How can we quantify, explain, and apply the uncertainty of complex soil maps predicted with neural networks?

Artificial neural networks (ANNs) have proven to be a useful tool for complex questions that involve large amounts of data. Our use case of predicting soil maps with ANNs is in high demand by government agencies, construction companies, or farmers, given cost and time intensive field work. However, there are two main challenges when applying ANNs.

NMDA Receptor-Mediated Signaling Pathways Enhance Radiation Resistance, Survival and Migration in Glioblastoma Cells-A Potential Target for Adjuvant Radiotherapy.

Glioblastoma is one of the most aggressive malignant brain tumors, with a survival time less than 15 months and characterized by a high radioresistance and the property of infiltrating the brain. Recent data indicate that the malignancy of glioblastomas depends on glutamatergic signaling via ionotropic glutamate receptors. In this study we revealed functional expression of Ca-permeable NMDARs in three glioblastoma cell lines.

NMDA Receptor Signaling Mediates cFos Expression via Top2β-Induced DSBs in Glioblastoma Cells.

The activation of Ca-permeable -methyl-D-aspartic acid (NMDA) receptor channels (NMDARs) is crucial for the development and survival of neurons, but many cancers use NMDAR-mediated signaling as well, enhancing the growth and invasiveness of tumors. Thus, NMDAR-dependent pathways emerge as a promising target in cancer therapy. Here, we use the LN229 and U-87MG glioblastoma multiforme (GBM) cells and immunofluorescence staining of 53BP1 to analyze NMDAR-induced DNA double-strand breaks (DSBs), which represent an important step in the NMDAR signaling pathway in neurons by facilitating the expression of early response genes.