855 resultados para Iris Colour Prediction
Resumo:
The objective of the present study was to evaluate the performance of a new bioelectrical impedance instrument, the Soft Tissue Analyzer (STA), which predicts a subject's body composition. A cross-sectional population study in which the impedance of 205 healthy adult subjects was measured using the STA. Extracellular water (ECW) volume (as a percentage of total body water, TBW) and fat-free mass (FFM) were predicted by both the STA and a compartmental model, and compared according to correlation and limits of agreement analysis, with the equivalent data obtained by independent reference methods of measurement (TBW measured by D2O dilution, and FFM measured by dual-energy X-ray absorptiometry). There was a small (2.0 kg) but significant (P < 0.02) difference in mean FFM predicted by the STA, compared with the reference technique in the males, but not in the females (-0.4 kg) or in the combined group (0.8 kg). Both methods were highly correlated. Similarly, small but significant differences for predicted mean ECW volume were observed. The limits of agreement for FFM and ECW were -7.5-9.9 and -4.1-3.0 kg, respectively. Both FFM and ECW (as a percentage of TBW) are well predicted by the STA on a population basis, but the magnitude of the limits of agreement with reference methods may preclude its usefulness for predicting body composition in an individual. In addition, the theoretical basis of an impedance method that does not include a measure of conductor length requires further validation. (C) Elsevier Science Inc. 2000.
Resumo:
A novel MRI method-diffusion tensor imaging-was used to compare the integrity of several white matter fibre tracts in patients with probable Alzheimer's disease. Relative to normal controls, patients with probable Alzheimer's disease showed a highly significant reduction in the integrity of the association white matter fibre tracts, such as the splenium of the corpus callosum, superior longitudinal fasciculus, and cingulum. By contrast, pyramidal tract integrity seemed unchanged. This novel finding is consistent with the clinical presentation of probable Alzheimer's disease, in which global cognitive decline is a more prominent feature than motor disturbance.
Resumo:
Members of the billfish family are highly visual predatory teleosts inhabiting the open ocean. Little is known about their visual abilities in detail, but past studies have indicated that these fishes were:ere likely to be monochromats. This study however, presents evidence of two anatomically distinct cone types in billfish. The cells are arranged in a regular mosaic pattern of single and twin cones as in many fishes, and this arrangement suggests that the different cone types also show different spectral sensitivity, which is the basis for colour vision. First measurements using microspectrophotometry (MSP) revealed a peak absorption of the rod pigment at 484 nm, indicating that MSP, despite technical difficulties, will be a decisive tool in proving colour vision in these offshore fishes. When hunting, billfish such as the sailfish flash bright blue bars on their sides. This colour reflects largely in ultraviolet (UV) light at 350 nm as revealed by spectrophotometric measurements. Billfish lenses block light of wavelengths below 400 nm, presumably rendering the animal blind to the UV component of its own body colour. Interestingly at least two prey species of billfish have lenses transmitting light in the UV waveband and are therefore likely to perceive a large fraction of the UV peak found in the blue bar of the sailfish. The possible biological significance of this finding is discussed.
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Hydrothermal alteration of a quartz-K-feldspar rock is simulated numerically by coupling fluid flow and chemical reactions. Introduction of CO2 gas generates an acidic fluid and produces secondary quartz, muscovite and/or pyrophyllite at constant temperature and pressure of 300 degrees C and 200 MPa. The precipitation and/or dissolution of the secondary minerals is controlled by either mass-action relations or rate laws. In our simulations the mass of the primary elements are conserved and the mass-balance equations are solved sequentially using an implicit scheme in a finite-element code. The pore-fluid velocity is assumed to be constant. The change of rock volume due to the dissolution or precipitation of the minerals, which is directly related to their molar volume, is taken into account. Feedback into the rock porosity and the reaction rates is included in the model. The model produces zones of pyrophyllite quartz and muscovite due to the dissolution of K-feldspar. Our model simulates, in a simplified way, the acid-induced alteration assemblages observed in various guises in many significant mineral deposits. The particular aluminosilicate minerals produced in these experiments are associated with the gold deposits of the Witwatersrand Basin.
Resumo:
Despite extensive study of the numerous immunoregulatory mechanisms that contribute to the immune-privileged nature of the anterior chamber (AC) of the eye, little is known of the functional nature of antigen-presenting cells (APC) present in the tissues adjoining the AC. In the present study, we have compared the antigen-presenting capacity of dendritic cells (DC) and macrophages isolated from the normal rat iris. Whereas iris DC exhibited a potent ability to stimulate resting allogeneic T cells in MLR cultures (an in-vitro correlate of the ability to induce primary T cell responses), resident iris macrophages displayed negligible MLR-stimulatory capacity. Significantly, iris macrophages could efficiently elicit proliferation of primed antigen-specific T cells (an in-vitro correlate of the ability to act as local APC in secondary responses). This antigen-presenting activity was approximately half that of fully mature iris DC and considerably greater than that of freshly isolated iris DC. A key contributor to the effectiveness of resident iris macrophage antigen presentation was considered to be the absence of lymphocytostatic control of T cell proliferation exerted by these cells. The results indicate dichotomous but complementary roles for DC (immune surveillance) and macrophages (local antigen presentation in secondary responses) in this tissue.
Resumo:
Objectives. The present study was designed to test the diathesis-stress components of Beck's cognitive theory of depression and the reformulated learned helplessness model of depression in the prediction of postpartum depressive symptomatology. Design and methods. The research used a two-wave longitudinal design-data were collected from 65 primiparous women during their third trimester of pregnancy and then 6 weeks after the birth. Cognitive vulnerability and initial depressive symptomatology were assessed at Time 1, whereas stress and postpartum depressive symptomatology were assessed at Time 2. Results. There was some support for the diathesis-stress component of Beck's cognitive theory, to the extent that the negative relationship between both general and maternal-specific dysfunctional attitudes associated with performance evaluation and Time 2 depressive symptomatology was strongest for women who reported high levels of parental stress. In a similar vein, the effects of dysfunctional attitudes (general and maternal-specific) associated with performance evaluation and need for approval (general measure only) on partner ratings of emotional distress were evident only among those women whose infants were rated as being temperamentally difficult. Conclusion. There was no support for the diathesis-stress component of the reformulated learned helplessness model of depression; however, there was some support for the diathesis-stress component of Beck's cognitive theory.
Resumo:
Promiscuous T-cell epitopes make ideal targets for vaccine development. We report here a computational system, multipred, for the prediction of peptide binding to the HLA-A2 supertype. It combines a novel representation of peptide/MHC interactions with a hidden Markov model as the prediction algorithm. multipred is both sensitive and specific, and demonstrates high accuracy of peptide-binding predictions for HLA-A*0201, *0204, and *0205 alleles, good accuracy for *0206 allele, and marginal accuracy for *0203 allele. multipred replaces earlier requirements for individual prediction models for each HLA allelic variant and simplifies computational aspects of peptide-binding prediction. Preliminary testing indicates that multipred can predict peptide binding to HLA-A2 supertype molecules with high accuracy, including those allelic variants for which no experimental binding data are currently available.
Resumo:
Background: A variety of methods for prediction of peptide binding to major histocompatibility complex (MHC) have been proposed. These methods are based on binding motifs, binding matrices, hidden Markov models (HMM), or artificial neural networks (ANN). There has been little prior work on the comparative analysis of these methods. Materials and Methods: We performed a comparison of the performance of six methods applied to the prediction of two human MHC class I molecules, including binding matrices and motifs, ANNs, and HMMs. Results: The selection of the optimal prediction method depends on the amount of available data (the number of peptides of known binding affinity to the MHC molecule of interest), the biases in the data set and the intended purpose of the prediction (screening of a single protein versus mass screening). When little or no peptide data are available, binding motifs are the most useful alternative to random guessing or use of a complete overlapping set of peptides for selection of candidate binders. As the number of known peptide binders increases, binding matrices and HMM become more useful predictors. ANN and HMM are the predictive methods of choice for MHC alleles with more than 100 known binding peptides. Conclusion: The ability of bioinformatic methods to reliably predict MHC binding peptides, and thereby potential T-cell epitopes, has major implications for clinical immunology, particularly in the area of vaccine design.
Resumo:
High performance video codec is mandatory for multimedia applications such as video-on-demand and video conferencing. Recent research has proposed numerous video coding techniques to meet the requirement in bandwidth, delay, loss and Quality-of-Service (QoS). In this paper, we present our investigations on inter-subband self-similarity within the wavelet-decomposed video frames using neural networks, and study the performance of applying the spatial network model to all video frames over time. The goal of our proposed method is to restore the highest perceptual quality for video transmitted over a highly congested network. Our contributions in this paper are: (1) A new coding model with neural network based, inter-subband redundancy (ISR) prediction for video coding using wavelet (2) The performance of 1D and 2D ISR prediction, including multiple levels of wavelet decompositions. Our result shows a short-term quality enhancement may be obtained using both 1D and 2D ISR prediction.
Resumo:
Carbon monoxide is the chief killer in fires. Dangerous levels of CO can occur when reacting combustion gases are quenched by heat transfer, or by mixing of the fire plume in a cooled under- or overventilated upper layer. In this paper, carbon monoxide predictions for enclosure fires are modeled by the conditional moment closure (CMC) method and are compared with laboratory data. The modeled fire situation is a buoyant, turbulent, diffusion flame burning under a hood. The fire plume entrains fresh air, and the postflame gases are cooled considerably under the hood by conduction and radiation, emulating conditions which occur in enclosure fires and lead to the freezing of CO burnout. Predictions of CO in the cooled layer are presented in the context of a complete computational fluid dynamics solution of velocity, temperature, and major species concentrations. A range of underhood equivalence ratios, from rich to lean, are investigated. The CMC method predicts CO in very good agreement with data. In particular, CMC is able to correctly predict CO concentrations in lean cooled gases, showing its capability in conditions where reaction rates change considerably.
Resumo:
Dormancy release was studied in four populations of annual ryegrass (Lolium rigidum) seeds to determine whether loss of dormancy in the field can be predicted from temperature alone or whether seed water content (WC) must also be considered. Freshly matured seeds were after-ripened at the northern and southern extremes of the Western Australian cereal cropping region and at constant 37degreesC. Seed WC was allowed to fluctuate with prevailing humidity, but full hydration was avoided by excluding rainfall. Dormancy was measured regularly during after-ripening by germinating seeds with 12-hourly light or in darkness. Germination was lower in darkness than in light/dark and dormancy release was slower when germination was tested in darkness. Seeds were consistently drier, and dormancy release was slower, during after-ripening at 37degreesC than under field conditions. However, within each population, the rate of dormancy release in the field (north and south) in terms of thermal time was unaffected by after-ripening site. While low seed WC slowed dormancy release in seeds held at 37degreesC, dormancy release in seeds after-ripened under Western Australian field conditions was adequately described by thermal after-ripening time, without the need to account for changes in WC elicited by fluctuating environmental humidity.
Resumo:
This study compared emotional Stroop interference in the emotional colour naming Stroop and the emotional counting Stroop by measuring reaction times and event-related potentials to positive, negative and neutral words. Twenty participants had ERPs recorded at 61 sites while performing both types of emotional Stroop tasks as well as congruent and incongruent conflict conditions. All participants rated stimulus emotionality retrospectively. A robust reaction time Stroop effect was observed in response latency for the traditional ‘‘conflict’’ conditions (congruent vs. incongruent) for the counting Stroop though not the colour naming Stroop task. There was also no evidence of emotional interference for either of the tasks; however, there was trend for positive interference in the colour naming Stroop. The P5 was identified as the event-related potential associated with emotional processing. For the P5 component, significant emotionality effects were evident in the emotional colour naming Stroop for latency (542 ms). There was a significant interaction between valence and hemisphere. The latency of the P5 in the right hemisphere was later for the positive words than negative and neutral. Comparable effects of valence were evident for the emotional counting Stroop for amplitude but not latency.
Resumo:
Computational models complement laboratory experimentation for efficient identification of MHC-binding peptides and T-cell epitopes. Methods for prediction of MHC-binding peptides include binding motifs, quantitative matrices, artificial neural networks, hidden Markov models, and molecular modelling. Models derived by these methods have been successfully used for prediction of T-cell epitopes in cancer, autoimmunity, infectious disease, and allergy. For maximum benefit, the use of computer models must be treated as experiments analogous to standard laboratory procedures and performed according to strict standards. This requires careful selection of data for model building, and adequate testing and validation. A range of web-based databases and MHC-binding prediction programs are available. Although some available prediction programs for particular MHC alleles have reasonable accuracy, there is no guarantee that all models produce good quality predictions. In this article, we present and discuss a framework for modelling, testing, and applications of computational methods used in predictions of T-cell epitopes. (C) 2004 Elsevier Inc. All rights reserved.