The Fresnel approximation in phase screen model is discussed and the coherencefunction is derived for k】】k.The application condition for Rino’s results is obtained,and it is|▽R<sub>△N<sub>e</sub>...The Fresnel approximation in phase screen model is discussed and the coherencefunction is derived for k】】k.The application condition for Rino’s results is obtained,and it is|▽R<sub>△N<sub>e</sub></sub>|/R<sub>△n<sub>e</sub></sub>【【1.展开更多
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 intrins...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.展开更多
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 fro...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.展开更多
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...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.展开更多
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 co...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.展开更多
To develop a new high-throughput screening model for human high-density lipoprotein(HDL)receptor(CD36 and LIMPⅡanalogous-1,CLA-1)agonists using CLA-1-expressing insect cells.Methods With the total RNA of human hepato...To develop a new high-throughput screening model for human high-density lipoprotein(HDL)receptor(CD36 and LIMPⅡanalogous-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.展开更多
The efficiency of particle screening was studied over a range of vibrational parameters including amplitude, frequency and vibrational direction. The Discrete Element Method (DEM) was used to simulate the screening pr...The efficiency of particle screening was studied over a range of vibrational parameters including amplitude, frequency and vibrational direction. The Discrete Element Method (DEM) was used to simulate the screening process. A functional relationship between efficiency and the parameters, both singly and combined, is established. The function is a complicated exponential. Optimal amplitude and frequency values are smaller for particles near the mesh and larger for other particles. The optimum vibration angle is 45° for nearly all kinds of particles. A transverse velocity, V⊥, was defined and V⊥=0.2 m/s was identified to be the most efficient operating point by both simulation and experimental observation. Comparison of these results with those reported by others is included.展开更多
The purpose of this study was to establish a drug screening method for small molecules extracted from traditional Chinese medicines(TCM) that have neuronal differentiation promoting effects, using P19 embryonic carcin...The purpose of this study was to establish a drug screening method for small molecules extracted from traditional Chinese medicines(TCM) that have neuronal differentiation promoting effects, using P19 embryonic carcinoma cell as a cell-based model. First, the constructed plasmid(p Tα1-Luc) was transfected into P19 cells to establish a screening model. Second, several TCMs were screened using the established model and all-trans-retinoic acid as a positive control. Finally, the underlying molecular mechanism was explored using immunofluorescence staining, q T-PCR, and Western blot analysis. Our results indicated that the drug screen model was established successfully and that both honokiol and hyperoside induced P19 differentiation into neurons, with the possible molecular mechanism being modulating the Wnt signaling pathway. In conclusion, the drug screening model developed in the present study provides a rapid, cell-based screening platform for identifying natural compounds with neuronal differentiation effects.展开更多
-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. T...-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.展开更多
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） compon...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.展开更多
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 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.展开更多
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 ...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.展开更多
It is quite common that both categorical and continuous covariates appear in the data. But, most feature screening methods for ultrahigh-dimensional classification assume the covariates are continuous. And applicable ...It is quite common that both categorical and continuous covariates appear in the data. But, most feature screening methods for ultrahigh-dimensional classification assume the covariates are continuous. And applicable feature screening method is very limited;to handle this non-trivial situation, we propose a model-free feature screening for ultrahigh-dimensional multi-classification with both categorical and continuous covariates. The proposed feature screening method will be based on Gini impurity to evaluate the prediction power of covariates. Under certain regularity conditions, it is proved that the proposed screening procedure possesses the sure screening property and ranking consistency properties. We demonstrate the finite sample performance of the proposed procedure by simulation studies and illustrate using real data analysis.展开更多
It is common for datasets to contain both categorical and continuous variables. However, many feature screening methods designed for high-dimensional classification assume that the variables are continuous. This limit...It is common for datasets to contain both categorical and continuous variables. However, many feature screening methods designed for high-dimensional classification assume that the variables are continuous. This limits the applicability of existing methods in handling this complex scenario. To address this issue, we propose a model-free feature screening approach for ultra-high-dimensional multi-classification that can handle both categorical and continuous variables. Our proposed feature screening method utilizes the Maximal Information Coefficient to assess the predictive power of the variables. By satisfying certain regularity conditions, we have proven that our screening procedure possesses the sure screening property and ranking consistency properties. To validate the effectiveness of our approach, we conduct simulation studies and provide real data analysis examples to demonstrate its performance in finite samples. In summary, our proposed method offers a solution for effectively screening features in ultra-high-dimensional datasets with a mixture of categorical and continuous covariates.展开更多
In ultra-high-dimensional data, it is common for the response variable to be multi-classified. Therefore, this paper proposes a model-free screening method for variables whose response variable is multi-classified fro...In ultra-high-dimensional data, it is common for the response variable to be multi-classified. Therefore, this paper proposes a model-free screening method for variables whose response variable is multi-classified from the point of view of introducing Jensen-Shannon divergence to measure the importance of covariates. The idea of the method is to calculate the Jensen-Shannon divergence between the conditional probability distribution of the covariates on a given response variable and the unconditional probability distribution of the covariates, and then use the probabilities of the response variables as weights to calculate the weighted Jensen-Shannon divergence, where a larger weighted Jensen-Shannon divergence means that the covariates are more important. Additionally, we also investigated an adapted version of the method, which is to measure the relationship between the covariates and the response variable using the weighted Jensen-Shannon divergence adjusted by the logarithmic factor of the number of categories when the number of categories in each covariate varies. Then, through both theoretical and simulation experiments, it was demonstrated that the proposed methods have sure screening and ranking consistency properties. Finally, the results from simulation and real-dataset experiments show that in feature screening, the proposed methods investigated are robust in performance and faster in computational speed compared with an existing method.展开更多
文摘The Fresnel approximation in phase screen model is discussed and the coherencefunction is derived for k】】k.The application condition for Rino’s results is obtained,and it is|▽R<sub>△N<sub>e</sub></sub>|/R<sub>△n<sub>e</sub></sub>【【1.
基金Fundamental Research Funds for Central Public Welfare Research Institutes(Grant No.2015PT350001)National Major Scientific and Technological Special Project for “Significant New Drugs Development”(Grant No.2015ZX09102007-009)
文摘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.
文摘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.
基金Supported by the Project of NINGBO Leading Medical Health Discipline,No.2022-B11Ningbo Natural Science Foundation,No.202003N4206Public Welfare Foundation of Ningbo,No.2021S108.
文摘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.
基金supported by the Ministry of Science and Technology of the People’s Republic of China (No.2020YFA0907500)the National Natural Science Foundation of China (Nos.22150710514,22021003,and 22106174)+1 种基金the Strategic Priority Research Program of the Chinese Academy of Sciences (No.XDPB200202)the Postdoc Science Foundation of China (No.2021M693322)。
文摘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.
基金supported by the National Natural Science Foundation of China(Grant No.39930190)Meg a-projects of Science Rescarch for the 10th Five-Year Plan(Grant No.2004AA2Z3784).
文摘To develop a new high-throughput screening model for human high-density lipoprotein(HDL)receptor(CD36 and LIMPⅡanalogous-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.
基金the Special Topic of Key Science and Technology of Fujian Province Fund (No.2006HZ0002-2)
文摘The efficiency of particle screening was studied over a range of vibrational parameters including amplitude, frequency and vibrational direction. The Discrete Element Method (DEM) was used to simulate the screening process. A functional relationship between efficiency and the parameters, both singly and combined, is established. The function is a complicated exponential. Optimal amplitude and frequency values are smaller for particles near the mesh and larger for other particles. The optimum vibration angle is 45° for nearly all kinds of particles. A transverse velocity, V⊥, was defined and V⊥=0.2 m/s was identified to be the most efficient operating point by both simulation and experimental observation. Comparison of these results with those reported by others is included.
基金supported by the China National Key Hi-Tech Innovation Project for the R&D of Novel Drugs(No.2009ZX09302)National Natural Science Foundation of China(No.81271338)the Specialized Research Fund for the Doctoral Program of Higher Education of China(No.20130096110011)
文摘The purpose of this study was to establish a drug screening method for small molecules extracted from traditional Chinese medicines(TCM) that have neuronal differentiation promoting effects, using P19 embryonic carcinoma cell as a cell-based model. First, the constructed plasmid(p Tα1-Luc) was transfected into P19 cells to establish a screening model. Second, several TCMs were screened using the established model and all-trans-retinoic acid as a positive control. Finally, the underlying molecular mechanism was explored using immunofluorescence staining, q T-PCR, and Western blot analysis. Our results indicated that the drug screen model was established successfully and that both honokiol and hyperoside induced P19 differentiation into neurons, with the possible molecular mechanism being modulating the Wnt signaling pathway. In conclusion, the drug screening model developed in the present study provides a rapid, cell-based screening platform for identifying natural compounds with neuronal differentiation effects.
文摘-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.
基金Supported by the National Eleventh Five-Year Plan of China(No.2006BA108B04-01)the National Basic Research Program of China(No.2005CB523503)
文摘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.
基金Supported by the Research Found for Doctoral Foundation of Institutions of Higher Education of China (20070385001)
文摘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.
基金CAMS Innovation Fund for Medical Sciences,No.2021-1-I2M-015National High Level Hospital Clinical Research Funding,No.2022-PUMCH-B-003.
文摘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.
文摘It is quite common that both categorical and continuous covariates appear in the data. But, most feature screening methods for ultrahigh-dimensional classification assume the covariates are continuous. And applicable feature screening method is very limited;to handle this non-trivial situation, we propose a model-free feature screening for ultrahigh-dimensional multi-classification with both categorical and continuous covariates. The proposed feature screening method will be based on Gini impurity to evaluate the prediction power of covariates. Under certain regularity conditions, it is proved that the proposed screening procedure possesses the sure screening property and ranking consistency properties. We demonstrate the finite sample performance of the proposed procedure by simulation studies and illustrate using real data analysis.
文摘It is common for datasets to contain both categorical and continuous variables. However, many feature screening methods designed for high-dimensional classification assume that the variables are continuous. This limits the applicability of existing methods in handling this complex scenario. To address this issue, we propose a model-free feature screening approach for ultra-high-dimensional multi-classification that can handle both categorical and continuous variables. Our proposed feature screening method utilizes the Maximal Information Coefficient to assess the predictive power of the variables. By satisfying certain regularity conditions, we have proven that our screening procedure possesses the sure screening property and ranking consistency properties. To validate the effectiveness of our approach, we conduct simulation studies and provide real data analysis examples to demonstrate its performance in finite samples. In summary, our proposed method offers a solution for effectively screening features in ultra-high-dimensional datasets with a mixture of categorical and continuous covariates.
文摘In ultra-high-dimensional data, it is common for the response variable to be multi-classified. Therefore, this paper proposes a model-free screening method for variables whose response variable is multi-classified from the point of view of introducing Jensen-Shannon divergence to measure the importance of covariates. The idea of the method is to calculate the Jensen-Shannon divergence between the conditional probability distribution of the covariates on a given response variable and the unconditional probability distribution of the covariates, and then use the probabilities of the response variables as weights to calculate the weighted Jensen-Shannon divergence, where a larger weighted Jensen-Shannon divergence means that the covariates are more important. Additionally, we also investigated an adapted version of the method, which is to measure the relationship between the covariates and the response variable using the weighted Jensen-Shannon divergence adjusted by the logarithmic factor of the number of categories when the number of categories in each covariate varies. Then, through both theoretical and simulation experiments, it was demonstrated that the proposed methods have sure screening and ranking consistency properties. Finally, the results from simulation and real-dataset experiments show that in feature screening, the proposed methods investigated are robust in performance and faster in computational speed compared with an existing method.
