Meningothelial Cells React to Elevated Pressure and Oxidative Stress

BACKGROUND: Meningothelial cells (MECs) are the cellular components of the meninges enveloping the brain. Although MECs are not fully understood, several functions of these cells have been described. The presence of desmosomes and tight junctions between MECs hints towards a barrier function protecting the brain. In addition, MECs perform endocytosis and, by the secretion of cytokines, are involved in immunological processes in the brain. However, little is known about the influence of pathological conditions on MEC function; e.g., during diseases associated with elevated intracranial pressure, hypoxia or increased oxidative stress. METHODS: We studied the effect of elevated pressure, hypoxia, and oxidative stress on immortalized human as well as primary porcine MECs. We used MTS (3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium) bioreduction assays to assess the proliferation of MECs in response to treatment and compared to untreated control cells. To assess endocytotic activity, the uptake of fluorescently labeled latex beads was analyzed by fluorescence microscopy. RESULTS: We found that exposure of MECs to elevated pressure caused significant cellular proliferation and a dramatic decrease in endocytotic activity. In addition, mild oxidative stress severely inhibited endocytosis. CONCLUSION: Elevated pressure and oxidative stress impact MEC physiology and might therefore influence the microenvironment of the subarachnoid space and thus the cerebrospinal fluid within this compartment with potential negative impact on neuronal function

A High Level Methodology for Monitoring Network-on-Chips

Grassi PR, Santambrogio M, Puttmann C, Pohl C, Porrmann M. A High Level Methodology for Monitoring Network-on-Chips. In: Diagnostic Services in Network-on-Chips (DSNOC 2009), Workshop at Design, Automation and Test in Europe. 2009

A full pipeline to analyze lung histopathology images

Histopathology images involve the analysis of tissue samples to diagnose several diseases, such as cancer. The analysis of tissue samples is a time-consuming procedure, manually made by medical experts, namely pathologists. Computational pathology aims to develop automatic methods to analyze Whole Slide Images (WSI), which are digitized histopathology images, showing accurate performance in terms of image analysis. Although the amount of available WSIs is increasing, the capacity of medical experts to manually analyze samples is not expanding proportionally. This paper presents a full automatic pipeline to classify lung cancer WSIs, considering four classes: Small Cell Lung Cancer (SCLC), non-small cell lung cancer divided into LUng ADenocarcinoma (LUAD) and LUng Squamous cell Carcinoma (LUSC), and normal tissue. The pipeline includes a self-supervised algorithm for pre-training the model and Multiple Instance Learning (MIL) for WSI classification. The model is trained with 2,226 WSIs and it obtains an AUC of 0.8558 ± 0.0051 and a weighted f1-score of 0.6537 ± 0.0237 for the 4-class classification on the test set. The capability of the model to generalize was evaluated by testing it on the public The Cancer Genome Atlas (TCGA) dataset on LUAD and LUSC classification. In this task, the model obtained an AUC of 0.9433 ± 0.0198 and a weighted f1-score of 0.7726 ± 0.0438

Improving the sensitivity of the heat-transfer method (HTM) for cancer cell detection with optimized sensor chips

© 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. In this article, we increased the sensitivity of the heat-transfer method (HTM) for the detection of breast cancer cells (ZR-75-1 cells, see figure) in phosphate buffered saline (PBS). The effect of small technological changes on the limit of detection (LoD) of the methodology was examined. To this extent, polished aluminum substrates with a mirror finish were used, replacing the unpolished chips used in previous studies. These chips were coated with a polyurethane layer and imprinted for the target cell type, creating a so-called surface imprinted-polymer (SIP). Binding of target cells to the SIP resulted in an increase of the thermal resistance at the solid-liquid interface under study. Background thermal resistance measurements were performed with polished and unpolished aluminum substrates. In addition, the effect of using silver paste as thermal coupling between the aluminum chip and the copper heat provider was analyzed. The results of these experiments reveal that optimal thermal contact is achieved when directly coupling the copper heat provider to the polished side of the aluminum substrate as evidenced by a decrease in the baseline thermal resistance. In addition, noise levels on the heat-transfer resistance (Rth) signal decreased by a factor in the optimal configuration. Dose-response curves were obtained using the optimized methodology and were compared with results obtained with the original substrates. These quantitative experiments demonstrated an improvement of the LoD by approximately thirty percent. ZR-75-1 cells applied onto a home-made rubber stamp.status: publishe