Electromechanical coupling of waves in nerve fibres

The propagation of an action potential (AP) in a nerve fibre is accompanied by mechanical and thermal effects. In this paper, an attempt is made to build up a mathematical model which couples the AP with a possible pressure wave (PW) in the axoplasm and waves in the nerve fibre wall (longitudinal—LW and transverse—TW) made of a lipid bilayer (biomembrane). A system of differential equations includes the governing equations of single waves with coupling forces between them. The single equations are kept as simple as possible in order to carry out the proof of concept. An assumption based on earlier studies is made that the coupling forces depend on changes (the gradient, time derivative) of the voltage. In addition, it is assumed that the transverse displacement of the biomembrane can be calculated from the gradient of the LW in the biomembrane. The computational simulation is focused to determining the influence of possible coupling forces on the emergence of mechanical waves from the AP. As a result, an ensemble of waves (AP, PW, LW, TW) emerges. The further experiments should verify assumptions about coupling forces.     

Efficient synthesis of an (aminooxy) acetylated‐somatostatin derivative using (aminooxy)acetic acid as a ‘carbonyl capture’ reagent

Owing to the high chemoselectivity between an aminooxy function and a carbonyl group, oxime ligation is one of the most preferred procedures for the preparation of peptide conjugates. However, the sensitivity of (aminooxy)acetylated peptides to ketones and aldehydes makes their synthesis and storage difficult. In our study, we established the efficient synthesis of an (aminooxy)acetylated‐somatostatin derivative in the presence of free (aminooxy)acetic acid, which was used as a ‘carbonyl capture’ reagent in the final cleavage step. This (aminooxy)acetylated compound was further used for the chemoselective ligation (oxime bond formation) with daunorubicin and 4‐fluorobenzaldehyde leading to the formation of conjugates with potential applications in targeted cancer chemotherapy and positron emission tomography. Copyright © 2010 European Peptide Society and John Wiley & Sons, Ltd.     

A Practical Approach to Language Complexity: A Wikipedia Case Study

In this paper we present statistical analysis of English texts from Wikipedia. We try to address the issue of language complexity empirically by comparing the simple English Wikipedia (Simple) to comparable samples of the main English Wikipedia (Main). Simple is supposed to use a more simplified language with a limited vocabulary, and editors are explicitly requested to follow this guideline, yet in practice the vocabulary richness of both samples are at the same level. Detailed analysis of longer units (n-grams of words and part of speech tags) shows that the language of Simple is less complex than that of Main primarily due to the use of shorter sentences, as opposed to drastically simplified syntax or vocabulary. Comparing the two language varieties by the Gunning readability index supports this conclusion. We also report on the topical dependence of language complexity, that is, that the language is more advanced in conceptual articles compared to person-based (biographical) and object-based articles. Finally, we investigate the relation between conflict and language complexity by analyzing the content of the talk pages associated to controversial and peacefully developing articles, concluding that controversy has the effect of reducing language complexity.     

Kalman filtering for disease-state estimation from microarray data

MOTIVATION: In this paper, we propose using the Kalman filter (KF) as a pre-processing step in microarray-based molecular diagnosis. Incorporating the expression covariance between genes is important in such classification problems, since this represents the functional relationships that govern tissue state. Failing to fulfil such requirements may result in biologically implausible class prediction models. Here, we show that employing the KF to remove noise (while retaining meaningful covariance and thus being able to estimate the underlying biological state from microarray measurements) yields linearly separable data suitable for most classification algorithms. RESULTS: We demonstrate the utility and performance of the KF as a robust disease-state estimator on publicly available binary and multi-class microarray datasets in combination with the most widely used classification methods to date. Moreover, using popular graphical representation schemes we show that our filtered datasets also have an improved visualization capability.     

Application of a simple likelihood ratio approximant to protein sequence classification

MOTIVATION: Likelihood ratio approximants (LRA) have been widely used for model comparison in statistics. The present study was undertaken in order to explore their utility as a scoring (ranking) function in the classification of protein sequences. RESULTS: We used a simple LRA-based on the maximal similarity (or minimal distance) scores of the two top ranking sequence classes. The scoring methods (Smith-Waterman, BLAST, local alignment kernel and compression based distances) were compared on datasets designed to test sequence similarities between proteins distantly related in terms of structure or evolution. It was found that LRA-based scoring can significantly outperform simple scoring methods.     

In vitro expansion of long-term repopulating hematopoietic stem cells in the presence of immobilized Jagged-1 and early acting cytokines

There is an increasing body of evidence that suggests that genes involved in cell fate decisions and pattern formation during development also play a key role in the continuous cell fate decisions made by adult tissue stem cells. Here we show that prolonged in vitro culture (14 days) of murine bone marrow lineage negative cells in medium supplemented with three early acting cytokines (stem cell factor, Flk-2/Flt-3 ligand, thrombopoietin) and with immobilized Notch ligand, Jagged-1, resulted in robust expansion of serially transplantable hematopoietic stem cells with long-term repopulating ability. We found that the absolute number of marrow cells was increased approximately 8 to 14-fold in all cultures containing recombinant growth factors. However, the frequency of high quality stem cells was markedly reduced at the same time, except in cultures containing growth factors and Jagged-1-coated Sepharose-4B beads. The absolute number of hematopoietic cells with long-term repopulating ability was increased approximately 10 to 20-fold in the presence of multivalent Notch ligand. These results support a role for combinatorial effects by Notch and cytokine-induced signaling pathways in regulating hematopoietic stem cell fate and to a potential role for Notch ligand in increasing cell numbers in clinical stem cell transplantation.     

Balanced ROC analysis (BAROC) protocol for the evaluation of protein similarities

Identification of problematic protein classes (domain types, protein families) that are difficult to predict from sequence is a key issue in genome annotation. ROC (Receiver Operating Characteristic) analysis is routinely used for the evaluation of protein similarities, however its results – the area under curve (AUC) values – are differentially biased for the various protein classes that are highly different in size. We show the bias can be compensated for by adjusting the length of the top list in a class-dependent fashion, so that the number of negatives within the top list will be equal to (or proportional with) the size of the positive class. Using this balanced protocol the problematic classes can be identified by their AUC values, or by a scatter diagram in which the AUC values are plotted against positive/negative ratio of the top list. The use of likelihood-ratio scoring (Kaján et al, Bioinformatics, 22, 2865–2869, 2007) the bias caused by class imbalance can be further decreased.     

Modelling of processes in nerve fibres at the interface of physiology and mathematics

Biomechanics and Modeling in Mechanobiology - The in silico simulations are widely used in contemporary systems biology including the analysis of nerve pulse propagation. As known from numerous...     

Statistics and bioinformatics in nutritional sciences: analysis of complex data in the era of systems biology

Over the past 2 decades, there have been revolutionary developments in life science technologies characterized by high throughput, high efficiency, and rapid computation. Nutritionists now have the advanced methodologies for the analysis of DNA, RNA, protein, low-molecular-weight metabolites, as well as access to bioinformatics databases. Statistics, which can be defined as the process of making scientific inferences from data that contain variability, has historically played an integral role in advancing nutritional sciences. Currently, in the era of systems biology, statistics has become an increasingly important tool to quantitatively analyze information about biological macromolecules. This article describes general terms used in statistical analysis of large, complex experimental data. These terms include experimental design, power analysis, sample size calculation, and experimental errors (Type I and II errors) for nutritional studies at population, tissue, cellular, and molecular levels. In addition, we highlighted various sources of experimental variations in studies involving microarray gene expression, real-time polymerase chain reaction, proteomics, and other bioinformatics technologies. Moreover, we provided guidelines for nutritionists and other biomedical scientists to plan and conduct studies and to analyze the complex data. Appropriate statistical analyses are expected to make an important contribution to solving major nutrition-associated problems in humans and animals (including obesity, diabetes, cardiovascular disease, cancer, ageing, and intrauterine growth retardation).