Feasibility of a Unitary Quantum Dynamics in the Gowdy T3T^3 Cosmological Model

It has been pointed out that it is impossible to obtain a unitary implementation of the dynamics for the polarized Gowdy $T^{3}$ cosmologies in an otherwise satisfactory, nonperturbative canonical quantization proposed for these spacetimes. By introducing suitable techniques to deal with deparametrized models in cosmology that possess an explicit time dependence (as it is the case for the toroidal Gowdy model), we present in this paper a detailed analysis about the roots of this failure of unitarity. We investigate the impediments to a unitary implementation of the evolution by considering modifications to the dynamics. These modifications may be regarded as perturbations. We show in a precise manner why and where unitary implementability fails in our system, and prove that the obstructions are extremely sensitive to modifications in the Hamiltonian that dictates the time evolution of the symmetry-reduced model. We are able to characterize to a certain extent how far the model is from unitarity. Moreover, we demonstrate that the dynamics can actually be approximated as much as one wants by means of unitary transformations.Comment: 12 pages, version accepted for publication in Physical Review

Sequencing Structural Variants in Cancer for Precision Therapeutics.

The identification of mutations that guide therapy selection for patients with cancer is now routine in many clinical centres. The majority of assays used for solid tumour profiling use DNA sequencing to interrogate somatic point mutations because they are relatively easy to identify and interpret. Many cancers, however, including high-grade serous ovarian, oesophageal, and small-cell lung cancer, are driven by somatic structural variants that are not measured by these assays. Therefore, there is currently an unmet need for clinical assays that can cheaply and rapidly profile structural variants in solid tumours. In this review we survey the landscape of 'actionable' structural variants in cancer and identify promising detection strategies based on massively-parallel sequencing.This work was supported by Cancer Research UK [grant numbers A15973, A15601: 454 G.M, J.D.B], VUmc Cancer Center Amsterdam [VUmc-CCA: BY] and the Dutch 455 Cancer Society [VU 2015-7882: BY].This is the author accepted manuscript. The final version is available from Cell/Elsevier via http://dx.doi.org/10.1016/j.tig.2016.07.00

Normalized, Segmented or Called aCGH Data?

Array comparative genomic hybridization (aCGH) is a high-throughput lab technique to measure genome-wide chromosomal copy numbers. Data from aCGH experiments require extensive pre-processing, which consists of three steps: normalization, segmentation and calling. Each of these pre-processing steps yields a different data set: normalized data, segmented data, and called data. Publications using aCGH base their findings on data from all stages of the pre-processing. Hence, there is no consensus on which should be used for further down-stream analysis. This consensus is however important for correct reporting of findings, and comparison of results from different studies. We discuss several issues that should be taken into account when deciding on which data are to be used. We express the believe that called data are best used, but would welcome opposing views

Transcriptomics reveals extensive inducible biotransformation in the soil-dwelling invertebrate Folsomia candida exposed to phenanthrene

Background: Polycyclic aromatic hydrocarbons are common pollutants in soil, have negative effects on soil ecosystems, and are potentially carcinogenic. The Springtail (Collembola) Folsomia candida is often used as an indicator species for soil toxicity. Here we report a toxicogenomic study that translates the ecological effects of the polycyclic aromatic hydrocarbon phenanthrene in soil to the early transcriptomic responses in Folsomia candida. Results: Microarrays wereused to examine two different exposure concentrations of phenanthrene, namely the EC10 (24.95 mg kg-1 soil) and EC50 (45.80 mg kg-1 soil) on reproduction of this springtail, which evoked 405 and 251 differentially expressed transcripts, respectively. Fifty transcripts were differential in response to either concentration. Many transcripts encoding xenobiotic detoxification and biotransformation enzymes (phases I, II, and III) were upregulated in response to either concentration. Furthermore, indications of general and oxidative stress were found in response to phenanthrene. Chitin metabolism appeared to be disrupted particularly at the low concentration, and protein translation appeared suppressed at the high concentration of phenanthrene; most likely in order to reallocate energy budgets for the detoxification process. Finally, an immune response was evoked especially in response to the high effect concentration, which was also described in a previous transcriptomic study using the same effect concentration (EC50) of cadmium. Conclusion: Our study provides new insights in the molecular mode of action of the important polluting class of polycyclic aromatic hydrocarbons in soil animals. Furthermore, we present a fast, sensitive, and specific soil toxicity test which enhances traditional tests and may help to improve current environmental risk assessments and monitoring of potentially polluted sites. © 2009 Nota et al; licensee BioMed Central Ltd

BAC to the future! or oligonucleotides: a perspective for micro array comparative genomic hybridization (array CGH)

The array CGH technique (Array Comparative Genome Hybridization) has been developed to detect chromosomal copy number changes on a genome-wide and/or high-resolution scale. It is used in human genetics and oncology, with great promise for clinical application. Until recently primarily PCR amplified bacterial artificial chromosomes (BACs) or cDNAs have been spotted as elements on the array. The large-scale DNA isolations or PCR amplifications of the large-insert clones necessary for manufacturing the arrays are elaborate and time-consuming. Lack of a high-resolution highly sensitive (commercial) alternative has undoubtedly hindered the implementation of array CGH in research and diagnostics. Recently, synthetic oligonucleotides as arrayed elements have been introduced as an alternative substrate for array CGH, both by academic institutions as well as by commercial providers. Oligonucleotide libraries or ready-made arrays can be bought off-the-shelf saving considerable time and efforts. For RNA expression profiling, we have seen a gradual transition from in-house printed cDNA-based expression arrays to oligonucleotide arrays and we expect a similar transition for array CGH. This review compares the different platforms and will attempt to shine a light on the ‘BAC to the future’ of the array CGH technique

Decoy receptor 1 (DCR1) promoter hypermethylation and response to irinotecan in metastatic colorectal cancer

Diversity in colorectal cancer biology is associated with variable responses to standard chemotherapy. We aimed to identify and validate DNA hypermethylated genes as predictive biomarkers for irinotecan treatment of metastatic CRC patients. Candidate genes were selected from 389 genes involved in DNA Damage Repair by correlation analyses between gene methylation status and drug response in 32 cell lines. A large series of samples (n=818) from two phase III clinical trials was used to evaluate these candidate genes by correlating methylation status to progression-free survival after treatment with first-line single-agent fluorouracil (Capecitabine or 5-fluorouracil) or combination chemotherapy (Capecitabine or 5-fluorouracil plus irinotecan (CAPIRI/FOLFIRI)). In the discovery (n=185) and initial validation set (n=166), patients with methylated Decoy Receptor 1 (DCR1) did not benefit from CAPIRI over Capecitabine treatment (discovery set: HR=1.2 (95%CI 0.7-1.9, p=0.6), validation set: HR=0.9 (95%CI 0.6-1.4, p=0.5)), whereas patients with unmethylated DCR1 did (discovery set: HR=0.4 (95%CI 0.3-0.6, p=0.00001), validation set: HR=0.5 (95%CI 0.3-0.7, p=0.0008)). These results could not be replicated in the external data set (n=467), where a similar effect size was found in patients with methylated and unmethylated DCR1 for FOLFIRI over 5FU treatment (methylated DCR1: HR=0.7 (95%CI 0.5-0.9, p=0.01), unmethylated DCR1: HR=0.8 (95%CI 0.6-1.2, p=0.4)). In conclusion, DCR1 promoter hypermethylation status is a potential predictive biomarker for response to treatment with irinotecan, when combined with capecitabine. This finding could not be replicated in an external validation set, in which irinotecan was combined with 5FU. These results underline the challenge and importance of extensive clinical evaluation of candidate biomarkers in multiple trials

Intensity-based analysis of dual-color gene expression data as an alternative to ratio-based analysis to enhance reproducibility

<p>Abstract</p> <p>Background</p> <p>Ratio-based analysis is the current standard for the analysis of dual-color microarray data. Indeed, this method provides a powerful means to account for potential technical variations such as differences in background signal, spot size and spot concentration. However, current high density dual-color array platforms are of very high quality, and inter-array variance has become much less pronounced. We therefore raised the question whether it is feasible to use an intensity-based analysis rather than ratio-based analysis of dual-color microarray datasets. Furthermore, we compared performance of both ratio- and intensity-based analyses in terms of reproducibility and sensitivity for differential gene expression.</p> <p>Results</p> <p>By analyzing three distinct and technically replicated datasets with either ratio- or intensity-based models, we determined that, when applied to the same dataset, intensity-based analysis of dual-color gene expression experiments yields 1) more reproducible results, and 2) is more sensitive in the detection of differentially expressed genes. These effects were most pronounced in experiments with large biological variation and complex hybridization designs. Furthermore, a power analysis revealed that for direct two-group comparisons above a certain sample size, ratio-based models have higher power, although the difference with intensity-based models is very small.</p> <p>Conclusions</p> <p>Intensity-based analysis of dual-color datasets results in more reproducible results and increased sensitivity in the detection of differential gene expression than the analysis of the same dataset with ratio-based analysis. Complex dual-color setups such as interwoven loop designs benefit most from ignoring the array factor. The applicability of our approach to array platforms other than dual-color needs to be further investigated.</p

Clonal Patterns Between Pouch Neoplasia and Prior Colorectal Neoplasia in Inflammatory Bowel Disease Patients:An Exploratory Cohort Study

Prior colorectal neoplasia is the strongest predictor of pouch neoplasia in inflammatory bowel disease, but the underlying mechanism is unknown. We observed clonality between colorectal and pouch neoplasia in 30% of patients, indicating that most pouch neoplasia develops clonally independent from prior colorectal lesions.</p