The protein p53 is a key regulator of cellular response to a wide variety of stressors. In cancer cells inhibitory regulators of p53 such as MDM2 and MDMX proteins are often overexpressed. We apply in silico techniques to better understand the role and interactions of these proteins in a cell cycle process. Furthermore we investigate the role of stochasticity in determining system behavior. We have found that stochasticity is able to affect system behavior profoundly. We also derive a general result for the way in which initially synchronized oscillating stochastic systems will fall out of synchronization with each other.
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http://dx.doi.org/10.3389/fonc.2013.00064 | DOI Listing |
J Trauma Nurs
January 2025
Author Affiliations: Penn Medicine, Department of Advanced Practice & Trauma Surgical Critical Care (Dr Saucier), Biostatistics, Hearing, & Speech, Ingram Cancer Center, Vanderbilt University School of Medicine (Dr Dietrich), School of Nursing, Vanderbilt University (Drs Maxwell and Minnick), Nashville, Tennessee; David E. Longnecker Associate Professor of Anesthesiology and Critical Care (Dr Lane-Fall), Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; and Surgical Service Line (Dr Messing), Inova Health System, Falls Church, Virginia.
Background: Patient transitions in critical care require coordination across provider roles and rely on the quality of providers' actions to ensure safety. Studying the behavior of providers who transition patients in critical care may guide future interventions that ultimately improve patient safety in this setting.
Objective: To establish the feasibility of using the Theory of Planned Behavior in a trauma environment and to describe provider behavior elements during trauma patient transfers (de-escalations) to non-critical care units.
J Trauma Nurs
January 2025
Author Affiliations: Castner Incorporated, Grand Island, NY (Dr Castner); Health Policy, Management, and Behavior, School of Public Health, University at Albany, Albany, New York (Dr Castner); Stony Brook University School of Nursing, Stony Brook, NY (Ms Zazzera); and Nursing Research and Evidence-Based Practice, Penn Medicine Lancaster General Health, Lancaster, PA (Dr Burchill).
Background: Trauma population health indicators are worsening in the United States. Nurses working in trauma care settings require specialized training for patient care. Little is known about national enumeration of nurses who hold skill-based trauma certificates.
View Article and Find Full Text PDFACS Appl Mater Interfaces
January 2025
State Key Laboratory of New Ceramics and Fine Processing, School of Materials Science and Engineering, Tsinghua University, Beijing 100084, China.
Low-loss microwave dielectrics are of significant importance for the miniaturization and integration of microwave devices. In this paper, the ceramics of nominal composition MgTiO ( = 3-6) are synthesized, and the correlations among their phase compositions, defect behaviors, and microwave dielectric properties are systematically investigated. The analyses indicate that the MgTiO ceramics are a biphasic system consisting of hexagonal ilmenite-structured MgTiO and cubic spinel-structured MgTiO.
View Article and Find Full Text PDFJ Public Health Manag Pract
November 2024
Author Affiliations: Department of Health Promotion, Education, and Behavior, University of South Carolina, Columbia, South Carolina (Ms Draper, Dr Younginer, and Mr Samin); Center for Excellence in Public Health, University of New England, Portland, Maine (Dr Rodriguez and Ms Bruno); and Department of Nutrition and Food Sciences, University of Rhode Island, Providence, Rhode Island (Dr Balestracci).
Objective: The study examines: 1) impacts of COVID-19 on the work of Supplemental Nutrition Assistance Program - Education (SNAP-Ed) implementers, 2) facilitators and barriers experienced in making adaptations, and 3) factors that would have helped with preparedness to adapt.
Design, Setting, And Participants: A purposive sample of 181 SNAP-Ed program implementers from across five states completed a survey or interview based on the study aims. Quantitative data was summarized with descriptive statistics and qualitative data was analyzed thematically.
This study introduces a high-resolution wind nowcasting model designed for aviation applications at Madeira International Airport, a location known for its complex wind patterns. By using data from a network of six meteorological stations and deep learning techniques, the produced model is capable of predicting wind speed and direction up to 30-minute ahead with 1-minute temporal resolution. The optimized architecture demonstrated robust predictive performance across all forecast horizons.
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