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| 1 | Modeling and optimization of Terminalia catappa L.kernel oil extraction using response surface methodology and artificial neural network显示文摘In this study,response surface methodology(RSM)and artificial neural network(ANN)were used to optimize Terminalia catappa L.kernel oil(TCKO)yield.Solvent extraction method was used for the oil extraction,with n-hexane as the extracting solvent.The highest oil yield was obtained at 55℃,150 min,and 0.5 mm.The physicochemical properties of the TCKO were determined using standard methods.Gas chromatographic(GC)analysis and Fourier Transform Infrared(FTIR)were respectively,used to determine the fatty acid composition and prevalent functional groups in TCKO.At optimum conditions of temperature,particle size and extraction time,the RSM predicted oil yield was 62.92%,which was validated as 60.34%,whereas ANN predicted yield was 60.39%,which was validated as 60.40%.The results of the physicochemical characterization of TCKO showed that the dielectric strength(DS),viscosity,flash and pour points values were 30.61 KV,20.29 mm^2 s^−1,260°C,and 3℃,respectively.Physicochemical characterization and FTIR results of TCKOindicated its potential industrial application,especially as transformer fluid.Fatty acids compositions result indicated that the oil was highly unsaturated;while XRD results of Terminalia catappa L.kernel(TCK)samples obtained,both before and after extraction,showed difference in their peaks and corresponding intensities,due to the damage effect of solvent.Finally,the obtained optimization results indicated that ANN was a better and more effective tool than RSM,due to its higher R^2 and lower RMS values. | Chinedu Matthew Agu Matthew Chukwudi Menkiti Ekwe Bassey Ekwe Albert Chibuzor Agulanna | 2020 | Artificial Intelligence in Agriculture2020，，1： | 3 |
| 2 | Immunohistochemical and molecular subtypes of breast cancer in Nigeria显示文摘 | Clement A. Adebamowo Ayotunde Famooto Temidayo O. Ogundiran Toyin Aniagwu Chibuzor Nkwodimmah Effiong E. Akang | 2008 | Breast Cancer Research and Treatment2008，，1： | 1 |
| 3 | Up-regulation of oxidative stress and inflammation in the brain of albino wistar rats following sub-acute administration of Synclisia scabrida root extract显示文摘Objective: Synclisia scabrida is a medicinal plant used over the years for the treatment ofseveral medical conditions yet there is paucity of information on its systemic and organspecific toxicity. Consequently, sub-acute neurotoxicity of root extract of Synclisia scabridawas evaluated in albino Wistar rats. Methods: Thirty male albino rats with average weightof 140g were randomized into 5 groups consisting of 6 rats in each group. Group 1 was thecontrol while 50 mg/kg, 100 mg/kg, 200 mg/kg and 400 mg/kg of the root extract wereadministered to Groups 2, 3, 4 and 5 respectively for 28 days. Malondialdehyde,glutathione, nitric oxide, protein, tumour necrosis factor-α, acetylcholine, catalase andacetylcholinesterase levels were measured in brain homogenates. Body weight of theanimals and histology of the hippocampus and cerebral cortex were evaluated. Results:Root extract of Synclisia scabrida was observed to increase malondialdehyde concentrationand decrease antioxidants biomarkers when compared with the control. Significantly(p<0.05) increased TNF-α concentration and acetylcholinesterase activity caused by theextract when compared with the control was observed. The concentration of acetylcholinesignificantly decreased in Synclisia scabrida treated groups in comparison with the control.The histomorphology of the hippocampus and cerebral cortex revealed pyknotic pyramidalneurons in Synclisia scabrida treated rat relative to the control with normal pyramidalneurons. The body weight of the extract treated groups were significantly decreased whencompared to the control Group. Conclusion: The study has demonstrated that the rootextract of Synclisia scabrida induces and up-regulates oxidative stress and inflammation inthe brain of male albino Wistar rat coupled with reduced acetylcholine concentration hencethe extract possesses neurotoxic potentials. | Emmanuel Uchechukwu Modo Ijeoma Nina Eke Utibe Evans Bassey Anthony Chibuzor Nnamudi Ekam Ime Akpakpan Okon Effiom Etim Iheanyichukwu Wopara Prosper Great Legborsi | 2022 | TMR Integrative Medicine2022，6，30： | 0 |
| 4 | A Systematic Review on Antituberculosis Drug Discovery and Antimycobacterial Potential of Biologically Synthesized Silver Nanoparticles:Overview and Future Perspectives显示文摘Rapid emergence and quick evolution of drug-resistant and aggressive mycobacterial strains have resulted in the present antimycobacterial drug crisis and the persistence of tuberculosis as a major public health problem.Green/biological nanotechnologies constitute an interesting area of research for discovering antimycobacterial agents.This review focused on the biological(green)synthesis of silver nanoparticles(AgNPs)as an alternative source of antimycobacterial agents.Data for this study were searched and screened from three electronic databases(Google Scholar,PubMed and ScienceDirect)following the Preferred Reporting Items for Systematic Reviews and Meta-analyses flowchart.Data from in total 17 eligible studieswere reported in this systematic review.Twelve of the 17 studies used plants to fabricate AgNPs,whereas the remaining five studies used microorganisms(bacteria and/or fungi).Silver as part of silver nitrate(AgNO3)was themetal precursor reported for the synthesis of AgNPs in these studies.Silver nanoparticles were mostly spherical,with sizes ranging from12 to140nm.Resultsbasedon minimum inhibitory concentrations varied between studies and were divided into three groups:(i)those more effective than the antibiotic(controls),(ii)those more effective than plant extracts,and(iii)those less effective than the antibiotic controls.In addition,little or no cytotoxicity effects were reported.Silver nanoparticles were also shown to be highly specific or selective toward mycobacterial strains.This systematic review highlights the antimycobacterial potential of biologically synthesized AgNPs,underscoring the possibility of discovering/developing new antimycobacterial agents using biological synthesis approaches with less toxicity and high selectivity. | Christian K.Ezeh Chibuzor N.Eze Uju M.E.Dibua Stephen C.Emencheta | 2022 | Infectious Microbes & Diseases2022，4，4： | 0 |
| 5 | Formulation of Domperidone Microspheres Using a Combination of Locally Extracted Chitosan and Hpmc as Polymers显示文摘 | Stephen Olaribigbe Majekodunmi Cynthia Chibuzor Uzoaganobi | 2017 | Journal of Chemistry and Chemical Engineering2017，11，2： | 0 |
| 6 | Survey on solidwastesmanagement by composting: Optimization of key process parameters for biofertilizer synthesis from agro wastes using response surface methodology (RSM)显示文摘The optimization of key process parameters for the transformation of agrowastes into biofertilizer has been demonstrated using response surface methodology(RSM).Biofertilizerwas produced by composting using 120 L capacity drum made of polyethylene as the composter.Composting time(X1),dosage ratio(X2)and moisture content(X3)were the independent factors while percentage nitrogen,phosphorus and potassium(N.P.K)were the response factors.The outcomes exhibited that composting time,dosage ratio and moisture content all significantly affects the mineralization of N.P.K at probability value of 0.0001.The coefficients of determination also called regression coefficients of 98.60%,99.79%and 97.80%for nitrogen,phosphorus and potassiumobserved between the predicted and the real value are obvious that the developed regression models can fit the experimental data well.It was seen from the optimization studies that the pinnacle value of N.P.K from the ideal conditions are 9.62%,8.97%and 5.62.Characterization of the composite uncovered that biofertilizer produced has a high potential for commercial application on agricultural land.It can be concluded that combination of sawdust,sewage sludge and vegetable waste is a good mixture for biofertilizer synthesis.Also,the nutrients release by the compost materials during the process of composting may be maximized when process conditions are circumspectly managed within the reported optimal value. | Christian O.Asadu Samuel O.Egbuna Thompson O.Chime Chibuzor N.Eze Dibia Kevin Gordian O.Mbah Anthony C.Ezema | 2019 | Artificial Intelligence in Agriculture2019，，3： | 0 |
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