Light microscopy combined with well-established protocols of two-dimensional cell culture facilitates high-throughput quantitative imaging to study biological phenomena. Accurate segmentation of individual cells in images enables exploration of complex biological questions, but can require sophisticated imaging processing pipelines in cases of low contrast and high object density. Deep learning-based methods are considered state-of-the-art for image segmentation but typically require vast amounts of annotated data, for which there is no suitable resource available in the field of label-free cellular imaging. Here, we present LIVECell, a large, high-quality, manually annotated and expert-validated dataset of phase-contrast images, consisting of over 1.6 million cells from a diverse set of cell morphologies and culture densities. To further demonstrate its use, we train convolutional neural network-based models using LIVECell and evaluate model segmentation accuracy with a proposed a suite of benchmarks.

We searched for linkage among 24 polymorphic loci (allozymes, RAPD, microsatellites) in three half-sib backcross families of rainbow trout (Oncorhynchus mykiss) produced by crossing strains divergent for the quantitative trait of upper temperature tolerance. Seven significant and two suggestive pairwise linkage associations between molecular marker loci were observed involving 14 loci clustered into four linkage groups. The association between a pair of allozyme loci (sIDHP-3* and mMEP-2*) has been reported previously. Recombination rates varied greatly between the sexes and families. Two quantitative trait loci (QTL) were mapped by detecting a significant association between variance in upper temperature tolerance and alleles at the microsatellite loci Omy325UoG and Ssa14DU. The two QTL appear to reside in different linkage groups and account for :13 per cent and 9 per cent of the overall additive genetic variance in upper temperature tolerance. No significant interaction was detected between Omy325UoG and Ssa14DU suggesting that the effects of the QTL are additive.

We searched for linkage among 24 polymorphic loci (allozymes, RAPD, microsatellites) in three half-sib backcross families of rainbow trout (Oncorhynchus mykiss) produced by crossing strains divergent for the quantitative trait of upper temperature tolerance. Seven significant and two suggestive pairwise linkage associations between molecular marker loci were observed involving 14 loci clustered into four linkage groups. The association between a pair of allozyme loci (sIDHP-3* and mMEP-2*) has been reported previously. Recombination rates varied greatly between the sexes and families. Two quantitative trait loci (QTL) were mapped by detecting a significant association between variance in upper temperature tolerance and alleles at the microsatellite loci Omy325UoG and Ssa14DU. The two QTL appear to reside in different linkage groups and account for :13 per cent and 9 per cent of the overall additive genetic variance in upper temperature tolerance. No significant interaction was detected between Omy325UoG and Ssa14DU suggesting that the effects of the QTL are additive.

No abstract

The mesenchymal-to-epithelial transition (MET) is an intrinsically mechanical process describing a multi-step progression where autonomous mesenchymal cells gradually become tightly linked, polarized epithelial cells. METs are fundamental to a wide range of biological processes, including the evolution of multicellular organisms, generation of primary and secondary epithelia during development and organogenesis, and the progression of diseases including cancer. In these cases, there is an interplay between the establishment of cell polarity and the mechanics of neighboring cells and microenvironment. In this review, we highlight a spectrum of METs found in normal development as well as in pathological lesions, and provide insight into the critical role mechanics play at each step. We define MET as an independent process, distinct from a reverse-EMT, and propose questions to further explore the cellular and physical mechanisms of MET.