Publications by authors named "I Rubin"

Objectives: The aim of this systematic review was to investigate the effect of antibiotics on the eradication of multidrug-resistant organisms (MRO) in intestinal carriers. We defined multidrug-resistant organisms as vancomycin-resistant (VREfm), and multidrug-resistant Gram-negative Methods: We searched the EMBASE, Cochrane Central, and PubMed databases from inception to medio November 2023. We included randomised and controlled clinical trials (RCTs), that investigated the effect of antibiotics on the eradication of multidrug-resistant organisms in intestinal carriers.

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Objectives: To determine if vancomycin-resistant (VREfm) carriers carry the same VREfm clone after a minimum follow-up of 365 days. For those carrying the same clone, we investigated the genomic evolution per year per genome.

Methods: We used WGS results to assign VREfm clones to each isolate and determine clone shifts.

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The aim of this review was to assess the efficacy and safety of GG (LGG) (previously known as GG) for the eradication of vancomycin-resistant (VREfm) in colonized carriers. We searched Cochrane Central, EMBASE, and the PubMed Library from inception to 21 August 2023, for randomized controlled trials (RCTs) investigating the effectiveness of LGG for the eradication of gastrointestinal carriage of VREfm. An initial screening was performed followed by a full-text evaluation of the papers.

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Recent studies at individual cell resolution have revealed phenotypic heterogeneity in nominally clonal tumor cell populations. The heterogeneity affects cell growth behaviors, which can result in departure from the idealized uniform exponential growth of the cell population. Here we measured the stochastic time courses of growth of an ensemble of populations of HL60 leukemia cells in cultures, starting with distinct initial cell numbers to capture a departure from the uniform exponential growth model for the initial growth ("take-off").

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Article Synopsis
  • Knowledge graphs are increasingly used for representing knowledge, but their complexity and the diversity of sources make integration difficult due to semantic incompatibilities.
  • The Biomedical Translator Consortium has created a question-answering system called the Translator, which aids human reasoning by addressing biomedical queries related to various diseases.
  • A monthly "Question-of-the-Month Challenge" has been established to explore specific issues like drug-related liver injury and coronavirus, providing insights and identifying technical challenges to enhance the Translator system, while also comparing it to Large Language Models like ChatGPT.
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