84 resultados para Lung nodule malignancy prediction

em University of Queensland eSpace - Australia


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Immunotherapy strategies aimed at increasing human Valpha24(+)Vbeta11(+) natural killer T (NKT) cell numbers are currently a major focus. To provide further information towards the goal of NKT cell-based immunotherapy, we assessed the effects of age, cancer status and prior anticancer treatment on NKT cell numbers and their expansion capacity following alpha-galactosylceramide (alpha-GalCer) stimulation. The percentage and absolute number of peripheral blood NKT cells was assessed in 40 healthy donors and 109 solid cancer patients ( colorectal ( n = 33), breast ( n = 10), melanoma ( n = 17), lung ( n = 8), renal cell carcinoma ( n = 10), other cancers ( n = 31)). Responsiveness to alpha-GalCer stimulation was also assessed in 28 of the cancer patients and 37 of the healthy donors. Natural killer T cell numbers were significantly reduced in melanoma and breast cancer patients. While NKT numbers decreased with age in healthy donors, NKT cells were decreased in these cancer subgroups despite age and sex adjustments. Prior radiation treatment was shown to contribute to the observed reduction in melanoma patients. Although cancer patient NKT cells were significantly less responsive to alpha-GalCer stimulation, they remained capable of substantial expansion. Natural killer T cells are therefore modulated by age, malignancy and prior anticancer treatment; however, cancer patient NKT cells remain capable of responding to alpha-GalCer-based immenotherapies.

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In recent years, the phrase 'genomic medicine' has increasingly been used to describe a new development in medicine that holds great promise for human health. This new approach to health care uses the knowledge of an individual's genetic make-up to identify those that are at a higher risk of developing certain diseases and to intervene at an earlier stage to prevent these diseases. Identifying genes that are involved in disease aetiology will provide researchers with tools to develop better treatments and cures. A major role within this field is attributed to 'predictive genomic medicine', which proposes screening healthy individuals to identify those who carry alleles that increase their susceptibility to common diseases, such as cancers and heart disease. Physicians could then intervene even before the disease manifests and advise individuals with a higher genetic risk to change their behaviour - for instance, to exercise or to eat a healthier diet - or offer drugs or other medical treatment to reduce their chances of developing these diseases. These promises have fallen on fertile ground among politicians, health-care providers and the general public, particularly in light of the increasing costs of health care in developed societies. Various countries have established databases on the DNA and health information of whole populations as a first step towards genomic medicine. Biomedical research has also identified a large number of genes that could be used to predict someone's risk of developing a certain disorder. But it would be premature to assume that genomic medicine will soon become reality, as many problems remain to be solved. Our knowledge about most disease genes and their roles is far from sufficient to make reliable predictions about a patient’s risk of actually developing a disease. In addition, genomic medicine will create new political, social, ethical and economic challenges that will have to be addressed in the near future.

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Multi-frequency bioimpedance analysis (MFBIA) was used to determine the impedance, reactance and resistance of 103 lamb carcasses (17.1-34.2 kg) immediately after slaughter and evisceration. Carcasses were halved, frozen and one half subsequently homogenized and analysed for water, crude protein and fat content. Three measures of carcass length were obtained. Diagonal length between the electrodes (right side biceps femoris to left side of neck) explained a greater proportion of the variance in water mass than did estimates of spinal length and was selected for use in the index L-2/Z to predict the mass of chemical components in the carcass. Use of impedance (Z) measured at the characteristic frequency (Z(c)) instead of 50 kHz (Z(50)) did not improve the power of the model to predict the mass of water, protein or fat in the carcass. While L-2/Z(50) explained a significant proportion of variation in the masses of body water (r(2) 0.64), protein (r(2) 0.34) and fat (r(2) 0.35), its inclusion in multi-variate indices offered small or no increases in predictive capacity when hot carcass weight (HCW) and a measure of rib fat-depth (GR) were present in the model. Optimized equations were able to account for 65-90 % of the variance observed in the weight of chemical components in the carcass. It is concluded that single frequency impedance data do not provide better prediction of carcass composition than can be obtained from measures of HCW and GR. Indices of intracellular water mass derived from impedance at zero frequency and the characteristic frequency explained a similar proportion of the variance in carcass protein mass as did the index L-2/Z(50).

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Motivation: Prediction methods for identifying binding peptides could minimize the number of peptides required to be synthesized and assayed, and thereby facilitate the identification of potential T-cell epitopes. We developed a bioinformatic method for the prediction of peptide binding to MHC class II molecules. Results: Experimental binding data and expert knowledge of anchor positions and binding motifs were combined with an evolutionary algorithm (EA) and an artificial neural network (ANN): binding data extraction --> peptide alignment --> ANN training and classification. This method, termed PERUN, was implemented for the prediction of peptides that bind to HLA-DR4(B1*0401). The respective positive predictive values of PERUN predictions of high-, moderate-, low- and zero-affinity binder-a were assessed as 0.8, 0.7, 0.5 and 0.8 by cross-validation, and 1.0, 0.8, 0.3 and 0.7 by experimental binding. This illustrates the synergy between experimentation and computer modeling, and its application to the identification of potential immunotheraaeutic peptides.

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The present study examined the relative importance of outcome expectancies and self-efficacy [1] in the prediction of alcohol dependence [2] and alcohol consumption in a sample of young adult drinkers drawn from a milieu previously reported as supportive of risky drinking. In predicting alcohol dependence, outcome expectancies were found to mediate self-efficacy and the same pattern was found for both males and females. This suggests that male and female drinkers may become more similar as they progress along the drinking continuum from risky drinking to dependent drinking. However, in women, in comparison to men, a greater array of expectancies and self-efficacy scales were found to predict heavy drinking, as measured by quantity and frequency. These results suggest that heavy drinking women are particularly at risk of developing drinking related complications and that preventative education needs to take into account gender differences.

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Recent El Nino events have stimulated interest in the development of modeling techniques to forecast extremes of climate and related health events. Previous studies have documented associations between specific climate variables (particularly temperature and rainfall) and outbreaks of arboviral disease. In some countries, such diseases are sensitive to Fl Nino. Here we describe a climate-based model for the prediction of Ross River virus epidemics in Australia. From a literature search and data on case notifications, we determined in which years there were epidemics of Ross River virus in southern Australia between 1928 and 1998. Predictor variables were monthly Southern Oscillation index values for the year of an epidemic or lagged by 1 year. We found that in southeastern states, epidemic years were well predicted by monthly Southern Oscillation index values in January and September in the previous year. The model forecasts that there is a high probability of epidemic Ross River virus in the southern states of Australia in 1999. We conclude that epidemics of arboviral disease can, at least in principle, be predicted on the basis of climate relationships.

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Obstruction of the fetal trachea is a potent stimulus for fetal lung growth and may have therapeutic potential in human fetuses with lung hypoplasia. However, the effects of increased lung expansion on lung development near midgestation, which is the preferred timing for fetal intervention, have not been well studied. Our aim was to determine the effects of increased lung expansion on lung development at 75-90 d of gestation in fetal sheep. In three groups of fetuses (n = 4 for each), the trachea was occluded for either 10 [10-d tracheal occlusion (TO) group] or 15 d (15-d TO group) or left intact (control fetuses). TO for both 10 and 15 d caused fetal hydrops, resulting in significantly increased fetal body weights. Both periods of TO significantly increased total lung DNA contents from 99.8 +/- 10.1 to 246.0 +/- 5.3 and 246.9 +/- 48.7 mg in 10- and 15-d TO fetuses, respectively. TO for 10 and 15 d also increased airspace diameter, although the percentage of lung occupied by airspace was not increased in 10-d TO fetuses due to large increases in interairway distances; this resulted from a large increase in mesenchymal tissue. The interairway distances at 15 d of TO were reduced compared with the 10-d value but were still similar to 30% larger than control values. We conclude that TO at

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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.

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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.

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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.

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The polymorphisms of the important xenobiotic metabolizing enzymes CYP2D6, CYP2C19 and CYP2E1 have been studied extensively in a large number of populations and show significant heterogeneity in the frequency of different alleles/genotypes and in the prevalence of the extensive and poor metabolizer phenotypes, Understanding of inter-ethnic differences in genotypes is important in prediction of either beneficial or adverse effects from therapeutic agents and other xenobiotics. Since no data were available for Australian Aborigines, we investigated the frequencies of alleles and genotypes for CYP2D6, CYP2C19 and CYP2E1 in a population living in the far north of Western Australia. Because of its geographical isolation, this population can serve as a model to study the impact of evolutionary forces on the distribution of different alleles for xenobiotic metabolizing enzymes. Twelve CYP2D6 alleles were analysed, The wild-type allele *1 was the most frequent (85.8%) and the non-functional alleles (*4, *5, *16) had an overall frequency of less than 10%. Only one subject (0.4%) was a poor metabolizer for CYP2D6 because of the genotype *5/*5, For CYP2C19, the frequencies of the *1 (wild-type) and the non-functional (*2 and *3) alleles were 50.2%, 35.5% and 14.3%, respectively. The combined CYP2C19 genotypes (*2/*2, *2/*3 or *3/*3) correspond to a predicted frequency of 25.6% for the CYP2C19 poor metabolizer phenotype, For CYP2E1, only one subject had the rare c2 allele giving an overall allele frequency of 0.2%. For CYP2D6 and CYP2C19, allele frequencies and predicted phenotypes differed significantly from those for Caucasians but were similar to those for Orientals indicating a close relationship to East Asian populations. Differences between Aborigines and Orientals in allele frequencies for CYP2D6*10 and CYP2E1 c2 may have arisen through natural selection, or genetic drift, respectively, Pharmacogenetics 11:69-76 (C) 2001 Lippincott Williams & Wilkins.

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Objective: To review the epidemiological evidence for the association between passive smoking and lung cancer. Method: Primary studies and meta-analyses examining the relationship between passive smoking and lung cancer were identified through a computerised literature search of Medline and Embase, secondary references, and experts in the field of passive smoking. Primary studies meeting the inclusion criteria were meta-analysed. Results From 1981 to the end of 1999 there have been 76 primary epidemiological studies of passive smoking and lung cancer, and 20 meta-analyses. There were 43 primary studies that met the inclusion criteria for this meta-analysis; more studies than previous assessments. The pooled relative risk (RR) for never-smoking women exposed to environmental tobacco smoke (ETS) from spouses, compared with unexposed never-smoking women was 1.29 (95% CI 1.17-1.43). Sequential cumulative meta-analysed results for each year from 1981 were calculated: since 1992 the RR has been greater than 1.25. For Western industrialised countries the RR for never-smoking women exposed to ETS compared with unexposed never-smoking women, was 1.21 (95% CI 1.10-1.33). Previously published international spousal meta-analyses have all produced statistically significant RRs greater than 1.17. Conclusions The abundance of evidence in this paper, and the consistency of findings across domestic and workplace primary studies, dosimetric extrapolations and meta-analyses, clearly indicates that non-smokers exposed to ETS are at increased risk of lung cancer. Implications: The recommended public health policy is for a total ban on smoking in enclosed public places and work sites.

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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.