Cardiovascular Concerns, Cancer Treatment, and Biological and Chronological Aging in Cancer: JACC Family Series.

Cardiovascular disease (CVD) and cancer are leading causes of death globally, particularly among the rapidly growing population of older adults (OAs). CVD is a leading cause of mortality among cancer survivors, often accelerated by cancer treatments associated with short- or long-term cardiotoxicity. Moreover, there is a dynamic relationship among CVD, cancer, and aging, characterized by shared risk factors and biological hallmarks, that plays an important role in caring for OAs, optimizing treatment approaches, and developing preventive strategies. Assessment of geriatric domains (eg, functional status, comorbidities, cognition, polypharmacy, nutritional status, social support, psychological well-being) is critical to individualizing treatment of OAs with cancer. The authors discuss considerations in caring for an aging population with cancer, including methods for the assessment of OAs with CVD and/or cardiovascular risk factors planned for cancer therapy. Multidisciplinary care is critical in optimizing patient outcomes and maintaining quality of life in this growing vulnerable population.

Genetic and chemical knockdown: a complementary strategy for evaluating an anti-infective target.

The equity of a drug target is principally evaluated by its genetic vulnerability with tools ranging from antisense- and microRNA-driven knockdowns to induced expression of the target protein. In order to upgrade the process of antibacterial target identification and discern its most effective type of inhibition, an in silico toolbox that evaluates its genetic and chemical vulnerability leading either to stasis or cidal outcome was constructed and validated. By precise simulation and careful experimentation using enolpyruvyl shikimate-3-phosphate synthase and its specific inhibitor glyphosate, it was shown that genetic knockdown is distinct from chemical knockdown. It was also observed that depending on the particular mechanism of inhibition, viz competitive, uncompetitive, and noncompetitive, the antimicrobial potency of an inhibitor could be orders of magnitude different. Susceptibility of Escherichia coli to glyphosate and the lack of it in Mycobacterium tuberculosis could be predicted by the in silico platform. Finally, as predicted and simulated in the in silico platform, the translation of growth inhibition to a cidal effect was able to be demonstrated experimentally by altering the carbon source from sorbitol to glucose.