Financialization, crisis and commodity correlation dynamics

Stronger investor interest in commodities may create closer integration with conventional asset markets. We estimate sudden and gradual changes in correlation between stocks, bonds and commodity futures returns driven by observable financial variables and time, using double smooth transition conditional correlation (DSTCC–GARCH) models. Most correlations begin the 1990s near zero but closer integration emerges around the early 2000s and reaches peaks during the recent crisis. Diversification benefits to investors across equity, bond and stock markets were significantly reduced. Increases in VIX and financial traders’ short open interest raise futures returns volatility for many commodities. Higher VIX also increases commodity returns correlation with equity returns for about half the pairs, indicating closer integration.

The correlation between electric field emission phenomenon and Schottky contact reverse bias characteristics in nanostructured systems

Two different morphologies of nanotextured molybdenum oxide were deposited by thermal evaporation. By measuring their field emission (FE) properties, an enhancement factor was extracted. Subsequently, these films were coated with a thin layer of Pt to form Schottky contacts. The current-voltage (I-V) characteristics showed low magnitude reverse breakdown voltages, which we attributed to the localized electric field enhancement. An enhancement factor was obtained from the I-V curves. We will show that the enhancement factor extracted from the I-V curves is in good agreement with the enhancement factor extracted from the FE measurements.

Managing memory and reducing I/O cost for correlation matrix calculation in bioinformatics

The generation of a correlation matrix from a large set of long gene sequences is a common requirement in many bioinformatics problems such as phylogenetic analysis. The generation is not only computationally intensive but also requires significant memory resources as, typically, few gene sequences can be simultaneously stored in primary memory. The standard practice in such computation is to use frequent input/output (I/O) operations. Therefore, minimizing the number of these operations will yield much faster run-times. This paper develops an approach for the faster and scalable computing of large-size correlation matrices through the full use of available memory and a reduced 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 problems with different correlation matrix sizes. The significant performance improvement of the approach over the existing approaches is demonstrated through benchmark examples.

Quantifying spatial structure in experimental observations and agent-based simulations using pair-correlation functions

We define a pair-correlation function that can be used to characterize spatiotemporal patterning in experimental images and snapshots from discrete simulations. Unlike previous pair-correlation functions, the pair-correlation functions developed here depend on the location and size of objects. The pair-correlation function can be used to indicate complete spatial randomness, aggregation or segregation over a range of length scales, and quantifies spatial structures such as the shape, size and distribution of clusters. Comparing pair-correlation data for various experimental and simulation images illustrates their potential use as a summary statistic for calibrating discrete models of various physical processes.

Fractal dimension of dried foods : a correlation between microstructure and porosity

The quality of dried food is affected by a number of factors including quality of raw material, initial microstructure, and drying conditions. The structure of the food materials goes through deformations due to the simultaneous effect of heat and mass transfer during the drying process. Shrinkage and changes in porosity, microstructure and appearance are some of the most remarkable features that directly influence overall product quality. Porosity and microstructure are the important material properties in relation to the quality attributes of dried foods. Fractal dimension (FD) is a quantitative approach of measuring surface, pore characteristics, and microstructural changes [1]. However, in the field of fractal analysis, there is a lack of research in developing relationship between porosity, shrinkage and microstructure of different solid food materials in different drying process and conditions [2-4]. Establishing a correlation between microstructure and porosity through fractal dimension during convective drying is the main objective of this work.

Spectroscopic correlation analysis of NMR-based metabonomics in exercise science

Spectroscopic studies of complex clinical fluids have led to the application of a more holistic approach to their chemical analysis becoming more popular and widely employed. The efficient and effective interpretation of multidimensional spectroscopic data relies on many chemometric techniques and one such group of tools is represented by so-called correlation analysis methods. Typical of these techniques are two-dimensional correlation analysis and statistical total correlation spectroscopy (STOCSY). Whilst the former has largely been applied to optical spectroscopic analysis, STOCSY was developed and has been applied almost exclusively to NMR metabonomic studies. Using a 1H NMR study of human blood plasma, from subjects recovering from exhaustive exercise trials, the basic concepts and applications of these techniques are examined. Typical information from their application to NMR-based metabonomics is presented and their value in aiding interpretation of NMR data obtained from biological systems is illustrated. Major energy metabolites are identified in the NMR spectra and the dynamics of their appearance and removal from plasma during exercise recovery are illustrated and discussed. The complementary nature of two-dimensional correlation analysis and statistical total correlation spectroscopy are highlighted.

Tumour necrosis is an independent prognostic marker in non-small cell lung cancer : correlation with biological variables

Background Tumour necrosis (TN) is recognized to be a consequence of chronic cellular hypoxia. TN and hypoxia correlate with poor prognosis in solid tumours. Methods In a retrospective study the prognostic implications of the extent of TN was evaluated in non-small cell lung cancer (NSCLC) and correlated with clinicopathological variables and expression of epidermal growth factor receptor, Bcl-2, p53 and matrix metalloproteinase-9 (MMP-9). Tissue specimens from 178 surgically resected cases of stage I-IIIA NSCLC with curative intent were studied. The specimens were routinely processed, formalin-fixed and paraffin-embedded. TN was graded as extensive or either limited or absent by two independent observers; disagreements were resolved using a double-headed microscope. The degree of reproducibility was estimated by re-interpreting 40 randomly selected cases after a 4 month interval. Results Reproducibility was attained in 36/40 cases, Kappa score=0.8 P<0.001. TN correlated with T-stage (P=0.001), platelet count (P=0.004) and p53 expression (P=0.031). Near significant associations of TN with N-stage (P=0.063) and MMP-9 expression (P=0.058) were seen. No association was found with angiogenesis (P=0.98). On univariate (P=0.0016) and multivariate analysis (P=0.023) TN was prognostic. Conclusion These results indicate that extensive TN reflects an aggressive tumour phenotype in NSCLC and may improve the predictive power of the TMN staging system. The lack of association between TN and angiogenesis may be important although these variables were not evaluated on serial sections. © 2002 Elsevier Science Ireland Ltd. All rights reserved.

Thromboxane synthase expression and correlation with VEGF and angiogenesis in non-small cell lung cancer

Background Thromboxane synthase (TXS) metabolizes prostaglandin H2 into thromboxanes, which are biologically active on cancer cells. TXS over-expression has been reported in a range of cancers, and associated with angiogenesis and poor outcome. TXS has been identified as a potential therapeutic target in NSCLC. This study examines a link between TXS expression, angiogenesis, and survival in NSCLC. Methods TXS and VEGF metabolite levels were measured in NSCLC serum samples (n=46) by EIA. TXB2 levels were correlated with VEGF. A 204-patient TMA was stained for TXS, VEGF, and CD-31 expression. Expression was correlated with a range of clinical parameters, including overall survival. TXS expression was correlated with VEGF and CD-31. Stable TXS clones were generated and the effect of overexpression on tumor growth and angiogenesis markers was examined in-vitro and in-vivo (xenograft mouse model). Results Serum TXB2 levels were correlated with VEGF (p<0.05). TXS and VEGF were expressed to a varying degree in NSCLC tissue. TXS was associated with VEGF (p<0.0001) and microvessel density (CD-31; p<0.05). TXS and VEGF expression levels were higher in adenocarcinoma (p<0.0001) and female patients (p<0.05). Stable overexpression of TXS increased VEGF secretion in-vitro. While no significant association with patient survival was observed for either TXS or VEGF in our patient cohort, TXS overexpression significantly (p<0.05) increased tumor growth in-vivo. TXS overexpression was also associated with higher levels of VEGF, microvessel density, and reduced apoptosis in xenograft tumors. Conclusion TXS promotes tumor growth in-vivo in NSCLC, an effect which is at least partly mediated through increased tumor angiogenesis.

Distinguishing between mechanisms of cell aggregation using pair-correlation functions

Many cell types form clumps or aggregates when cultured in vitro through a variety of mechanisms including rapid cell proliferation, chemotaxis, or direct cell-to-cell contact. In this paper we develop an agent-based model to explore the formation of aggregates in cultures where cells are initially distributed uniformly, at random, on a two-dimensional substrate. Our model includes unbiased random cell motion, together with two mechanisms which can produce cell aggregates: (i) rapid cell proliferation, and (ii) a biased cell motility mechanism where cells can sense other cells within a finite range, and will tend to move towards areas with higher numbers of cells. We then introduce a pair-correlation function which allows us to quantify aspects of the spatial patterns produced by our agent-based model. In particular, these pair-correlation functions are able to detect differences between domains populated uniformly at random (i.e. at the exclusion complete spatial randomness (ECSR) state) and those where the proliferation and biased motion rules have been employed - even when such differences are not obvious to the naked eye. The pair-correlation function can also detect the emergence of a characteristic inter-aggregate distance which occurs when the biased motion mechanism is dominant, and is not observed when cell proliferation is the main mechanism of aggregate formation. This suggests that applying the pair-correlation function to experimental images of cell aggregates may provide information about the mechanism associated with observed aggregates. As a proof of concept, we perform such analysis for images of cancer cell aggregates, which are known to be associated with rapid proliferation. The results of our analysis are consistent with the predictions of the proliferation-based simulations, which supports the potential usefulness of pair correlation functions for providing insight into the mechanisms of aggregate formation.

Correlation between extent of osteolytic damage and metastatic burden of human breast cancer metastasis in nude mice : real-time PCR quantitation

Orthotopic or intracardiac injection of human breast cancer cell lines into immunocompromised mice allows study of the molecular basis of breast cancer metastasis. We have established a quantitative real-time PCR approach to analyze metastatic spread of human breast cancer cells inoculated into nude mice via these routes. We employed MDA-MB-231 human breast cancer cells genetically tagged with a bacterial β-galactosidase (Lac-Z) retroviral vector, enabling their detection by TaqMan® real-time PCR. PCR detection was linear, specific, more sensitive than conventional PCR, and could be used to directly quantitate metastatic burden in bone and soft organs. Attesting to the sensitivity and specificity of the PCR detection strategy, as few as several hundred metastatic MDA-MB-231 cells were detectable in 100 μm segments of paraffin-embedded lung tissue, and only in samples adjacent to sections that scored positive by histological detection. Moreover, the measured real-time PCR metastatic burden in the bone environment (mouse hind-limbs, n = 48) displayed a high correlation to the degree of osteolytic damage observed by high resolution X-ray analysis (r2 = 0.972). Such a direct linear relationship to tumor burden and bone damage substantiates the so-called 'vicious cycle' hypothesis in which metastatic tumor cells promote the release of factors from the bone which continue to stimulate the tumor cells. The technique provides a useful tool for molecular and cellular analysis of human breast cancer metastasis to bone and soft organs, can easily be extended to other cell/marker/organ systems, and should also find application in preclinical assessment of anti-metastatic modalities.

Binding and degradation of hyaluronan by human breast cancer cell lines expressing different forms of CD44 : correlation with invasive potential

In the present study, we examined a panel of human breast cancer cell lines with regard to their expression of CD44 and ability to bind and degrade hyaluronan. The cell lines expressed varying amounts of different molecular weight forms of CD44 (85-200 kDa) and, in general, those that expressed the greatest amounts of CD44 were the most invasive as judged by in vitro assays. In addition, the ability to bind and degrade hyaluronan was restricted to the cell lines expressing high levels of CD44, and both these functions were blocked by an antibody to CD44 (Hermes-1). Moreover, the rate of [3H]hyaluronan degradation was highly correlated with the amount of CD44 (r = 0.951, P < 0.0001), as well as with the invasive potential of the cells. Scatchard analysis of the [3H]hyaluronan binding of these cells revealed the existence of significant differences in both their binding capacity and their dissociation constant. To determine the source of this deviation, the different molecular weight forms of CD44 were partially separated by gel filtration chromatography. In all cell lines, the 85 kDa form was able to bind hyaluronan, although with different affinities. In contrast, not all of the high molecular weight forms of CD44 had this ability. These results illustrate the diversity of CD44 molecules in invasive tumor cells, and suggest that one of their major functions is to degrade hyaluronan.

Correlation of tumor- and stromal-derived MT1-MMP expression with progression of human ovarian tumors in SCID mice

Human ovarian carcinoma samples were orthotopically implanted into SCID mice to investigate the contribution of matrix metalloproteases (MMPs) to the spread of ovarian tumors. Mice were inoculated with patient tumor samples, and developed ovarian tumors over a 16-week period with metastasis occurring in some mice. Species-specific quantitative RT-PCR was used to identify the source of tumor-associated MMPs. Membrane-type (MT)1-MMP mRNA was significantly increased in high-grade tumors, tumors with evidence of serosal involvement, and tumors in which distant metastases were detected. The increase in MT1-MMP expression was predominantly from the human tumor cells, with a minor contribution from the mouse ovarian stroma. Neither human nor mouse MT2-MMP were correlated with tumor progression and MT3-MMP levels were negligible. While tumor cells did not produce significant amounts of MMP-2 or MMP-9, the presence of tumor was associated with increased levels of MMP-2 expression by mouse ovarian stroma. Stromal-derived MT1-MMP was greater in large tumors and was associated with stromal MMP-2 expression but neither was significantly linked with metastasis. These studies indicate that tumor-derived MT1-MMP, more so than other gelatinolytic MMPs, is strongly linked to aggressive tumor behavior. This orthotopic model of human ovarian carcinoma is appropriate for studying ovarian tumor progression, and will be valuable in the further investigation of the metastatic process.

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.

Quantitative analysis of survivin in colorectal adenocarcinoma : increased expression and correlation with telomerase activity

The aims of the present study are to quantitatively analyze survivin expression, its clinicopathologic roles, and correlation with telomerase activity in a large cohort of patients with colorectal adenocarcinoma. Real-time polymerase chain reaction was used to quantitate expression level of survivin messenger RNA and human telomerase reverse transcriptase messenger RNA (telomerase activity) in 51 patients with colorectal adenocarcinomas. The findings were correlated with the clinicopathologic features of patients, which were prospectively collected into a computerized database. Survivin messenger RNA was expressed in all tumor samples. The level of expression in tumor tissues was increased in comparison with matched nontumor mucosa in the same patient (P = .01). The level of expression of survivin was significantly correlated with the level of human telomerase reverse transcriptase expression (P = .008) and size of the colorectal adenocarcinomas (P = .004). Survival of the patients with colorectal adenocarcinoma was associated with the TNM stages (P = .001) and not with the level of expression of survivin. Thus, survivin activity was altered in colorectal adenocarcinoma. The high prevalence of survivin expression and correlation with telomerase activity are important factors for consideration in gene targeting therapy for colorectal adenocarcinoma.

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.