ARL, predictive technology /

Mode of access: Internet.

Siting the Superconducting Super Collider in Illinois : an overview and predictive model of cultural and paleobiological resources in the SSC study area, northern Illinois /

Cover title.

Traffic assignment. Predictive curves and their application, including machine procedures developed in the Detroit traffic study.

Cover title.

Study to evaluate the adequacy and predictive value of fish and wildlife planning recommendations at Corps of Engineers reservoir projects : individual reservoir project evaluation reports : the Pat Mayse Lake project /

"July 1983"--Cover.

Adequacy and predictive value of fish and wildlife planning recommendations at Corps of Engineers reservoir projects /

Mode of access: Internet.

Predictive design procedures, VESYS users manual : an interim design method for flexible pavements using the VESYS structural subsystem /

Mode of access: Internet.

Pro-fibrotic polymorphisms predictive of advanced liver fibrosis in the severely obese

Background/Aims: Insulin resistance and systemic hypertension are predictors of advanced fibrosis in obese patients with non-alcoholic fatty liver disease (NAFLD). Genetic factors may also be important. We hypothesize that high angiotensinogen (AT) and transforming growth factor-beta1 (TGF-beta1) producing genotypes increase the risk of liver fibrosis in obese subjects with NAFLD. Methods: One hundred and five of 130 consecutive severely obese patients having a liver biopsy at the time of laparoscopic obesity surgery agreed to have genotype analysis. Influence of specific genotype or combination of genotypes on the stage of hepatic fibrosis was assessed after controlling for known risk factors. Results: There was no fibrosis in 70 (67%), stages 1-2 in 21 (20%) and stages 3-4 fibrosis in 14 (13%) of subjects. There was no relationship between either high AT or TGF-beta1 producing genotypes alone and hepatic fibrosis after controlling for confounding factors. However, advanced hepatic fibrosis occurred in five of 13 subjects (odds ratio 5.7, 95% confidence interval 1.5-21.2, P = 0.005) who inherited both high AT and TGF-beta1 producing polymorphisms. Conclusions: The combination of high AT and TGF-beta1 producing polymorphisms is associated with advanced hepatic fibrosis in obese patients with NAFLD. These findings support the hypothesis that angiotensin II stimulated TGF-beta1 production may promote hepatic fibrosis. (C) 2003 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

Quantitative justification for target concentration intervention - parameter variability and predictive performance using population pharmacokinetic models for aminoglycosides

Aims [1] To quantify the random and predictable components of variability for aminoglycoside clearance and volume of distribution [2] To investigate models for predicting aminoglycoside clearance in patients with low serum creatinine concentrations [3] To evaluate the predictive performance of initial dosing strategies for achieving an aminoglycoside target concentration. Methods Aminoglycoside demographic, dosing and concentration data were collected from 697 adult patients (>=20 years old) as part of standard clinical care using a target concentration intervention approach for dose individualization. It was assumed that aminoglycoside clearance had a renal and a nonrenal component, with the renal component being linearly related to predicted creatinine clearance. Results A two compartment pharmacokinetic model best described the aminoglycoside data. The addition of weight, age, sex and serum creatinine as covariates reduced the random component of between subject variability (BSVR) in clearance (CL) from 94% to 36% of population parameter variability (PPV). The final pharmacokinetic parameter estimates for the model with the best predictive performance were: CL, 4.7 l h(-1) 70 kg(-1); intercompartmental clearance (CLic), 1 l h(-1) 70 kg(-1); volume of central compartment (V-1), 19.5 l 70 kg(-1); volume of peripheral compartment (V-2) 11.2 l 70 kg(-1). Conclusions Using a fixed dose of aminoglycoside will achieve 35% of typical patients within 80-125% of a required dose. Covariate guided predictions increase this up to 61%. However, because we have shown that random within subject variability (WSVR) in clearance is less than safe and effective variability (SEV), target concentration intervention can potentially achieve safe and effective doses in 90% of patients.

Predictive genetic test decisions for Huntington's disease: context, appraisal and new moral imperatives

Predictive testing is one of the new genetic technologies which, in conjunction with developing fields such as pharmacogenomics, promises many benefits for preventive and population health. Understanding how individuals appraise and make genetic test decisions is increasingly relevant as the technology expands. Lay understandings of genetic risk and test decision-making, located within holistic life frameworks including family or kin relationships, may vary considerably from clinical representations of these phenomena. The predictive test for Huntington's disease (HD), whilst specific to a single-gene, serious, mature-onset but currently untreatable disorder, is regarded as a model in this context. This paper reports upon a qualitative Australian study which investigated predictive test decision-making by individuals at risk for HD, the contexts of their decisions and the appraisals which underpinned them. In-depth interviews were conducted in Australia with 16 individuals at 50% risk for HD, with variation across testing decisions, gender, age and selected characteristics. Findings suggested predictive testing was regarded as a significant life decision with important implications for self and others, while the right not to know genetic status was staunchly and unanimously defended. Multiple contexts of reference were identified within which test decisions were located, including intra- and inter-personal frameworks, family history and experience of HID, and temporality. Participants used two main criteria in appraising test options: perceived value of, or need for the test information, for self and/or significant others, and degree to which such information could be tolerated and managed, short and long-term, by self and/or others. Selected moral and ethical considerations involved in decision-making are examined, as well as the clinical and socio-political contexts in which predictive testing is located. The paper argues that psychosocial vulnerabilities generated by the availability of testing technologies and exacerbated by policy imperatives towards individual responsibility and self-governance should be addressed at broader societal levels. (C) 2003 Elsevier Science Ltd. All rights reserved.

Relative accuracy and predictive ability of direct valuation methods, price to aggregate earnings method and a hybrid approach

In this paper, we assess the relative performance of the direct valuation method and industry multiplier models using 41 435 firm-quarter Value Line observations over an 11 year (1990–2000) period. Results from both pricingerror and return-prediction analyses indicate that direct valuation yields lower percentage pricing errors and greater return prediction ability than the forward price to aggregated forecasted earnings multiplier model. However, a simple hybrid combination of these two methods leads to more accurate intrinsic value estimates, compared to either method used in isolation. It would appear that fundamental analysis could benefit from using one approach as a check on the other.

Predictive vaccinology: Optimisation of predictions using support vector machine classifiers

Promiscuous human leukocyte antigen (HLA) binding peptides are ideal targets for vaccine development. Existing computational models for prediction of promiscuous peptides used hidden Markov models and artificial neural networks as prediction algorithms. We report a system based on support vector machines that outperforms previously published methods. Preliminary testing showed that it can predict peptides binding to HLA-A2 and -A3 super-type molecules with excellent accuracy, even for molecules where no binding data are currently available.