INSIGHT: A population-scale COVID-19 testing strategy combining point-of-care diagnosis with centralized high-throughput sequencing.

We present INSIGHT [isothermal NASBA (nucleic acid sequence-based amplification) sequencing-based high-throughput test], a two-stage coronavirus disease 2019 testing strategy, using a barcoded isothermal NASBA reaction. It combines point-of-care diagnosis with next-generation sequencing, aiming to achieve population-scale testing. Stage 1 allows a quick decentralized readout for early isolation of presymptomatic or asymptomatic patients. It gives results within 1 to 2 hours, using either fluorescence detection or a lateral flow readout, while simultaneously incorporating sample-specific barcodes. The same reaction products from potentially hundreds of thousands of samples can then be pooled and used in a highly multiplexed sequencing-based assay in stage 2. This second stage confirms the near-patient testing results and facilitates centralized data collection. The 95% limit of detection is <50 copies of viral RNA per reaction. INSIGHT is suitable for further development into a rapid home-based, point-of-care assay and is potentially scalable to the population level

INSIGHT: A population-scale COVID-19 testing strategy combining point-of-care diagnosis with centralized high-throughput sequencing.

We present INSIGHT [isothermal NASBA (nucleic acid sequence-based amplification) sequencing-based high-throughput test], a two-stage coronavirus disease 2019 testing strategy, using a barcoded isothermal NASBA reaction. It combines point-of-care diagnosis with next-generation sequencing, aiming to achieve population-scale testing. Stage 1 allows a quick decentralized readout for early isolation of presymptomatic or asymptomatic patients. It gives results within 1 to 2 hours, using either fluorescence detection or a lateral flow readout, while simultaneously incorporating sample-specific barcodes. The same reaction products from potentially hundreds of thousands of samples can then be pooled and used in a highly multiplexed sequencing-based assay in stage 2. This second stage confirms the near-patient testing results and facilitates centralized data collection. The 95% limit of detection is <50 copies of viral RNA per reaction. INSIGHT is suitable for further development into a rapid home-based, point-of-care assay and is potentially scalable to the population level

Comparative evaluation of instrument segmentation and tracking methods in minimally invasive surgery

Intraoperative segmentation and tracking of minimally invasive instruments is a prerequisite for computer- and robotic-assisted surgery. Since additional hardware like tracking systems or the robot encoders are cumbersome and lack accuracy, surgical vision is evolving as promising techniques to segment and track the instruments using only the endoscopic images. However, what is missing so far are common image data sets for consistent evaluation and benchmarking of algorithms against each other. The paper presents a comparative validation study of different vision-based methods for instrument segmentation and tracking in the context of robotic as well as conventional laparoscopic surgery. The contribution of the paper is twofold: we introduce a comprehensive validation data set that was provided to the study participants and present the results of the comparative validation study. Based on the results of the validation study, we arrive at the conclusion that modern deep learning approaches outperform other methods in instrument segmentation tasks, but the results are still not perfect. Furthermore, we show that merging results from different methods actually significantly increases accuracy in comparison to the best stand-alone method. On the other hand, the results of the instrument tracking task show that this is still an open challenge, especially during challenging scenarios in conventional laparoscopic surgery

Long non-coding RNA PCAT19 safeguards DNA in quiescent endothelial cells by preventing uncontrolled phosphorylation of replication protein A2

In healthy vessels, endothelial cells maintain a stable, differentiated, and growth-arrested phenotype for years. Upon injury, a rapid phenotypic switch facilitates proliferation to restore tissue perfusion. Here we report the identification of the endothelial cell-enriched long non-coding RNA (lncRNA) PCAT19, which contributes to the proliferative switch and acts as a safeguard for the endothelial genome. PCAT19 is enriched in confluent, quiescent endothelial cells and binds to the full replication protein A (RPA) complex in a DNA damage- and cell-cycle-related manner. Our results suggest that PCAT19 limits the phosphorylation of RPA2, primarily on the serine 33 (S33) residue, and thereby facilitates an appropriate DNA damage response while slowing cell cycle progression. Reduction in PCAT19 levels in response to either loss of cell contacts or knockdown promotes endothelial proliferation and angiogenesis. Collectively, PCAT19 acts as a dynamic guardian of the endothelial genome and facilitates rapid switching from quiescence to proliferation

A cell atlas of human thymic development defines T cell repertoire formation.

The thymus provides a nurturing environment for the differentiation and selection of T cells, a process orchestrated by their interaction with multiple thymic cell types. We used single-cell RNA sequencing to create a cell census of the human thymus across the life span and to reconstruct T cell differentiation trajectories and T cell receptor (TCR) recombination kinetics. Using this approach, we identified and located in situ CD8αα+ T cell populations, thymic fibroblast subtypes, and activated dendritic cell states. In addition, we reveal a bias in TCR recombination and selection, which is attributed to genomic position and the kinetics of lineage commitment. Taken together, our data provide a comprehensive atlas of the human thymus across the life span with new insights into human T cell development

NCoR1 limits angiogenic capacity by altering Notch signaling

Highlights • NCoR1 is the most highly expressed endothelial corepressor. • Loss of NCoR1 promotes angiogenic function in endothelial cells. • Loss of NCoR1 promotes a tip cell position during angiogenic sprouting. Abstract Corepressors negatively regulate gene expression by chromatin compaction. Targeted regulation of gene expression could provide a means to control endothelial cell phenotype. We hypothesize that by targeting corepressor proteins, endothelial angiogenic function can be improved. To study this, the expression and function of nuclear corepressors in human umbilical vein endothelial cells (HUVEC) and in murine organ culture was studied. RNA-seq revealed that nuclear receptor corepressor 1 (NCoR1), silencing mediator of retinoid and thyroid hormone receptors (SMRT) and repressor element-1 silencing transcription factor (REST) are the highest expressed corepressors in HUVECs. Knockout and knockdown strategies demonstrated that the depletion of NCoR1 increased the angiogenic capacity of endothelial cells, whereas depletion of SMRT or REST did not. Interestingly, the effect was VEGF signaling independent. NCoR1 depletion significantly upregulated angiogenesis-associated genes, especially tip cell genes, including ESM1, DLL4 and NOTCH4, as observed by RNA- and ATAC-seq. Confrontation assays comparing cells with and without NCoR1-deficiency revealed that loss of NCoR1 promotes a tip-cell position during spheroid sprouting. Moreover, a proximity ligation assay identified NCoR1 as a direct binding partner of the Notch-signaling-related transcription factor RBPJk. Luciferase assays showed that siRNA-mediated knockdown of NCOR1 promotes RBPJk activity. Furthermore, NCoR1 depletion prompts upregulation of several elements in the Notch signaling cascade. Downregulation of NOTCH4, but not NOTCH1, prevented the positive effect of NCOR1 knockdown on spheroid outgrowth. Collectively, these data indicate that decreasing NCOR1 expression is an attractive approach to promote angiogenic function

Predicting the Strongest Domain-Domain Contact in Interacting Protein Pairs

Experiments to determine the complete 3-dimensional structures of protein complexes are difficult to perform and only a limited range of such structures are available.In contrast, large-scale screening experiments have identified thousands of pairwise interactions between proteins, but such experiments do not produce explicit structural information.In addition, the data produced by these high through-put experiments contain large numbers of false positive results, and can be biased against detection of certain types of interaction.Several methods exist that analyse such pairwise interaction data in terms of the constituent domains within proteins, scoring pairs of domain superfamilies according to their propensity to interact.These scores can be used to predict the strongest domain-domain contact (the contact with the largest surface area) between interacting proteins for which the domain-level structures of the individual proteins are known.We test this predictive approach on a set of pairwise protein interactions taken from the Protein Quaternary Structure (PQS) database for which the true domain-domain contacts are known.While the overall prediction success rate across the whole test data set is poor, we shown how interactions in the test data set for which the training data are not informative can be automatically excluded from the prediction process, giving improved prediction success rates at the expense of restricted coverage of the test data.