93 research outputs found
Urban Primacy And Regional Economic Development In The Third World
A Geographical Proceedings article.Many developing countries are now being persuaded that an appropriate urbanization strategy could provide them with one of the means of achieving the modernization of their societies (Mabogunje 1973). Unfortunately the information upon which to base sound urbanization policies is invariably lacking, and frequently assumptions are made without the relevant questions being asked, let alone answered. In this paper four critical questions are asked, and an attempt is made to suggest a framework within which answers may be sought. It is recognized that any answers will be at best tentative, given the current state of research into what is an immensely complex subject. But it is also true that Third World planners cannot await the conclusions of present and future generations of researchers: they need guidelines, however inadequately based, for immediate policy formulation
Co-infection status of novel parvovirus’s (PPV2 to 4) with porcine circovirus 2 in porcine respiratory disease complex and porcine circovirus-associated disease from 1997 to 2012
Publication history: Accepted - 12 September 2020; Published online - 18 October 2020.As global pig health diseases, porcine respiratory disease complex (PRDC) and porcine
circovirus-associated disease (PCVAD) generate substantial economic losses despite
pigs been vaccinated against the primary causative virus, highlighting the importance
of understanding virome interactions and specifically co-factor infections. Established
primary endemic pathogens for PRDC include porcine circovirus 2 (PCV2), porcine
reproductive and respiratory syndrome virus (PRRSv) and swine influenza virus (SIV),
and PCV2 aetiology in interaction with other co-infecting viruses can result in PCVAD.
Porcine parvovirus (PPV) 1 is a well-characterized virus with an available vaccine preventing
reproductive failure in sows. However, whilst novel PPV 2 to 7 viruses have been
identified since 2001, their viral pathogenic potential in clinical and subclinical disease
remains to be determined. Therefore, this study has sought to develop a better understanding
of their potential role as associated co-infections in PRDC and PCVAD by examining
archival samples for the presence of PCV2 and the novel parvoviruses PPV2-4
from clinically diseased pigs across production age stages. Epidemiologically, the novel
PPV2 was found to be the most prevalent within the fattener age group with PPV2-4
statistically associated with pig respiratory disease and enteric ulcers. Additionally, statistical
modelling by latent class analysis (LCA) on veterinary pathology scored pigs found
a clustering co-factor association between PPV2 and PCV2, suggesting the novel PPV
may be involved in PRDC and PCVAD. Phylogenetic analysis of novel PPVs revealed the
PPV2 capsid evolution to be diverged from the original strains with a low nucleotide homology
of 88%–96% between two distinct clades. These findings determine that novel
PPV 2–4 viruses are statistically associated as co-infectors in a diseased pig population,
and significantly detected PPV2 clustering co-infection frequency with PCV2 in PRDC
and PCVAD diseased pigs through LCA analysis
Avian Influenza Risk Perception, Hong Kong
A telephone survey of 986 Hong Kong households determined exposure and risk perception of avian influenza from live chicken sales. Householders bought 38,370,000 live chickens; 11% touched them when buying, generating 4,220,000 exposures annually; 36% (95% confidence interval [CI] 33%–39%) perceived this as risky, 9% (7%–11%) estimated >50% likelihood of resultant sickness, whereas 46% (43%–49%) said friends worried about such sickness. Recent China travel (adjusted odds ratio 0.35; CI 0.13–0.91), traditional beliefs (1.20, 1.06–1.13), willingness to change (0.29, 0.11–0.81) and believing cooking protects against avian influenza (8.66, 1.61-46.68) predicted buying. Birth in China (2.79, 1.43–5.44) or overseas (4.23, 1.43–12.53) and unemployment (3.87, 1.24–12.07) predicted touching. Age, avian influenza contagion worries, husbandry threat, avian influenza threat, and avian influenza anxiety predicted perceived sickness risk. High population exposures to live chickens and low perceived risk are potentially important health threats in avian influenza
Determining gene expression on a single pair of microarrays
<p>Abstract</p> <p>Background</p> <p>In microarray experiments the numbers of replicates are often limited due to factors such as cost, availability of sample or poor hybridization. There are currently few choices for the analysis of a pair of microarrays where N = 1 in each condition. In this paper, we demonstrate the effectiveness of a new algorithm called PINC (PINC is Not Cyber-T) that can analyze Affymetrix microarray experiments.</p> <p>Results</p> <p>PINC treats each pair of probes within a probeset as an independent measure of gene expression using the Bayesian framework of the Cyber-T algorithm and then assigns a corrected p-value for each gene comparison.</p> <p>The p-values generated by PINC accurately control False Discovery rate on Affymetrix control data sets, but are small enough that family-wise error rates (such as the Holm's step down method) can be used as a conservative alternative to false discovery rate with little loss of sensitivity on control data sets.</p> <p>Conclusion</p> <p>PINC outperforms previously published methods for determining differentially expressed genes when comparing Affymetrix microarrays with N = 1 in each condition. When applied to biological samples, PINC can be used to assess the degree of variability observed among biological replicates in addition to analyzing isolated pairs of microarrays.</p
Reanalysis and Simulation Suggest a Phylogenetic Microarray Does Not Accurately Profile Microbial Communities
The second generation (G2) PhyloChip is designed to detect over 8700 bacteria and archaeal and has been used over 50 publications and conference presentations. Many of those publications reveal that the PhyloChip measures of species richness greatly exceed statistical estimates of richness based on other methods. An examination of probes downloaded from Greengenes suggested that the system may have the potential to distort the observed community structure. This may be due to the sharing of probes by taxa; more than 21% of the taxa in that downloaded data have no unique probes. In-silico simulations using these data showed that a population of 64 taxa representing a typical anaerobic subterranean community returned 96 different taxa, including 15 families incorrectly called present and 19 families incorrectly called absent. A study of nasal and oropharyngeal microbial communities by Lemon et al (2010) found some 1325 taxa using the G2 PhyloChip, however, about 950 of these taxa have, in the downloaded data, no unique probes and cannot be definitively called present. Finally, data from Brodie et al (2007), when re-examined, indicate that the abundance of the majority of detected taxa, are highly correlated with one another, suggesting that many probe sets do not act independently. Based on our analyses of downloaded data, we conclude that outputs from the G2 PhyloChip should be treated with some caution, and that the presence of taxa represented solely by non-unique probes be independently verified
Beliefs about weight and breast cancer: An interview study with high risk women following a 12 month weight loss intervention
This is an Version of Record of an article published by BioMed Central in Hereditary Cancer in Clinical Practice on 9 January 2015, available online: http://www.hccpjournal.com/content/13/1/1 This is an Open Access article distributed under the terms of the Creative Commons Attribution License(http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and
reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Breast cancer is the most common cancer in the UK. Lifestyle factors including excess weight contribute to risk of developing the disease. Whilst the exact links between weight and breast cancer are still emerging, it is imperative to explore how women understand these links and if these beliefs impact on successful behaviour change. Overweight/obese premenopausal women (aged 35–45) with a family history of breast cancer (lifetime risk 17–40%) were invited to a semi-structured interview following their participation in a 12 month weight loss intervention aimed at reducing their risk of breast cancer. Interviews were carried out with 9 women who successfully achieved ≥5% weight loss and 11 who were unsuccessful. Data were transcribed verbatim and analysed using thematic analysis. Three themes were developed from the analysis. The first theme how women construct and understand links between weight and breast cancer risk is composed of two subthemes, the construction of weight and breast cancer risk and making sense of weight and breast cancer risk. The second theme - motivation and adherence to weight loss interventions - explains that breast cancer risk can be a motivating factor for adherence to a weight loss intervention. The final theme, acceptance of personal responsibility for health is composed of two subthemes responsibility for one’s own health and responsibility for family health through making sensible lifestyle choices.Beliefs about weight and breast cancer risk were informed by social networks, media reports and personal experiences of significant others diagnosed with breast cancer. Our study has highlighted common doubts, anxieties and questions and the importance of providing a credible rationale for weight control and weight loss which addresses individual concerns
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The impact of alternative trait-scaling hypotheses for the maximum photosynthetic carboxylation rate (Vcmax) on global gross primary production
The maximum photosynthetic carboxylation rate (Vcmax) is an influential plant trait that has multiple scaling hypotheses, which is a source of uncertainty in predictive understanding of global gross primary production (GPP).
Four trait-scaling hypotheses (plant functional type, nutrient limitation, environmental filtering, and plant plasticity) with nine specific implementations were used to predict global Vcmax distributions and their impact on global GPP in the Sheffield Dynamic Global Vegetation Model (SDGVM).
Global GPP varied from 108.1 to 128.2 PgC yr−1, 65% of the range of a recent model intercomparison of global GPP. The variation in GPP propagated through to a 27% coefficient of variation in net biome productivity (NBP). All hypotheses produced global GPP that was highly correlated (r = 0.85–0.91) with three proxies of global GPP.
Plant functional type-based nutrient limitation, underpinned by a core SDGVM hypothesis that plant nitrogen (N) status is inversely related to increasing costs of N acquisition with increasing soil carbon, adequately reproduced global GPP distributions. Further improvement could be achieved with accurate representation of water sensitivity and agriculture in SDGVM. Mismatch between environmental filtering (the most data-driven hypothesis) and GPP suggested that greater effort is needed understand Vcmax variation in the field, particularly in northern latitudes
Building Dynamic Service Analytics Capabilities for the Digital Marketplace
Service firms are now interacting with customers through a multitude of channels or touchpoints. This progression into the digital realm is leading to an explosion of data, and warranting advanced analytic methods to manage service systems. Known as big data analytics, these methods harness insights to deliver, serve, and enhance the customer experience in the digital marketplace. Although global economies are becoming service-oriented, little attention is paid to the role of analytics in service systems. As such, drawing on a systematic literature review and thematic analysis of 30 in-depth interviews, this study aims to understand the nature of service analytics to identify its capability dimensions. Integrating the diverse areas of research on service systems, big data and dynamic capability theories, we propose a dynamic service analytics capabilities (DSAC) framework consisting of management, technology, talent, data governance, model development, and service innovation capability. We also propose a future research agenda to advance DSAC research for the emerging service systems in the digital marketplace
Nutrient Administration and Resistance Training
Skeletal muscle tissue is tightly regulated throughout our bodies by balancing its synthesis and breakdown. Many factors are known to exist that cause profound changes on the overall status of skeletal muscle, some of which include exercise, nutrition, hormonal influences and disease. Muscle hypertrophy results when protein synthesis is greater than protein breakdown. Resistance training is a popular form of exercise that has been shown to increase muscular strength and muscular hypertrophy. In general, resistance training causes a stimulation of protein synthesis as well as an increase in protein breakdown, resulting in a negative balance of protein. Providing nutrients, specifically amino acids, helps to stimulate protein synthesis and improve the overall net balance of protein. Strategies to increase the concentration and availability of amino acids after resistance exercise are of great interest and have been shown to effectively increase overall protein synthesis. [1-3] After exercise, providing carbohydrate has been shown to mildly stimulate protein synthesis while addition of free amino acids prior to and after exercise, specifically essential amino acids, causes a rapid pronounced increase in protein synthesis as well as protein balance.[1,3] Evidence exists for a dose-response relationship of infused amino acids while no specific regimen exists for optimal dosing upon ingestion. Ingestion of whole or intact protein sources (e.g., protein powders, meal-replacements) has been shown to cause similar improvements in protein balance after resistance exercise when compared to free amino acid supplements. Future research should seek to determine optimal dosing of ingested intact amino acids in addition to identifying the cellular mechanistic machinery (e.g. transcriptional and translational mechanisms) for causing the increase in protein synthesis
A framework for human microbiome research
A variety of microbial communities and their genes (the microbiome) exist throughout the human body, with fundamental roles in human health and disease. The National Institutes of Health (NIH)-funded Human Microbiome Project Consortium has established a population-scale framework to develop metagenomic protocols, resulting in a broad range of quality-controlled resources and data including standardized methods for creating, processing and interpreting distinct types of high-throughput metagenomic data available to the scientific community. Here we present resources from a population of 242 healthy adults sampled at 15 or 18 body sites up to three times, which have generated 5,177 microbial taxonomic profiles from 16S ribosomal RNA genes and over 3.5 terabases of metagenomic sequence so far. In parallel, approximately 800 reference strains isolated from the human body have been sequenced. Collectively, these data represent the largest resource describing the abundance and variety of the human microbiome, while providing a framework for current and future studies
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