Interpol: An R package for preprocessing of protein sequences

<p>Abstract</p> <p>Background</p> <p>Most machine learning techniques currently applied in the literature need a fixed dimensionality of input data. However, this requirement is frequently violated by real input data, such as DNA and protein sequences, that often differ in length due to insertions and deletions. It is also notable that performance in classification and regression is often improved by numerical encoding of amino acids, compared to the commonly used sparse encoding.</p> <p>Results</p> <p>The software "Interpol" encodes amino acid sequences as numerical descriptor vectors using a database of currently 532 descriptors (mainly from AAindex), and normalizes sequences to uniform length with one of five linear or non-linear interpolation algorithms. Interpol is distributed with open source as platform independent R-package. It is typically used for preprocessing of amino acid sequences for classification or regression.</p> <p>Conclusions</p> <p>The functionality of Interpol widens the spectrum of machine learning methods that can be applied to biological sequences, and it will in many cases improve their performance in classification and regression.</p

Two-Fermion Bound States within the Bethe-Salpeter Approach

To solve the spinor-spinor Bethe-Salpeter equation in Euclidean space we propose a novel method related to the use of hyperspherical harmonics. We suggest an appropriate extension to form a new basis of spin-angular harmonics that is suitable for a representation of the vertex functions. We present a numerical algorithm to solve the Bethe-Salpeter equation and investigate in detail the properties of the solution for the scalar, pseudoscalar and vector meson exchange kernels including the stability of bound states. We also compare our results to the non relativistic ones and to the results given by light front dynamics.Comment: 32 pages, XIII Tables, 8 figure

The principal neurons of the medial nucleus of the trapezoid body and NG2+ glial cells receive coordinated excitatory synaptic input

Glial cell processes are part of the synaptic structure and sense spillover of transmitter, while some glial cells can even receive direct synaptic input. Here, we report that a defined type of glial cell in the medial nucleus of the trapezoid body (MNTB) receives excitatory glutamatergic synaptic input from the calyx of Held (CoH). This giant glutamatergic terminal forms an axosomatic synapse with a single principal neuron located in the MNTB. The NG2 glia, as postsynaptic principal neurons, establish synapse-like structures with the CoH terminal. In contrast to the principal neurons, which are known to receive excitatory as well as inhibitory inputs, the NG2 glia receive mostly, if not exclusively, α-amino-3-hydroxy-5-methyl-isoxazole-4-propionic acid receptor–mediated evoked and spontaneous synaptic input. Simultaneous recordings from neurons and NG2 glia indicate that they partially receive synchronized spontaneous input. This shows that an NG2+ glial cell and a postsynaptic neuron share presynaptic terminals

Neuron–astrocyte interactions in the medial nucleus of the trapezoid body

The calyx of Held (CoH) synapse serves as a model system to analyze basic mechanisms of synaptic transmission. Astrocyte processes are part of the synaptic structure and contact both pre- and postsynaptic membranes. In the medial nucleus of the trapezoid body (MNTB), midline stimulation evoked a current response that was not mediated by glutamate receptors or glutamate uptake, despite the fact that astrocytes express functional receptors and transporters. However, astrocytes showed spontaneous Ca2+ responses and neuronal slow inward currents (nSICs) were recorded in the postsynaptic principal neurons (PPNs) of the MNTB. These currents were correlated with astrocytic Ca2+ activity because dialysis of astrocytes with BAPTA abolished nSICs. Moreover, the frequency of these currents was increased when Ca2+ responses in astrocytes were elicited. NMDA antagonists selectively blocked nSICs while D-serine degradation significantly reduced NMDA-mediated currents. In contrast to previous studies in the hippocampus, these NMDA-mediated currents were rarely synchronized

Dislocations and the enhancement of superconductivity in odd-parity superconductor Sr2_2RuO4_4

We report observation of the enhancement of superconductivity near lattice dislocations and the absence of the strengthening of vortex pinning in odd-parity superconductor Sr$_2$RuO$_4$, both surprising results in direct contrast to the well known sensitivity of superconductivity in Sr$_2$RuO$_4$ to disorder. The enhanced superconductivity appears to be related fundamentally to the two-component nature of the superconducting order parameter, as revealed in our phenomenological theory taking into account the effect of symmetry reduction near a dislocation.Comment: 5 pages, 4 figures, submitted to Physical Review Letter

Generosity motivated by acceptance - evolutionary analysis of an anticipation game

We here present both experimental and theoretical results for an Anticipation Game, a two-stage game wherein the standard Dictator Game is played after a matching phase wherein receivers use the past actions of dictators to decide whether to interact with them. The experimental results for three different treatments show that partner choice induces dictators to adjust their donations towards the expectations of the receivers, giving significantly more than expected in the standard Dictator Game. Adding noise to the dictators' reputation lowers the donations, underlining that their actions are determined by the knowledge provided to receivers. Secondly, we show that the recently proposed stochastic evolutionary model where payoff only weakly drives evolution and individuals can make mistakes requires some adaptations to explain the experimental results. We observe that the model fails in reproducing the heterogeneous strategy distributions. We show here that by explicitly modelling the dictators' probability of acceptance by receivers and introducing a parameter that reflects the dictators' capacity to anticipate future gains produces a closer fit to the aforementioned strategy distributions. This new parameter has the important advantage that it explains where the dictators' generosity comes from, revealing that anticipating future acceptance is the key to success.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Hypoxia Alters Cell Cycle Regulatory Protein Expression and Induces Premature Maturation of Oligodendrocyte Precursor Cells

Periventricular white matter injury (PWMI) is a common form of brain injury sustained by preterm infants. A major factor that predisposes to PWMI is hypoxia. Because oligodendrocytes (OLs) are responsible for myelination of axons, abnormal OL development or function may affect brain myelination. At present our understanding of the influences of hypoxia on OL development is limited. To examine isolated effects of hypoxia on OLs, we examined the influences of hypoxia on OL development in vitro.Cultures of oligodendrocyte precursor cells (OPCs) were prepared from mixed glial cultures and were 99% pure. OPCs were maintained at 21% O(2) or hypoxia (1% or 4% O(2)) for up to 7 days. We observed that 1% O(2) lead to an increase in the proportion of myelin basic protein (MBP)-positive OLs after 1 week in culture, and a decrease in the proportion of platelet-derived growth factor receptor alpha (PDGFRalpha)-positive cells suggesting premature OL maturation. Increased expression of the cell cycle regulatory proteins p27(Kip1) and phospho-cdc2, which play a role in OL differentiation, was seen as well.These results show that hypoxia interferes with the normal process of OL differentiation by inducing premature OPC maturation

Bacterial Gut Symbionts Contribute to Seed Digestion in an Omnivorous Beetle

Obligate bacterial symbionts alter the diets of host animals in numerous ways, but the ecological roles of facultative bacterial residents that colonize insect guts remain unclear. Carabid beetles are a common group of beneficial insects appreciated for their ability to consume insect prey and seeds, but the contributions of microbes to diet diversification in this and similar groups of facultative granivores are largely unknown.Using 16S rRNA gene clone libraries and terminal restriction fragment (tRF) length polymorphism analyses of these genes, we examined the bacterial communities within the guts of facultatively granivorous, adult Harpalus pensylvanicus (Carabidae), fed one of five dietary treatments: 1) an untreated Field population, 2) Seeds with antibiotics (seeds were from Chenopodium album), 3) Seeds without antibiotics, 4) Prey with antibiotics (prey were Acheta domesticus eggs), and 5) Prey without antibiotics. The number of seeds and prey consumed by each beetle were recorded following treatment. Harpalus pensylvanicus possessed a fairly simple gut community of approximately 3-4 bacterial operational taxonomic units (OTU) per beetle that were affiliated with the Gammaproteobacteria, Bacilli, Alphaproteobacteria, and Mollicutes. Bacterial communities of the host varied among the diet and antibiotic treatments. The field population and beetles fed seeds without antibiotics had the closest matching bacterial communities, and the communities in the beetles fed antibiotics were more closely related to each other than to those of the beetles that did not receive antibiotics. Antibiotics reduced and altered the bacterial communities found in the beetle guts. Moreover, beetles fed antibiotics ate fewer seeds, and those beetles that harbored the bacterium Enterococcus faecalis consumed more seeds on average than those lacking this symbiont.We conclude that the relationships between the bacterium E. faecalis and this factultative granivore's ability to consume seeds merit further investigation, and that facultative associations with symbiotic bacteria have important implications for the nutritional ecology of their hosts

Machine learning on normalized protein sequences

<p>Abstract</p> <p>Background</p> <p>Machine learning techniques have been widely applied to biological sequences, e.g. to predict drug resistance in HIV-1 from sequences of drug target proteins and protein functional classes. As deletions and insertions are frequent in biological sequences, a major limitation of current methods is the inability to handle varying sequence lengths.</p> <p>Findings</p> <p>We propose to normalize sequences to uniform length. To this end, we tested one linear and four different non-linear interpolation methods for the normalization of sequence lengths of 19 classification datasets. Classification tasks included prediction of HIV-1 drug resistance from drug target sequences and sequence-based prediction of protein function. We applied random forests to the classification of sequences into "positive" and "negative" samples. Statistical tests showed that the linear interpolation outperforms the non-linear interpolation methods in most of the analyzed datasets, while in a few cases non-linear methods had a small but significant advantage. Compared to other published methods, our prediction scheme leads to an improvement in prediction accuracy by up to 14%.</p> <p>Conclusions</p> <p>We found that machine learning on sequences normalized by simple linear interpolation gave better or at least competitive results compared to state-of-the-art procedures, and thus, is a promising alternative to existing methods, especially for protein sequences of variable length.</p