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<title>SHS Publications 2018</title>
<link>http://hdl.handle.net/123456789/512</link>
<description/>
<pubDate>Thu, 09 Apr 2026 23:36:20 GMT</pubDate>
<dc:date>2026-04-09T23:36:20Z</dc:date>
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<title>Distribution of the cytochrome P450 CYP2C8*2 allele in Brazzaville, Republic of Congo</title>
<link>http://hdl.handle.net/123456789/527</link>
<description>Distribution of the cytochrome P450 CYP2C8*2 allele in Brazzaville, Republic of Congo
Peko, S. M; Ntoumi, F; Vouvoungui, C; Nderu, DF; Kobawila, S. C; Velavan, T.  P; Koukouikila-Koussounda
Background: Cytochrome P450 (CYP) enzymes are essential in the metabolism of most drugs used today. Single nucleotide polymorphism(s) occurring in CYP genes can adversely affect drug pharmacokinetics, efficacy, and safety. Individuals carrying the CYP2C8*2 c.805A &gt; T (CYP2C8*2; rs11572103) allele have impaired amodiaquine metabolism, increased risk of amodiaquine-related adverse events, and may promote the selection of drug-resistant parasite strains. This study investigated the distribution of the CYP2C8*2 allele in Brazzaville, Republic of Congo, where artesunate + amodiaquine is used as the second-line treatment for uncomplicated Plasmodium falciparum malaria.&#13;
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Methods: A total of 285 febrile children visiting the Marien Ngouabi paediatric hospital were genotyped for CYP2C8*2 using PCR-restriction fragment length polymorphism (PCR-RFLP). The allele frequencies and genotype distribution were determined.&#13;
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Results: The CYP2C8*2 allele was successfully genotyped in 75% (213/285) of the study participants. The CYP2C8*2A allele had a frequency of 63%, whereas the CYP2C8*2T allele had a frequency of 37%. Genotypes CYP2C8*2AA (rapid metabolizer), CYP2C8*2AT (intermediate metabolizer), and CYP2C8*2TT (poor metabolizer) were observed in 44%, 38%, and 18% of the investigated participants, respectively.&#13;
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Conclusions: This study gives the first description of CYP2C8*2 allele distribution in the Republic of Congo and highlights the potential risk of amodiaquine-related adverse events. Information from this study will be beneficial during pharmacovigilance investigations.
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<pubDate>Fri, 01 Jan 2021 00:00:00 GMT</pubDate>
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<dc:date>2021-01-01T00:00:00Z</dc:date>
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<title>Genetic diversity and population structure of Plasmodium falciparum in kenyan–ugandan border areas.</title>
<link>http://hdl.handle.net/123456789/525</link>
<description>Genetic diversity and population structure of Plasmodium falciparum in kenyan–ugandan border areas.
Nderu, D; Kimani, F; Karanja, E; Thiong'o, K; Akinyi, M; Too, E; Chege, W; NamMbati, E; Wangai, L.N.; Meyer, C.G.; Vela
Kenya has, in the last decade, made tremendous progress in the fight against malaria. Nevertheless, continued surveillance of the genetic diversity and population structure of Plasmodium falciparum is required to refine malaria control and to adapt and improve elimination strategies. Twelve neutral microsatellite loci were genotyped in 201 P. falciparum isolates obtained from the Kenyan-Ugandan border (Busia) and from two inland malaria-endemic sites situated in western (Nyando) and coastal (Msambweni) Kenya. Analyses were done to assess the genetic diversity (allelic richness and expected heterozygosity, [He ]), multilocus linkage disequilibrium ( IAS ) and population structure. A similarly high degree of genetic diversity was observed among the three parasite populations surveyed (mean He = 0.76; P &gt; 0.05). Except in Msambweni, random association of microsatellite loci was observed, indicating high parasite out-breeding. Low to moderate genetic structure (FST = 0.022-0.076; P &lt; 0.0001) was observed with only 5% variance in allele frequencies observed among the populations. This study shows that the genetic diversity of P. falciparum populations at the Kenyan-Ugandan border is comparable to the parasite populations from inland Kenya. In addition, high genetic diversity, panmixia and weak population structure in this study highlight the fitness of Kenyan P. falciparum populations to successfully withstand malaria control interventions.
</description>
<pubDate>Tue, 01 Jan 2019 00:00:00 GMT</pubDate>
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<dc:date>2019-01-01T00:00:00Z</dc:date>
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<title>Origin and spread of antimalarial resistance in Africa.</title>
<link>http://hdl.handle.net/123456789/326</link>
<description>Origin and spread of antimalarial resistance in Africa.
Laura, N
he Western Cambodia region is infamous for its malaria parasites. Twice already in the 1950s and the 1960s they have developed resistance to key drugs, and the underlying mutations spread inevitably around the world, forcing public health sector to nd new ways to contain the disease. It is now happening again. Over the years, artemisinin, the most powerful drug available for management of malaria, has reported in a substantial number of individuals in Cambodia, Myanmar, Vietnam, Laos, and border regions of Thailand. Researchers and public health experts worry that history may repeat itself and the resistant parasites spread globally. Recent discovery of drug resistance-associated genes, pfcrt, pfmdr1, dhfr, dhps, and k13 and applications of microsatellite markers anking the genes have revealed of the evolution of resistant parasites to all classes of antimalarials and the geographical distribution of drug resistance. Here, we review our recent knowledge of the Origin and spread of parasite resistance to the previously used drugs (chloroquine, sulfadoxine/pyrimethamine) and artemisinin combination therapy. Though efforts to prevent and eliminate resistance so far are still unsuccessful, but, new advances into the genes other than the threat insight should help scientists identify and track resistant parasites including nding better ways to contain them
</description>
<pubDate>Tue, 01 Jan 2019 00:00:00 GMT</pubDate>
<guid isPermaLink="false">http://hdl.handle.net/123456789/326</guid>
<dc:date>2019-01-01T00:00:00Z</dc:date>
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<title>Analysis of Tobacco Smoking Patterns in Relation to Age and Employment Status: A Case Study of Kirinyaga Central Constituency</title>
<link>http://hdl.handle.net/123456789/321</link>
<description>Analysis of Tobacco Smoking Patterns in Relation to Age and Employment Status: A Case Study of Kirinyaga Central Constituency
Munyiri, LM; Gachoki, PK; Gitonga, JN
International Research Journal of Advanced Engineering and ScienceISSN (Online): 2455-9024474Munyiri  LM,  GachokiPK,  and  Gitonga  JN, “Analysis  of  Tobacco  Smoking Patterns  in  Relation  to  Age  and  Employment  Status:  A  Case Study  of  Kirinyaga  Central  Constituency,”International  Research  Journal  of  Advanced  Engineering  and  Science,  Volume  4,  Issue  2,  pp. 474-477, 2019.Analysis of Tobacco Smoking Patterns in Relation to Age and Employment Status: A Case Study of Kirinyaga Central ConstituencyMunyiri LM1, GachokiPK2,Gitonga JN31, 3Department of Pure and Applied Sciences, Kirinyaga University, P.O Box 143-10300, Kerugoya, Kenya2Department of Physical Sciences, Chuka University, P.O Box 109-60400, Chuka, KenyaCorresponding authors’ email; 1lucasmunyiri@gmail.com; 2pkgachoki@gmail.comAbstract—Tobacco is dried leaves of the plant Nicotina tabacum. It contains  the  drug  nicotine  for  the  effects  of  which  it’s  smoked, chewed  or  inhaled  as  powder,  smoking  being  the  most  common method  of  consuming  tobacco.  Tobacco  smoking  originated  among Native Americans in Eastern North America where tobacco is native. Tobacco  smoking  may  be  influenced  by  various  factors  which  may include:  individual  level  factors  such  as  (age,  gender,  and  social-class).  A  country’s  national  economic  development  or  its implementation  on  tobacco  control  policies  may  adhere  to  tobacco smoking. The general objective  of  this  study  was to  examine  if  there exist  a  relationship  between  smoking,  age  and  employment  status. This   study   took   into   account   the   following   variables;   tobacco smoking as the dependent variable, age and employment status as the independent  variable.  The  scope of  the  study  was  Kirinyaga  Central Constituency, samples taken from its four wards. Stratified sampling was used, the target sample was 100. The study had a response rate of  97%.  The  main  instrument  of  data  collection  was  questionnaires; the  data  gathered  was  both  qualitative  and  quantitative.  Data  was keyed in using epi-data software and analysed using SPSS. Data was analysed  using  descriptive  statistics  and  multiple  logistic  regression analysis. The study also consisted of 3 hypotheses testing which were validated   using   Chi-Square   tests   of   independence.   The   results revealed that employment status influences tobacco smoking from the multiple  logistic  regression  analysis.  The  conclusion  from this  study was  that  there  exists  a  relationship  between  employment  status  and tobacco smoking in Kirinyaga Central Constituency
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<pubDate>Tue, 01 Jan 2019 00:00:00 GMT</pubDate>
<guid isPermaLink="false">http://hdl.handle.net/123456789/321</guid>
<dc:date>2019-01-01T00:00:00Z</dc:date>
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