Archives de 3 juin 2008

DNA damage induced by chronic inflammation contributes to colon carcinogenesis in mice

DNA damage induced by chronic inflammation contributes to colon carcinogenesis in mice

Lisiane B. Meira, James M. Bugni, Stephanie L. Green, Chung-Wei Lee, Bo Pang, Diana Borenshtein, Barry H. Rickman, Arlin B. Rogers, Catherine A. Moroski-Erkul, Jose L. McFaline, David B. Schauer, Peter C. Dedon, James G. Fox, and Leona D. Samson

J. Clin. Invest. Lisiane B. Meira, et al. doi:10.1172/JCI35073

Chronic inflammation increases cancer risk. While it is clear that cell signaling elicited by inflammatory cytokines promotes tumor development, the impact of DNA damage production resulting from inflammation-associated reactive oxygen and nitrogen species (RONS) on tumor development has not been directly tested. RONS induce DNA damage that can be recognized by alkyladenine DNA glycosylase (Aag) to initiate base excision repair. Using a mouse model of episodic inflammatory bowel disease by repeated administration of dextran sulfate sodium in the drinking water, we show that Aag-mediated DNA repair prevents colonic epithelial damage and reduces the severity of dextran sulfate sodium–induced colon tumorigenesis. Importantly, DNA base lesions expected to be induced by RONS and recognized by Aag accumulated to higher levels in Aag-deficient animals following stimulation of colonic inflammation. Finally, as a test of the generality of this effect we show that Aag-deficient animals display more severe gastric lesions that are precursors of gastric cancer after chronic infection with Helicobacter pylori. These data demonstrate that the repair of DNA lesions formed by RONS during chronic inflammation is important for protection against colon carcinogenesis.

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A New Step In Evolution

[Update]REPLAYING EVOLUTION

A New Step In Evolution

Ratzy et Staune devraient avoir les boules :-) Enfin, ils ont perdu une occasion de ne pas raconter une grosse connerie.

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Implementing Arithmetic and Other Analytic Operations By Transcriptional Regulation

Implementing Arithmetic and Other Analytic Operations By Transcriptional Regulation:

by Sean M. Cory, Theodore J. Perkins

The biochemistry of the cell is daunting in its complexity. In order to understand this complexity, we are often forced to use metaphors or construct analogies to systems that we understand better. One long-standing analogy is to digital computers, with their large networks of interacting components that manage to act in coherent and useful ways. Indeed, we know from both theoretical models and empirical observations that biological entities such as genes can sometimes be described accurately by digital, or logical, expressions—turning on or off in response to regulatory signals. However, far more sophisticated computations can also take place, as has been documented in the responses of genes such as the lac operon or Endo-16. We analyze chemical kinetic models of transcriptional gene regulation and show that even simple models are capable of nearly arbitrary analog computations, ranging from elementary arithmetic operations to general analytic functions. Understanding the computational capacities of genes, and of biochemical systems more generally, tells us what to look for when studying natural systems and tells us what we can hope to build by biological engineering.

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Measuring Global Credibility with Application to Local Sequence Alignment

Measuring Global Credibility with Application to Local Sequence Alignment:

by Bobbie-Jo M. Webb-Robertson, Lee Ann McCue, Charles E. Lawrence

Sequence alignment is the cornerstone capability used by a multitude of computational biology applications, such as phylogeny reconstruction and identification of common regulatory mechanisms. Sequence alignment methods typically seek a high-scoring alignment between a pair of sequences, and assign a statistical significance to this single alignment. However, because a single alignment of two (or more) sequences is a point estimate, it may not be representative of the entire set (ensemble) of possible alignments of those sequences; thus, there may be considerable uncertainty associated with any one alignment among an immense ensemble of possibilities. To address the uncertainty of a proposed alignment, we used a Bayesian probabilistic approach to assess an alignment’s reliability in the context of the entire ensemble of possible alignments. Our approach performs a global assessment of the degree to which the members of the ensemble depart from a selected alignment, thereby determining a credibility limit. In an evaluation of the popular maximum similarity alignment and the centroid alignment (i.e., the alignment that is in the center of the posterior distribution of alignments), we find that the centroid yields tighter credibility limits (on average) than the maximum similarity alignment. Beyond the usual interest in putting error limits on point estimates, our findings of substantial variability in credibility limits of alignments argue for wider adoption of these limits, so the degree of error is delineated prior to the subsequent use of the alignments.

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Prise de bec

[Re-update]
En ayant fouillé un peu je me rends compte que l’article de J-P Bombled n’a fait que changer de place :-)

[update] VF m’apprend dans les commentaires que l’article de J-P Bombled ne figure plus sur le site de Blaise Pascal. Dommage pour Blaise Pascal. Mais le Net étant ce qu’il est, pour l’instant vous pouvez le trouver en cache de Google, et de toute façon j’en ai fait une copie pour plus tard, quand il disparaîtra du dit cache. Si vous avez envie/besoin de le lire, faites-moi signe.
Si J-P Bombled souhaite publier son texte quelque part sur le Net, je lui propose un post invité ici-même.


Il y a une prise de bec, signée par Jean-Pierre Bombled, publiée sur le site du Réseau Blaise Pascal, qui mérite le détour, presque digne du Canard Enchaîné. La cible directe est le finalisme et anthropocentrisme qu’affiche Trinh Xuan Tuan, de l’UIP, le pote à Staune.

Ca ne serait pas exceptionnel, la thèse de TXT n’appelant que des critiques négatives ou la béatitude de l’ignorance, si elle n’était pas le fait d’un croyant théiste, qui semble pleinement, agréablement, conscient de la différence entre Science et croyance. Et qui l’exprime de la seule façon que je trouve respectable, rationnellement :

Par ailleurs, si l’on admet un doute méthodologique sur la connaissance observable actuelle, est-ce bien raisonnable de se lancer – sans un doute infiniment plus considérable – dans des affirmations soigneusement voilées (cf. la partie ré-enchantement du monde) sur ce qui n’est pas observable ; laissant croire que la connaissance de cet inobservable est possible, avec d’autres méthodologies mais surtout avec un degré de vérité considérable ?

Ne serait-il pas paradoxal d’affirmer et de se comporter comme si l’on avait plus raison [2] de se fier à l’inobservable qu’à l’observable ? On peut croire (c’est-à-dire adhérer de tout son cœur à de l’inobservable et régler sa vie sur de l’inobservable), mais on ne peut dire que cet inobservable est plus sûr et certain que l’observable. On peut tout à fait dire (avec raison, selon moi) que cet inobservable est plus important et plus vital pour le croyant que l’observable. Mais on ne peut pas dire que l’adhésion sincère et profonde (du croyant) fait office de preuve de la vérité de ce sur quoi (ou qui) porte l’adhésion ou de celle du contenu de l’adhésion.

Il faut accepter qu’il y ait un risque de « plante » dans l’acte de confiance, d’adhésion, de foi. C’est frustrant ; cependant il faut l’assumer.

Croire n’est pas savoir [3]. Nous sommes des croyants, pas des sachants.

Après les discussions sur les créationnistes et leur sale manie de vouloir s’adonner à la scienligion pour soutenir leur foi, le positionnement de Jean-Pierre Bombled me donne envie de lui serrer la paluche et de m’asseoir pour boire un coup et papoter avec lui.

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A Probabilistic Model of Local Sequence Alignment That Simplifies Statistical Significance Estimation

A Probabilistic Model of Local Sequence Alignment That Simplifies Statistical Significance Estimation:

Sequence database searches are a fundamental tool of molecular biology, enabling researchers to identify related sequences in other organisms, which often provides invaluable clues to the function and evolutionary history of genes. The power of database searches to detect more and more remote evolutionary relationships – essentially, to look back deeper in time – has improved steadily, with the adoption of more complex and realistic models. However, database searches require not just a realistic scoring model, but also the ability to distinguish good scores from bad ones – the ability to calculate the statistical significance of scores. For many models and scoring schemes, accurate statistical significance calculations have either involved expensive computational simulations, or not been feasible at all. Here, I introduce a probabilistic model of local sequence alignment that has readily predictable score statistics for position-specific profile scoring systems, and not just for traditional optimal alignment scores, but also for more powerful log-likelihood ratio scores derived in a full probabilistic inference framework. These results remove one of the main obstacles that have impeded the use of more powerful and biologically realistic statistical inference methods in sequence homology searches.

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