Time-frequency component analysis of somatosensory evoked potentials in rats

<p>Abstract</p> <p>Background</p> <p>Somatosensory evoked potential (SEP) signal usually contains a set of detailed temporal components measured and identified in a time domain, giving meaningful information on physiological mechanisms of the nervous system. The purpose of this study is to measure and identify detailed time-frequency components in normal SEP using time-frequency analysis (TFA) methods and to obtain their distribution pattern in the time-frequency domain.</p> <p>Methods</p> <p>This paper proposes to apply a high-resolution time-frequency analysis algorithm, the matching pursuit (MP), to extract detailed time-frequency components of SEP signals. The MP algorithm decomposes a SEP signal into a number of elementary time-frequency components and provides a time-frequency parameter description of the components. A clustering by estimation of the probability density function in parameter space is followed to identify stable SEP time-frequency components.</p> <p>Results</p> <p>Experimental results on cortical SEP signals of 28 mature rats show that a series of stable SEP time-frequency components can be identified using the MP decomposition algorithm. Based on the statistical properties of the component parameters, an approximated distribution of these components in time-frequency domain is suggested to describe the complex SEP response.</p> <p>Conclusion</p> <p>This study shows that there is a set of stable and minute time-frequency components in SEP signals, which are revealed by the MP decomposition and clustering. These stable SEP components have specific localizations in the time-frequency domain.</p

Recent Developments in Quantitative Finance: An Overview

Quantitative finance combines mathematical finance, financial statistics, financial econometrics and empirical finance to provide a solid quantitative foundation for the analysis of financial issues. The purpose of this special issue on “Recent developments in quantitative finance” is to highlight some areas of research in which novel methods in quantitative finance have contributed significantly to the analysis of financial issues, specifically fast methods for large-scale non-elliptical portfolio optimization, the impact of acquisitions on new technology stocks: the Google-Motorola case, the effects of firm characteristics and recognition policy on employee stock options prices after controlling for self-selection, searching for landmines in equity markets, whether CEO incentive pay improves bank performance, using a quantile regression analysis of U.S. commercial banks, testing price pressure, information, feedback trading, and smoothing effects for energy exchange traded funds, actuarial implications of structural changes in El Niño-Southern Oscillation Index dynamics, credit spreads and bankruptcy information from options data, QMLE of a standard exponential ACD model: asymptotic distribution and residual correlation, and using two-part quantile regression to analyze how earnings shocks affect stock repurchases

Recent Developments in Quantitative Finance: An Overview

Quantitative finance combines mathematical finance, financial statistics, financial econometrics and empirical finance to provide a solid quantitative foundation for the analysis of financial issues. The purpose of this special issue on “Recent developments in quantitative finance” is to highlight some areas of research in which novel methods in quantitative finance have contributed significantly to the analysis of financial issues, specifically fast methods for large-scale non-elliptical portfolio optimization, the impact of acquisitions on new technology stocks: the Google-Motorola case, the effects of firm characteristics and recognition policy on employee stock options prices after controlling for self-selection, searching for landmines in equity markets, whether CEO incentive pay improves bank performance, using a quantile regression analysis of U.S. commercial banks, testing price pressure, information, feedback trading, and smoothing effects for energy exchange traded funds, actuarial implications of structural changes in El Niño-Southern Oscillation Index dynamics, credit spreads and bankruptcy information from options data, QMLE of a standard exponential ACD model: asymptotic distribution and residual correlation, and using two-part quantile regression to analyze how earnings shocks affect stock repurchases

Association between plasma levels of hyaluronic acid and functional outcome in acute stroke patients

BACKGROUND: Activation of hyaluronic acid (HA) and associated enzyme synthesis has been demonstrated in experimental stroke animal models. Our study aimed to investigate the plasma levels of HA in acute stroke patients and the associations between HA levels and functional outcome. METHODS: This was a multicenter case–control study. Acute stroke patients and age- and sex-matched non-stroke controls were recruited. Plasma levels of HA in acute stroke patients were determined at <48 hours and at 48 to 72 hours after stroke onset by standard ELISA. Favorable functional outcome was defined as modified Rankin scale ≤2 at 3 months after stroke. RESULTS: The study included 206 acute stroke patients, including 43 who had intracerebral hemorrhage and 163 who had ischemic stroke, and 159 controls. The plasma levels of HA in the acute stroke patients were significantly higher than those in the controls (219.7 ± 203.4 ng/ml for <48 hours and 343.1 ± 710.3 ng/ml for 48 to 72 hours versus 170.4 ± 127.9 ng/ml in the controls; both P < 0.05). For intracerebral hemorrhage patients, HA ≤500 ng/ml (<48 hours) was an independent favorable outcome predictor (P = 0.016). For ischemic stroke patients, an inverted U-shaped association between plasma HA (48 to 72 hours) and outcome was noted, indicating that ischemic stroke patients with too high or too low plasma HA levels tended to have an unfavorable outcome. CONCLUSION: HA plasma level was elevated in patients with acute stroke, and can predict 3-month functional outcome, particularly for patients with intracerebral hemorrhage

Mechanistic insights into selective oxidation of polyaromatic compounds using RICO chemistry

Ruthenium‐ion‐catalyzed oxidation (RICO) of polyaromatic hydrocarbons (PAHs) has been studied in detail using experimental and computational approaches to explore the reaction mechanism. DFT calculations show that regioselectivity in these reactions can be understood in terms of the preservation of aromaticity in the initial formation of a [3+2] metallocycle intermediate at the most‐isolated double bond. We identify two competing pathways: C−C bond cleavage leading to a dialdehyde and C‐H activation followed by H migration to the RuOx complex to give diketones. Experimentally, the oxidation of pyrene and phenanthrene has been carried out in monophasic and biphasic solvent systems. Our results show that diketones are the major product for both phenanthrene and pyrene substrates. These diketone products are shown to be stable under our reaction conditions so that higher oxidation products (acids and their derivatives) are assigned to the competing pathway through the dialdehyde. Experiments using 18O‐labelled water do show incorporation of oxygen from the solvents into products, but this may take place during the formation of the reactive RuO4 species rather than directly during PAH oxidation. When the oxidation of pyrene is carried out using D2O, a kinetic isotope effect (KIE) is observed implying that water is involved in the rate‐determining step leading to the diketone products

The Slow-Releasing Hydrogen Sulfide Donor, GYY4137, Exhibits Novel Anti-Cancer Effects In Vitro and In Vivo

The slow-releasing hydrogen sulfide (H2S) donor, GYY4137, caused concentration-dependent killing of seven different human cancer cell lines (HeLa, HCT-116, Hep G2, HL-60, MCF-7, MV4-11 and U2OS) but did not affect survival of normal human lung fibroblasts (IMR90, WI-38) as determined by trypan blue exclusion. Sodium hydrosulfide (NaHS) was less potent and not active in all cell lines. A structural analogue of GYY4137 (ZYJ1122) lacking sulfur and thence not able to release H2S was inactive. Similar results were obtained using a clonogenic assay. Incubation of GYY4137 (400 µM) in culture medium led to the generation of low (<20 µM) concentrations of H2S sustained over 7 days. In contrast, incubation of NaHS (400 µM) in the same way led to much higher (up to 400 µM) concentrations of H2S which persisted for only 1 hour. Mechanistic studies revealed that GYY4137 (400 µM) incubated for 5 days with MCF-7 but not IMR90 cells caused the generation of cleaved PARP and cleaved caspase 9, indicative of a pro-apoptotic effect. GYY4137 (but not ZYJ1122) also caused partial G2/M arrest of these cells. Mice xenograft studies using HL-60 and MV4-11 cells showed that GYY4137 (100–300 mg/kg/day for 14 days) significantly reduced tumor growth. We conclude that GYY4137 exhibits anti-cancer activity by releasing H2S over a period of days. We also propose that a combination of apoptosis and cell cycle arrest contributes to this effect and that H2S donors should be investigated further as potential anti-cancer agents

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN