The effectiveness of telemedicine interventions to address maternal depression: a systematic review and meta-analysis

Introduction Maternal depression (MD), is an overarching term for depression affecting pregnant women and mothers for up to 12 months postpartum. Because MD may have chronic and long-lasting effects, it is an important public health concern. The extent to which telemedicine may be an effective way to provide services to sufferers of MD is unknown, therefore, this review aimed to assess the available evidence. Methods We conducted a search of The Cochrane Library, PubMed/MEDLINE, PsycINFO, and EMBASE for relevant randomised controlled trials published between 2000 and 2018; we then conducted a systematic review and meta-analysis. Results We identified 10 studies for inclusion. Therapeutic strategies involved cognitive behavioural therapy (CBT), behavioural activation and other psychoeducation. Eight trials reported significant improvement in depression scores post-intervention; four studies that conducted post-intervention follow-up found that these improvements continued. However, high attrition rates and lack of blinding were common problems. Discussion This review found limited evidence supporting the delivery of CBT for the treatment of MD and anxiety using telemedicine. However, most of the evidence only studied improvements in postpartum depression, indicating that use of telemedicine to provide MD intervention is still small and an under-researched area

Consistency of in vitro drug sensitivities within pharmacological classes

Multiple comparative analyses between the common drugs and cell lines of the Genomics of Drug Sensitivity in Cancer (GDSC) and the Cancer Therapeutics Response Portal (CTRP) have previously shown low consistency between the in vitro phenotypic measures of a drug in one study with the other. While several potential sources of inconsistency have been tested, the similar targets of tested compounds has yet to be tested as a contributing factor of discrepancy. This analysis includes two methods of reclassifying drugs into classes based on their targets to identify the truer set of consistent cell lines, showing an increased correlation between the two pharmacogenomic studies

ToxicoDB:an integrated database to mine and visualize large-scale toxicogenomic datasets

In the past few decades, major initiatives have been launched around the world to address chemical safety testing. These efforts aim to innovate and improve the efficacy of existing methods with the long-term goal of developing new risk assessment paradigms. The transcriptomic and toxicological profiling of mammalian cells has resulted in the creation of multiple toxicogenomic datasets and corresponding tools for analysis. To enable easy access and analysis of these valuable toxicogenomic data, we have developed ToxicoDB (toxicodb.ca), a free and open cloud-based platform integrating data from large in vitro toxicogenomic studies, including gene expression profiles of primary human and rat hepatocytes treated with 231 potential toxicants. To efficiently mine these complex toxicogenomic data, ToxicoDB provides users with harmonized chemical annotations, time- and dose-dependent plots of compounds across datasets, as well as the toxicity-related pathway analysis. The data in ToxicoDB have been generated using our open-source R package, ToxicoGx (github.com/bhklab/ToxicoGx). Altogether, ToxicoDB provides a streamlined process for mining highly organized, curated, and accessible toxicogenomic data that can be ultimately applied to preclinical toxicity studies and further our understanding of adverse outcomes.</p