Calculation of the Biological Efficiency of the Proton Component from 14.8 MeV Neutron Irradiation in Computational Biology with Help of Video Cards

Bulletin of Experimental Biology and Medicine - Fast neutron therapy, which previously has demonstrated effective results, but along with a large number of complications, can again be considered a...     

Psychopharmacological Effects of Stimulation of the Functions of Neural Stem Cells by STAT3 Inhibitor under Conditions of Modeled Ethanol-Induced Encephalopathy

Bulletin of Experimental Biology and Medicine - The psychopharmacological effects of a stimulator of functions of progenitor cells of the nervous tissue STAT3 inhibitor (STAT3 Inhibitor XIV, LLL12)...     

A Mathematical Model of a Thermoelectric Device for the Treatment of Whitlow by Local Hypothermia

Biomedical Engineering - A mathematical model of a thermoelectric device for the treatment of whitlow by local hypothermia is discussed. The model is based on a solution of the heat conduction task...     

Rapalogs induce non-apoptotic,autophagy-dependent cell death in HPV-negative TP53 mutant head and neck squamous cell carcinoma

TP53 is the most frequently mutated gene in head and neck squamous cell carcinoma (HNSCC). Patients with HPV-negative TP53 mutant HNSCC have the worst prognosis, necessitating additional agents for treatment. Since mutant p53 causes sustained activation of the PI3K/AKT/mTOR signaling pathway, we investigated the effect of rapalogs RAD001 and CCI-779 on HPV-negative mutTP53 HNSCC cell lines and xenografts. Rapalogs significantly reduced cell viability and colony formation. Interestingly, rapalogs-induced autophagy with no effect on apoptosis. Pretreatment with autophagy inhibitors, 3-methyladenine (3-MA) and ULK-101 rescued the cell viability by inhibiting rapalog-induced autophagy, suggesting that both RAD001 and CCI-779 induce non-apoptotic autophagy-dependent cell death (ADCD). Moreover, rapalogs upregulated the levels of ULK1 and pULK1 S555 with concomitant downregulation of the mTORC1 pathway. However, pretreatment of cells with rapalogs prevented the ULK-101-mediated inhibition of ULK1 to sustained autophagy, suggesting that rapalogs induce ADCD through the activation of ULK1. To further translate our in vitro studies, we investigated the effect of RAD001 in HPV-negative mutTP53 (HN31 and FaDu) tumor cell xenograft model in nude mice. Mice treated with RAD001 exhibited a significant tumor volume reduction without induction of apoptosis, and with a concomitant increase in autophagy. Further, treatment with RAD001 was associated with a considerable increase in pULK1 S555 and ULK1 levels through the inhibition of mTORC1. 3-MA reversed the effect of RAD001 on FaDu tumor growth suggesting that RAD001 promotes ACDC in HPV-negative mutTP53 xenograft. This is the first report demonstrating that rapalogs promote non-apoptotic ADCD in HPV-negative mutTP53 HNSCC via the ULK1 pathway. Further studies are required to establish the promising role of rapalogs in preventing the regrowth of HPV-negative mutTP53 HNSCC.     

Application of computer-generated images to train pattern recognition used in semiquantitative immunohistochemistry scoring

This study aimed to clarify whether the pattern recognition involved in scoring proliferation fractions can be trained by abstract computerized images of virtual tissues. Twenty computer-generated images with randomly distributed blue or red dots were scored by 12 probands (all co-workers or collaborators of the Institute of Pathology, University of Bonn). Afterward, the probands underwent a training phase during which they received an immediate feedback on the actual rate of positivity after each image. Finally, the initial testing series was rescored. In a second round with 15 different probands, 20 Ki-67 immunohistochemistry images of tonsil tissue were scored, followed by the same training phase with computer-generated images, before the immunohistochemistry slides were scored again. Paired t-tests were used to compare the differences in mean rates pre- and post-training. Concerning computerized images, untrained probands scored the percentages of positive dots with a mean deviation from the true rates of 8.2%. Following training, the same testing series was scored significantly better with a mean deviation of 4.9% (mean improvement 3.3%, p < 0.001). Scoring real immunohistochemistry slides, the training with computerized images also improved correct estimations, albeit to a lesser degree (mean improvement 1%, p = 0.03). Abstract computerized images of virtual tissues may be a useful tool to train and improve the accuracy of pattern recognition involved in semiquantitative scoring of immunohistochemistry slides. As a side results, this study highlights the value of computer-generated images to verify the performance of image-analysis software.     

Correction to: The protean world of non-coding RNAs in glioblastoma

Journal of Molecular Medicine -