Study of a Novel Antiosteoporosis Screening Model Targeted on Cathepsin K

Objective To establish an effective assay to access the effects of natural products on cathepsin K for screening antiosteoporosis drugs. Methods To obtain the purified cathepsin K, we cloned the target fragment from the mRNA of human osteosacoma cell line MG63 and demonstrated its correctness through DNA sequencing. Cathepsin K was expressed in a high amount in E.coli after IPTG induction, and was purified to near homogenetity through resolution and column purification. The specificity of the protein was shown by Western blotting experiment. The biological activity of the components in the fermentation broth was assayed by their inhibitory effects on cathepsin K and its analog papain. Results With the inhibition of papain activity as a screen index, the fermentation samples of one thousand strains of fungi were tested and 9 strains among them showed strong inhibitory effects. The crude products of the fermentation broth were tested for their specific inhibitory effects on the purified human cathepsin K, the product of fungi 2358 shows the highest specificity against cathepsin K. Conclusions The compounds isolated from fungi 2358 show the highest biological activity and are worth further structure elucidation and function characterization.

Development of a New High-throughput Screening Model for Human High Density Lipoprotein Receptor (CLA-1) Agonists

To develop a new high-throughput screening model for human high-density lipoprotein （HDL） receptor （CD36 and LIMPⅡ analogous-1, CLA-1） agonists using CLA-1-expressing insect cells. Methods With the total RNA of human hepatoma cells BEL-7402 as template, the complementary DNA （cDNA） of CLA-1 was amplified by reverse transcription-polymerase chain reaction （RT-PCR）. Bac-to-Bac baculovirus expression system was used to express CLA-1 in insect cells. CLA-1 cDNA was cloned downstream of polyhedrin promoter of Autographa californica nuclear polyhedrosis virus （AcNPV） into donor vector pFastBacl and recombinant pFastBacl-CLA-1 was transformed into E. coli DH10Bac to transpose CLA-1 cDNA to bacrnid DNA. Recombinant bacrnid-CLA-1 was transfected into Spodopterafrugiperda Sf9 insect cells to produce recombinant baculovirus particles. Recombinant CLA- 1 was expressed on the membrane of Sf9 cells infected with the recombinant baculoviruses. A series of parameters of DiI-lipoprotein binding assays of CLA-1-expressing Sf9 cells in 96-well plates were optimized. Results Western blot analysis and DiI-lipoprotein binding assays confirmed that CLA-1 expressed in insect cells had similar immunoreactivity and ligand binding activity as its native counterpart. A reliable and sensitive in vitro cell-based assay was established to assess the activity of CLA-1 and used to screen agonists from different sample libraries. Conclusion Human HDL receptor CLA-1 was successfully expressed in Sf9 insect cells and a novel high-throughput screening model for CLA-1 agonists was developed. Utilization of this model allows us to identify potent and selective CLA-1 agonists which might possibly be used as therapeutics for atherosclerosis.

Development and validation of a prediction model for early screening of people at high risk for colorectal cancer

BACKGROUND Colorectal cancer(CRC)is a serious threat worldwide.Although early screening is suggested to be the most effective method to prevent and control CRC,the current situation of early screening for CRC is still not optimistic.In China,the incidence of CRC in the Yangtze River Delta region is increasing dramatically,but few studies have been conducted.Therefore,it is necessary to develop a simple and efficient early screening model for CRC.AIM To develop and validate an early-screening nomogram model to identify individuals at high risk of CRC.METHODS Data of 64448 participants obtained from Ningbo Hospital,China between 2014 and 2017 were retrospectively analyzed.The cohort comprised 64448 individuals,of which,530 were excluded due to missing or incorrect data.Of 63918,7607(11.9%)individuals were considered to be high risk for CRC,and 56311(88.1%)were not.The participants were randomly allocated to a training set(44743)or validation set(19175).The discriminatory ability,predictive accuracy,and clinical utility of the model were evaluated by constructing and analyzing receiver operating characteristic(ROC)curves and calibration curves and by decision curve analysis.Finally,the model was validated internally using a bootstrap resampling technique.RESULTS Seven variables,including demographic,lifestyle,and family history information,were examined.Multifactorial logistic regression analysis revealed that age[odds ratio(OR):1.03,95%confidence interval(CI):1.02-1.03,P<0.001],body mass index(BMI)(OR:1.07,95%CI:1.06-1.08,P<0.001),waist circumference(WC)(OR:1.03,95%CI:1.02-1.03 P<0.001),lifestyle(OR:0.45,95%CI:0.42-0.48,P<0.001),and family history(OR:4.28,95%CI:4.04-4.54,P<0.001)were the most significant predictors of high-risk CRC.Healthy lifestyle was a protective factor,whereas family history was the most significant risk factor.The area under the curve was 0.734(95%CI:0.723-0.745)for the final validation set ROC curve and 0.735(95%CI:0.728-0.742)for the training set ROC curve.The calibration curve demonstrated a high correlation between the CRC high-risk population predicted by the nomogram model and the actual CRC high-risk population.CONCLUSION The early-screening nomogram model for CRC prediction in high-risk populations developed in this study based on age,BMI,WC,lifestyle,and family history exhibited high accuracy.

Developmental toxicity assessment of neonicotinoids and organophosphate esters with a human embryonic stem cell-and metabolism-based fast-screening model

In recent years,neonicotinoids(NEOs)and organophosphate esters(OPEs)have been widely used as substitutes for traditional pesticides and brominated fame-retardants,respectively.Previous studies have shown that those compounds can be frequently detected in environmental and human samples,are able to penetrate the placental barrier,and are toxic to animals.Thus,it is reasonable to speculate that NEOs and OPEs may have potential adverse effects in humans,especially during development.We employed a human embryonic stem cell differentiation-and liver S9 fraction metabolism-based fast screening model to assess the potential embryonic toxicity of those two types of chemicals.We show that four NEO and five OPE prototypes targeted mostly ectoderm specification,as neural ectoderm and neural crest genes were down-regulated,and surface ectoderm and placode markers up-regulated.Human liver S9 fraction's treatment could generally reduce the effects of the chemicals,except in a few specific instances,indicating the liver may detoxify NEOs and OPEs.Our findings suggest that NEOs and OPEs interfere with human early embryonic development.

Establishment and application of the screening model of the Mycobacterium tuberculosis β-lactamase BlaC inhibitors

With the continuous emergence and rapid spread of multidrug-resistant and extensively-drug-resistant Mycobacterium tuberculosis strains, it is imperative to develop novel therapies against this bacterium. The intrinsic β-lactam resistance of M. tuberculosis is primarily due to the production of an Ambler class-A β-lactamase BlaC, which limits the application of β-lactam antibiotics in the treatment of tuberculosis. Therefore, the inhibitors of BlaC could be novel anti-tuberculosis drug synergistic agents to recover the sensibility of M. Tuberculosis to the β-lactam antibiotics. In the present study, BlaC of M. tuberculosis was expressed and purified to establish a screening model of the BlaC inhibitors. The screening conditions were determined, and the screening model was evaluated to fit for the high throughput screening. A total of 22 BlaC inhibitors were screened out from 26 400 compound samples with a positive rate of 0.083%. Taken together, our findings lay the foundation for the discovery of novel anti-tuberculosis drug synergistic agents in clinic.

Preliminary Research on a Mesenchymal Stem Cell-model for Screening Traditional Chinese Medicines

The authors focused their attention on the establishment of a mesenchymal stem cell（MSC） model for screening traditional Chinese medicines（TCMs） so as to investigate the effects of Shuanglong Formula（SLF） components（Ginsenosides and salvianolic acids） and ingredients（ginsenoside Rb1 and salvianolic acid B） on cardiomyocyte differentiation from MSCs.The SLF components were analyzed and quantified by HPLC-TOF-MS.Cardiomyocyte differentiation was induced by culturing MSCs in the induction medium supplemented with SLF ingredients,SLF components,5-azacytidine（5-aza）,5-aza＋SLF ingredients and 5-aza＋SLF components,respectively,for up to 30 d,and evulated by the expression of Cardiac-specific myosin heavy chain（MHC） and troponin I（TnI） via immunofluoresent staining.Slow growth rate and changed morphology were observed during cardiomyocyte differentiation.After 20 d of induction,differentiating MSCs were positive for MHC and TnI staining.The effects of SLF components were better than those of SLF ingredients.Taken together,SLF can induce the differentiation of MSCs into cardiomyogenic cells in vitro,and MSCs can be used as a powerful tool for screening TCMs.

The potential role of the three-dimensional-bioprinting model in screening and developing drugs

Recently,we have read with great interest the original article used different spatial configuration models of colorectal cancer(CRC)for validating the antitumor efficacy with Diiminoquinone.We feel obliged to provide new insight into the drug screening models by integrating and analyzing the original method and result.These comments may provide comprehensive insights into threedimensional drug screening models and the difference between pathologic subtypes in CRC.

Virtual Substrates Screening Model of Triacylglycerol Lipase from Bacillus thermocatenulanatus

A reliable 3-D structure of Triacylglycerol lipase from Bacillus thermocatenulanatus was constructed by homology modeling. Under molecular dynamics simulation, it was refined and checked. The model was further used as a receptor to search binding sites and carry out flexible docking with a range of substrates, whose enzyme activities were already measured. By inputting a series of docking results, virtual substrates screening models were established and assessed. Monadic nonlinear solution demanded less data but was weak in fitting enzyme activity data with little difference; its mean absolute percentage error （MAPE） of regression was 0.67 and mean square error （MSE） was 1.73 U/mg. Both quadratic stepwise regression and BP neural network were good in regression and prediction; however, more data were required. In the cross-validation of 12 groups, overall MAPE of regression and prediction for the former were 0.18 and 0.49, while the latter was 0.55 and 0.36. MSE values for these two methods were 0.95 and 1.20 U/mg, respectively. Therefore, monadic nonlinear regression model can be used as a preliminary screening one; quadratic stepwise regression and BP neural network approach can be applied to precise screening.

Seasonal responses of monthly mean sea levels in the Bohai Sea to hydrometeorological forcing and their double screening regression models

-In this paper, the maximum entropy spectral, the cross-spectral and the frequency response analyses are madeon the basis of the data of monthly mean sea levels at coastal stations in the Bohai Sea during 1965-1986. The results show that the annual fluctuations of the monthly mean sea levels in the Bohai Sea are the results of the coupling response of seasonal variations of the marine hydrometeorological factors. Furthermore, the regression prediction equation is obtained by using the double screening stepwise regression analysis method . Through the prediction test , it is proved that the obtained results are desirable.

Mesons in the Constituent Quark Model

The quark-antiquark （q^-q） spectrum is studied by solving the Schrōdinger equation in the framework of nonrelativistic constituent quark model. An overall good fit to the experimental data of meson is obtained. The interactions between quark and antiquark consist of quadratic colour confinement-exchange, one-gluon-exchange, and Goldstone-boson-exchange potentials.

基于知识图谱的疾病筛查模型研究:以新型冠状病毒肺炎为例

目的形成一套基于机器学习等技术、面向疾病筛查的模型构建方法与路径,推进我国常见疾病、传染病的预测预防与早期干预。方法以新型冠状病毒肺炎为例,基于统计学和知识图谱理论,利用大数据和机器学习技术,提取疾病数据集的特征数据,构建基于机器学习的疾病早期筛查模型。结果对500例风险人员进行模型测试,并依据核酸检测结果评价模型的准确率,测试结果表明,模型有较高的准确率。结论研究构建的疾病筛查模型较好地解决了传统疾病筛查效率低、准确性差的瓶颈问题,实现了居民及医疗机构对疾病的早期筛查与识别,可以在不同医疗机构以及互联网端推广使用。

Progress in the development and application of plant-based antiviral agents

Plant virus disease is one of the major causes of biological disasters in agriculture worldwide. Given the complexity of transmission media and plant disease infection mechanisms, the prevention and control of plant viral diseases is a great challenge, and an efficient green pesticide is urgently needed. For this reason, when developing candidate drug leads to regulate plant viruses, pesticide experts have focused on characteristics such as low pesticide resistance, eco-friendliness, and novel mechanism. Researchers have also theoretically investigated the molecular targets of viruses infecting agricultural crops. Antiviral screening models have been constructed based on these molecular targets, and the mechanisms of commercial drugs and high-activity compounds have been extensively investigated. After screening, some compounds have been applied in the field and found to have good commercial prospects; these drugs may be used to create new green antiviral pesticides to control plant viruses. This paper reviews the screening, mode of action, development and application of recently used plant-based antiviral agents.

Screening ionic liquids for efficiently extracting perfluoroalkyl chemicals (PFACs) from wastewater

Liquid-liquid extraction(LLE)using ionic liquids(ILs)-based methods to remove perfluoroalkyl chemicals(PFACs),such as perfluorooctanoic acid(PFOA)and perfluorooctane sulfonic acid(PFOS),from wastewater,is an important strategy.However,the lack of physicochemical and LLE data limits the selection of the most suitable ILs for the extraction of PFACs.In this work,1763 ILs for PFACs extraction from water were systematically screened using COSMOtherm to estimate the infinite dilution activity coefficient(lnγ^(∞))of PFOA and PFOS in water and ILs.To evaluate the accuracy of COSMOtherm,8 ILs with various lnγ^(∞)values were selected,and their extraction efficiency(E)and distribution coefficient(D_(exp))were measured experimentally.The results showed that the predicted lnγ^(∞)decreased as the increase of experimental extraction efficiency of PFOA or PFOS,while the tendency of predicted distribution coefficient(D_(pre))was consistent with the experimental(D_(exp))results.This work provides an efficient basis for selecting ILs for the extraction of PFACs from wastewater.

Calculation and Analysis of Mean Opacity of Gold Mixtures

A screened hydrogenic model for 1 splitting （SHML） is used to calculate the Rosseland mean opacities of high-Z Au, Ta, Yb, Ho, C-d, Sm, Nd, Sn, Ag plasmas and mixtures of gold and these elements at high temperature （ T = 200 - 400 eV） and dense （ρ= 1 g/cm^3）. From the calculated Rosseland mean opacities of the mixtures, Au-Nd seems to be a better choice than other mixtures. Simultaneously, the reason that the mean opacities of mixture of Au-Sn decrease slightly when T = 400 eV is analyzed.

DUCK HEPATITIS B VIRUS MODEL FOR SCREENING OF ANTIVIRAL AGENTS FROM MEDICINAL HERBS

The effects of the extracts of 20 Chinese medicinal herbs and an antiviral drug foscarnet on duck hepatitis B virus (DHBV) endogenous DNA polymerase (DNAp) activity were compared. The extracts of P. urinaria showed a dose-dependent inhibition on DHBV DNAp. And those of other herbs showed little inhibition effect. Primary duck hepatocyte (PDH) cultures were used for evaluating effects of the extract of P. urinaria, foscarnet and acyclovir (ACV) on DHBV, and all the drugs or the extracts showed inhibition of DHBV DNA replication. Furthermore, in vivo trials were carried out. Peking ducks infected with LJ-76 strain of DHBV were treated with the extract of P. urinaria or ACV and compared with placebo treated control ducks. The treatment results in the loss or reduction of circulating viral DHBV DNA and DHBsAg.

THE ROLE OF DIPYRIDAMOLE IN PREVENTING ANGIOGENESIS IMPAIRMENT BY HOMOCYSTEINE AND ADENOSINE: A MODEL FOR SCREENING HERBAL BIOACTIVES

Herbal bioactives have been shown to influence the pathogenesis of homocysteine associated vascular complications.However,there are no simple cellular models to study their role in preventing angiogenesis impairment by homocysteine and adenosine.Using dipyridamole,an inhibitor for nucleoside transport,we examined its mechanism of action on impaired

Prioritization of risk genes in colorectal cancer by integrative analysis of multi-omics data and gene networks

Genome-wide association studies(GWASs)have identified over 140 colorectal cancer(CRC)-associated loci;however,target genes at the majority of loci and underlying molecular mechanisms are poorly understood.Here,we utilized a Bayesian approach,integrative risk gene selector(iRIGS),to prioritize risk genes at CRC GWAS loci by integrating multi-omics data.As a result,a total of 105 high-confidence risk genes(HRGs)were identified,which exhibited strong gene dependencies for CRC and enrichment in the biological processes implicated in CRC.Among the 105 HRGs,CEBPB,located at the 20q13.13 locus,acted as a transcription factor playing critical roles in cancer.Our subsequent assays indicated the tumor promoter function of CEBPB that facilitated CRC cell proliferation by regulating multiple oncogenic pathways such as MAPK,PI3K-Akt,and Ras signaling.Next,by integrating a fine-mapping analysis and three independent case-control studies in Chinese populations consisting of 8,039 cases and 12,775 controls,we elucidated that rs1810503,a putative functional variant regulating CEBPB,was associated with CRC risk(OR=0.90,95%CI=0.86–0.93,P=1.07×10^(−7)).The association between rs1810503 and CRC risk was further validated in three additional multi-ancestry populations consisting of 24,254 cases and 58,741 controls.Mechanistically,the rs1810503 A to T allele change weakened the enhancer activity in an allele-specific manner to decrease CEBPB expression via longrange promoter-enhancer interactions,mediated by the transcription factor,REST,and thus decreased CRC risk.In summary,our study provides a genetic resource and a generalizable strategy for CRC etiology investigation,and highlights the biological implications of CEBPB in CRC tumorigenesis,shedding new light on the etiology of CRC.

Prevalence of chronic kidney disease and prediabetes and associated risk factors： a community-based screening in Zhuhai, Southern China

Background The prevalence of chronic kidney disease （CKD） and prediabetes has increased in China, and at different rates in different locations. Therefore a community-based screening research was conducted in order to determine the prevalence of CKD and prediabetes, and to analyze associated risk factors of CKD and prediabetes in a city of Southern China.Methods A total of 7801 community residents aged 18 year and older from 6 communities were screened by a stratified random cluster sampling method. An estimated glomerular filtration rate （eGFR）, albuminuria, fasting plasma glucose （FPG）, and homeostatic model assessment of insulin resistance （HOMA-IR） were measured. Age-standardized prevalence was calculated by the direct method with the use of data on the population distribution in China in 2006. Multivariate logistic analysis was used to analyze the risk factors of CKD and ＂prediabetes, and association of insulin resistance （IR） with CKD and prediabetes was analyzed.Results The age-standardized prevalence of CKD was 12.5%, eGFR 〈60 ml.min^-1.1.73 m2 was 2.7% and ACR （albumin to creatinine ratio） 〉30 mg/g was 10.3%. The age-standardized prevalence of prediabetes was 12.1%. Logistic regression suggests that IR was a common independent risk factor of CKD and prediabetes. Further analysis show that HOMA-IR was increased with the aggravation of kidney injury and FPG. Conclusion CKD and prediabetes have become a major public health problem in Zhuhai, Southern China; insulin resistance may be an important risk factor.

Parametric sensitivity analysis of precipitation and temperature based on multi-uncertainty quantification methods in the Weather Research and Forecasting model

Sensitivity analysis(SA) has been widely used to screen out a small number of sensitive parameters for model outputs from all adjustable parameters in weather and climate models, helping to improve model predictions by tuning the parameters. However, most parametric SA studies have focused on a single SA method and a single model output evaluation function, which makes the screened sensitive parameters less comprehensive. In addition, qualitative SA methods are often used because simulations using complex weather and climate models are time-consuming. Unlike previous SA studies, this research has systematically evaluated the sensitivity of parameters that affect precipitation and temperature simulations in the Weather Research and Forecasting(WRF) model using both qualitative and quantitative global SA methods. In the SA studies, multiple model output evaluation functions were used to conduct various SA experiments for precipitation and temperature. The results showed that five parameters(P3, P5, P7, P10, and P16) had the greatest effect on precipitation simulation results and that two parameters(P7 and P10) had the greatest effect for temperature. Using quantitative SA, the two-way interactive effect between P7 and P10 was also found to be important, especially for precipitation. The microphysics scheme had more sensitive parameters for precipitation, and P10(the multiplier for saturated soil water content) was the most sensitive parameter for both precipitation and temperature. From the ensemble simulations, preliminary results indicated that the precipitation and temperature simulation accuracies could be improved by tuning the respective sensitive parameter values, especially for simulations of moderate and heavy rain.

Monitoring model for predicting maize grain moisture at the filling stage using NIRS and a small sample size

The change in the maize moisture content during different growth stages is an important indicator to evaluate the growth status of maize.In particular,the moisture content during the grain-filling stage reflects the grain quality and maturity and it can also be used as an important indicator for breeding and seed selection.At present,the drying method is usually used to calculate the moisture content and the dehydration rate at the grain-filling stage,however,it requires large sample size and long test time.In order to monitor the change in the moisture content at the maize grain-filling stage using small sample set,the Bootstrap re-sampling strategy-sample set partitioning based on joint x-y distances-partial least squares(Bootstrap-SPXY-PLS)moisture content monitoring model and near-infrared spectroscopy for small sample sizes of 10,20,and 50 were used.To improve the prediction accuracy of the model,the optimal number of factors of the model was determined and the comprehensive evaluation thresholds RVP(coefficient of determination(R^(2)),the root mean square error of cross-validation(RMSECV)and the root mean square error of prediction(RMSEP))was proposed for sub-model screening.The model exhibited a good performance for predicting the moisture content of the maize grain at the filling stage for small sample set.For the sample sizes of 20 and 50,the R^(2) values were greater than 0.99.The average deviations of the predicted and reference values of the model were 0.1078%,0.057%,and 0.0918%,respectively.Therefore,the model was effective for monitoring the moisture content at the grain-filling stage for a small sample size.The method is also suitable for the quantitative analysis of different concentrations using near-infrared spectroscopy and small sample size.