Recurrence-based time series analysis by means of complex network methods

Complex networks are an important paradigm of modern complex systems sciences which allows quantitatively assessing the structural properties of systems composed of different interacting entities. During the last years, intensive efforts have been spent on applying network-based concepts also for the analysis of dynamically relevant higher-order statistical properties of time series. Notably, many corresponding approaches are closely related with the concept of recurrence in phase space. In this paper, we review recent methodological advances in time series analysis based on complex networks, with a special emphasis on methods founded on recurrence plots. The potentials and limitations of the individual methods are discussed and illustrated for paradigmatic examples of dynamical systems as well as for real-world time series. Complex network measures are shown to provide information about structural features of dynamical systems that are complementary to those characterized by other methods of time series analysis and, hence, substantially enrich the knowledge gathered from other existing (linear as well as nonlinear) approaches.Comment: To be published in International Journal of Bifurcation and Chaos (2011

A codon substitution model that incorporates the effect of the GC contents, the gene density and the density of CpG islands of human chromosomes

Abstract Background Developing a model for codon substitutions is essential for the analyses of protein sequences. Recent studies on the mutation rates in the non-coding regions have shown that CpG mutation rates in the human genome are negatively correlated to the local GC content and to the densities of functional elements. This study aimed at understanding the effect of genomic features, namely, GC content, gene density, and frequency of CpG islands, on the rates of codon substitution in human chromosomes. Results Codon substitution rates of CpG to TpG mutations, TpG to CpG mutations, and non-CpG transitions and transversions in humans were estimated by comparing the coding regions of thousands of human and chimpanzee genes and inferring their ancestral sequences by using macaque genes as the outgroup. Since the genomic features are depending on each other, partial regression coefficients of these features were obtained. Conclusion The substitution rates of codons depend on gene densities of the chromosomes. Transcription-associated mutation is one such pressure. On the basis of these results, a model of codon substitutions that incorporates the effect of genomic features on codon substitution in human chromosomes was developed.</p

A metabolomics cell-based approach for anticipating and investigating drug-induced liver injury

In preclinical stages of drug development, anticipating potential adverse drug effects such as toxicity is an important issue for both saving resources and preventing public health risks. Current in vitro cytotoxicity tests are restricted by their predictive potential and their ability to provide mechanistic information. This study aimed to develop a metabolomic mass spectrometry-based approach for the detection and classification of drug-induced hepatotoxicity. To this end, the metabolite profiles of human derived hepatic cells (i.e., HepG2) exposed to different well-known hepatotoxic compounds acting through different mechanisms (i.e., oxidative stress, steatosis, phospholipidosis, and controls) were compared by multivariate data analysis, thus allowing us to decipher both common and mechanism-specific altered biochemical pathways. Briefly, oxidative stress damage markers were found in the three mechanisms, mainly showing altered levels of metabolites associated with glutathione and γ-glutamyl cycle. Phospholipidosis was characterized by a decreased lysophospholipids to phospholipids ratio, suggestive of phospholipid degradation inhibition. Whereas, steatosis led to impaired fatty acids β-oxidation and a subsequent increase in triacylglycerides synthesis. The characteristic metabolomic profiles were used to develop a predictive model aimed not only to discriminate between non-toxic and hepatotoxic drugs, but also to propose potential drug toxicity mechanism(s)

Amerindian Helicobacter pylori Strains Go Extinct, as European Strains Expand Their Host Range

We studied the diversity of bacteria and host in the H. pylori-human model. The human indigenous bacterium H. pylori diverged along with humans, into African, European, Asian and Amerindian groups. Of these, Amerindians have the least genetic diversity. Since niche diversity widens the sets of resources for colonizing species, we predicted that the Amerindian H. pylori strains would be the least diverse. We analyzed the multilocus sequence (7 housekeeping genes) of 131 strains: 19 cultured from Africans, 36 from Spanish, 11 from Koreans, 43 from Amerindians and 22 from South American Mestizos. We found that all strains that had been cultured from Africans were African strains (hpAfrica1), all from Spanish were European (hpEurope) and all from Koreans were hspEAsia but that Amerindians and Mestizos carried mixed strains: hspAmerind and hpEurope strains had been cultured from Amerindians and hpEurope and hpAfrica1 were cultured from Mestizos. The least genetically diverse H. pylori strains were hspAmerind. Strains hpEurope were the most diverse and showed remarkable multilocus sequence mosaicism (indicating recombination). The lower genetic structure in hpEurope strains is consistent with colonization of a diversity of hosts. If diversity is important for the success of H. pylori, then the low diversity of Amerindian strains might be linked to their apparent tendency to disappear. This suggests that Amerindian strains may lack the needed diversity to survive the diversity brought by non-Amerindian hosts

IL-1β Suppresses Innate IL-25 and IL-33 Production and Maintains Helminth Chronicity.

Approximately 2 billion people currently suffer from intestinal helminth infections, which are typically chronic in nature and result in growth retardation, vitamin A deficiency, anemia and poor cognitive function. Such chronicity results from co-evolution between helminths and their mammalian hosts; however, the molecular mechanisms by which these organisms avert immune rejection are not clear. We have found that the natural murine helminth, Heligmosomoides polygyrus bakeri (Hp) elicits the secretion of IL-1β in vivo and in vitro and that this cytokine is critical for shaping a mucosal environment suited to helminth chronicity. Indeed in mice deficient for IL-1β (IL-1β(-/-)), or treated with the soluble IL-1βR antagonist, Anakinra, helminth infection results in enhanced type 2 immunity and accelerated parasite expulsion. IL-1β acts to decrease production of IL-25 and IL-33 at early time points following infection and parasite rejection was determined to require IL-25. Taken together, these data indicate that Hp promotes the release of host-derived IL-1β that suppresses the release of innate cytokines, resulting in suboptimal type 2 immunity and allowing pathogen chronicity

Advances in structure elucidation of small molecules using mass spectrometry

The structural elucidation of small molecules using mass spectrometry plays an important role in modern life sciences and bioanalytical approaches. This review covers different soft and hard ionization techniques and figures of merit for modern mass spectrometers, such as mass resolving power, mass accuracy, isotopic abundance accuracy, accurate mass multiple-stage MS(n) capability, as well as hybrid mass spectrometric and orthogonal chromatographic approaches. The latter part discusses mass spectral data handling strategies, which includes background and noise subtraction, adduct formation and detection, charge state determination, accurate mass measurements, elemental composition determinations, and complex data-dependent setups with ion maps and ion trees. The importance of mass spectral library search algorithms for tandem mass spectra and multiple-stage MS(n) mass spectra as well as mass spectral tree libraries that combine multiple-stage mass spectra are outlined. The successive chapter discusses mass spectral fragmentation pathways, biotransformation reactions and drug metabolism studies, the mass spectral simulation and generation of in silico mass spectra, expert systems for mass spectral interpretation, and the use of computational chemistry to explain gas-phase phenomena. A single chapter discusses data handling for hyphenated approaches including mass spectral deconvolution for clean mass spectra, cheminformatics approaches and structure retention relationships, and retention index predictions for gas and liquid chromatography. The last section reviews the current state of electronic data sharing of mass spectra and discusses the importance of software development for the advancement of structure elucidation of small molecules

Indirect search for dark matter from the Galactic Center and halo with the Super-Kamiokande detector

We present a search for an excess of neutrino interactions due to dark matter in the form of weakly interacting massive particles (WIMPs) annihilating in the Galactic center or halo based on the data set of Super-Kamiokande-I, -II, -III and -IV taken from 1996 to 2016. We model the neutrino flux, energy, and flavor distributions assuming WIMP self-annihilation is dominant to ν ¯ ν , μ + μ − , b ¯ b , or W + W − . The excess is in comparison to atmospheric neutrino interactions which are modeled in detail and fit to data. Limits on the self-annihilation cross section ⟨ σ A V ⟩ are derived for WIMP masses in the range 1 GeV to 10 TeV, reaching as low as 9.6 × 10 − 23     cm 3   s − 1 for 5 GeV WIMPs in b ¯ b mode and 1.2 × 10 − 24     cm 3   s − 1 for 1 GeV WIMPs in ν ¯ ν mode. The obtained sensitivity of the Super-Kamiokande detector to WIMP masses below several tens of GeV is the best among similar indirect searches to date