Studying the rate of convergence of gradient optimisation algorithms via the theory of optimal experimental design

The most common class of methods for solving quadratic optimisation problems is the class of gradient algorithms, the most famous of which being the Steepest Descent algorithm. The development of a particular gradient algorithm, the Barzilai-Borwein algorithm, has sparked a lot of research in the area in recent years and many algorithms now exist which have faster rates of convergence than that possessed by the Steepest Descent algorithm. The technology to effectively analyse and compare the asymptotic rates of convergence of gradient algorithms is, however, limited and so it is somewhat unclear from literature as to which algorithms possess the faster rates of convergence. In this thesis methodology is developed to enable better analysis of the asymptotic rates of convergence of gradient algorithms applied to quadratic optimisation problems. This methodology stems from a link with the theory of optimal experimental design. It is established that gradient algorithms can be related to algorithms for constructing optimal experimental designs for linear regression models. Furthermore, the asymptotic rates of convergence of these gradient algorithms can be expressed through the asymptotic behaviour of multiplicative algorithms for constructing optimal experimental designs. The described connection to optimal experimental design has also been used to influence the creation of several new gradient algorithms which would not have otherwise been intuitively thought of. The asymptotic rates of convergence of these algorithms are studied extensively and insight is given as to how some gradient algorithms are able to converge faster than others. It is demonstrated that the worst rates are obtained when the corresponding multiplicative procedure for updating the designs converges to the optimal design. Simulations reveal that the asymptotic rates of convergence of some of these new algorithms compare favourably with those of existing gradient-type algorithms such as the Barzilai-Borwein algorithm.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Time-aging time-stress superposition in soft glass under tensile deformation field

We have studied the tensile deformation behaviour of thin films of aging aqueous suspension of Laponite, a model soft glassy material, when subjected to a creep flow field generated by a constant engineering normal stress. Aqueous suspension of Laponite demonstrates aging behaviour wherein it undergoes time dependent enhancement of its elastic modulus as well as its characteristic relaxation time. However, under application of the normal stress, the rate of aging decreases and in the limit of high stress, the aging stops with the suspension now undergoing a plastic deformation. Overall, it is observed that the aging that occurs over short creep times at small normal stresses is same as the aging that occurs over long creep times at large normal stresses. This observation allows us to suggest an aging time - process time - normal stress superposition principle, which can predict rheological behaviour at longer times by carrying out short time tests.Comment: 26 pages, 7 figures, To appear in Rheologica Act

High inorganic phosphate intake promotes tumorigenesis at early stages in a mouse model of lung cancer

© 2015 Lee et al. Inorganic phosphate (Pi) is required by all living organisms for the development of organs such as bone, muscle, brain, and lungs, regulating the expression of several critical genes as well as signal transduction. However, little is known about the effects of prolonged dietary Pi consumption on lung cancer progression. This study investigated the effects of a highphosphate diet (HPD) in a mouse model of adenocarcinoma. K-rasLA1 mice were fed a normal diet (0.3% Pi) or an HPD (1% Pi) for 1, 2, or 4 months. Mice were then sacrificed and subjected to inductively coupled plasma mass/optical emission spectrometry and laser ablation inductively coupled plasma mass-spectrometry analyses, western blot analysis, histopathological, immunohistochemical, and immunocytochemical analyses to evaluate tumor formation and progression (including cell proliferation, angiogenesis, and apoptosis), changes in ion levels and metabolism, autophagy, epithelial-to-mesenchymal transition, and protein translation in the lungs. An HPD accelerated tumorigenesis, as evidenced by increased adenoma and adenocarcinoma rates as well as tumor size. However, after 4 months of the HPD, cell proliferation was arrested, and marked increases in liver and lung ion levels and in energy production via the tricarboxylic acid cycle in the liver were observed, which were accompanied by increased autophagy and decreased angiogenesis and apoptosis. These results indicate that an HPD initially promotes but later inhibits lung cancer progression because of metabolic adaptation leading to tumor cell quiescence. Moreover, the results suggest that carefully regulated Pi consumption are effective in lung cancer prevention

A Stratified Transcriptomics Analysis of Polygenic Fat and Lean Mouse Adipose Tissues Identifies Novel Candidate Obesity Genes

Obesity and metabolic syndrome results from a complex interaction between genetic and environmetal factors. In addition to brain-regulated processes, recent genome wide association studies have indicated that genes highly expressed in adipose tissue affect the distribution and function of fat and thus contribute to obesity. Using a stratified transcriptome gene enrichment approach we attempted to identify adipose tissue-specific obesity genes in the unique polygenic fat (F) mouse strain generated by selective breeding over 60 generations for divergent adiposity from a comparator lean (L) strain. To enrich for adipose tissue obesity genes a ˝snap-shot˝ pooled-sample transcriptome comparison of key fat depots and non adipose tissue (muscle, liver, kidney) was performed. Known obesity quantitative trait loci (QTL) information for the model allowed us to further filter genes for increased likelihood of being causal or secondary for obesity. This successfully identified several genes previously linked to obesity (C1qr1, and Np3r) as positional QTL candidate genes elevated specifically in F line adipose tissue.A number of novel obesity candidate genes were also identified (Thbs1, Ppp1rd, Tmepai, Trp53inp2, Ttc7b, Tuba1a, Fgf13, Fmr) that have inferred rolesin fat cell function. Quantitative microarray analysis was then applied to the most phenotypically divergent adipose depot after exaggerating F and L strain differences with chronic high fat feeding which revealed a dictinct gene expression profile of line, fat depot and diet-responsive inflammatory, angiogenic and metabolic pathaways. Selected candidate genes Npr3 and Thbs1, as well as Gys2, a non-QTL gene that otherwise passed our enrichment criteria were characterised, revealing novel functional effects consistent with a contribution to obesity. A focussed candidate gene enrichment strategy in the unique F and L model has identified novel adipose tissue-enriched genes contributing to obesity

Post-transcriptional gene regulation: From genome-wide studies to principles

Post-transcriptional regulation of gene expression plays important roles in diverse cellular processes such as development, metabolism and cancer progression. Whereas many classical studies explored the mechanistics and physiological impact on specific mRNA substrates, the recent development of genome-wide analysis tools enables the study of post-transcriptional gene regulation on a global scale. Importantly, these studies revealed distinct programs of RNA regulation, suggesting a complex and versatile post-transcriptional regulatory network. This network is controlled by specific RNA-binding proteins and/or non-coding RNAs, which bind to specific sequence or structural elements in the RNAs and thereby regulate subsets of mRNAs that partly encode functionally related proteins. It will be a future challenge to link the spectra of targets for RNA-binding proteins to post-transcriptional regulatory programs and to reveal its physiological implications

Extensive Gene-Specific Translational Reprogramming in a Model of B Cell Differentiation and Abl-Dependent Transformation

To what extent might the regulation of translation contribute to differentiation programs, or to the molecular pathogenesis of cancer? Pre-B cells transformed with the viral oncogene v-Abl are suspended in an immortalized, cycling state that mimics leukemias with a BCR-ABL1 translocation, such as Chronic Myelogenous Leukemia (CML) and Acute Lymphoblastic Leukemia (ALL). Inhibition of the oncogenic Abl kinase with imatinib reverses transformation, allowing progression to the next stage of B cell development. We employed a genome-wide polysome profiling assay called Gradient Encoding to investigate the extent and potential contribution of translational regulation to transformation and differentiation in v-Abl-transformed pre-B cells. Over half of the significantly translationally regulated genes did not change significantly at the level of mRNA abundance, revealing biology that might have been missed by measuring changes in transcript abundance alone. We found extensive, gene-specific changes in translation affecting genes with known roles in B cell signaling and differentiation, cancerous transformation, and cytoskeletal reorganization potentially affecting adhesion. These results highlight a major role for gene-specific translational regulation in remodeling the gene expression program in differentiation and malignant transformation