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Articles 1831 - 1833 of 1833
Full-Text Articles in Medical Genetics
Advancing Medical Applications Of Cancer Nanotechnology: Highlighting Two Decades Of The Nci's Nanotechnology Characterization Laboratory Service To The Research Community, Rachael M Crist, Yechezkel Barenholz, Ahuva Cern, Kate N Clark, Pieter R Cullis, Cheryl Dean, Neil Desai, Mauro Ferrari, Matthieu Germain, Carmen A Giacomantonio, Emma Grabarnik, Piotr Grodzinski, Atara Hod, Barry E Kennedy, Ruvanthi N Kularatne, Glen S Kwon, Emmanuel Loeb, Erin B Noftall, Len Pagliaro, Morteza Rasoulianboroujeni, Alexander Roth, Darren Rowles, Kulbir Singh, Nicole F Steinmetz, Zhanna Yehtina, Yao Zhang, Daniel Zilbersheid, Jeffrey D Clogston, Stephan T Stern, Marina A Dobrovolskaia
Advancing Medical Applications Of Cancer Nanotechnology: Highlighting Two Decades Of The Nci's Nanotechnology Characterization Laboratory Service To The Research Community, Rachael M Crist, Yechezkel Barenholz, Ahuva Cern, Kate N Clark, Pieter R Cullis, Cheryl Dean, Neil Desai, Mauro Ferrari, Matthieu Germain, Carmen A Giacomantonio, Emma Grabarnik, Piotr Grodzinski, Atara Hod, Barry E Kennedy, Ruvanthi N Kularatne, Glen S Kwon, Emmanuel Loeb, Erin B Noftall, Len Pagliaro, Morteza Rasoulianboroujeni, Alexander Roth, Darren Rowles, Kulbir Singh, Nicole F Steinmetz, Zhanna Yehtina, Yao Zhang, Daniel Zilbersheid, Jeffrey D Clogston, Stephan T Stern, Marina A Dobrovolskaia
Center for Medical Ethics and Health Policy Staff Publications
The Nanotechnology Characterization Laboratory (NCL) is a US federally funded resource providing characterization and expertise to the cancer nanomedicine research community. Founded as a formal partnership among the US National Cancer Institute (NCI), the US Food and Drug Administration (FDA), and the US National Institute of Standards and Technology (NIST), the NCL has spent two decades developing a one-of-a-kind service with broad multidisciplinary expertise to meet the needs of a rapidly evolving drug development field. To mark the 20th anniversary of the lab's founding, the NCL hosted a symposium to highlight the achievements of the cancer nanomedicine field, showcase novel, …
Methadone For Critically Ill Patients Under Mechanical Ventilation In The Intensive Care Unit: A Systematic Review, Sérgio Martins Pereira, Megan Abbott, João Francisco Figueiredo Marcondes Ferraz, Akash Goel, Andrea Rigamonti, Charmaine De Castro, Lisa Burry, Airton Leonardo De Oliveira Manoel, Michael Chaim Sklar
Methadone For Critically Ill Patients Under Mechanical Ventilation In The Intensive Care Unit: A Systematic Review, Sérgio Martins Pereira, Megan Abbott, João Francisco Figueiredo Marcondes Ferraz, Akash Goel, Andrea Rigamonti, Charmaine De Castro, Lisa Burry, Airton Leonardo De Oliveira Manoel, Michael Chaim Sklar
Center for Medical Ethics and Health Policy Staff Publications
Purpose: Pain may pose significant challenges in the intensive care unit, especially in mechanically ventilated patients. Methadone has recently emerged as an alternative option for eliciting acute analgesia. In this systematic review, we evaluated the use of methadone in mechanically ventilated patients in the intensive care unit.
Source: We searched MEDLINE, EMBASE, Wiley's Cochrane Library, CINAHL, PubMed (non-MEDLINE), Scopus, and LILACS databases from inception to January 24th, 2025. Eligible studies included randomized controlled trials and observational studies that compared the use of methadone to the standard of care or to other analgosedation strategies in mechanically ventilated patients in the intensive …
Id-Gba: Subgraph Extension With Information Distance Guilt By Association In Complex Networks, Predrag Obradovic, Vladimir Kovacevic, Aleksandar Milosavljevic, Varduhi Petrosyan
Id-Gba: Subgraph Extension With Information Distance Guilt By Association In Complex Networks, Predrag Obradovic, Vladimir Kovacevic, Aleksandar Milosavljevic, Varduhi Petrosyan
Faculty, Staff and Students Publications
Here, we introduce the ID-GBA (Information Distance Guilt By Association) method to expand highly connected sets of nodes by deploying a novel algorithm for subgraph extension based on the guilt-by-association principle and information distance. In this study, ID-GBA was utilized to expand disease clusters, and identify novel disease genes. We first validate its ability to expand related disease sets from disease/disease graphs built using Open Targets' gene association scores. We then analyze disease/control gene expression networks and show that ID-GBA recaptures known disease genes in nine disease/control graphs. Compared to existing methods such as Random Walk with Restarts and Personalized …