Utilisation of remote sensing for the study of debris-covered glaciers : development and testing of techniques on Miage Glacier, Italian Alps

An increase in the number of debris-covered glaciers and expansion of debris cover across many glaciers has been documented in many of the world’s major glacierised mountain ranges over the last 100 years. Debris cover has a profound impact on glacier mass balance with thick layers insulating the underlying ice and dramatically reducing ablation, while thin or patchy cover accelerates ablation through albedo reduction. Few debris-covered glaciers have been studied in comparison with ‘clean’ glaciers and their response to climatic change is uncertain. Remote sensing, integrated with field data, offers a powerful but as yet unrealised tool for studying and monitoring changes in debris-covered glaciers. Hence, this thesis focuses on two key aims: i) to test the utility of visible/near infrared satellite sensors, such as TERRA ASTER, for studying debris-covered glaciers; ii) to develop techniques to fully exploit the capability of these satellite sensors to extract useful information, and monitor changes over time. Research was focused on four interrelated studies at the Miage Glacier, in the Italian Alps. First, a new method of extracting debris-thickness patterns from ASTER thermal-band imagery was developed, based on a physical energy-balance model for a debris surface. The method was found to be more accurate than previous empirical approaches, when compared with field thickness measurements, and has the potential advantage of transferability to other sites. The high spatial variability of 2 m air temperature, which does not conform to a standard lapse rate, presents a difficulty for this approach and was identified as an important area for future research. Secondly, ASTER and Landsat TM data are used to map debris-cover extent and its change over time using several different methods. A number of problems were encountered in mapping debris extent including cloud cover and snow confusion, spatial resolution, and identifying the boundary between continuous and sporadic debris. Analysis of two images in late summer 1990 and 2004 revealed only a small up glacier increase in debris cover has occurred, confirming other work’s conclusions that the debris cover on Miage Glacier increased to its present extent prior to the 1990s. A third area of research used ASTER DEMs to monitor surface elevation changes of the Miage Glacier over time to update previous studies. Surface velocities on the glacier tongue were also calculated between 2004-2005 using feature-tracking of ASTER orthorectified visible band imagery and ASTER DEMs. However, ASTER DEMs were found to be rather poor for both applications due to large elevation errors in topographically rough parts of the glacier, which prevented a full analysis and comparison of results to previous surface elevation and velocity studies. Finally, the lithological units of the debris cover were mapped, based on the spectral differences of different rock types in the debris layer, providing information both on the location and concentration of different rock types on the surface. Therefore, the identification in the variation in emissivity throughout the glacier surface can be identified, which in turn has an impact upon calculated surface temperatures and ablation respectively. Overall, this research presents a significant contribution to understanding the impact of a debris layer on an alpine glacier, which is an area of key interest and current focus of many present glaciological studies. Since future glacial monitoring will increasingly have to consider supraglacial debris cover as a common occurrence, due to climate warming impacts of glacial retreat and permafrost melting. This contribution is achieved through the successful application of methods which utilise ASTER data to estimate debris thickness and debris extent, and the lithological mapping of debris cover. Therefore, the potential for incorporating these remote sensing techniques for debris-covered glaciers into current global glacier monitoring programs has been highlighted. However the utility of ASTER derived DEMs for surface elevation change analysis and surface velocity estimations in a study site of steep and varied terrain has been identified as questionable, due to issues of ASTER DEM accuracy in these regions.EThOS - Electronic Theses Online ServiceCarnegie Trust for the Universities of Scotland : Remote Sensing and Photogrammetry SocietyGBUnited Kingdo

Utilisation of remote sensing for the study of debris-covered glaciers : development and testing of techniques on Miage Glacier, Italian Alps

An increase in the number of debris-covered glaciers and expansion of debris cover across many glaciers has been documented in many of the world’s major glacierised mountain ranges over the last 100 years. Debris cover has a profound impact on glacier mass balance with thick layers insulating the underlying ice and dramatically reducing ablation, while thin or patchy cover accelerates ablation through albedo reduction. Few debris-covered glaciers have been studied in comparison with ‘clean’ glaciers and their response to climatic change is uncertain. Remote sensing, integrated with field data, offers a powerful but as yet unrealised tool for studying and monitoring changes in debris-covered glaciers. Hence, this thesis focuses on two key aims: i) to test the utility of visible/near infrared satellite sensors, such as TERRA ASTER, for studying debris-covered glaciers; ii) to develop techniques to fully exploit the capability of these satellite sensors to extract useful information, and monitor changes over time. Research was focused on four interrelated studies at the Miage Glacier, in the Italian Alps. First, a new method of extracting debris-thickness patterns from ASTER thermal-band imagery was developed, based on a physical energy-balance model for a debris surface. The method was found to be more accurate than previous empirical approaches, when compared with field thickness measurements, and has the potential advantage of transferability to other sites. The high spatial variability of 2 m air temperature, which does not conform to a standard lapse rate, presents a difficulty for this approach and was identified as an important area for future research. Secondly, ASTER and Landsat TM data are used to map debris-cover extent and its change over time using several different methods. A number of problems were encountered in mapping debris extent including cloud cover and snow confusion, spatial resolution, and identifying the boundary between continuous and sporadic debris. Analysis of two images in late summer 1990 and 2004 revealed only a small up glacier increase in debris cover has occurred, confirming other work’s conclusions that the debris cover on Miage Glacier increased to its present extent prior to the 1990s. A third area of research used ASTER DEMs to monitor surface elevation changes of the Miage Glacier over time to update previous studies. Surface velocities on the glacier tongue were also calculated between 2004-2005 using feature-tracking of ASTER orthorectified visible band imagery and ASTER DEMs. However, ASTER DEMs were found to be rather poor for both applications due to large elevation errors in topographically rough parts of the glacier, which prevented a full analysis and comparison of results to previous surface elevation and velocity studies. Finally, the lithological units of the debris cover were mapped, based on the spectral differences of different rock types in the debris layer, providing information both on the location and concentration of different rock types on the surface. Therefore, the identification in the variation in emissivity throughout the glacier surface can be identified, which in turn has an impact upon calculated surface temperatures and ablation respectively. Overall, this research presents a significant contribution to understanding the impact of a debris layer on an alpine glacier, which is an area of key interest and current focus of many present glaciological studies. Since future glacial monitoring will increasingly have to consider supraglacial debris cover as a common occurrence, due to climate warming impacts of glacial retreat and permafrost melting. This contribution is achieved through the successful application of methods which utilise ASTER data to estimate debris thickness and debris extent, and the lithological mapping of debris cover. Therefore, the potential for incorporating these remote sensing techniques for debris-covered glaciers into current global glacier monitoring programs has been highlighted. However the utility of ASTER derived DEMs for surface elevation change analysis and surface velocity estimations in a study site of steep and varied terrain has been identified as questionable, due to issues of ASTER DEM accuracy in these regions.EThOS - Electronic Theses Online ServiceCarnegie Trust for the Universities of Scotland : Remote Sensing and Photogrammetry SocietyGBUnited Kingdo

Multiplex ligation-dependent probe amplification (MLPA) analysis is an effective tool for the detection of novel intragenic PLA2G6 mutations: Implications for molecular diagnosis

Phospholipase associated neurodegeneration (PLAN) comprises a heterogeneous group of autosomal recessive neurological disorders caused by mutations in the PLA2G6 gene. Direct gene sequencing detects 85% mutations in infantile neuroaxonal dystrophy. We report the novel use of multiplex ligation-dependent probe amplification (MLPA) analysis to detect novel PLA2G6 duplications and deletions. The identification of such copy number variants (CNVs) expands the PLAN mutation spectrum and may account for up to 12.5% of PLA2G6 mutations. MLPA should thus be employed to detect CNVs of PLA2G6 in patients who show clinical features of PLAN but in whom both disease-causing mutations cannot be identified on routine sequencin

A web-based intervention (RESTORE) to support self-management of cancer-related fatigue following primary cancer treatment: a multi-centre proof of concept randomised controlled trial

Purpose: Cancer-related fatigue (CRF) is a frequent and distressing symptom experienced after cancer treatment. RESTORE is the first web-based resource designed to enhance self-efficacy to manage CRF following curative-intent treatment. The aim of this study is to test the proof of concept and inform the design of an effectiveness trial. Methods: A multi-centre parallel-group two-armed (1:1) exploratory randomised controlled trial (RCT) with qualitative process evaluation was employed in the study. Participants (≥18 years; ≤5 years post treatment with moderate to severe fatigue) were recruited and randomly assigned to RESTORE or a leaflet. Feasibility and acceptability were measured by recruitment, attrition, intervention adherence, completion of outcome measures and process evaluation. Change in self-efficacy to manage CRF was also explored. Outcome measures were completed at baseline (T0), 6 weeks (T1) and 12 weeks (T2). Data were analysed using mixed-effects linear regression and directed content analysis. Results: One hundred and sixty-three people participated in the trial and 19 in the process evaluation. The intervention was feasible (39 % of eligible patients consented) and acceptable (attrition rate 36 %). There was evidence of higher fatigue self-efficacy at T1 in the intervention group vs comparator (mean difference 0.51 [−0.08 to 1.11]), though the difference in groups decreased by 12 weeks. Time since diagnosis influenced perceived usefulness of the intervention. Modifications were suggested. Conclusion: Proof of concept was achieved. The RESTORE intervention should be subject to a definitive trial with some adjustments. Provision of an effective supportive resource would empower cancer survivors to manage CRF after treatment completion

Balancing the dilution and oddity effects: Decisions depend on body size

Background Grouping behaviour, common across the animal kingdom, is known to reduce an individual's risk of predation; particularly through dilution of individual risk and predator confusion (predator inability to single out an individual for attack). Theory predicts greater risk of predation to individuals more conspicuous to predators by difference in appearance from the group (the ‘oddity’ effect). Thus, animals should choose group mates close in appearance to themselves (eg. similar size), whilst also choosing a large group. Methodology and Principal Findings We used the Trinidadian guppy (Poecilia reticulata), a well known model species of group-living freshwater fish, in a series of binary choice trials investigating the outcome of conflict between preferences for large and phenotypically matched groups along a predation risk gradient. We found body-size dependent differences in the resultant social decisions. Large fish preferred shoaling with size-matched individuals, while small fish demonstrated no preference. There was a trend towards reduced preferences for the matched shoal under increased predation risk. Small fish were more active than large fish, moving between shoals more frequently. Activity levels increased as predation risk decreased. We found no effect of unmatched shoal size on preferences or activity. Conclusions and Significance Our results suggest that predation risk and individual body size act together to influence shoaling decisions. Oddity was more important for large than small fish, reducing in importance at higher predation risks. Dilution was potentially of limited importance at these shoal sizes. Activity levels may relate to how much sampling of each shoal was needed by the test fish during decision making. Predation pressure may select for better decision makers to survive to larger size, or that older, larger fish have learned to make shoaling decisions more efficiently, and this, combined with their size relative to shoal-mates, and attractiveness as prey items influences shoaling decisions

Prospective multicentre evaluation and refinement of an analysis tool for magnetic resonance spectroscopy of childhood cerebellar tumours

AbstractBackgroundA tool for diagnosing childhood cerebellar tumours using magnetic resonance (MR) spectroscopy peak height measurement has been developed based on retrospective analysis of single-centre data.ObjectiveTo determine the diagnostic accuracy of the peak height measurement tool in a multicentre prospective study, and optimise it by adding new prospective data to the original dataset.Materials and methodsMagnetic resonance imaging (MRI) and single-voxel MR spectroscopy were performed on children with cerebellar tumours at three centres. Spectra were processed using standard scanner software and peak heights for N-acetyl aspartate, creatine, total choline and myo-inositol were measured. The original diagnostic tool was used to classify 26 new tumours as pilocytic astrocytoma, medulloblastoma or ependymoma. These spectra were subsequently combined with the original dataset to develop an optimised scheme from 53 tumours in total.ResultsOf the pilocytic astrocytomas, medulloblastomas and ependymomas, 65.4% were correctly assigned using the original tool. An optimized scheme was produced from the combined dataset correctly assigning 90.6%. Rare tumour types showed distinctive MR spectroscopy features.ConclusionThe original diagnostic tool gave modest accuracy when tested prospectively on multicentre data. Increasing the dataset provided a diagnostic tool based on MR spectroscopy peak height measurement with high levels of accuracy for multicentre data

Integrative analyses identify modulators of response to neoadjuvant aromatase inhibitors in patients with early breast cancer

Introduction Aromatase inhibitors (AIs) are a vital component of estrogen receptor positive (ER+) breast cancer treatment. De novo and acquired resistance, however, is common. The aims of this study were to relate patterns of copy number aberrations to molecular and proliferative response to AIs, to study differences in the patterns of copy number aberrations between breast cancer samples pre- and post-AI neoadjuvant therapy, and to identify putative biomarkers for resistance to neoadjuvant AI therapy using an integrative analysis approach. Methods Samples from 84 patients derived from two neoadjuvant AI therapy trials were subjected to copy number profiling by microarray-based comparative genomic hybridisation (aCGH, n = 84), gene expression profiling (n = 47), matched pre- and post-AI aCGH (n = 19 pairs) and Ki67-based AI-response analysis (n = 39). Results Integrative analysis of these datasets identified a set of nine genes that, when amplified, were associated with a poor response to AIs, and were significantly overexpressed when amplified, including CHKA, LRP5 and SAPS3. Functional validation in vitro, using cell lines with and without amplification of these genes (SUM44, MDA-MB134-VI, T47D and MCF7) and a model of acquired AI-resistance (MCF7-LTED) identified CHKA as a gene that when amplified modulates estrogen receptor (ER)-driven proliferation, ER/estrogen response element (ERE) transactivation, expression of ER-regulated genes and phosphorylation of V-AKT murine thymoma viral oncogene homolog 1 (AKT1). Conclusions These data provide a rationale for investigation of the role of CHKA in further models of de novo and acquired resistance to AIs, and provide proof of concept that integrative genomic analyses can identify biologically relevant modulators of AI response