Urban Cholera transmission hotspots and their implications for Reactive Vaccination: evidence from Bissau city, Guinea Bissau

Use of cholera vaccines in response to epidemics (reactive vaccination) may provide an effective supplement to traditional control measures. In Haiti, reactive vaccination was considered but, until recently, rejected in part due to limited global supply of vaccine. Using Bissau City, Guinea-Bissau as a case study, we explore neighborhood-level transmission dynamics to understand if, with limited vaccine and likely delays, reactive vaccination can significantly change the course of a cholera epidemic

Joint genetic analysis for dairy cattle performance across countries in sub-Saharan Africa

This study assessed the feasibility of across-country genetic evaluation of dairy cattle in sub-Saharan Africa where data on livestock production are scarce. Genetic parameters were estimated for the 305-day milk yield in the first lactation and across five lactations, for age at first calving and for interval between first and second calving. Estimated breeding values of individual animals for these traits were calculated. There were records from 2 333, 25 208, and 5 929 Holstein cows in Kenya, South Africa, and Zimbabwe, and 898 and 65134 Jersey cows from Kenya and South Africa. Genetic gain from sire selection within and across countries. was predicted Genetic links between countries were determined from sires with daughters that had records in two or more countries, and from common ancestral sires across seven generations on both the maternal and paternal sides of the pedigree. Each country was treated as a trait in the across-country evaluation. The results showed that genetic variance and heritability were not always estimable within country, but were significantly different from zero in the across-country evaluation. In all three countries, there was greater genetic gain in all traits from an across-country genetic evaluation owing to greater accuracy of selection compared with within country. Kenya stood to benefit most from an across-country evaluation, followed by Zimbabwe, then South Africa. An across-country breeding programme using joint genetic evaluation would be feasible, provided that there were genetic links across countries, and would provide a platform for accelerated genetic progress through selection and germplasm exchange between sub-Saharan African countries.Keywords: across-country genetic evaluation, genetic connectedness, genetic progres

Impact of Acute Malaria on Pre-Existing Antibodies to Viral and Vaccine Antigens in Mice and Humans

Vaccine-induced immunity depends on long-lived plasma cells (LLPCs) that maintain antibody levels. A recent mouse study showed that Plasmodium chaubaudi infection reduced pre-existing influenza-specific antibodies--raising concerns that malaria may compromise pre-existing vaccine responses. We extended these findings to P. yoelii infection, observing decreases in antibodies to model antigens in inbred mice and to influenza in outbred mice, associated with LLPC depletion and increased susceptibility to influenza rechallenge. We investigated the implications of these findings in Malian children by measuring vaccine-specific IgG (tetanus, measles, hepatitis B) before and after the malaria-free 6-month dry season, 10 days after the first malaria episode of the malaria season, and after the subsequent dry season. On average, vaccine-specific IgG did not decrease following acute malaria. However, in some children malaria was associated with an accelerated decline in vaccine-specific IgG, underscoring the need to further investigate the impact of malaria on pre-existing vaccine-specific antibodies

Phenotypic Characterization According to the Feather Color of Indigenous Muscovy Ducks Bred in the Back Yard in Brazzaville, the Congo

. In Congo, waterfowl genetic resources are constituted by native population of Muscovy ducks that play an important role in food security. The present study aimed to identify and to characterize strains bred in the back yard in the households in Brazzaville. A sample of 154 households drawn over seven districts of Brazzaville was enrolled in the survey. Adults ducks found in the households were identified, pictured by a key of determination and then compared by using the multi resolution analysis image method. The survey recorded 13 strains in which four were considered as newly since they have never been reported elsewhere. These strains received temporally the name of the districts where they have been identified for the first time Makelékélé 1 (0.34%, n=6), Makélékélé 2 (0.11%, n =2), Poto poto 1 (0.28%, n=5) and in Poto poto 2 (0.11%, n=2). Finally, the survey reported nine classical strains such as black plumage, duclair, white, tortora, sepia, chocolate, lavender, grey and canizie. The apparent wide variation in plumage colors is an indication that the duck populations have not been ‘purified' through selective breeding. In the context of the valorization of poultry biodiversity, this work represents a step toward a better knowledge of the production abilities of local ducks breeds in Congo

An iterative identification procedure for dynamic modeling of biochemical networks

<p>Abstract</p> <p>Background</p> <p>Mathematical models provide abstract representations of the information gained from experimental observations on the structure and function of a particular biological system. Conferring a predictive character on a given mathematical formulation often relies on determining a number of non-measurable parameters that largely condition the model's response. These parameters can be identified by fitting the model to experimental data. However, this fit can only be accomplished when identifiability can be guaranteed.</p> <p>Results</p> <p>We propose a novel iterative identification procedure for detecting and dealing with the lack of identifiability. The procedure involves the following steps: 1) performing a structural identifiability analysis to detect identifiable parameters; 2) globally ranking the parameters to assist in the selection of the most relevant parameters; 3) calibrating the model using global optimization methods; 4) conducting a practical identifiability analysis consisting of two (<it>a priori </it>and <it>a posteriori</it>) phases aimed at evaluating the quality of given experimental designs and of the parameter estimates, respectively and 5) optimal experimental design so as to compute the scheme of experiments that maximizes the quality and quantity of information for fitting the model.</p> <p>Conclusions</p> <p>The presented procedure was used to iteratively identify a mathematical model that describes the NF-<it>κ</it>B regulatory module involving several unknown parameters. We demonstrated the lack of identifiability of the model under typical experimental conditions and computed optimal dynamic experiments that largely improved identifiability properties.</p

Antibacterial properties of tualang honey and its effect in burn wound management: a comparative study

<p>Abstract</p> <p>Background</p> <p>The use of honey as a natural product of <it>Apis </it>spp. for burn treatment has been widely applied for centuries. Tualang honey has been reported to have antibacterial properties against various microorganisms, including those from burn-related diagnoses, and is cheaper and easier to be absorbed by Aquacel dressing. The aim of this study is to evaluate the potential antibacterial properties of tualang honey dressing and to determine its effectiveness as a partial thickness burn wound dressing.</p> <p>Methods</p> <p>In order to quantitate the bioburden of the swabs, pour plates were performed to obtain the colony count (CFU/ml). Swabs obtained from burn wounds were streaked on blood agar and MacConkey agar for bacterial isolation and identification. Later, antibacterial activity of Aquacel-tualang honey, Aquacel-Manuka honey, Aquacel-Ag and Aquacel- plain dressings against bacteria isolated from patients were tested (<it>in-vitro</it>) to see the effectiveness of those dressings by zone of inhibition assays.</p> <p>Results</p> <p>Seven organisms were isolated. Four types of Gram-negative bacteria, namely <it>Enterobacter cloacae</it>, <it>Klebsiella pneumoniae</it>, <it>Pseudomonas </it>spp. and <it>Acinetobacter </it>spp., and three Gram-positive bacteria, namely <it>Staphylococcus aureus</it>, coagulase-negative <it>Staphylococcus aureus </it>(CONS) and <it>Streptococcus </it>spp., were isolated. Total bacterial count decreased on day 6 and onwards. In the <it>in-vitro </it>antibacterial study, Aquacel-Ag and Aquacel-Manuka honey dressings gave better zone of inhibition for Gram positive bacteria compared to Aquacel-Tualang honey dressing. However, comparable results were obtained against Gram negative bacteria tested with Aquacel-Manuka honey and Aquacel-Tualang honey dressing.</p> <p>Conclusions</p> <p>Tualang honey has a bactericidal as well as bacteriostatic effect. It is useful as a dressing, as it is easier to apply and is less sticky compared to Manuka honey. However, for Gram positive bacteria, tualang honey is not as effective as usual care products such as silver-based dressing or medical grade honey dressing.</p

Data-driven reverse engineering of signaling pathways using ensembles of dynamic models

Signaling pathways play a key role in complex diseases such as cancer, for which the development of novel therapies is a difficult, expensive and laborious task. Computational models that can predict the effect of a new combination of drugs without having to test it experimentally can help in accelerating this process. In particular, network-based dynamic models of these pathways hold promise to both understand and predict the effect of therapeutics. However, their use is currently hampered by limitations in our knowledge of the underlying biochemistry, as well as in the experimental and computational technologies used for calibrating the models. Thus, the results from such models need to be carefully interpreted and used in order to avoid biased predictions. Here we present a procedure that deals with this uncertainty by using experimental data to build an ensemble of dynamic models. The method incorporates steps to reduce overfitting and maximize predictive capability. We find that by combining the outputs of individual models in an ensemble it is possible to obtain a more robust prediction. We report results obtained with this method, which we call SELDOM (enSEmbLe of Dynamic lOgic-based Models), showing that it improves the predictions previously reported for several challenging problems.JRB and DH acknowledge funding from the EU FP7 project NICHE (ITN Grant number 289384). JRB acknowledges funding from the Spanish MINECO project SYNBIOFACTORY (grant number DPI2014-55276-C5-2-R). AFV acknowledges funding from the Galician government (Xunta de Galiza) through the I2C postdoctoral fellowship ED481B2014/133-0. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.info:eu-repo/semantics/publishedVersio