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。

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.

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.

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.

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. .

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.

Multi-variable grey model (MGM(1,n,q)) based on genetic algorithm and its application in urban water consumption

Urban water consumption has some characteristics of grey because it is influenced by economy, population, standard of living and so on. The multi-variable grey model (MGM(1,n)), as the expansion and complement of GM(1,1) model, reveals the relationship between restriction and stimulation among variables, and the genetic algorithm has the whole optimal and parallel characteristics. In this paper, the parameter q of MGM(1,n) model was optimized, and a multi-variable grey model (MGM(1,n,q)) was built by using the genetic algorithm. The model was validated by examining the urban water consumption from 1990 to 2003 in Dalian City. The result indicated that the multi-variable grey model (MGM(1,n,q)) based on genetic algorithm was better than MGM(1,n) model, and the MGM(1,n) model was better than MGM(1,1) model.

The Non-Equidistant Grey GRM (1, 1) Model and Its Application

Applying the modeling method of Grey system and accumulated generating operation of reciprocal number for the problem of lower precision as well as lower adaptability in non-equidistant GM (1, 1) model, the calculation formulas were deduced and a non-equidistant GRM (1, 1) model generated by accumulated generating operation of reciprocal number was put forward .The grey GRM (1, 1) model can be used in non-equal interval & equal interval time series and has the characteristic of high precision as well as high adaptability. Example validates the practicability and reliability of the proposed model.

The Modified GM( 1 , 1) Grey Forecast Model

Because the impacts of the factors such as some disturbances are graduallyadded into the system, the grey forecast results will deviate from the systemtrue value. To improve the forecast precision, Pro-Dens Julons provided twomethfor-But they had not consider the impact of artificial disturbance. LiZhihua et al. of Qinghua Univ. presented another method. This paper revisesthe method and make it be a spocial case.

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。

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。

以专科护士为主导的“1+1+X”协同管理模式对稳定型心绞痛患者病情、自我管理能力的影响分析

目的研究以专科护士为主导的“1+1+X”协同管理模式对稳定型心绞痛患者病情、自我管理能力的影响。方法方便选取2021年3月—2023年3月聊城市第二人民医院心血管内科收治的86例稳定型心绞痛患者为研究对象,根据不同护理方法分为常规组和协同管理组,各43例。常规组采用常规护理,协同管理组采用以专科护士为主导的“1+1+X”协同管理模式护理,两组均持续护理1个月。观察对比两组患者护理前后生活质量[健康调查简表(MOS Item Short Form Health Survey,SF-36)]、焦虑抑郁心理状况、自我管理能力[冠心病自我管理行为量表(Coronary Artery Disease Self-management Scale,CSMS)]。结果护理后,协同管理组SF-36量表评分高于常规组,差异有统计学意义(P<0.05);协同管理组焦虑自评量表(38.18±3.52)分、抑郁自评量表(39.21±3.24)分均优于常规组的(43.23±3.61)分、(45.03±3.69)分,差异有统计学意义(t=6.568、7.772,P均<0.05);协同管理组CSMS评分高于常规组,差异有统计学意义(P均<0.05)。结论以专科护士为主导的“1+1+X”协同管理模式应用于稳定型心绞痛患者护理可有效提升生活质量,改善不良心理状态,提高自我管理能力。

塔里木盆地顺北1号断裂带奥陶系碳酸盐岩储层结构表征及三维地质建模

综合利用地震、测井、岩心以及动态生产资料,对塔里木盆地顺北1号断裂带断控型碳酸盐岩储集体的内部结构进行了层级划分;基于层级划分,通过地震资料属性提取与转换、深度学习、基于目标示性点过程模拟以及离散裂缝网络模拟(DFN)等方法建立了三维地质模型,并以模型进行油气储量和油藏数值模拟,将拟合结果与实际生产数据进行对比。研究结果表明:(1)顺北1号断裂带奥陶系断控型储层按层级由大到小分为走滑断裂影响带、断控体、类洞穴、类洞穴内簇充填和裂缝带共5个层级。(2)走滑断裂影响带受应力差异影响具有分段性,可细分为挤压段、拉分段和平移段;断控体在拉分段发育断裂交会型、单支走滑型,在平移段发育双断裂交错型和两断裂交会型,在挤压段发育双断裂扭曲型和双断裂交会型,共有6种平面组合样式;类洞穴在地震剖面上呈串珠状反射特征;类洞穴内部分为栅体与栅间(基岩),其中栅体又可进一步分为簇(角砾带)、簇间(裂缝带),整体表现为栅状结构,簇的物性更好;裂缝带为类洞穴的主要储集空间,在簇内部比簇间更发育,在一间房组比鹰山组更发育,一间房组和鹰山组均以发育高角度裂缝为主,在两者连接处则以发育水平缝为主。(3)地质模型预测的油气储量与地质分析储量误差为1.75%,模型模拟的生产井地层压力及累产液结果与生产动态吻合度较高,拟合误差小于10%。

“互联网+”背景下“1+X”证书制度融通人才培养模式优化探索

职业教育作为一种教育类型,侧重于实践技能和实际工作能力的培养,要求所培养的人才必须具有一定的文化水平和专业知识技能。“1+X”证书制度在制度层面上将学校与企业联系起来,相互合作,共同培养复合型技术人才。在“互联网+”背景下,本文在职业教育领域中,通过实施目标融合、标准互通、校企协同、多元评价等措施,探索了“1+X”证书制度融通人才培养模式的优化思路与方法,旨在加强学校与企业的联系,培养企业需要的复合型技术人才。

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.

1+X证书制度下Web前端开发人才培养模式探索——以海南软件职业技术学院为例

Web前端开发职业技能等级证书是首批启动试点的6个1+X职业技能等级证书之一,海南软件职业技术学院是Web前端开发职业技能等级证书首批启动试点院校之一。文章以海南软件职业技术学院为例,研究了Web前端开发职业技能等级标准,分析了Web前端开发人才培养方案及其存在的问题,优化了基于1+X证书制度的人才培养模式和人才培养评价模式。