Simple fixes of unintended large genetic insertions uncovered in genome editing offer improved safety and reliability.

New research, published recently in Proceedings of the National Academy of Sciences, uncovers the unique dynamics governing the endoplasmic reticulum (ER)’s evolution and addresses the long-standing mystery of just how this organelle sustains life at the cellular level, with implications for understanding disease.  

A groundbreaking study by researchers from the University of Namur, Belgium introduces a novel, contactless method for identifying animal species used in historical parchment manuscripts, an essential aspect of cultural heritage studies. Traditionally, species identification has been performed using slightly invasive methods, but this innovative classification model instead uses reflectance spectrophotometry, covering the ultraviolet, visible and near-infrared spectra, combined with machine learning for data analysis. This research was published Oct. 17 in Intelligent Computing, a Science Partner Journal, in an article titled “Animal Species Identification in Historical Parchments by Continuous Wavelet Transform–Convolutional Neural Network Classifier Applied to Ultraviolet–Visible–Near-Infrared Spectroscopic Data.”