63 research outputs found
Short-term impacts of an unconditional cash transfer program on child schooling: Experimental evidence from Malawi.
This study analyzes the impact of a positive income shock on child schooling outcomes using experimental data from an unconditional cash transfer program in Malawi. Since households receive the cash and parents are responsible for making spending decisions, we also examine the intervening pathways between cash transfers and child schooling. Data comes from a cluster-randomized study of Malawi’s Social Cash Transfer Program (SCTP). After a baseline survey, households in village clusters were randomly assigned to treatment and control arms with treatment villages receiving transfers immediately and control villages assigned a later entry. We test for treatment impacts on a panel of school-aged children (6–17) using a differences-in-differences model. After a years’ worth of transfers, we find the Malawi SCTP both improves enrollment rates and decreases dropouts. The main intervening pathway between the program and schooling is education expenditures, suggesting that the cash improves the demand for education by reducing financial constraints
Paying for Happiness: Experimental Results from a Large Cash Transfer Program in Malawi
This study analyzes the short-term impact of an exogenous, positive income shock on caregivers’ subjective well-being (SWB) in Malawi using panel data from 3,365 households targeted to receive Malawi’s Social Cash Transfer Program that provides unconditional cash to ultra-poor, labor-constrained households. The study consists of a cluster-randomized, longitudinal design. After the baseline survey, half of these village clusters were randomly selected to receive the transfer and a follow-up was conducted 17 months later. We find that the short-term impact of household income increases from the cash transfer leads to substantial SWB gains among caregivers. After a year’s worth of transfers, caregivers in beneficiary households have higher life satisfaction and are more likely to believe in a better future. We examine whether program impacts on consumption, food security, resilience, and hopefulness could explain the increase in SWB but do not find that any of these mechanisms individually mediate our results
Prevalence and risk factors associated with sexually transmitted infections (STIs) among women of reproductive age in Swaziland.
BACKGROUND: Sexually transmitted infections (STIs) remain an important public health problem with approximately half a billion new cases annually among persons aged 15-49 years. Epidemiological data on STIs among women of reproductive age in Swaziland are limited. The availability of epidemiological data on STIs and associated risk factors in this population is essential for the development of successful prevention, diagnosis and management strategies in the country. The study aimed to determine the prevalence and risk factors associated with STIs. METHODS: A total of 655 women aged 15-49 years were systematically enrolled from five health facilities using a cross-sectional study design. Cervical specimen were tested using GeneXpert CT/NG Assays for Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (NG), GeneXpertTV Assay for Trichomonas vaginalis (TV), and GeneXpert HPV Assays for hr-HPV. Blood samples were tested using Alere Determine HIV-1/2Ag/Ab Combo and Trinity Biotech Uni-Gold Recombigen HIV test for confirmation for HIV, and Rapid Plasma Reagin and TPHA test for confirmation for Treponema pallidum (syphilis). Genital warts were assessed prior to specimen collection. Survey weighted analyses were done to estimate the population burden of STIs. RESULTS: The four most common curable STIs: CT, NG, TV, Treponema pallidum (syphilis), as well as genital warts were considered in this study. The overall weighted prevalence of any of these five STIs was 19.4% (95% CI: 14.9-24.8), corresponding to 72 990 women with STIs in Swaziland. The estimated prevalences were 7.0% (95% CI: 4.1-11.2) for CT, 6.0% (95% CI: 3.8-8.8) for NG, 8.4% (95% CI: 5.4-12.8) for TV, 1.4% (95% CI: 1.1-10.2) for syphilis and 2.0% (95% CI: 1.0-11.4) for genital warts. The overall weighted HIV prevalence was 42.7% (95%CI: 35.7-46.2). Among hr-HPV positive women, 18.8% (95% CI: 13.1-26.3) had one STI, while 6.3% (95% CI: 3.3-11.7) had multiple STIs. Risk factors associated with STIs were being employed (OR = 2.2, 95% CI: 1.0-4.7), self-employed (OR = 2.8, 95% CI: 1.5-5.5) and being hr-HPV positive (OR = 2.0, 95% CI: 1.3-3.1). Age (0.9, 95% CI: 0.8-0.9), being married (OR = 0.4, 95% CI: 0.3-0.7) and not using condoms with regular partners (OR = 0.5, 95% CI: 0.3-0.9) were inversely associated with STIs. CONCLUSION: STIs are highly prevalent among women of reproductive age in Swaziland. Thus, a comprehensive STIs screening, surveillance and treatment programme would be justified and could potentially lower the burden of STIs in the country
Prevalence of and Associated Risk Factors for High Risk Human Papillomavirus among Sexually Active Women, Swaziland.
BACKGROUND: High risk human papillomavirus (hr-HPV) infection and the dual burden of HIV remains a huge challenge in some low-income countries (LICs) such as Swaziland with limited or no data. We estimated the prevalence and investigated determinants of hr-HPV, including HIV infection among sexually active women in Swaziland. METHODS: A total of 655 women aged between 15 and 49 years from five health facilities were randomly enrolled using a cross-sectional study design. Cervical cells were tested for hr-HPV types using GeneXpert HPV Assays. RESULTS: The overall weighted hr-HPV prevalence was 46.2% (95%CI: 42.8-49.5). Of hr-HPV infected women, 12.4% (95%CI: 8.6-17.5) were HPV16-positive, 13.8% (95%CI:12.0-15.8) were positive for HPV18/45, 26.7% (95%CI: 24.2-29.3) for HPV31/33/35/52/58, 7.6% (95%CI: 7.6-11.9) for HPV51/59 and 11.0%, (95%CI: 7.9-15.3) for HPV39/56/66/68. Prevalence of hr-HPV decreased with increasing age. Overall HIV prevalence remained high (42.7%; 95%CI: 35.7-46.2). HIV infection was associated with hr-HPV infection (Adjusted OR = 4.9, 95%CI: 3.043-7.8, p<0.001). Overall hr-HPV/HIV co-infection was 24.4% (95%CI: 20.3-29.1) which was significantly higher among younger age groups (p<0.001). Prevalence of multiple group hr-HPV infection was significantly higher in HIV-positive versus -negative women (27.7% and 12.7% respectively, p<0.001). The presence, absence or unknown of history of STI with HIV did not appear to modify the relationship with hr-HPV (OR = 4.2, 95%CI: 2.6-7.1, OR = 4.6, 95%CI: 2.8-7.7, p<0.001, p<0.001 and OR = 4.1, 95%CI: 1.3-13.4, p<0.021 respectively). CONCLUSION: The prevalence of hr-HPV infection was high and significantly associated with HIV among sexually active women. Furthermore, the study has provided essential information about the HIV link with hr-HPV infections which may explain the high prevalence among HIV infected women. This can contribute to policy development and planning of prevention strategies incorporating HPV infection prevention especially among youth and HIV infected people
Predicting protein linkages in bacteria: Which method is best depends on task
<p>Abstract</p> <p>Background</p> <p>Applications of computational methods for predicting protein functional linkages are increasing. In recent years, several bacteria-specific methods for predicting linkages have been developed. The four major genomic context methods are: Gene cluster, Gene neighbor, Rosetta Stone, and Phylogenetic profiles. These methods have been shown to be powerful tools and this paper provides guidelines for when each method is appropriate by exploring different features of each method and potential improvements offered by their combination. We also review many previous treatments of these prediction methods, use the latest available annotations, and offer a number of new observations.</p> <p>Results</p> <p>Using <it>Escherichia coli </it>K12 and <it>Bacillus subtilis</it>, linkage predictions made by each of these methods were evaluated against three benchmarks: functional categories defined by COG and KEGG, known pathways listed in EcoCyc, and known operons listed in RegulonDB. Each evaluated method had strengths and weaknesses, with no one method dominating all aspects of predictive ability studied. For functional categories, as previous studies have shown, the Rosetta Stone method was individually best at detecting linkages and predicting functions among proteins with shared KEGG categories while the Phylogenetic profile method was best for linkage detection and function prediction among proteins with common COG functions. Differences in performance under COG versus KEGG may be attributable to the presence of paralogs. Better function prediction was observed when using a weighted combination of linkages based on reliability versus using a simple unweighted union of the linkage sets. For pathway reconstruction, 99 complete metabolic pathways in <it>E. coli </it>K12 (out of the 209 known, non-trivial pathways) and 193 pathways with 50% of their proteins were covered by linkages from at least one method. Gene neighbor was most effective individually on pathway reconstruction, with 48 complete pathways reconstructed. For operon prediction, Gene cluster predicted completely 59% of the known operons in <it>E. coli </it>K12 and 88% (333/418)in <it>B. subtilis</it>. Comparing two versions of the <it>E. coli </it>K12 operon database, many of the unannotated predictions in the earlier version were updated to true predictions in the later version. Using only linkages found by both Gene Cluster and Gene Neighbor improved the precision of operon predictions. Additionally, as previous studies have shown, combining features based on intergenic region and protein function improved the specificity of operon prediction.</p> <p>Conclusion</p> <p>A common problem for computational methods is the generation of a large number of false positives that might be caused by an incomplete source of validation. By comparing two versions of a database, we demonstrated the dramatic differences on reported results. We used several benchmarks on which we have shown the comparative effectiveness of each prediction method, as well as provided guidelines as to which method is most appropriate for a given prediction task.</p
Fusion and Fission of Genes Define a Metric between Fungal Genomes
Gene fusion and fission events are key mechanisms in the evolution of gene architecture, whose effects are visible in protein architecture when they occur in coding sequences. Until now, the detection of fusion and fission events has been performed at the level of protein sequences with a post facto removal of supernumerary links due to paralogy, and often did not include looking for events defined only in single genomes. We propose a method for the detection of these events, defined on groups of paralogs to compensate for the gene redundancy of eukaryotic genomes, and apply it to the proteomes of 12 fungal species. We collected an inventory of 1,680 elementary fusion and fission events. In half the cases, both composite and element genes are found in the same species. Per-species counts of events correlate with the species genome size, suggesting a random mechanism of occurrence. Some biological functions of the genes involved in fusion and fission events are slightly over- or under-represented. As already noted in previous studies, the genes involved in an event tend to belong to the same functional category. We inferred the position of each event in the evolution tree of the 12 fungal species. The event localization counts for all the segments of the tree provide a metric that depicts the “recombinational” phylogeny among fungi. A possible interpretation of this metric as distance in adaptation space is proposed
A Systems Model for Immune Cell Interactions Unravels the Mechanism of Inflammation in Human Skin
Inflammation is characterized by altered cytokine levels produced by cell populations in a highly interdependent manner. To elucidate the mechanism of an inflammatory reaction, we have developed a mathematical model for immune cell interactions via the specific, dose-dependent cytokine production rates of cell populations. The model describes the criteria required for normal and pathological immune system responses and suggests that alterations in the cytokine production rates can lead to various stable levels which manifest themselves in different disease phenotypes. The model predicts that pairs of interacting immune cell populations can maintain homeostatic and elevated extracellular cytokine concentration levels, enabling them to operate as an immune system switch. The concept described here is developed in the context of psoriasis, an immune-mediated disease, but it can also offer mechanistic insights into other inflammatory pathologies as it explains how interactions between immune cell populations can lead to disease phenotypes
Coverage of whole proteome by structural genomics observed through protein homology modeling database
We have been developing FAMSBASE, a protein homology-modeling database of whole ORFs predicted from genome sequences. The latest update of FAMSBASE (http://daisy.nagahama-i-bio.ac.jp/Famsbase/), which is based on the protein three-dimensional (3D) structures released by November 2003, contains modeled 3D structures for 368,724 open reading frames (ORFs) derived from genomes of 276 species, namely 17 archaebacterial, 130 eubacterial, 18 eukaryotic and 111 phage genomes. Those 276 genomes are predicted to have 734,193 ORFs in total and the current FAMSBASE contains protein 3D structure of approximately 50% of the ORF products. However, cases that a modeled 3D structure covers the whole part of an ORF product are rare. When portion of an ORF with 3D structure is compared in three kingdoms of life, in archaebacteria and eubacteria, approximately 60% of the ORFs have modeled 3D structures covering almost the entire amino acid sequences, however, the percentage falls to about 30% in eukaryotes. When annual differences in the number of ORFs with modeled 3D structure are calculated, the fraction of modeled 3D structures of soluble protein for archaebacteria is increased by 5%, and that for eubacteria by 7% in the last 3 years. Assuming that this rate would be maintained and that determination of 3D structures for predicted disordered regions is unattainable, whole soluble protein model structures of prokaryotes without the putative disordered regions will be in hand within 15 years. For eukaryotic proteins, they will be in hand within 25 years. The 3D structures we will have at those times are not the 3D structure of the entire proteins encoded in single ORFs, but the 3D structures of separate structural domains. Measuring or predicting spatial arrangements of structural domains in an ORF will then be a coming issue of structural genomics
Promoter Complexity and Tissue-Specific Expression of Stress Response Components in Mytilus galloprovincialis, a Sessile Marine Invertebrate Species
The mechanisms of stress tolerance in sessile animals, such as molluscs, can offer fundamental insights into the adaptation of organisms for a wide range of environmental challenges. One of the best studied processes at the molecular level relevant to stress tolerance is the heat shock response in the genus Mytilus. We focus on the upstream region of Mytilus galloprovincialis Hsp90 genes and their structural and functional associations, using comparative genomics and network inference. Sequence comparison of this region provides novel evidence that the transcription of Hsp90 is regulated via a dense region of transcription factor binding sites, also containing a region with similarity to the Gamera family of LINE-like repetitive sequences and a genus-specific element of unknown function. Furthermore, we infer a set of gene networks from tissue-specific expression data, and specifically extract an Hsp class-associated network, with 174 genes and 2,226 associations, exhibiting a complex pattern of expression across multiple tissue types. Our results (i) suggest that the heat shock response in the genus Mytilus is regulated by an unexpectedly complex upstream region, and (ii) provide new directions for the use of the heat shock process as a biosensor system for environmental monitoring
Meta-analysis of type 2 Diabetes in African Americans Consortium
Type 2 diabetes (T2D) is more prevalent in African Americans than in Europeans. However, little is known about the genetic risk in African Americans despite the recent identification of more than 70 T2D loci primarily by genome-wide association studies (GWAS) in individuals of European ancestry. In order to investigate the genetic architecture of T2D in African Americans, the MEta-analysis of type 2 DIabetes in African Americans (MEDIA) Consortium examined 17 GWAS on T2D comprising 8,284 cases and 15,543 controls in African Americans in stage 1 analysis. Single nucleotide polymorphisms (SNPs) association analysis was conducted in each study under the additive model after adjustment for age, sex, study site, and principal components. Meta-analysis of approximately 2.6 million genotyped and imputed SNPs in all studies was conducted using an inverse variance-weighted fixed effect model. Replications were performed to follow up 21 loci in up to 6,061 cases and 5,483 controls in African Americans, and 8,130 cases and 38,987 controls of European ancestry. We identified three known loci (TCF7L2, HMGA2 and KCNQ1) and two novel loci (HLA-B and INS-IGF2) at genome-wide significance (4.15 × 10(-94)<P<5 × 10(-8), odds ratio (OR) = 1.09 to 1.36). Fine-mapping revealed that 88 of 158 previously identified T2D or glucose homeostasis loci demonstrated nominal to highly significant association (2.2 × 10(-23) < locus-wide P<0.05). These novel and previously identified loci yielded a sibling relative risk of 1.19, explaining 17.5% of the phenotypic variance of T2D on the liability scale in African Americans. Overall, this study identified two novel susceptibility loci for T2D in African Americans. A substantial number of previously reported loci are transferable to African Americans after accounting for linkage disequilibrium, enabling fine mapping of causal variants in trans-ethnic meta-analysis studies.Peer reviewe
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