aspect,elevation,curvature,land cover,geomorphology,overburden depth,lithology,distance to rivers and distance to roads.These factors were instrumental in predicting the output variable,which was the probability of landslide occurrence.Statistical analysis of the models’performance indicated that the DG-RBFN model,with an Area Under ROC Curve(AUC)of 0.931,outperformed the other models.The AB-RBFN model achieved an AUC of 0.929,the MB-RBFN model had an AUC of 0.913,and the MLP model recorded an AUC of 0.926.These results suggest that the advanced ensemble ML model DG-RBFN was more accurate than traditional statistical model,single MLP model,and other ensemble models in preparing trustworthy landslide susceptibility maps,thereby enhancing land use planning and decision-making.

基于MAP法的线路板重金属铜氨废水处理研究

随着线路板的广泛应用,其在印刷过程中产生的铜氨废水的排放问题日益突出。铜氨废水中氨氮和铜离子对环境的危害较大,为了解决该问题,提出了一种MAP法和折点氯化法相结合的方法。该方法首先向铜氨废水中加入镁盐和磷酸盐,将氨氮转化为MAP沉淀,降低铜氨废水中氨氮的浓度,同时可以将MAP回收再利用;然后向剩余浓液中加入过量的NaClO溶液,进一步将溶液中的氨氮浓度降低,随着NaClO溶液的增加,反应液会逐渐呈碱性,而Cu^(2+)在碱性环境中会与OH-生成Cu(OH)_(2)沉淀,进而降低Cu^(2+)的浓度,从而使铜氨废水中的氨氮和Cu2+的浓度均符合《中华人民共和国环境保护法》的排放要求;最后通过纳氏试剂分光光度法和火焰原子吸收光度法检验反应后浓液中氨氮和Cu^(2+)的浓度。经过验证得知,该方法可以显著降低氨氮和Cu^(2+)的浓度。

Compiling molecular evidence from a tetraploid rose genome into a near-saturated map for the identification of pigment-related genes

With their high economic value and cultural significance,modern roses are one of the most important ornamental plants.Because of their complicated genetic background and tetraploid nature,the creation of high-density genetic maps of roses has been a challenge that has slowed the pace of molecular breeding for modern roses.The current construction of tetraploid genetic maps based on existing diploid rose genomes could lead to inaccurate marker information and genotyping results.Therefore,we generated the first high-quality tetraploid genome of Rosa chinensis‘Yunzheng Xiawei.'Utilizing Illumina,PacBio,and Hi-C sequencing technologies,we assembled a genome of 858.59 Mb with 14pseudo-chromosomes.Mode of inheritance analysis using PolyOrigin indicated that modern roses show both quadrivalent and bivalent pairing.Based on this reference genome,high-density genetic maps were constructed using MSTmap with nearly saturated markers.Quantitative trait locus(QTL)analysis was conducted using WinQTLCart and R/qtl for flavonoids and carotenoids,and 11 QTL clusters were identified.By combining the genome annotation,phylogenetic analyses,and gene expression analyses,we were able to identify several key genes related to flavonoid and carotenoid biosynthesis.This study provides the basis for further genetic analyses of highly heterozygous tetraploid roses and could facilitate the progress of marker-assisted selection in modern roses.

Identification of long InDels through whole genome resequencing to fine map qIF05-1 for seed isoflavone content in soybean(Glycine max L. Merr.)

Soybean seed isoflavones are a type of secondary metabolites that can provide health and nutrition benefits for humans. In our previous study, a stable quantitative trait locus(QTL) qIF05-1 controlling the seed isoflavone content in soybean was detected on chromosome(Chr.) 05 in a recombinant inbred line(RIL) population from a cross of Huachun 2×Wayao. In this study, the parental lines were re-sequenced using the Illumina Solexa System with deep coverage. A total of 63,099 polymorphic long insertions and deletions(InDels)(≥15 bp)were identified between the parents Huachun 2 and Wayao. The InDels were unevenly distributed on 20chromosomes of soybean, varying from 1,826 in Chr. 12 to 4,544 in Chr. 18. A total of 10,002 long InDels(15.85% of total) were located in genic regions, including 1,139 large-effect long InDels which resulted in truncated or elongated protein sequences. In the qIF05-1 region, 68 long InDels were detected between the two parents. Using a progeny recombination experiment and genotype analysis, the qIF05-1 locus was mapped into a 102.2 kb genomic region, and this region contained 12 genes. By RNA-seq data analysis, genome sequence comparison and functional validation through ectopic expression in Arabidopsis thaliana, Glyma.05G208300(described as GmEGL3), which is a basic helix-loop-helix(bHLH) transcription factor in plants, emerged as the most likely confirmed gene in qIF05-1. These long InDels can be used as a type of complementary genetic method for QTL fine mapping, and they can facilitate genetic studies and molecular-assisted selection breeding in soybean.

GPU-Enabled Isogometric Topology Optimization with Bezier Element Stiffness Mapping

Due to the high-order B-spline basis functions utilized in isogeometric analysis(IGA)and the repeatedly updating global stiffness matrix of topology optimization,Isogeometric topology optimization(ITO)intrinsically suffers from the computationally demanding process.In this work,we address the efficiency problem existing in the assembling stiffness matrix and sensitivity analysis using B˙ezier element stiffness mapping.The Element-wise and Interaction-wise parallel computing frameworks for updating the global stiffness matrix are proposed for ITO with B˙ezier element stiffness mapping,which differs from these ones with the traditional Gaussian integrals utilized.Since the explicit stiffness computation formula derived from B˙ezier element stiffness mapping possesses a typical parallel structure,the presented GPU-enabled ITO method can greatly accelerate the computation speed while maintaining its high memory efficiency unaltered.Numerical examples demonstrate threefold speedup:1)the assembling stiffness matrix is accelerated by 10×maximumly with the proposed GPU strategy;2)the solution efficiency of a sparse linear system is enhanced by up to 30×with Eigen replaced by AMGCL;3)the efficiency of sensitivity analysis is promoted by 100×with GPU applied.Therefore,the proposed method is a promising way to enhance the numerical efficiency of ITO for both single-patch and multiple-patch design problems.

DTI联合T2 mapping在神经根型颈椎病神经根损伤定量评价中的应用

目的:探讨弥散张量成像(DTI)联合T2 mapping技术在定量评价神经根型颈椎病患者神经根损伤中的应用价值。方法:对82例神经根型颈椎病患者与30例健康志愿者进行颈椎间盘常规MRI、DTI、T2 mapping及T1 Vibe检查。测量所有受试者神经根的各序列参数,包括FA(各向异性分数)、ADC(表观扩散系数)、AD(轴向扩散系数)、RD(径向扩散系数)及T2值。利用VAS评分对患者进行疼痛学评分。比较患者受压神经根与健康志愿者神经根的各序列参数值差异,并分析各序列参数值与VAS评分的相关性。结果:神经根型颈椎病患者的患侧神经根较健侧及健康志愿者神经根FA值显著减低,ADC、AD、RD、T2值显著升高(P<0.05)。患侧神经根FA平均值与VAS评分呈中度负相关(r=-0.544),ADC、AD、RD、T2平均值与VAS呈正相关(ADC:r=0.457;AD:0.249;RD:0.390;T2:r=0.497)(P<0.05)。ROC曲线分析显示,当DTI所有参数与T2值联合时,曲线下面积(AUC)最大,为0.980,对应的敏感度为95.3%,特异度为94.6%。结论:DTI及T2 mapping技术可以用于评价神经根型颈椎病患者颈神经根损伤,且当DTI与T2 mapping联合使用时可获得最佳诊断效能。

Application of sparse time-frequency decomposition to seismic data

The Gabor and S transforms are frequently used in time-frequency decomposition methods. Constrained by the uncertainty principle, both transforms produce low-resolution time-frequency decomposition results in the time and frequency domains. To improve the resolution of the time-frequency decomposition results, we use the instantaneous frequency distribution function（IFDF） to express the seismic signal. When the instantaneous frequencies of the nonstationary signal satisfy the requirements of the uncertainty principle, the support of IFDF is just the support of the amplitude ridges in the signal obtained using the short-time Fourier transform. Based on this feature, we propose a new iteration algorithm to achieve the sparse time-frequency decomposition of the signal. The iteration algorithm uses the support of the amplitude ridges of the residual signal obtained with the short-time Fourier transform to update the time-frequency components of the signal. The summation of the updated time-frequency components in each iteration is the result of the sparse timefrequency decomposition. Numerical examples show that the proposed method improves the resolution of the time-frequency decomposition results and the accuracy of the analysis of the nonstationary signal. We also use the proposed method to attenuate the ground roll of field seismic data with good results.

TVAR Time-frequency Analysis for Non-stationary Vibration Signals of Spacecraft

Predicting the time-varying auto-spectral density of a spacecraft in high-altitude orbits requires an accurate model for the non-stationary random vibration signals with densely spaced modal frequency. The traditional time-varying algorithm limits prediction accuracy, thus affecting a number of operational decisions. To solve this problem, a time-varying auto regressive （TVAR） model based on the process neural network （PNN） and the empirical mode decomposition （EMD） is proposed. The time-varying system is tracked on-line by establishing a time-varying parameter model, and then the relevant parameter spectrum is obtained. Firstly, the EMD method is utilized to decompose the signal into several intrinsic mode functions （IMFs）. Then for each IMF, the PNN is established and the time-varying auto-spectral density is obtained. Finally, the time-frequency distribution of the signals can be reconstructed by linear superposition. The simulation and the analytical results from an example demonstrate that this approach possesses simplicity, effectiveness, and feasibility, as well as higher frequency resolution.

Intelligibility evaluation of enhanced whisper in joint time-frequency domain

Some factors influencing the intelligibility of the enhanced whisper in the joint time-frequency domain are evaluated. Specifically, both the spectrum density and different regions of the enhanced spectrum are analyzed. Experimental results show that for a spectrum of some density, the joint time-frequency gain-modification based speech enhancement algorithm achieves significant improvement in intelligibility. Additionally, the spectrum region where the estimated spectrum is smaller than the clean spectrum, is the most important region contributing to intelligibility improvement for the enhanced whisper. The spectrum region where the estimated spectrum is larger than twice the size of the clean spectrum is detrimental to speech intelligibility perception within the whisper context.

融合Mind Map优势助力完善线上线下教学衔接--以园林树木学树种识别教学为例

疫情当前,线上线下混合式教学已经成为课程教学新模式。树种识别是园林树木学教学的重点和难点,也是教学目的之一。由于课程涉及的树种种类繁多,知识点琐碎,专业术语抽象,再加上课时少任务重,使得教师在教学过程中无法将所有树种的特征逐一讲解到,学生在学习过程中也容易混淆,无法有效吸收知识点。因此,在课程的教学改革中,通过引入Mind Map帮助厘清知识框架,优化知识结构,搭建知识关联,不仅使教师授课过程更顺畅,而且能够激发学生在线学习的兴趣,促使学生养成“整理知识点”的良好习惯,使学习效率大幅度提高,从而创建高效的线上课堂,有效巩固混合式教学的教学效果。

Effects of Gabor transform parameters on signa time-frequency resolution

In this paper, it is described that the time-frequency resolution of geophysical signals is affected by the time window function attenuation coefficient and sampling interval and how such effects are eliminated effectively. Improving the signal resolution is the key to signal time-frequency analysis processing and has wide use in geophysical data processing and extraction of attribute parameters. In this paper, authors research the effects of the attenuation coefficient choice of the Gabor transform window function and sampling interval on signal resolution. Unsuitable parameters not only decrease the signal resolution on the frequency spectrum but also miss the signals. It is essential to first give the optimum window and range of parameters through time-frequency analysis simulation using the Gabor transform. In the paper, the suggestions about the range and choice of the optimum sampling interval and processing methods of general seismic signals are given.

磁共振T1rho序列、T2 mapping技术在膝关节早期软骨退变早期诊断中的评估价值

目的探讨磁共振T1rho序列、T2 mapping技术在膝关节早期软骨退变早期诊断中的评估价值。方法选取2020年1月至2022年11月在我院治疗的110例膝关节早期软骨退变患者(观察组),按照疾病严重程度分为轻度退变组及重度退变组,另选取同期在我院进行体检的64例健康者为对照组,受试者均行磁共振T1rho序列、T2 mapping技术扫描,测量受试者T2值及T1ρ值,探讨磁共振T1rho序列、T2 mapping技术在膝关节早期软骨退变早期诊断中的评估价值。结果观察组股骨外侧面、股骨内侧面、胫骨外侧面、胫骨内侧面、髋骨面T2值均明显高于对照组(P<0.05),重度退变亚组患者股骨外侧面、股骨内侧面、胫骨外侧面、胫骨内侧面、髋骨面T2值显著高于轻度退变者(P<0.05);观察组股骨内踝负重区、股骨内踝非负重区、股骨外踝负重区、股骨外踝非负重区、胫骨外侧平台区、胫骨内侧平台区、髌后软骨区磁共振T1ρ值明显高于对照组(P<0.05),重度退变亚组患者股骨内踝负重区、股骨内踝非负重区、股骨外踝负重区、股骨外踝非负重区、胫骨外侧平台区、胫骨内侧平台区、髌后软骨区磁共振T1ρ值明显高于轻度退变亚组患者(P<0.05);磁共振T1rho序列在膝关节早期软骨退变中早期诊断及严重程度评估中的的诊断ROC值及特异度明显高于T2 mapping技术(P<0.05),但后者具有更高的敏感度(P<0.05)。结论磁共振T1rho序列、T2 mapping技术均能有效反映膝关节早期软骨退变中软骨组织学成分变化情况,还可为膝关节软骨退变严重程度评估提供客观依据,二者具有一定互补价值。

MR T2^(*)mapping成像技术定量评价腰椎小关节炎软骨损伤

背景:腰椎小关节炎是引起下腰痛的一个主要原因,目前主要依靠MRI进行初步定性诊断,但仍有一定漏诊、误诊的概率发生,因此MR T2^(*)mapping成像技术有望成为定量检查腰椎小关节炎软骨损伤的重要检测手段。目的:探讨MR T2^(*)mapping成像技术在定量分析腰椎小关节炎软骨损伤退变中的应用价值。方法:收集南京医科大学第四附属医院2020年4月至2022年3月门诊或住院合并下腰痛共110例患者,设为病例组;同时招募无症状志愿者80例,设为对照组。对所有纳入对象L1-S1的小关节行3.0 T MR扫描,获取T2^(*)mapping横断位图像和T2WI图像,分别对所有小关节软骨进行Weishaupt分级及T2^(*)值测量,收集数据并行统计学分析。不同小关节Weishaupt分级之间小关节软骨T2^(*)值比较采用单因素方差分析。结果与结论:①经统计分析发现,病例组腰椎小关节软骨T2^(*)值(17.6±1.5)ms明显较对照组(21.4±1.3)ms降低,差异有显著性意义(P<0.05);②在病例组中,随着腰椎小关节Weishaupt分级增加,小关节软骨T2^(*)值也呈逐渐下降趋势,且这种差异有显著性意义(P<0.05);③提示T2^(*)mapping能够较好地显示腰椎小关节软骨损伤的早期病理变化,腰椎小关节软骨的T2^(*)值能够定量评估腰椎小关节的软骨损伤程度;T2^(*)mapping成像技术能为影像学诊断腰椎小关节炎软骨早期损伤提供很好的理论依据,具有重要的临床应用价值。

MOLLI T1 mapping定量技术在儿童脑发育评估中的应用可行性探讨

目的探讨改良回顾反转恢复(modified Look-Locker inversion recover,MOLLI)序列T1 mapping定量技术在定量评价儿童脑部发育中的价值。材料与方法纳入头部磁共振检查正常的儿童53例,使用优化后的MOLLI及磁化准备2快速采集梯度回波(magnetization prepared 2 rapid acquisition gradient echoes,MP2RAGE)序列对每例受检者的36个脑区进行T1 mapping定量分析。评价两个序列所得各脑区T1值的一致性,比较两个序列各脑区T1值的差异,分析两个序列各脑区T1值与年龄之间的相关性。结果MOLLI序列和MP2RAGE序列除在双侧脑桥背侧、大脑脚组内相关系数(intra-class correlation coefficient,ICC)<0.8(P<0.001)外,其余脑区ICC均>0.8(P<0.001)。两个序列各脑区的T1值差异均有统计学意义(P<0.05,FDR校正),MOLLI组各脑区T1值高于MP2RAGE组。两个序列各脑区的T1值均与年龄呈负相关(P均<0.001)。结论优化后的MOLLI序列可用于儿童脑部发育的定量评价,与MP2RAGE序列一致性好,可较准确地量化脑区的T1值,为儿童神经系统的研究提供了新的方法选择。

MAP添加液对冰冻解冻去甘油红细胞保存的质量影响

目的观察冰冻解冻去甘油红细胞悬浮于MAP添加液中对保存效果的影响,探索最佳保存方式。方法本研究将采集后d 3的400 mL全血,离心制备成浓缩红细胞,使用ACP 215全自动血细胞仪,加入40%复方甘油溶液,置于-65℃超低温冰箱中保存30 d,解冻去甘油洗涤后,等量分离成两袋,以添加0.9%氯化钠溶液为对照组;添加MAP为实验组,两组保存于2~6℃冷藏条件下,分别于0、1、3、5、7、14 d取样检测血液学参数指标、溶血指标、细胞代谢指标,观察两组在14 d保存期内的质量变化情况。结果研究发现两组红细胞在解冻去甘油后6项质控项目包括容量、血红蛋白含量、游离血红蛋白含量、白细胞残留量、甘油残留量、无菌试验的检测值均符合《全血及成分血质量要求》(GB18469-2012);压积、红细胞计数、Hb洗涤后回收率、MCV符合《冰冻红细胞质量评价指标专家共识》检测限值,血小板残留量超过检测限值(≤1%);在14 d保存期内,两组的RBC、Hct、MCV和血红蛋白含量值无统计学意义;两组游离血红蛋白、溶血率和K+值随保存时间延长而增加,分别于3、5、7、14 d;3、5、7、14 d;14 d组间有统计学意义(P<0.05),两组红细胞渗透脆性于14 d组间有统计学意义(P<0.05);两组ATP、pH值随保存时间延长而下降,分别于3、5、7 d;1、3、5、7、14 d组间有统计学意义(P<0.05)。结论悬浮于MAP添加液中的冰冻解冻去甘油红细胞可将血液保存期延长至7 d,本研究为相关标准的制定提供参考依据。

番鸭VIPR1和miR-317以及MAP3K7和miR-244靶向关系的研究

试验旨在验证番鸭就巢相关miRNA与靶基因靶向关系。试验利用miRanda、PITA和RNAhybrid三个软件的交集预测miR-317和miR-244靶基因,构建VIPR1-pmirGLO/MAP3K7-pmirGLO野生型和突变型双荧光素酶重组载体,将miR-317/VIPR1-Wt和miR-244/MAP3K7-Wt分别共转染至鸭胚成纤维细胞,检测双荧光素酶活性。结果显示:与miR-NC组相比,miR-317/VIPR1-Wt共转染组相对荧光值显著降低(P<0.05);VIPR1突变后,miR-NC组与miR-317组的相对荧光值不显著(P>0.05),说明突变后完全抑制miR-317对VIPR1的结合作用,VIPR1与miR-317之间存在相互结合作用。与miR-NC组相比,miR-244/MAP3K7-Wt共转染组相对荧光值无显著性差异(P>0.05);MAP3K7突变后,miR-NC组与miR-244组的相对荧光值差异不显著(P>0.05),表明MAP3K7与miR-244之间不存在相互结合作用。研究提示,miR-317与VIPR1存在确切靶向结合位点,即VIPR1是miRNA miR-317的靶基因,而miR-244与MAP3K7不存在靶向关系。