Asunto(s)
Servicios Médicos de Urgencia , Gases Nobles/farmacología , Síndrome de Paro Post-Cardíaco/tratamiento farmacológico , Terapia Respiratoria/métodos , Animales , Argón/farmacología , Argón/uso terapéutico , Monóxido de Carbono/farmacología , Monóxido de Carbono/uso terapéutico , Modelos Animales de Enfermedad , Servicios Médicos de Urgencia/métodos , Servicios Médicos de Urgencia/normas , Helio/farmacología , Helio/uso terapéutico , Humanos , Hidrógeno/farmacología , Hidrógeno/uso terapéutico , Sulfuro de Hidrógeno/farmacología , Sulfuro de Hidrógeno/uso terapéutico , Óxido Nítrico/farmacología , Óxido Nítrico/uso terapéutico , Gases Nobles/uso terapéutico , Síndrome de Paro Post-Cardíaco/fisiopatología , Terapia Respiratoria/normas , Terapia Respiratoria/estadística & datos numéricos , Xenón/farmacología , Xenón/uso terapéuticoRESUMEN
The COVID-19 pandemic has created unique challenges for the U.S. healthcare system due to the staggering mismatch between healthcare system capacity and patient demand. The healthcare industry has been a relatively slow adopter of digital innovation due to the conventional belief that humans need to be at the center of healthcare delivery tasks. However, in the setting of the COVID-19 pandemic, artificial intelligence (AI) may be used to carry out specific tasks such as pre-hospital triage and enable clinicians to deliver care at scale. Recognizing that the majority of COVID-19 cases are mild and do not require hospitalization, Partners HealthCare (now Mass General Brigham) implemented a digitally-automated pre-hospital triage solution to direct patients to the appropriate care setting before they showed up at the emergency department and clinics, which would otherwise consume resources, expose other patients and staff to potential viral transmission, and further exacerbate supply-and-demand mismatching. Although the use of AI has been well-established in other industries to optimize supply and demand matching, the introduction of AI to perform tasks remotely that were traditionally performed in-person by clinical staff represents a significant milestone in healthcare operations strategy.
Asunto(s)
Inteligencia Artificial , COVID-19 , Prestación Integrada de Atención de Salud/organización & administración , Triaje/métodos , Toma de Decisiones Clínicas/métodos , Líneas Directas/estadística & datos numéricos , Humanos , Massachusetts , Pandemias , Gestión de la Salud PoblacionalRESUMEN
NF-kappaB activation in bronchial epithelial cells is important for the development of allergic airway inflammation, and may control the expression of critical mediators of allergic inflammation such as thymic stromal lymphopoietin (TSLP) and the chemokine CCL20. Members of the caspase recruitment domain (CARD) family of proteins are differentially expressed in tissue and help mediate NF-kappaB activity in response to numerous stimuli. Here we demonstrate that CARMA3 (CARD10) is specifically expressed in human airway epithelial cells, and that expression of CARMA3 in these cells leads to activation of NF-kappaB. CARMA3 has recently been shown to mediate NF-kappaB activation in embryonic fibroblasts after stimulation with lysophosphatidic acid (LPA), a bioactive lipid-mediator that is elevated in the lungs of individuals with asthma. Consistent with this, we demonstrate that stimulation of airway epithelial cells with LPA leads to increased expression of TSLP and CCL20. We then show that inhibition of CARMA3 activity in airway epithelial cells reduces LPA-mediated NF-kappaB activity and the production of TSLP and CCL20. In conclusion, these data demonstrate that LPA stimulates TSLP and CCL20 expression in bronchial epithelial cells via CARMA3-mediated NF-kappaB activation.