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Gerald Van Belle

Publications and source records attributed to Gerald Van Belle.

2 recordsLinked to original sources

Hormonal exposures and the risk of intracranial meningioma in women: a population-based case-control study.

BACKGROUND: The role of exogenous hormone exposures in the development of meningioma is unclear, but these exposures have been proposed as one hypothesis to explain the over-abundance of such tumors in women. METHODS: The association between oral contraception (OC) or hormone replacement therapy (HRT) and intracranial meningioma in women was investigated using a population-based, matched case-control study. Exposures for 143 cases and 286 controls matched on age within five years were obtained by interview. Diagnoses were confirmed histopathologically and estrogen and progesterone receptor assays conducted. RESULTS: Although risk of meningioma appeared modestly elevated in past OC users (OR = 1.5, 95% CI 0.8 - 2.7), and in current users (OR = 2.5, 95% CI 0.5 - 12.6), the confidence intervals were wide. No significant association between meningioma risk and duration of OC use was found. Likewise, risk of meningioma was only weakly associated with past use of HRT (OR = 0.7, 95% CI 0.4 - 1.3), and not at all with current use of HRT (OR = 1.0, 95% CI 0.5 - 2.2). Of 142 available specimens, 2 (1%) expressed estrogen receptors, whereas 130 (92%) expressed progesterone receptors (PR). OC use was associated with increased risk of a meningioma expressing less rather than more PR (OR = 3.2, 95% CI 1.3 - 8.0). Overall, in post menopausal women, HRT use appeared to confer a non-significant protective effect, and was not associated with low or high PR expressing meningiomas. CONCLUSION: This study found little evidence of associations between meningioma and exogenous hormone exposures in women but did suggest that some hormonal exposures may influence tumor biology in those women who develop meningioma.

Adult↗

Randomized sequence databases for tandem mass spectrometry peptide and protein identification.

Tandem mass spectrometry (MS/MS) combined with database searching is currently the most widely used method for high-throughput peptide and protein identification. Many different algorithms, scoring criteria, and statistical models have been used to identify peptides and proteins in complex biological samples, and many studies, including our own, describe the accuracy of these identifications, using at best generic terms such as "high confidence." False positive identification rates for these criteria can vary substantially with changing organisms under study, growth conditions, sequence databases, experimental protocols, and instrumentation; therefore, study-specific methods are needed to estimate the accuracy (false positive rates) of these peptide and protein identifications. We present and evaluate methods for estimating false positive identification rates based on searches of randomized databases (reversed and reshuffled). We examine the use of separate searches of a forward then a randomized database and combined searches of a randomized database appended to a forward sequence database. Estimated error rates from randomized database searches are first compared against actual error rates from MS/MS runs of known protein standards. These methods are then applied to biological samples of the model microorganism Shewanella oneidensis strain MR-1. Based on the results obtained in this study, we recommend the use of use of combined searches of a reshuffled database appended to a forward sequence database as a means providing quantitative estimates of false positive identification rates of peptides and proteins. This will allow researchers to set criteria and thresholds to achieve a desired error rate and provide the scientific community with direct and quantifiable measures of peptide and protein identification accuracy as opposed to vague assessments such as "high confidence."

Databases, Protein↗