44 research outputs found
Evaluation of geospatial methods to generate subnational HIV prevalence estimates for local level planning
Objective: There is evidence of substantial subnational variation in the HIV epidemic.
However, robust spatial HIV data are often only available at high levels of geographic
aggregation and not at the finer resolution needed for decision making. Therefore,
spatial analysis methods that leverage available data to provide local estimates of HIV
prevalence may be useful. Such methods exist but have not been formally compared
when applied to HIV.
Design/methods: Six candidate methods – including those used by the Joint United
Nations Programme on HIV/AIDS to generate maps and a Bayesian geostatistical
approach applied to other diseases – were used to generate maps and subnational
estimates of HIV prevalence across three countries using cluster level data from
household surveys. Two approaches were used to assess the accuracy of predictions:
internal validation, whereby a proportion of input data is held back (test dataset) to
challenge predictions; and comparison with location-specific data from household
surveys in earlier years.
Results: Each of the methods can generate usefully accurate predictions of prevalence
at unsampled locations, with the magnitude of the error in predictions similar across
approaches. However, the Bayesian geostatistical approach consistently gave marginally the strongest statistical performance across countries and validation procedures.
Conclusions: Available methods may be able to furnish estimates of HIV prevalence at
finer spatial scales than the data currently allow. The subnational variation revealed can
be integrated into planning to ensure responsiveness to the spatial features of the
epidemic. The Bayesian geostatistical approach is a promising strategy for integrating
HIV data to generate robust local estimates
Transcriptome profiling of Pinus radiata juvenile wood with contrasting stiffness identifies putative candidate genes involved in microfibril orientation and cell wall mechanics
<p>Abstract</p> <p>Background</p> <p>The mechanical properties of wood are largely determined by the orientation of cellulose microfibrils in secondary cell walls. Several genes and their allelic variants have previously been found to affect microfibril angle (MFA) and wood stiffness; however, the molecular mechanisms controlling microfibril orientation and mechanical strength are largely uncharacterised. In the present study, cDNA microarrays were used to compare gene expression in developing xylem with contrasting stiffness and MFA in juvenile <it>Pinus radiata </it>trees in order to gain further insights into the molecular mechanisms underlying microfibril orientation and cell wall mechanics.</p> <p>Results</p> <p>Juvenile radiata pine trees with higher stiffness (HS) had lower MFA in the earlywood and latewood of each ring compared to low stiffness (LS) trees. Approximately 3.4 to 14.5% out of 3, 320 xylem unigenes on cDNA microarrays were differentially regulated in juvenile wood with contrasting stiffness and MFA. Greater variation in MFA and stiffness was observed in earlywood compared to latewood, suggesting earlywood contributes most to differences in stiffness; however, 3-4 times more genes were differentially regulated in latewood than in earlywood. A total of 108 xylem unigenes were differentially regulated in juvenile wood with HS and LS in at least two seasons, including 43 unigenes with unknown functions. Many genes involved in cytoskeleton development and secondary wall formation (cellulose and lignin biosynthesis) were preferentially transcribed in wood with HS and low MFA. In contrast, several genes involved in cell division and primary wall synthesis were more abundantly transcribed in LS wood with high MFA.</p> <p>Conclusions</p> <p>Microarray expression profiles in <it>Pinus radiata </it>juvenile wood with contrasting stiffness has shed more light on the transcriptional control of microfibril orientation and the mechanical properties of wood. The identified candidate genes provide an invaluable resource for further gene function and association genetics studies aimed at deepening our understanding of cell wall biomechanics with a view to improving the mechanical properties of wood.</p