Loss-of-function fibroblast growth factor receptor-2 mutations in melanoma

We report that 10% of melanoma tumors and cell lines harbor mutations in the fibroblast growth factor receptor 2 (FGFR2) gene. These novel mutations include three truncating mutations and 20 missense mutations occurring at evolutionary conserved residues in FGFR2 as well as among all four FGFRs. The mutation spectrum is characteristic of those induced by UV radiation. Mapping of these mutations onto the known crystal structures of FGFR2 followed by in vitro and in vivo studies show that these mutations result in receptor loss of function through several distinct mechanisms, including loss of ligand binding affinity, impaired receptor dimerization, destabilization of the extracellular domains, and reduced kinase activity. To our knowledge, this is the first demonstration of loss-of-function mutations in a class IV receptor tyrosine kinase in cancer. Taken into account with our recent discovery of activating FGFR2 mutations in endometrial cancer, we suggest that FGFR2 may join the list of genes that play context-dependent opposing roles in cancer.

Comparison of intranasal and transcutaneous immunization for induction of protective immunity against chlamydia muridarum respiratory tract infection

Chlamydia pneumoniae causes a range of respiratory infections including bronchitis, pharyngitis and pneumonia. Infection has also been implicated in exacerbation/initiation of asthma and chronic obstructive pulmonary disease (COPD) and may play a role in atherosclerosis and Alzheimer's disease. We have used a mouse model of Chlamydia respiratory infection to determine the effectiveness of intranasal (IN) and transcutaneous immunization (TCI) to prevent Chlamydia lung infection. Female BALB/c mice were immunized with chlamydial major outer membrane protein (MOMP) mixed with cholera toxin and CpG oligodeoxynucleotide adjuvants by either the IN or TCI routes. Serum and bronchoalveolar lavage (BAL) were collected for antibody analysis. Mononuclear cells from lung-draining lymph nodes were stimulated in vitro with MOMP and cytokine mRNA production determined by real time PCR. Animals were challenged with live Chlamydia and weighed daily following challenge. At day 10 (the peak of infection) animals were sacrificed and the numbers of recoverable Chlamydia in lungs determined by real time PCR. MOMP-specific antibody-secreting cells in lung tissues were also determined at day 10 post-infection. Both IN and TCI protected animals against weight loss compared to non-immunized controls with both immunized groups gaining weight by day 10-post challenge while controls had lost 6% of body weight. Both immunization protocols induced MOMP-specific IgG in serum and BAL while only IN immunization induced MOMP-specific IgA in BAL. Both immunization routes resulted in high numbers of MOMP-specific antibody-secreting cells in lung tissues (IN > TCI). Following in vitro re-stimulation of lung-draining lymph node cells with MOMP; IFNγ mRNA increased 20-fold in cells from IN immunized animals (compared to non-immunized controls) while IFNγ levels increased 6- to 7-fold in TCI animals. Ten days post challenge non-immunized animals had >7000 IFU in their lungs, IN immunized animals <50 IFU and TCI immunized animals <1500 IFU. Thus, both intranasal and transcutaneous immunization protected mice against respiratory challenge with Chlamydia. The best protection was obtained following IN immunization and correlated with IFNγ production by mononuclear cells in lung-draining LN and MOMP-specific IgA in BAL.

Evaluating multivariate volatility forecasts : how effective are statistical and economic loss functions?

Multivariate volatility forecasts are an important input in many financial applications, in particular portfolio optimisation problems. Given the number of models available and the range of loss functions to discriminate between them, it is obvious that selecting the optimal forecasting model is challenging. The aim of this thesis is to thoroughly investigate how effective many commonly used statistical (MSE and QLIKE) and economic (portfolio variance and portfolio utility) loss functions are at discriminating between competing multivariate volatility forecasts. An analytical investigation of the loss functions is performed to determine whether they identify the correct forecast as the best forecast. This is followed by an extensive simulation study examines the ability of the loss functions to consistently rank forecasts, and their statistical power within tests of predictive ability. For the tests of predictive ability, the model confidence set (MCS) approach of Hansen, Lunde and Nason (2003, 2011) is employed. As well, an empirical study investigates whether simulation findings hold in a realistic setting. In light of these earlier studies, a major empirical study seeks to identify the set of superior multivariate volatility forecasting models from 43 models that use either daily squared returns or realised volatility to generate forecasts. This study also assesses how the choice of volatility proxy affects the ability of the statistical loss functions to discriminate between forecasts. Analysis of the loss functions shows that QLIKE, MSE and portfolio variance can discriminate between multivariate volatility forecasts, while portfolio utility cannot. An examination of the effective loss functions shows that they all can identify the correct forecast at a point in time, however, their ability to discriminate between competing forecasts does vary. That is, QLIKE is identified as the most effective loss function, followed by portfolio variance which is then followed by MSE. The major empirical analysis reports that the optimal set of multivariate volatility forecasting models includes forecasts generated from daily squared returns and realised volatility. Furthermore, it finds that the volatility proxy affects the statistical loss functions’ ability to discriminate between forecasts in tests of predictive ability. These findings deepen our understanding of how to choose between competing multivariate volatility forecasts.

Assessment of retinal structure and visual function in association with diabetic peripheral neuropathy

Diabetes is an increasingly prevalent disease worldwide. Providing early management of the complications can prevent morbidity and mortality in this population. Peripheral neuropathy, a significant complication of diabetes, is the major cause of foot ulceration and amputation in diabetes. Delay in attending to complication of the disease contributes to significant medical expenses for diabetic patients and the community. Early structural changes to the neural components of the retina have been demonstrated to occur prior to the clinically visible retinal vasculature complication of diabetic retinopathy. Additionally visual functionloss has been shown to exist before the ophthalmoscopic manifestations of vasculature damage. The purpose of this thesis was to evaluate the relationship between diabetic peripheral neuropathy and both retinal structure and visual function. The key question was whether diabetic peripheral neuropathy is the potential underlying factor responsible for retinal anatomical change and visual functional loss in people with diabetes. This study was conducted on a cohort with type 2 diabetes. Retinal nerve fibre layer thickness was assessed by means of Optical Coherence Tomography (OCT). Visual function was assessed using two different methods; Standard Automated Perimetry (SAP) and flicker perimetry were performed within the central 30 degrees of fixation. The level of diabetic peripheral neuropathy (DPN) was assessed using two techniques - Quantitative Sensory Testing and Neuropathy Disability Score (NDS). These techniques are known to be capable of detecting DPN at very early stages. NDS has also been shown as a gold standard for detecting 'risk of foot ulceration'. Findings reported in this thesis showed that RNFL thickness, particularly in the inferior quadrant, has a significant association with severity of DPN when the condition has been assessed using NDS. More specifically it was observed that inferior RNFL thickness has the ability to differentiate individuals who are at higher risk of foot ulceration from those who are at lower risk, indicating that RNFL thickness can predict late-staged DPN. Investigating the association between RNFL and QST did not show any meaningful interaction, which indicates that RNFL thickness for this cohort was not as predictive of neuropathy status as NDS. In both of these studies, control participants did not have different results from the type 2 cohort who did not DPN suggesting that RNFL thickness is not a marker for diagnosing DPN at early stages. The latter finding also indicated that diabetes per se, is unlikely to affect the RNFL thickness. Visual function as measured by SAP and flicker perimetry was found to be associated with severity of peripheral neuropathy as measured by NDS. These findings were also capable of differentiating individuals at higher risk of foot ulceration; however, visual function also proved not to be a maker for early diagnosis of DPN. It was found that neither SAP, nor flicker sensitivity have meaningful associations with DPN when neuropathy status was measured using QST. Importantly diabetic retinopathy did not explain any of the findings in these experiments. The work described here is valuable as no other research to date has investigated the association between diabetic peripheral neuropathy and either retinal structure or visual function.

Oxygen delivery through high-flow nasal cannulae increase end-expiratory lung volume and reduce respiratory rate in post-cardiac surgical patients

Background: High-flow nasal cannulae (HFNC) create positive oropharyngeal airway pressure but it is unclear how their use affects lung volume. Electrical impedance tomography (EIT) allows assessment of changes in lung volume by measuring changes in lung impedance. Primary objectives were to investigate the effects of HFNC on airway pressure (Paw) and end-expiratory lung volume (EELV), and to identify any correlation between the two. Secondary objectives were to investigate the effects of HFNC on respiratory rate (RR), dyspnoea, tidal volume and oxygenation; and the interaction between body mass index (BMI) and EELV. Methods: Twenty patients prescribed HFNC post-cardiac surgery were investigated. Impedance measures, Paw, PaO2/FiO2 ratio, RR and modified Borg scores were recorded first on low flow oxygen (nasal cannula or Hudson face mask) and then on HFNC. Results: A strong and significant correlation existed between Paw and end-expiratory lung impedance (EELI) (r=0.7, p<0.001). Compared with low flow oxygen, HFNC significantly increased EELI by 25.6% (95% CI 24.3, 26.9) and Paw by 3.0 cmH2O (95% CI 2.4, 3.7). RR reduced by 3.4 breaths per minute (95% CI 1.7, 5.2) with HFNC use, tidal impedance variation increased by 10.5% (95% CI 6.1, 18.3) and PaO2/FiO2 ratio improved by 30.6 mmHg (95% CI 17.9, 43.3). HFNC improved subjective dyspnoea scoring (p=0.023). Increases in EELI were significantly influenced by BMI, with larger increases associated with higher BMIs (p<0.001). Conclusions: This study suggests that HFNC improve dyspnoea and oxygenation by increasing both EELV and tidal volume, and are most beneficial in patients with higher BMIs.