6 research outputs found

    What is the Machine Learning?

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    Applications of machine learning tools to problems of physical interest are often criticized for producing sensitivity at the expense of transparency. To address this concern, we explore a data planing procedure for identifying combinations of variables -- aided by physical intuition -- that can discriminate signal from background. Weights are introduced to smooth away the features in a given variable(s). New networks are then trained on this modified data. Observed decreases in sensitivity diagnose the variable's discriminating power. Planing also allows the investigation of the linear versus non-linear nature of the boundaries between signal and background. We demonstrate the efficacy of this approach using a toy example, followed by an application to an idealized heavy resonance scenario at the Large Hadron Collider. By unpacking the information being utilized by these algorithms, this method puts in context what it means for a machine to learn.Comment: 6 pages, 3 figures. Version published in PRD, discussion adde

    Unliganded-ERα increases Stat3 pathway activity.

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    <p>A) - The c-Src phosphorylation state (on tyrosine 416 and 527) and Stat3 (on tyrosine 705) were monitored during 3 hrs of serum deprivation by Western blotting in PC12-C2, PC12-ER2 and PC12-ER-Y537S cells. Total Erk<sub>1-2</sub> was used as loading control. Histograms are the mean ± SEM of three separate experiments. In each case, results were expressed as the ratio of phosphorylation state/Erk<sub>1-2</sub> for Src and Stat3. Columns with different superscripts differ significantly (p<0.05 by Student test). B) - Basal Stat3 transcriptional activity was determined in PC12-WT, PC12-C2, PC12-ER (ER1 and ER2) clones after 36 hrs of transient transfection. The Stat3 reporter gene activity was obtained after normalization of the luciferase activity with the β-galactosidase activity. Results correspond to the mean ± SEM of three separate experiments. Columns with different superscripts differ significantly (p<0.05 by Student test).</p

    Unliganded ERα protects cells against apoptosis.

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    <p>A) - PC12 wild type cells (PC12-WT), PC12 cells transfected with the empty plasmid (PC12-C2) or PC12 stably transfected with ERα encoding plasmid (clones PC12-ER1 and PC12-ER2) were grown in the presence or not of charcoal stripped FCS for 24 hrs with or without E<sub>2</sub> (10<sup>-8</sup> M). Cell viability was then assessed using the quantification of cellular ATP (Vialight HS kit from Lonza). Results are expressed in reference with control clone (PC12-C2) maintained in 5% charcoal stripped FCS. B) - caspase-3 activity was determined in control clone (PC12-C2) and in ERα-positive cells (PC12-ER2) after 24 hrs of culture in the presence or not of charcoal stripped FCS. C) - MCF7 cells were transfected with siRNA targeting ERα or with non-specific siRNA. Twenty four hours later, MCF7 cells were maintained in phenol red-free DMEM/F12 medium containing or not 10% charcoal stripped FCS for 24 hrs before cell viability was assessed using ViaLight HS kit (Lonza). In order to control knockdown efficiency, total protein was extracted from MCF7 cells and the level of ERα was analyzed by western blotting. D) - PC12-C2, PC12-ER1 and PC12-ER2 cells were transiently transfected with an ERE-TK-Luc reporter gene together with CMV-β-Gal. Twelve hours after transfection, the cells were treated or not with E<sub>2</sub> (10<sup>-9</sup> M) or ICI (10<sup>-7</sup> M) for 24 hrs. Normalized luciferase activities were standardized to the reporter gene activity measured in ethanol treated PC12-C2 cells. E) - PC12-C2, PC12-ER1 and PC12-ER2 cells were grown in medium with or without FCS for 24 hrs, in the presence or not of ICI (10<sup>-7</sup> M). Cell viability was then assessed using ViaLight HS kit (Lonza). Results are expressed in reference with control clone (PC12-C2 maintained in 5% charcoal stripped FCS. For all the experiments, values correspond to the mean ± SEM of at least three separate experiments. Columns with different superscripts differ significantly (p<0.05 by Student test).</p

    Ligand-independent protection against apoptosis depends on tyrosine 537 of ERα.

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    <p>A) - Total protein was extracted from different PC12 clones and the level of ERα was analyzed by Western blotting. B) - Cell viability (right panel) of mutated PC12 clones (left panel) was determined after 24 hrs of serum deprivation using ViaLight HS kit (Lonza). For each clone, viability was expressed in percent in reference to the viability of the same clone maintained in medium containing 5% charcoal stripped serum (value 100). Values correspond to the mean ± SEM of at least three separate experiments. Columns with different superscripts differ significantly (p<0.05 by Student test).</p

    <i>In situ</i> PLA detection of endogenous ERα/Src interaction in PC12 and MCF7 cells.

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    <p> A) - Immunocytochemistry for ERα (left panels) and Src (right panels) in MCF7, PC12-C2, PC12-ER2 and PC12-ER-Y537S, grown in medium containing 5% of charcoal stripped serum. The nuclei were counterstained with Dapi (blue) (Obj: X20). B) - <i>In situ</i> PLA for ERα/Src dimers in MCF7, PC12-C2, PC12-ER2 and PC12-ER-Y537S grown in medium containing 5% of charcoal stripped serum with vehicle (upper panels) or with E<sub>2</sub> (10<sup>-8</sup> M) for 5 min (lower panels). The detected dimers are represented by red dots and the nuclei were counterstained with Dapi (blue). C) - Quantification of PLA signals per cell was performed by computer-assisted analysis as reported in the Materials and Methods section. Values correspond to the mean ± SEM of at least three separate experiments (10 fields; more than 500 cells/experiment). Columns with different superscripts differ significantly (p<0.05 by Student test).</p

    Additional file 5: Figure S3. of Glyceollins trigger anti-proliferative effects through estradiol-dependent and independent pathways in breast cancer cells

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    GO enrichment analysis of different treatment-related expression patterns. Eight expression patterns are matched with a selection of GO terms from the ontology “phenotypes,” “biological process,” “cellular component” and “pathways.” The numbers of genes associated with each GO term are indicated in the first column. Enrichment is indicated by bolded rectangles, where the first number indicates the number of genes found in our analysis and the second the number expected with a random list of genes. Overrepresented genes in a specific GO term are shown in red, and underrepresented genes are shown in blue. (TIFF 2724 kb
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