1,249 research outputs found
Acquisition of growth-inhibitory antibodies against blood-stage Plasmodium falciparum
Background Antibodies that inhibit the growth of blood-stage Plasmodium falciparum may play an important role in acquired and vaccine-induced immunity in humans. However, the acquisition and activity of these antibodies is not well understood. Methods We tested dialysed serum and purified immunoglobulins from Kenyan children and adults for inhibition of P. falciparum blood-stage growth in vitro using different parasite lines. Serum antibodies were measured by ELISA to blood-stage parasite antigens, extracted from P. falciparum schizonts, and to recombinant merozoite surface protein 1 (42 kDa C-terminal fragment, MSP1-42). Results Antibodies to blood-stage antigens present in schizont protein extract and to recombinant MSP1-42 significantly increased with age and were highly correlated. In contrast, growth-inhibitory activity was not strongly associated with age and tended to decline marginally with increasing age and exposure, with young children demonstrating the highest inhibitory activity. Comparison of growth-inhibitory activity among samples collected from the same population at different time points suggested that malaria transmission intensity influenced the level of growth-inhibitory antibodies. Antibodies to recombinant MSP1-42 were not associated with growth inhibition and high immunoglobulin G levels were poorly predictive of inhibitory activity. The level of inhibitory activity against different isolates varied. Conclusions Children can acquire growth-inhibitory antibodies at a young age, but once they are acquired they do not appear to be boosted by on-going exposure. Inhibitory antibodies may play a role in protection from early childhood malaria
The effects of linkage disequilibrium in large scale SNP datasets for MDR
<p>Abstract</p> <p>Background</p> <p>In the analysis of large-scale genomic datasets, an important consideration is the power of analytical methods to identify accurate predictive models of disease. When trying to assess sensitivity from such analytical methods, a confounding factor up to this point has been the presence of linkage disequilibrium (LD). In this study, we examined the effect of LD on the sensitivity of the Multifactor Dimensionality Reduction (MDR) software package.</p> <p>Results</p> <p>Four relative amounts of LD were simulated in multiple one- and two-locus scenarios for which the position of the functional SNP(s) within LD blocks varied. Simulated data was analyzed with MDR to determine the sensitivity of the method in different contexts, where the sensitivity of the method was gauged as the number of times out of 100 that the method identifies the correct one- or two-locus model as the best overall model. As the amount of LD increases, the sensitivity of MDR to detect the correct functional SNP drops but the sensitivity to detect the disease signal and find an indirect association increases.</p> <p>Conclusions</p> <p>Higher levels of LD begin to confound the MDR algorithm and lead to a drop in sensitivity with respect to the identification of a direct association; it does not, however, affect the ability to detect indirect association. Careful examination of the solution models generated by MDR reveals that MDR can identify loci in the correct LD block; though it is not always the functional SNP. As such, the results of MDR analysis in datasets with LD should be carefully examined to consider the underlying LD structure of the dataset.</p
Incorporating prior knowledge improves detection of differences in bacterial growth rate
BACKGROUND: Robust statistical detection of differences in the bacterial growth rate can be challenging, particularly when dealing with small differences or noisy data. The Bayesian approach provides a consistent framework for inferring model parameters and comparing hypotheses. The method captures the full uncertainty of parameter values, whilst making effective use of prior knowledge about a given system to improve estimation. RESULTS: We demonstrated the application of Bayesian analysis to bacterial growth curve comparison. Following extensive testing of the method, the analysis was applied to the large dataset of bacterial responses which are freely available at the web-resource, ComBase. Detection was found to be improved by using prior knowledge from clusters of previously analysed experimental results at similar environmental conditions. A comparison was also made to a more traditional statistical testing method, the F-test, and Bayesian analysis was found to perform more conclusively and to be capable of attributing significance to more subtle differences in growth rate. CONCLUSIONS: We have demonstrated that by making use of existing experimental knowledge, it is possible to significantly improve detection of differences in bacterial growth rate
A patient with bilateral pheochromocytoma as part of a Von Hippel-Lindau (VHL) syndrome type 2C
Timely HAART initiation may pave the way for a better viral control
<p>Abstract</p> <p>Background</p> <p>When to initiate antiretroviral therapy in HIV infected patients is a diffcult clinical decision. Actually, it is still a matter of discussion whether early highly active antiretroviral therapy (HAART) during primary HIV infection may influence the dynamics of the viral rebound, in case of therapy interruption, and overall the main disease course.</p> <p>Methods</p> <p>In this article we use a computational model and clinical data to identify the role of HAART timing on the residual capability to control HIV rebound after treatment suspension. Analyses of clinical data from three groups of patients initiating HAART respectively before seroconversion (very early), during the acute phase (early) and in the chronic phase (late), evidence differences arising from the very early events of the viral infection.</p> <p>Results</p> <p>The computational model allows a fine grain assessment of the impact of HAART timing on the disease outcome, from acute to chronic HIV-1 infection. Both patients' data and computer simulations reveal that HAART timing may indeed affect the HIV control capability after treatment discontinuation. In particular, we find a median time to viral rebound that is significantly longer in very early than in late patients.</p> <p>Conclusions</p> <p>A timing threshold is identified, corresponding to approximately three weeks post-infection, after which the capability to control HIV replication is lost. Conversely, HAART initiation occurring within three weeks from the infection could allow to preserve a significant control capability. This time could be related to the global triggering of uncontrolled immune activation, affecting residual immune competence preservation and HIV reservoir establishment.</p
Social health and change in cognitive capability among older adults:findings from four European longitudinal studies
Introduction: In this study we examine whether social health markers measured at baseline are associated with differences in cognitive capability and in the rate of cognitive decline over an 11-to-18-year period among older adults and compare results across studies. Methods: We applied an integrated data analysis approach to 16,858 participants (mean age 65 years; 56% female) from the National Survey for Health and Development (NSHD), the English Longitudinal Study of Aging (ELSA), the Swedish National Study on Aging and Care in Kungsholmen (SNAC-K), and the Rotterdam Study. We used multilevel models to examine social health in relation to cognitive capability and the rate of cognitive decline. Results: Pooled estimates show distinct relationships between markers of social health and cognitive domains e.g., a large network size (≥6 people vs none) was associated with higher executive function (0.17 SD[95%CI:0.0, 0.34], I2=27%) but not with memory (0.08 SD[95%CI: -0.02, 0.18], I2=19%). We also observed pooled associations between being married or cohabiting, having a large network size and participating in social activities with slower decline in cognitive capability, however estimates were close to zero e.g., 0.01SD/year [95%CI: 0.01 to 0.02] I2=19% for marital status and executive function. There were clear study-specific differences: results for average processing speed were the most homogenous and results for average memory were the most heterogenous. Conclusion: Overall, markers of good social health have a positive association with cognitive capability. However, we found differential associations between specific markers of social health and cognitive domains and differences between studies. These findings highlight the importance of examining between study differences and considering context specificity of findings in developing and deploying any intervention
Stress related epigenetic changes may explain opportunistic success in biological invasions in Antipode mussels
Different environmental factors could induce epigenetic changes, which are likely involved in the biological invasion process. Some of these factors are driven by humans as, for example, the pollution and deliberate or accidental introductions and others are due to natural conditions such as salinity. In this study, we have analysed the relationship between different stress factors: time in the new location, pollution and salinity with the methylation changes that could be involved in the invasive species tolerance to new environments. For this purpose, we have analysed two different mussels’ species, reciprocally introduced in antipode areas: the Mediterranean blue mussel Mytilus galloprovincialis and the New Zealand pygmy mussel Xenostrobus securis, widely recognized invaders outside their native distribution ranges. The demetylathion was higher in more stressed population, supporting the idea of epigenetic is involved in plasticity process. These results can open a new management protocols, using the epigenetic signals as potential pollution monitoring tool. We could use these epigenetic marks to recognise the invasive status in a population and determine potential biopollutants
Assessment of Forest Biomass and Carbon Stocks at Stand Level Using Site-Specific Primary Data to Support Forest Management
To quantify and map woody biomass (WB) and forest carbon (C) stocks, several models were developed. They differ in terms of scale of application, details related to the input data required and outputs provided. Local Authorities, such as Mountain Communities, can be supported in sustainable forest planning and management by providing specific models in which the reference unit is the same as the one reported in the Forest Management Plans (FMP), i.e. the forest stand. In the Lombardy Region (Northern Italy), a few studies were performed to assess WB and forest C stocks, and they were generally based on data coming from regional\u2014or national\u2014forest inventories and remote sensing, without taking into account data collected in the FMPs. For this study, the first version of the stand-level model \u201cWOody biomass and Carbon ASsessment\u201d (WOCAS) for WB and C stocks calculation was improved into a second version (WOCAS v2) and preliminary results about its first application to 2019 forest stands of Valle Camonica District (Lombardy Region) are presented. Since the model WOCAS uses the growing stock as the main driver for the calculation, it can be applied in any other forest area where the same input data are available
On epidemic modeling in real time: An application to the 2009 Novel A (H1N1) influenza outbreak in Canada
<p>Abstract</p> <p>Background</p> <p>Management of emerging infectious diseases such as the 2009 influenza pandemic A (H1N1) poses great challenges for real-time mathematical modeling of disease transmission due to limited information on disease natural history and epidemiology, stochastic variation in the course of epidemics, and changing case definitions and surveillance practices.</p> <p>Findings</p> <p>The Richards model and its variants are used to fit the cumulative epidemic curve for laboratory-confirmed pandemic H1N1 (pH1N1) infections in Canada, made available by the Public Health Agency of Canada (PHAC). The model is used to obtain estimates for turning points in the initial outbreak, the basic reproductive number (R<sub>0</sub>), and for expected final outbreak size in the absence of interventions. Confirmed case data were used to construct a best-fit 2-phase model with three turning points. R<sub>0 </sub>was estimated to be 1.30 (95% CI 1.12-1.47) for the first phase (April 1 to May 4) and 1.35 (95% CI 1.16-1.54) for the second phase (May 4 to June 19). Hospitalization data were also used to fit a 1-phase model with R<sub>0 </sub>= 1.35 (1.20-1.49) and a single turning point of June 11.</p> <p>Conclusions</p> <p>Application of the Richards model to Canadian pH1N1 data shows that detection of turning points is affected by the quality of data available at the time of data usage. Using a Richards model, robust estimates of R<sub>0 </sub>were obtained approximately one month after the initial outbreak in the case of 2009 A (H1N1) in Canada.</p
The Genomics of Speciation in Drosophila: Diversity, Divergence, and Introgression Estimated Using Low-Coverage Genome Sequencing
In nature, closely related species may hybridize while still retaining their distinctive identities. Chromosomal regions that experience reduced recombination in hybrids, such as within inversions, have been hypothesized to contribute to the maintenance of species integrity. Here, we examine genomic sequences from closely related fruit fly taxa of the Drosophila pseudoobscura subgroup to reconstruct their evolutionary histories and past patterns of genic exchange. Partial genomic assemblies were generated from two subspecies of Drosophila pseudoobscura (D. ps.) and an outgroup species, D. miranda. These new assemblies were compared to available assemblies of D. ps. pseudoobscura and D. persimilis, two species with overlapping ranges in western North America. Within inverted regions, nucleotide divergence among each pair of the three species is comparable, whereas divergence between D. ps. pseudoobscura and D. persimilis in non-inverted regions is much lower and closer to levels of intraspecific variation. Using molecular markers flanking each of the major chromosomal inversions, we identify strong crossover suppression in F1 hybrids extending over 2 megabase pairs (Mbp) beyond the inversion breakpoints. These regions of crossover suppression also exhibit the high nucleotide divergence associated with inverted regions. Finally, by comparison to a geographically isolated subspecies, D. ps. bogotana, our results suggest that autosomal gene exchange between the North American species, D. ps. pseudoobscura and D. persimilis, occurred since the split of the subspecies, likely within the last 200,000 years. We conclude that chromosomal rearrangements have been vital to the ongoing persistence of these species despite recent hybridization. Our study serves as a proof-of-principle on how whole genome sequencing can be applied to formulate and test hypotheses about species formation in lesser-known non-model systems
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