Correlation between BRAF mutation and the clinicopathological parameters in papillary thyroid carcinoma with particular reference to follicular variant

Mutation of the BRAF gene is common in thyroid cancer. Follicular variant of papillary thyroid carcinoma is a variant of papillary thyroid carcinoma that has created continuous diagnostic controversies among pathologists. The aims of this study are to (1) investigate whether follicular variant of papillary thyroid carcinoma has a different pattern of BRAF mutation than conventional papillary thyroid carcinoma in a large cohort of patients with typical features of follicular variant of papillary thyroid carcinoma and (2) to study the relationship of clinicopathological features of papillary thyroid carcinomas with BRAF mutation. Tissue blocks from 76 patients with diagnostic features of papillary thyroid carcinomas (40 with conventional type and 36 with follicular variant) were included in the study. From these, DNA was extracted and BRAF V600E mutations were detected by polymerase chain reaction followed by restriction enzyme digestion and sequencing of exon 15. Analysis of the data indicated that BRAF V600E mutation is significantly more common in conventional papillary thyroid carcinoma (58% versus 31%, P = .022). Furthermore, the mutation was often noted in female patients (P = .017), in high-stage cancers (P = .034), and in tumors with mild lymphocytic thyroiditis (P = .006). We concluded that follicular variant of papillary thyroid carcinoma differs from conventional papillary thyroid carcinoma in the rate of BRAF mutation. The results of this study add further information indicating that mutations in BRAF play a role in thyroid cancer development and progression.

Optimizing I/O cost and managing memory for composition vector method based on correlation matrix calculation in bioinformatics

The generation of a correlation matrix for set of genomic sequences is a common requirement in many bioinformatics problems such as phylogenetic analysis. Each sequence may be millions of bases long and there may be thousands of such sequences which we wish to compare, so not all sequences may fit into main memory at the same time. Each sequence needs to be compared with every other sequence, so we will generally need to page some sequences in and out more than once. In order to minimize execution time we need to minimize this I/O. This paper develops an approach for faster and scalable computing of large-size correlation matrices through the maximal exploitation of available memory and reducing the number of I/O operations. The approach is scalable in the sense that the same algorithms can be executed on different computing platforms with different amounts of memory and can be applied to different bioinformatics problems with different correlation matrix sizes. The significant performance improvement of the approach over previous work is demonstrated through benchmark examples.

Co-movements in commodity prices : a note based on network analysis

This article analyses co-movements in a wide group of commodity prices during the time period 1992–2010. Our methodological approach is based on the correlation matrix and the networks inside. Through this approach we are able to summarize global interaction and interdependence, capturing the existing heterogeneity in the degrees of synchronization between commodity prices. Our results produce two main findings: (a) we do not observe a persistent increase in the degree of co-movement of the commodity prices in our time sample, however from mid-2008 to the end of 2009 co-movements almost doubled when compared with the average correlation; (b) we observe three groups of commodities which have exhibited similar price dynamics (metals, oil and grains, and oilseeds) and which have increased their degree of co-movement during the sampled period.

Fully automated, semiautomated, and manual morphometric analysis of corneal subbasal nerve plexus in individuals with and without diabetes

Purpose The aim of the study was to determine the association, agreement, and detection capability of manual, semiautomated, and fully automated methods of corneal nerve fiber length (CNFL) quantification of the human corneal subbasal nerve plexus (SNP). Methods Thirty-three participants with diabetes and 17 healthy controls underwent laser scanning corneal confocal microscopy. Eight central images of the SNP were selected for each participant and analyzed using manual (CCMetrics), semiautomated (NeuronJ), and fully automated (ACCMetrics) software to quantify the CNFL. Results For the entire cohort, mean CNFL values quantified by CCMetrics, NeuronJ, and ACCMetrics were 17.4 ± 4.3 mm/mm2, 16.0 ± 3.9 mm/mm2, and 16.5 ± 3.6 mm/mm2, respectively (P < 0.01). CNFL quantified using CCMetrics was significantly higher than those obtained by NeuronJ and ACCMetrics (P < 0.05). The 3 methods were highly correlated (correlation coefficients 0.87–0.98, P < 0.01). The intraclass correlation coefficients were 0.87 for ACCMetrics versus NeuronJ and 0.86 for ACCMetrics versus CCMetrics. Bland–Altman plots showed good agreement between the manual, semiautomated, and fully automated analyses of CNFL. A small underestimation of CNFL was observed using ACCMetrics with increasing the amount of nerve tissue. All 3 methods were able to detect CNFL depletion in diabetic participants (P < 0.05) and in those with peripheral neuropathy as defined by the Toronto criteria, compared with healthy controls (P < 0.05). Conclusions Automated quantification of CNFL provides comparable neuropathy detection ability to manual and semiautomated methods. Because of its speed, objectivity, and consistency, fully automated analysis of CNFL might be advantageous in studies of diabetic neuropathy.

Polybrominated diphenyl ethers and age: analysis of pooled human blood serum from birth to over 60 years

Polybrominated diphenyl ethers (PBDEs) are considered to be a cost effective and efficient way to reduce flammability therefore reducing harm caused by fires. PBDEs are incorporated into a variety of manufactured products and are found worldwide in biological and environmental samples (e.g. Hites et al. 2004). Unlike other persistent organic pollutants there is limited data on PBDE concentrations by age and/or other population specific factors. Some studies have shown no variation in adult serum PBDE concentrations with age (e.g. Mazdai et al., 2003, Meironyte Guvenius et al., 2003) while Petreas et al. (2003) and Schecter et al. (2005) found results to be suggestive of an age trend in adult data but no statistically significant correlation was found. In addition to the data on adult concentrations there is limited data which investigates the levels of PBDEs in infants and young children. Fangström et al. (2005) showed that in seven year olds there was no difference in PBDE concentration when compared to adult concentrations. While Thomsen et al. (2002, 2005) found the concentration of PBDEs in pooled samples of blood serum from a 0-4 years age group to be higher than other age groups (4 to > 60 years). In addition, a family of four was studied in the U.S. and the concentrations were found to be greatest in the 18-month-old infant followed by the 5 year old child, then the mother and father (Fischer et al., 2006). The objectives of this study were to assess age, gender and regional trends of PBDE concentrations in a representative sample of the Australian population.

Proportionality : a valid alternative to correlation for relative data

Relative abundance data is common in the life sciences, but appreciation that it needs special analysis and interpretation is scarce. Correlation is popular as a statistical measure of pairwise association but should not be used on data that carry only relative information. Using timecourse yeast gene expression data, we show how correlation of relative abundances can lead to conclusions opposite to those drawn from absolute abundances, and that its value changes when different components are included in the analysis. Once all absolute information has been removed, only a subset of those associations will reliably endure in the remaining relative data, specifically, associations where pairs of values behave proportionally across observations. We propose a new statistic φ to describe the strength of proportionality between two variables and demonstrate how it can be straightforwardly used instead of correlation as the basis of familiar analyses and visualization methods.

Different correlation of Sphingosine-1-Phosphate receptor 1 with receptor activator of nuclear factor kappa B ligand and regulatory T cells in rat periapical lesions

Introduction Sphingosine-1-phosphate receptor 1 (S1P1) is crucial for regulation of immunity and bone metabolism. This study aimed to investigate the expression of S1P1 in rat periapical lesions and its relationship with receptor activator of nuclear factor kappa B ligand (RANKL) and regulatory T (Treg) cells. Methods Periapical lesions were induced by pulp exposure in the first lower molars of 55 Wistar rats. Thirty rats were killed on days 0, 7, 14, 21, 28, and 35, and their mandibles were harvested for x-ray imaging, micro–computed tomography scanning, histologic observation, immunohistochemistry, enzyme histochemistry, and double immunofluorescence analysis. The remaining 25 rats were killed on days 0, 14, 21, 28, and 35, and mandibles were harvested for flow cytometry. Results The volume and area of the periapical lesions increased from day 0 to day 21 and then remained comparably stable after day 28. S1P1-positive cells were observed in the inflammatory periapical regions; the number of S1P1-positive cells peaked at day 14 and then decreased from day 21 to day 35. The distribution of S1P1-positive cells was positively correlated with the dynamics of RANKL-positive cells but was negatively correlated with that of Treg cells. Conclusions S1P1 expression was differentially correlated with RANKL and Treg cell infiltration in the periapical lesions and is therefore a contributing factor to the pathogenesis of such lesions.

Performance evaluation of non-thermal plasma on particulate matter, ozone and CO2 correlation for diesel exhaust emission reduction

This study is seeking to investigate the effect of non-thermal plasma technology in the abatement of particulate matter (PM) from the actual diesel exhaust. Ozone (O3) strongly promotes PM oxidation, the main product of which is carbon dioxide (CO2). PM oxidation into the less harmful product (CO2) is the main objective whiles the correlation between PM, O3 and CO2 is considered. A dielectric barrier discharge reactor has been designed with pulsed power technology to produce plasma inside the diesel exhaust. To characterise the system under varied conditions, a range of applied voltages from 11 kVPP to 21kVPP at repetition rates of 2.5, 5, 7.5 and 10 kHz, have been experimentally investigated. The results show that by increasing the applied voltage and repetition rate, higher discharge power and CO2 dissociation can be achieved. The PM removal efficiency of more than 50% has been achieved during the experiments and high concentrations of ozone on the order of a few hundreds of ppm have been observed at high discharge powers. Furthermore, O3, CO2 and PM concentrations at different plasma states have been analysed for time dependence. Based on this analysis, an inverse relationship between ozone concentration and PM removal has been found and the role of ozone in PM removal in plasma treatment of diesel exhaust has been highlighted.

The Driver Behaviour Questionnaire as accident predictor: A methodological re-meta-analysis

Problem The Manchester Driver Behaviour Questionnaire (DBQ) is the most commonly used self-report tool in traffic safety research and applied settings. It has been claimed that the violation factor of this instrument predicts accident involvement, which was supported by a previous meta-analysis. However, that analysis did not test for methodological effects, or include contacting researchers to obtain unpublished results. Method The present study re-analysed studies on prediction of accident involvement from DBQ factors, including lapses, and many unpublished effects. Tests of various types of dissemination bias and common method variance were undertaken. Results Outlier analysis showed that some effects were probably not reliable data, but excluding them did not change the results. For correlations between violations and crashes, tendencies for published effects to be larger than unpublished ones and for effects to decrease over time were observed, but were not significant. Also, analysis using the proxy of the mean of accidents in studies indicated that studies where effects for violations are unknown have smaller effect sizes. These differences indicate dissemination bias. Studies using self-reported accidents as dependent variables had much larger effects than those using recorded accident data. Also, zero-order correlations were larger than partial correlations that controlled for exposure. Similarly, violations/accidents effects were strong only when there was also a strong correlation between accidents and exposure. Overall, the true effect is probably very close to zero (r<.07) for violations versus traffic accident involvement, depending upon which systematic tendencies in the data are controlled for. Conclusions: Methodological factors and dissemination bias have inflated the mean effect size of the DBQ in the published literature. Strong evidence of various artefactual effects is apparent. Practical Applications A greater level of care should be taken if the DBQ continues to be used in traffic safety research. Also, validation of self-reports should be more comprehensive in the future, taking into account the possibility of common method variance.

Electromyography and sonomyography analysis of the tibialis anterior: a cross sectional study

Background Foot dorsiflexion plays an essential role in both controlling balance and human gait. Electromyography (EMG) and sonomyography (SMG) can provide information on several aspects of muscle function. The aim was to establish the relationship between the EMG and SMG variables during isotonic contractions of foot dorsiflexors. Methods Twenty-seven healthy young adults performed the foot dorsiflexion test on a device designed ad hoc. EMG variables were maximum peak and area under the curve. Muscular architecture variables were muscle thickness and pennation angle. Descriptive statistical analysis, inferential analysis and a multivariate linear regression model were carried out. The confidence level was established with a statistically significant p-value of less than 0.05. Results The correlation between EMG variables and SMG variables was r = 0.462 (p < 0.05). The linear regression model to the dependent variable “peak normalized tibialis anterior (TA)” from the independent variables “pennation angle and thickness”, was significant (p = 0.002) with an explained variance of R2 = 0.693 and SEE = 0.16. Conclusions There is a significant relationship and degree of contribution between EMG and SMG variables during isotonic contractions of the TA muscle. Our results suggest that EMG and SMG can be feasible tools for monitoring and assessment of foot dorsiflexors. TA muscle parameterization and assessment is relevant in order to know that increased strength accelerates the recovery of lower limb injuries.

Correlation between architectural variables and torque in the erector spinae muscle during maximal isometric contraction

This study analysed whether a significant relationship exists between the torque and muscle thickness and pennation angle of the erector spinae muscle during a maximal isometric lumbar extension with the lumbar spine in neutral position. This was a cross-sectional study in which 46 healthy adults performed three repetitions for 5 s of maximal isometric lumbar extension with rests of 90 s. During the lumbar extensions, bilateral ultrasound images of the erector spinae muscle (to measure pennation angle and muscle thickness) and torque were acquired. Reliability test analysis calculating the internal consistency (Cronbach's alpha) of the measure, correlation between pennation angle, muscle thickness and torque extensions were examined. Through a linear regression the contribution of each independent variable (muscle thickness and pennation angle) to the variation of the dependent variable (torque) was calculated. The results of the reliability test were: 0.976–0.979 (pennation angle), 0.980–0.980 (muscle thickness) and 0.994 (torque). The results show that pennation angle and muscle thickness were significantly related to each other with a range between 0.295 and 0.762. In addition, multiple regression analysis showed that the two variables considered in this study explained 68% of the variance in the torque. Pennation angle and muscle thickness have a moderate impact on the variance exerted on the torque during a maximal isometric lumbar extension with the lumbar spine in neutral position.

Tensor-based analysis of genetic influences on brain integrity using DTI in 100 twins

Information from the full diffusion tensor (DT) was used to compute voxel-wise genetic contributions to brain fiber microstructure. First, we designed a new multivariate intraclass correlation formula in the log-Euclidean framework. We then analyzed used the full multivariate structure of the tensor in a multivariate version of a voxel-wise maximum-likelihood structural equation model (SEM) that computes the variance contributions in the DTs from genetic (A), common environmental (C) and unique environmental (E) factors. Our algorithm was tested on DT images from 25 identical and 25 fraternal twin pairs. After linear and fluid registration to a mean template, we computed the intraclass correlation and Falconer's heritability statistic for several scalar DT-derived measures and for the full multivariate tensors. Covariance matrices were found from the DTs, and inputted into SEM. Analyzing the full DT enhanced the detection of A and C effects. This approach should empower imaging genetics studies that use DTI.

Multivariate variance-components analysis in DTI

Twin studies are a major research direction in imaging genetics, a new field, which combines algorithms from quantitative genetics and neuroimaging to assess genetic effects on the brain. In twin imaging studies, it is common to estimate the intraclass correlation (ICC), which measures the resemblance between twin pairs for a given phenotype. In this paper, we extend the commonly used Pearson correlation to a more appropriate definition, which uses restricted maximum likelihood methods (REML). We computed proportion of phenotypic variance due to additive (A) genetic factors, common (C) and unique (E) environmental factors using a new definition of the variance components in the diffusion tensor-valued signals. We applied our analysis to a dataset of Diffusion Tensor Images (DTI) from 25 identical and 25 fraternal twin pairs. Differences between the REML and Pearson estimators were plotted for different sample sizes, showing that the REML approach avoids severe biases when samples are smaller. Measures of genetic effects were computed for scalar and multivariate diffusion tensor derived measures including the geodesic anisotropy (tGA) and the full diffusion tensors (DT), revealing voxel-wise genetic contributions to brain fiber microstructure.

Morphometric analysis of the thoracic intervertebral foramen osseous anatomy in adolescent idiopathic scoliosis using low dose computerized tomography

Introduction. The dimensions of the thoracic intervertebral foramen in adolescent idiopathic scoliosis (AIS) have not previously been quantified. During posterior approach scoliosis correction surgery pedicle screws may occasionally breach into the foramen. Better understanding of the dimensions of the foramen may be useful in surgical planning. This study describes a reproducible method for measurement of the thoracic foramen in AIS using computerized tomography (CT). Methods. In 23 pre-operative female patients with Lenke 1 type AIS with right side convexity major curves confined to the thoracic spine the foraminal height (FH), foraminal width (FW), pedicle to superior articular process distance (P-SAP) and cross sectional foraminal area (FA) were measured using multiplanar reconstructed CT. Measurements were made at entrance, midpoint and exit of the thoracic foramina from T1/T2 to T11/T12. Results were correlated with potential dependent variables of major curve Cobb Angle measured on X-ray and CT, Age, Weight, Lenke classification subtype, Risser Grade and number of spinal levels in the major curve. Results. The FH, FW, P-SAP and FA dimensions and ratios are all significantly larger on the convexity of the major curve and maximal at or close to the apex. Mean thoracic foraminal dimensions change in a predictable manner relative to position on the major thoracic curve. There was no significant correlation with the measured foraminal dimensions or ratios and the potential dependent variables. The average ratio of convexity to concavity dimensions at the apex foramina for entrance, midpoint and exit respectively are FH (1.50, 1.38, 1.25), FW (1.28, 1.30, 0.98), FA (2.06, 1.84, 1.32), P-SAP (1.61, 1.47, 1.30). Conclusion. Foraminal dimensions of the thoracic spine are significantly affected by AIS. Foraminal dimensions have a predictable convexity to concavity ratio relative to the proximity to the major curve apex. Surgeons should be aware of these anatomical differences during scoliosis correction surgery.

Topological properties and fractal analysis of a recurrence network constructed from fractional Brownian motions

Many studies have shown that we can gain additional information on time series by investigating their accompanying complex networks. In this work, we investigate the fundamental topological and fractal properties of recurrence networks constructed from fractional Brownian motions (FBMs). First, our results indicate that the constructed recurrence networks have exponential degree distributions; the average degree exponent 〈λ〉 increases first and then decreases with the increase of Hurst index H of the associated FBMs; the relationship between H and 〈λ〉 can be represented by a cubic polynomial function. We next focus on the motif rank distribution of recurrence networks, so that we can better understand networks at the local structure level. We find the interesting superfamily phenomenon, i.e., the recurrence networks with the same motif rank pattern being grouped into two superfamilies. Last, we numerically analyze the fractal and multifractal properties of recurrence networks. We find that the average fractal dimension 〈dB〉 of recurrence networks decreases with the Hurst index H of the associated FBMs, and their dependence approximately satisfies the linear formula 〈dB〉≈2-H, which means that the fractal dimension of the associated recurrence network is close to that of the graph of the FBM. Moreover, our numerical results of multifractal analysis show that the multifractality exists in these recurrence networks, and the multifractality of these networks becomes stronger at first and then weaker when the Hurst index of the associated time series becomes larger from 0.4 to 0.95. In particular, the recurrence network with the Hurst index H=0.5 possesses the strongest multifractality. In addition, the dependence relationships of the average information dimension 〈D(1)〉 and the average correlation dimension 〈D(2)〉 on the Hurst index H can also be fitted well with linear functions. Our results strongly suggest that the recurrence network inherits the basic characteristic and the fractal nature of the associated FBM series.