Comparison of telerobotic and conventional ultrasonography in children: a crossover bicentric pilot study.

Background: The MELODY system allows for performing ultrasonography on a patient remotely and has been proposed to assess disease characteristics in the context of the coronavirus disease 2019 (COVID-19) pandemic. The aim of this interventional crossover study was to address the feasibility of the system in children aged 1 to 10 years old. Methods: Children underwent ultrasonography with a telerobotic ultrasound system followed by a second conventional examination by a different sonographer. Results: In total, 38 children were enrolled, and 76 examinations were performed, with 76 scans analyzed. The mean [standard deviation (SD)] age of participants was 5.7 (2.7) years (range, 1-10 years). We found substantial agreement between telerobotic and conventional ultrasonography [κ=0.74 (95% CI: 0.53-0.94), P<0.005]. The mean (SD) duration was longer for telerobotic than conventional examinations [26.0 (2.5) vs. 13.9 (11.2) min, P<0.0001]. Abdominal organs and abnormalities were similarly visualized on telerobotic and conventional ultrasonography. Cardiac echocardiography provided reliable diagnoses, with non-significantly different measurements with both techniques, although the visualization score was significantly higher with conventional than telerobotic ultrasonography (P<0.05). On lung analysis, both examinations identified consolidations and pleural effusion, whereas visualization and total lung score were similar with the 2 techniques. Overall, 45% of parents reported that their children felt less pressure with the telerobotic system. Conclusions: Telerobotic ultrasonography may be effective, feasible, and well-tolerated in children.

Completing the TRB family: newly characterized members show ancient evolutionary origins and distinct localization, yet similar interactions.

Telomere repeat binding proteins (TRBs) belong to a family of proteins possessing a Myb-like domain which binds to telomeric repeats. Three members of this family (TRB1, TRB2, TRB3) from Arabidopsis thaliana have already been described as associated with terminal telomeric repeats (telomeres) or short interstitial telomeric repeats in gene promoters (telo-boxes). They are also known to interact with several protein complexes: telomerase, Polycomb repressive complex 2 (PRC2) E(z) subunits and the PEAT complex (PWOs-EPCRs-ARIDs-TRBs). Here we characterize two novel members of the TRB family (TRB4 and TRB5). Our wide phylogenetic analyses have shown that TRB proteins evolved in the plant kingdom after the transition to a terrestrial habitat in Streptophyta, and consequently TRBs diversified in seed plants. TRB4-5 share common TRB motifs while differing in several others and seem to have an earlier phylogenetic origin than TRB1-3. Their common Myb-like domains bind long arrays of telomeric repeats in vitro, and we have determined the minimal recognition motif of all TRBs as one telo-box. Our data indicate that despite the distinct localization patterns of TRB1-3 and TRB4-5 in situ, all members of TRB family mutually interact and also bind to telomerase/PRC2/PEAT complexes. Additionally, we have detected novel interactions between TRB4-5 and EMF2 and VRN2, which are Su(z)12 subunits of PRC2.

Image analysis workflows to reveal the spatial organization of cell nuclei and chromosomes.

Nucleus, chromatin, and chromosome organization studies heavily rely on fluorescence microscopy imaging to elucidate the distribution and abundance of structural and regulatory components. Three-dimensional (3D) image stacks are a source of quantitative data on signal intensity level and distribution and on the type and shape of distribution patterns in space. Their analysis can lead to novel insights that are otherwise missed in qualitative-only analyses. Quantitative image analysis requires specific software and workflows for image rendering, processing, segmentation, setting measurement points and reference frames and exporting target data before further numerical processing and plotting. These tasks often call for the development of customized computational scripts and require an expertise that is not broadly available to the community of experimental biologists. Yet, the increasing accessibility of high- and super-resolution imaging methods fuels the demand for user-friendly image analysis workflows. Here, we provide a compendium of strategies developed by participants of a training school from the COST action INDEPTH to analyze the spatial distribution of nuclear and chromosomal signals from 3D image stacks, acquired by diffraction-limited confocal microscopy and super-resolution microscopy methods (SIM and STED). While the examples make use of one specific commercial software package, the workflows can easily be adapted to concurrent commercial and open-source software. The aim is to encourage biologists lacking custom-script-based expertise to venture into quantitative image analysis and to better exploit the discovery potential of their images.Abbreviations: 3D FISH: three-dimensional fluorescence in situ hybridization; 3D: three-dimensional; ASY1: ASYNAPTIC 1; CC: chromocenters; CO: Crossover; DAPI: 4',6-diamidino-2-phenylindole; DMC1: DNA MEIOTIC RECOMBINASE 1; DSB: Double-Strand Break; FISH: fluorescence in situ hybridization; GFP: GREEN FLUORESCENT PROTEIN; HEI10: HUMAN ENHANCER OF INVASION 10; NCO: Non-Crossover; NE: Nuclear Envelope; Oligo-FISH: oligonucleotide fluorescence in situ hybridization; RNPII: RNA Polymerase II; SC: Synaptonemal Complex; SIM: structured illumination microscopy; ZMM (ZIP: MSH4: MSH5 and MER3 proteins); ZYP1: ZIPPER-LIKE PROTEIN 1.