Expanding the editable genome and CRISPR-Cas9 versatility using DNA cutting-free gene targeting based on in trans paired nicking

Genome editing typically involves recombination between donor nucleic acids and acceptor genomic sequences subjected to double-stranded DNA breaks (DSBs) made by programmable nucleases (e.g. CRISPR-Cas9). Yet, nucleases yield off-target mutations and, most pervasively, unpredictable target allele disruptions. Remarkably, to date, the untoward phenotypic consequences of disrupting allelic and non-allelic (e.g. pseudogene) sequences have received scant scrutiny and, crucially, remain to be addressed. Here, we demonstrate that gene-edited cells can lose fitness as a result of DSBs at allelic and non-allelic target sites and report that simultaneous single-stranded DNA break formation at donor and acceptor DNA by CRISPR-Cas9 nickases (in trans paired nicking) mostly overcomes such disruptive genotype-phenotype associations. Moreover, in trans paired nicking gene editing can efficiently and precisely add large DNA segments into essential and multiple-copy genomic sites. As shown herein by genotyping assays and high-throughput genome-wide sequencing of DNA translocations, this is achieved while circumventing most allelic and non-allelic mutations and chromosomal rearrangements characteristic of nuclease-dependent procedures. Our work demonstrates that in trans paired nicking retains target protein dosages in gene-edited cell populations and expands gene editing to chromosomal tracts previously not possible to modify seamlessly due to their recurrence in the genome or essentiality for cell function.Stem cells & developmental biolog

Lanthanide Induced Photoluminescence in Lead-Free Cs₂AgBiBr₆ Bulk Perovskite: Insights From Optical and Theoretical Investigations

The search for materials substituting toxic lead in metal halide perovskites has recently placed emphasis on the Cs2AgBiBr6 double perovskite as a possible candidate. The poor light-emissive features of this species, mainly associated to the indirect nature of the band gap and the strongly bound exciton, however, currently make it unsuitable for solid-state lighting applications. Doping with lanthanides is an established strategy to implement luminescence in poorly emissive materials, with the additional advantage of tuning the wavelength of emission independently from the host band structure. We discuss here the impact of Eu- and Yb-doping on the absorption and emission properties of Cs2AgBiBr6 polycrystalline thin films, obtained from solution-processing of hydrothermally synthesized bulk crystalline powders, by combining experiments and density functional theory calculations. Eu(III) incorporation does not lead to the characteristic 5D0→7F2 emission feature at 2 eV, while only a weak sub band-gap radiative emission ascribed to a trap-assisted recombination process is reported. On the other hand, we demonstrate that Yb(III) incorporated in the bulk double perovskite leads to an intense and exclusive photoluminescence emission in the near-infrared (NIR) from thin films, as a result of the efficient sensitization of the lanthanide centered 2F5/2→2F7/2 transition, with favorable mid-gap energetic position. Yb-doping may be thus exploited for the future development of stable and sustainable perovskite NIR-light emitters

Lanthanide-Induced Photoluminescence in Lead-Free Cs2AgBiBr6Bulk Perovskite: Insights from Optical and Theoretical Investigations

Emphasis was recently placed on the Cs2AgBiBr6 double perovskite as a possible candidate to substitute toxic lead in metal halide perovskites. However, its poor light-emissive features currently make it unsuitable for solid-state lighting. Lanthanide doping is an established strategy to implement luminescence in poorly emissive materials, with the additional advantage of fine-tuning the emission wavelength. We discuss here the impact of Eu and Yb doping on the optical properties of Cs2AgBiBr6 thin films, obtained from the solution processing of hydrothermally synthesized bulk crystalline powders, by combining experiments and density functional theory calculations. Eu(III) incorporation does not lead to the characteristic 5D0 → 7F2 emission feature at 2 eV, while only a weak trap-assisted sub-band gap radiative emission is reported. Oppositely, we demonstrate that incorporated Yb(III) leads to an intense and exclusive photoluminescence emission in the near-infrared as a result of the efficient sensitization of the lanthanide 2F5/2 → 2F7/2 transition

Supervised machine learning on Galactic filaments. Revealing the filamentary structure of the Galactic interstellar medium

Context. Filaments are ubiquitous in the Galaxy, and they host star formation. Detecting them in a reliable way is therefore key towards our understanding of the star formation process. Aims: We explore whether supervised machine learning can identify filamentary structures on the whole Galactic plane. Methods: We used two versions of UNet-based networks for image segmentation. We used H2 column density images of the Galactic plane obtained with Herschel Hi-GAL data as input data. We trained the UNet-based networks with skeletons (spine plus branches) of filaments that were extracted from these images, together with background and missing data masks that we produced. We tested eight training scenarios to determine the best scenario for our astrophysical purpose of classifying pixels as filaments. Results: The training of the UNets allows us to create a new image of the Galactic plane by segmentation in which pixels belonging to filamentary structures are identified. With this new method, we classify more pixels (more by a factor of 2 to 7, depending on the classification threshold used) as belonging to filaments than the spine plus branches structures we used as input. New structures are revealed, which are mainly low-contrast filaments that were not detected before. We use standard metrics to evaluate the performances of the different training scenarios. This allows us to demonstrate the robustness of the method and to determine an optimal threshold value that maximizes the recovery of the input labelled pixel classification. Conclusions: This proof-of-concept study shows that supervised machine learning can reveal filamentary structures that are present throughout the Galactic plane. The detection of these structures, including low-density and low-contrast structures that have never been seen before, offers important perspectives for the study of these filaments

Surgical Explantation of Transcatheter Aortic Valve Bioprostheses: A Statewide Experience

BACKGROUND: Despite the rapid adoption of transcatheter aortic valve replacement (TAVR) since its initial approval in 2011, the frequency and outcomes of surgical explantation of TAVR devices (TAVR-explant) is poorly understood. METHODS: Patients undergoing TAVR-explant between January 2012 and June 2020 at 33 hospitals in Michigan were identified in the Society of Thoracic Surgeons Database and linked to index TAVR data from the Transcatheter Valve Therapy Registry through a statewide quality collaborative. The primary outcome was operative mortality. Indications for TAVR-explant, contraindications to redo TAVR, operative data, and outcomes were collected from Society of Thoracic Surgeons and Transcatheter Valve Therapy databases. Baseline Society of Thoracic Surgeons Predicted Risk of Mortality was compared between index TAVR and TAVR-explant. RESULTS: Twenty-four surgeons at 12 hospitals performed TAVR-explants in 46 patients (median age, 73). The frequency of TAVR-explant was 0.4%, and the number of explants increased annually. Median time to TAVR-explant was 139 days and among known device types explanted, most were self-expanding valves (29/41, 71%). Common indications for TAVR-explant were procedure-related failure (35%), paravalvular leak (28%), and need for other cardiac surgery (26%). Contraindications to redo TAVR included need for other cardiac surgery (28%), unsuitable noncoronary anatomy (13%), coronary obstruction (11%), and endocarditis (11%). Overall, 65% (30/46) of patients underwent concomitant procedures, including aortic repair/replacement in 33% (n=15), mitral surgery in 22% (n=10), and coronary artery bypass grafting in 16% (n=7). The median Society of Thoracic Surgeons Predicted Risk of Mortality was 4.2% at index TAVR and 9.3% at TAVR-explant (P=0.001). Operative mortality was 20% (9/46) and 76% (35/46) of patients had in-hospital complications. Of patients alive at discharge, 37% (17/37) were discharged home and overall 3-month survival was 73±14%. CONCLUSIONS: TAVR-explant is rare but increasing, and its clinical impact is substantial. As the utilization of TAVR expands into younger and lower-risk patients, providers should consider the potential for future TAVR-explant during selection of an initial valve strategy

VST: the telescope progress toward stars

The VST telescope is in an advanced stage of integration in Chile, after a period of work spent mainly on the active optics system, started in mid-2007. We present the results of the recent work on the primary and secondary mirror support systems and on the mirror cell auxiliary units

Vialactea Visual Analytics tool for Star Formation studies of the Galactic Plane

We present a visual analytics tool, based on the VisIVO suite, to exploit a combination of all new-generation surveys of the Galactic Plane to study the star formation process of the Milky Way. The tool has been developed within the VIALACTEA project, founded by the 7th Framework Programme of the European Union, that creates a common forum for the major new-generation surveys of the Milky Way Galactic Plane from the near infrared to the radio, both in thermal continuum and molecular lines. Massive volumes of data are produced by space missions and ground-based facilities and the ability to collect and store them is increasing at a higher pace than the ability to analyze them. This gap leads to new challenges in the analysis pipeline to discover information contained in the data. Visual analytics focuses on handling these massive, heterogeneous, and dynamic volumes of information accessing the data previously processed by data mining algorithms and advanced analysis techniques with highly interactive visual interfaces offering scientists the opportunity for in-depth understanding of massive, noisy, and high-dimensional data

Constructing Impactful Machine Learning Research for Astronomy: Best Practices for Researchers and Reviewers

Machine learning has rapidly become a tool of choice for the astronomical community. It is being applied across a wide range of wavelengths and problems, from the classification of transients to neural network emulators of cosmological simulations, and is shifting paradigms about how we generate and report scientific results. At the same time, this class of method comes with its own set of best practices, challenges, and drawbacks, which, at present, are often reported on incompletely in the astrophysical literature. With this paper, we aim to provide a primer to the astronomical community, including authors, reviewers, and editors, on how to implement machine learning models and report their results in a way that ensures the accuracy of the results, reproducibility of the findings, and usefulness of the method.Comment: 14 pages, 3 figures; submitted to the Bulletin of the American Astronomical Societ