Training for performance : insights from molecular biology

In this commentary the authors discuss the molecular basis of the training adaptation and review the role of several key signaling proteins important in the adaptation to endurance and resistance training.

Computational fluid dynamic analysis of intracranial aneurysmal bleb formation

Background The management of unruptured aneurysms is controversial with the decision to treat influenced by aneurysm characteristics including size and morphology. Aneurysmal bleb formation is thought to be associated with an increased risk of rupture. Objective To correlate computational fluid dynamic (CFD) indices with bleb formation. Methods Anatomical models were constructed from three-dimensional rotational angiogram (3DRA) data in 27 patients with cerebral aneurysms harbouring single blebs. Additional models representing the aneurysm before bleb formation were constructed by digitally removing the bleb. We characterised haemodynamic features of models both with and without the bleb using CFDs. Flow structure, wall shear stress (WSS), pressure and oscillatory shear index (OSI) were analysed. Results There was a statistically significant association between bleb location at or adjacent to the point of maximal WSS (74.1%, p=0.019), irrespective of rupture status. Aneurysmal blebs were related to the inflow or outflow jet in 88.9% of cases (p<0.001) whilst 11.1% were unrelated. Maximal wall pressure and OSI were not significantly related to bleb location. The bleb region attained a lower WSS following its formation in 96.3% of cases (p<0.001) and was also lower than the average aneurysm WSS in 86% of cases (p<0.001). Conclusion Cerebral aneurysm blebs generally form at or adjacent to the point of maximal WSS and are aligned with major flow structures. Wall pressure and OSI do not contribute to determining bleb location. The measurement of WSS using CFD models may potentially predict bleb formation and thus improve the assessment of rupture risk in unruptured aneurysms.

Computational simulation of the early stage of bone healing under different configurations of locking compression plates

Flexible fixation or the so-called ‘biological fixation’ has been shown to encourage the formation of fracture callus, leading to better healing outcomes. However, the nature of the relationship between the degree of mechanical stability provided by a flexible fixation and the optimal healing outcomes has not been fully understood. In this study, we have developed a validated quantitative model to predict how cells in fracture callus might respond to change in their mechanical microenvironment due to different configurations of locking compression plate (LCP) in clinical practice, particularly in the early stage of healing. The model predicts that increasing flexibility of the LCP by changing the bone–plate distance (BPD) or the plate working length (WL) could enhance interfragmentary strain in the presence of a relatively large gap size (.3 mm). Furthermore, conventional LCP normally results in asymmetric tissue development during early stage of callus formation, and the increase of BPD or WL is insufficient to alleviate this problem.

Porohyperelastic analysis of single chondrocyte using AFM and inverse FEA

The aim of this paper is to determine the creep and relaxation responses of single chondrocytes in vitro. Firstly, Atomic Force Microscopy (AFM) was used to obtain the force-indentation curves of single chondrocytes at the strain-rate of 7.05 s-1. This result was then employed in inverse finite element analysis (FEA) using porohyperelastic (PHE) idealization of the cells to determine their mechanical properties. The PHE model results agreed well with AFM experimental data. This PHE model was then utilized to study chondrocyte’s creep and relaxation behaviors. The results revealed that the effect of fluid was predominant for cell’s mechanical behaviors and that the PHE is a good model for biomechanics studies of chondrocytes.

Rapid match-searching for gene silencing assessment

Motivation: Gene silencing, also called RNA interference, requires reliable assessment of silencer impacts. A critical task is to find matches between silencer oligomers and sites in the genome, in accordance with one-to-many matching rules (G-U matching, with provision for mismatches). Fast search algorithms are required to support silencer impact assessments in procedures for designing effective silencer sequences.Results: The article presents a matching algorithm and data structures specialized for matching searches, including a kernel procedure that addresses a Boolean version of the database task called the skyline search. Besides exact matches, the algorithm is extended to allow for the location-specific mismatches applicable in plants. Computational tests show that the algorithm is significantly faster than suffix-tree alternatives. © The Author 2010. Published by Oxford University Press. All rights reserved.

Correlating flow induced shear stress and chondrocytes activity in micro-porous scaffold using computational fluid dynamics and rapid prototyping

Flow induced shear stress plays an important role in regulating cell growth and distribution in scaffolds. This study sought to correlate wall shear stress and chondrocytes activity for engineering design of micro-porous osteochondral grafts based on the hypothesis that it is possible to capture and discriminate between the transmitted force and cell response at the inner irregularities. Unlike common tissue engineering therapies with perfusion bioreactors in which flow-mediated stress is the controlling parameter, this work assigned the associated stress as a function of porosity to influence in vitro proliferation of chondrocytes. D-optimality criterion was used to accommodate three pore characteristics for appraisal in a mixed level fractional design of experiment (DOE); namely, pore size (4 levels), distribution pattern (2 levels) and density (3 levels). Micro-porous scaffolds (n=12) were fabricated according to the DOE using rapid prototyping of an acrylic-based bio-photopolymer. Computational fluid dynamics (CFD) models were created correspondingly and used on an idealized boundary condition with a Newtonian fluid domain to simulate the dynamic microenvironment inside the pores. In vitro condition was reproduced for the 3D printed constructs seeded by high pellet densities of human chondrocytes and cultured for 72 hours. The results showed that cell proliferation was significantly different in the constructs (p<0.05). Inlet fluid velocity of 3×10-2mms-1 and average shear stress of 5.65×10-2 Pa corresponded with increased cell proliferation for scaffolds with smaller pores in hexagonal pattern and lower densities. Although the analytical solution of a Poiseuille flow inside the pores was found insufficient for the description of the flow profile probably due to the outside flow induced turbulence, it showed that the shear stress would increase with cell growth and decrease with pore size. This correlation demonstrated the basis for determining the relation between the induced stress and chondrocyte activity to optimize microfabrication of engineered cartilaginous constructs.

Electrocatalytically switchable CO2 capture : first principle computational exploration of carbon nanotubes with pyridinic nitrogen

Carbon nanotubes with specific nitrogen doping are proposed for controllable, highly selective, and reversible CO2 capture. Using density functional theory incorporating long-range dispersion corrections, we investigated the adsorption behavior of CO2 on (7,7) single-walled carbon nanotubes (CNTs) with several nitrogen doping configurations and varying charge states. Pyridinic-nitrogen incorporation in CNTs is found to induce an increasing CO2 adsorption strength with electron injecting, leading to a highly selective CO2 adsorption in comparison with N2. This functionality could induce intrinsically reversible CO2 adsorption as capture/release can be controlled by switching the charge carrying state of the system on/off. This phenomenon is verified for a number of different models and theoretical methods, with clear ramifications for the possibility of implementation with a broader class of graphene-based materials. A scheme for the implementation of this remarkable reversible electrocatalytic CO2-capture phenomenon is considered.

Supplementary information : weighted tree kernels for sequence analysis

Genomic sequences are fundamentally text documents, admitting various representations according to need and tokenization. Gene expression depends crucially on binding of enzymes to the DNA sequence at small, poorly conserved binding sites, limiting the utility of standard pattern search. However, one may exploit the regular syntactic structure of the enzyme's component proteins and the corresponding binding sites, framing the problem as one of detecting grammatically correct genomic phrases. In this paper we propose new kernels based on weighted tree structures, traversing the paths within them to capture the features which underpin the task. Experimentally, we and that these kernels provide performance comparable with state of the art approaches for this problem, while offering significant computational advantages over earlier methods. The methods proposed may be applied to a broad range of sequence or tree-structured data in molecular biology and other domains.

A computational study of carbon dioxide adsorption on solid boron

Capturing and sequestering carbon dioxide (CO2) can provide a route to partial mitigation of climate change associated with anthropogenic CO2 emissions. Here we report a comprehensive theoretical study of CO2 adsorption on two phases of boron, α-B12 and γ-B28. The theoretical results demonstrate that the electron deficient boron materials, such as α-B12 and γ-B28, can bond strongly with CO2 due to Lewis acid-base interactions because the electron density is higher on their surfaces. In order to evaluate the capacity of these boron materials for CO2 capture, we also performed calculations with various degrees of CO2 coverage. The computational results indicate CO2 capture on the boron phases is a kinetically and thermodynamically feasible process, and therefore from this perspective these boron materials are predicted to be good candidates for CO2 capture.

A multiscale road map of cancer spheroids : incorporating experimental and mathematical modelling to understand cancer progression

Computational models represent a highly suitable framework, not only for testing biological hypotheses and generating new ones but also for optimising experimental strategies. As one surveys the literature devoted to cancer modelling, it is obvious that immense progress has been made in applying simulation techniques to the study of cancer biology, although the full impact has yet to be realised. For example, there are excellent models to describe cancer incidence rates or factors for early disease detection, but these predictions are unable to explain the functional and molecular changes that are associated with tumour progression. In addition, it is crucial that interactions between mechanical effects, and intracellular and intercellular signalling are incorporated in order to understand cancer growth, its interaction with the extracellular microenvironment and invasion of secondary sites. There is a compelling need to tailor new, physiologically relevant in silico models that are specialised for particular types of cancer, such as ovarian cancer owing to its unique route of metastasis, which are capable of investigating anti-cancer therapies, and generating both qualitative and quantitative predictions. This Commentary will focus on how computational simulation approaches can advance our understanding of ovarian cancer progression and treatment, in particular, with the help of multicellular cancer spheroids, and thus, can inform biological hypothesis and experimental design.

Consensus σ70 promoter prediction using hadoop

MapReduce frameworks such as Hadoop are well suited to handling large sets of data which can be processed separately and independently, with canonical applications in information retrieval and sales record analysis. Rapid advances in sequencing technology have ensured an explosion in the availability of genomic data, with a consequent rise in the importance of large scale comparative genomics, often involving operations and data relationships which deviate from the classical Map Reduce structure. This work examines the application of Hadoop to patterns of this nature, using as our focus a wellestablished workflow for identifying promoters - binding sites for regulatory proteins - Across multiple gene regions and organisms, coupled with the unifying step of assembling these results into a consensus sequence. Our approach demonstrates the utility of Hadoop for problems of this nature, showing how the tyranny of the "dominant decomposition" can be at least partially overcome. It also demonstrates how load balance and the granularity of parallelism can be optimized by pre-processing that splits and reorganizes input files, allowing a wide range of related problems to be brought under the same computational umbrella.

Reaction of Aromatic Peroxyl Radicals with Alkynes: A Mass Spectrometric and Computational Study Using the Distonic Radical Ion Approach

The reaction of the aromatic distonic peroxyl radical cations N-methyl pyridinium-4-peroxyl (PyrOO center dot+) and 4-(N,N,N-trimethyl ammonium)-phenyl peroxyl (AnOO center dot+), with symmetrical dialkyl alkynes 10?ac was studied in the gas phase by mass spectrometry. PyrOO center dot+ and AnOO center dot+ were produced through reaction of the respective distonic aryl radical cations Pyr center dot+ and An center dot+ with oxygen, O2. For the reaction of Pyr center dot+ with O2 an absolute rate coefficient of k1=7.1X10-12 cm3 molecule-1 s-1 and a collision efficiency of 1.2?% was determined at 298 K. The strongly electrophilic PyrOO center dot+ reacts with 3-hexyne and 4-octyne with absolute rate coefficients of khexyne=1.5X10-10 cm3 molecule-1 s-1 and koctyne=2.8X10-10 cm3 molecule-1 s-1, respectively, at 298 K. The reaction of both PyrOO center dot+ and AnOO center dot+ proceeds by radical addition to the alkyne, whereas propargylic hydrogen abstraction was observed as a very minor pathway only in the reactions involving PyrOO center dot+. A major reaction pathway of the vinyl radicals 11 formed upon PyrOO center dot+ addition to the alkynes involves gamma-fragmentation of the peroxy O?O bond and formation of PyrO center dot+. The PyrO center dot+ is rapidly trapped by intermolecular hydrogen abstraction, presumably from a propargylic methylene group in the alkyne. The reaction of the less electrophilic AnOO center dot+ with alkynes is considerably slower and resulted in formation of AnO center dot+ as the only charged product. These findings suggest that electrophilic aromatic peroxyl radicals act as oxygen atom donors, which can be used to generate alpha-oxo carbenes 13 (or isomeric species) from alkynes in a single step. Besides gamma-fragmentation, a number of competing unimolecular dissociative reactions also occur in vinyl radicals 11. The potential energy diagrams of these reactions were explored with density functional theory and ab initio methods, which enabled identification of the chemical structures of the most important products.

A comparison of the gas phase acidities of phospholipid headgroups: Experimental and computational studies

Proton-bound dimers consisting of two glycerophospholipids with different headgroups were prepared using negative ion electrospray ionization and dissociated in a triple quadrupole mass spectrometer. Analysis of the tandem mass spectra of the dimers using the kinetic method provides, for the first time, an order of acidity for the phospholipid classes in the gas phase of PE < PA << PG < PS < PI. Hybrid density functional calculations on model phospholipids were used to predict the absolute deprotonation enthalpies of the phospholipid classes from isodesmic proton transfer reactions with phosphoric acid. The computational data largely support the experimental acidity trend, with the exception of the relative acidity ranking of the two most acidic phospholipid species. Possible causes of the discrepancy between experiment and theory are discussed and the experimental trend is recommended. The sequence of gas phase acidities for the phospholipid headgroups is found to (1) have little correlation with the relative ionization efficiencies of the phospholipid classes observed in the negative ion electrospray process, and (2) correlate well with fragmentation trends observed upon collisional activation of phospholipid \[M - H](-) anions. (c) 2005 American Society for Mass Spectrometry.

Using performance-based evaluation to close the loop between biological and robotic navigation

In this paper we describe the benefits of a performance-based approach to modeling biological systems for use in robotics. Specifically, we describe the RatSLAM system, a computational model of the navigation processes thought to drive navigation in a part of the rodent brain called the hippocampus. Unlike typical computational modeling approaches, which focus on biological fidelity, RatSLAM’s development cycle has been driven primarily by performance evaluation on robots navigating in a wide variety of challenging, real world environments. We briefly describe three seminal results, two in robotics and one in biology. In addition, we present current research on brain-inspired learning algorithms with the aim of enabling a robot to autonomously learn how best to use its sensor suite to navigate, without requiring any specific knowledge of the robot, sensor types or environment characteristics. Our aim is to drive discussion on the merits of practical, performance-focused implementations of biological models in robotics.

Supplementary material : large scale read classification for next generation sequencing

Next Generation Sequencing (NGS) has revolutionised molecular biology, resulting in an explosion of data sets and an increasing role in clinical practice. Such applications necessarily require rapid identification of the organism as a prelude to annotation and further analysis. NGS data consist of a substantial number of short sequence reads, given context through downstream assembly and annotation, a process requiring reads consistent with the assumed species or species group. Highly accurate results have been obtained for restricted sets using SVM classifiers, but such methods are difficult to parallelise and success depends on careful attention to feature selection. This work examines the problem at very large scale, using a mix of synthetic and real data with a view to determining the overall structure of the problem and the effectiveness of parallel ensembles of simpler classifiers (principally random forests) in addressing the challenges of large scale genomics.