282 research outputs found
A study protocol to investigate the relationship between dietary fibre intake and fermentation, colon cell turnover, global protein acetylation and early carcinogenesis: the FACT study
Background: A number of studies, notably EPIC, have shown a descrease in colorectal cancer risk associated with increased fibre consumption. Whilst the underlying mechanisms are likely to be multifactorial, production of the short-chain fatty-acid butyrate fro butyratye is frequently cited as a major potential contributor to the effect. Butyrate inhibits histone deacetylases, which work on a wide range of proteins over and above histones. We therefore hypothesized that alterations in the acetylated proteome may be associated with a cancer risk phenotype in the colorectal mucosa, and that such alterations are candidate biomarkers for effectiveness of fibre interventions in cancer prevention.
Methods an design: There are two principal arms to this study: (i) a cross-sectional study (FACT OBS) of 90 subjects recruited from gastroenterology clinics and; (ii) an intervention trial in 40 subjects with an 8 week high fibre intervention. In both studies the principal goal is to investigate a link between fibre intake, SCFA production and global protein acetylation. The primary measure is level of faecal butyrate, which it is hoped will be elevated by moving subjects to a high fibre diet. Fibre intakes will be estimated in the cross-sectional group using the EPIC Food Frequency Questionnaire. Subsidiary measures of the effect of butyrate on colon mucosal function and precancerous phenotype will include measures of apoptosis, apoptotic regulators cell cycle and cell division.
Discussion: This study will provide a new level of mechanistic data on alterations in the functional proteome in response to the colon microenvironment which may underwrite the observed cancer preventive effect of fibre. The study may yield novel candidate biomarkers of fibre fermentation and colon mucosal function
Screening synteny blocks in pairwise genome comparisons through integer programming
<p>Abstract</p> <p>Background</p> <p>It is difficult to accurately interpret chromosomal correspondences such as true orthology and paralogy due to significant divergence of genomes from a common ancestor. Analyses are particularly problematic among lineages that have repeatedly experienced whole genome duplication (WGD) events. To compare multiple "subgenomes" derived from genome duplications, we need to relax the traditional requirements of "one-to-one" syntenic matchings of genomic regions in order to reflect "one-to-many" or more generally "many-to-many" matchings. However this relaxation may result in the identification of synteny blocks that are derived from ancient shared WGDs that are not of interest. For many downstream analyses, we need to eliminate weak, low scoring alignments from pairwise genome comparisons. Our goal is to objectively select subset of synteny blocks whose total scores are maximized while respecting the duplication history of the genomes in comparison. We call this "quota-based" screening of synteny blocks in order to appropriately fill a quota of syntenic relationships within one genome or between two genomes having WGD events.</p> <p>Results</p> <p>We have formulated the synteny block screening as an optimization problem known as "Binary Integer Programming" (BIP), which is solved using existing linear programming solvers. The computer program QUOTA-ALIGN performs this task by creating a clear objective function that maximizes the compatible set of synteny blocks under given constraints on overlaps and depths (corresponding to the duplication history in respective genomes). Such a procedure is useful for any pairwise synteny alignments, but is most useful in lineages affected by multiple WGDs, like plants or fish lineages. For example, there should be a 1:2 ploidy relationship between genome A and B if genome B had an independent WGD subsequent to the divergence of the two genomes. We show through simulations and real examples using plant genomes in the rosid superorder that the quota-based screening can eliminate ambiguous synteny blocks and focus on specific genomic evolutionary events, like the divergence of lineages (in cross-species comparisons) and the most recent WGD (in self comparisons).</p> <p>Conclusions</p> <p>The QUOTA-ALIGN algorithm screens a set of synteny blocks to retain only those compatible with a user specified ploidy relationship between two genomes. These blocks, in turn, may be used for additional downstream analyses such as identifying true orthologous regions in interspecific comparisons. There are two major contributions of QUOTA-ALIGN: 1) reducing the block screening task to a BIP problem, which is novel; 2) providing an efficient software pipeline starting from all-against-all BLAST to the screened synteny blocks with dot plot visualizations. Python codes and full documentations are publicly available <url>http://github.com/tanghaibao/quota-alignment</url>. QUOTA-ALIGN program is also integrated as a major component in SynMap <url>http://genomevolution.com/CoGe/SynMap.pl</url>, offering easier access to thousands of genomes for non-programmers.</p
Clinical and pathological features of BRCA1 associated carcinomas in a hospital-based sample of Dutch breast cancer patients
Thus far, studies investigating the differences in tumour characteristics between breast cancer in BRCA1-carriers and other patients, have focused on highly selected groups of patients, potentially limiting the conclusions that can be drawn. Previously, we had identified 10 patients with BRCA1 germline mutations in a hospital-based series of 642 breast cancer patients not selected for age or family history. The aim of this analysis is to investigate the clinical and pathological features of these BRCA1 associated carcinomas as compared to other breast cancers in this representative sample. Tumours from patients with BRCA1 germline mutations (n= 10) were compared to an age-matched sample of other patients (n= 50) from the same cohort. The following characteristics were considered: axillary nodal status and tumour size, histologic parameters (tumour type, histologic grade, mitotic rate, tubule formation, nuclear grade, CIS and lymphangio invasion) and expression of several proteins (oestrogen and progesterone receptors, cyclin D1, p53, HER2/neu, E-cadherin). In BRCA1associated tumours receptors for oestrogen and progesterone were expressed less frequently (respectively P= 0.001 and P= 0.002) than in controls, which is in line with findings from other studies. Other differences were also in accordance with findings from other studies, although not statistically significant. We conclude that the features of BRCA1 associated tumours detected in a hospital-based series of breast cancer patients not selected for family history of age at diagnosis are similar to tumours in cases selected for family history or age at diagnosis. © 2001 Cancer Research Campaign http://www.bjcancer.co
Hybrid Titanium/Biodegradable Polymer Implants with an Hierarchical Pore Structure as a Means to Control Selective Cell Movement
UNLABELLED: In order to improve implant success rate, it is important to enhance their responsiveness to the prevailing conditions following implantation. Uncontrolled movement of inflammatory cells and fibroblasts is one of these in vivo problems and the porosity properties of the implant have a strong effect on these. Here, we describe a hybrid system composed of a macroporous titanium structure filled with a microporous biodegradable polymer. This polymer matrix has a distinct porosity gradient to accommodate different cell types (fibroblasts and epithelial cells). The main clinical application of this system will be the prevention of restenosis due to excessive fibroblast migration and proliferation in the case of tracheal implants. METHODOLOGY/PRINCIPAL FINDINGS: A microbead-based titanium template was filled with a porous Poly (L-lactic acid) (PLLA) body by freeze-extraction method. A distinct porosity difference was obtained between the inner and outer surfaces of the implant as characterized by image analysis and Mercury porosimetry (9.8±2.2 µm vs. 36.7±11.4 µm, p≤0.05). On top, a thin PLLA film was added to optimize the growth of epithelial cells, which was confirmed by using human respiratory epithelial cells. To check the control of fibroblast movement, PKH26 labeled fibroblasts were seeded onto Titanium and Titanium/PLLA implants. The cell movement was quantified by confocal microscopy: in one week cells moved deeper in Ti samples compared to Ti/PLLA. CONCLUSIONS: In vitro experiments showed that this new implant is effective for guiding different kind of cells it will contact upon implantation. Overall, this system would enable spatial and temporal control over cell migration by a gradient ranging from macroporosity to nanoporosity within a tracheal implant. Moreover, mechanical properties will be dependent mainly on the titanium frame. This will make it possible to create a polymeric environment which is suitable for cells without the need to meet mechanical requirements with the polymeric structure
Glucose Depletion in the Airway Surface Liquid Is Essential for Sterility of the Airways
Diabetes mellitus predisposes the host to bacterial infections. Moreover, hyperglycemia has been shown to be an independent risk factor for respiratory infections. The luminal surface of airway epithelia is covered by a thin layer of airway surface liquid (ASL) and is normally sterile despite constant exposure to bacteria. The balance between bacterial growth and killing in the airway determines the outcome of exposure to inhaled or aspirated bacteria: infection or sterility. We hypothesized that restriction of carbon sources –including glucose– in the ASL is required for sterility of the lungs. We found that airway epithelia deplete glucose from the ASL via a novel mechanism involving polarized expression of GLUT-1 and GLUT-10, intracellular glucose phosphorylation, and low relative paracellular glucose permeability in well-differentiated cultures of human airway epithelia and in segments of airway epithelia excised from human tracheas. Moreover, we found that increased glucose concentration in the ASL augments growth of P. aeruginosa in vitro and in the lungs of hyperglycemic ob/ob and db/db mice in vivo. In contrast, hyperglycemia had no effect on intrapulmonary bacterial growth of a P. aeruginosa mutant that is unable to utilize glucose as a carbon source. Our data suggest that depletion of glucose in the airway epithelial surface is a novel mechanism for innate immunity. This mechanism is important for sterility of the airways and has implications in hyperglycemia and conditions that result in disruption of the epithelial barrier in the lung
Meta-analysis of variation suggests that embracing variability improves both replicability and generalizability in preclinical research
The replicability of research results has been a cause of increasing concern to the scientific community. The long-held belief that experimental standardization begets replicability has also been recently challenged, with the observation that the reduction of variability within studies can lead to idiosyncratic, lab-specific results that cannot be replicated. An alternative approach is to, instead, deliberately introduce heterogeneity, known as "heterogenization" of experimental design. Here, we explore a novel perspective in the heterogenization program in a meta-analysis of variability in observed phenotypic outcomes in both control and experimental animal models of ischemic stroke. First, by quantifying interindividual variability across control groups, we illustrate that the amount of heterogeneity in disease state (infarct volume) differs according to methodological approach, for example, in disease induction methods and disease models. We argue that such methods may improve replicability by creating diverse and representative distribution of baseline disease state in the reference group, against which treatment efficacy is assessed. Second, we illustrate how meta-analysis can be used to simultaneously assess efficacy and stability (i.e., mean effect and among-individual variability). We identify treatments that have efficacy and are generalizable to the population level (i.e., low interindividual variability), as well as those where there is high interindividual variability in response; for these, latter treatments translation to a clinical setting may require nuance. We argue that by embracing rather than seeking to minimize variability in phenotypic outcomes, we can motivate the shift toward heterogenization and improve both the replicability and generalizability of preclinical research
In silico pathway reconstruction: Iron-sulfur cluster biogenesis in Saccharomyces cerevisiae
BACKGROUND: Current advances in genomics, proteomics and other areas of molecular biology make the identification and reconstruction of novel pathways an emerging area of great interest. One such class of pathways is involved in the biogenesis of Iron-Sulfur Clusters (ISC). RESULTS: Our goal is the development of a new approach based on the use and combination of mathematical, theoretical and computational methods to identify the topology of a target network. In this approach, mathematical models play a central role for the evaluation of the alternative network structures that arise from literature data-mining, phylogenetic profiling, structural methods, and human curation. As a test case, we reconstruct the topology of the reaction and regulatory network for the mitochondrial ISC biogenesis pathway in S. cerevisiae. Predictions regarding how proteins act in ISC biogenesis are validated by comparison with published experimental results. For example, the predicted role of Arh1 and Yah1 and some of the interactions we predict for Grx5 both matches experimental evidence. A putative role for frataxin in directly regulating mitochondrial iron import is discarded from our analysis, which agrees with also published experimental results. Additionally, we propose a number of experiments for testing other predictions and further improve the identification of the network structure. CONCLUSION: We propose and apply an iterative in silico procedure for predictive reconstruction of the network topology of metabolic pathways. The procedure combines structural bioinformatics tools and mathematical modeling techniques that allow the reconstruction of biochemical networks. Using the Iron Sulfur cluster biogenesis in S. cerevisiae as a test case we indicate how this procedure can be used to analyze and validate the network model against experimental results. Critical evaluation of the obtained results through this procedure allows devising new wet lab experiments to confirm its predictions or provide alternative explanations for further improving the models
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