Rural and urban differences in metabolic profiles in a Cameroonian population

Introduction: The difference between modern lifestyle in urban areas and the traditional way of life in rural areas may affect the population’s health in developing countries proportionally. In this study, we sought to describe and compare the metabolic (fasting blood sugar and lipid profile) profile in an urban and rural sample of a Cameroonian population, and study the association to anthropometric risk factors of obesity. Methods: 332 urban and 120 rural men and women originating from the Sanaga Maritime Department and living in the Littoral Region in Cameroon voluntarily participated in this study. In all participants, measurement of height, weight, waist circumference, hip circumference, blood pressure systolic (SBP) and blood pressure diastolic (DBP), resting heart rate (RHR), blood glucose and lipids was carried out using standard methods. Total body fat (BF%) was measured using bio-impedancemetry. Body mass index (BMI) and waist to hip ratio (WHR) were calculated. Low Density Lipoprotein-cholesterol (LDL-c) concentrations were calculated using the Friedwald formula. World Health Organization criteria were used to define high and low levels of blood pressure, metabolic and anthropometric factors. Results: The highest blood pressure values were found in rural men. Concerning resting heart rate, only the youngest women’s age group showed a significant difference between urban and rural areas (79 ± 14 bpm vs 88 ± 12 bpm, p = 0.04) respectively. As opposed to the general tendency in our population, blood glucose was higher in rural men and women compared to their urban counterparts in the older age group (6.00 ± 2.56 mmol/L vs 5.72 ± 2.72 mmol/L, p = 0.030; 5.77 ± 3.72 vs 5.08 ± 0.60, p = 0,887 respectively). Triglycerides (TG) were significantly higher in urban than rural men (1.23 ± 0.39 mmol/L vs 1.17 ± 0.64 mmol/L, p = 0.017). High Density Lipoprotein-cholesterol (HDL-c) levels were higher in rural compared to urban men (2.60 ± 0.10 35mmol/L vs 1.97 ± 1.14 mmol/L, p < 0.001 respectively). However, total Cholesterol (TC) and LDL-c were significantly higher in urban than in rural men (p<0.001 and p=0.005) and women (p <0.001 respectively. Diabetes’ rate in this population was 6.6%. This rate was higher in the rural (8.3%) than in the urban area (6.0%). Age and RHR were significantly higher in diabetic women than in non-diabetics (p=0.007; p=0.032 respectively). In a multiple regression, age was an independent predictor of SBP, DBP and RHR in the entire population. Age predicted blood glucose in rural women only. BMI, WC and BF% were independent predictors of RHR in rural population, especially in men. WC and BF% predicted DBP in rural men only. Anthropometric parameters did not predict the lipid profile. Conclusion: Lipid profile was less atherogenic in rural than in urban area. The rural population was older than the urban one. Blood pressure and blood glucose were positively associated to age in men and women respectively; this could explain the higher prevalence of diabetes in rural than in urban area. The association of these metabolic variables to obesity indices is more frequent and important in urban than in rural area.Key words: Adults, anthropometry, lipid profile, blood glucose, blood pressure, diabetes, urban, rural, Cameroo

Population genetic structure of the malaria vector Anopheles nili in sub-Saharan Africa

<p>Abstract</p> <p>Background</p> <p><it>Anopheles nili </it>is a widespread efficient vector of human malaria parasites in the humid savannas and forested areas of sub-Saharan Africa. Understanding <it>An. nili </it>population structure and gene flow patterns could be useful for the development of locally-adapted vector control measures.</p> <p>Methods</p> <p>Polymorphism at eleven recently developed microsatelitte markers, and sequence variation in four genes within the 28s rDNA subunit (ITS2 and D3) and mtDNA (COII and ND4) were assessed to explore the level of genetic variability and differentiation among nine populations of <it>An. nili </it>from Senegal, Ivory Coast, Burkina Faso, Nigeria, Cameroon and the Democratic Republic of Congo (DRC).</p> <p>Results</p> <p>All microsatellite loci successfully amplified in all populations, showing high and very similar levels of genetic diversity in populations from West Africa and Cameroon (mean Rs = 8.10-8.88, mean He = 0.805-0.849) and much lower diversity in the Kenge population from DRC (mean Rs = 5.43, mean He = 0.594). Bayesian clustering analysis of microsatellite allelic frequencies revealed two main genetic clusters in the dataset. The first one included only the Kenge population and the second grouped together all other populations. High Fst estimates based on microsatellites (Fst > 0.118, P < 0.001) were observed in all comparisons between Kenge and all other populations. By contrast, low Fst estimates (Fst < 0.022, P < 0.05) were observed between populations within the second cluster. The correlation between genetic and geographic distances was weak and possibly obscured by demographic instability. Sequence variation in mtDNA genes matched these results, whereas low polymorphism in rDNA genes prevented detection of any population substructure at this geographical scale.</p> <p>Conclusion</p> <p>Overall, high genetic homogeneity of the <it>An. nili </it>gene pool was found across its distribution range in West and Central Africa, although demographic events probably resulted in a higher level of genetic isolation in the marginal population of Kenge (DRC). The role of the equatorial forest block as a barrier to gene flow and the implication of such findings for vector control are discussed.</p

Hardcoding and dynamic implementation of finite automata Citation for published version (APA): Hardcoding and Dynamic Implementation of Finite Automata

Abstract The theoretical complexity of a string recognizer is linear to the length of the string being tested for acceptance. However, for some kind of strings the processing time largely depends on the number of states visited by the recognizer at run-time. Various experiments are conducted in order to compare the time efficiency of both hardcoded and table-driven algorithms when using such strings patterns. The results of the experiments are cross-compared in order to show the efficiency of the hardcoded algorithm over its table-driven counterpart. This help further the investigations on the problem of the dynamic implementation of finite automata. It is shown that we can rely on the history of the states previously visited in the dynamic framework in order to predict the suitable algorithm for acceptance testing

The Art of

To hardcode and algorithm means to build into it the data that it requires. In this paper, we present various experiments in hardcoding the transition table of a finite state machine directly into string-recognizing code. Experiments are carried out in two phases. The first phase is limited to the analysis of the hardcoded behavior in relation to acceptance or rejection of a single symbol in some arbitrary state of some finite automaton. Then follows a simulation of the analysis of some hardcoded solution for recognizing an entire string. Measurements are provided to show the time efficiency gains by various hardcoded versions over the traditional table-driven approach

Emergence of CTX-M-15-producing enterobacteria in Cameroon and characterization of a blaCTX-M-15-carrying element

CTX-M-15-producing Klebsiella pneumoniae and Escherichia coli emerged recently in Cameroon. CTX-M-15 was encoded by two different multiresistance plasmids, of which one carried an ISEcp1-blaCTX-M-15 element flanked by a 5-bp target site duplication and inserted within a Tn2-derived sequence. A truncated form of this element in the second plasmid was identified