University of Nice Sophia Antipolis

About: University of Nice Sophia Antipolis is a education organization based out in Nice, France. It is known for research contribution in the topics: Population & Stars. The organization has 10291 authors who have published 19964 publications receiving 680762 citations. The organization is also known as: UNS & University of Nice-Sophia Antipolis.

Fibroblast activation in cancer: when seed fertilizes soil

Abstract: In solid cancers, activated fibroblasts acquire the capacity to provide fertile soil for tumor progression. Specifically, cancer-associated fibroblasts (CAFs) establish a strong relationship with cancer cells. This provides advantages to both cell types: whereas cancer cells initiate and sustain CAF activation, CAFs support cancer cell growth, motility and invasion. This results in tumor progression, metastasis and chemoresistance. Numerous studies have detailed the mechanisms involved in fibroblast activation and cancer progression, some of which are reviewed in this article. Cancer cells and CAFs are "partners in crime", and their interaction is supported by inflammation. An understanding of the enemy, the cancer cell population and its "allies" should provide novel opportunities for targeted-drug development. Graphical Abstract Molecular mechanism of fibroblast activation. a Normal fibroblasts are the most common cell type in the extracellular matrix and are responsible for the synthesis of collagens and fibrilar proteins. Under normal conditions, fibroblasts maintain tissue homeostasis and contribute to proper cell communication and function. Fibroblasts can be activated by a diverse set of factors secreted from cancer or immune cells. Not only growth factors such as TGF-β, PDGF, HGF and FGF but also interleukins, metalloproteinases and reactive oxygen species can promote activation. Likewise, transcriptional factors such as NF-κB and HSF-1 play an important role, as do the gene family of metalloproteinase inhibitors, Timp and the NF-κB subunit, p62. Interestingly, fibroblasts themselves can stimulate cancer cells to support activation further. b Once activated, fibroblasts undergo a phenotype switch and become cancer-associated fibroblasts (CAFs) expressing various markers such as α-SMA, FSP1, vimentin and periostatin. c Recently, the LIF/GP130/IL6-R pathway has been identified as a signaling cascade involved in fibroblast activation. Upon LIF stimulation, JAK is phosphorylated and further activates STAT3, a transcriptional factor that is then translocated into the nucleus where it promotes the transcription of genes responsible for cell growth, differentiation, proliferation and apoptosis. Ruxolitinib can inhibit JAK and prevent STAT3 activation. Further on, the maintenance of JAK activation is supported by epigenetical changes and post-translational modifications. Once pSTAT3 is acetylated by histon acetyltransferase, p300, it leads to the loss of expression of SHP-1, which is a negative regulator of the JAK/STAT pathway. Silencing of SHP-1 steers the constitutive activation of JAK and STAT3.

Generating a Condensed Representation for Association Rules

Abstract: Association rule extraction from operational datasets often produces several tens of thousands, and even millions, of association rules. Moreover, many of these rules are redundant and thus useless. Using a semantic based on the closure of the Galois connection, we define a condensed representation for association rules. This representation is characterized by frequent closed itemsets and their generators. It contains the non-redundant association rules having minimal antecedent and maximal consequent, called min-max association rules. We think that these rules are the most relevant since they are the most general non-redundant association rules. Furthermore, this representation is a basis, i.e., a generating set for all association rules, their supports and their confidences, and all of them can be retrieved needless accessing the data. We introduce algorithms for extracting this basis and for reconstructing all association rules. Results of experiments carried out on real datasets show the usefulness of this approach. In order to generate this basis when an algorithm for extracting frequent itemsets--such as Apriori for instance--is used, we also present an algorithm for deriving frequent closed itemsets and their generators from frequent itemsets without using the dataset.

Early transcriptomic events in microdissected Arabidopsis nematode-induced giant cells.

Abstract: Root-knot nematodes differentiate highly specialized feeding cells in roots (giant cells, GCs), through poorly characterized mechanisms that include extensive transcriptional changes. While global transcriptome analyses have used galls, which are complex root structures that include GCs and surrounding tissues, no global gene expression changes specific to GCs have been described. We report on the differential transcriptome of GCs versus root vascular cells, induced in Arabidopsis by Meloidogyne javanica at a very early stage of their development, 3 days after infection (d.p.i.). Laser microdissection was used to capture GCs and root vascular cells for microarray analysis, which was validated through qPCR and by a promoter-GUS fusion study. Results show that by 3 d.p.i., GCs exhibit major gene repression. Although some genes showed similar regulation in both galls and GCs, the majority had different expression patterns, confirming the molecular distinctiveness of the GCs within the gall. Most of the differentially regulated genes in GCs have no previously assigned function. Comparisons with other transcriptome analyses revealed similarities between GCs and cell suspensions differentiating into xylem cells. This suggests a molecular link between GCs and developing vascular cells, which represent putative GC stem cells. Gene expression in GCs at 3 d.p.i. was also found to be similar to crown galls induced by Agrobacterium tumefaciens, a specialized root biotroph.