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Journal Article
Olaniran, O, F.C. A, Omoya FO, Odediran S, R.E. H-olajokun, A. A, Odetoyin B, I.O. A, Oyetoke O, and D.O..  2016.  Antibacterial, {{Haematological Parameters}} and {{Phytochemical Analysis}} of the {{Leaf Extracts}} of {{Moringa Oleifera}}, dec. International Journal of clinical pathology. 3:3–5. Abstract

Antimicrobial resistance has become a global problem and Strategies to improve the current situation necessitate finding new and innovative antimicrobial agents. Forty apparently healthy albino mice of either sex, weighing between 19kg and 27kg, aged 2 to 3 weeks were purchased and the various concentration of the extracts from Moringa oleifera leaves were given orally to the mice, the highest mean PCV was recorded in 800mg (33.0{$\pm$}1.22), White blood cell count 400mg (3,725{$\pm$}923.20), Neutrophil count100mg (24.8{$\pm$}7{$\pm$}.65) and lymphocytes count 400mg (87.5{$\pm$}1.85), ethanol extracts had PCV to be highest in 200mg, White Blood Cell WBC 100mg (14,000{$\pm$}9453.4), neutrophils count 400mg(12.8{$\pm$}2.02) and lymphocytes count 800mg (91.5{$\pm$}2.22), the antimicrobial activity of the extracts on clinical isolates showed that the water extract 800mg/ml had the highest zone of inhibition of 6mm on the Escherichia coli, 19mm against Staphylococcus aureus, 18mm against Proteus mirabilis and 14mm against Escherichia coli, the ethanol extracts 800mg/ml had the highest zone of inhibition of 8mm against Salmonella typhii. 6mm against E.coli and S.aureus and 5mm against P. mirabilis, The phytochemical screening showed that both water and ethanol extracts had Flavonoid, Tannin, Glycoside, Terpenoid and Saponin with the absence of alkaloids in water, while reducing sugar was absent in both with Terpenoid having the highest concentrations in ethanol extracts 12.95mg/g and water extracts10.30mg/g.

L.J.J, G, W.L A, M E, P.A M, T B, B A, P D, F.K.N A, S.A B, A M, M L, E.A A-A, W D, P T, O J, M D, P A, A.A O, R B, G P-R, M G, S O-Y, G.O O, P.B O, L A-R, F A, T H, P G, M.O O, C.J B, M.L M, A.A A, J.C M, A B.  2016.  Association studies and direct DNA sequencing implicate genetic susceptibility loci in the etiology of nonsyndromic orofacial clefts in sub-Saharan African populations. J Dental Research. 95(11):1245-1256.
EJ, L, H L, JC C, JR S, E F, G W, CA L, D J, CC L, Doheny KF, T MH, J R, C S, J J, B E, AR V, K N, J S, AE C, F D, K C, RG M, RT L, RT L, A W, PA R, LL F, CD P, la EMC C-de P, AC L, LC V-R, AM L-P, DR V, M A-B, EE C, JC M, FA P, IM O, FM C, JT H, SH B, CJ B´, A B, PA M, WL A, O J, Braimah RO, BS A, MA E, M D, M K, F S, L M, de J E´quez S, SM W, L M, RA C, JC M, ML M.  2016.  A genome-wide association study of nonsyndromic cleft palate identifies an etiologic missense variant in GRHL3. . Am J Hum Genet. 98:744–754.
E.J, L, H L, J.C C, J.R S, E F, G W, C.A L, D J, C.C L, K.F D, T MH, J R, C S, J J, B E, A.R V, K N, A.C L, L.C V-R, A.M L-P, D.R V, M A-B, A.E C, L.L F, C.D P, la E.M.C C-de P, F D, K C, R.G M, R.T L, A W, P.A R, E.E C, J.C M, F.A P, I.M O, F.M C, J.T H, S.H B, C.J B´, A B, P.A M, W.L A, O J, R.O B, B.S A, M.A E, F A, M K, F S, L M, de J E´quez S, S.M W, L M, J.C M, M.L M.  2016.  A multi-ethnic genome-wide association study identifies novel loci for non-syndromic cleft lip with or without cleft palate on 2p24.2, 17q23 and 19q13. Human Molecular Genetics. 25(13):2862-2872.
R.O, B, K.C N, F.J O, S.B A.  2016.  Oral Health Related Quality of Life (OHRQoL) following third molar surgery in Sub-Saharan Africans; an observational study. Pan African Medical Journal. 25:97-102.
Vidya, KM, Rao UK, Nittayananta W, Liu H, Owotade FJ.  2016.  Oral mycoses and other opportunistic infections in HIV: therapy and emerging problems - a workshop report. Oral Diseases. 22(1):158-165.
Sartelli, M, Weber DG, Ruppé E, Bassetti M, Wright BJ, Ansaloni L, Catena F, Coccolini F, Abu-Zidan FM, Coimbra R, others.  2016.  Antimicrobials: a global alliance for optimizing their rational use in intra-abdominal infections (AGORA). World journal of emergency surgery. 11:1–32., Number 1: Springer Abstract
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Adeoye, AA, Udoh JE, Rotimi EA, Ikeobi CON, Adebambo OA.  2015.  HAEMATOLOGY AND SERUM BIOCHEMISTRY OF F AND F PIGS PRODUCED BY 1 2 ASF- RECOVERED PIGS. Ife Journal of Science. 17(2)adeoye_et_al_5.pdf
Bolaji, OS, Ixang PA, Oladosu OR, Koya F, Fayose RS, Rabiu BA.  2015.  Ionospheric time-delay over Akure using global positioning system observations. Acta Geophysica. 60(3):884-899.
A, B, P M, N T, W A, M E, C M, R A, C O, P A, O O, A A, H O, B A, R B, A O, I O, E A, P O, L A-R, A A.  2015.  Multidisciplinary approach to genomic research in Africa: the AfriCRAN model. . Pan African Medical Journal . 21(229):1-5.
Isadare, D, Adeoye M, Adetunji A, Oluwasegun K, Rominiyi A, Akinluwade K.  2015.  Effect of as-cast cooling on the microstructure and mechanical properties of agehardened 7000 series aluminium alloy. International Journal of Materials Engineering. 5:5–9. Abstract
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Olakanmi, OO, Ojone OM, Seun AO, Adeyemi ID, Joseph AK, Taofeek TA, Abel OO, Rasaki AA.  2015.  A Microcontroller-based Design for Energy Efficient Nickel-chrome Plating Process. American Chemical Science Journal. Abstract
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Ranti, OS, Kayode TH, Olorunniwo OE, Atanda PO, Aramide FO.  2015.  Production and Characterization of Clay Bonded Carbon Refractory from Ifon Clay and Spent Graphite Electrode. International Journal of Metallurgical Engineering. 4:33–39., Number 2: Scientific & Academic Publishing Abstract
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Gabriel-Ajobiewe, R, RAO, Cyril-Olutayo M, Olumekun V, FJ A.  2014.  Effect of Bambusa tuldoides cv. ventricosa leaf extracted with fermented steep liquors of maize and sorghum on some pathogenic organisms, 12. Malaysian Journal of Microbiology. 10:280-289. Abstract
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A, B, P M, W A, M E, L G, R B, B A, J R, C E, J O, O O, A L, F A, T H, I M, P G, M D, M G, A A, M M, J M.  2014.  Rare functional variants in genome-wide association identified candidate genes for nonsyndromic clefts in the African population.. Am J Med Genet A. 164A(10):2567-2571.
Siccardi, M, Rajoli RKR, Curley P, Olagunju A, Moss D, Owen A.  2013.  Physiologically based pharmacokinetic models for the optimization of antiretroviral therapy: recent progress and future perspective, 2013. Future Virology. 8(9):871-890.: Future Medicine AbstractWebsite

Anti-HIV therapy is characterized by the chronic administration of antiretrovirals (ARVs), and consequently, several problems can arise during the management of HIV-positive patients. ARV disposition can be simulated by combining system data describing a population of patients and in vitro drug data through physiologically based pharmacokinetic (PBPK) models, which mathematically describe absorption, distribution, metabolism and elimination. PBPK modeling can find application in the investigation of clinically relevant scenarios, while providing the opportunity for a better understanding of the mechanisms regulating drug distribution. In this review, we have analyzed the most recent applications of PBPK models for ARVs and highlighted some of the most interesting areas of use, such as drug–drug interaction, pharmacogenetics, factors regulating absorption and tissue penetration, as well as therapy optimization in special populations. The application of the PBPK modeling approach might not be limited to the investigation of hypothetical clinical issues, but could be used to inform future prospective clinical trials.

Rengasamy, KR, Aderogba M, Amoo S, Stirk W, van Staden J.  2013.  Potential antiradical and alpha-glucosidase inhibitors from Ecklonia maxima (Osbeck) Papenfuss, 11. Food chemistry. 141:1412-5. Abstract
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Adebajo, A, Odediran S, Nneji C, Iwalewa E, Rukunga G, Aladesanmi A, Gathirwa J, Ademowo O, Olugbade T, Schmidt T, Verspohl E.  2013.  Evaluation of Ethnomedical Claims II: Antimalarial Activities of Gongronema latifolium Root and Stem, 04. Journal of Herbs. 19 Abstract
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Haire, B, Folayan MO, Hankins C, Sugarman J, McCormack S, Ramjee G, Warren M.  2013.  Ethical considerations in determining standard of prevention packages for HIV prevention trials: Examining PrEP. Developing World Bioethics . 13(2):87-94doi:10.1111/dewb.12032..
Adebajo, AC, Odediran SA, Nneji CM, Iwalewa EO, Rukunga GM, Aladesanmi AJ, Gathirwa JW, Ademowo OG, Olugbade TA, Schmidt TJ, Verspohl EJ.  2013.  Evaluation of Ethnomedical Claims II: Antimalarial Activities of Gongronema latifolium Root and Stem. Journal of Herbs, Spices & Medicinal Plants. 19(2):97-118., Number 2: Taylor & Francis AbstractWebsite

Methanolic extract and chromatographic fractions of Gongronema latifolium were tested against clinical isolates of Plasmodium falciparum-, P. yoelii nigeriensis-infected mice, chloroquine-sensitive (D6) and chloroquine-resistant (W2) P. falciparum clones. The isolates, characterized as a 1:1 mixture of α-amyrin and β-amyrin cinnamates (1a/1b), lupenyl cinnamate (2) and lupenyl acetate (3), were assayed using the clones. Extract, most active vacuum liquid and column chromatographic fractions had respective ED50 values of 120.85, 32.03, 25.62 mg.kg-1 and IC50 of 36.27, 9.45, 7.05 μg.mL-1, against W2 clones. Lupenyl acetate had 18.96 μg.mL-1, indicating synergistic action of the constituents. Results justified its ethnomedical use for treating malaria.

Ramos-Gomez, F, Folayan MO.  2013.  Oral health considerations in HIV-infected children . Curr HIV/AIDS Rep. :10.1007/s11904-013-0163-y.
Siccardi, M, Rajoli RKR, Curley P, Olagunju A, Moss D, Owen A.  2013.  Physiologically based pharmacokinetic models for the optimization of antiretroviral therapy: recent progress and future perspectives. Future Virology. 8(9):871-90. Abstract

Anti-HIV therapy is characterized by the chronic administration of antiretrovirals (ARVs), and consequently, several problems can arise during the management of HIV-positive patients. ARV disposition can be simulated by combining system data describing a population of patients and in vitro drug data through physiologically based pharmacokinetic (PBPK) models, which mathematically describe absorption, distribution, metabolism and elimination. PBPK modeling can find application in the investigation of clinically relevant scenarios, while providing the opportunity for a better understanding of the mechanisms regulating drug distribution. In this review, we have analyzed the most recent applications of PBPK models for ARVs and highlighted some of the most interesting areas of use, such as drug–drug interaction, pharmacogenetics, factors regulating absorption and tissue penetration, as well as therapy optimization in special populations. The application of the PBPK modeling approach might not be limited to the investigation of hypothetical clinical issues, but could be used to inform future prospective clinical trials.

Siccardi, M, Olagunju A, Seden K, Ebrahimjee F, Rannard S, Back D, Owen A.  2013.  Use of a physiologically-based pharmacokinetic model to simulate artemether dose adjustment for overcoming the drug-drug interaction with efavirenz. In Silico Pharmacology. 1:4 doi:10.1186/2193-9616-1-4(1:4) AbstractIn Silico Pharmacology website

Purpose

To treat malaria, HIV-infected patients normally receive artemether (80 mg twice daily) concurrently with antiretroviral therapy and drug-drug interactions can potentially occur. Artemether is a substrate of CYP3A4 and CYP2B6, antiretrovirals such as efavirenz induce these enzymes and have the potential to reduce artemether pharmacokinetic exposure. The aim of this study was to develop an in vitro in vivo extrapolation (IVIVE) approach to model the interaction between efavirenz and artemether. Artemether dose adjustments were then simulated in order to predict optimal dosing in co-infected patients and inform future interaction study design.

Methods

In vitro data describing the chemical properties, absorption, distribution, metabolism and elimination of efavirenz and artemether were obtained from published literature and included in a physiologically based pharmacokinetic model (PBPK) to predict drug disposition simulating virtual clinical trials. Administration of efavirenz and artemether, alone or in combination, were simulated to mirror previous clinical studies and facilitate validation of the model and realistic interpretation of the simulation. Efavirenz (600 mg once daily) was administered to 50 virtual subjects for 14 days. This was followed by concomitant administration of artemether (80 mg eight hourly) for the first two doses and 80 mg (twice daily) for another two days.

Results

Simulated pharmacokinetics and the drug-drug interaction were in concordance with available clinical data. Efavirenz induced first pass metabolism and hepatic clearance, reducing artemether Cmax by 60% and AUC by 80%. Dose increases of artemether, to correct for the interaction, were simulated and a dose of 240 mg was predicted to be sufficient to overcome the interaction and allow therapeutic plasma concentrations of artemether.

Conclusions

The model presented here provides a rational platform to inform the design for a clinical drug interaction study that may save time and resource while the optimal dose is determined empirically. Wider application of IVIVE could help researchers gain a better understanding of the molecular mechanisms underpinning variability in drug disposition.

Siccardi, M, Olagunju A, Seden K, Ebrahimjee F, Rannard S, Back D, Owen A.  2013.  Use of a physiologicallybased pharmacokinetic model to simulate artemether dose adjustment for overcoming the drug-drug interaction with efavirenz. In Silico Pharmacology. 1(4) Abstract

PURPOSE: To treat malaria, HIV-infected patients normally receive artemether (80 mg twice daily) concurrently with antiretroviral therapy and drug-drug interactions can potentially occur. Artemether is a substrate of CYP3A4 and CYP2B6, antiretrovirals such as efavirenz induce these enzymes and have the potential to reduce artemether pharmacokinetic exposure. The aim of this study was to develop an in vitro in vivo extrapolation (IVIVE) approach to model the interaction between efavirenz and artemether. Artemether dose adjustments were then simulated in order to predict optimal dosing in co-infected patients and inform future interaction study design.

METHODS: In vitro data describing the chemical properties, absorption, distribution, metabolism and elimination of efavirenz and artemether were obtained from published literature and included in a physiologically based pharmacokinetic model (PBPK) to predict drug disposition simulating virtual clinical trials. Administration of efavirenz and artemether, alone or in combination, were simulated to mirror previous clinical studies and facilitate validation of the model and realistic interpretation of the simulation. Efavirenz (600 mg once daily) was administered to 50 virtual subjects for 14 days. This was followed by concomitant administration of artemether (80 mg eight hourly) for the first two doses and 80 mg (twice daily) for another two days.

RESULTS: Simulated pharmacokinetics and the drug-drug interaction were in concordance with available clinical data. Efavirenz induced first pass metabolism and hepatic clearance, reducing artemether Cmax by 60% and AUC by 80%. Dose increases of artemether, to correct for the interaction, were simulated and a dose of 240 mg was predicted to be sufficient to overcome the interaction and allow therapeutic plasma concentrations of artemether.

CONCLUSIONS: The model presented here provides a rational platform to inform the design for a clinical drug interaction study that may save time and resource while the optimal dose is determined empirically. Wider application of IVIVE could help researchers gain a better understanding of the molecular mechanisms underpinning variability in drug disposition.