Biomedical subjects

Myla Strawderman

Publications and source records attributed to Myla Strawderman.

3 recordsLinked to original sources

PubMed2004

Enduring effects of prenatal cocaine exposure on selective attention and reactivity to errors: evidence from an animal model.

Adult Long-Evans rats, exposed prenatally to 1 of 4 doses of cocaine (0.0,0.5,1.0, or 3.0 mg/kg iv), were tested on a 3-choice visual attention task with an olfactory distractor presented unpredictably on one third of the trials. The performance of all 3 cocaine-exposed groups was significantly more disrupted than that of controls by the presentation of distractors. Results demonstrate that prenatal cocaine exposure increases susceptibility to distractors, using a task specifically designed to measure this function. In addition, the present study revealed that individuals exposed to cocaine in utero exhibit greater performance disruption after an error than controls, in certain types of tasks. Both areas of dysfunction, impaired selective attention and impaired arousal regulation, have important functional consequences in humans, possibly affecting the school performance and social development of cocaine-exposed children.

Animals↗

PubMed2002

Preoperative parameters for predicting early prostate cancer recurrence after radical prostatectomy.

OBJECTIVES: To determine whether easily measurable prostate biopsy features could complement Gleason score, prostate-specific antigen (PSA), or clinical stage in predicting recurrence-free survival after prostatectomy. Information relating preoperative parameters to recurrence-free survival is needed to counsel patients with newly diagnosed prostate cancer regarding expectations for postprostatectomy cancer control. METHODS: The data of a cohort of 588 consecutive prostatectomy patients (median age 61 years, range 39 to 83) with ascertained preoperative data and up to 4 years of postprostatectomy follow-up were analyzed. Bivariate and multivariate Cox proportional hazards analysis evaluated preoperative factors (clinical stage, PSA, biopsy Gleason score, greatest percentage of a biopsy core involved by cancer [GPC], number of biopsy cores containing cancer, perineural invasion) to identify those relating significantly to recurrence-free survival. Functional forms of these factors were evaluated to optimize accuracy in predicting cancer control. RESULTS: The baseline parameters significantly affecting PSA-free survival included PSA level (P <0.01), biopsy Gleason score (P = 0.04), and GPC (P <0.01). Although clinical stage and perineural invasion had a marginal association with PSA-free survival as univariate factors, this association was not independently significant in multivariable analysis. The multivariate Cox model using PSA, Gleason score, and GPC was highly predictive of PSA free-survival (chi-square = 48.2, P = 0.0001). A set of plots representing these data can be used to identify the risk of early postoperative PSA recurrence on the basis of specific preoperative PSA, Gleason score, and GPC values. CONCLUSIONS: These findings provide a highly significant model and a simple tool for assisting preoperative patient counseling regarding predicted cancer control after radical prostatectomy.

Adult↗

PubMed2002

Tissue microarray sampling strategy for prostate cancer biomarker analysis.

High-density tissue microarrays (TMA) are useful for profiling protein expression in a large number of samples but their use for clinical biomarker studies may be limited in heterogeneous tumors like prostate cancer. In this study, the optimization and validation of a tumor sampling strategy for a prostate cancer outcomes TMA is performed. Prostate cancer proliferation determined by Ki-67 immunohistochemistry was tested. Ten replicate measurements of proliferation using digital image analysis (CAS200, Bacus Labs, Lombard, IL, USA) were made on 10 regions of prostate cancer from a standard glass slide. Five matching tissue microarray sample cores (0.6 mm diameter) were sampled from each of the 10 regions in the parallel study. A bootstrap resampling analysis was used to statistically simulate all possible permutations of TMA sample number per region or sample. Statistical analysis compared TMA samples with Ki-67 expression in standard pathology immunohistochemistry slides. The optimal sampling for TMA cores was reached at 3 as fewer TMA samples significantly increased Ki-67 variability and a larger number did not significantly improve accuracy. To validate these results, a prostate cancer outcomes tissue microarray containing 10 replicate tumor samples from 88 cases was constructed. Similar to the initial study, 1 to 10 randomly selected cores were used to evaluate the Ki-67 expression for each case, computing the 90th percentile of the expression from all samples used in each model. Using this value, a Cox proportional hazards analysis was performed to determine predictors of time until prostate-specific antigen (PSA) recurrence after radical prostatectomy for clinically localized prostate cancer. Examination of multiple models demonstrated that 4 cores was optimal. Using a model with 4 cores, a Cox regression model demonstrated that Ki-67 expression, preoperative PSA, and surgical margin status predicted time to PSA recurrence with hazard ratios of 1.49 (95% confidence interval [CI] 1.01-2.20, p = 0.047), 2.36 (95% CI 1.15-4.85, p = 0.020), and 9.04 (95% CI 2.42-33.81, p = 0.001), respectively. Models with 3 cores to determine Ki-67 expression were also found to predict outcome. In summary, 3 cores were required to optimally represent Ki-67 expression with respect to the standard tumor slide. Three to 4 cores gave the optimal predictive value in a prostate cancer outcomes array. Sampling strategies with fewer than 3 cores may not accurately represent tumor protein expression. Conversely, more than 4 cores will not add significant information. This prostate cancer outcomes array should be useful in evaluating other putative prostate cancer biomarkers.

Biomarkers↗