Introduction: The 2019 coronavirus, known as SARS-CoV-2 and COVID-19, was named a pandemic by the WHO in March 2020. It binds to the ACE-2 receptor and transmembrane serine protease 2 and is highly virulent. There are many sequelae of this virus, including neurological consequences. We have performed a literature review of the neurological sequelae of COVID-19 with relation to neuroimaging and then present a case series. Case Series: Seven cases were seen by neurology consultants at the Hospital for Special Surgery in New York City between February and May of 2020; 5 met criteria. The majority of these consultations were called for encephalopathy. Some had neuroimaging of brain MRI or head CT, which all showed microvascular disease. One case had prior imaging without microvascular disease. Summary/Conclusion: It is known that vascular disease is a risk factor for severe COVID-19 infection. This case series demonstrates presence of microvascular disease in patients with encephalopathy. We know that microvascular disease can be a risk factor for toxic metabolic encephalopathy. It is unclear if the microvascular disease was present prior to infection, although at least one patient had prior imaging without microvascular disease. More research is needed to determine if COVID-19 infection can cause vascular disease.

Mass cytometry enables high-dimensional, single-cell analysis of cell type and state. In mass cytometry, rare earth metals are used as reporters on antibodies. Analysis of metal abundances using the mass cytometer allows determination of marker expression in individual cells. Mass cytometry has previously been applied only to cell suspensions. To gain spatial information, we have coupled immunohistochemical and immunocytochemical methods with high-resolution laser ablation to CyTOF mass cytometry. This approach enables the simultaneous imaging of 32 proteins and protein modifications at subcellular resolution; with the availability of additional isotopes, measurement of over 100 markers will be possible. We applied imaging mass cytometry to human breast cancer samples, allowing delineation of cell subpopulations and cell-cell interactions and highlighting tumor heterogeneity. Imaging mass cytometry complements existing imaging approaches. It will enable basic studies of tissue heterogeneity and function and support the transition of medicine toward individualized molecularly targeted diagnosis and therapies.

Single-cell analyses have revealed extensive intra-and inter-patient cancer heterogeneity 1 , but complex single-cell phenotypes and their spatial context are not yet reflected in the histologic stratification that is the foundation of many clinical decisions. Here, we used imaging mass cytometry 2 to simultaneously quantify 35 biomarkers resulting in 720 highdimension immunohistochemistry pathology images of tumor tissue from 352 breast cancer patients for whom long-term survival data were available. Spatial, single-cell analysis identified tumor and stromal single-cell phenotypes, their organization and heterogeneity, and enabled categorization of breast cancer cellular architecture based on cellular composition and tissue organization. Our analysis revealed multi-cellular features of the tumor microenvironment and novel breast cancer subgroups associated with distinct clinical outcomes. Thus, spatially resolved, single-cell analysis can characterize intra-tumor phenotypic heterogeneity in a disease-relevant manner with the potential to inform patient-specific diagnosis. MainHistologic and phenotypic differences between tumors guide cancer diagnosis, prognosis, and selection of treatment. Currently, breast cancer patients are graded based on tumor structure and cellular morphology, and subcategorized when more than 1% of tumor cells contain hormone receptors or more than 10% express high levels of HER2 or have amplified HER2 [3][4][5] . This leaves a large portion of cells uncharacterized even though additional molecular subclasses and morphologic features have been identified as prognostic [6][7][8][9] . It is clear that clonal evolution and spatially distinct tumor microenvironments drive inter-and intra-patient cellular

Single-cell, spatially resolved ‘omics analysis of tissues is poised to transform biomedical research and clinical practice. We have developed an open-source, computational multiplex image cytometry analysis toolbox (miCAT) to enable interactive, quantitative, and comprehensive exploration of individual cell phenotypes, cell-to-cell interactions, microenvironments, and morphological structures within intact tissues. We highlight the unique abilities of miCAT by analysis of highly multiplexed mass cytometry images of human breast cancer tissues.

Secretion of C-C chemokine ligand 2 (CCL2) by mammary tumours recruits CCR2-expressing inflammatory monocytes to primary tumours and metastatic sites, and CCL2 neutralization in mice inhibits metastasis by retaining monocytes in the bone marrow. Here we report a paradoxical effect of CCL2 in four syngeneic mouse models of metastatic breast cancer. Surprisingly, interruption of CCL2 inhibition leads to an overshoot of metastases and accelerates death. This is the result of monocyte release from the bone marrow and enhancement of cancer cell mobilization from the primary tumour, as well as blood vessel formation and increased proliferation of metastatic cells in the lungs in an interleukin (IL)-6- and vascular endothelial growth factor (VEGF)-A-dependent manner. Notably, inhibition of CCL2 and IL-6 markedly reduced metastases and increased survival of the animals. CCL2 has been implicated in various neoplasias and adopted as a therapeutic target. However, our results call for caution when considering anti-CCL2 agents as monotherapy in metastatic disease and highlight the tumour microenvironment as a critical determinant of successful anti-metastatic therapy.