Dasatinib and Doxorubicin Treatment of Sarcoma Initiating Cells: A Possible New Treatment Strategy

Background. One of the major challenges affecting sarcoma treatment outcome, particularly that of metastatic disease, is resistance to chemotherapy. Cancer-initiating cells are considered a major contributor to this resistance. Methods. An immortalised nontransformed human stromal (mesenchymal) stem cell line hMSC-TERT4 and a transformed cell line hMSC-TERT20-CE8, known to form sarcoma-like tumours when implanted in immune-deficient mice, were used as models. Receptor tyrosine kinase (RTK) activation was analysed by RTK arrays and cellular viability after tyrosine kinases inhibitor (TKI) treatment with or without doxorubicin was assessed by MTS assay. Results. Initial results showed that the hMSC-TERT4 was more doxorubicin-sensitive while hMSC-TERT20-CE8 was less doxorubicin-sensitive evidenced by monitoring cell viability in the presence of doxorubicin at different doses. The epidermal growth factor receptor (EGFR) was activated in both cell lines. However hMSC-TERT20-CE8 exhibited significantly higher expression of the EGFR ligands. EGFR inhibitors such as erlotinib and afatinib alone or in combination with doxorubicin failed to further decrease cell viability of hMSC-TERT20-CE8. However, inhibition with the TKI dasatinib in combination with doxorubicin decreased cell viability of the hMSC-TERT20-CE8 cell line. Conclusion. Our results demonstrate that dasatinib, but not EGFR-directed treatment, can decrease cell viability of stromal cancer stem cells less sensitive to doxorubicin

Generating stable molecules using imitation and reinforcement learning

Chemical space is routinely explored by machine learning methods to discover interesting molecules, before time-consuming experimental synthesizing is attempted. However, these methods often rely on a graph representation, ignoring 3D information necessary for determining the stability of the molecules. We propose a reinforcement learning (RL) approach for generating molecules in Cartesian coordinates allowing for quantum chemical prediction of the stability. To improve sample-efficiency we learn basic chemical rules from imitation learning (IL) on the GDB-11 database to create an initial model applicable for all stoichiometries. We then deploy multiple copies of the model conditioned on a specific stoichiometry in a RL setting. The models correctly identify low energy molecules in the database and produce novel isomers not found in the training set. Finally, we apply the model to larger molecules to show how RL further refines the IL model in domains far from the training data

Upregulation of Mrps18a in breast cancer identified by selecting phage antibody libraries on breast tissue sections

Abstract Background One of the hallmarks of cancer is an altered energy metabolism, and here, mitochondria play a central role. Previous studies have indicated that some mitochondrial ribosomal proteins change their expression patterns upon transformation. Method In this study, we have used the selection of recombinant antibody libraries displayed on the surface of filamentous bacteriophage as a proteomics discovery tool for the identification of breast cancer biomarkers. A small subpopulation of breast cells expressing both cytokeratin 19 and cytokeratin 14 was targeted using a novel selection procedure. Results We identified the mitochondrial ribosomal protein s18a (Mrps18a) as a protein which is upregulated in breast cancer. However, Mrps18a was not homogeneously upregulated in all cancer cells, suggesting the existence of sub-populations within the tumor. The upregulation was not confined to cytokeratin 19 and cytokeratin 14 double positive cells. Conclusion This study illustrates how phage display can be applied towards the discovery of proteins which exhibit changes in their expression patterns. We identified the mitochondrial protein Mrps18a as being upregulated in human breast cancer cells compared to normal breast cells

Det middelalderlige fyrstemåltid fra Marsk Stig til Valdemar Atterdag cirka 1300-1350

Denne artikel fremlægger en tværfaglig oversigt over fyrstemåltidet i første halvdel af 1300-tallet, det vil sige på Erik Menveds og Valdemar Atterdags tid. Det er i højmiddelalderen, at fyrstemåltidet som arena for forhandlinger om magt og hierarki for første gang kan dokumenteres: Den fyrstelige eneret på vildt og ferskvandsfisk, det offentlige måltid og den hierarkiske placering af deltagerne ved bordet er eksempler på dette: alle træk, der kendetegner det eftermiddelalderlige fyrstemåltid. Det er således i højmiddelalderen, at traditionen for det fyrstelige måltid som repræsentativt rum bliver etableret, og det er en tradition, der varer ved helt til vore dage