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Results for “Predictive testing”

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PubMed1994

Predictive testing of radiosensitivity in non-small cell carcinoma of the lung.

The paper reviews the prognostic factors which influence the radiosensitivity of non-small cell lung cancer. The clonogenic cell numbers, hypoxic fraction, tumour cell kinetics and inherent radiosensitivity are considered. In the future the measurement of these factors may play an important role in decision making as to the best management for patients with non-small cell lung cancer.

Carcinoma, Non-Small-Cell Lung↗
PubMed2004

In vitro evaluation of matrix metalloproteinases as predictive testing for nickel, a model sensitizing agent.

The identification of potential damage due to chemical exposure in the workplace is a major health and regulatory concern. Traditional tests that measure both sensitization and elicitation responses require the use of animals. An alternative to this widespread use of experimental animals could have a crucial impact on risk assessment, especially for the preliminary screening of new molecules. We developed an in vitro model for the screening of potential toxic compounds. Human keratinocytes (HaCat) were used as target cells while matrix metalloproteinases (MMP) were selected as responders because they are key enzymes involved in extracellular matrix (ECM) degradation in physiological and pathological conditions. Chemical exposure was performed using nickel sulphate as a positive tester. Nickel contact induced upregulation of MMP-2 and IL-8 mRNA production. Molecular activation occurred even at very low nickel concentrations even though no phenotypic changes were observed. MMP-9 accumulation was found in the medium of treated cells with respect to controls. These observations led to the hypothesis that even minimal exposure can accumulate transcriptional activity resulting in long-term clinical signs after contact. Our simple in vitro model can be applied as a useful preliminary complement to the animal studies to screen the effects of new potential toxic compounds.

Animal Testing Alternatives↗
PubMed2004

Drug hypersensitivity reactions in skin: understanding mechanisms and the development of diagnostic and predictive tests.

Cutaneous manifestations of drug hypersensitivity can be serious and potentially life threatening and may prevent effective drug therapy. T cells play an important role in the pathology of drug hypersensitivity reactions. Classical studies suggest that T-cell activation requires drug bioactivation, covalent binding to protein and antigen processing to stimulate an immune response. Recent studies have shown that drugs can also be presented to T cells in the absence of antigen processing and drug metabolism. In this article, sulfamethoxazole is used as a paradigm to describe the chemical mechanisms involved in the initiation and maintenance of an aberrant drug antigen specific T-cell response. Presentation of the same drug to different individuals can cause a variety of skin diseases. Such reactions have been classified according to the phenotype and functionality of the T-cell response. This review summarises the different forms of cutaneous hypersensitivity reactions and describes how T-cell clones generated from hypersensitive patients have been used to study the cellular mechanisms of anticonvulsant hypersensitivity. Potential uses of in vitro cell culture assays for patient diagnosis and drug evaluation are also discussed.

Animals↗
PubMed2006

Testing predictions of macroscopic binary diffusion coefficients using lattice models with site heterogeneity.

Quantitatively predicting mass transport rates for chemical mixtures in porous materials is important in applications of materials such as adsorbents, membranes, and catalysts. Because directly assessing mixture transport experimentally is challenging, theoretical models that can predict mixture diffusion coefficients using only single-component information would have many uses. One such model was proposed by Skoulidas, Sholl, and Krishna (Langmuir, 2003, 19, 7977), and applications of this model to a variety of chemical mixtures in nanoporous materials have yielded promising results. In this paper, the accuracy of this model for predicting mixture diffusion coefficients in materials that exhibit a heterogeneous distribution of local binding energies is examined. To examine this issue, single-component and binary mixture diffusion coefficients are computed using kinetic Monte Carlo for a two-dimensional lattice model over a wide range of lattice occupancies and compositions. The approach suggested by Skoulidas, Sholl, and Krishna is found to be accurate in situations where the spatial distribution of binding site energies is relatively homogeneous, but is considerably less accurate for strongly heterogeneous energy distributions.

Journal Article↗