Publications by authors named "Ashley Gilbert"

Kava is an Oceanic plant in which the root is consumed as a beverage and is becoming increasingly popular. The effects of kava consumption may include sedation, euphoria, and impairment of motor coordination. This article demonstrates kava impairment through four cases of self-reported kava use supported with Drug Recognition Expert (DRE) evaluations of each subject.

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Glioblastoma multiforme (GBM), the most common form of primary malignant brain cancer in adults, is a devastating disease for which effective treatment has remained elusive for over 75 years. One reason for the minimal progress during this time is the lack of accurate preclinical models to represent the patient's tumor's in vivo environment, causing a disconnect in drug therapy effectiveness between the laboratory and clinic. While patient-derived xenografts (PDX's or xenolines) are excellent human tumor representations, they are not amenable to high throughput testing.

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Development of effective novel anti-tumor treatments will require improved in vitro models that incorporate physiologic microenvironments and maintain intratumoral heterogeneity, including tumor initiating cells. Brain tumor initiating cells (BTIC) are a target for cancer therapy, because BTICs are highly tumorigenic and contribute to tumor angiogenesis, invasion, and therapeutic resistance. Current leading studies rely on BTIC isolation from patient-derived xenografts followed by propagation as neurospheres.

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The use of patient-derived xenografts for modeling cancers has provided important insight into cancer biology and drug responsiveness. However, they are time consuming, expensive, and labor intensive. To overcome these obstacles, many research groups have turned to spheroid cultures of cancer cells.

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The cancer literature is filled with promising preclinical studies demonstrating impressive efficacy for new therapeutics, yet translation of these approaches into clinical successes has been rare, indicating that current methods used to predict efficacy are suboptimal. The most likely reason for the limitation of these studies is the disconnect between preclinical models and cancers treated in the clinic. Specifically, most preclinical models are poor representations of human disease.

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Purpose: Researchers are currently seeking relevant lung cancer biomarkers in order to make informed decisions regarding therapeutic selection for patients in so-called "precision medicine." However, there are challenges to obtaining adequate lung cancer tissue for molecular analyses. Furthermore, current molecular testing of tumors at the genomic or transcriptomic level are very indirect measures of biological response to a drug, particularly for small molecule inhibitors that target kinases.

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