773 research outputs found

    Circulating C-reactive protein and breast cancer risk – systematic literature review and meta-analysis of prospective cohort studies

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    We conducted a systematic literature review to explore the association between circulating C-reactive protein (CRP), a low-grade inflammation biomarker, and breast cancer risk. Relevant prospective studies in women were identified in PubMed and Web of Science until February 2015. Random-effects dose-response metaanalysis was conducted, overall and in post-menopausal women. Twelve out of 15 studies identified were included in the meta-analysis on any breast cancers (3,522 cases, 69,610 women) and nine on postmenopausal breast cancer (2,516 cases, 36,847 women). For each doubling of CRP concentration, a 7% (95% CI: 2%–12%) and 6% (95% CI: 1%–11%) increased risk was observed (I2=47% and 32%; P heterogeneity=0.04 and 0.17), respectively. The association was linear over most of the range of CRP concentrations. Positive associations remained in the studies that examined the exclusion of early years of follow-up. Associations were attenuated in studies adjusted for lifestyle factors, which partly explained the significant heterogeneity between studies in the overall analysis. On average, the associations in studies adjusted or not adjusted for body mass index were similar. Low-grade inflammation may have a role in breast cancer development. Additional prospective studies are needed to better understand confounding and effect modification from lifestyle factors

    Les turbo-codes Ă  roulettes

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    é - Le problÚme majeur dans l'implémentation matérielle d'un turbo-décodeur réside dans le manque de parallélisme des algorithmes de décodage MAP. Cet article propose un nouveau procédé de turbo-codage basé sur deux idées: le codage de chaque dimension par P codes convolutifs récursifs circulaires indépendants et des contraintes sur la structure de l'entrelaceur qui permet de décoder en parallÚle les P codes convolutifs dans chaque dimension. La construction des codes constituants et de l'entrelaceur est décrite et analysée. Un haut degré de parallélisme est obtenu avec des performances équivalentes ou meilleures que les meilleurs turbo-codes connus. L'architecture parallÚle du décodeur permet de réduire la complexité du turbo-décodeur pour des applications à trÚs hauts débits

    Implementation of the Enhanced Recovery After Surgery (ERASÂź) program in neurosurgery.

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    Over the past decade, Enhanced Recovery After Surgery (ERASÂź) guidelines have been proven to simplify postoperative care and improve recovery in several surgical disciplines. The authors set out to create and launch an ERASÂź program for cranial neurosurgery that meets official ERASÂź Society standards. The authors summarize the successive steps taken to achieve this goal in two specific neurosurgical conditions and describe the challenges they faced. Pituitary neuroendocrine tumors (Pit-NET) resected by a transsphenoidal approach and craniosynostosis (Cs) repair were selected as appropriate targets for the implementation of ERASÂź program in the Department of Neurosurgery. A multidisciplinary team with experience in managing these pathologies was created. A specialized ERASÂź nurse coordinator was hired. An ERASÂź certification process was performed involving 4 seminars separated by 3 active phases under the supervision of an ERASÂź coach. The ERASÂź Pit-NET team included 8 active members. The ERASÂź Cs team included 12 active members. Through the ERASÂź certification process, areas for improvement were identified, local protocols were written, and the ERASÂź program was implemented. Patient-centered strategies were developed to increase compliance with the ERASÂź protocols. A prospective database was designed for ongoing program evaluation. Certification was achieved in 18 months. Direct costs and time requirements are reported. Successful ERASÂź certification requires a committed multidisciplinary team, an ERASÂź coach, and a dedicated nurse coordinator

    Anomalous metamagnetism in the low carrier density Kondo lattice YbRh3Si7

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    We report complex metamagnetic transitions in single crystals of the new low carrier Kondo antiferromagnet YbRh3Si7. Electrical transport, magnetization, and specific heat measurements reveal antiferromagnetic order at T_N = 7.5 K. Neutron diffraction measurements show that the magnetic ground state of YbRh3Si7 is a collinear antiferromagnet where the moments are aligned in the ab plane. With such an ordered state, no metamagnetic transitions are expected when a magnetic field is applied along the c axis. It is therefore surprising that high field magnetization, torque, and resistivity measurements with H||c reveal two metamagnetic transitions at mu_0H_1 = 6.7 T and mu_0H_2 = 21 T. When the field is tilted away from the c axis, towards the ab plane, both metamagnetic transitions are shifted to higher fields. The first metamagnetic transition leads to an abrupt increase in the electrical resistivity, while the second transition is accompanied by a dramatic reduction in the electrical resistivity. Thus, the magnetic and electronic degrees of freedom in YbRh3Si7 are strongly coupled. We discuss the origin of the anomalous metamagnetism and conclude that it is related to competition between crystal electric field anisotropy and anisotropic exchange interactions.Comment: 23 pages and 4 figures in the main text. 7 pages and 5 figures in the supplementary materia

    Evaluation of a candidate breast cancer associated SNP in ERCC4 as a risk modifier in BRCA1 and BRCA2 mutation carriers. Results from the Consortium of Investigators of Modifiers of BRCA1/BRCA2 (CIMBA)

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    Background: In this study we aimed to evaluate the role of a SNP in intron 1 of the ERCC4 gene (rs744154), previously reported to be associated with a reduced risk of breast cancer in the general population, as a breast cancer risk modifier in BRCA1 and BRCA2 mutation carriers. Methods: We have genotyped rs744154 in 9408 BRCA1 and 5632 BRCA2 mutation carriers from the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) and assessed its association with breast cancer risk using a retrospective weighted cohort approach. Results: We found no evidence of association with breast cancer risk for BRCA1 (per-allele HR: 0.98, 95% CI: 0.93–1.04, P=0.5) or BRCA2 (per-allele HR: 0.97, 95% CI: 0.89–1.06, P=0.5) mutation carriers. Conclusion: This SNP is not a significant modifier of breast cancer risk for mutation carriers, though weak associations cannot be ruled out. A Osorio1, R L Milne2, G Pita3, P Peterlongo4,5, T Heikkinen6, J Simard7, G Chenevix-Trench8, A B Spurdle8, J Beesley8, X Chen8, S Healey8, KConFab9, S L Neuhausen10, Y C Ding10, F J Couch11,12, X Wang11, N Lindor13, S Manoukian4, M Barile14, A Viel15, L Tizzoni5,16, C I Szabo17, L Foretova18, M Zikan19, K Claes20, M H Greene21, P Mai21, G Rennert22, F Lejbkowicz22, O Barnett-Griness22, I L Andrulis23,24, H Ozcelik24, N Weerasooriya23, OCGN23, A-M Gerdes25, M Thomassen25, D G Cruger26, M A Caligo27, E Friedman28,29, B Kaufman28,29, Y Laitman28, S Cohen28, T Kontorovich28, R Gershoni-Baruch30, E Dagan31,32, H Jernström33, M S Askmalm34, B Arver35, B Malmer36, SWE-BRCA37, S M Domchek38, K L Nathanson38, J Brunet39, T RamĂłn y Cajal40, D Yannoukakos41, U Hamann42, HEBON37, F B L Hogervorst43, S Verhoef43, EB GĂłmez GarcĂ­a44,45, J T Wijnen46,47, A van den Ouweland48, EMBRACE37, D F Easton49, S Peock49, M Cook49, C T Oliver49, D Frost49, C Luccarini50, D G Evans51, F Lalloo51, R Eeles52, G Pichert53, J Cook54, S Hodgson55, P J Morrison56, F Douglas57, A K Godwin58, GEMO59,60,61, O M Sinilnikova59,60, L Barjhoux59,60, D Stoppa-Lyonnet61, V Moncoutier61, S Giraud59, C Cassini62,63, L Olivier-Faivre62,63, F RĂ©villion64, J-P Peyrat64, D Muller65, J-P Fricker65, H T Lynch66, E M John67, S Buys68, M Daly69, J L Hopper70, M B Terry71, A Miron72, Y Yassin72, D Goldgar73, Breast Cancer Family Registry37, C F Singer74, D Gschwantler-Kaulich74, G Pfeiler74, A-C Spiess74, Thomas v O Hansen75, O T Johannsson76, T Kirchhoff77, K Offit77, K Kosarin77, M Piedmonte78, G C Rodriguez79, K Wakeley80, J F Boggess81, J Basil82, P E Schwartz83, S V Blank84, A E Toland85, M Montagna86, C Casella87, E N Imyanitov88, A Allavena89, R K Schmutzler90, B Versmold90, C Engel91, A Meindl92, N Ditsch93, N Arnold94, D Niederacher95, H Deißler96, B Fiebig97, R Varon-Mateeva98, D Schaefer99, U G Froster100, T Caldes101, M de la Hoya101, L McGuffog49, A C Antoniou49, H Nevanlinna6, P Radice4,5 and J BenĂ­tez1,3 on behalf of CIMB

    Training Signaling Pathway Maps to Biochemical Data with Constrained Fuzzy Logic: Quantitative Analysis of Liver Cell Responses to Inflammatory Stimuli

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    Predictive understanding of cell signaling network operation based on general prior knowledge but consistent with empirical data in a specific environmental context is a current challenge in computational biology. Recent work has demonstrated that Boolean logic can be used to create context-specific network models by training proteomic pathway maps to dedicated biochemical data; however, the Boolean formalism is restricted to characterizing protein species as either fully active or inactive. To advance beyond this limitation, we propose a novel form of fuzzy logic sufficiently flexible to model quantitative data but also sufficiently simple to efficiently construct models by training pathway maps on dedicated experimental measurements. Our new approach, termed constrained fuzzy logic (cFL), converts a prior knowledge network (obtained from literature or interactome databases) into a computable model that describes graded values of protein activation across multiple pathways. We train a cFL-converted network to experimental data describing hepatocytic protein activation by inflammatory cytokines and demonstrate the application of the resultant trained models for three important purposes: (a) generating experimentally testable biological hypotheses concerning pathway crosstalk, (b) establishing capability for quantitative prediction of protein activity, and (c) prediction and understanding of the cytokine release phenotypic response. Our methodology systematically and quantitatively trains a protein pathway map summarizing curated literature to context-specific biochemical data. This process generates a computable model yielding successful prediction of new test data and offering biological insight into complex datasets that are difficult to fully analyze by intuition alone.National Institutes of Health (U.S.) (NIH grant P50-GM68762)National Institutes of Health (U.S.) (Grant U54-CA112967)United States. Dept. of Defense (Institute for Collaborative Biotechnologies

    GOBLET: The Global Organisation for Bioinformatics Learning, Education and Training

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    In recent years, high-throughput technologies have brought big data to the life sciences. The march of progress has been rapid, leaving in its wake a demand for courses in data analysis, data stewardship, computing fundamentals, etc., a need that universities have not yet been able to satisfy—paradoxically, many are actually closing “niche” bioinformatics courses at a time of critical need. The impact of this is being felt across continents, as many students and early-stage researchers are being left without appropriate skills to manage, analyse, and interpret their data with confidence. This situation has galvanised a group of scientists to address the problems on an international scale. For the first time, bioinformatics educators and trainers across the globe have come together to address common needs, rising above institutional and international boundaries to cooperate in sharing bioinformatics training expertise, experience, and resources, aiming to put ad hoc training practices on a more professional footing for the benefit of all

    GOBLET: the Global Organisation for Bioinformatics Learning, Education and Training

    Get PDF
    In recent years, high-throughput technologies have brought big data to the life sciences. The march of progress has been rapid, leaving in its wake a demand for courses in data analysis, data stewardship, computing fundamentals, etc., a need that universities have not yet been able to satisfy--paradoxically, many are actually closing "niche" bioinformatics courses at a time of critical need. The impact of this is being felt across continents, as many students and early-stage researchers are being left without appropriate skills to manage, analyse, and interpret their data with confidence. This situation has galvanised a group of scientists to address the problems on an international scale. For the first time, bioinformatics educators and trainers across the globe have come together to address common needs, rising above institutional and international boundaries to cooperate in sharing bioinformatics training expertise, experience, and resources, aiming to put ad hoc training practices on a more professional footing for the benefit of all

    The Promise and Challenge of Therapeutic MicroRNA Silencing in Diabetes and Metabolic Diseases

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    MicroRNAs (miRNAs) are small, non-coding, RNA molecules that regulate gene expression. They have a long evolutionary history and are found in plants, viruses, and animals. Although initially discovered in 1993 in Caenorhabditis elegans, they were not appreciated as widespread and abundant gene regulators until the early 2000s. Studies in the last decade have found that miRNAs confer phenotypic robustness in the face of environmental perturbation, may serve as diagnostic and prognostic indicators of disease, underlie the pathobiology of a wide array of complex disorders, and represent compelling therapeutic targets. Pre-clinical studies in animal models have demonstrated that pharmacologic manipulation of miRNAs, mostly in the liver, can modulate metabolic phenotypes and even reverse the course of insulin resistance and diabetes. There is cautious optimism in the field about miRNA-based therapies for diabetes, several of which are already in various stages of clinical trials. This review will highlight both the promise and the most pressing challenges of therapeutic miRNA silencing in diabetes and related conditions
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