4 resultados para Activated partial thromboplastin time (APTT)
em eResearch Archive - Queensland Department of Agriculture
Resumo:
The anti-thrombotic properties of an anthocyanin-rich Queen Garnet plum juice (QGPJ) and anthocyanin-free prune juice (PJ) were studied in this randomised, double-blind, crossover trial. Twenty-one healthy subjects (M = 10, F = 11) consumed QGPJ, PJ or placebo, 200 mL/day for 28-days followed by a 2-week wash-out period. Only QGPJ supplementation inhibited platelet aggregation induced by ADP (<5%, P = 0.02), collagen (<2.7%, P < 0.001) and arachidonic acid (<4%, P < 0.001); reduced platelet activation-dependent surface-marker P-selectin expression of activated de-granulated platelets (<17.2%, P = 0.04); prolonged activated-partial thromboplastin clotting time (>2.1 s, P = 0.03); reduced plasma-fibrinogen (<7.5%, P = 0.02) and malondialdehyde levels, a plasma biomarker of oxidative stress ( P = 0.016). PJ supplementation increased plasma hippuric acid content ( P = 0.018). QGPJ or PJ supplementation did not affect blood cell counts, lipid profile, or inflammation markers. Our findings suggest that QGPJ but not PJ has the potential to significantly attenuate thrombosis by reducing platelet activation/hyper-coagulability and oxidative stress.
Resumo:
The endemic non-pathogenic Australian rabbit calicivirus RCV-A1 is known to provide some cross protection to lethal infection with the closely related Rabbit Haemorrhagic Disease Virus (RHDV). Despite its obvious negative impacts on viral biocontrol of introduced European rabbits in Australia, little is known about the extent and mechanisms of this cross protection. In this study 46 rabbits from a colony naturally infected with RCV-A1 were exposed to RHDV. Survival rates and survival times did not correlate with titres of serum antibodies specific to RCV-A1 or cross reacting to RHDV, but were instead influenced by the time between infection with the two viruses, demonstrating for the first time that the cross protection to lethal RHDV infection is transient. These findings are an important step towards a better understanding of the complex interactions of co-occurring pathogenic and non-pathogenic lagoviruses.
Resumo:
High-throughput techniques are necessary to efficiently screen potential lignocellulosic feedstocks for the production of renewable fuels, chemicals, and bio-based materials, thereby reducing experimental time and expense while supplanting tedious, destructive methods. The ratio of lignin syringyl (S) to guaiacyl (G) monomers has been routinely quantified as a way to probe biomass recalcitrance. Mid-infrared and Raman spectroscopy have been demonstrated to produce robust partial least squares models for the prediction of lignin S/G ratios in a diverse group of Acacia and eucalypt trees. The most accurate Raman model has now been used to predict the S/G ratio from 269 unknown Acacia and eucalypt feedstocks. This study demonstrates the application of a partial least squares model composed of Raman spectral data and lignin S/G ratios measured using pyrolysis/molecular beam mass spectrometry (pyMBMS) for the prediction of S/G ratios in an unknown data set. The predicted S/G ratios calculated by the model were averaged according to plant species, and the means were not found to differ from the pyMBMS ratios when evaluating the mean values of each method within the 95 % confidence interval. Pairwise comparisons within each data set were employed to assess statistical differences between each biomass species. While some pairwise appraisals failed to differentiate between species, Acacias, in both data sets, clearly display significant differences in their S/G composition which distinguish them from eucalypts. This research shows the power of using Raman spectroscopy to supplant tedious, destructive methods for the evaluation of the lignin S/G ratio of diverse plant biomass materials.
Resumo:
High-throughput techniques are necessary to efficiently screen potential lignocellulosic feedstocks for the production of renewable fuels, chemicals, and bio-based materials, thereby reducing experimental time and expense while supplanting tedious, destructive methods. The ratio of lignin syringyl (S) to guaiacyl (G) monomers has been routinely quantified as a way to probe biomass recalcitrance. Mid-infrared and Raman spectroscopy have been demonstrated to produce robust partial least squares models for the prediction of lignin S/G ratios in a diverse group of Acacia and eucalypt trees. The most accurate Raman model has now been used to predict the S/G ratio from 269 unknown Acacia and eucalypt feedstocks. This study demonstrates the application of a partial least squares model composed of Raman spectral data and lignin S/G ratios measured using pyrolysis/molecular beam mass spectrometry (pyMBMS) for the prediction of S/G ratios in an unknown data set. The predicted S/G ratios calculated by the model were averaged according to plant species, and the means were not found to differ from the pyMBMS ratios when evaluating the mean values of each method within the 95 % confidence interval. Pairwise comparisons within each data set were employed to assess statistical differences between each biomass species. While some pairwise appraisals failed to differentiate between species, Acacias, in both data sets, clearly display significant differences in their S/G composition which distinguish them from eucalypts. This research shows the power of using Raman spectroscopy to supplant tedious, destructive methods for the evaluation of the lignin S/G ratio of diverse plant biomass materials. © 2015, The Author(s).