Studies of the gastro-oesophageal junction in normal and overweight healthy volunteers

Introduction: Oesophageal adenocarcinoma has increased dramatically in incidence over the past three decades with a particularly high burden of disease at the gastro-oesophageal junction. Many cases occur in individuals without known gastro-oesophageal reflux disease and in the absence of Barrett’s oesophagus suggesting that mechanisms other than traditional reflux may be important. Distal squamous mucosa may be prone to acid damage even in the absence of traditional reflux by the mechanism of distal opening of the lower oesophageal sphincter. This is splaying of the distal segment of lower oesophageal sphincter allowing acid ingress without traditional reflux. It has been suggested that the cardiac mucosa at the gastro-oesophageal junction, separating oesophageal squamous mucosa and acid secreting columnar mucosa of the stomach may be an abnormal mucosa arising as a consequence of acid damage. By this theory the cardiac mucosa is metaplastic and akin to ultra-short Barrett’s oesophagus. Obesity is a known risk factor for adenocarcinoma at the gastro-oesophageal junction and its rise has paralleled that of oesophageal cancer. Some of this excess risk undoubtedly operates through stress on the gastro-oesophageal junction and a predisposition to reflux. However we sought to explore the impact of obesity on the gastro-oesophageal junction in healthy volunteers without reflux and in particular to determine the characteristics of the cardiac mucosa and mechanisms of reflux in this group. Methods: 61 healthy volunteers with normal and increased waist circumference were recruited. 15 were found to have a hiatus hernia during the study protocol and were analysed separately. Volunteers had comprehensive pathological, physiological and anatomical assessments of the gastro-oesophageal junction including endoscopy with biopsies, MRI scanning before and after a standardised meal, prolonged recording of pH and manometry before and after a meal and screening by fluoroscopy to identify the squamo-columnar junction. In the course of the early manometric assessments a potential error associated with the manometry system recordings was identified. We therefore also sought to document and address this on the benchtop and in vivo. Key Findings: 1. In documenting the behaviour of the manoscan we described an immediate effect of temperature change on the pressure recorded by the sensors; ‘thermal effect’ and an ongoing drift of the recorded pressure with time; ‘baseline drift’. Thermal effect was well compensated within the standard operation of the system but baseline drift not addressed. Applying a linear correction to recorded data substantially reduced the error associated with baseline drift. 2. In asymptomatic healthy volunteers there was lengthening of the cardiac mucosa in association with central obesity and age. Furthermore, the cardiac mucosa in healthy volunteers demonstrated an almost identical immunophenotype to non-IM Barrett’s mucosa, which is considered to arise by metaplasia of oesophageal squamous mucosa. These findings support the hypothesis that the cardia is metaplastic in origin. 3. We have demonstrated a plausible mechanism of damage to distal squamous mucosa in association with obesity. In those with a large waist circumference we observed increased ingress of acid within but not across the lower oesophageal sphincter; ‘intrasphincteric reflux’ 4. The 15 healthy volunteers with a hiatus hernia were compared to 15 controls matched for age, gender and waist circumference. Those with a hiatus hernia had a longer cardiac mucosa and although they did not have excess traditional reflux they had excess distal acid exposure by short segment acid reflux and intrasphincteric acid reflux. Conclusions: These findings are likely to be relevant to adenocarcinoma of the gastro-oesophageal junction

A principal component approach to space-based gravitational wave astronomy

The current approach to data analysis for the Laser Interferometry Space Antenna (LISA) depends on the time delay interferometry observables (TDI) which have to be generated before any weak signal detection can be performed. These are linear combinations of the raw data with appropriate time shifts that lead to the cancellation of the laser frequency noises. This is possible because of the multiple occurrences of the same noises in the different raw data. Originally, these observables were manually generated starting with LISA as a simple stationary array and then adjusted to incorporate the antenna's motions. However, none of the observables survived the flexing of the arms in that they did not lead to cancellation with the same structure. The principal component approach is another way of handling these noises that was presented by Romano and Woan which simplified the data analysis by removing the need to create them before the analysis. This method also depends on the multiple occurrences of the same noises but, instead of using them for cancellation, it takes advantage of the correlations that they produce between the different readings. These correlations can be expressed in a noise (data) covariance matrix which occurs in the Bayesian likelihood function when the noises are assumed be Gaussian. Romano and Woan showed that performing an eigendecomposition of this matrix produced two distinct sets of eigenvalues that can be distinguished by the absence of laser frequency noise from one set. The transformation of the raw data using the corresponding eigenvectors also produced data that was free from the laser frequency noises. This result led to the idea that the principal components may actually be time delay interferometry observables since they produced the same outcome, that is, data that are free from laser frequency noise. The aims here were (i) to investigate the connection between the principal components and these observables, (ii) to prove that the data analysis using them is equivalent to that using the traditional observables and (ii) to determine how this method adapts to real LISA especially the flexing of the antenna. For testing the connection between the principal components and the TDI observables a 10x 10 covariance matrix containing integer values was used in order to obtain an algebraic solution for the eigendecomposition. The matrix was generated using fixed unequal arm lengths and stationary noises with equal variances for each noise type. Results confirm that all four Sagnac observables can be generated from the eigenvectors of the principal components. The observables obtained from this method however, are tied to the length of the data and are not general expressions like the traditional observables, for example, the Sagnac observables for two different time stamps were generated from different sets of eigenvectors. It was also possible to generate the frequency domain optimal AET observables from the principal components obtained from the power spectral density matrix. These results indicate that this method is another way of producing the observables therefore analysis using principal components should give the same results as that using the traditional observables. This was proven by fact that the same relative likelihoods (within 0.3%) were obtained from the Bayesian estimates of the signal amplitude of a simple sinusoidal gravitational wave using the principal components and the optimal AET observables. This method fails if the eigenvalues that are free from laser frequency noises are not generated. These are obtained from the covariance matrix and the properties of LISA that are required for its computation are the phase-locking, arm lengths and noise variances. Preliminary results of the effects of these properties on the principal components indicate that only the absence of phase-locking prevented their production. The flexing of the antenna results in time varying arm lengths which will appear in the covariance matrix and, from our toy model investigations, this did not prevent the occurrence of the principal components. The difficulty with flexing, and also non-stationary noises, is that the Toeplitz structure of the matrix will be destroyed which will affect any computation methods that take advantage of this structure. In terms of separating the two sets of data for the analysis, this was not necessary because the laser frequency noises are very large compared to the photodetector noises which resulted in a significant reduction in the data containing them after the matrix inversion. In the frequency domain the power spectral density matrices were block diagonals which simplified the computation of the eigenvalues by allowing them to be done separately for each block. The results in general showed a lack of principal components in the absence of phase-locking except for the zero bin. The major difference with the power spectral density matrix is that the time varying arm lengths and non-stationarity do not show up because of the summation in the Fourier transform.