Resident macrophages restrain pathological adipose tissue remodeling and protect vascular integrity in obese mice.

Tissue-resident macrophages in white adipose tissue (WAT) dynamically adapt to the metabolic changes of their microenvironment that are often induced by excess energy intake. Currently, the exact contribution of these macrophages in obesity-driven WAT remodeling remains controversial. Here, using a transgenic CD169-DTR mouse strain, we provide new insights into the interplay between CD169+ adipose tissue macrophages (ATMs) and their surrounding WAT microenvironment. Using targeted in vivo ATM ablation followed by transcriptional and metabolic WAT profiling, we found that ATMs protect WAT from the excessive pathological remodeling that occurs during obesity. As obesity progresses, ATMs control not only vascular integrity, adipocyte function, and lipid and metabolic derangements but also extracellular matrix accumulation and resultant fibrosis in the WAT. The protective role of ATMs during obesity-driven WAT dysfunction supports the notion that ATMs represent friends, rather than foes, as has previously assumed.

Automated image analysis method to detect and quantify fat cell infiltration in hematoxylin and eosin stained human pancreas histology images.

Fatty infiltration in pancreas leading to steatosis is a major risk factor in pancreas transplantation. Hematoxylin and eosin (H and E) is one of the common histological staining techniques that provides information on the tissue cytoarchitecture. Adipose (fat) cells accumulation in pancreas has been shown to impact beta cell survival, its endocrine function and pancreatic steatosis and can cause non-alcoholic fatty pancreas disease (NAFPD). The current automated tools (E.g. Adiposoft) available for fat analysis are suited for white fat tissue which is homogeneous and easier to segment unlike heterogeneous tissues such as pancreas where fat cells continue to play critical physiopathological functions. The currently, available pancreas segmentation tool focuses on endocrine islet segmentation based on cell nuclei detection for diagnosis of pancreatic cancer. In the current study, we present a fat quantifying tool, Fatquant, which identifies fat cells in heterogeneous H and E tissue sections with reference to diameter of fat cell. Using histological images from a public database, we observed an intersection over union of 0.797 to 0.962 and 0.675 to 0.937 for manual versus Fatquant analysis of pancreas and liver, respectively.