Strategies used as spectroscopy of financial markets reveal new stylized facts

We propose a new set of stylized facts quantifying the structure of financial markets. The key idea is to study the combined structure of both investment strategies and prices in order to open a qualitatively new level of understanding of financial and economic markets. We study the detailed order flow on the Shenzhen Stock Exchange of China for the whole year of 2003. This enormous dataset allows us to compare (i) a closed national market (A-shares) with an international market (B-shares), (ii) individuals and institutions and (iii) real investors to random strategies with respect to timing that share otherwise all other characteristics. We find that more trading results in smaller net return due to trading frictions. We unveiled quantitative power laws with non-trivial exponents, that quantify the deterioration of performance with frequency and with holding period of the strategies used by investors. Random strategies are found to perform much better than real ones, both for winners and losers. Surprising large arbitrage opportunities exist, especially when using zero-intelligence strategies. This is a diagnostic of possible inefficiencies of these financial markets.Comment: 13 pages including 5 figures and 1 tabl

Predicting residue-wise contact orders in proteins by support vector regression

BACKGROUND: The residue-wise contact order (RWCO) describes the sequence separations between the residues of interest and its contacting residues in a protein sequence. It is a new kind of one-dimensional protein structure that represents the extent of long-range contacts and is considered as a generalization of contact order. Together with secondary structure, accessible surface area, the B factor, and contact number, RWCO provides comprehensive and indispensable important information to reconstructing the protein three-dimensional structure from a set of one-dimensional structural properties. Accurately predicting RWCO values could have many important applications in protein three-dimensional structure prediction and protein folding rate prediction, and give deep insights into protein sequence-structure relationships. RESULTS: We developed a novel approach to predict residue-wise contact order values in proteins based on support vector regression (SVR), starting from primary amino acid sequences. We explored seven different sequence encoding schemes to examine their effects on the prediction performance, including local sequence in the form of PSI-BLAST profiles, local sequence plus amino acid composition, local sequence plus molecular weight, local sequence plus secondary structure predicted by PSIPRED, local sequence plus molecular weight and amino acid composition, local sequence plus molecular weight and predicted secondary structure, and local sequence plus molecular weight, amino acid composition and predicted secondary structure. When using local sequences with multiple sequence alignments in the form of PSI-BLAST profiles, we could predict the RWCO distribution with a Pearson correlation coefficient (CC) between the predicted and observed RWCO values of 0.55, and root mean square error (RMSE) of 0.82, based on a well-defined dataset with 680 protein sequences. Moreover, by incorporating global features such as molecular weight and amino acid composition we could further improve the prediction performance with the CC to 0.57 and an RMSE of 0.79. In addition, combining the predicted secondary structure by PSIPRED was found to significantly improve the prediction performance and could yield the best prediction accuracy with a CC of 0.60 and RMSE of 0.78, which provided at least comparable performance compared with the other existing methods. CONCLUSION: The SVR method shows a prediction performance competitive with or at least comparable to the previously developed linear regression-based methods for predicting RWCO values. In contrast to support vector classification (SVC), SVR is very good at estimating the raw value profiles of the samples. The successful application of the SVR approach in this study reinforces the fact that support vector regression is a powerful tool in extracting the protein sequence-structure relationship and in estimating the protein structural profiles from amino acid sequences

Construction and Analysis of High-Complexity Ribosome Display Random Peptide Libraries

Random peptide libraries displayed on the ribosome are becoming a new tool for the in vitro selection of biologically relevant macromolecules, including epitopes, antagonists, enzymes, and cell-surface receptors. Ribosome display is a cell-free system of coupling individual nascent proteins (phenotypes) to their corresponding mRNA (genotypes) by the formation of stable protein-ribosome-mRNA complexes and permitting the selection of a functional nascent protein by iterative cycles of panning and reverse transcription-polymerase chain reaction (RT-PCR) amplification in vitro. The complexity of the random peptide library is critical for the success of a panning experiment; greater the diversity of sequences within the library, the more likely it is that the library comprises sequences that can bind a given target with specific affinity. Here, we have used the cell-free system Escherichia coli S30 lysate to construct high-complexity random peptide libraries (>1014 independent members) by introducing strategies that are different from the methods described by Mattheakis et al. and Lamla et al. The key step in our method is to produce nanomole (nmol) amounts of DNA elements that are necessary for in vitro transcription/translation by using PCR but not plasmid DNA. Library design strategies and protocols that facilitate rapid identification are also presented

Notch signaling contributes to the maintenance of both normal neural stem cells and patient-derived glioma stem cells

<p>Abstract</p> <p>Background</p> <p>Cancer stem cells (CSCs) play an important role in the development and recurrence of malignant tumors including glioma. Notch signaling, an evolutionarily conserved pathway mediating direct cell-cell interaction, has been shown to regulate neural stem cells (NSCs) and glioma stem cells (GSCs) in normal neurogenesis and pathological carcinogenesis, respectively. However, how Notch signaling regulates the proliferation and differentiation of GSCs has not been well elucidated.</p> <p>Methods</p> <p>We isolated and cultivate human GSCs from glioma patient specimens. Then on parallel comparison with NSCs, we inhibited Notch signaling using γ-secretase inhibitors (GSI) and assessed the potential functions of Notch signaling in human GSCs.</p> <p>Results</p> <p>Similar to the GSI-treated NSCs, the number of the primary and secondary tumor spheres from GSI-treated GSCs decreased significantly, suggesting that the proliferation and self-renewal ability of GSI-treated GSCs were attenuated. GSI-treated GSCs showed increased differentiation into mature neural cell types in differentiation medium, similar to GSI-treated NSCs. Next, we found that GSI-treated tumor spheres were composed of more intermediate progenitors instead of CSCs, compared with the controls. Interestingly, although inhibition of Notch signaling decreased the ratio of proliferating NSCs in long term culture, we found that the ratio of G2+M phase-GSCs were almost undisturbed on GSI treatment within 72 h.</p> <p>Conclusions</p> <p>These data indicate that like NSCs, Notch signaling maintains the patient-derived GSCs by promoting their self-renewal and inhibiting their differentiation, and support that Notch signal inhibitor GSI might be a prosperous candidate of the treatment targeting CSCs for gliomas, however, with GSI-resistance at the early stage of GSCs cell cycle.</p

Ancient horizontal gene transfer and the last common ancestors

Background The genomic history of prokaryotic organismal lineages is marked by extensive horizontal gene transfer (HGT) between groups of organisms at all taxonomic levels. These HGT events have played an essential role in the origin and distribution of biological innovations. Analyses of ancient gene families show that HGT existed in the distant past, even at the time of the organismal last universal common ancestor (LUCA). Most gene transfers originated in lineages that have since gone extinct. Therefore, one cannot assume that the last common ancestors of each gene were all present in the same cell representing the cellular ancestor of all extant life. Results Organisms existing as part of a diverse ecosystem at the time of LUCA likely shared genetic material between lineages. If these other lineages persisted for some time, HGT with the descendants of LUCA could have continued into the bacterial and archaeal lineages. Phylogenetic analyses of aminoacyl-tRNA synthetase protein families support the hypothesis that the molecular common ancestors of the most ancient gene families did not all coincide in space and time. This is most apparent in the evolutionary histories of seryl-tRNA synthetase and threonyl-tRNA synthetase protein families, each containing highly divergent “rare” forms, as well as the sparse phylogenetic distributions of pyrrolysyl-tRNA synthetase, and the bacterial heterodimeric form of glycyl-tRNA synthetase. These topologies and phyletic distributions are consistent with horizontal transfers from ancient, likely extinct branches of the tree of life. Conclusions Of all the organisms that may have existed at the time of LUCA, by definition only one lineage is survived by known progeny; however, this lineage retains a genomic record of heterogeneous genetic origins. The evolutionary histories of aminoacyl-tRNA synthetases (aaRS) are especially informative in detecting this signal, as they perform primordial biological functions, have undergone several ancient HGT events, and contain many sites with low substitution rates allowing deep phylogenetic reconstruction. We conclude that some aaRS families contain groups that diverge before LUCA. We propose that these ancient gene variants be described by the term “hypnologs”, reflecting their ancient, reticulate origin from a time in life history that has been all but erased”.National Science Foundation (U.S.) (Grant DEB 0830024)Exobiology Program (U.S.) (Grant NNX10AR85G)United States. National Aeronautics and Space Administration (Postdoctoral Program

Phylogenetic Comparison of F-Box (FBX) Gene Superfamily within the Plant Kingdom Reveals Divergent Evolutionary Histories Indicative of Genomic Drift

The emergence of multigene families has been hypothesized as a major contributor to the evolution of complex traits and speciation. To help understand how such multigene families arose and diverged during plant evolution, we examined the phylogenetic relationships of F-Box (FBX) genes, one of the largest and most polymorphic superfamilies known in the plant kingdom. FBX proteins comprise the target recognition subunit of SCF-type ubiquitin-protein ligases, where they individually recruit specific substrates for ubiquitylation. Through the extensive analysis of 10,811 FBX loci from 18 plant species, ranging from the alga Chlamydomonas reinhardtii to numerous monocots and eudicots, we discovered strikingly diverse evolutionary histories. The number of FBX loci varies widely and appears independent of the growth habit and life cycle of land plants, with a little as 198 predicted for Carica papaya to as many as 1350 predicted for Arabidopsis lyrata. This number differs substantially even among closely related species, with evidence for extensive gains/losses. Despite this extraordinary inter-species variation, one subset of FBX genes was conserved among most species examined. Together with evidence of strong purifying selection and expression, the ligases synthesized from these conserved loci likely direct essential ubiquitylation events. Another subset was much more lineage specific, showed more relaxed purifying selection, and was enriched in loci with little or no evidence of expression, suggesting that they either control more limited, species-specific processes or arose from genomic drift and thus may provide reservoirs for evolutionary innovation. Numerous FBX loci were also predicted to be pseudogenes with their numbers tightly correlated with the total number of FBX genes in each species. Taken together, it appears that the FBX superfamily has independently undergone substantial birth/death in many plant lineages, with its size and rapid evolution potentially reflecting a central role for ubiquitylation in driving plant fitness

Evaluation of a Novel Biphasic Culture Medium for Recovery of Mycobacteria: A Multi-Center Study

on L-J slants. Automated liquid culture systems are expensive. A low-cost culturing medium capable of rapidly indicating the presence of mycobacteria is needed. The aim of this study was to develop and evaluate a novel biphasic culture medium for the recovery of mycobacteria from clinical sputum specimens from suspected pulmonary tuberculosis patients.<0.001).

Analysis and computer program for rupture-risk prediction of abdominal aortic aneurysms

BACKGROUND: Ruptured abdominal aortic aneurysms (AAAs) are the 13(th )leading cause of death in the United States. While AAA rupture may occur without significant warning, its risk assessment is generally based on critical values of the maximum AAA diameter (>5 cm) and AAA-growth rate (>0.5 cm/year). These criteria may be insufficient for reliable AAA-rupture risk assessment especially when predicting possible rupture of smaller AAAs. METHODS: Based on clinical evidence, eight biomechanical factors with associated weighting coefficients were determined and summed up in terms of a dimensionless, time-dependent severity parameter, SP(t). The most important factor is the maximum wall stress for which a semi-empirical correlation has been developed. RESULTS: The patient-specific SP(t) indicates the risk level of AAA rupture and provides a threshold value when surgical intervention becomes necessary. The severity parameter was validated with four clinical cases and its application is demonstrated for two AAA cases. CONCLUSION: As part of computational AAA-risk assessment and medical management, a patient-specific severity parameter 0 < SP(t) < 1.0 has been developed. The time-dependent, normalized SP(t) depends on eight biomechanical factors, to be obtained via a patient's pressure and AAA-geometry measurements. The resulting program is an easy-to-use tool which allows medical practitioners to make scientific diagnoses, which may save lives and should lead to an improved quality of life