Ketamine, a non-competitive N-methyl-D-aspartate receptor (NMDAR) antagonist, has been employed clinically as an intravenous anesthetic since the 1970s. More recently, ketamine has received attention for its rapid antidepressant effects and is actively being explored as a treatment for a wide range of neuropsychiatric syndromes. In model systems, ketamine appears to display a combination of neurotoxic and neuroprotective properties that are context dependent. At anesthetic doses applied during neurodevelopmental windows, ketamine contributes to inflammation, autophagy, apoptosis, and enhances levels of reactive oxygen species. At the same time, subanesthetic dose ketamine is a powerful activator of multiple parallel neurotrophic signaling cascades with neuroprotective actions that are not always NMDAR-dependent. Here, we summarize results from an array of preclinical studies that highlight a complex landscape of intracellular signaling pathways modulated by ketamine and juxtapose the somewhat contrasting neuroprotective and neurotoxic features of this drug.
Although current literature about the "cure versus care" issue tends to promote a patient-centered approach, the disease-centered approach remains the prevailing model in practice. The perceived dichotomy between the two approaches has created a barrier that could make it difficult for medical students and physicians to integrate psychosocial aspects of patient care into the prevailing disease-based model. This article examines the influence of the formal and hidden curricula on the perception of these two approaches and finds that the hidden curriculum perpetuates the notion that "cure" and "care" based approaches are dichotomous despite significant changes in formal curricula that promote a more integrated approach. The authors argue that it is detrimental for clinicians to view the two approaches as oppositional rather than complementary and attempt to give recommendations on how the influence of the hidden curriculum can be reduced to get a both-cure-and-care-approach, rather than an either-cure-or-care-approach.
Deployment and access to state-of-the-art diagnostic technologies remains a fundamental challenge in providing equitable global cancer care to low-resource settings. The expansion of digital pathology in recent years and its interface with computational biomarkers provides an opportunity to democratize access to personalized medicine. Here we describe a low-cost platform for digital side capture and computational analysis composed of open-source components. The platform provides low-cost ($200) digital image capture from glass slides and is capable of real-time computational image analysis using an open-source deep learning (DL) algorithm and Raspberry Pi ($35) computer. We validate the performance of deep learning models’ performance using images captured from the open-source workstation and show similar model performance when compared against significantly more expensive standard institutional hardware.
Goals of care conversations are often tough when patients face a poor prognosis, yet when patients are from a different culture it may be even more difficult. However, seeing cultural values as complementing rather than opposing could be beneficial to the care of the patient.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.