Background: The rich biodiversity of medicinal plants and their importance as sources of novel therapeutics and lead compounds warrant further research. Despite advances in debulking surgery and chemotherapy, the risks of recurrence of ovarian cancer and resistance to therapy are significant and the clinical outcomes of ovarian cancer remain poor or even incurable.
Objective: This study aims to investigate the effects of leaf extracts from a medicinal plant Leea indica and its selected phytoconstituents on human ovarian cancer cells and in combination with oxaliplatin and natural killer (NK) cells.
(Vitaceae) is a Southeast Asian medicinal plant. In this study, an ethyl acetate fraction of leaves was studied for its phytoconstituents using high-performance liquid chromatography-electrospray ionization-mass spectrometry (HPLC-ESI-microTOF-Q-MS/MS) analysis. A total of 31 compounds of different classes, including benzoic acid derivatives, phenolics, flavonoids, catechins, dihydrochalcones, coumarins, megastigmanes, and oxylipins were identified using LC-MS/MS.
View Article and Find Full Text PDFStudy Objectives: Stimulated reporting occurs when patients and healthcare professionals are influenced or "stimulated" by media publicity to report specific drug-related adverse reactions, significantly biasing pharmacovigilance analyses. Among countries where the non-benzodiazepine hypnotic drug zolpidem is marketed, the United States experienced a comparable surge of media reporting during 2006-2009 linking the above drug with the development of complex neuropsychiatric sleep-related behaviors. However, the effect of this stimulated reporting in the United States Food and Drug Administration Adverse Event Reporting System has not been explored.
View Article and Find Full Text PDFPharmacoepidemiol Drug Saf
July 2015
Purpose: The US Food and Drug Administration Adverse Event Reporting System (FAERS), one of the world's largest spontaneous reporting systems, is difficult to use because of report duplication and a lack of standardisation in the recording of drug names. Unresolved data quality issues may distort statistical analyses, rendering the results difficult to interpret when detecting and monitoring adverse effects of pharmaceutical products. The aim of this study was to develop and implement a data cleaning protocol to identify and resolve drug nomenclature issues.
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