Tumor-associated macrophages (TAM) are an important component of the tumor stroma and exert several tumor-promoting activities. Strongly pro-angiogenic TAMs that reside in hypoxic tumor areas highly express macrophage mannose receptor (MMR, CD206)

We highlight the main features of lymphoid neogenesis specifically in the lungs of patients with IPAH, providing new evidence of immunological mechanisms in this severe condition.

Dendritic cells (DCs) regulate both immunity and tolerance. Here we have shown that the ubiquitin editing enzyme A20 (Tnfaip3) determines the activation threshold of DCs, via control of canonical NF-κB activation. Tnfaip3(fl/fl)Cd11c-cre(+) mice lacking A20 in DCs demonstrated spontaneous proliferation of conventional and double-negative T cells, their conversion to interferon-γ (IFN-γ)-producing effector cells, and expansion of plasma cells. They developed ds-DNA antibodies, nephritis, the antiphospholipid syndrome, and lymphosplenomegaly-features of systemic lupus erythematosus-and extramedullary hematopoiesis. A20-deficient DCs were resistant to apoptosis, caused by increased sensitivity to CD40L and RANKL prosurvival signals and upregulation of antiapoptotic proteins Bcl-2 and Bcl-x. They captured injected apoptotic cells more efficiently, resisted the inhibitory effects of apoptotic cells, and induced self-reactive effector lymphocytes. Because genetic polymorphisms in TNFAIP3 are associated with human autoimmune disorders, these findings identify A20-mediated control of DC activation as a crucial checkpoint in the development of systemic autoimmunity.

In this work, uniform manifold approximation and projection (UMAP) is applied for nonlinear dimensionality reduction and visualization of mass spectrometry imaging (MSI) data. We evaluate the performance of the UMAP algorithm on MSI data sets acquired in mouse pancreas and human lymphoma samples and compare it to those of principal component analysis (PCA), t-distributed stochastic neighbor embedding (t-SNE), and the Barnes−Hut (BH) approximation of t-SNE. Furthermore, we compare different distance metrics in (BH) t-SNE and UMAP and propose the use of spatial autocorrelation as a means of comparing the resulting low-dimensional embeddings. The results indicate that UMAP is competitive with t-SNE in terms of visualization and is well-suited for the dimensionality reduction of large (>100 000 pixels) MSI data sets. With an almost fourfold decrease in runtime, it is more scalable in comparison with the current state-of-the-art: t-SNE or the Barnes−Hut approximation of t-SNE. In what seems to be the first application of UMAP to MSI data, we assess the value of applying alternative distance metrics, such as the correlation, cosine, and the Chebyshev metric, in contrast to the traditionally used Euclidean distance metric. Furthermore, we propose "histomatch" as an additional custom distance metric for the analysis of MSI data.