Analytical methods based on ion mobility and mass spectrometry for metabolomics

Travelling wave ion mobility spectrometry (TWIMS) in combination with ultra-high performance liquid chromatography (UHPLC) and mass spectrometry (MS) has been applied successfully for the untargeted, global metabolic profiling of biofluids such as mouse plasma and saliva. Methods based on UHPLC-MS alone and in combination with ion mobility spectrometry (UHPLC-IM-MS) have been developed and validated for the untargeted metabolite profiling of saliva, obtained non-invasively by passive drool. Three separate metabolic profiling studies have been carried out in conjunction with bioinformatics strategies to identify potential metabolomic biomarker ions that are associated with efficacy of rice bran in colorectal cancer, physiological stress and that have the potential for the diagnosis of asthma. The advantages offered by the utility of ion mobility in UHPLC-MS based metabolic profiling studies, including the increased analytical space, mass spectral clean-up of contaminants such as PEG post-UHPLC-IM-MS analysis, enhancement of the selectivity of targeted metabolites as well as the potential for the identification of metabolites by comparison of ion mobility drift times have been highlighted. Ten potential metabolic biomarker ions of asthma have been identified from the moderate asthmatics from untargeted metabolite profiling of saliva by UHPLC-MS. A predictive model based on partial least squares discriminant analysis (PLS-DA) has been constructed using these ten discriminant ions, which demonstrates good predictive capability for moderate asthmatics and controls. Potential metabolic biomarker ions of physiological stress have been identified through untargeted metabolite profiling analysis of saliva samples collected before and after exercise by UHPLC-IM-MS. Valerolactam has been identified as a potential biomarker of physiological stress from saliva by comparison of retention time, ion mobility drift time and MS/MS spectra with a standard of δ-valerolactam

Towards standardisation in breathomics

Exhaled breath VOCs analysis is safe and non-invasive method of monitoring for human metabolic profiles and has the potential to become diagnostic tool in clinical practise. This thesis first describe in detail the different aspects of exhaled breath VOCs and its use as diagnostic tool in respiratory diseases. The current exhaled breath analysis work-flow including breath sampling, analysis and data processing is also described. A single exhaled breath sample can contain in excess of 500 different chemical species. There is a wide range of factors that can cause the variability to individual breath profiles. In order to detect small changes in breath profiles, a standardised and reproducible approach to exhaled breath analysis methodology is required. The long term storage of exhaled breath samples using multi-sorbent tubes is investigated, the optimum storage protocol and condition is discussed. A portable breath sampling system was also developed for remote sampling. The introduction of this new feature enables breath sampling to be carried out outside the designated laboratory with no location restriction. This feature combined with the easy to use and non-invasive original sampling unit designed for subjects with impaired lung function minimise participant stress level and discomfort. It also utilises the custom developed air supply filtration assembly to create a standardised purified breathable air that can minimise the method variability and improve standardisation to breath samples collected. This methodology is tested in an excise induced bronchoconstriction (EIB) study where two groups of participants: healthy and excise induced bronchoconstriction (EIB) positive undergo high intensity cardiopulmonary exercise testing (CPET). The data from two groups of participants is analysed and three markers which shown correlation with EIB positive participants are determined

Multichannel analysis of normal and continuous adventitious respiratory sounds for the assessment of pulmonary function in respiratory diseases

Premi extraordinari doctorat UPC curs 2015-2016, àmbit d’Enginyeria IndustrialRespiratory sounds (RS) are produced by turbulent airflows through the airways and are inhomogeneously transmitted through different media to the chest surface, where they can be recorded in a non-invasive way. Due to their mechanical nature and airflow dependence, RS are affected by respiratory diseases that alter the mechanical properties of the respiratory system. Therefore, RS provide useful clinical information about the respiratory system structure and functioning. Recent advances in sensors and signal processing techniques have made RS analysis a more objective and sensitive tool for measuring pulmonary function. However, RS analysis is still rarely used in clinical practice. Lack of a standard methodology for recording and processing RS has led to several different approaches to RS analysis, with some methodological issues that could limit the potential of RS analysis in clinical practice (i.e., measurements with a low number of sensors, no controlled airflows, constant airflows, or forced expiratory manoeuvres, the lack of a co-analysis of different types of RS, or the use of inaccurate techniques for processing RS signals). In this thesis, we propose a novel integrated approach to RS analysis that includes a multichannel recording of RS using a maximum of five microphones placed over the trachea and the chest surface, which allows RS to be analysed at the most commonly reported lung regions, without requiring a large number of sensors. Our approach also includes a progressive respiratory manoeuvres with variable airflow, which allows RS to be analysed depending on airflow. Dual RS analyses of both normal RS and continuous adventitious sounds (CAS) are also proposed. Normal RS are analysed through the RS intensity–airflow curves, whereas CAS are analysed through a customised Hilbert spectrum (HS), adapted to RS signal characteristics. The proposed HS represents a step forward in the analysis of CAS. Using HS allows CAS to be fully characterised with regard to duration, mean frequency, and intensity. Further, the high temporal and frequency resolutions, and the high concentrations of energy of this improved version of HS, allow CAS to be more accurately characterised with our HS than by using spectrogram, which has been the most widely used technique for CAS analysis. Our approach to RS analysis was put into clinical practice by launching two studies in the Pulmonary Function Testing Laboratory of the Germans Trias i Pujol University Hospital for assessing pulmonary function in patients with unilateral phrenic paralysis (UPP), and bronchodilator response (BDR) in patients with asthma. RS and airflow signals were recorded in 10 patients with UPP, 50 patients with asthma, and 20 healthy participants. The analysis of RS intensity–airflow curves proved to be a successful method to detect UPP, since we found significant differences between these curves at the posterior base of the lungs in all patients whereas no differences were found in the healthy participants. To the best of our knowledge, this is the first study that uses a quantitative analysis of RS for assessing UPP. Regarding asthma, we found appreciable changes in the RS intensity–airflow curves and CAS features after bronchodilation in patients with negative BDR in spirometry. Therefore, we suggest that the combined analysis of RS intensity–airflow curves and CAS features—including number, duration, mean frequency, and intensity—seems to be a promising technique for assessing BDR and improving the stratification of BDR levels, particularly among patients with negative BDR in spirometry. The novel approach to RS analysis developed in this thesis provides a sensitive tool to obtain objective and complementary information about pulmonary function in a simple and non-invasive way. Together with spirometry, this approach to RS analysis could have a direct clinical application for improving the assessment of pulmonary function in patients with respiratory diseases.Los sonidos respiratorios (SR) se generan con el paso del flujo de aire a través de las vías respiratorias y se transmiten de forma no homogénea hasta la superficie torácica. Dada su naturaleza mecánica, los SR se ven afectados en gran medida por enfermedades que alteran las propiedades mecánicas del sistema respiratorio. Por lo tanto, los SR proporcionan información clínica relevante sobre la estructura y el funcionamiento del sistema respiratorio. La falta de una metodología estándar para el registro y procesado de los SR ha dado lugar a la aparición de diferentes estrategias de análisis de SR con ciertas limitaciones metodológicas que podrían haber restringido el potencial y el uso de esta técnica en la práctica clínica (medidas con pocos sensores, flujos no controlados o constantes y/o maniobras forzadas, análisis no combinado de distintos tipos de SR o uso de técnicas poco precisas para el procesado de los SR). En esta tesis proponemos un método innovador e integrado de análisis de SR que incluye el registro multicanal de SR mediante un máximo de cinco micrófonos colocados sobre la tráquea yla superficie torácica, los cuales permiten analizar los SR en las principales regiones pulmonares sin utilizar un número elevado de sensores . Nuestro método también incluye una maniobra respiratoria progresiva con flujo variable que permite analizar los SR en función del flujo respiratorio. También proponemos el análisis combinado de los SR normales y los sonidos adventicios continuos (SAC), mediante las curvas intensidad-flujo y un espectro de Hilbert (EH) adaptado a las características de los SR, respectivamente. El EH propuesto representa un avance importante en el análisis de los SAC, pues permite su completa caracterización en términos de duración, frecuencia media e intensidad. Además, la alta resolución temporal y frecuencial y la alta concentración de energía de esta versión mejorada del EH permiten caracterizar los SAC de forma más precisa que utilizando el espectrograma, el cual ha sido la técnica más utilizada para el análisis de SAC en estudios previos. Nuestro método de análisis de SR se trasladó a la práctica clínica a través de dos estudios que se iniciaron en el laboratorio de pruebas funcionales del hospital Germans Trias i Pujol, para la evaluación de la función pulmonar en pacientes con parálisis frénica unilateral (PFU) y la respuesta broncodilatadora (RBD) en pacientes con asma. Las señales de SR y flujo respiratorio se registraron en 10 pacientes con PFU, 50 pacientes con asma y 20 controles sanos. El análisis de las curvas intensidad-flujo resultó ser un método apropiado para detectar la PFU , pues encontramos diferencias significativas entre las curvas intensidad-flujo de las bases posteriores de los pulmones en todos los pacientes , mientras que en los controles sanos no encontramos diferencias significativas. Hasta donde sabemos, este es el primer estudio que utiliza el análisis cuantitativo de los SR para evaluar la PFU. En cuanto al asma, encontramos cambios relevantes en las curvas intensidad-flujo yen las características de los SAC tras la broncodilatación en pacientes con RBD negativa en la espirometría. Por lo tanto, sugerimos que el análisis combinado de las curvas intensidad-flujo y las características de los SAC, incluyendo número, duración, frecuencia media e intensidad, es una técnica prometedora para la evaluación de la RBD y la mejora en la estratificación de los distintos niveles de RBD, especialmente en pacientes con RBD negativa en la espirometría. El método innovador de análisis de SR que se propone en esta tesis proporciona una nueva herramienta con una alta sensibilidad para obtener información objetiva y complementaria sobre la función pulmonar de una forma sencilla y no invasiva. Junto con la espirometría, este método puede tener una aplicación clínica directa en la mejora de la evaluación de la función pulmonar en pacientes con enfermedades respiratoriasAward-winningPostprint (published version

Analysis of speech and other sounds

This thesis comprises a study of various types of signal processing techniques, applied to the tasks of extracting information from speech, cough, and dolphin sounds. Established approaches to analysing speech sounds for the purposes of low data rate speech encoding, and more generally to determine the characteristics of the speech signal, are reviewed. Two new speech processing techniques, shift-and-add and CLEAN (which have previously been applied in the field of astronomical image processing), are developed and described in detail. Shift-and-add is shown to produce a representation of the long-term "average" characteristics of the speech signal. Under certain simplifying assumptions, this can be equated to the average glottal excitation. The iterative deconvolution technique called CLEAN is employed to deconvolve the shift-and-add signal from the speech signal. Because the resulting "CLEAN" signal has relatively few non-zero samples, it can be directly encoded at a low data rate. The performance of a low data rate speech encoding scheme that takes advantage of this attribute of CLEAN is examined in detail. Comparison with the multi-pulse LP C approach to speech coding shows that the new method provides similar levels of performance at medium data rates of about 16kbit/s. The changes that occur in the character of a person's cough sounds when that person is afflicted with asthma are outlined. The development and implementation of a micro-computer-based cough sound analysis system, designed to facilitate the ongoing study of these sounds, is described. The system performs spectrographic analysis on the cough sounds. A graphical user interface allows the sound waveforms and spectra to be displayed and examined in detail. Preliminary results are presented, which indicate that the spectral content of cough sounds are changed by asthma. An automated digital approach to studying the characteristics of Hector's dolphin vocalisations is described. This scheme characterises the sounds by extracting descriptive parameters from their time and frequency domain envelopes. The set of parameters so obtained from a sample of click sequences collected from free-ranging dolphins is analysed by principal component analysis. Results are presented which indicate that Hector's dolphins produce only a small number of different vocal sounds. In addition to the statistical analysis, several of the clicks, which are assumed to be used for echo-location, are analysed in terms of their range-velocity ambiguity functions. The results suggest that Hector's dolphins can distinguish targets separated in range by about 2cm, but are unable to separate targets that differ only in their velocity

Development of a handheld breath analyser for the monitoring of energy expenditure

Metabolic rate is not routinely assessed in healthcare for the general population, nor is it a measure commonly recorded for in-patients (incorrect feeding can slow post-operation recovery rate). For the general community, this lack of knowledge prevents the accurate determination of calorific need and is a factor contributing towards the onset of an overweight and an increasingly obese population. In the UK alone, obesity costs the National Health Service a staggering £5 billion annually. In this thesis a novel low-cost hand-held breath analyser is presented in order to measure human energy expenditure (EE). A unique optical CO2 sensor was developed, capable of sampling exhaled breath with a fast response time ~1 s and resilience to a humidity range of ~30 % to near saturated. The device was tested in a laboratory gas testing rig and a detection limit of ~25 ppm CO2 was measured. A low power metal oxide sensor (~100 mW) was developed to detect volatile organic compounds (VOCs) in the breath, for disease detection and investigation of the variation of inter-individual metabolism processes. The device was sensitive to acetone (100 to 300 ppm, which is a biomarker for type-I diabetes). Other VOCs, such as NO2 were tested (10 to 250 ppb). Further work includes investigating the inter-individual variance of metabolism processes, for which the metal oxide sensor would be well-suited. Software was developed to operate the gas testing rig and acquire sensor output data in real-time. An application was written for smartphones to enable EE measurements with the breath analyser, outside of a laboratory environment. Three hand-held analysers were constructed and tested with a trial of 10 subjects. A counterpart (benchmark) unit with medical grade commercial sensors (cost of ~£2500) and hospital respiratory rooms (reference) were included in the trial. The newly developed analysers improved upon the performance of the benchmark system (average EE measurement error +2.4 % compared to +7.9 %). The affordable device offered far greater accuracy than the traditional method often used by practitioners (predictive equations, error +41.4%). It is proposed a set of periodic (hourly) breath measurements could be used to determine daily EE. The EE analyser and associated low-cost sensors developed in this work offer a potential solution to halt the growing cost of an obese population and provide point-of-care health management

Studying the effect of cigarette smoke exposure on murine models of allergic asthma

Exposure to pollution and active or passive smoking have been associated with a worsened asthma severity and a reduced response to treatment. These poorly controlled asthmatics are responsible for the majority of the economic burden of the disease but how pollution and/or cigarette smoke (CS) impacts on the disease is not well understood. The aim of this thesis was to develop a murine model of allergic asthma where CS exposure results in a change in model phenotype and the sensitivity of the response to pharmacological intervention. Two preclinical models of allergic asthma were utilised: the ovalbumin (OVA) model which had previously been established in-house, and the house dust mite (HDM) model which I developed in this thesis. As topical HDM exposure is known to cause innate inflammation I developed an allergic model where HDM challenge resulted in inflammation only in the mice which had been previously sensitised to HDM. The allergic inflammation in this model was accompanied by allergic airway hyper responsiveness, however the LAR was not observed in this model. CS exposure did not have a dramatic impact on the cellular inflammation in either the OVA- or the HDM-driven model, nor did it impact upon the anti-inflammatory effects of oral steroid treatment with the exception of the addition of a steroid-insensitive neutrophil population. However CS exposure attenuated the AHR observed in the OVA and the HDM models. Finally cigarette smoke exposure not only enhanced the OVA-induced LAR but also rendered this response completely insensitive to oral steroid treatment. Further investigation into the effects of CS in these two models may provide clues as to the mechanisms behind the effect of smoking on asthma in the clinic. The CS-enhanced LAR model could be invaluable in understanding the clinical phenotype of treatment resistance in smoking asthmatics.Open Acces

ReSCon '10, Research Student Conference: Book of Abstracts

The third SED Research Student Conference (ReSCon2010) was hosted over three days, 21-23 June 2010, in the Hamilton Centre at Brunel University. The conference consisted of oral and poster presentations, which showcased the high quality and diversity of the research being conducted within the School of Engineering and Design. The abstracts and presentations were the result of ongoing research by postgraduate research students from the School. The conference is held annually, and ReSCon plays a key role in contributing to research and innovations within the School