The impact on nurses and nurse managers of introducing PEPFAR clinical services in urban government clinics in Uganda

BACKGROUND: Improving provider performance is central to strengthening health services in developing countries. Because of critical shortages of physicians, many clinics in sub-Saharan Africa are led by nurses. In addition to clinical skills, nurse managers need practical managerial skills and adequate resources to ensure procurement of essential supplies, quality assurance implementation, and productive work environment. Giving nurses more autonomy in their work empowers them in the workplace and has shown to create positive influence on work attitudes and behaviors. The Infectious Disease Institute, an affiliate of Makerere University College of Health Science, in an effort to expand the needed HIV services in the Ugandan capital, established a community-university partnership with the Ministry of Health to implement an innovative model to build capacity in HIV service delivery. This paper evaluates the impact on the nurses from this innovative program to provide more health care in six nurse managed Kampala City Council (KCC) Clinics. METHODS: A mixed method approach was used. The descriptive study collected key informant interviews from the six nurse managers, and administered a questionnaire to 20 staff nurses between September and December 2009. Key themes were manually identified from the interviews, and the questionnaire data were analyzed using SPSS. RESULTS: Introducing new HIV services into six KCC clinics was positive for the nurses. They identified the project as successful because of perceived improved environment, increase in useful in-service training, new competence to manage patients and staff, improved physical infrastructure, provision of more direct patient care, motivation to improve the clinic because the project acted on their suggestions, and involvement in role expansion. All of these helped empower the nurses, improving quality of care and increasing job satisfaction. CONCLUSIONS: This community-university HIV innovative model was successful from the point of view of the nurses and nurse managers. This model shows promise in increasing effective, quality health service; HIV and other programs can build capacity and empower nurses and nurse managers to directly implement such services. It also demonstrates how MakCHS can be instrumental through partnerships in designing and testing effective strategies, building human health resources and improving Ugandan health outcomes

Genome-wide association scan meta-analysis identifies three Loci influencing adiposity and fat distribution.

To identify genetic loci influencing central obesity and fat distribution, we performed a meta-analysis of 16 genome-wide association studies (GWAS, N = 38,580) informative for adult waist circumference (WC) and waist-hip ratio (WHR). We selected 26 SNPs for follow-up, for which the evidence of association with measures of central adiposity (WC and/or WHR) was strong and disproportionate to that for overall adiposity or height. Follow-up studies in a maximum of 70,689 individuals identified two loci strongly associated with measures of central adiposity; these map near TFAP2B (WC, P = 1.9x10(-11)) and MSRA (WC, P = 8.9x10(-9)). A third locus, near LYPLAL1, was associated with WHR in women only (P = 2.6x10(-8)). The variants near TFAP2B appear to influence central adiposity through an effect on overall obesity/fat-mass, whereas LYPLAL1 displays a strong female-only association with fat distribution. By focusing on anthropometric measures of central obesity and fat distribution, we have identified three loci implicated in the regulation of human adiposity

Biodiversity in urban gardens: assessing the accuracy of citizen science data on garden hedgehogs

Urban gardens provide a rich habitat for species that are declining in rural areas. However, collecting data in gardens can be logistically-challenging, time-consuming and intrusive to residents. This study examines the potential of citizen scientists to record hedgehog sightings and collect habitat data within their own gardens using an online questionnaire. Focussing on a charismatic species meant that the number of responses was high (516 responses were obtained in 6 weeks, with a ~ 50:50% split between gardens with and without hedgehog sightings). While many factors commonly thought to influence hedgehog presence (e.g. compost heaps) were present in many hedgehog-frequented gardens, they were not discriminatory as they were also found in gardens where hedgehogs were not seen. Respondents were most likely to have seen hedgehogs in their garden if they had also seen hedgehogs elsewhere in their neighbourhood. However, primary fieldwork using hedgehog ‘footprint tunnels’ showed that hedgehogs were found to be just as prevalent in gardens in which hedgehogs had previously been reported as gardens where they had not been reported. Combining these results indicates that hedgehogs may be more common in urban and semi-urban gardens than previously believed, and that casual volunteer records of hedgehogs may be influenced more by the observer than by habitat preferences of the animal. When verified, volunteer records can provide useful information, but care is needed in interpreting these data

New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk.

Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes

Identification and Functional Characterization of G6PC2 Coding Variants Influencing Glycemic Traits Define an Effector Transcript at the G6PC2-ABCB11 Locus

Genome wide association studies (GWAS) for fasting glucose (FG) and insulin (FI) have identified common variant signals which explain 4.8% and 1.2% of trait variance, respectively. It is hypothesized that low-frequency and rare variants could contribute substantially to unexplained genetic variance. To test this, we analyzed exome-array data from up to 33,231 non-diabetic individuals of European ancestry. We found exome-wide significant (P<5×10-7) evidence for two loci not previously highlighted by common variant GWAS: GLP1R (p.Ala316Thr, minor allele frequency (MAF)=1.5%) influencing FG levels, and URB2 (p.Glu594Val, MAF = 0.1%) influencing FI levels. Coding variant associations can highlight potential effector genes at (non-coding) GWAS signals. At the G6PC2/ABCB11 locus, we identified multiple coding variants in G6PC2 (p.Val219Leu, p.His177Tyr, and p.Tyr207Ser) influencing FG levels, conditionally independent of each other and the non-coding GWAS signal. In vitro assays demonstrate that these associated coding alleles result in reduced protein abundance via proteasomal degradation, establishing G6PC2 as an effector gene at this locus. Reconciliation of single-variant associations and functional effects was only possible when haplotype phase was considered. In contrast to earlier reports suggesting that, paradoxically, glucose-raising alleles at this locus are protective against type 2 diabetes (T2D), the p.Val219Leu G6PC2 variant displayed a modest but directionally consistent association with T2D risk. Coding variant associations for glycemic traits in GWAS signals highlight PCSK1, RREB1, and ZHX3 as likely effector transcripts. These coding variant association signals do not have a major impact on the trait variance explained, but they do provide valuable biological insights

Identification and functional characterization of G6PC2 coding variants influencing glycemic traits define an effector transcript at the G6PC2-ABCB11 locus.

Genome wide association studies (GWAS) for fasting glucose (FG) and insulin (FI) have identified common variant signals which explain 4.8% and 1.2% of trait variance, respectively. It is hypothesized that low-frequency and rare variants could contribute substantially to unexplained genetic variance. To test this, we analyzed exome-array data from up to 33,231 non-diabetic individuals of European ancestry. We found exome-wide significant (P<5×10-7) evidence for two loci not previously highlighted by common variant GWAS: GLP1R (p.Ala316Thr, minor allele frequency (MAF)=1.5%) influencing FG levels, and URB2 (p.Glu594Val, MAF = 0.1%) influencing FI levels. Coding variant associations can highlight potential effector genes at (non-coding) GWAS signals. At the G6PC2/ABCB11 locus, we identified multiple coding variants in G6PC2 (p.Val219Leu, p.His177Tyr, and p.Tyr207Ser) influencing FG levels, conditionally independent of each other and the non-coding GWAS signal. In vitro assays demonstrate that these associated coding alleles result in reduced protein abundance via proteasomal degradation, establishing G6PC2 as an effector gene at this locus. Reconciliation of single-variant associations and functional effects was only possible when haplotype phase was considered. In contrast to earlier reports suggesting that, paradoxically, glucose-raising alleles at this locus are protective against type 2 diabetes (T2D), the p.Val219Leu G6PC2 variant displayed a modest but directionally consistent association with T2D risk. Coding variant associations for glycemic traits in GWAS signals highlight PCSK1, RREB1, and ZHX3 as likely effector transcripts. These coding variant association signals do not have a major impact on the trait variance explained, but they do provide valuable biological insights

Neurod1 Suppresses Hair Cell Differentiation in Ear Ganglia and Regulates Hair Cell Subtype Development in the Cochlea

Background: At least five bHLH genes regulate cell fate determination and differentiation of sensory neurons, hair cells and supporting cells in the mammalian inner ear. Cross-regulation of Atoh1 and Neurog1 results in hair cell changes in Neurog1 null mice although the nature and mechanism of the cross-regulation has not yet been determined. Neurod1, regulated by both Neurog1 and Atoh1, could be the mediator of this cross-regulation. Methodology/Principal Findings: We used Tg(Pax2-Cre) to conditionally delete Neurod1 in the inner ear. Our data demonstrate for the first time that the absence of Neurod1 results in formation of hair cells within the inner ear sensory ganglia. Three cell types, neural crest derived Schwann cells and mesenchyme derived fibroblasts (neither expresses Neurod1) and inner ear derived neurons (which express Neurod1) constitute inner ear ganglia. The most parsimonious explanation is that Neurod1 suppresses the alternative fate of sensory neurons to develop as hair cells. In the absence of Neurod1, Atoh1 is expressed and differentiates cells within the ganglion into hair cells. We followed up on this effect in ganglia by demonstrating that Neurod1 also regulates differentiation of subtypes of hair cells in the organ of Corti. We show that in Neurod1 conditional null mice there is a premature expression of several genes in the apex of the developing cochlea and outer hair cells are transformed into inner hair cells. Conclusions/Significance: Our data suggest that the long noted cross-regulation of Atoh1 expression by Neurog1 migh