Site-specific Mutants of Oncomodulin: 1H NMR and optical stopped-flow studies of the effect on the metal binding properties of an Asp59 → Glu59 substitution in the calcium-specific site

Abstract High resolution 1H nuclear magnetic resonance spectroscopy and optical stopped-flow techniques have been used to study the metal binding properties of a site-specific mutant of bacterial recombinant oncomodulin in which glutamate has replaced a liganding aspartate at position 59 in the CD calcium-binding site. In particular we have followed the replacement of calcium by lutetium in bacterial recombinant oncomodulin and D59E oncomodulin to provide a measure of the protein's preferences for metal ions of different ionic radii. The result of the Asp----Glu substitution is to make the mutant oncomodulin more similar to rat parvalbumin in terms of its relative CD- and EF-domain affinities for lutetium(III), that is to increase its affinity for metal ions with smaller ionic radii. This finding supports the original hypothesis that the presence of Asp at sequence position 59 is an important factor in the reduced preference of the CD site of oncomodulin for smaller metals such as magnesium (Williams, T. C., Corson, D. C., Sykes, B. D., and MacManus, J. P. (1987) J. Biol. Chem. 262, 6248-6256). However, our studies show that both the CD and the EF sites are affected by this single residue substitution suggesting that many factors play a role in the metal binding affinity and interaction between the two sites

A reusable benchmark of brain-age prediction from M/EEG resting-state signals

Population-level modeling can define quantitative measures of individual aging by applying machine learning to large volumes of brain images. These measures of brain age, obtained from the general population, helped characterize disease severity in neurological populations, improving estimates of diagnosis or prognosis. Magnetoencephalography (MEG) and Electroencephalography (EEG) have the potential to further generalize this approach towards prevention and public health by enabling assessments of brain health at large scales in socioeconomically diverse environments. However, more research is needed to define methods that can handle the complexity and diversity of M/EEG signals across diverse real-world contexts. To catalyse this effort, here we propose reusable benchmarks of competing machine learning approaches for brain age modeling. We benchmarked popular classical machine learning pipelines and deep learning architectures previously used for pathology decoding or brain age estimation in 4 international M/EEG cohorts from diverse countries and cultural contexts, including recordings from more than 2500 participants. Our benchmarks were built on top of the M/EEG adaptations of the BIDS standard, providing tools that can be applied with minimal modification on any M/EEG dataset provided in the BIDS format. Our results suggest that, regardless of whether classical machine learning or deep learning was used, the highest performance was reached by pipelines and architectures involving spatially aware representations of the M/EEG signals, leading to R^2 scores between 0.60-0.71. Hand-crafted features paired with random forest regression provided robust benchmarks even in situations in which other approaches failed. Taken together, this set of benchmarks, accompanied by open-source software and high-level Python scripts, can serve as a starting point and quantitative reference for future efforts at developing M/EEG-based measures of brain aging. The generality of the approach renders this benchmark reusable for other related objectives such as modeling specific cognitive variables or clinical endpoints

Review of code and phase biases in multi-GNSS positioning

A review of the research conducted until present on the subject of Global Navigation Satellite System (GNSS) hardware-induced phase and code biases is here provided. Biases in GNSS positioning occur because of imperfections and/or physical limitations in the GNSS hardware. The biases are a result of small delays between events that ideally should be simultaneous in the transmission of the signal from a satellite or in the reception of the signal in a GNSS receiver. Consequently, these biases will also be present in the GNSS code and phase measurements and may there affect the accuracy of positions and other quantities derived from the observations. For instance, biases affect the ability to resolve the integer ambiguities in Precise Point Positioning (PPP), and in relative carrier phase positioning when measurements from multiple GNSSs are used. In addition, code biases affect ionospheric modeling when the Total Electron Content is estimated from GNSS measurements. The paper illustrates how satellite phase biases inhibit the resolution of the phase ambiguity to an integer in PPP, while receiver phase biases affect multi-GNSS positioning. It is also discussed how biases in the receiver channels affect relative GLONASS positioning with baselines of mixed receiver types. In addition, the importance of code biases between signals modulated onto different carriers as is required for modeling the ionosphere from GNSS measurements is discussed. The origin of biases is discussed along with their effect on GNSS positioning, and descriptions of how biases can be estimated or in other ways handled in the positioning process are provided.QC 20170922</p

Study on cycle-slip detection and repair methods for a single dual-frequency global positioning system (GPS) receiver

In this work, we assessed the performance of the cycle-slip detection methods: Turbo Edit (TE), Melbourne-Wübbena wide-lane ambiguity (MWWL) and forward and backward moving window averaging (FBMWA). The TE and MWWL methods were combined with ionospheric total electron content rate (TECR), and the FBMWA with second-order time-difference phase ionosphere residual (STPIR) and TECR. Under different scenarios, 10 Global Positioning System (GPS) datasets were used to assess the performance of the methods for cycle-slip detection. The MWWL-TECR delivered the best performance in detecting cycle-slips for 1 s data. The relative comparisons show that the FBMWA-TECR method performed slightly better than its original version, FBMWA-STPIR, detecting 100% and 73%, respectively. For data with a sample rate of 5 s, the FBMWA-TECR performed better than MWWL-TECR. However, the FBMWA is suitable only for post-processing, which refers to applications where the data are processed after the fact

Mining metabolites: extracting the yeast metabolome from the literature

Text mining methods have added considerably to our capacity to extract biological knowledge from the literature. Recently the field of systems biology has begun to model and simulate metabolic networks, requiring knowledge of the set of molecules involved. While genomics and proteomics technologies are able to supply the macromolecular parts list, the metabolites are less easily assembled. Most metabolites are known and reported through the scientific literature, rather than through large-scale experimental surveys. Thus it is important to recover them from the literature. Here we present a novel tool to automatically identify metabolite names in the literature, and associate structures where possible, to define the reported yeast metabolome. With ten-fold cross validation on a manually annotated corpus, our recognition tool generates an f-score of 78.49 (precision of 83.02) and demonstrates greater suitability in identifying metabolite names than other existing recognition tools for general chemical molecules. The metabolite recognition tool has been applied to the literature covering an important model organism, the yeast Saccharomyces cerevisiae, to define its reported metabolome. By coupling to ChemSpider, a major chemical database, we have identified structures for much of the reported metabolome and, where structure identification fails, been able to suggest extensions to ChemSpider. Our manually annotated gold-standard data on 296 abstracts are available as supplementary materials. Metabolite names and, where appropriate, structures are also available as supplementary materials

An assessment of smartphone and low-cost multi-GNSS single-frequency RTK positioning for low, medium and high ionospheric disturbance periods

The emerging GNSSs make single-frequency (SF) RTK positioning possible. In this contribution two different types of low-cost (few hundred USDs) RTK receivers are analyzed, which can track L1 GPS, B1 BDS, E1 Galileo and L1 QZSS, or any combinations thereof, for a location in Dunedin, New Zealand. These SF RTK receivers can potentially give competitive ambiguity resolution and positioning performance to that of more expensive (thousands USDs) dual-frequency (DF) GPS receivers. A smartphone implementation of one of these SF receiver types is also evaluated. The least-squares variance component estimation (LS-VCE) procedure is first used to formulate a realistic stochastic model, which assures that our receivers at hand can achieve the best possible ambiguity resolution and RTK positioning performance. The best performing low-cost SF RTK receiver types are then assessed against DF GPS receivers and survey-grade antennas. Real data with ionospheric disturbances at low, medium and high levels are analyzed, while making use of the ionosphere-weighted model. It will be demonstrated that when the presence of the residual ionospheric delays increases, instantaneous RTK positioning is not possible for any of the receivers, and a multi-epoch model is necessary to use. It is finally shown that the low-cost SF RTK performance can remain competitive to that of more expensive DF GPS receivers even when the ionospheric disturbance level reaches a Kp-index of 7-, i.e. for a strong geomagnetic storm, for the baseline at hand

Stringent response of Escherichia coli: revisiting the bibliome using literature mining

Understanding the mechanisms responsible for cellular responses depends on the systematic collection and analysis of information on the main biological concepts involved. Indeed, the identification of biologically relevant concepts in free text, namely genes, tRNAs, mRNAs, gene products and small molecules, is crucial to capture the structure and functioning of different responses. Results In this work, we review literature reports on the study of the stringent response in Escherichia coli. Rather than undertaking the development of a highly specialised literature mining approach, we investigate the suitability of concept recognition and statistical analysis of concept occurrence as means to highlight the concepts that are most likely to be biologically engaged during this response. The co-occurrence analysis of core concepts in this stringent response, i.e. the (p)ppGpp nucleotides with gene products was also inspected and suggest that besides the enzymes RelA and SpoT that control the basal levels of (p)ppGpp nucleotides, many other proteins have a key role in this response. Functional enrichment analysis revealed that basic cellular processes such as metabolism, transcriptional and translational regulation are central, but other stress-associated responses might be elicited during the stringent response. In addition, the identification of less annotated concepts revealed that some (p)ppGpp-induced functional activities are still overlooked in most reviews. Conclusions In this paper we applied a literature mining approach that offers a more comprehensive analysis of the stringent response in E. coli. The compilation of relevant biological entities to this stress response and the assessment of their functional roles provided a more systematic understanding of this cellular response. Overlooked regulatory entities, such as transcriptional regulators, were found to play a role in this stress response. Moreover, the involvement of other stress-associated concepts demonstrates the complexity of this cellular response

Photodynamic and Antibiotic Therapy Impair the Pathogenesis of Enterococcus faecium in a Whole Animal Insect Model

Enterococcus faecium has emerged as one of the most important pathogens in healthcare-associated infections worldwide due to its intrinsic and acquired resistance to many antibiotics, including vancomycin. Antimicrobial photodynamic therapy (aPDT) is an alternative therapeutic platform that is currently under investigation for the control and treatment of infections. PDT is based on the use of photoactive dye molecules, widely known as photosensitizer (PS). PS, upon irradiation with visible light, produces reactive oxygen species that can destroy lipids and proteins causing cell death. We employed Galleria mellonella (the greater wax moth) caterpillar fatally infected with E. faecium to develop an invertebrate host model system that can be used to study the antimicrobial PDT (alone or combined with antibiotics). In the establishment of infection by E. faecium in G. mellonella, we found that the G. mellonella death rate was dependent on the number of bacterial cells injected into the insect hemocoel and all E. faecium strains tested were capable of infecting and killing G. mellonella. Antibiotic treatment with ampicillin, gentamicin or the combination of ampicillin and gentamicin prolonged caterpillar survival infected by E. faecium (P = 0.0003, P = 0.0001 and P = 0.0001, respectively). In the study of antimicrobial PDT, we verified that methylene blue (MB) injected into the insect followed by whole body illumination prolonged the caterpillar survival (P = 0.0192). Interestingly, combination therapy of larvae infected with vancomycin-resistant E. faecium, with antimicrobial PDT followed by vancomycin, significantly prolonged the survival of the caterpillars when compared to either antimicrobial PDT (P = 0.0095) or vancomycin treatment alone (P = 0.0025), suggesting that the aPDT made the vancomycin resistant E. faecium strain more susceptible to vancomycin action. In summary, G. mellonella provides an invertebrate model host to study the antimicrobial PDT and to explore combinatorial aPDT-based treatments

Retrotransposons and the evolution of mammalian gene expression

Transposable elements, and retroviral-like elements in particular, are a rich potential source of genetic variation within a host's genome. Many mutations of endogenous genes in phylogenetically diverse organisms are due to insertion of elements that affect gene expression by altering the normal pattern of regulation. While few such associations are known to have been maintained over time, two recently elucidated examples suggest transposable elements may have a significant impact in evolution of gene expression. The first example, concerning the mouse sex-limited protein ( Slp ), clearly establishes that ancient retroviral enhancer sequences now confer hormonal dependence on the adjacent gene. The second example shows that within the human amylase gene family, salivary specific expression has arisen due to inserted sequences, deriving perhaps from a conjunction of two retrotransposable elements.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/42800/1/10709_2004_Article_BF00133720.pd

Twenty years of coordination technologies: State-of-the-art and perspectives

Since complexity of inter- and intra-systems interactions is steadily increasing in modern application scenarios (e.g., the IoT), coordination technologies are required to take a crucial step towards maturity. In this paper we look back at the history of the COORDINATION conference in order to shed light on the current status of the coordination technologies there proposed throughout the years, in an attempt to understand success stories, limitations, and possibly reveal the gap between actual technologies, theoretical models, and novel application needs