Radiomics and Machine Learning in the Prediction of Cardiovascular Disease

Carotid atherosclerosis is a major risk factor for ischaemic stroke which is a leading cause of death worldwide. For stroke survivors, 1 in 4 will have another stroke within five years. Carotid CT angiography (CTA) is commonly performed following an ischaemic stroke or transient ischemic attack to help guide patient management in the secondary prevention of stroke. For example, carotid endarterectomy surgery plus medical therapy or medical therapy alone. The degree of carotid stenosis is the mainstay in making this decision and uses only one aspect of anatomical information that can be obtained from a carotid CTA scan. Radiomics, sometimes called ‘texture analysis’, is the extraction of quantitative data from medical images that may not be apparent to the naked eye and has already demonstrated clinical utility in oncology for applications ranging from lesion characterisation to tumour grading and prognostication. Machine learning refers to the process of learning from experience (in this case data), rather than following pre-programmed rules. This thesis presents the findings of a proof-of-principle study to assess the value of radiomics in identifying the ‘vulnerable plaque’ and the ‘vulnerable patient’ within the context of cerebrovascular events. To evaluate the potential of radiomic features as imaging biomarkers, their reproducibility and robustness to morphological perturbations were assessed, as well as their biological associations with both PET and immunohistochemistry data. The ability of radiomic features to classify different carotid artery types, namely, culprit, non-culprit and asymptomatic carotid arteries was assessed using several machine learning classifiers. This was subsequently compared with a deep learning approach, which has greater capacity for data mining than feature-based machine learning approaches. Overall, radiomics could extract further useful information from carotid CTA scans. Culprit versus non-culprit carotid arteries in symptomatic patients and asymptomatic carotid arteries from asymptomatic patients had different radiomic profiles that could be leveraged using machine learning for better classification performance than carotid calcification or carotid PET imaging alone. Reliable and robust CT-based carotid radiomic features were identified that were associated with the degree of inflammation underlying the carotid artery. If validated with future prospective studies, this has the potential to improve personalised patient care in stroke management and advance clinical decision-making.Cambridge School of Clinical Medicine, the Medical Research Council's Doctoral Training Partnership and the Frank Edward Elmore Fun

Images out of water : aspects of the interpretation of Ancient maritime grafitti

Pictorial graffiti representing ships from prehistory, protohistory and the early medieval period are frequently examined by nautical historians and archaeologists seeking information about ancient ship technology. Examples of the academic discussion and interpretation of these images may be found from the nineteenth century to the present day, in a wide range of studies. Many of these works reflect their writers' casual, even disdainful attitudes to ancient graffiti. This may be seen in their approach to the information which these images appear to contain, which may concentrate, for example, on the certain aspects of particular subjects without reference to details in their immediate or wider contexts, which may have a bearing on the images' form and meaning. In a similar vein, other writers have interpreted ancient ship graffiti using concepts of art, such as the assumption of realism of depiction, which may be inappropriate to some early visual imagery. This thesis argues that ancient ship graffiti need a more detailed and systematic interpretation as both art and artefact before their contribution to nautical history may be more reliably evaluated. In order to explore the many challenges which these graffiti offer, a multi-disciplinary approach is used, to consider aspects of the relationship between formal art and graffiti, the psychology of image making, symbolism, the philosophy of interpretation, archaeology, and the social meaning of physical context. Following these theoretical discussions, five case studies from a number of different regional and chronological groups have been chosen to provide some examples of many of the issues which were considered. It is hoped that this study demonstrates that an approach to the interpretation of ancient ship graffiti which avoids a narrow concentration on nautical technology may reveal more of their potential as evidence, not only for the form and use of early ships, but also for other aspects of life in the past

Characterization of recombinant human lactoferrin N-glycans expressed in the milk of transgenic cows.

Lactoferrin (LF) is one of the most abundant bioactive glycoproteins in human milk. Glycans attached through N-glycosidic bonds may contribute to Lactoferrin functional activities. In contrast, LF is present in trace amounts in bovine milk. Efforts to increase LF concentration in bovine milk led to alternative approaches using transgenic cows to express human lactoferrin (hLF). This study investigated and compared N-glycans in recombinant human lactoferrin (rhLF), bovine lactoferrin (bLF) and human lactoferrin by Nano-LC-Chip-Q-TOF Mass Spectrometry. The results revealed a high diversity of N-glycan structures, including fucosylated and sialylated complex glycans that may contribute additional bioactivities. rhLF, bLF and hLF had 23, 27 and 18 N-glycans respectively with 8 N-glycan in common overall. rhLF shared 16 N-glycan with bLF and 9 N-glycan with hLF while bLF shared 10 N-glycan with hLF. Based on the relative abundances of N-glycan types, rhLF and hLF appeared to contain mostly neutral complex/hybrid N-glycans (81% and 52% of the total respectively) whereas bLF was characterized by high mannose glycans (65%). Interestingly, the majority of hLF N-glycans were fucosylated (88%), whereas bLF and rhLF had only 9% and 20% fucosylation, respectively. Overall, this study suggests that rhLF N-glycans share more similarities to bLF than hLF

Plasmon scattering from holes: from single hole scattering to Young's experiment

In this article, the scattering of surface plasmon polaritons (SPPs) into photons at holes is investigated. A local, electrically excited source of SPPs using a scanning tunnelling microscope (STM) produces an outgoing circular plasmon wave on a thick (200 nm) gold film on glass containing holes of 250, 500 and 1000 nm diameter. Fourier plane images of the photons from hole-scattered plasmons show that the larger the hole diameter, the more directional the scattered radiation. These results are confirmed by a model where the hole is considered as a distribution of horizontal dipoles whose relative amplitudes, directions, and phases depend linearly on the local SPP electric field. An SPP-Young's experiment is also performed, where the STM-excited SPP-wave is incident on a pair of 1 $\mu$m diameter holes in the thick gold film. The visibility of the resulting fringes in the Fourier plane is analyzed to show that the polarization of the electric field is maintained when SPPs scatter into photons. From this SPP-Young's experiment, an upper bound of $\approx$ 200 nm for the radius of this STM-excited source of surface plasmon polaritons is determined

Delivery of Family-Based Treatment for Adolescent Anorexia Nervosa in a Public Health Care Setting: Research Versus Non-Research Specialty Care.

Comparing evidence-based psychotherapy (EBP) to usual care typically demonstrates the superiority of EBPs, although this has not been studied for eating disorders EBPs such as family-based treatment (FBT). The current study set out to examine weight outcomes for adolescents with anorexia nervosa who received FBT through a randomized clinical research trial (RCT, n = 54) or non-research specialty care (n = 56) at the same specialist pediatric eating disorder service. Weight was recorded throughout outpatient treatment (up to 18 sessions over 6 months), as well as at 6- and 12-month follow-up. Survival curves were used to examine time to weight restoration [greater than 95% median body mass index (mBMI)] as predicted by type of care (RCT vs. non-research specialty care), baseline clinical and demographic characteristics, and their potential interaction. Results did not indicate a significant main effect for type of care, but there was a significant effect for baseline weight (p = .03), such that weight restoration was achieved faster across both treatment types for those with a higher initial %mBMI. These data suggest that weight restoration achieved in non-research specialty care FBT was largely similar to that achieved in a controlled research trial. Clinical Trial Registration:http://www.anzctr.org.au/, identifier ACTRN12610000216011

IDENTIFICATION OF FLOOR AND VAULTING APTITUDE IN 8·14 YEAR OLD TALENT-SELECTED FEMALE GYMNASTS

Training programs can be designed and monitored to maximise high aptitude for floor and vault when the key attributes are identified, and then used to recognize apparatus ability in talent-selected gymnasts. The aim of this study was to identify the anthropometric and physical prerequisites for high difficulty floor tumbling and vaulting. Twenty female gymnasts performed handstand push-offs, single and multiple jumps on a portable Kistler force plate. The gymnasts were also examined when sprinting, vaulting, and performing broad jumps. Each gymnast's best vault, three best noor tumbling skills and their anthropometric characteristics were also recorded. High squat jump force and power, vault take-off velocity, and sprinting speed indicated vaulting talent. High vault running speed and reduced handstand push-off ground contact time indicated high floor ability

Relative Positional Encoding for Speech Recognition and Direct Translation

Transformer models are powerful sequence-to-sequence architectures that are capable of directly mapping speech inputs to transcriptions or translations. However, the mechanism for modeling positions in this model was tailored for text modeling, and thus is less ideal for acoustic inputs. In this work, we adapt the relative position encoding scheme to the Speech Transformer, where the key addition is relative distance between input states in the self-attention network. As a result, the network can better adapt to the variable distributions present in speech data. Our experiments show that our resulting model achieves the best recognition result on the Switchboard benchmark in the non-augmentation condition, and the best published result in the MuST-C speech translation benchmark. We also show that this model is able to better utilize synthetic data than the Transformer, and adapts better to variable sentence segmentation quality for speech translation.Comment: Submitted to Interspeech 202

An edge CLT for the log determinant of Laguerre ensembles

We obtain a CLT for $\log|\det(M_n-s_n)|$ where $M_n$ is a Laguerre $\beta$ ensemble and $s_n=d_++\sigma_n n^{-2/3}$ with $d_+$ denoting the upper edge of the limiting spectrum of $M_n$ and $\sigma_n$ a slowly growing function ($\log\log^2 n\ll\sigma_n\ll\log^2 n$). A similar result was proved for Wigner matrices by Johnstone, Klochkov, Onatski, and Pavlyshyn. Obtaining this type of CLT of Laguerre matrices is of interest for statistical testing of critically spiked sample covariance matrices as well as free energy of bipartite spherical spin glasses at critical temperature.Comment: 45 page

Effects of Diet Composition and Insulin Resistance Status on Plasma Lipid Levels in a Weight Loss Intervention in Women.

BackgroundOptimal macronutrient distribution of weight loss diets has not been established. The distribution of energy from carbohydrate and fat has been observed to promote differential plasma lipid responses in previous weight loss studies, and insulin resistance status may interact with diet composition and affect weight loss and lipid responses.Methods and resultsOverweight and obese women (n=245) were enrolled in a 1-year behavioral weight loss intervention and randomly assigned to 1 of 3 study groups: a lower fat (20% energy), higher carbohydrate (65% energy) diet; a lower carbohydrate (45% energy), higher fat (35% energy) diet; or a walnut-rich, higher fat (35% energy), lower carbohydrate (45% energy) diet. Blood samples and data available from 213 women at baseline and at 6 months were the focus of this analysis. Triglycerides, total cholesterol, and high- and low-density lipoprotein cholesterol were quantified and compared between and within groups. Triglycerides decreased in all study arms at 6 months (P<0.05). The walnut-rich diet increased high-density lipoprotein cholesterol more than either the lower fat or lower carbohydrate diet (P<0.05). The walnut-rich diet also reduced low-density lipoprotein cholesterol in insulin-sensitive women, whereas the lower fat diet reduced both total cholesterol and high-density lipoprotein cholesterol in insulin-sensitive women (P<0.05). Insulin sensitivity and C-reactive protein levels also improved.ConclusionsWeight loss was similar across the diet groups, although insulin-sensitive women lost more weight with a lower fat, higher carbohydrate diet versus a higher fat, lower carbohydrate diet. The walnut-rich, higher fat diet resulted in the most favorable changes in lipid levels.Clinical trial registrationURL: http://www.clinicaltrials.gov. Unique identifier: NCT01424007