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  • Bentham Science Publishers Ltd.  (15)
  • Chen, Qin  (15)
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  • Bentham Science Publishers Ltd.  (15)
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  • 1
    Online Resource
    Online Resource
    Dairy Safety Prediction Based on Machine Learning Combined with Chemicals
    Bentham Science Publishers Ltd. ; 2020
    In:  Medicinal Chemistry Vol. 16, No. 5 ( 2020-08-07), p. 664-676
    Details
    In: Medicinal Chemistry, Bentham Science Publishers Ltd., Vol. 16, No. 5 ( 2020-08-07), p. 664-676
    Abstract: Dairy safety has caused widespread concern in society. Unsafe dairy products have threatened people's health and lives. In order to improve the safety of dairy products and effectively prevent the occurrence of dairy insecurity, countries have established different prevention and control measures and safety warnings. Objective: The purpose of this study is to establish a dairy safety prediction model based on machine learning to determine whether the dairy products are qualified. Methods: The 34 common items in the dairy sampling inspection were used as features in this study. Feature selection was performed on the data to obtain a better subset of features, and different algorithms were applied to construct the classification model. Results: The results show that the prediction model constructed by using a subset of features including “total plate”, “water” and “nitrate” is superior. The SN, SP and ACC of the model were 62.50%, 91.67% and 72.22%, respectively. It was found that the accuracy of the model established by the integrated algorithm is higher than that by the non-integrated algorithm. Conclusion: This study provides a new method for assessing dairy safety. It helps to improve the quality of dairy products, ensure the safety of dairy products, and reduce the risk of dairy safety.
    Type of Medium: Online Resource
    ISSN: 1573-4064
    URL: Article
    DOI: 10.2174/1573406415666191004142810
    Language: English
    Publisher: Bentham Science Publishers Ltd.
    Publication Date: 2020
    SSG: 15,3
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  • 2
    Online Resource
    Online Resource
    Cordycepin Exerts Neuroprotective Effects via an Anti-Apoptotic Mechanism based on the Mitochondrial Pathway in a Rotenone-Induced Parkinsonism Rat Model
    Bentham Science Publishers Ltd. ; 2019
    In:  CNS & Neurological Disorders - Drug Targets Vol. 18, No. 8 ( 2019-12-30), p. 609-620
    Details
    In: CNS & Neurological Disorders - Drug Targets, Bentham Science Publishers Ltd., Vol. 18, No. 8 ( 2019-12-30), p. 609-620
    Abstract: Cordycepin (Cor), one of the major bioactive components of the traditional Chinese medicine Cordyceps militaris, has been used in clinical practice for several years. However, its neuroprotective effect remains unknown. Aim: The purpose of the study was to evaluate the neuroprotective effects of Cor using a rotenoneinduced Parkinson’s Disease (PD) rat model and to delineate the possible associated molecular mechanisms. Methods: In vivo, behavioural tests were performed based on the 10-point scale and grid tests. Levels of dopamine and its metabolites in the striatum and the numbers of TH-positive neurons in the Substantia Nigra pars compacta (SNpc) were investigated by high-performance liquid chromatography with electrochemical detection and immunohistochemical staining, respectively. In vitro, cell apoptosis rates and Mitochondrial Membrane Potential (MMP) were analysed by flow cytometry and the mRNA and protein levels of Bax, Bcl-2, Bcl-xL, Cytochrome c (Cyt-c), and caspase-3 were determined by quantitative real-time PCR and western blotting. Results: Showed that Cor significantly improved dyskinesia, increased the numbers of TH-positive neurons in the SNpc, and maintained levels of dopamine and its metabolites in the striatum in rotenone- induced PD rats. We also found that apoptosis was suppressed and the loss of MMP was reversed with Cor treatment. Furthermore, Cor markedly down-regulated the expression of Bax, upregulated Bcl-2 and Bcl-xL, inhibited the activation of caspase-3, and decreased the release of Cyt-c from the mitochondria to the cytoplasm, as compared to those in the rotenone-treated group. Conclusion: Therefore, Cor protected dopamine neurons against rotenone-induced apoptosis by improving mitochondrial dysfunction in a PD model, demonstrating its therapeutic potential for this disease.
    Type of Medium: Online Resource
    ISSN: 1871-5273
    URL: Article
    DOI: 10.2174/1871527318666190905152138
    Language: English
    Publisher: Bentham Science Publishers Ltd.
    Publication Date: 2019
    SSG: 15,3
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    Online Resource
  • 3
    Online Resource
    Online Resource
    An Epidemic Avian Influenza Prediction Model Based on Google Trends
    Bentham Science Publishers Ltd. ; 2019
    In:  Letters in Organic Chemistry Vol. 16, No. 4 ( 2019-03-20), p. 303-310
    Details
    In: Letters in Organic Chemistry, Bentham Science Publishers Ltd., Vol. 16, No. 4 ( 2019-03-20), p. 303-310
    Abstract: The occurrence of epidemic avian influenza (EAI) not only hinders the development of a country & #039;s agricultural economy, but also seriously affects human beings’ life. Recently, the information collected from Google Trends has been increasingly used to predict various epidemics. In this study, using the relevant keywords in Google Trends as well as the multiple linear regression approach, a model was developed to predict the occurrence of epidemic avian influenza. It was demonstrated by rigorous cross-validations that the success rates achieved by the new model were quite high, indicating the predictor will become a very useful tool for hospitals and health providers.
    Type of Medium: Online Resource
    ISSN: 1570-1786
    URL: Article
    DOI: 10.2174/1570178615666180724103325
    Language: English
    Publisher: Bentham Science Publishers Ltd.
    Publication Date: 2019
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  • 4
    Online Resource
    Online Resource
    Recent Advances of Terahertz Imaging Technologies
    Bentham Science Publishers Ltd. ; 2012
    In:  Recent Patents on Signal Processing Vol. 2, No. 1 ( 2012-03-09), p. 4-11
    Details
    In: Recent Patents on Signal Processing, Bentham Science Publishers Ltd., Vol. 2, No. 1 ( 2012-03-09), p. 4-11
    Type of Medium: Online Resource
    ISSN: 1877-6124
    URL: Article
    DOI: 10.2174/1877612411202010004
    Language: English
    Publisher: Bentham Science Publishers Ltd.
    Publication Date: 2012
    detail.hit.zdb_id: 2618748-6
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  • 5
    Online Resource
    Online Resource
    Recent Advances of Terahertz Imaging Technologies
    Bentham Science Publishers Ltd. ; 2012
    In:  Recent Patents on Signal Processinge Vol. 2, No. 1 ( 2012-04-01), p. 4-11
    Details
    In: Recent Patents on Signal Processinge, Bentham Science Publishers Ltd., Vol. 2, No. 1 ( 2012-04-01), p. 4-11
    Type of Medium: Online Resource
    ISSN: 2210-6863
    URL: Article
    DOI: 10.2174/2210686311202010004
    Language: English
    Publisher: Bentham Science Publishers Ltd.
    Publication Date: 2012
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  • 6
    Online Resource
    Online Resource
    A Study of the Mechanism of Binding between Neratinib and MAD2L1 Based on Molecular Simulation and Multi-spectroscopy Methods
    Bentham Science Publishers Ltd. ; 2020
    In:  Current Pharmaceutical Design Vol. 25, No. 40 ( 2020-01-01), p. 4287-4295
    Details
    In: Current Pharmaceutical Design, Bentham Science Publishers Ltd., Vol. 25, No. 40 ( 2020-01-01), p. 4287-4295
    Abstract: Nilatinib is an irreversible tyrosine kinase inhibitor, which is used in the treatment of some kinds of cancer. To study the interaction between Neratinib and MAD2L1, a potential tumor target, is of guiding significance for enriching the medicinal value of Neratinib. Method: The binding mechanism between Mitotic arrest deficient 2-like protein 1 (MAD2L1) and Neratinib under simulative physiological conditions was investigated by molecule simulation and multi-spectroscopy approaches. Results: Molecular docking showed the most possible binding mode of Neratinib-MAD2L1 and the potential binding sites and interaction forces of the interaction between MAD2L1 and Neratinib. Fluorescence spectroscopy experiments manifested that Neratinib could interact with MAD2L1 and form a complex by hydrogen bond and van der Waals interaction. These results were consistent with the conclusions obtained from molecular docking. In addition, according to Synchronous fluorescence and three-dimensional fluorescence results, Neratinib might lead to the conformational change of MAD2L1, which may affect the biological functions of MAD2L1. Conclusion: This study indicated that Neratinib could interact with MAD2L1 and lead to the conformational change of MAD2L1. These works provide helpful insights for the further study of biological function of MAD2L1 and novel pharmacological utility of Neratinib.
    Type of Medium: Online Resource
    ISSN: 1381-6128
    URL: Article
    DOI: 10.2174/1381612825666191107102413
    Language: English
    Publisher: Bentham Science Publishers Ltd.
    Publication Date: 2020
    SSG: 15,3
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  • 7
    Online Resource
    Online Resource
    CD28: A New Drug Target for Immune Disease
    Bentham Science Publishers Ltd. ; 2020
    In:  Current Drug Targets Vol. 21, No. 6 ( 2020-04-24), p. 589-598
    Details
    In: Current Drug Targets, Bentham Science Publishers Ltd., Vol. 21, No. 6 ( 2020-04-24), p. 589-598
    Abstract: CD28, a cell surface glycoprotein receptor, predominantly expressed on activated T cells, belongs to the Ig superfamily and provides a critical co-stimulatory signal. CTLA-4 has sequence homology to CD28, and is expressed on T cells after activation. It provides an inhibition signal coordinated with CD28 to regulate T cell activation. Both of them regulate T cell proliferation and differentiation and play an important role in the immune response pathway in vivo. Objective: We studied the special role of different structural sites of CD28 in producing costimulatory signals. Methods: We reviewed the relevant literature, mainly regarding the structure of CD28 to clarify its biological function, and its role in the immune response. Results: In recent years, increasingly attention has been paid to CD28, which is considered as a key therapeutic target for many modern diseases, especially some immune diseases. Conclusion: In this paper, we mainly introduce the structure of CD28 and its related biological functions, as well as the application of costimulatory pathways targeting CD28 in disease treatment.
    Type of Medium: Online Resource
    ISSN: 1389-4501
    URL: Article
    DOI: 10.2174/1389450120666191114102830
    Language: English
    Publisher: Bentham Science Publishers Ltd.
    Publication Date: 2020
    SSG: 15,3
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  • 8
    Online Resource
    Online Resource
    Identify Compounds' Target Against Alzheimer's Disease Based on In-Silico Approach
    Bentham Science Publishers Ltd. ; 2019
    In:  Current Alzheimer Research Vol. 16, No. 3 ( 2019-03-27), p. 193-208
    Details
    In: Current Alzheimer Research, Bentham Science Publishers Ltd., Vol. 16, No. 3 ( 2019-03-27), p. 193-208
    Abstract: Alzheimer's disease swept every corner of the globe and the number of patients worldwide has been rising. At present, there are as many as 30 million people with Alzheimer's disease in the world, and it is expected to exceed 80 million people by 2050. Consequently, the study of Alzheimer’s drugs has become one of the most popular medical topics. Methods: In this study, in order to build a predicting model for Alzheimer’s drugs and targets, the attribute discriminators CfsSubsetEval, ConsistencySubsetEval and FilteredSubsetEval are combined with search methods such as BestFirst, GeneticSearch and Greedystepwise to filter the molecular descriptors. Then the machine learning algorithms such as BayesNet, SVM, KNN and C4.5 are used to construct the 2D-Structure Activity Relationship(2D-SAR) model. Its modeling results are utilized for Receiver Operating Characteristic curve(ROC) analysis. Results: The prediction rates of correctness using Randomforest for AChE, BChE, MAO-B, BACE1, Tau protein and Non-inhibitor are 77.0%, 79.1%, 100.0%, 94.2%, 93.2% and 94.9%, respectively, which are overwhelming as compared to those of BayesNet, BP, SVM, KNN, AdaBoost and C4.5. Conclusion: In this paper, we conclude that Random Forest is the best learner model for the prediction of Alzheimer’s drugs and targets. Besides, we set up an online server to predict whether a small molecule is the inhibitor of Alzheimer's target at http://47.106.158.30:8080/AD/. Furthermore, it can distinguish the target protein of a small molecule.
    Type of Medium: Online Resource
    ISSN: 1567-2050
    URL: Article
    DOI: 10.2174/1567205016666190103154855
    Language: English
    Publisher: Bentham Science Publishers Ltd.
    Publication Date: 2019
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  • 9
    Online Resource
    Online Resource
    Advances in Antidiabetic Drugs Targeting Insulin Secretion
    Bentham Science Publishers Ltd. ; 2019
    In:  Current Pharmaceutical Design Vol. 24, No. 34 ( 2019-01-22), p. 3990-3997
    Details
    In: Current Pharmaceutical Design, Bentham Science Publishers Ltd., Vol. 24, No. 34 ( 2019-01-22), p. 3990-3997
    Abstract: Diabetes mellitus (DM) is a disease of systemic metabolic disorders caused by the decrease of secretion or sensitivity of insulin. In recent years, the study of insulin-related drug targets and the development of new drugs have become the popular topic of current medical research, and studies have shown that multiple signaling pathways are associated with diabetes treatment. At present, some new drugs based on the new target design have been listed on the market and have achieved good hypoglycemic effect. However, most of the drugs are still in the clinical or pre-clinical stage. The efficacy and safety of the drugs need further clinical validation. Objective: This article will introduce the advancements of targets and drugs to promote insulin secretion.
    Type of Medium: Online Resource
    ISSN: 1381-6128
    URL: Article
    DOI: 10.2174/1381612824666181112113756
    Language: English
    Publisher: Bentham Science Publishers Ltd.
    Publication Date: 2019
    SSG: 15,3
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  • 10
    Online Resource
    Online Resource
    Gene Therapy for Parkinsons Disease: Progress and Challenges
    Bentham Science Publishers Ltd. ; 2005
    In:  Current Gene Therapy Vol. 5, No. 1 ( 2005-02-01), p. 71-80
    Details
    In: Current Gene Therapy, Bentham Science Publishers Ltd., Vol. 5, No. 1 ( 2005-02-01), p. 71-80
    Type of Medium: Online Resource
    ISSN: 1566-5232
    URL: Article
    DOI: 10.2174/1566523052997505
    Language: English
    Publisher: Bentham Science Publishers Ltd.
    Publication Date: 2005
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