What is the Machine Learning?

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

Activation of the MKL1/actin signaling pathway induces hormonal escape in estrogen-responsive breast cancer cell lines.

International audienceEstrogen receptor alpha (ERα) is generally considered to be a good prognostic marker because almost 70% of ERα-positive tumors respond to anti-hormone therapies. Unfortunately, during cancer progression, mammary tumors can escape from estrogen control, resulting in resistance to treatment. In this study, we demonstrate that activation of the actin/megakaryoblastic leukemia 1 (MKL1) signaling pathway promotes the hormonal escape of estrogen-sensitive breast cancer cell lines. The actin/MKL1 signaling pathway is silenced in differentiated ERα-positive breast cancer MCF-7 and T47D cell lines and active in ERα-negative HMT-3522 T4-2 and MDA-MB-231 breast cancer cells, which have undergone epithelial-mesenchymal transition. We showed that MKL1 activation in MCF-7 cells, either by modulating actin dynamics or using MKL1 mutants, down-regulates ERα expression and abolishes E2-dependent cell growth. Interestingly, the constitutively active form of MKL1 represses PR and HER2 expression in these cells and increases the expression of HB-EGF, TGFβ, and amphiregulin growth factors in an E2-independent manner. The resulting expression profile (ER-, PR-, HER2-) typically corresponds to the triple-negative breast cancer expression profile

Codon adaptation by synonymous mutations impacts the functional properties of the estrogen receptor-alpha protein in breast cancer cells

International audienceOestrogen receptor-alpha (ER alpha) positivity is intimately associated with the development of hormone-dependent breast cancers. A major challenge in the treatment of these cancers is to understand and overcome the mechanisms of endocrine resistance. Recently, two distinct translation programmes using specific transfer RNA (tRNA) repertoires and codon usage frequencies were evidenced during cell proliferation and differentiation. Considering the phenotype switch of cancer cells to more proliferating and less-differentiated states, we can speculate that the changes in the tRNA pool and codon usage that likely occur make the ER alpha coding sequence no longer adapted, impacting translational rate, co-translational folding and the resulting functional properties of the protein. To verify this hypothesis, we generated an ER alpha synonymous coding sequence whose codon usage was optimized to the frequencies observed in genes expressed specifically in proliferating cells and then investigated the functional properties of the encoded receptor. We demonstrate that such a codon adaptation restores ER alpha activities to levels observed in differentiated cells, including: (a) an enhanced contribution exerted by transactivation function 1 (AF1) in ER alpha transcriptional activity; (b) enhanced interactions with nuclear receptor corepressor 1 and 2 [NCoR1 and NCoR2 (also known as SMRT) respectively], promoting repressive capability; and (c) reduced interactions with SRC proto-oncogene, non-receptor tyrosine kinase (Src) and phosphoinositide 3-kinase (PI3K) p85 kinases, inhibiting MAPK and AKT signalling pathway

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

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

Peroxisome proliferator-activated receptor alpha improves pancreatic adaptation to insulin resistance in obese mice and reduces lipotoxicity in human islets

Peroxisome proliferator-activated receptor (PPAR) alpha is a transcription factor controlling lipid and glucose homeostasis. PPAR alpha-deficient (-/-) mice are protected from high-fat diet-induced insulin resistance. However, the impact of PPAR alpha in the pathophysiological setting of obesity-related insulin resistance is unknown. Therefore, PPAR alpha(-/-) mice in an obese (ob/ob) background were generated. PPAR alpha deficiency did not influence the growth curves of the obese mice but surprisingly resulted in a severe, age-dependent hyperglycemia. PPAR alpha deficiency did not aggravate peripheral insulin resistance. By contrast, PPAR alpha(-/-) ob/ob mice developed pancreatic beta-cell dysfunction characterized by reduced mean islet area and decreased insulin secretion in response to glucose in vitro and in vivo. In primary human pancreatic islets, PPAR alpha agonist treatment prevented fatty acid-induced impairment of glucose-stimulated insulin secretion, apoptosis, and triglyceride accumulation. These results indicate that PPAR alpha improves the adaptative response of the pancreatic beta-cell to pathological conditions. PPAR alpha could thus represent a promising target in the prevention of type 2 diabetes