RESUMEN
Collaborative intelligence reflects the promise and limits of leveraging artificial intelligence (AI) technologies in clinical care. It involves the use of advanced analytics and computing power with an understanding that humans bear responsibility for the accuracy, completeness and any inherent bias found in the training data. Clinicians benefit from using this technology to address increased complexity and information overload, support continuous care and optimized resource allocation, and to enact efforts to eradicate disparities in health care access and quality. This requires active clinician engagement with the technology, a general understanding of how the machine produced its insight, the limitations of the algorithms, and the need to screen datasets for bias. Importantly, by interacting, the clinician and the analytics will create trust based on the clinician's critical thinking skills leveraged to discern value of machine outputs within clinical context. Utilization of collaborative intelligence should be staged with the level of understanding and evidence. It is particularly well suited to low-complexity non-urgent care and to identifying individuals at rising risk within a population. Clinician involvement in algorithm development and the amassing of evidence to support safety and efficacy will propel adoption. Utilization of collaborative intelligence represents the natural progression of health care innovation, and if thoughtfully constructed and equitably deployed, holds the promise to decrease clinician burden and improve access to care.
RESUMEN
Obesity is a major risk factor for psoriasis, but how obesity disrupts the regulatory mechanisms that keep skin inflammation in check is unclear. Here, we found that skin was enriched with a unique population of CD4+Foxp3+ regulatory T (Treg) cells expressing the nuclear receptor peroxisome proliferation-activated receptor gamma (PPARγ). PPARγ drove a distinctive transcriptional program and functional suppression of IL-17A+ γδ T cell-mediated psoriatic inflammation. Diet-induced obesity, however, resulted in a reduction of PPARγ+ skin Treg cells and a corresponding loss of control over IL-17A+ γδ T cell-mediated inflammation. Mechanistically, PPARγ+ skin Treg cells preferentially took up elevated levels of long-chain free fatty acids in obese mice, which led to cellular lipotoxicity, oxidative stress, and mitochondrial dysfunction. Harnessing the anti-inflammatory properties of these PPARγ+ skin Treg cells could have therapeutic potential for obesity-associated inflammatory skin diseases.
Asunto(s)
Psoriasis , Linfocitos T Reguladores , Animales , Ratones , PPAR gamma , Interleucina-17 , Piel , Psoriasis/inducido químicamente , Inflamación , ObesidadRESUMEN
Given the unprecedented growth of global health initiatives in the past decade, informal diplomacy between technical partners plays an increasingly important role in shaping opportunities and outcomes. This article describes a course developed and executed specifically to equip U.S. military health professionals with core skills in practical diplomacy critical to help them successfully plan and implement public health surveillance, research, and capacity building programs with partner nation governments and organizations. We identified core competencies in practical diplomacy for laboratory and public health researchers, catalogued and evaluated existing training programs, and then developed a pilot course in global health diplomacy for military medical researchers. The pilot course was held in June 2012, and focused on analyzing contemporary issues related to global health diplomacy through the framework of actors, drivers, and policies that affect public health research and capacity-building, beginning at the level of global health governance and cooperation and moving progressively to regional (supranational), national, and institutional perspective. This course represents an approach geared toward meeting the needs specific to U.S. military public health personnel and researchers working in international settings.