Investigating the spatial variation and risk factors of childhood anaemia in four sub-Saharan African countries.

BACKGROUND: The causes of childhood anaemia are multifactorial, interrelated and complex. Such causes vary from country to country, and within a country. Thus, strategies for anaemia control should be tailored to local conditions and take into account the specific etiology and prevalence of anaemia in a given setting and sub-population. In addition, policies and programmes for anaemia control that do not account for the spatial heterogeneity of anaemia in children may result in certain sub-populations being excluded, limiting the effectiveness of the programmes. This study investigated the demographic and socio-economic determinants as well as the spatial variation of anaemia in children aged 6 to 59 months in Kenya, Malawi, Tanzania and Uganda. METHODS: The study made use of data collected from nationally representative Malaria Indicator Surveys (MIS) and Demographic and Health Surveys (DHS) conducted in all four countries between 2015 and 2017. During these surveys, all children under the age of five years old in the sampled households were tested for malaria and anaemia. A child's anaemia status was based on the World Health Organization's cut-off points where a child was considered anaemic if their altitude adjusted haemoglobin (Hb) level was less than 11 g/dL. The explanatory variables considered comprised of individual, household and cluster level factors, including the child's malaria status. A multivariable hierarchical Bayesian geoadditive model was used which included a spatial effect for district of child's residence. RESULTS: Prevalence of childhood anaemia ranged from 36.4% to 61.9% across the four countries. Children with a positive malaria result had a significantly higher odds of anaemia [AOR = 4.401; 95% CrI: (3.979, 4.871)]. After adjusting for a child's malaria status and other demographic, socio-economic and environmental factors, the study revealed distinct spatial variation in childhood anaemia within and between Malawi, Uganda and Tanzania. The spatial variation appeared predominantly due to unmeasured district-specific factors that do not transcend boundaries. CONCLUSIONS: Anaemia control measures in Malawi, Tanzania and Uganda need to account for internal spatial heterogeneity evident in these countries. Efforts in assessing the local district-specific causes of childhood anaemia within each country should be focused on

Cochlear function in patients with chronic kidney disease

Objective: To evaluate cochlear functioning in patients (18 - 45 years old) with varying stages of chronic kidney disease (CKD). Using purposive sampling, 50 participants, 10 in each of the 5 stages of CKD, were selected and underwent pure tone audiometric testing and distortion product otoacoustic emissions (DPOAEs). Results: Significant differences (p<0.05) were found between pure tone audiometry and DPOAEs in detecting early cochlear dysfunction in the high-frequency range in stages 3 (6 000/5 000 Hz; p=0.00), 4 (6 000/5 000 Hz; p<0.03) and 5 (4 000/3 333 Hz; p<0.01, 8 000/6 667 Hz:p<0.05) with DPOAEs being more sensitive in identifying early cochlear dysfunction. Patients in stages 1 and 2 presented with normal puretone thresholds and DPOAEs, suggesting that cochlear functioning in these patients was normal. Early cochlear dysfunction, thereby indicating a subclinical hearing loss, was identified in stages 3, 4 and 5 by DPOAE testing. In addition, blood test results, drug intake and concomitant conditions were recorded and analysed which suggested a relationship between reduced cochlear functioning and increased electrolyte levels, treatment regimens and concomitant conditions. Conclusion: Participants in the later stages of CKD presented with early cochlear dysfunction, presenting with subclinical hearing loss. It was postulated that this subclinical hearing loss resulted from a combination of electrolytic, urea and creatinine imbalances, together with concomitant medical conditions and ototoxic drug intake. It was concluded that audiological monitoring be included in the management of patients with CKD and that DPOAEs be introduced as part of the test battery to monitor cochlear function in patients with varying degrees of CKD

A maximum likelihood estimation procedure for binary data from cross-over studies

A maximum likelihood estimation procedure is presented for the expected frequencies when modelling binary data from two-period cross-over studies. This procedure provides a simple approach to parameter estimation in models for binary data from cross-over experiments, and in particular for a log-nonlinear model proposed by Becker and Balagtas (1993).http://www.sastat.org.za/journal.ht

The evaluation of exposure risks for natural transmission of scrapie within an infected flock

Background: Although the epidemiology of scrapie has been broadly understood for many years, attempts to introduce voluntary or compulsory controls to eradicate the disease have frequently failed. Lack of precision in defining the risk factors on farm has been one of the challenges to designing control strategies. This study attempted to define which parts of the annual flock management cycle represented the greatest risk of infection to naive lambs exposed to the farm environment at different times.Results: In VRQ/VRQ lambs exposed to infected sheep at pasture or during lambing, and exposed to the buildings in which lambing took place, the attack rate was high and survival times were short. Where exposure was to pasture alone the number of sheep affected in each experimental group was reduced, and survival times were longer and related to length of exposure.Conclusion: At the flock level, eradication and control strategies for scrapie must take into account the need to decontaminate buildings used for lambing, and to reduce (or prevent) the exposure of lambs to infected sheep, especially in the later stages of incubation, and at lambing. The potential for environmental contamination from pasture should also be considered. Genotype selection may still prove to be the only viable tool to prevent infection from contaminated pasture, reduce environmental contamination and limit direct transmission from sheep to sheep

Counteractive effects of antenatal glucocorticoid treatment on D1 receptor modulation of spatial working memory

RATIONALE: Antenatal exposure to the glucocorticoid dexamethasone dramatically increases the number of mesencephalic dopaminergic neurons in rat offspring. However, the consequences of this expansion in midbrain dopamine (DA) neurons for behavioural processes in adulthood are poorly understood, including working memory that depends on DA transmission in the prefrontal cortex (PFC). OBJECTIVES: We therefore investigated the influence of antenatal glucocorticoid treatment (AGT) on the modulation of spatial working memory by a D1 receptor agonist and on D1 receptor binding and DA content in the PFC and striatum. METHODS: Pregnant rats received AGT on gestational days 16-19 by adding dexamethasone to their drinking water. Male offspring reared to adulthood were trained on a delayed alternation spatial working memory task and administered the partial D1 agonist SKF38393 (0.3-3 mg/kg) by systemic injection. In separate groups of control and AGT animals, D1 receptor binding and DA content were measured post-mortem in the PFC and striatum. RESULTS: SKF38393 impaired spatial working memory performance in control rats but had no effect in AGT rats. D1 binding was significantly reduced in the anterior cingulate cortex, prelimbic cortex, dorsal striatum and ventral pallidum of AGT rats compared with control animals. However, AGT had no significant effect on brain monoamine levels. CONCLUSIONS: These findings demonstrate that D1 receptors in corticostriatal circuitry down-regulate in response to AGT. This compensatory effect in D1 receptors may result from increased DA-ergic tone in AGT rats and underlie the resilience of these animals to the disruptive effects of D1 receptor activation on spatial working memory

Crop Updates 2005 - Lupins and Pulses

This session covers sixty five papers from different authors: 1. 2004 LUPIN AND PULSE INDUSTRY HIGHLIGHTS, Peter White Department of Agriculture 2. BACKGROUND, Peter White Department of Agriculture 2004 REGIONAL ROUNDUP 3. Northern Agricultural Region, Martin Harries, Department of Agriculture 4. Central Agricultural Region, Ian Pritchard, Department of Agriculture 5. Great Southern and Lakes, Rodger Beermier, Department of Agriculture 6. Esperance Port Zone, Mark Seymour, Department of Agriculture, and David Syme, The Grain Pool of WA LUPIN AND PULSE PRODUCTION AGRONOMY AND GENETIC IMPROVEMENT 7. Lupin, Martin Harries, Department of Agriculture 8. Narrow-leafed lupin breeding, Bevan Buirchell, Department of Agriculture 9. Yellow lupin breeding in Western Australia, Kedar Adhikari, Mark Sweetingham and Bevan Buirchell, Department of Agriculture 10. WALAB2000 - First Anthracnose resistant albus lupins, Kedar Adhikari, Bevan Buirchell, MarkSweetingham and Geoff Thomas, Department of Agriculture 11. Improving lupin grain quality and yield through genetic manipulation of key physiological traits, Jon Clements1 and Bevan Buirchell2,1CLIMA, The University of Western Australia 2Department of Agriculture 12. Lupin alkaloids in four Australian species, Shao Fang Wang, Chemistry Centre (WA), CLIMA, The University of Western Australia 13. Improving lupin tolerance to herbicides of metribuzin, isoxaflutole and carfentrazone-ethyl, Ping Si1, Mark Sweetingham12, Bevan Buirchell12, David Bowran2 and Huaan Yang12 , 1CLIMA, The University of Western Australia, 2Department of Agriculture 14. Combined cultural and shielded sprayer herbicide application for weed management, Martin Harries and Mike Baker Department of Agriculture 15. Field testing of lupin seed of various sources with and without post maturity, pre harvest rain for field establishment, Martin Harries, Wayne Parker, Mike Baker, Department of Agriculture 16. Lupin seed rate by wide row spacing, Martin Harries, Bob French, Damien Owen D’arcy, Department of Agriculture 17. How environment influences row spacing response in lupins, Bob French, Department of Agriculture 18. The effect of wider row spacing on lupin architecture, growth and nutrient uptake dynamics, Bill Bowden and Craig Scanlan, Department of Agriculture 19. Fertiliser placement and application rate in wide rows, Martin Harries, Damien Owen D’arcy, Department of Agriculture 20. The pros and cons of cowing lupins in ‘wide’ rows, Wayne Parker, Bob French and Martin Harries, Department of Agriculture 21. Investigation into the influence of row orientation in lupin crops, Jeff Russell1 and Angie Roe2, 1Department of Agriculture, 2Farm Focus Consultants 22. Making the most of Mandelup, Greg Shea and Chris Matthews, Department of Agriculture 23. The effect of wild radish density and lupin cultivars on their competition at Merredin, Shahab Pathan, Abul Hashem and Bob French, Department of Agriculture 24. The potential of pearl lupin (Lupinus mutabilis) for southern Australia, Jon Clements1, Mark Sweetingham2, Bevan Buirchell2, Sofia Sipsas2, Geoff Thomas2, John Quealy1, Roger Jones2, Clive Francis1, Colin Smith2 and Gordon Francis1, 1CLIMA, University of Western Australia 2Department of Agriculture 25. Field pea, Mark Seymour, Department of Agriculture 26. Breeding highlights, Tanveer. Khan and Bob French, Department of Agriculture 27. Variety evaluation, Tanveer Khan, Kerry Regan, Jenny Garlinge and Rod Hunter, Department of Agriculture 28. Large scale field pea variety trials, Martin Harries, Department of Agriculture 29. Kaspa demonstrations, Rodger Beermier, Mark Seymour, Ian Pritchard, Graham Mussell, Department of Agriculture 30. Field pea harvesting demonstration at Merredin, Glen Riethmuller, Greg Shea and Bob French, Department of Agriculture 31. Does Kaspa respond differently to disease, fungicides, time of sowing or seed rate, Mark Seymour, Department of Agriculture 32. Field pea response to foliar Manganese in mallee district, Mark Seymour, Department of Agriculture 33. Kaspa harvesting observations 2004, Mark Seymour, Ian Pritchard, Glen Riethmuller, Department of Agriculture 34. ‘Blackspot Manager’ for understanding blackspot of peas and ascochyta blight management, Moin Salam and Jean Galloway, Department of Agriculture 35. 250,000 ha of field pea in WA – Is it sustainable? Larn McMurray1 and Mark Seymour2, 1South Australian Research and Development Institute, 2Department of Agriculture 36. Desi chickpea, Wayne Parker, Department of Agriculture 37. Breeding highlights, Tanveer Khan1,2 and Kadambot Siddique2,1Department of Agriculture, 2CLIMA, The University of Western Australia 38. Variety evaluation, Tanveer Khan, Kerry Regan, Jenny Garlinge and Rod Hunter, Department of Agriculture 39. Large scale variety testing of desi chickpeas, Martin Harries, Greg Shea, Mike Baker, Dirranie Kirby, Department of Agriculture 40. Desi variety chickpea trial, Martin Harries and Murray Blyth, Department of Agriculture 41. Seeding rates and row spacing of chickpea desi, Martin Harries, MurrayBlyth, Damien Owen D’arcy, Department of Agriculture 42. Molecular characterisation of chickpea wild relatives, Fucheng Shan, Heather Clarke and Kadambot Siddique, CLIMA, The University of Western Australia 43. Plant phosphorus status has a limited influence on the concentration of phosphorus-mobilising carboxylates in the rhizosphere of chickpea, Madeleine Wouterlood, Hans Lambers and Erik Veneklaas, The University of Western Australia 44. Kabuli chickpea, Kerry Regan, Department of Agriculture, and CLIMA, The University of Western Australia 45. ‘Kimberly Large’ A high quality and high yielding new variety for the Ord River Irrigation Area, Kerry Regan1,2, Kadambot Siddique2, Peter White1,2, Peter Smith1 and Gae Plunkett1,1Department of Agriculture, 2CLIMA, University of Western Australia 46. Development of ascochyta resistant and high quality varieties for Australia, Kadambot Siddique1, Kerry Regan1,2, Tim Pope1 and Mike Baker2, 1CLIMA, The University of Western Australia 2Department of Agriculture 47. Towards double haploids in chickpeas and field pea, Janine Croser, Julia Wilson and Kadambot Siddique, CLIMA, The University of Western Australia 48. Crossing chickpea with wild Cicer relatives to introduce resistance to disease and tolerance to environmental stress, Heather Clarke and Kadambot Siddique, CLIMA, The University of Western Australia 49. Faba bean, Peter White, Department of Agriculture 50. Germplasm evaluation, Peter White1,2, Kerry Regan1,2, Tim Pope2, Martin Harries1, Mark Seymour1, Rodger Beermier1 and Leanne Young1, 1Department of Agriculture, 2CLIMA, The University of Western Australia 51. Lentil, Kerry Regan, Department of Agriculture, and CLIMA, The University of Western Australia 52. Variety and germplasm evaluation, Kerry Regan1,2, Tim Pope2, Leanne Young1, Martin Harries1, Murray Blyth1 and Michael Materne3, 1Department of Agriculture, 2CLIMA, University of Western Australia, 3Department of Primary Industries, Victoria 53. Lathyrus species, Kadambot Siddique1, Kerry Regan2, and Colin Hanbury2, 1CLIMA, the University of Western Australia, 2Department of Agricultur

The impact of missing data on clinical trials : a re-analysis of a placebo controlled trial of Hypericum perforatum (St Johns wort) and sertraline in major depressive disorder.

CAPRISA, 2013.Rationale and objective Hypericum perforatum (St John's wort) is used to treat depression, but the effectiveness has not been established. Recent guidelines described the analysis of clinical trials with missing data, inspiring the reanalysis of this trial using proper missing data methods. The objective was to determine whether hypericum was superior to placebo in treating major depression. Methods A placebo-controlled, randomized clinical trial was conducted for 8 weeks to determine the effectiveness of hypericum or sertraline in reducing depression, measured using the Hamilton depression scale. We performed sensitivity analyses under different assumptions about the missing data process. Results Three hundred forty participants were randomized, with 28 % lost to follow-up. The missing data mechanism was not missing completely at random. Under missing at random assumptions, some sensitivity analyses found no difference between either treatment arm and placebo, while some sensitivity analyses found a significant difference from baseline to week 8 between sertraline and placebo (−1.28, 95 % credible interval [−2.48; −0.08]), but not between hypericum and placebo (0.56, [−0.64;1.76]). The results were similar when the missing data process was assumed to be missing not at random. Conclusions There is no difference between hypericum and placebo, regardless of the assumption about the missing data process. There is a significant difference between sertraline and placebo with some statistical methods used. It is important to conduct an analysis that takes account of missing data using valid statistically principled methods. The assumptions about the missing data process could influence the results

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead