Predicting off-site deposition of spray drift from horticultural spraying through porous barriers on soil and plant surfaces

New Zealand is a recognised leader in horticultural practices which include the use of boundary shelterbelts around orchards. These shelterbelts were primarily established to provide protection to the crop but are also an effective means of ameliorating agrichemical spray drift that may arise from the crop production area. Shelterbelt structure ranges from large trees (ranging from broad leaf to needle in structure) to hedgerows and artificial netting. The efficiency of the shelterbelt in capturing spray drift is known to depend on factors such as spray drift droplet size, wind velocity and the vegetation structure. However more specific information and models are required to define the capture efficiency to form part of a comprehensive spray drift management system

The shelf life of wine

The aim of this project was to investigate and develop models for the shelf life of bottled wine and, in particular, the effects of elevated temperatures to the ageing process. The problem was divided into three sub-problems. First, calculations were made to describe the temperature of wine in a single bottle when subjected to an elevated external temperature, and then this was extended to pallets of cartons of wine. Second, equations were derived for the gas flow through the cork when a wine bottle is subject to oscillatory external temperatures, as is common in a domestic storage situation. Third, the temperature dependent reaction rates of the wine ageing process were considered and calculations performed on how elevated decrease shelf life. Suggestions were made as to relatively simple experiments that can be performed to test the models presented here

How much do delayed health care seeking, delayed care provision and diversion from primary care contribute to the transmission of STIs

Objectives: To explore the changing pattern of condom use from 1990 to 2000; to identify sociodemographic and behavioural factors associated with condom use; and reasons for condom use in 2000. Methods: Large probability sample surveys administered among those resident in Britain aged 16–44 (n = 13 765 in 1990, n = 11 161 in 2000). Face to face interviews with self completion components collected sociodemographic, behavioural, and attitudinal data. Results: Condom use in the past year among sexually active 16–24 year old men increased from 61.0% in 1990 to 82.1% in 2000 (p<0.0001), and from 42.0% to 63.2% (p<0.0001) among women of the same age, with smaller increases among older age groups. Among individuals reporting at least two partners in the previous 4 week period, approximately two thirds reported inconsistent or no condom use (63.1% (95% CI 55.9% to 69.8%) of the men and 68.5% (95% CI 57.6% to 77.7%) of the women). Conclusions: Rates of condom use increased substantially between 1990 and 2000, particularly among young people. However, inconsistent condom use by individuals with high rates of partner acquisition may contribute significantly to the recent resurgence in STIs. This group is an important target for intensive and specific sexual health interventions

Pandemic (H1N1) 2009 influenza community transmission was established in one Australian state when the virus was first identified in North America

BACKGROUND In mid-June 2009 the State of Victoria in Australia appeared to have the highest notification rate of pandemic (H1N1) 2009 influenza in the world. We hypothesise that this was because community transmission of pandemic influenza was already well established in Victoria at the time testing for the novel virus commenced. In contrast, this was not true for the pandemic in other parts of Australia, including Western Australia (WA). METHODS We used data from detailed case follow-up of patients with confirmed infection in Victoria and WA to demonstrate the difference in the pandemic curve in two Australian states on opposite sides of the continent. We modelled the pandemic in both states, using a susceptible-infected-removed model with Bayesian inference accounting for imported cases. RESULTS Epidemic transmission occurred earlier in Victoria and later in WA. Only 5% of the first 100 Victorian cases were not locally acquired and three of these were brothers in one family. By contrast, 53% of the first 102 cases in WA were associated with importation from Victoria. Using plausible model input data, estimation of the effective reproductive number for the Victorian epidemic required us to invoke an earlier date for commencement of transmission to explain the observed data. This was not required in modelling the epidemic in WA. CONCLUSION Strong circumstantial evidence, supported by modelling, suggests community transmission of pandemic influenza was well established in Victoria, but not in WA, at the time testing for the novel virus commenced in Australia. The virus is likely to have entered Victoria and already become established around the time it was first identified in the US and Mexico

Searching for Sharp Drops in the Incidence of Pandemic A/H1N1 Influenza by Single Year of Age

BACKGROUND During the 2009 H1N1 pandemic (pH1N1), morbidity and mortality sparing was observed among the elderly population; it was hypothesized that this age group benefited from immunity to pH1N1 due to cross-reactive antibodies generated from prior infection with antigenically similar influenza viruses. Evidence from serologic studies and genetic similarities between pH1N1 and historical influenza viruses suggest that the incidence of pH1N1 cases should drop markedly in age cohorts born prior to the disappearance of H1N1 in 1957, namely those at least 52-53 years old in 2009, but the precise range of ages affected has not been delineated. METHODS AND FINDINGS To test for any age-associated discontinuities in pH1N1 incidence, we aggregated laboratory-confirmed pH1N1 case data from 8 jurisdictions in 7 countries, stratified by single year of age, sex (when available), and hospitalization status. Using single year of age population denominators, we generated smoothed curves of the weighted risk ratio of pH1N1 incidence, and looked for sharp drops at varying age bandwidths, defined as a significantly negative second derivative. Analyses stratified by hospitalization status and sex were used to test alternative explanations for observed discontinuities. We found that the risk of laboratory-confirmed infection with pH1N1 declines with age, but that there was a statistically significant leveling off or increase in risk from about 45 to 50 years of age, after which a sharp drop in risk occurs until the late fifties. This trend was more pronounced in hospitalized cases and in women and was independent of the choice in smoothing parameters. The age range at which the decline in risk accelerates corresponds to the cohort born between 1951-1959 (hospitalized) and 1953-1960 (not hospitalized). CONCLUSIONS The reduced incidence of pH1N1 disease in older individuals shows a detailed age-specific pattern consistent with protection conferred by exposure to influenza A/H1N1 viruses circulating before 1957.The project described was supported by the National Institute Of General Medical Sciences [Award Number U54GM088558], http://www.nigms.nih. gov/. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute Of General Medical Sciences or the National Institutes of Health. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Searching for Sharp Drops in the Incidence of Pandemic A/H1N1 Influenza by Single Year of Age

Background: During the 2009 H1N1 pandemic (pH1N1), morbidity and mortality sparing was observed among the elderly population; it was hypothesized that this age group benefited from immunity to pH1N1 due to cross-reactive antibodies generated from prior infection with antigenically similar influenza viruses. Evidence from serologic studies and genetic similarities between pH1N1 and historical influenza viruses suggest that the incidence of pH1N1 cases should drop markedly in age cohorts born prior to the disappearance of H1N1 in 1957, namely those at least 52–53 years old in 2009, but the precise range of ages affected has not been delineated. Methods and Findings: To test for any age-associated discontinuities in pH1N1 incidence, we aggregated laboratory-confirmed pH1N1 case data from 8 jurisdictions in 7 countries, stratified by single year of age, sex (when available), and hospitalization status. Using single year of age population denominators, we generated smoothed curves of the weighted risk ratio of pH1N1 incidence, and looked for sharp drops at varying age bandwidths, defined as a significantly negative second derivative. Analyses stratified by hospitalization status and sex were used to test alternative explanations for observed discontinuities. We found that the risk of laboratory-confirmed infection with pH1N1 declines with age, but that there was a statistically significant leveling off or increase in risk from about 45 to 50 years of age, after which a sharp drop in risk occurs until the late fifties. This trend was more pronounced in hospitalized cases and in women and was independent of the choice in smoothing parameters. The age range at which the decline in risk accelerates corresponds to the cohort born between 1951–1959 (hospitalized) and 1953–1960 (not hospitalized). Conclusions: The reduced incidence of pH1N1 disease in older individuals shows a detailed age-specific pattern consistent with protection conferred by exposure to influenza A/H1N1 viruses circulating before 1957

Searching for sharp drops in the incidence of pandemic A/H1N1 Influenza by single year of age

Fil: Hartman Jacobs, Jessica. Harvard School of Public Health. Department of Epidemiology; Estados Unidos.Fil: Archer, Brett Nicholas. National Health Laboratory Service. National Institute for Communicable Diseases; Sudáfrica.Fil: Baker, Michael G. University of Otago. Department of Public Health; Nueva Zelanda.Fil: Cowling, Benjamin J. The University of Hong Kong. School of Public Health; China.Fil: Heffernan, Richard T. Wisconsin Department of Health Services. Division of Public Health; Estados Unidos.Fil. Mercer, Geoff. Australian National University. National Centre for Epidemiology and Population Health; Australia.Fil: Uez, Osvaldo. ANLIS Dr.C.G.Malbrán. Instituto Nacional de Epidemiología; Argentina.Fil: Hanshaoworakul, Wanna. Ministry of Public Health. Department of Disease Control; Tailandia.Fil: Viboud, Cécile. National Institutes of Health. Division of International Epidemiology and Population Studies; Estados Unidos.Fil: Schwartz, Joel. Harvard School of Public Health. Department of Epidemiology; Estados Unidos.Fil: Tchetgen Tchetgen, Eric. Harvard School of Public Health. Department of Epidemiology; Estados Unidos.Fil: Lipsitch, Marc. Harvard School of Public Health. Department of Epidemiology; Estados Unidos.BackgroundDuring the 2009 H1N1 pandemic (pH1N1), morbidity and mortality sparing was observed among the elderly population; it was hypothesized that this age group benefited from immunity to pH1N1 due to cross-reactive antibodies generated from prior infection with antigenically similar influenza viruses. Evidence from serologic studies and genetic similarities between pH1N1 and historical influenza viruses suggest that the incidence of pH1N1 cases should drop markedly in age cohorts born prior to the disappearance of H1N1 in 1957, namely those at least 52–53 years old in 2009, but the precise range of ages affected has not been delineated.Methods and FindingsTo test for any age-associated discontinuities in pH1N1 incidence, we aggregated laboratory-confirmed pH1N1 case data from 8 jurisdictions in 7 countries, stratified by single year of age, sex (when available), and hospitalization status. Using single year of age population denominators, we generated smoothed curves of the weighted risk ratio of pH1N1 incidence, and looked for sharp drops at varying age bandwidths, defined as a significantly negative second derivative. Analyses stratified by hospitalization status and sex were used to test alternative explanations for observed discontinuities. We found that the risk of laboratory-confirmed infection with pH1N1 declines with age, but that there was a statistically significant leveling off or increase in risk from about 45 to 50 years of age, after which a sharp drop in risk occurs until the late fifties. This trend was more pronounced in hospitalized cases and in women and was independent of the choice in smoothing parameters. The age range at which the decline in risk accelerates corresponds to the cohort born between 1951–1959 (hospitalized) and 1953–1960 (not hospitalized).ConclusionsThe reduced incidence of pH1N1 disease in older individuals shows a detailed age-specific pattern consistent with protection conferred by exposure to influenza A/H1N1 viruses circulating before 1957

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

The contribution of X-linked coding variation to severe developmental disorders

Abstract: Over 130 X-linked genes have been robustly associated with developmental disorders, and X-linked causes have been hypothesised to underlie the higher developmental disorder rates in males. Here, we evaluate the burden of X-linked coding variation in 11,044 developmental disorder patients, and find a similar rate of X-linked causes in males and females (6.0% and 6.9%, respectively), indicating that such variants do not account for the 1.4-fold male bias. We develop an improved strategy to detect X-linked developmental disorders and identify 23 significant genes, all of which were previously known, consistent with our inference that the vast majority of the X-linked burden is in known developmental disorder-associated genes. Importantly, we estimate that, in male probands, only 13% of inherited rare missense variants in known developmental disorder-associated genes are likely to be pathogenic. Our results demonstrate that statistical analysis of large datasets can refine our understanding of modes of inheritance for individual X-linked disorders