A near infrared (NIR) fluorescent polymeric nanoparticle, commercialized under the name X-Sight 761 (X761), was tested for compatibility with pre-clinical in vivo imaging applications. In one experiment, an optical clearance profile was obtained by performing whole animal fluorescence imaging over the course of 48 hours on mice injected intravenously with X761. In a second trial, a temporal biodistribution was assessed by conducting necropsy and ex vivo analysis of X761 tissue accumulation at selected time points over a 48 hours period after i.v. injection. Taken together, the data demonstrate a sustained distribution of X761 into all major tissues over the time course, with an extremely low net clearance from the animal. This unique behavior is attributed to cell uptake mediated by the polycationic surface of X761. These properties negate the use of X761 as a reporter within a classical targeted molecular probe construct, in which selective concentration at a target site and rapid clearance from background tissues are needed to develop contrast. Nevertheless, the brightness and stability of X761 is well suited for a range of other applications, ranging from broad based in vivo drug delivery to in vitro fluorescence assays.
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http://dx.doi.org/10.1166/jbn.2013.1477 | DOI Listing |
Crit Care
January 2025
Division of Digestive and Liver Diseases, Columbia University Irving Medical Center, 630 West 168th Street, P&S 3-401, New York, NY, 10032, USA.
Background: Patients admitted to the intensive care unit (ICU) often have gut colonization with pathogenic bacteria and such colonization is associated with increased risk for death and infection. We conducted a trial to determine whether a prebiotic would improve the gut microbiome to decrease gut pathogen colonization and decrease downstream risk for infection among newly admitted medical ICU patients with sepsis.
Methods: This was a randomized, double-blind, placebo-controlled trial of adults who were admitted to the medical ICU for sepsis and were receiving broad-spectrum antibiotics.
Implement Sci
January 2025
Nursing Research Institute, St Vincent's Health Network Sydney, St Vincent's Hospital Melbourne & Australian Catholic University, Level 5, deLacy Building, St. Vincent's Hospital, 390 Victoria Street, Darlinghurst, 2010, New South Wales, Australia.
Background: Despite evidence supporting interventions that improve outcomes for patients with stroke, their implementation remains suboptimal. Facilitation can support implementation of research into clinical practice by helping people develop the strategies to implement change. However, variability in the amount (dose) and type of facilitation activities/facilitator roles that make up the facilitation strategies (content), may affect the effectiveness of facilitation.
View Article and Find Full Text PDFNat Chem Biol
January 2025
Department of Chemistry, University of Wisconsin-Madison, Madison, WI, USA.
Protein aggregates are associated with numerous diseases. Here we report a platform for the rapid phenotypic selection of protein aggregation inhibitors from genetically encoded cyclic peptide libraries in Escherichia coli based on phage-assisted continuous evolution (PACE). We developed a new PACE-compatible selection for protein aggregation inhibition and used it to identify cyclic peptides that suppress amyloid-β42 and human islet amyloid polypeptide aggregation.
View Article and Find Full Text PDFSci Rep
January 2025
Enzymology and Applied Biocatalysis Research Center, Faculty of Chemistry and Chemical Engineering, Babeș-Bolyai University, Arany János Street 11, 400028, Cluj-Napoca, Romania.
Efficient monitoring of the enzymatic PET-hydrolysis is crucial for developing novel plastic-degrading biocatalysts. Herein, we aimed to upgrade in terms of accuracy the analytical methods useful for monitoring enzymatic PET-degradation. For the HPLC-based assessment, the incorporation of an internal standard within the analytic procedure enabled a more accurate quantification of the overall TPA content and the assessment of molar distributions and relative content of each aromatic degradation product.
View Article and Find Full Text PDFSci Rep
January 2025
EIAS Data Science Lab, College of Computer and Information Sciences, Prince Sultan University, 11586, Riyadh, Saudi Arabia.
During the Covid-19 pandemic, the widespread use of social media platforms has facilitated the dissemination of information, fake news, and propaganda, serving as a vital source of self-reported symptoms related to Covid-19. Existing graph-based models, such as Graph Neural Networks (GNNs), have achieved notable success in Natural Language Processing (NLP). However, utilizing GNN-based models for propaganda detection remains challenging because of the challenges related to mining distinct word interactions and storing nonconsecutive and broad contextual data.
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