We celebrate women in science with a playlist of our top trending video interviews
Meet the women who are making a critical impact in the fields of food science, nanomedicine, and healthcare
8 Mar 2022
Editorial article
To celebrate International Women’s Day, we have pulled together a playlist of top interviews with female scientists from The Scientists' Channel, our independent video platform for scientists and clinical experts around the world to share their work.
The role of polyploid giant cancer cells in disease
Dr. Michelle Dawson, Brown University, shares her research on cell metabolism and interactions. Dawson further explains how deepening our understanding of how polyploid giant cancer cells (PGCC) interact is vital in determining how they give rise to invasive cancers.
Personalized nanomedicine: Advanced targeted therapy to treat rare disease
Dr. Nura Mohamed, research associate at Qatar University, discusses how she is applying nanomedicine to improve the detection and treatment strategy of pulmonary arterial hypertension. Mohamed highlights why scientific collaboration is necessary in order to identify appropriate nanoparticle properties.
Why is analyzing highly polar pesticides in food and the environment so hard?
Ann-Kathrin Wachtler, food chemist at CVUA Stuttgart Official Institute for Food Control, explores the challenges associated with analyzing very high numbers of samples for highly polar pesticides and other compounds.
Combating the threat of antimicrobial resistance: The promising rapid tests for antimicrobial susceptibility
Dr. Tiziana Di Martino, chief medical officer at Q-linea, explores the benefits of rapid antimicrobial susceptibility testing (AST) technology and shares how a minimum inhibitory concentration result is utilized within clinical practice to help guide patient treatments.
Machine learning in healthcare: How the principles of consumer-focused AI could save lives
Prof. Regina Barzilay, faculty lead for artificial intelligence at MIT Jameel Clinic, describes how she is using machine learning to take on some of the major challenges in healthcare such as clinical diagnostics, improving care outcomes, and drug discovery.
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