Acupuncture at the “Huatuojiaji” point affects nerve root regional interleukin-1 level in a rat model of lumbar nerve root compression

BACKGROUND：It has been shown that interleukin-1 （IL-1） may cause inflammatory reactions, which stimulate the nerve root of patients with lumbar intervertebral disc protrusion and leads to pain. Whether the clinical curative effects of acupuncture in the treatment of lumbar and leg pain are linked to an inhibition of local IL-1 secretion is unknown. OBJECTIVE： To assess the influence of acupuncture on IL-1, this study was designed to verify the effects of acupuncture at the ＂Huatuojiaji （Extra）＂ point on the nerve root in a rat model of lumbar nerve root compression, compared with administration of meloxicam, a non-steroidal anti-inflammatory drug. DESIGN, TIME AND SETTING： Randomized, controlled, molecular biology experiment, performed at the Experimental Center, Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University between September 2005 and April 2006. MATERIALS： Forty healthy adult Sprague Dawley rats of either gender were included in this study. The rats were randomly and evenly divided into the following four groups： normal control, model, acupuncture and meloxicam groups. Lumbar nerve root compression was induced in rats in the model, acupuncture, and meloxicam groups by inserting a specially made silicon rubber slice at the juncture of the L5 nerve root and the dural sac. The acupuncture needle （pattern number N3030, 30#, 1.5 inch） was purchased from Suzhou Medical Appliance Factory, China. IL-1 enzyme linked immunosorbent assay （ELISA） kit was purchased from Santa Cruz Biotechnology, Inc., USA. METHODS： The acupuncture group was acupunctured at the ＂Huatuojiaji＂ point, which is lateral to the compressed L5-6 nerve root, with an acupuncture depth of 0.5 cm. There were two treatment courses, each of involved seven 20-minute acupuncture sessions, one session a day. The meloxicam group was administered intragastrically 3.75 mg/kg meloxicam （5 mg meloxicam /10 mL physiological saline）. Rats in the normal control group and model group received an intragastric administration of 10 mL/kg physiological saline. All administrations were performed once a day. MAIN OUTCOME MEASURES： At day 14 post-surgery, the IL-1 level in the compressed nerve root was determined by a streptavidin-peroxidase （S-P） immunohistochemical method, and IL-1β mRNA expression in the compressed nerve root was simultaneously detected by real-time reverse transcription-polymerase chain reaction. RESULTS： The expression levels of IL-1 and IL-1β mRNA in the L5 nerve root were significantly higher in the model group than in the control group （P 〈 0.01）. However, the expression levels of IL-1 and IL-1β mRNA were significantly lower in the acupuncture and meloxicam groups than in the model group （P 〈 0.05–0.01）. Expression levels of IL-1 and IL-1β mRNA were significantly higher in the acupuncture group than in the meloxicam group （P 〈 0.01）. CONCLUSION： Acupuncture at the ＂Huatuojiaji＂ point decreases the IL-1 level by inhibiting IL-1β mRNA expression to a greater extent than meloxicam administration.

Asymptotic normality of error density estimator in stationary and explosive autoregressive models

In this paper,we consider the limit distribution of the error density function estima-tor in the rst-order autoregressive models with negatively associated and positively associated random errors.Under mild regularity assumptions,some asymptotic normality results of the residual density estimator are obtained when the autoregressive models are stationary process and explosive process.In order to illustrate these results,some simulations such as con dence intervals and mean integrated square errors are provided in this paper.It shows that the residual density estimator can replace the density\estimator"which contains errors.

Establishment of a humanized ST6GAL1 mouse model for influenza research

Background:This study aimed to construct and characterize a humanized influenza mouse model expressing hST6GAL1.Methods:Humanized fragments,consisting of the endothelial cell-specific K18 promoter,human ST6GAL1-encoding gene,and luciferase gene,were microinjected into the fertilized eggs of mice.The manipulated embryos were transferred into the oviducts of pseudopregnant female mice.The offspring were identified using PCR.Mice exhibiting elevated expression of the hST6GAL1 gene were selectively bred for propagation,and in vivo analysis was performed for screening.Expression of the humanized gene was tested by performing immunohistochemical(IHC)analysis.Hematologic and biochemical analyses using the whole blood and serum of humanized hST6GAL1 mice were performed.Results:Successful integration of the human ST6GAL1 gene into the mouse genome led to the overexpression of human SiaT ST6GAL1.Seven mice were identified as carrying copies of the humanized gene,and the in vivo analysis indicated that hST6GAL1gene expression in positive mice mirrored influenza virus infection characteristics.The IHC results revealed that hST6GAL1 was expressed in the lungs of humanized mice.Moreover,the hematologic and biochemical parameters of the positive mice were within the normal range.Conclusion:A humanized influenza mouse model expressing the hST6GAL1 gene was successfully established and characterized.

Tidal modeling based on satellite altimetry observations of TOPEX/ Poseidon, Jason1, Jason2, and Jason3 with high prediction capability: A case study of the Baltic Sea

This research aims to optimize the utilization of long-term sea level data from the TOPEX/Poseidon,Jason1,Jason2,and Jason3 altimetry missions for tidal modeling.We generate a time series of along-track observations and apply a developed method to produce tidal models with specific tidal constituents for each location.Our tidal modeling methodology follows an iterative process:partitioning sea surface height(SSH)observations into analysis/training and prediction/validation parts and ultimately identi-fying the set of tidal constituents that provide the best predictions at each time series location.The study focuses on developing 1256 time series along the altimetry tracks over the Baltic Sea,each with its own set of tidal constituents.Verification of the developed tidal models against the sSH observations within the prediction/validation part reveals mean absolute error(MAE)values ranging from 0.0334 m to 0.1349 m,with an average MAE of 0.089 m.The same validation process is conducted on the FES2014 and EOT20 global tidal models,demonstrating that our tidal model,referred to as BT23(short for Baltic Tide 2023),outperforms both models with an average MAE improvement of 0.0417 m and 0.0346 m,respectively.In addition to providing details on the development of the time series and the tidal modeling procedure,we offer the 1256 along-track time series and their associated tidal models as supplementary materials.We encourage the satellite altimetry community to utilize these resources for further research and applications.

An approach to estimate tree height using PolInSAR data constructed by the Sentinel-1 dual-pol SAR data and RVoG model

We estimate tree heights using polarimetric interferometric synthetic aperture radar(PolInSAR)data constructed by the dual-polarization(dual-pol)SAR data and random volume over the ground(RVoG)model.Considering the Sentinel-1 SAR dual-pol(SVV,vertically transmitted and vertically received and SVH,vertically transmitted and horizontally received)configuration,one notes that S_(HH),the horizontally transmitted and horizontally received scattering element,is unavailable.The S_(HH)data were constructed using the SVH data,and polarimetric SAR(PolSAR)data were obtained.The proposed approach was first verified in simulation with satisfactory results.It was next applied to construct PolInSAR data by a pair of dual-pol Sentinel-1A data at Duke Forest,North Carolina,USA.According to local observations and forest descriptions,the range of estimated tree heights was overall reasonable.Comparing the heights with the ICESat-2 tree heights at 23 sampling locations,relative errors of 5 points were within±30%.Errors of 8 points ranged from 30%to 40%,but errors of the remaining 10 points were>40%.The results should be encouraged as error reduction is possible.For instance,the construction of PolSAR data should not be limited to using SVH,and a combination of SVH and SVV should be explored.Also,an ensemble of tree heights derived from multiple PolInSAR data can be considered since tree heights do not vary much with time frame in months or one season.

Numerical Models and Methods of Atmospheric Parameters Originating in the Formation of the Earth’s Climatic Cycle

Atmospheric models are physical equations based on the ideal gas law. Applied to the atmosphere, this law yields equations for water, vapor (gas), ice, air, humidity, dryness, fire, and heat, thus defining the model of key atmospheric parameters. The distribution of these parameters across the entire planet Earth is the origin of the formation of the climatic cycle, which is a normal climatic variation. To do this, the Earth is divided into eight (8) parts according to the number of key parameters to be defined in a physical representation of the model. Following this distribution, numerical models calculate the constants for the formation of water, vapor, ice, dryness, thermal energy (fire), heat, air, and humidity. These models vary in complexity depending on the indirect trigonometric direction and simplicity in the sum of neighboring models. Note that the constants obtained from the equations yield 275.156˚K (2.006˚C) for water, 273.1596˚K (0.00963˚C) for vapor, 273.1633˚K (0.0133˚C) for ice, 0.00365 in/s for atmospheric dryness, 1.996 in2/s for humidity, 2.993 in2/s for air, 1 J for thermal energy of fire, and 0.9963 J for heat. In summary, this study aims to define the main parameters and natural phenomena contributing to the modification of planetary climate. .

成纤维细胞生长因子受体1 抑制剂对胶原诱导关节炎模型大鼠骨破坏的影响

背景:课题组前期的研究表明靶向成纤维细胞生长因子受体1(fibroblast growth factor receptor 1,FGFR1)可能是治疗类风湿性关节炎的有效靶点。目的:探讨FGFR1抑制剂(PD173074)对胶原诱导关节炎模型大鼠骨破坏的影响。方法:将25只雌性SD大鼠随机分为5组,正常对照组、模型组、甲氨蝶呤组、PD173074低剂量组、PD173074高剂量组。除正常对照组外,其余各组大鼠建立Ⅱ型胶原诱导关节炎模型。造模成功后正常组及模型组大鼠腹腔注射无菌PBS,甲氨蝶呤组药物注射剂量为1.04 mg/kg,PD173074低剂量组和高剂量组药物注射剂量分别为5,20 mg/kg,1次/周。给药4周后取材,观察大鼠临床症状以及关节肿胀情况,踝关节Micro-CT三维重建及分析,观察踝关节病理变化,检测关节周围血管生成情况及核因子κB受体活化因子配体的表达,检测关节滑膜中p-FGFR1、血管内皮生长因子A、抗酒石酸酸性磷酸酶的表达,观察肝、脾、肾病理变化并计算肝、脾、肾指数。结果与结论:①PD173074能够减轻模型大鼠踝关节临床症状及关节肿胀,延缓骨质丢失,改善骨结构,减轻关节滑膜侵袭以及软骨骨侵蚀,降低关节周围破骨细胞数量,抑制关节滑膜组织中的血管生成,降低核因子κB受体活化因子配体的表达,抑制FGFR1磷酸化蛋白、抗酒石酸酸性磷酸酶和血管内皮生长因子A的蛋白表达。②大鼠肝、脾、肾病理观察表明经过PD173074治疗后无明显的毒副作用。③研究证明了FGFR1抑制剂能够延缓Ⅱ型胶原诱导关节炎模型大鼠关节炎症及骨破坏的进展,并抑制血管的生成。初步验证了PD173074在Ⅱ型胶原诱导关节炎模型中的治疗作用,其可能是通过抑制FGFR1磷酸化发挥作用,为寻找类风湿性关节炎新的治疗靶点提供了方向。

Application of Modelica Based Multi- Domain Modeling and Simulation for Gravity-1

In the R&D phase of Gravity-1(YL-1), a multi-domain modeling and simulation technology based on Modelica language was introduced, which was a recent attempt in the practice of modeling and simulation method for launch vehicles in China. It realizes a complex coupling model within a unified model for different domains, so that technologists can work on one model. It ensured the success of YL-1 first launch mission, supports rapid iteration, full validation, and tight design collaboration.

Exploiting fly models to investigate rare human neurological disorders

Rare neurological diseases,while individually are rare,collectively impact millions globally,leading to diverse and often severe neurological symptoms.Often attributed to genetic mutations that disrupt protein function or structure,understanding their genetic basis is crucial for accurate diagnosis and targeted therapies.To investigate the underlying pathogenesis of these conditions,researchers often use non-mammalian model organisms,such as Drosophila(fruit flies),which is valued for their genetic manipulability,cost-efficiency,and preservation of genes and biological functions across evolutionary time.Genetic tools available in Drosophila,including CRISPR-Cas9,offer a means to manipulate gene expression,allowing for a deep exploration of the genetic underpinnings of rare neurological diseases.Drosophila boasts a versatile genetic toolkit,rapid generation turnover,and ease of large-scale experimentation,making it an invaluable resource for identifying potential drug candidates.Researchers can expose flies carrying disease-associated mutations to various compounds,rapidly pinpointing promising therapeutic agents for further investigation in mammalian models and,ultimately,clinical trials.In this comprehensive review,we explore rare neurological diseases where fly research has significantly contributed to our understanding of their genetic basis,pathophysiology,and potential therapeutic implications.We discuss rare diseases associated with both neuron-expressed and glial-expressed genes.Specific cases include mutations in CDK19 resulting in epilepsy and developmental delay,mutations in TIAM1 leading to a neurodevelopmental disorder with seizures and language delay,and mutations in IRF2BPL causing seizures,a neurodevelopmental disorder with regression,loss of speech,and abnormal movements.And we explore mutations in EMC1 related to cerebellar atrophy,visual impairment,psychomotor retardation,and gain-of-function mutations in ACOX1 causing Mitchell syndrome.Loss-of-function mutations in ACOX1 result in ACOX1 deficiency,characterized by very-long-chain fatty acid accumulation and glial degeneration.Notably,this review highlights how modeling these diseases in Drosophila has provided valuable insights into their pathophysiology,offering a platform for the rapid identification of potential therapeutic interventions.Rare neurological diseases involve a wide range of expression systems,and sometimes common phenotypes can be found among different genes that cause abnormalities in neurons or glia.Furthermore,mutations within the same gene may result in varying functional outcomes,such as complete loss of function,partial loss of function,or gain-of-function mutations.The phenotypes observed in patients can differ significantly,underscoring the complexity of these conditions.In conclusion,Drosophila represents an indispensable and cost-effective tool for investigating rare neurological diseases.By facilitating the modeling of these conditions,Drosophila contributes to a deeper understanding of their genetic basis,pathophysiology,and potential therapies.This approach accelerates the discovery of promising drug candidates,ultimately benefiting patients affected by these complex and understudied diseases.

Study on the Prediction of Rice Blast Based on the Unbiased GM (1,1) Model

To create a new prediction model, the unbiased GM （1,1） model is optimized by the five-point slide method in this paper. Then, based on the occurrence areas of dce blast in Enshi District during 1995 -2004, the new model and unbiased GM （1, 1 ） model are applied to predict the occurrence areas of rice blast during 2005 -2010. Predicting outcomes show that the prediction accuracy of five-point unbiased sliding optimized GM （1, 1 ） model is higher than the unbiased GM （1,1） model. Finally, combined with the prediction results, the author provides some suggestion for Enshi District in the prevention and control of rice blast in 2010.

River channel flood forecasting method of coupling wavelet neural network with autoregressive model

Based on analyzing the limitations of the commonly used back-propagation neural network （BPNN）, a wavelet neural network （WNN） is adopted as the nonlinear river channel flood forecasting method replacing the BPNN. The WNN has the characteristics of fast convergence and improved capability of nonlinear approximation. For the purpose of adapting the timevarying characteristics of flood routing, the WNN is coupled with an AR real-time correction model. The AR model is utilized to calculate the forecast error. The coefficients of the AR real-time correction model are dynamically updated by an adaptive fading factor recursive least square（RLS） method. The application of the flood forecasting method in the cross section of Xijiang River at Gaoyao shows its effectiveness.

Protective Effects of Oral Fructose-1, 6-diphosphate on Liver Injury in Animal Models

Aim To investigate the effects of FDP on different liver injury models to explore the possibility of FDP used as an oral liver protective agent. Methods Chronic liver injury model in rats was induced by carbon tetrachloride （ CCl4 ） ; Acute liver injury model in mice was induced by aminogalactose （GAIN） or lipopolysaccharide （LPS）. Results In CCl4-induced chronic liver injury model, FDP （1 , 4 g·kg^-1·d^-1, q.d., for 10 weeks） significantly lowered ALT, AST,γ-glutamyl transpeptidase （γ-GT）, alkaline phosphatase （ALP）, and total bilirubin （T-BIL） in serum compared with vehicle; simultaneously it evidently elevated abnormal total protein （TP）, albumin （ALB） and total cholesterol （ T-CHO ） levels in serum; it also dose-dependently reduced hydroxyproline contents in hepatic tissue. 4 g·kg^-1·d^-1 of FDP apparently decreased incidence of hepatic cirrhosis, and alleviated pathological changes of liver tissue. In GaiN-induced model, 1.0 - 4. 0 g·kg^-1·d^-1 of FDP （ bid, for 3 d ） significantly lowered alanine aminotransferase （ ALT ） and aspartate aminotransferase （ AST ） levels in serum ; it also decreased liver coefficient. 4. 0 g·kg^-1·d^-1 of FDP significantly alleviated pathological changes of cell ultra-structures. In LPS-induced model, only high dose of FDP （4. 0 g·kg^-1·d^-1, bid, for 12 d） significantly decreased ALT level in serum. Conclusion This study first demonstrated the protective effect of oral FDP on chronic liver injury caused by CCl4, and confirmed its effect on acute liver injury at the same time, suggesting that Long-term oral FDP is efficacious against liver injury induced by different factors and can be used as an oral liver protective agent in clinic.

基于Sentinel-1/2改进极化指数和纹理特征的土壤含盐量反演模型

目前Sentinel-1/2协同反演植被土壤含盐量的研究大多是基于Sentinel-2光谱信息和Sentinel-1后向散射系数,没有考虑Sentinel-2光谱信息容易受土壤亮度等信息影响,Sentinel-1后向散射系数容易受土壤粗糙度和水分影响。为进一步提高Sentinel-1/2协同反演植被土壤含盐量的精度,用水云模型对雷达卫星后向散射系数进行校正,消除植被影响;然后协同Sentinel-2纹理特征,基于VIP、OOB、PCA 3种变量筛选和RF、ELM、Cubist 3种机器学习回归模型构建植被土壤含盐量反演模型。研究结果表明:经过水云模型去除植被影响后的雷达后向散射系数及其极化组合指数与土壤含盐量的相关性有一定程度的提高。不同变量选择方法与不同机器学习方法耦合模型在反演土壤含盐量中,OOB变量筛选方法与RF、ELM和Cubist 3种机器学习方法的耦合模型精度最佳,建模集和验证集的R2都在0.750以上,且验证集的RMSE和MAE均最小;其中OOB-Cubist耦合模型精度最高,且R_(v)^(2)/R_(c)^(2)为0.955,具有良好的鲁棒性。研究可为机器学习协同物理模型、光学卫星协同雷达卫星在土壤含盐量反演中的进一步应用提供思路。

北京市东城区2009—2019年蝇类生态学监测结果分析及其预测方法探讨

目的 掌握北京市东城区2009—2019年蝇种类、密度、分布及其季节消长规律,探讨基于生态学监测的蝇类密度预测方法,为东城区蝇类预测与科学防控提供依据。方法 收集整理东城区2009—2019年蝇类生态学监测数据并进行分析;利用MATLAB R2018b软件构建的季节性差分自回归移动平均模型(SARIMA)对2019年4—10月的蝇类密度进行预测并与实际监测值进行比较,验证模型预测效果。结果 2009—2019年东城区各生态学监测点蝇类年平均密度为7.09只/笼,优势蝇种为麻蝇科,占捕获蝇总数的56.82%,占比超过5%以上的蝇种类依次为厩腐蝇(11.74%)、家蝇(10.17%)、丝光绿蝇(8.99%)和大头金蝇(6.93%);不同生境中,宾馆饭店蝇类密度最高,为11.86只/笼,餐饮外环境最低,为2.20只/笼,麻蝇科在不同生境中均为优势种群;蝇类密度高峰主要出现在7月和8月。基于历史生态学监测数据构建的最优模型SARIMA(0,1,4)(2,1,3)12预测2019年4—10月的蝇类密度与实际密度基本一致,实际监测值均落在预测值95%置信区间内,模型评价指标均方根误差(RMSE)和平均绝对误差(MAE)分别为1.379和1.014,预测效果较好。结论 2009—2019年北京市东城区以麻蝇科为优势种群,宾馆饭店是蝇类防控的重点场所,活动高峰主要出现在7—8月;通过对SARIMA模型效果评价,该方法可用于蝇类密度短期变化趋势预测。

基于新型“1+X+N”人才培养模式的一流本科课程建设探索

为了适应时代的发展需求,响应国务院提出的在应用型本科高校启动“学历证书+若干职业技能等级证书”制度(即“1+X”证书制度)的试点工作,民办本科院校积极探索“1+X+N”人才培养新模式。在人才培养新模式下,省级一流本科课程光纤通信技术课程组从明确课程定位、推动教学改革、加大资源建设、优化教学内容与实施过程、推进课程思政、改善课程成绩评定等方面开展工作,努力提升学生在光纤通信方面的综合应用能力,培养出满足新时代通信发展需求的高质量人才。

1+X证书制度背景下“育训结合、能力递进、书证融通”育人模式的探索与实践

2019年《国家职业教育改革实施方案》要求启动“学历证书+若干职业技能等级证书”制度。文章基于“1+X”证书制度下的书证融通在实施过程中存在的问题,从模块化课程体系构建、信息化资源与教材开发、平台搭建、师资队伍建设、考核评价体系、体制机制保障等方面开展研究,逐步构建学生、学校、行业、企业、社会多方共赢的良好局面,为实现新时代中国职业教育事业的全面优质发展奠定基础。

基于GF-1数据的耕地土壤镉(Cd)含量遥感估算方法

本文采用多种光谱变换和回归分析方法探索了使用GF-1卫星影像监测耕地土壤镉(Cd)含量的可行性。首先针对获取的GF-1原始影像数据,在完成预处理及剔除植被信息后进行倒对数、平方根和反正弦平方根变换,生成4套光谱影像;然后分别用采样点5 m缓冲区内各套影像光谱统计值与Cd含量进行相关性分析和多种回归分析。选择模型决定系数最高(>95%)的反正弦平方根变换后的自适应重加权回归方法构建的线性回归模型作为遥感估算模型。遥感估算结果在稻田积水、边缘地带等出现了异常估算值;笔者分析原因后应用线性插值的方法得到最终估算结果。相关性分析和建模精度表明该方法是可行的,有望应用于实际土壤质量监测和土地管理中。

AUTOREGRESSIVE MODEL AND POWER SPECTRUM CHARATERISTICS OF CURRENT SIGNAL IN HIGH FREQUENCY GROUP PULSE MICRO-ELECTROCHEMICAL MACHINING

The identification of the inter-electrode gap size in the high frequency group pulse micro-electrochemical machining （HGPECM） is mainly discussed. The auto-regressive（AR） model of group pulse current flowing across the cathode and the anode are created under different situations with different processing parameters and inter-electrode gap size. The AR model based on the current signals indicates that the order of the AR model is obviously different relating to the different processing conditions and the inter-electrode gap size; Moreover, it is different about the stability of the dynamic system, i.e. the white noise response of the Green＇s function of the dynamic system is diverse. In addition, power spectrum method is used in the analysis of the dynamic time series about the current signals with different inter-electrode gap size, the results show that there exists a strongest power spectrum peak, characteristic power spectrum（CPS）, to the current signals related to the different inter-electrode gap size in the range of 0～5 kHz. Therefore, the CPS of current signals can implement the identification of the inter-electrode gap.

Divalent metal transporter 1 expression and iron deposition in the substantia nigra of a rat model of Parkinson's disease

Extensive iron deposition has been observed in the midbrain substantia nigra （SN） of Parkinson＇s disease （PD） patients, but the mechanisms of iron deposition in the SN remain poorly understood. The present study investigated the relationship between dopaminergic neuronal damage, iron content changes, and divalent metal transporter 1 （DMT1） in the midbrain SN of PD rats to explore the relationship between time of iron deposition and DMT1 expression. Frozen midbrain SN sections from model rats were stained with Perls＇ iron. Results showed massive loss of tyrosine hydroxylase （TH）-positive cells in the SN and increased DMT1 expression in model group rats. No obvious iron deposition was observed in the SN during early stages after damage, but significant iron deposition was detected at 8 weeks post-injury. Results demonstrate that the loss of TH-positive cells in the SN appeared simultaneously with increased DMT1 expression. Extensive iron deposition occurred at 8 weeks post injury, which could be regarded as an early time window of iron deposition.

Prediction model of interval grey number based on DGM(1,1)

In grey system theory,the studies in the field of grey prediction model are focused on real number sequences,rather than grey number ones.Hereby,a prediction model based on interval grey number sequences is proposed.By mining the geometric features of interval grey number sequences on a two-dimensional surface,all the interval grey numbers are converted into real numbers by means of certain algorithm,and then the prediction model is established based on those real number sequences.The entire process avoids the algebraic operations of grey number,and the prediction problem of interval grey number is usefully solved.Ultimately,through an example＇s program simulation,the validity and practicability of this novel model are verified.