The US stock market leads the Federal funds rate and Treasury bond yields

Using a recently introduced method to quantify the time varying lead-lag dependencies between pairs of economic time series (the thermal optimal path method), we test two fundamental tenets of the theory of fixed income: (i) the stock market variations and the yield changes should be anti-correlated; (ii) the change in central bank rates, as a proxy of the monetary policy of the central bank, should be a predictor of the future stock market direction. Using both monthly and weekly data, we found very similar lead-lag dependence between the S&P500 stock market index and the yields of bonds inside two groups: bond yields of short-term maturities (Federal funds rate (FFR), 3M, 6M, 1Y, 2Y, and 3Y) and bond yields of long-term maturities (5Y, 7Y, 10Y, and 20Y). In all cases, we observe the opposite of (i) and (ii). First, the stock market and yields move in the same direction. Second, the stock market leads the yields, including and especially the FFR. Moreover, we find that the short-term yields in the first group lead the long-term yields in the second group before the financial crisis that started mid-2007 and the inverse relationship holds afterwards. These results suggest that the Federal Reserve is increasingly mindful of the stock market behavior, seen at key to the recovery and health of the economy. Long-term investors seem also to have been more reactive and mindful of the signals provided by the financial stock markets than the Federal Reserve itself after the start of the financial crisis. The lead of the S&P500 stock market index over the bond yields of all maturities is confirmed by the traditional lagged cross-correlation analysis.Comment: 12 pages, 7 figures, 1 tabl

Application of kernel functions for accurate similarity search in large chemical databases

Background Similaritysearch in chemical structure databases is an important problem with many applications in chemical genomics, drug design, and efficient chemical probe screening among others. It is widely believed that structure based methods provide an efficient way to do the query. Recently various graph kernel functions have been designed to capture the intrinsic similarity of graphs. Though successful in constructing accurate predictive and classification models, graph kernel functions can not be applied to large chemical compound database due to the high computational complexity and the difficulties in indexing similarity search for large databases. Results To bridge graph kernel function and similarity search in chemical databases, we applied a novel kernel-based similarity measurement, developed in our team, to measure similarity of graph represented chemicals. In our method, we utilize a hash table to support new graph kernel function definition, efficient storage and fast search. We have applied our method, named G-hash, to large chemical databases. Our results show that the G-hash method achieves state-of-the-art performance for k-nearest neighbor (k-NN) classification. Moreover, the similarity measurement and the index structure is scalable to large chemical databases with smaller indexing size, and faster query processing time as compared to state-of-the-art indexing methods such as Daylight fingerprints, C-tree and GraphGrep. Conclusions Efficient similarity query processing method for large chemical databases is challenging since we need to balance running time efficiency and similarity search accuracy. Our previous similarity search method, G-hash, provides a new way to perform similarity search in chemical databases. Experimental study validates the utility of G-hash in chemical databases

Markers for the identification of late breast cancer recurrence

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited

Genetic and epigenetic silencing of the beclin 1 gene in sporadic breast tumors

<p>Abstract</p> <p>Background</p> <p>Beclin 1, an important autophagy-related protein in human cells, is involved in cell death and cell survival. <it>Beclin 1 </it>mapped to human chromosome 17q21. It is widely expressed in normal mammary epithelial cells. Although down-regulated expression with mono-allelic deletions of <it>beclin 1 </it>gene was frequently observed in breast tumors, whether there was other regulatory mechanism of <it>beclin 1 </it>was to be investigated. We studied the expression of beclin 1 and explored the possible regulatory mechanisms on its expression in breast tumors.</p> <p>Methods</p> <p>20 pairs of tumors and adjacent normal tissues from patients with sporadic breast invasive ductal cancer (IDCs) were collected. The mRNA expression of <it>beclin 1 </it>was detected by real-time quantitative RT-PCR. Loss of heterozygosity (LOH) was determined by real-time quantitative PCR and microsatellite methods. The protein expression of beclin 1, p53, BRCA1 and BRCA2 was assessed by immunohistochemistry. CpG islands in 5' genomic region of beclin 1 gene were identified using MethylPrimer Program. Sodium bisulfite sequencing was used in examining the methylation status of each CpG island.</p> <p>Results</p> <p>Decreased <it>beclin 1 </it>mRNA expression was detected in 70% of the breast tumors, and the protein levels were co-related to the mRNA levels. Expression of <it>beclin 1 </it>mRNA was demonstrated to be much higher in the BRCA1 positive tumors than that in the BRCA1 negative ones. Loss of heterozygosity was detected in more than 45% of the breast tumors, and a dense cluster of CpG islands was found from the 5' end to the intron 2 of the <it>beclin 1 </it>gene. Methylation analysis showed that the promoter and the intron 2 of beclin 1 were aberrantly methylated in the tumors with decreased expression.</p> <p>Conclusions</p> <p>These data indicated that LOH and aberrant DNA methylation might be the possible reasons of the decreased expression of <it>beclin 1 </it>in the breast tumors. The findings here shed some new light on the regulatory mechanisms of beclin 1 in breast cancer.</p

Cross-Platform Comparison of Microarray-Based Multiple-Class Prediction

High-throughput microarray technology has been widely applied in biological and medical decision-making research during the past decade. However, the diversity of platforms has made it a challenge to re-use and/or integrate datasets generated in different experiments or labs for constructing array-based diagnostic models. Using large toxicogenomics datasets generated using both Affymetrix and Agilent microarray platforms, we carried out a benchmark evaluation of cross-platform consistency in multiple-class prediction using three widely-used machine learning algorithms. After an initial assessment of model performance on different platforms, we evaluated whether predictive signature features selected in one platform could be directly used to train a model in the other platform and whether predictive models trained using data from one platform could predict datasets profiled using the other platform with comparable performance. Our results established that it is possible to successfully apply multiple-class prediction models across different commercial microarray platforms, offering a number of important benefits such as accelerating the possible translation of biomarkers identified with microarrays to clinically-validated assays. However, this investigation focuses on a technical platform comparison and is actually only the beginning of exploring cross-platform consistency. Further studies are needed to confirm the feasibility of microarray-based cross-platform prediction, especially using independent datasets

Ni–Al diffusion barrier layer for integrating ferroelectric capacitors on Si

2005-2006 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Structure of hadron resonances with a nearby zero of the amplitude

We discuss the relation between the analytic structure of the scattering amplitude and the origin of an eigenstate represented by a pole of the amplitude.If the eigenstate is not dynamically generated by the interaction in the channel of interest, the residue of the pole vanishes in the zero coupling limit. Based on the topological nature of the phase of the scattering amplitude, we show that the pole must encounter with the Castillejo-Dalitz-Dyson (CDD) zero in this limit. It is concluded that the dynamical component of the eigenstate is small if a CDD zero exists near the eigenstate pole. We show that the line shape of the resonance is distorted from the Breit-Wigner form as an observable consequence of the nearby CDD zero. Finally, studying the positions of poles and CDD zeros of the KbarN-piSigma amplitude, we discuss the origin of the eigenstates in the Lambda(1405) region.Comment: 7 pages, 3 figures, v2: published versio

The selective Cox-2 inhibitor Celecoxib suppresses angiogenesis and growth of secondary bone tumors: An intravital microscopy study in mice

BACKGROUND: The inhibition of angiogenesis is a promising strategy for the treatment of malignant primary and secondary tumors in addition to established therapies such as surgery, chemotherapy, and radiation. There is strong experimental evidence in primary tumors that Cyclooxygenase-2 (Cox-2) inhibition is a potent mechanism to reduce angiogenesis. For bone metastases which occur in up to 85% of the most frequent malignant primary tumors, the effects of Cox-2 inhibition on angiogenesis and tumor growth remain still unclear. Therefore, the aim of this study was to investigate the effects of Celecoxib, a selective Cox-2 inhibitor, on angiogenesis, microcirculation and growth of secondary bone tumors. METHODS: In 10 male severe combined immunodeficient (SCID) mice, pieces of A549 lung carcinomas were implanted into a newly developed cranial window preparation where the calvaria serves as the site for orthotopic implantation of the tumors. From day 8 after tumor implantation, five animals (Celecoxib) were treated daily with Celecoxib (30 mg/kg body weight, s.c.), and five animals (Control) with the equivalent amount of the CMC-based vehicle. Angiogenesis, microcirculation, and growth of A549 tumors were analyzed by means of intravital microscopy. Apoptosis was quantified using the TUNEL assay. RESULTS: Treatment with Celecoxib reduced both microvessel density and tumor growth. TUNEL reaction showed an increase in apoptotic cell death of tumor cells after treatment with Celecoxib as compared to Controls. CONCLUSION: Celecoxib is a potent inhibitor of tumor growth of secondary bone tumors in vivo which can be explained by its anti-angiogenic and pro-apoptotic effects. The results indicate that a combination of established therapy regimes with Cox-2 inhibition represents a possible application for the treatment of bone metastases