https://www.selleckchem.com/products/ITF2357(Givinostat).html Adenine base editors (ABE) enable single nucleotide modifications without the need for double-stranded DNA breaks (DSBs) induced by conventional CRIPSR/Cas9-based approaches. However, most approaches that employ ABEs require inefficient downstream technologies to identify desired targeted mutations within large populations of manipulated cells. In this study, we developed a fluorescence-based method, named "Cas9-mediated adenosine transient reporter for editing enrichment" (CasMAs-TREE; herein abbreviated XMAS-TREE), to facilitate the real-time identification of base-edited cell populations. To establish a fluorescent-based assay able to detect ABE activity within a cell in real time, we designed a construct encoding a mCherry fluorescent protein followed by a stop codon (TGA) preceding the coding sequence for a green fluorescent protein (GFP), allowing translational readthrough and expression of GFP after A-to-G conversion of the codon to "TGG." At several independent loci, we demonstrate that XMAS-TREE n the future, XMAS-TREE will greatly accelerate the application of ABEs in biomedical research. Knowledge is often produced from data generated in scientific investigations. An ever-growing number of scientific studies in several domains result into a massive amount of data, from which obtaining new knowledge requires computational help. For example, Alzheimer's Disease, a life-threatening degenerative disease that is not yet curable. As the scientific community strives to better understand it and find a cure, great amounts of data have been generated, and new knowledge can be produced. A proper representation of such knowledge brings great benefits to researchers, to the scientific community, and consequently, to society. In this article, we study and evaluate a semi-automatic method that generates knowledge graphs (KGs) from biomedical texts in the scientific literature. Our solution explores natural la