Intratumoral budding as a potential parameter of tumor progression in mismatch repair-proficient and mismatch repair-deficient colorectal cancer patients

In colorectal cancer, tumor budding at the invasive front (peritumoral budding) is an established prognostic parameter and decreased in mismatch repair-deficient tumors. In contrast, the clinical relevance of tumor budding within the tumor center (intratumoral budding) is not yet known. The aim of the study was to determine the correlation of intratumoral budding with peritumoral budding and mismatch repair status and the prognostic impact of intratumoral budding using 2 independent patient cohorts. Following pancytokeratin staining of whole-tissue sections and multiple-punch tissue microarrays, 2 independent cohorts (group 1: n = 289; group 2: n = 222) with known mismatch repair status were investigated for intratumoral budding and peritumoral budding. In group 1, intratumoral budding was strongly correlated to peritumoral budding (r = 0.64; P < .001) and less frequent in mismatch repair-deficient versus mismatch repair-proficient cases (P = .177). Sensitivity and specificity for lymph node positivity were 72.7% and 72.1%. In mismatch repair-proficient cancers, high-grade intratumoral budding was associated with right-sided location (P = .024), advanced T stage (P = .001) and N stage pN (P < .001), vascular invasion (P = .041), infiltrating tumor margin (P = .003), and shorter survival time (P = .014). In mismatch repair-deficient cancers, high intratumoral budding was linked to higher tumor grade (P = .004), vascular invasion (P = .009), infiltrating tumor margin (P = .005), and more unfavorable survival time (P = .09). These associations were confirmed in group 2. High-grade intratumoral budding was a poor prognostic factor in univariate (P < .001) and multivariable analyses (P = .019) adjusting for T stage, N stage distant metastasis, and adjuvant therapy. These preliminary results on 511 patients show that intratumoral budding is an independent prognostic factor, supporting the future investigation of intratumoral budding in larger series of both preoperative and postoperative rectal and colon cancer specimens.

On Ribosome Load, Codon Bias and Protein Abundance

Different codons encoding the same amino acid are not used equally in protein-coding sequences. In bacteria, there is a bias towards codons with high translation rates. This bias is most pronounced in highly expressed proteins, but a recent study of synthetic GFP-coding sequences did not find a correlation between codon usage and GFP expression, suggesting that such correlation in natural sequences is not a simple property of translational mechanisms. Here, we investigate the effect of evolutionary forces on codon usage. The relation between codon bias and protein abundance is quantitatively analyzed based on the hypothesis that codon bias evolved to ensure the efficient usage of ribosomes, a precious commodity for fast growing cells. An explicit fitness landscape is formulated based on bacterial growth laws to relate protein abundance and ribosomal load. The model leads to a quantitative relation between codon bias and protein abundance, which accounts for a substantial part of the observed bias for E. coli. Moreover, by providing an evolutionary link, the ribosome load model resolves the apparent conflict between the observed relation of protein abundance and codon bias in natural sequences and the lack of such dependence in a synthetic gfp library. Finally, we show that the relation between codon usage and protein abundance can be used to predict protein abundance from genomic sequence data alone without adjustable parameters.

On Ribosome Load, Codon Bias and Protein Abundance

Different codons encoding the same amino acid are not used equally in protein-coding sequences. In bacteria, there is a bias towards codons with high translation rates. This bias is most pronounced in highly expressed proteins, but a recent study of synthetic GFP-coding sequences did not find a correlation between codon usage and GFP expression, suggesting that such correlation in natural sequences is not a simple property of translational mechanisms. Here, we investigate the effect of evolutionary forces on codon usage. The relation between codon bias and protein abundance is quantitatively analyzed based on the hypothesis that codon bias evolved to ensure the efficient usage of ribosomes, a precious commodity for fast growing cells. An explicit fitness landscape is formulated based on bacterial growth laws to relate protein abundance and ribosomal load. The model leads to a quantitative relation between codon bias and protein abundance, which accounts for a substantial part of the observed bias for E. coli. Moreover, by providing an evolutionary link, the ribosome load model resolves the apparent conflict between the observed relation of protein abundance and codon bias in natural sequences and the lack of such dependence in a synthetic gfp library. Finally, we show that the relation between codon usage and protein abundance can be used to predict protein abundance from genomic sequence data alone without adjustable parameters.

3D Computerized Occlusion Rating of Embolized Experimental Aneurysms Using Noninvasive 1.5T MR Imaging

For embolized cerebral aneurysms, the initial occlusion rate is the most powerful parameter to predict aneurysm rerupture and recanalization. However, the occlusion rate is only estimated subjectively in clinical routine. To minimize subjective bias, computer occlusion-rating (COR) was successfully validated for 2D images. To minimize the remaining inaccuracy of 2D-COR, COR was applied to 1.5T 3D MR imaging.

Planetary Gear Modal Vibration Experiments and Correlation against Lumped-Parameter and Finite Element Models

Experimental modal analysis techniques are applied to characterize the planar dynamic behavior of two spur planetary gears. Rotational and translational vibrations of the sun gear, carrier, and planet gears are measured. Experimentally obtained natural frequencies, mode shapes, and dynamic response are compared to the results from lumped-parameter and finite element models. Two qualitatively different classes of mode shapes in distinct frequency ranges are observed in the experiments and confirmed by the lumped-parameter model, which considers the accessory shafts and fixtures in the system to capture all of the natural frequencies and modes. The finite element model estimates the high-frequency modes that have significant tooth mesh deflection without considering the shafts and fixtures. The lumped-parameter and finite element models accurately predict the natural frequencies and modal properties established by experimentation. Rotational, translational, and planet mode types presented in published mathematical studies are confirmed experimentally. The number and types of modes in the low-frequency and high-frequency bands depend on the degrees of freedom in the central members and planet gears, respectively. The accuracy of natural frequency prediction is improved when the planet bearings have differing stiffnesses in the tangential and radial directions, consistent with the bearing load direction. (C) 2012 Elsevier Ltd. All rights reserved.

Testing the allegiance bias hypothesis: a meta-analysis

This meta-analysis investigated whether the association between researcher allegiance (RA) and the relative effect of two psychotherapies can be explained through the methodological weaknesses of the treatment comparisons. Seventy-nine comparisons of psychotherapies for depression or posttraumatic stress disorder (PTSD) were included. Methodological quality (MQ) was investigated as both a moderator and a mediator of the RA-outcome association. MQ included balanced nonspecific factors, balanced specific factors, conceptual quality, patients-per-therapist ratio, randomization to conditions and outcome assessment. The RA-outcome association was stronger when the MQ was low, suggesting a buffering effect of MQ. In addition, differences in the conceptual quality of treatments mediated the effect of RA on outcome. The results support the view that RA acts as a bias in treatment comparisons.

Impact of random and systematic recall errors and selection bias in case--control studies on mobile phone use and brain tumors in adolescents (CEFALO study)

Whether the use of mobile phones is a risk factor for brain tumors in adolescents is currently being studied. Case--control studies investigating this possible relationship are prone to recall error and selection bias. We assessed the potential impact of random and systematic recall error and selection bias on odds ratios (ORs) by performing simulations based on real data from an ongoing case--control study of mobile phones and brain tumor risk in children and adolescents (CEFALO study). Simulations were conducted for two mobile phone exposure categories: regular and heavy use. Our choice of levels of recall error was guided by a validation study that compared objective network operator data with the self-reported amount of mobile phone use in CEFALO. In our validation study, cases overestimated their number of calls by 9% on average and controls by 34%. Cases also overestimated their duration of calls by 52% on average and controls by 163%. The participation rates in CEFALO were 83% for cases and 71% for controls. In a variety of scenarios, the combined impact of recall error and selection bias on the estimated ORs was complex. These simulations are useful for the interpretation of previous case-control studies on brain tumor and mobile phone use in adults as well as for the interpretation of future studies on adolescents.

The GABRIEL Advanced Surveys: study design, participation and evaluation of bias

Exposure to farming environments has been shown to protect substantially against asthma and atopic disease across Europe and in other parts of the world. The GABRIEL Advanced Surveys (GABRIELA) were conducted to determine factors in farming environments which are fundamental to protecting against asthma and atopic disease. The GABRIEL Advanced Surveys have a multi-phase stratified design. In a first-screening phase, a comprehensive population-based survey was conducted to assess the prevalence of exposure to farming environments and of asthma and atopic diseases (n = 103,219). The second phase was designed to ascertain detailed exposure to farming environments and to collect biomaterial and environmental samples in a stratified random sample of phase 1 participants (n = 15,255). A third phase was carried out in a further stratified sample only in Bavaria, southern Germany, aiming at in-depth respiratory disease and exposure assessment including extensive environmental sampling (n = 895). Participation rates in phase 1 were around 60% but only about half of the participating study population consented to further study modules in phase 2. We found that consenting behaviour was related to familial allergies, high parental education, wheeze, doctor diagnosed asthma and rhinoconjunctivitis, and to a lesser extent to exposure to farming environments. The association of exposure to farm environments with asthma or rhinoconjunctivitis was not biased by participation or consenting behaviour. The GABRIEL Advanced Surveys are one of the largest studies to shed light on the protective 'farm effect' on asthma and atopic disease. Bias with regard to the main study question was able to be ruled out by representativeness and high participation rates in phases 2 and 3. The GABRIEL Advanced Surveys have created extensive collections of questionnaire data, biomaterial and environmental samples promising new insights into this area of research.