The readability of textual materials in biology

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The discourse of biology lectures : aspects of its mode and text structure

The present thesis investigates mode related aspects in biology lecture discourse and attempts to identify the position of this variety along the spontaneous spoken versus planned written language continuum. Nine lectures (of 43,000 words) consisting of three sets of three lectures each, given by the three lecturers at Aston University, make up the corpus. The indeterminacy of the results obtained from the investigation of grammatical complexity as measured in subordination motivates the need to take the analysis beyond sentence level to the study of mode related aspects in the use of sentence-initial connectives, sub-topic shifting and paraphrase. It is found that biology lecture discourse combines features typical of speech and writing at sentence as well as discourse level: thus, subordination is more used than co-ordination, but one degree complexity sentence is favoured; some sentence initial connectives are only found in uses typical of spoken language but sub-topic shift signalling (generally introduced by a connective) typical of planned written language is a major feature of the lectures; syntactic and lexical revision and repetition, interrupted structures are found in the sub-topic shift signalling utterance and paraphrase, but the text is also amenable to analysis into sentence like units. On the other hand, it is also found that: (1) while there are some differences in the use of a given feature, inter-speaker variation is on the whole not significant; (2) mode related aspects are often motivated by the didactic function of the variety; and (3) the structuring of the text follows a sequencing whose boundaries are marked by sub-topic shifting and the summary paraphrase. This study enables us to draw four theoretical conclusions: (1) mode related aspects cannot be approached as a simple dichotomy since a combination of aspects of both speech and writing are found in a given feature. It is necessary to go to the level of textual features to identify mode related aspects; (2) homogeneity is dominant in this sample of lectures which suggests that there is a high level of standardization in this variety; (3) the didactic function of the variety is manifested in some mode related aspects; (4) the features studied play a role in the structuring of the text.

Reporter ion-based mass spectrometry approaches for the detection of non-enzymatic protein modifications in biological samples

Development of mass spectrometry techniques to detect protein oxidation, which contributes to signalling and inflammation, is important. Label-free approaches have the advantage of reduced sample manipulation, but are challenging in complex samples owing to undirected analysis of large data sets using statistical search engines. To identify oxidised proteins in biological samples, we previously developed a targeted approach involving precursor ion scanning for diagnostic MS3 ions from oxidised residues. Here, we tested this approach for other oxidations, and compared it with an alternative approach involving the use of extracted ion chromatograms (XICs) generated from high-resolution MSMS data using very narrow mass windows. This accurate mass XIC data methodology was effective at identifying nitrotyrosine, chlorotyrosine, and oxidative deamination of lysine, and for tyrosine oxidations highlighted more modified peptide species than precursor ion scanning or statistical database searches. Although some false positive peaks still occurred in the XICs, these could be identified by comparative assessment of the peak intensities. The method has the advantage that a number of different modifications can be analysed simultaneously in a single LC-MSMS run. This article is part of a Special Issue entitled: Posttranslational Protein modifications in biology and Medicine. Biological significance: The use of accurate mass extracted product ion chromatograms to detect oxidised peptides could improve the identification of oxidatively damaged proteins in inflammatory conditions. © 2013 Elsevier B.V.

A survey of self-awareness and its application in computing systems

Novel computing systems are increasingly being composed of large numbers of heterogeneous components, each with potentially different goals or local perspectives, and connected in networks which change over time. Management of such systems quickly becomes infeasible for humans. As such, future computing systems should be able to achieve advanced levels of autonomous behaviour. In this context, the system's ability to be self-aware and be able to self-express becomes important. This paper surveys definitions and current understanding of self-awareness and self-expression in biology and cognitive science. Subsequently, previous efforts to apply these concepts to computing systems are described. This has enabled the development of novel working definitions for self-awareness and self-expression within the context of computing systems.

Like grandfather, like grandson: Erasmus and Charles Darwin on evolution

Last year (2009) marked the bicentenary of Charles Darwin's birth and the sesquicentenary of The Origin of Species. This article examines the influence of Erasmus Darwin on Charles's evolutionary thought and shows how, in many ways, Erasmus anticipated his much better-known grandson. It discusses the similarity in the mindsets of the two Darwins, asks how far the younger Darwin was exposed to the elder's evolutionary thought, examines the similarities and differences in their theories of evolution, and ends by showing the surprising similarity between their theories of inheritance. Erasmus's influence on Charles is greater than customarily acknowledged, and now is an opportune time to bring the grandfather out from behind the glare of his stellar grandson.

The mammalian MAPK/ERK pathway exhibits properties of a negative feedback amplifier

Three-tiered kinase modules, such as the Raf-MEK (mitogen-activated or extracellular signal-regulated protein kinase kinase)-ERK (extracellular signal-regulated kinase) mitogen-activated protein kinase pathway, are widespread in biology, suggesting that this structure conveys evolutionarily advantageous properties. We show that the three-tiered kinase amplifier module combined with negative feedback recapitulates the design principles of a negative feedback amplifier (NFA), which is used in electronic circuits to confer robustness, output stabilization, and linearization of nonlinear signal amplification. We used mathematical modeling and experimental validation to demonstrate that the ERK pathway has properties of an NFA that (i) converts intrinsic switch-like activation kinetics into graded linear responses, (ii) conveys robustness to changes in rates of reactions within the NFA module, and (iii) stabilizes outputs in response to drug-induced perturbations of the amplifier. These properties determine biological behavior, including activation kinetics and the response to drugs.

Lipoxidation adducts with peptides and proteins:deleterious modifications or signalling mechanisms?

Protein lipoxidation refers to the modification by electrophilic lipid oxidation products to form covalent adducts, which for many years has been considered as a deleterious consequence of oxidative stress. Oxidized lipids or phospholipids containing carbonyl moieties react readily with lysine to form Schiff bases; alternatively, oxidation products containing α,β-unsaturated moieties are susceptible to nucleophilic attack by cysteine, histidine or lysine residues to yield Michael adducts, overall corresponding to a large number of possible protein adducts. The most common detection methods for lipoxidized proteins take advantage of the presence of reactive carbonyl groups to add labels, or use antibodies. These methods have limitations in terms of specificity and identification of the modification site. The latter question is satisfactorily addressed by mass spectrometry, which enables the characterization of the adduct structure. This has allowed the identification of lipoxidized proteins in physiological and pathological situations. While in many cases lipoxidation interferes with protein function, causing inhibition of enzymatic activity and increased immunogenicity, there are a small number of cases where lipoxidation results in gain of function or activity. For certain proteins lipoxidation may represent a form of redox signaling, although more work is required to confirm the physiological relevance and mechanisms of such processes. This article is part of a Special Issue entitled: Posttranslational Protein modifications in biology and Medicine. © 2013 Elsevier B.V.

Stabilising cysteinyl thiol oxidation and nitrosation for proteomic analysis

Oxidation and S-nitrosylation of cysteinyl thiols (Cys-SH) to sulfenic (Cys-SOH), sulfinic (Cys-SO2H), sulfonic acids (Cys-SO3H), disulphides and S-nitrosothiols are suggested as important post-translational modifications that can activate or deactivate the function of many proteins. Non-enzymatic post-translational modifications to cysteinyl thiols have been implicated in a wide variety of physiological and pathophysiological states but have been difficult to monitor in a physiological setting because of a lack of experimental tools. The purpose of this review is to bring together the approaches that have been developed for stably trapping cysteine either in its reduced or oxidised forms for enrichment and or subsequent mass spectrometric analysis. These tools are providing insight into potential targets for post-translational modifications to cysteine modification in vivo. This article is part of a Special Issue entitled: Special Issue: Posttranslational Protein modifications in biology and Medicine. © 2013.

Statnote 36: Do the data fit the Poisson distribution

In previous Statnotes, many of the statistical tests described rely on the assumption that the data are a random sample from a normal or Gaussian distribution. These include most of the tests in common usage such as the ‘t’ test ), the various types of analysis of variance (ANOVA), and Pearson’s correlation coefficient (‘r’) . In microbiology research, however, not all variables can be assumed to follow a normal distribution. Yeast populations, for example, are a notable feature of freshwater habitats, representatives of over 100 genera having been recorded . Most common are the ‘red yeasts’ such as Rhodotorula, Rhodosporidium, and Sporobolomyces and ‘black yeasts’ such as Aurobasidium pelculans, together with species of Candida. Despite the abundance of genera and species, the overall density of an individual species in freshwater is likely to be low and hence, samples taken from such a population will contain very low numbers of cells. A rare organism living in an aquatic environment may be distributed more or less at random in a volume of water and therefore, samples taken from such an environment may result in counts which are more likely to be distributed according to the Poisson than the normal distribution. The Poisson distribution was named after the French mathematician Siméon Poisson (1781-1840) and has many applications in biology, especially in describing rare or randomly distributed events, e.g., the number of mutations in a given sequence of DNA after exposure to a fixed amount of radiation or the number of cells infected by a virus given a fixed level of exposure. This Statnote describes how to fit the Poisson distribution to counts of yeast cells in samples taken from a freshwater lake.

Visualisation of bioinformatics datasets

Analysing the molecular polymorphism and interactions of DNA, RNA and proteins is of fundamental importance in biology. Predicting functions of polymorphic molecules is important in order to design more effective medicines. Analysing major histocompatibility complex (MHC) polymorphism is important for mate choice, epitope-based vaccine design and transplantation rejection etc. Most of the existing exploratory approaches cannot analyse these datasets because of the large number of molecules with a high number of descriptors per molecule. This thesis develops novel methods for data projection in order to explore high dimensional biological dataset by visualising them in a low-dimensional space. With increasing dimensionality, some existing data visualisation methods such as generative topographic mapping (GTM) become computationally intractable. We propose variants of these methods, where we use log-transformations at certain steps of expectation maximisation (EM) based parameter learning process, to make them tractable for high-dimensional datasets. We demonstrate these proposed variants both for synthetic and electrostatic potential dataset of MHC class-I. We also propose to extend a latent trait model (LTM), suitable for visualising high dimensional discrete data, to simultaneously estimate feature saliency as an integrated part of the parameter learning process of a visualisation model. This LTM variant not only gives better visualisation by modifying the project map based on feature relevance, but also helps users to assess the significance of each feature. Another problem which is not addressed much in the literature is the visualisation of mixed-type data. We propose to combine GTM and LTM in a principled way where appropriate noise models are used for each type of data in order to visualise mixed-type data in a single plot. We call this model a generalised GTM (GGTM). We also propose to extend GGTM model to estimate feature saliencies while training a visualisation model and this is called GGTM with feature saliency (GGTM-FS). We demonstrate effectiveness of these proposed models both for synthetic and real datasets. We evaluate visualisation quality using quality metrics such as distance distortion measure and rank based measures: trustworthiness, continuity, mean relative rank errors with respect to data space and latent space. In cases where the labels are known we also use quality metrics of KL divergence and nearest neighbour classifications error in order to determine the separation between classes. We demonstrate the efficacy of these proposed models both for synthetic and real biological datasets with a main focus on the MHC class-I dataset.

Fiber optically integrated cost-effective spectrometer for optical coherence tomography

A tilted fiber Bragg grating (TFBG) was integrated as the dispersive element in a high performance biomedical imaging system. The spectrum emitted by the 23 mm long active region of the fiber is projected through custom designed optics consisting of a cylindrical lens for vertical beam collimation and successively by an achromatic doublet onto a linear detector array. High resolution tomograms of biomedical samples were successfully acquired by the frequency domain OCT-system. Tomograms of ophthalmic and dermal samples obtained by the frequency domain OCT-system were obtained achieving 2.84 μm axial and 10.2 μm lateral resolution. The miniaturization reduces costs and has the potential to further extend the field of application for OCT-systems in biology, medicine and technology. © 2014 SPIE.

Philosophy's loss, neurology's gain:the endeavor of John Hughlings-Jackson

The year 2011 marked the centenary of the death of one of the founders of British neurology, John Hughlings-Jackson (1835-1911). By common consent he was a great clinician. But he was more. He endeavored to use clinical observations to throw light on one of the great problems of the modern world, the problem of mind. Hughlings-Jackson's daily contact with mentalities warped by neurological disease caused him to ponder deeply the nature of the mind-brain relationship, nowadays often known simply as the "hard problem. " In particular, he saw the danger of conflating mind and brain, a danger that has grown greater with the spectacular growth of neuroscientific knowledge during the last century. Although Hughlings-Jackson's neuroscientific thought is long outdated, his philosophic endeavors remain highly instructive. © 2012 by The Johns Hopkins University Press.

Three-factor models versus time series models:quantifying time-dependencies of interactions between stimuli in cell biology and psychobiology for short longitudinal data

Signal integration determines cell fate on the cellular level, affects cognitive processes and affective responses on the behavioural level, and is likely to be involved in psychoneurobiological processes underlying mood disorders. Interactions between stimuli may subjected to time effects. Time-dependencies of interactions between stimuli typically lead to complex cell responses and complex responses on the behavioural level. We show that both three-factor models and time series models can be used to uncover such time-dependencies. However, we argue that for short longitudinal data the three factor modelling approach is more suitable. In order to illustrate both approaches, we re-analysed previously published short longitudinal data sets. We found that in human embryonic kidney 293 cells cells the interaction effect in the regulation of extracellular signal-regulated kinase (ERK) 1 signalling activation by insulin and epidermal growth factor is subjected to a time effect and dramatically decays at peak values of ERK activation. In contrast, we found that the interaction effect induced by hypoxia and tumour necrosis factor-alpha for the transcriptional activity of the human cyclo-oxygenase-2 promoter in HEK293 cells is time invariant at least in the first 12-h time window after stimulation. Furthermore, we applied the three-factor model to previously reported animal studies. In these studies, memory storage was found to be subjected to an interaction effect of the beta-adrenoceptor agonist clenbuterol and certain antagonists acting on the alpha-1-adrenoceptor / glucocorticoid-receptor system. Our model-based analysis suggests that only if the antagonist drug is administer in a critical time window, then the interaction effect is relevant.

The molecular biology of senile plaques and neurofibrillary tangles in Alzheimer’s disease

Since the earliest descriptions of the disease, senile plaques (SP) and neurofibrillary tangles (NFT) have been regarded as the pathological 'hallmarks' of Alzheimer's disease (AD). Whether or not SP and NFT are sufficient cause to explain the neurodegeneration of AD is controversial. The major molecular constituents of these lesions, viz., beta-amyloid (Ass) and tau, have played a defining role both in the diagnosis of the disease and in studies of pathogenesis. The molecular biology of SP and NFT, however, is complex with many chemical constituents. An individual constituent could be the residue of a pathogenic gene mutation, result from cellular degeneration, or reflect the acquisition of new proteins by diffusion and molecular binding. This review proposes that the molecular composition of SP and NFT is largely a consequence of cell degeneration and the later acquisition of proteins. Such a conclusion has implications both for the diagnosis of AD and in studies of disease pathogenesis.