Role of CD44 in clear cell renal cell carcinoma invasiveness after antiangiogenic treatment

Treballs Finals de Grau de Farmàcia, Facultat de Farmàcia, Universitat de Barcelona, 2017. Tutor/a: Joan Carles Rodríguez Rubio.[eng] During last century, big effort to understand the biochemical basis of cancer was carried out. One of the principal branches of these cancer investigations used drugs to prevent the formation of new blood vessels –process called angiogenesis– responsible for the nutrients supply of the tumour. These drugs are generally called antiangiogenics. It was discovered that some types of tumour have or develop resistance to these drugs when treatment was long enough. For that reason, mechanisms of resistance, aggressiveness, invasion and/or metastasis after the treatment are nowadays relevant to study. Recently, a protein that could be involved in the increased invasiveness of tumour cells after the antiangiogenic treatment appeared. This project collects some evidence that indicates that this protein, called CD44, might play a role in the increased invasion after antiangiogenic treatment in mouse models of renal carcinoma.[cat] Durant l’últim segle, s’ha fet un gran esforç per aprofundir en la basant bioquímica de la investigació contra el càncer. Una de les branques principals d’aquesta investigació utilitza fàrmacs que prevenen la formació de nous vasos sanguinis –procés anomenat angiogènesis- encarregats de nodrir el tumor. Aquests fàrmacs es diuen generalment antiangiogènics. S’ha descobert que alguns tipus de tumor tenen o desenvolupen resistència a aquests fàrmacs quan el tractament és prou llarg. Per aquesta raó, actualment s’està investigant profundament quins són els mecanismes pels quals apareix aquesta resistència, així com també perquè els tumors es tornen més agressius, invasius i/o metastàtics després del tractament. Recentment s’ha descobert una proteïna que podria estar involucrada en l’augment de la invasivitat de les cèl·lules tumorals després del tractament antiangiogènic. Aquest treball recull algunes de les evidències que apunten cap al paper de la proteïna CD44 en l’increment de la invasió tumoral post-tractament amb fàrmacs antiangiogènics en models ratolins de càncer renal

Le degré de grammaticalisation de HAVE : application d’une méthodologie développée par Joan Bybee et William Pagliuca

International audienc

Additional file 4: of The role of breast-feeding in infant immune system: a systems perspective on the intestinal microbiome

Microbial abundance tables. (CSV 14 kb

Inventory control with product returns: The impact of imperfect information

Product returns are characterized by considerable uncertainty on time and quantity. In the literature on inventory management for product return environments best forecasts of future returns are associated with methods that use the most information regarding product return history. In practice, however, data is often scarce and unreliable, while forecasts based on historical data, reliable or not, are never perfect. In this paper we therefore investigate the impact of imperfect information with respect to the return process on inventory management performance. We show that in the case of imperfect information the most informed method does not necessarily lead to best performance. The results have relevant implications regarding investments in product return information systems.OTB Research Institut

Additional file 7: of Nonlinear transcriptomic response to dietary fat intake in the small intestine of C57BL/6J mice

Over-represented Gene Ontology Biological Process (GOBP) terms that are completely up-regulated. For each GOBP term we summarize: the total number of genes in the microarray (gene set size, labelled as Set size), the count of genes extracted with our analysis (observed hits, labelled as Hits), and the adjusted p-values. Intestine sections: Prox = proximal; Mid = middle; Dist = distal. Response types: lm = linear; log = logarithm; exp = exponential. (PDF 204 kb

<i>CPS1</i> –Glycine network.

<p>Networks for <i>CPS1</i> and Glycine (77 and 383 nodes, respectively) were built from publicly available databases and subsequently merged. Purple nodes belong to the <i>CPS1</i> network; green nodes belong to the Glycine network; orange nodes are shared between the two networks (33). The bigger nodes represent <i>CPS1</i> and Glycine. Nodes with bigger labels represent the genes in the One carbon pool by folate KEGG pathway underlined from the gene enrichment analysis.</p

Manhattan plot of Glycine.

<p>(a) Genome-wide association of glycine and (b) zoom on chromosome 2. The two green dots represent the SNPs significantly associated with glycine levels: rs10206976 (chr 2:210749914) and rs12613336 (chr 2:210704675), in the <i>CPS1</i> gene. Significativity (p—value = 5.0e-8) and suggestive (p—value = 1.0e-5) thresholds are provided as red and blue lines respectively.</p

Gene expression and BMI.

<p>Gene expression and BMI.</p

Gene expression and weight maintenance.

<p>Gene expression and weight maintenance.</p

<i>CPS1</i> gene expression and weight maintenance.

<p>Box plots for <i>CPS1</i> gene expression at PWL, for weight maintainers (WMs) and weight maintenance resistors (WRs), defined as ΔBMI < 4% and ΔBMI > = 4% increase (p-value = 0.04, corrected for age and sex).</p