Assessment of Hepatocyte Ploidy by Flow Cytometry

Deep-Learning-Based Hepatic Ploidy Quantification Using H&E Histopathology Images

Polyploidy, the duplication of the entire genome within a single cell, is a significant characteristic of cells in many tissues, including the liver. The quantification of hepatic ploidy typically relies on flow cytometry and immunofluorescence (IF) imaging, which are not widely available in clinical settings due to high financial and time costs. To improve accessibility for clinical samples, we developed a computational algorithm to quantify hepatic ploidy using hematoxylin-eosin (H&E) histopathology images, which are commonly obtained during routine clinical practice. Our algorithm uses a deep learning model to first segment and classify different types of cell nuclei in H&E images. It then determines cellular ploidy based on the relative distance between identified hepatocyte nuclei and determines nuclear ploidy using a fitted Gaussian mixture model. The algorithm can establish the total number of hepatocytes and their detailed ploidy information in a region of interest (ROI) on H&E images. This is the first successful attempt to automate ploidy analysis on H&E images. Our algorithm is expected to serve as an important tool for studying the role of polyploidy in human liver disease.

Agarose/crystalline nanocellulose (CNC) composites promote bone marrow-derived mast cell integrity, degranulation and receptor expression but inhibit production of de novo synthesized mediators

Introduction: Mast cells are highly granulated tissue-resident leukocytes that require a three-dimensional matrix to differentiate and mediate immune responses. However, almost all cultured mast cells rely on two-dimensional suspension or adherent cell culture systems, which do not adequately reflect the complex structure that these cells require for optimal function. Methods: Crystalline nanocellulose (CNC), consisting of rod-like crystals 4-15 nm in diameter and 0.2-1 µm in length, were dispersed in an agarose matrix (12.5% w/v), and bone marrow derived mouse mast cells (BMMC) were cultured on the agarose/CNC composite. BMMC were activated with the calcium ionophore A23187 or immunoglobulin E (IgE) and antigen (Ag) to crosslink high affinity IgE receptors (FcεRI). Results: BMMC cultured on a CNC/agarose matrix remained viable and metabolically active as measured by reduction of sodium 3'-[1-[(phenylamino)-carbony]-3,4-tetrazolium]-bis(4-methoxy-6-nitro) benzene-sulfonic acid hydrate (XTT), and the cells maintained their membrane integrity as analyzed by measuring the release of lactate dehydrogenase (LDH) and propidium iodide exclusion by flow cytometry. Culture on CNC/agarose matrix had no effect on BMMC degranulation in response to IgE/Ag or A23187. However, culture of BMMC on a CNC/agarose matrix inhibited A23187-and IgE/Ag-activated production of tumor necrosis factor (TNF) and other mediators such as IL-1β, IL-4, IL-6, IL-13, MCP-1/CCL2, MMP-9 and RANTES by as much as 95%. RNAseq analysis indicated that BMMC expressed a unique and balanced transcriptome when cultured on CNC/agarose. Discussion: These data demonstrate that culture of BMMCs on a CNC/agarose matrix promotes cell integrity, maintains expression of surface biomarkers such as FcεRI and KIT and preserves the ability of BMMC to release pre-stored mediators in response to IgE/Ag and A23187. However, culture of BMMC on CNC/agarose matrix inhibits BMMC production of de novo synthesized mediators, suggesting that CNC may be altering specific phenotypic characteristics of these cells that are associated with late phase inflammatory responses.