A promising deep learning-assistive algorithm for histopathological screening of colorectal cancer.

Colorectal cancer is one of the most common cancers worldwide, accounting for an annual estimated 1.8 million incident cases. With the increasing number of colonoscopies being performed, colorectal biopsies make up a large proportion of any histopathology laboratory workload.

Image Analysis Using Machine Learning for Automated Detection of Hemoglobin H Inclusions in Blood Smears - A Method for Morphologic Detection of Rare Cells.

Background: Morphologic rare cell detection is a laborious, operator-dependent process which has the potential to be improved by the use of image analysis using artificial intelligence. Detection of rare hemoglobin H (HbH) inclusions in red cells in the peripheral blood is a common screening method for alpha-thalassemia. This study aims to develop a convolutional neural network-based algorithm for the detection of HbH inclusions.

Author Correction: Single-cell analysis of EphA clustering phenotypes to probe cancer cell heterogeneity.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Author Correction: Single-cell analysis of EphA clustering phenotypes to probe cancer cell heterogeneity.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Single-cell analysis of EphA clustering phenotypes to probe cancer cell heterogeneity.

The Eph family of receptor tyrosine kinases is crucial for assembly and maintenance of healthy tissues. Dysfunction in Eph signaling is causally associated with cancer progression. In breast cancer cells, dysregulated Eph signaling has been linked to alterations in receptor clustering abilities.

Matrix mechanics controls FHL2 movement to the nucleus to activate p21 expression.

Substrate rigidity affects many physiological processes through mechanochemical signals from focal adhesion (FA) complexes that subsequently modulate gene expression. We find that shuttling of the LIM domain (domain discovered in the proteins, Lin11, Isl-1, and Mec-3) protein four-and-a-half LIM domains 2 (FHL2) between FAs and the nucleus depends on matrix mechanics. In particular, on soft surfaces or after the loss of force, FHL2 moves from FAs into the nucleus and concentrates at RNA polymerase (Pol) II sites, where it acts as a transcriptional cofactor, causing an increase in p21 gene expression that will inhibit growth on soft surfaces.

Nuclear transport of paxillin depends on focal adhesion dynamics and FAT domains.

The nuclear transport of paxillin appears to be crucial for paxillin function but the mechanism of transport remains unclear. Here, we show that the nuclear transport of paxillin is regulated by focal adhesion turnover and the presence of FAT domains. Focal adhesion turnover was controlled using triangular or circular fibronectin islands.