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Ihechukwu Chinyere 《代数通讯》2018,46(4):1464-1475
This is the second of two papers in which we study a group which is the quotient of a free product of groups by the normal closure of a single word that is contained in a subgroup which has the form of a free product of two cyclic groups. We use known properties of generalized triangle groups, together with detailed analysis of pictures and of words in free monoids, to prove a number of results such as a Freiheitssatz and the existence of Mayer-Vietoris sequences for such groups under suitable hypotheses. The results generalize those in an earlier article of the second author and Shwartz. 相似文献
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Kristina Clemons Chinyere Nnaji Guido F. Verbeck 《Journal of the American Society for Mass Spectrometry》2014,25(5):705-711
Direct inject electrospray mass spectrometry offers minimal sample preparation and a “shotgun” approach to analyzing samples. However, complex matrix effects often make direct inject an undesirable sample introduction technique, particularly for trace level analytes. Highlighted here is our solution to the pitfalls of direct inject mass spectrometry and other ambient ionization methods with a focus on trace explosives. Direct analyte-probed nanoextraction coupled to nanospray ionization mass spectrometry solves selectivity issues and reduces matrix effects while maintaining minimal sample preparation requirements. With appropriate solvent conditions, most explosive residues can be analyzed with this technique regardless of the nature of the substance (i.e., nitroaromatic, oxidizing salt, or peroxide). Figure
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Ihechukwu Chinyere 《代数通讯》2018,46(3):1138-1154
In this paper and a sequel, we study a group which is the quotient of a free product of groups by the normal closure of a single word that is contained in a subgroup which has the form of a free product of two cyclic groups. We use known properties of generalized triangle groups, together with detailed analysis of pictures and of words in free monoids, to prove a number of results such as a Freiheitssatz and the existence of Mayer-Vietoris sequences for such groups under suitable hypotheses. The results generalize those in an earlier article of the second author and Shwartz. 相似文献
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Oluwafemi Adeleke Ojo Adebola Busola Ojo Charles Okolie Mary-Ann Chinyere Nwakama Matthew Iyobhebhe Ikponmwosa Owen Evbuomwan Charles Obiora Nwonuma Rotdelmwa Filibus Maimako Abayomi Emmanuel Adegboyega Odunayo Anthonia Taiwo Khalaf F. Alsharif Gaber El-Saber Batiha 《Molecules (Basel, Switzerland)》2021,26(7)
Neurodegenerative diseases, for example Alzheimer’s, are perceived as driven by hereditary, cellular, and multifaceted biochemical actions. Numerous plant products, for example flavonoids, are documented in studies for having the ability to pass the blood-brain barrier and moderate the development of such illnesses. Computer-aided drug design (CADD) has achieved importance in the drug discovery world; innovative developments in the aspects of structure identification and characterization, bio-computational science, and molecular biology have added to the preparation of new medications towards these ailments. In this study we evaluated nine flavonoid compounds identified from three medicinal plants, namely T. diversifolia, B. sapida, and I. gabonensis for their inhibitory role on acetylcholinesterase (AChE), butyrylcholinesterase (BChE) and monoamine oxidase (MAO) activity, using pharmacophore modeling, auto-QSAR prediction, and molecular studies, in comparison with standard drugs. The results indicated that the pharmacophore models produced from structures of AChE, BChE and MAO could identify the active compounds, with a recuperation rate of the actives found near 100% in the complete ranked decoy database. Moreso, the robustness of the virtual screening method was accessed by well-established methods including enrichment factor (EF), receiver operating characteristic curve (ROC), Boltzmann-enhanced discrimination of receiver operating characteristic (BEDROC), and area under accumulation curve (AUAC). Most notably, the compounds’ pIC50 values were predicted by a machine learning-based model generated by the AutoQSAR algorithm. The generated model was validated to affirm its predictive model. The best models achieved for AChE, BChE and MAO were models kpls_radial_17 (R2 = 0.86 and Q2 = 0.73), pls_38 (R2 = 0.77 and Q2 = 0.72), kpls_desc_44 (R2 = 0.81 and Q2 = 0.81) and these externally validated models were utilized to predict the bioactivities of the lead compounds. The binding affinity results of the ligands against the three selected targets revealed that luteolin displayed the highest affinity score of −9.60 kcal/mol, closely followed by apigenin and ellagic acid with docking scores of −9.60 and −9.53 kcal/mol, respectively. The least binding affinity was attained by gallic acid (−6.30 kcal/mol). The docking scores of our standards were −10.40 and −7.93 kcal/mol for donepezil and galanthamine, respectively. The toxicity prediction revealed that none of the flavonoids presented toxicity and they all had good absorption parameters for the analyzed targets. Hence, these compounds can be considered as likely leads for drug improvement against the same. 相似文献
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