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Traditional diagnostic neuropathology relies on subjective interpretation of visual data obtained from a brightfield microscopy. This approach causes high variability, unsatisfactory reproducibility, and inability for multiplexing even among experts. These problems may affect patient outcomes and confound clinical decision-making. Also, standard histological processing of pathological specimens leads to auto-fluorescence and other artifacts, a reason why fluorescent microscopy is not routinely implemented in diagnostic pathology. To overcome these problems, objective and quantitative methods are required to help neuropathologists in their clinical decision-making. Therefore, we propose a computerized image analysis method to validate anti-PTBP1 antibody for its potential use in diagnostic neuropathology. Images were obtained from standard neuropathological specimens stained with anti-PTBP1 antibody. First, the noise characteristics of the images were modeled and images are de-noised according to the noise model. Next, images are filtered with sigma-adaptive Gaussian filtering for normalization, and cell nuclei are detected and segmented with a k-means-based deterministic approach. Experiments on 29 data sets from 3 cases of brain tumor and reactive gliosis show statistically significant differences between the number of positively stained nuclei in images stained with and without anti-PTBP1 antibody. The experimental analysis of specimens from 3 different brain tumor groups and 1 reactive gliosis group indicates the feasibility of using anti-PTBP1 antibody in diagnostic neuropathology, and computerized image analysis provides a systematic and quantitative approach to explore feasibility. [ABSTRACT FROM AUTHOR]

Glioblastoma is a devastating disease, and there is an urgent need to develop novel therapies, such as oncolytic HSV1 (OV) to effectively target tumor cells. OV therapy depends on tumor-specific replication leading to destruction of neoplastic tissues. Host responses that curtail virus replication limit its efficacy in vivo. We have previously shown that cysteine-rich 61 protein (CCN1) activates a type 1 IFN antiviral defense response in glioblastoma cells. Incorporating TCGA data, we found CCN1 expression to be a negative prognostic factor for glioblastoma patients. Based on this, we used neutralizing antibodies against CCN1 to investigate its effect on OV therapy. Use of an anti-CCN1 antibody in mice bearing glioblastomas treated with OV led to enhanced virus expression along with reduced immune cell infiltration. OV-induced CCN1 increases macrophage migration toward infected glioblastoma cells by directly binding macrophages and also by enhancing the proinflammatory activation of macrophages inducing MCP-1 expression in glioblastoma cells. Activation of macrophages by CCN1 also increases viral clearance. Neutralization of integrin αMβ2 reversed CCN1-induced macrophage activation and migration, and reduced MCP-1 expression by glioblastoma cells. Our findings reveal that CCN1 plays a novel role in pathogen clearance; increasing macrophage infiltration and activation resulting in increased virus clearance in tumors. [ABSTRACT FROM AUTHOR]