ABSTRACT
PROBLEM: The COVID-19 pandemic has challenged health care systems in an unprecedented way by imposing new demands on health care resources and scientific knowledge. There has also been an exceedingly fast accumulation of new information on this novel virus. As the traditional peer-review process takes time, there is currently a significant gap between the ability to generate new data and the ability to critically evaluate them. This problem of an excess of mixed-quality data, or infodemic, is echoing throughout the scientific community. APPROACH: The authors aimed to help their colleagues at the Rambam Medical Center, Haifa, Israel, manage the COVID-19 infodemic with a methodologic solution: establishing an in-house mechanism for continuous literature review and knowledge distribution (March-April 2020). Their methodology included the following building blocks: a dedicated literature review team, artificial intelligence-based research algorithms, brief written updates in a graphical format, large-scale webinars and online meetings, and a feedback loop. OUTCOMES: During the first month (April 2020), the project produced 21 graphical updates. After consideration of feedback from colleagues and final editing, 13 graphical updates were uploaded to the center's website; of these, 31% addressed the clinical presentation of the disease and 38% referred to specific treatments. This methodology as well as the graphical updates it generated were adopted by the Israeli Ministry of Health and distributed in a hospital preparation kit. NEXT STEPS: The authors believe they have established a novel methodology that can assist in the battle against COVID-19 by making high-quality scientific data more accessible to clinicians. In the future, they expect this methodology to create a favorable uniform standard for evidence-guided health care during infodemics. Further evolution of the methodology may include evaluation of its long-term sustainability and impact on the day-to-day clinical practice and self-confidence of clinicians who treat COVID-19 patients.
Subject(s)
Academic Medical Centers , Biomedical Research , COVID-19 , Evidence-Based Practice/methods , Information Dissemination/methods , Information Services , Review Literature as Topic , Academic Medical Centers/methods , Academic Medical Centers/organization & administration , Artificial Intelligence , COVID-19/diagnosis , COVID-19/epidemiology , COVID-19/therapy , Disease Outbreaks , Evidence-Based Practice/organization & administration , Humans , Information Services/organization & administration , Israel/epidemiology , Peer Review, ResearchABSTRACT
Tissue engineering provides unique opportunities for disease modeling, drug testing, and regenerative medicine applications. The use of cell-seeded scaffolds to promote tissue development is the hallmark of the tissue engineering. Among the different types of scaffolds (derived from either natural or synthetic polymers) used in the field, the use of decellularized tissues/organs is specifically attractive. The decellularization process involves the removal of native cells from the original tissue, allowing for the preservation of the three-dimensional (3D) macroscopic and microscopic structures of the tissue and extracellular matrix (ECM) composition. Following recellularization, the resulting scaffold provides the seeded cells with the appropriate biological signals and mechanical properties of the original tissue. Here, we describe different methods to create viable scaffolds from decellularized heart and liver as useful tools to study and exploit ECM biological key factors for the generation of engineered tissues with enhanced regenerative properties.
