Cardiac arrest: An interdisciplinary scoping review of clinical literature from 2020.

Objectives: The Interdisciplinary Cardiac Arrest Research Review (ICARE) group was formed in 2018 to conduct an annual search of peer-reviewed literature relevant to cardiac arrest. Now in its third year, the goals of the review are to highlight annual updates in the interdisciplinary world of clinical cardiac arrest research with a focus on clinically relevant and impactful clinical and population-level studies from 2020.

Methods: A search of PubMed using keywords related to clinical research in cardiac arrest was conducted.

Unrecognized cardiac arrests: A one-year review of audio from emergency medical dispatch calls.

Objectives: Immediate recognition of out-of-hospital cardiac arrest (OHCA) by Emergency Medical Dispatch (EMD) operators is crucial to facilitate timely initiation of telephone cardiopulmonary resuscitation (T-CPR) and to enable the appropriate level of Emergency Medical Services (EMS) response. The goal of this study was to identify patterns that can increase EMD-level recognition of cardiac arrests prior to EMS arrival.

Methods: The Combined Communications Center in Alachua County, Florida provided audio recordings of all emergency calls from January 1, 2018 to November 16, 2018 dispatched as a chief complaint other than OHCA, but later identified as cardiac arrest.

Cardiac arrest: An interdisciplinary scoping review of the literature from 2019.

Objectives: The Interdisciplinary Cardiac Arrest Research Review (ICARE) group was formed in 2018 to conduct a systematic annual search of peer-reviewed literature relevant to cardiac arrest. Now in its second year, the goals of the review are to illustrate best practices in research and help reduce compartmentalization of knowledge by disseminating clinically relevant advances in the field of cardiac arrest across disciplines.

Methods: An electronic search of PubMed using keywords related to cardiac arrest was conducted.

Innovation in resuscitation: A novel clinical decision display system for advanced cardiac life support.

Introduction: The Advanced Cardiac Life Support (ACLS) Clinical Decision Display System (CDDS) is a novel application designed to optimize team organization and facilitate decision-making during ACLS resuscitations. We hypothesized that resuscitation teams would more consistently adhere to ACLS guideline time intervals in simulated resuscitation scenarios with the CDDS compared to without.

Methods: We conducted a simulation-based, non-blinded, randomized, crossover-design study with resuscitation teams comprised of Emergency Medicine physicians, registered nurses, critical care technicians, and paramedics.

Interactions between specific phytoplankton and bacteria affect lake bacterial community succession.

Time-series observations and a phytoplankton manipulation experiment were combined to test the hypothesis that phytoplankton succession effects changes in bacterial community composition. Three humic lakes were sampled weekly May-August and correlations between relative abundances of specific phytoplankton and bacterial operational taxonomic units (OTUs) in each time series were determined. To experimentally characterize the influence of phytoplankton, bacteria from each lake were incubated with phytoplankton from one of the three lakes or no phytoplankton.

Gut microbiome metagenomics analysis suggests a functional model for the development of autoimmunity for type 1 diabetes.

Recent studies have suggested a bacterial role in the development of autoimmune disorders including type 1 diabetes (T1D). Over 30 billion nucleotide bases of Illumina shotgun metagenomic data were analyzed from stool samples collected from four pairs of matched T1D case-control subjects collected at the time of the development of T1D associated autoimmunity (i.e.

Toward defining the autoimmune microbiome for type 1 diabetes.

Several studies have shown that gut bacteria have a role in diabetes in murine models. Specific bacteria have been correlated with the onset of diabetes in a rat model. However, it is unknown whether human intestinal microbes have a role in the development of autoimmunity that often leads to type 1 diabetes (T1D), an autoimmune disorder in which insulin-secreting pancreatic islet cells are destroyed.

PANGEA: pipeline for analysis of next generation amplicons.

High-throughput DNA sequencing can identify organisms and describe population structures in many environmental and clinical samples. Current technologies generate millions of reads in a single run, requiring extensive computational strategies to organize, analyze and interpret those sequences. A series of bioinformatics tools for high-throughput sequencing analysis, including pre-processing, clustering, database matching and classification, have been compiled into a pipeline called PANGEA.