Cell fate decisions involved in vascular and hematopoietic embryonic development are still poorly understood. An ETS transcription factor Etv2 functions as an evolutionarily conserved master regulator of vasculogenesis. Here we report a single-cell transcriptomic analysis of hematovascular development in wild-type and etv2 mutant zebrafish embryos. Distinct transcriptional signatures of different types of hematopoietic and vascular progenitors are identified using an etv2 ci32Gt gene trap line, in which the Gal4 transcriptional activator is integrated into the etv2 gene locus. We observe a cell population with a skeletal muscle signature in etv2-deficient embryos. We demonstrate that multiple etv2 ci32Gt ; UAS:GFP cells differentiate as skeletal muscle cells instead of contributing to vasculature in etv2-deficient embryos. Wnt and FGF signaling promote the differentiation of these putative multipotent etv2 progenitor cells into skeletal muscle cells. We conclude that etv2 actively represses muscle differentiation in vascular progenitors, thus restricting these cells to a vascular endothelial fate.

Vasculogenesis involves the differentiation of vascular endothelial progenitors de novo from undifferentiated mesoderm, their migration and coalescence to form the major embryonic vessels and the acquisition of arterial or venous identity. Vascular Endothelial Growth Factor (Vegf) signaling plays multiple roles during vascular development. However, its function during embryonic vasculogenesis has been controversial. Previous studies have implicated Vegf signaling in either regulating arteriovenous specification or overall vascular endothelial differentiation. To clarify the role of Vegf in embryonic vasculogenesis and identify its downstream targets, we used chemical inhibitors of Vegf receptor (Vegfr) signaling in zebrafish embryos as well as zebrafish genetic mutants. A high level of chemical inhibition of Vegfr signaling resulted in the reduction of overall vascular endothelial marker gene expression, including downregulation of both arterial and venous markers, ultimately leading to the apoptosis of vascular endothelial cells. In contrast, a low level of Vegfr inhibition specifically blocked arterial specification while the expression of venous markers appeared largely unaflected or increased. Inhibition of Vegfr signaling prior to the initiation of vasculogenesis reduced overall vascular endothelial differentiation, while inhibition of Vegfr signaling starting at mid-somitogenesis stages largely inhibited arterial specification. Conversely, Vegf overexpression resulted in the expansion of both arterial and pan-endothelial markers, while the expression of several venous-specific markers was downregulated. We further show that Vegf signaling affects overall endothelial differentiation by modulating the expression of the ETS transcription factor etv2/etsrp. etv2 expression was downregulated in Vegfr-inhibited embryos, and expanded in Vegfaa-overexpressing embryos. Furthermore, vascular-specific overexpression of etv2 in Vegfr-inhibited embryos rescued defects in vascular endothelial differentiation. Similarly, vegfaa genetic mutants displayed a combination of the two phenotypes observed with chemical Vegfr inhibition: the expression of arterial and pan-endothelial markers including etv2 was downregulated while the expression of most venous markers was either expanded or unchanged. Based on these results we propose a revised model which explains the different phenotypes observed upon inhibition of Vegf signaling: low levels of Vegf signaling promote overall vascular endothelial differentiation and cell survival by upregulating etv2 expression, while high levels of Vegf signaling promote arterial and inhibit venous specification.

Background Acute respiratory distress syndrome (ARDS) is a condition that is often considered to have broad and subjective diagnostic criteria and is associated with significant mortality and morbidity. Early and accurate prediction of ARDS and related conditions such as hypoxemia and sepsis could allow timely administration of therapies, leading to improved patient outcomes. Objective The aim of this study is to perform an exploration of how multilabel classification in the clinical setting can take advantage of the underlying dependencies between ARDS and related conditions to improve early prediction of ARDS in patients. Methods The electronic health record data set included 40,703 patient encounters from 7 hospitals from April 20, 2018, to March 17, 2021. A recurrent neural network (RNN) was trained using data from 5 hospitals, and external validation was conducted on data from 2 hospitals. In addition to ARDS, 12 target labels for related conditions such as sepsis, hypoxemia, and COVID-19 were used to train the model to classify a total of 13 outputs. As a comparator, XGBoost models were developed for each of the 13 target labels. Model performance was assessed using the area under the receiver operating characteristic curve. Heat maps to visualize attention scores were generated to provide interpretability to the neural networks. Finally, cluster analysis was performed to identify potential phenotypic subgroups of patients with ARDS. Results The single RNN model trained to classify 13 outputs outperformed the individual XGBoost models for ARDS prediction, achieving an area under the receiver operating characteristic curve of 0.842 on the external test sets. Models trained on an increasing number of tasks resulted in improved performance. Earlier prediction of ARDS nearly doubled the rate of in-hospital survival. Cluster analysis revealed distinct ARDS subgroups, some of which had similar mortality rates but different clinical presentations. Conclusions The RNN model presented in this paper can be used as an early warning system to stratify patients who are at risk of developing one of the multiple risk outcomes, hence providing practitioners with the means to take early action.

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