Improving Drug Response Prediction Using Dual Similarity Regularization

Anti-cancer medicine for a particular patient has been a personal medical goal. Many computational models have been proposed by researchers to predict drug response. But predictive accuracy still remains a challenge. Base on this concept which “Similar cells have similar responses to drugs”, we developed the basic method of matrix factorization method by adding fines to similarity. So that the distance of latent factors to two cell lines or (drug) should be inversely related to similarity. This means that two similar drugs or similar cell lines should have a short distance, whereas two similar cell lines or non-similar drugs should have a large gap with their latent factors. We proposed a Dual similarity-regularized matrix factorization (DSRMF) model, then generated new data for drug similarity from the two-dimensional three-dimensional chemical structure, which were obtained from the CCLE and GDSC databases. In this research, by using the proposed model, and generating new drug similarity data we achieved the average Pearson correlation coefficient (PCC) about 0.96, and average mean square error (RMSE) Root about 0.30, between the observed value and the predicted value for the cell line response to the drug. Our analysis in this research showed, using heterogeneous data, has better results, and can be obtained with the proposed model, using other panels’ cancer cell lines, to calculate similarity between cells. Also, by imposing more restrictions on the similarity between cells, we were able to achieve more accurate prediction for the response of the cell line to the anticancer drug.

Laminar-specific cortico-cortical loops in mouse visual cortex

Many theories propose recurrent interactions across the cortical hierarchy, but it is unclear if cortical circuits are selectively wired to implement looped computations. Using subcellular channelrhodopsin-2-assisted circuit mapping in mouse visual cortex, we compared feedforward (FF) or feedback (FB) cortico-cortical (CC) synaptic input to cells projecting back to the input source (looped neurons) with cells projecting to a different cortical or subcortical area. FF and FB afferents showed similar cell-type selectivity, making stronger connections with looped neurons than with other projection types in layer (L)5 and L6, but not in L2/3, resulting in selective modulation of activity in looped neurons. In most cases, stronger connections in looped L5 neurons were located on their apical tufts, but not on their perisomatic dendrites. Our results reveal that CC connections are selectively wired to form monosynaptic excitatory loops and support a differential role of supragranular and infragranular neurons in hierarchical recurrent computations.

Hyperspectral imaging-based exosome microarray for rapid molecular profiling of extracellular vesicles

A high-throughput hyperspectral image-based exosome (EV) microarray technology to differentiate EVs released by similar cell types or phenotypes.

Improving Drug Response Prediction Using Dual Similarity Regularization

Background:Anti-cancer medicine for a particular patient has been a personal medical goal. Many computational models have been proposed by researchers to predict drug response. But predictive accuracy still remains a challenge. Base on this concept which “Similar cells have similar responses to drugs”, we developed the basic method of matrix factorization method by adding fines to similarity. So that the distance of latent factors to two cell lines or (drug) should be inversely related to similarity. This means that two similar drugs or similar cell lines should have a short distance, whereas two similar cell lines or non-similar drugs should have a large gap with their latent factors.Results:We proposed a Dual similarity-regularized matrix factorization (DSRMF) model, then generated new data for drug similarity from the two-dimensional three-dimensional chemical structure, which were obtained from the CCLE and GDSC databases. In this research, by using the proposed model, and generating new drug similarity data we achieved the average Pearson correlation coefficient (PCC) about 0.96, and average mean square error (RMSE) Root about 0.30, between the observed value and the predicted value for the cell line response to the drug, Conclusions:Our analysis in this research showed, using heterogeneous data, has better results, and can be obtained with the proposed model, using other panels’ cancer cell lines, to calculate similarity between cells. Also, by imposing more restrictions on the similarity between cells, we were able to achieve more accurate prediction for the response of the cell line to the anticancer drug.

Diatom-Derived Polyunsaturated Aldehydes Activate Similar Cell Death Genes in Two Different Systems: Sea Urchin Embryos and Human Cells

Programmed cell death, such as apoptosis and autophagy, are key processes that are activated early on during development, leading to remodelling in embryos and homeostasis in adult organisms. Genomic conservation of death factors has been largely investigated in the animal and plant kingdoms. In this study, we analysed, for the first time, the expression profile of 11 genes involved in apoptosis (extrinsic and intrinsic pathways) and autophagy in sea urchin Paracentrotus lividus embryos exposed to antiproliferative polyunsaturated aldehydes (PUAs), and we compared these results with those obtained on the human cell line A549 treated with the same molecules. We found that sea urchins and human cells activated, at the gene level, a similar cell death response to these compounds. Despite the evolutionary distance between sea urchins and humans, we observed that the activation of apoptotic and autophagic genes in response to cytotoxic compounds is a conserved process. These results give first insight on death mechanisms of P. lividus death mechanisms, also providing additional information for the use of this marine organism as a useful in vitro model for the study of cell death signalling pathways activated in response to chemical compounds.

Cytotoxicity of long-term denture base materials

Introduction: The aim of this study was to evaluate the cytotoxic effect of various denture base materials following four different aging periods. Methods: In total, 48 disc-shaped specimens per each group were prepared: Group I: acrylic resin polymerized in cool water and heated up to 100°C over 45 min and boiled for 15 min; Group II: acrylic resin polymerized under pressure in 40°C–45°C water bath for 10 min; Group III: autopolymerized hard relining resin Cold Liner Rebase; Group IV: autopolymerized hard relining resin Truliner; Group V: soft relining resin DentuSil. Then the specimens were stored in water for 24 h or 15 days, or thermocycled 2500 times or 10,000 times. Cytotoxicity was evaluated with 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay using L929 cells after 72-h cell incubation. Cell viability percentages were counted and statistical analyses were performed. The results were also evaluated according to ISO standard 10993-5. Results: All materials showed similar cell viability percentages following 24-h water storage and 2500 and 10,000 thermal cycles. Following 15-day water storage, a statistically significant difference was observed between the materials. Comparisons of the aging periods for each material showed statistically significant differences. Groups III and IV showed moderately cytotoxic effect following 15-day water storage. The remaining groups showed slightly cytotoxic or non-cytotoxic effect. Discussion: Polymerizing acrylic resins under pressure can be an alternative to conventional polymerizing to ensure a faster denture repair while providing similar cell viability values. Heat-cured acrylic resins provide higher cell viability than hard chairside lining materials in a 15-day period.