957 research outputs found

    Correlation of clinical data, anatomical site and disease stage in colorectal cancer

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    Objective: To evaluate the colorectal cancer clinical data with respect to the anatomical location and stage of disease. Design: Retrospective observational study. Setting: Kenyatta National Hospital (KNH), Nairobi, Kenya. Subjects: Two hundred and fifty three tumours were categorised as right colonic (RCC), left colonic (LCC) and rectal (RC) lesions. The distribution of symptoms (rectal bleeding, tenesmus, change in bowel habits, abdominal pain, intestinal obstruction, rectal mass), anaemia, transfusion requirement, and the Dukes\' stages were compared for right colon, left colon and rectal tumours. Results: There were 54 RCC, 59 LCC, 140 RC lesions. Patient delay from onset of symptom(s) to presentation was a mean of 26.6 ± 43, 20 ± 25 and 33.7 ± 42 weeks for right, left and rectal lesions respectively (p = 0.092). The proportion of patients presenting with rectal bleeding was 21%, 44% and 79% for RCC, LCC and RC lesions, respectively. The prevalence of intestinal obstruction was 14.8%, 27.1% and 43.6% in right, left and rectal lesions, respectively. The haemoglobin levels were significantly lower for right sided lesions (p = 0.05 for right colon/rectum pair; p = 0.059 for right colon/ left colon pair). The sites of the lesions had no relationship to the stage of disease at presentation. Conclusion: In patients with colorectal cancer, the duration of symptoms was prolonged irrespective of the anatomical sub-sites. Symptoms were evenly distributed across the anatomical regions except for bleeding and obstruction which predominated in rectal and left colon cancers respectively. This underlines the need for early investigations in patients with rectal bleeding, change of bowel habit, intestinal obstruction and anaemia. East African Medical Journla Vol. 85 (6) 2008: pp. 259-26

    Thermal conductivity measurement of liquids in a microfluidic device

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    A new microfluidic-based approach to measuring liquid thermal conductivity is developed to address the requirement in many practical applications for measurements using small (microlitre) sample size and integration into a compact device. The approach also gives the possibility of high-throughput testing. A resistance heater and temperature sensor are incorporated into a glass microfluidic chip to allow transmission and detection of a planar thermal wave crossing a thin layer of the sample. The device is designed so that heat transfer is locally one-dimensional during a short initial time period. This allows the detected temperature transient to be separated into two distinct components: a short-time, purely one-dimensional part from which sample thermal conductivity can be determined and a remaining long-time part containing the effects of three-dimensionality and of the finite size of surrounding thermal reservoirs. Identification of the one-dimensional component yields a steady temperature difference from which sample thermal conductivity can be determined. Calibration is required to give correct representation of changing heater resistance, system layer thicknesses and solid material thermal conductivities with temperature. In this preliminary study, methanol/water mixtures are measured at atmospheric pressure over the temperature range 30–50°C. The results show that the device has produced a measurement accuracy of within 2.5% over the range of thermal conductivity and temperature of the tests. A relation between measurement uncertainty and the geometric and thermal properties of the system is derived and this is used to identify ways that error could be further reduced

    TeV Scale Implications of Non Commutative Space time in Laboratory Frame with Polarized Beams

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    We analyze e+eγγe^{+}e^{-}\rightarrow \gamma\gamma, eγeγe^{-}\gamma \rightarrow e^{-}\gamma and γγe+e\gamma\gamma \rightarrow e^{+}e^{-} processes within the Seiberg-Witten expanded noncommutative scenario using polarized beams. With unpolarized beams the leading order effects of non commutativity starts from second order in non commutative(NC) parameter i.e. O(Θ2)O(\Theta^2), while with polarized beams these corrections appear at first order (O(Θ)O(\Theta)) in cross section. The corrections in Compton case can probe the magnetic component(ΘB\vec{\Theta}_B) while in Pair production and Pair annihilation probe the electric component(ΘE\vec{\Theta}_E) of NC parameter. We include the effects of earth rotation in our analysis. This study is done by investigating the effects of non commutativity on different time averaged cross section observables. The results which also depends on the position of the collider, can provide clear and distinct signatures of the model testable at the International Linear Collider(ILC).Comment: 22 pages, 19 figures, new comments and references added, few typos corrected, Published in JHE

    An Integrated Model of Multiple-Condition ChIP-Seq Data Reveals Predeterminants of Cdx2 Binding

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    Regulatory proteins can bind to different sets of genomic targets in various cell types or conditions. To reliably characterize such condition-specific regulatory binding we introduce MultiGPS, an integrated machine learning approach for the analysis of multiple related ChIP-seq experiments. MultiGPS is based on a generalized Expectation Maximization framework that shares information across multiple experiments for binding event discovery. We demonstrate that our framework enables the simultaneous modeling of sparse condition-specific binding changes, sequence dependence, and replicate-specific noise sources. MultiGPS encourages consistency in reported binding event locations across multiple-condition ChIP-seq datasets and provides accurate estimation of ChIP enrichment levels at each event. MultiGPS's multi-experiment modeling approach thus provides a reliable platform for detecting differential binding enrichment across experimental conditions. We demonstrate the advantages of MultiGPS with an analysis of Cdx2 binding in three distinct developmental contexts. By accurately characterizing condition-specific Cdx2 binding, MultiGPS enables novel insight into the mechanistic basis of Cdx2 site selectivity. Specifically, the condition-specific Cdx2 sites characterized by MultiGPS are highly associated with pre-existing genomic context, suggesting that such sites are pre-determined by cell-specific regulatory architecture. However, MultiGPS-defined condition-independent sites are not predicted by pre-existing regulatory signals, suggesting that Cdx2 can bind to a subset of locations regardless of genomic environment. A summary of this paper appears in the proceedings of the RECOMB 2014 conference, April 2–5.National Science Foundation (U.S.) (Graduate Research Fellowship under Grant 0645960)National Institutes of Health (U.S.) (grant P01 NS055923)Pennsylvania State University. Center for Eukaryotic Gene Regulatio

    Genetic Architecture of Highly Complex Chemical Resistance Traits across Four Yeast Strains

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    Many questions about the genetic basis of complex traits remain unanswered. This is in part due to the low statistical power of traditional genetic mapping studies. We used a statistically powerful approach, extreme QTL mapping (X-QTL), to identify the genetic basis of resistance to 13 chemicals in all 6 pairwise crosses of four ecologically and genetically diverse yeast strains, and we detected a total of more than 800 loci. We found that the number of loci detected in each experiment was primarily a function of the trait (explaining 46% of the variance) rather than the cross (11%), suggesting that the level of genetic complexity is a consistent property of a trait across different genetic backgrounds. Further, we observed that most loci had trait-specific effects, although a small number of loci with effects in many conditions were identified. We used the patterns of resistance and susceptibility alleles in the four parent strains to make inferences about the allele frequency spectrum of functional variants. We also observed evidence of more complex allelic series at a number of loci, as well as strain-specific signatures of selection. These results improve our understanding of complex traits in yeast and have implications for study design in other organisms

    Using Expression and Genotype to Predict Drug Response in Yeast

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    Personalized, or genomic, medicine entails tailoring pharmacological therapies according to individual genetic variation at genomic loci encoding proteins in drug-response pathways. It has been previously shown that steady-state mRNA expression can be used to predict the drug response (i.e., sensitivity or resistance) of non-genotyped mammalian cancer cell lines to chemotherapeutic agents. In a real-world setting, clinicians would have access to both steady-state expression levels of patient tissue(s) and a patient's genotypic profile, and yet the predictive power of transcripts versus markers is not well understood. We have previously shown that a collection of genotyped and expression-profiled yeast strains can provide a model for personalized medicine. Here we compare the predictive power of 6,229 steady-state mRNA transcript levels and 2,894 genotyped markers using a pattern recognition algorithm. We were able to predict with over 70% accuracy the drug sensitivity of 104 individual genotyped yeast strains derived from a cross between a laboratory strain and a wild isolate. We observe that, independently of drug mechanism of action, both transcripts and markers can accurately predict drug response. Marker-based prediction is usually more accurate than transcript-based prediction, likely reflecting the genetic determination of gene expression in this cross

    New Abundant Microbial Groups in Aquatic Hypersaline Environments

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    We describe the microbiota of two hypersaline saltern ponds, one of intermediate salinity (19%) and a NaCl saturated crystallizer pond (37%) using pyrosequencing. The analyses of these metagenomes (nearly 784 Mb) reaffirmed the vast dominance of Haloquadratum walsbyi but also revealed novel, abundant and previously unsuspected microbial groups. We describe for the first time, a group of low GC Actinobacteria, related to freshwater Actinobacteria, abundant in low and intermediate salinities. Metagenomic assembly revealed three new abundant microbes: a low-GC euryarchaeon with the lowest GC content described for any euryarchaeon, a high-GC euryarchaeon and a gammaproteobacterium related to Alkalilimnicola and Nitrococcus. Multiple displacement amplification and sequencing of the genome from a single archaeal cell of the new low GC euryarchaeon suggest a photoheterotrophic and polysaccharide-degrading lifestyle and its relatedness to the recently described lineage of Nanohaloarchaea. These discoveries reveal the combined power of an unbiased metagenomic and single cell genomic approach
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