Health
NIH awards research grant for COVID-19 detection technology
The National Institutes of Health (NIH) recently awarded eight research grants for the development of new technologies aimed at early diagnosis of severe COVID-19 infections in pediatric patients.
Awarded for predicting severity of viral-associated inflammatory disease in children in NIH’s Laboratory Diagnostics and Artificial Intelligence (PreVAILkIds) initiative. They support programs on the use of new approaches and tools to address COVID-19 testing and surveillance gaps.
Some cases of COVID-19 lead to mild or no symptoms, while others lead to severe consequences such as pediatric multisystem inflammatory syndrome (MIS-C), which leads to inflammation of one or more organs. leads to These include kidneys, lungs, heart, skin, brain, eyes, and digestive tract.
Research funded from the 2020 award has led to prototype methods and techniques with potential clinical use. The results of his PreVAILkIds study in 2020 will contribute to testing technologies that can detect immune cells associated with MIS-C and a database to determine a child’s risk of her MIS-C and severe her COVID-19. Connected.
The new award will enable researchers to develop further methods for rapidly diagnosing MIS-C and identifying individuals at increased risk of severe long-term effects from COVID-19.
One of the most recent winners is Jane C. Burns, MD of the University of California. Burns was awarded for diagnosing and predicting children’s risk of COVID-19-related illnesses.
Another recipient of this award is Dr. Cedric Manlhiot of Johns Hopkins University. Manlhiot was awarded for his data science approach to identifying and managing MIS-C associated with COVID-19.
The third winner is Dr. Ananth V. Annapragada of Baylor College of Medicine, who used artificial intelligence to assess COVID-19 risk in children. The fourth winner is Audrey R. Odom John, MD, PhD, from Children’s Hospital of Philadelphia, who diagnosed her with MIS-C in a febrile child.
The fifth winner is Usha Sethuraman, M.D., Ph.D., who used a severity protector that integrates salivary transcriptomics and proteomics with multi-neural network intelligence in children with COVID-19.
The sixth winner is Juan C. Salazar, MD, MPH, Children’s Medical Center, Connecticut, who identified a biomarker signature of prognostic value for MIS-C. The seventh winner is Charles Yen Chiu, MD, PhD, from the University of California, for the discovery and clinical validation of host biomarkers for disease severity and his MIS-C in the case of COVID-19.
The final winner is Lawrence Kleinman, M.D., M.P.H., from Rutgers Robert Wood Johnson Medical School for his clinical and translational approaches to predicting severe illness in children with COVID-19. Created a network to grow.
reference
NIH is funding eight studies to advance rapid diagnosis of COVID-19-related inflammatory syndromes in children. National Institutes of Health. January 9, 2023. Accessed 10 January 2023. https://www.nih.gov/news-events/news-releases/nih-funds-eight-studies-advance-rapid-diagnosis-covid-19-related-sensitive-syndrome-children
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Sources 2/ https://www.contemporarypediatrics.com/view/nih-awards-research-grants-for-covid-19-detection-technologies The mention sources can contact us to remove/changing this article |
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