Development and use of bioanalytical instrumentation and signal analysis methods for rapid sampling microdialysis monitoring of neuro-intensive care patients

This thesis focuses on the development and use of analysis tools to monitor brain injury patients. For this purpose, an online amperometric analyzer of cerebral microdialysis samples for glucose and lactate has been developed and optimized within the Boutelle group. The initial aim of this thesis was to significantly improve the signal-to-noise ratio and limit of detection of the assay to allow reliable quantification of the analytical data. The first approach was to re-design the electronic instrumentation of the assay. Printed-circuit boards were fabricated and proved very low noise, stable and much smaller than the previous potentiostats. The second approach was to develop generic data processing algorithms to remove three complex types of noise that commonly contaminate analytical signals: spikes, non-stationary ripples and baseline drift. The general strategy consisted in identifying the types of noise, characterising them, and subsequently subtracting them from the otherwise unprocessed data set. Spikes were effectively removed with 96.8% success and ripples were removed with minimal distortion of the signal resulting in an increased signal-to-noise ratio by up to 250%. This allowed reliable quantification of traces from ten patients monitored with the online microdialysis assay. Ninety-six spontaneous metabolic events in response to spreading depolarizations were resolved. These were characterized by a fall in glucose by -32.0 μM and a rise in lactate by +23.1 μM (median values) for over a 20-minute time-period. With frequently repeating events, this led to a progressive depletion of brain glucose. Finally, to improve the temporal coupling between the metabolic data and the electro-cortical signals, a flow-cell was engineered to integrate a potassium selective electrode into the microdialysate flow stream. With good stability over hours of continuous use and a 90% response time of 65 seconds, this flow cell was used for preliminary in vivo experiments the Max Planck Institute in Cologne

Classification of glucose records from patients at diabetes risk using a combined permutation entropy algorithm

[EN] Background and objectives : The adoption in clinical practice of electronic portable blood or interstitial glucose monitors has enabled the collection, storage, and sharing of massive amounts of glucose level readings. This availability of data opened the door to the application of a multitude of mathematical methods to extract clinical information not discernible with conventional visual inspection. The objective of this study is to assess the capability of Permutation Entropy (PE) to find differences between glucose records of healthy and potentially diabetic subjects. Methods : PE is a mathematical method based on the relative frequency analysis of ordinal patterns in time series that has gained a lot of attention in the last years due to its simplicity, robustness, and per- formance. We study in this paper the applicability of this method to glucose records of subjects at risk of diabetes in order to assess the predictability value of this metric in this context. Results : PE, along with some of its derivatives, was able to find significant differences between diabetic and non¿diabetic patients from records acquired up to 3 years before the diagnosis. The quantitative results for PE were 3.5878 ±0.3916 for the nondiabetic class, and 3.1564 ±0.4166 for the diabetic class. With a classification accuracy higher than 70%, and by means of a Cox regression model, PE demonstrated that it is a very promising candidate as a risk stratification tool for continuous glucose monitoring. Conclusion : PE can be considered as a prospective tool for the early diagnosis of the glucoregulatory system.Cuesta Frau, D.; Miró Martínez, P.; Oltra Crespo, S.; Jordán Núñez, J.; Vargas-Rojo, B.; Vigil-Medina, L. (2018). Classification of glucose records from patients at diabetes risk using a combined permutation entropy algorithm. Computer Methods and Programs in Biomedicine. 165:197-204. https://doi.org/10.1016/j.cmpb.2018.08.018S19720416

The metabolome as a diagnostic for maximal aerobic capacity during exercise in type 1 diabetes

\ua9 The Author(s) 2024.Aims/hypothesis: Our aim was to characterise the in-depth metabolic response to aerobic exercise and the impact of residual pancreatic beta cell function in type 1 diabetes. We also aimed to use the metabolome to distinguish individuals with type 1 diabetes with reduced maximal aerobic capacity in exercise defined by V˙O2peak. Methods: Thirty participants with type 1 diabetes (≥3 years duration) and 30 control participants were recruited. Groups did not differ in age or sex. After quantification of peak stimulated C-peptide, participants were categorised into those with undetectable (<3 pmol/l), low (3–200 pmol/l) or high (>200 pmol/l) residual beta cell function. Maximal aerobic capacity was assessed by V˙O2peak test and did not differ between control and type 1 diabetes groups. All participants completed 45 min of incline treadmill walking (60% V˙O2peak) with venous blood taken prior to exercise, immediately post exercise and after 60 min recovery. Serum was analysed using targeted metabolomics. Metabolomic data were analysed by multivariate statistics to define the metabolic phenotype of exercise in type 1 diabetes. Receiver operating characteristic (ROC) curves were used to identify circulating metabolomic markers of maximal aerobic capacity (V˙O2peak) during exercise in health and type 1 diabetes. Results: Maximal aerobic capacity (V˙O2peak) inversely correlated with HbA1c in the type 1 diabetes group (r2=0.17, p=0.024). Higher resting serum tricarboxylic acid cycle metabolites malic acid (fold change 1.4, p=0.001) and lactate (fold change 1.22, p=1.23 710−5) differentiated people with type 1 diabetes. Higher serum acylcarnitines (AC) (AC C14:1, F value=12.25, p=0.001345; AC C12, F value=11.055, p=0.0018) were unique to the metabolic response to exercise in people with type 1 diabetes. C-peptide status differentially affected metabolic responses in serum ACs during exercise (AC C18:1, leverage 0.066; squared prediction error 3.07). The malic acid/pyruvate ratio in rested serum was diagnostic for maximal aerobic capacity (V˙O2peak) in people with type 1 diabetes (ROC curve AUC 0.867 [95% CI 0.716, 0.956]). Conclusions/interpretation: The serum metabolome distinguishes high and low maximal aerobic capacity and has diagnostic potential for facilitating personalised medicine approaches to manage aerobic exercise and fitness in type 1 diabetes. Graphical Abstract: (Figure presented.)

Development of instrumentation for autofluorescence spectroscopy and its application to tissue autofluorescence studies and biomedical research

Autofluorescence spectroscopy is a promising non-invasive label-free approach to characterise biological samples and has shown potential to report structural and biochemical changes occurring in tissue owing to pathological transformations. This thesis discusses the development of compact and portable single point fibre-optic probe-based instrumentation for time-resolved spectrofluorometry, utilising spectrally resolved time-correlated single photon counting (TCSPC) detection and white light reflectometry. Following characterisation and validation, two of these instruments were deployed in clinical settings and their potential to report structural and metabolic alterations in tissue associated with osteoarthritis and heart disease was investigated. Osteoarthritis is a chronic and progressive disease of the joint characterised by irreversible destruction of articular cartilage for which there is no effective treatment. Working with the Kennedy Institute of Rheumatology, we investigated the potential of time-resolved autofluorescence spectroscopy as a diagnostic tool for early detection and monitoring of the progression of osteoarthritis. Our studies in enzymatically degenerated porcine and murine cartilage, which serve as models for osteoarthritis, suggest that autofluorescence lifetime is sensitive to disruption of the two major extracellular matrix components, aggrecan and collagen. Preliminary autofluorescence lifetime data were also obtained from ex vivo human tissue presenting naturally occurring osteoarthritis. Overall, our studies indicate that autofluorescence lifetime may offer a non-invasive readout to monitor cartilage matrix integrity that could contribute to future diagnosis of early cartilage defects as well as monitoring the efficacy of therapeutic agents. This thesis also explored the potential of time-resolved autofluorescence spectroscopy and steady-state white-light reflectometry of tissue to report structural and metabolic changes associated with cardiac disease, both ex vivo and in vivo, in collaboration with clinical colleagues from the National Heart and Lung Institute. Using a Langendorff rat model, the autofluorescence signature of cardiac tissue was investigated following different insults to the heart. We were able to correlate and translate results obtained from ex vivo Langendorff data to an in vivo myocardial infarction model in rats, where we report structural and functional alterations in the infarcted and remote myocardium at different stages following infarction. This investigation stimulated the development of a clinically viable instrument to be used in open-chest surgical procedures in humans, of which progress to date is described. 4 The impact of time-resolved autofluorescence spectroscopy for label-free diagnosis of diseased would be significantly enhanced if the cost of the instrumentation could be reduced below what is achievable with commercial TCSPC-based technology. The last part of this thesis concerns the development of compact and portable instrumentation utilising low-cost FPGA-based circuitry that can be used with laser diodes and photon-counting photomultipliers. A comprehensive description of this instrument is presented together with data from its application to both fluorescence lifetime standards and biological tissue. The lower potential cost of this instrument could enhance the potential of autofluorescence lifetime metrology for commercial development and clinical deployment.Open Acces

Time-dependent metabolic phenotyping of inflammatory dysregulation

A rich and functional description of a patient health status is the fundamental basis for the personalisation of treatment and the targeting of interventions. The function of inflammation in the healing process as well as its involvement in most major diseases is well established, yet the specific mechanism by which it contributes to the pathogenesis is still not fully understood. If conditions arising from a dysregulation of the inflammatory process are to be treated before they become irreversible, a novel understanding of these pathologies must be achieved and a stratification of patients based on their inflammatory status undertaken. The work presented in this thesis aims to deliver new analytical and statistical approaches to support the investigation of the time-dependent dysregulation of inflammation. Lipid mediators have been described as exerting a major role in the initiation and regulation of the inflammatory response, yet analytical platforms for their large-scale characterisation in human biofluids are lacking. This thesis reports the validation of an assay for the simultaneous quantification of pro- and anti-inflammatory signalling molecules in multiple human biofluids. The coverage of the assay in each biofluid is subsequently established, characterising inflammatory signalling across biological compartments. A second study explores the assay’s applicability in a clinical context; investigating the relationship between lipid mediators, current clinical markers of inflammation and post-operative complications. Characterising the interplay between signalling and regulatory networks is key to understanding a living system’s response to perturbations, yet few statistical approaches are suited for the detection of time-dependent patterns in short and irregularly sampled longitudinal datasets. This thesis reports the development of a statistical approach to support the identification of altered time-trajectories in such studies. The method’s wide applicability is subsequently demonstrated on two investigations covering the diversity of metabolic phenotyping data generation platforms. This thesis is a proof of concept for the characterisation of patient-specific inflammatory status in a clinical context and the identification of altered time-dependent patterns. Both analytical and statistical developments have been motivated by the needs of real world applications and provide a template for the characterisation and analysis of the molecular basis for treatment.Open Acces

Characterising the chemical and physical properties of phase-change nanodroplets

Phase-change nanodroplets have attracted increasing interest in recent years as ultrasound theranostic nanoparticles. They are smaller compared to microbubbles and they may distribute better in tissues (e.g. in tumours). They are composed of a stabilising shell and a perfluorocarbon core. Nanodroplets can vaporise into echogenic microbubbles forming cavitation nuclei when exposed to ultrasound. Their perfluorocarbon core phase-change is responsible for the acoustic droplet vaporisation. However, methods to quantify the perfluorocarbon core in nanodroplets are lacking. This is an important feature that can help explain nanodroplet phase change characteristics. In this study, we fabricated nanodroplets using lipids shell and perfluorocarbons. To assess the amount of perfluorocarbon in the core we used two methods, 19F-NMR and FTIR. To assess the cavitation after vaporisation we used an ultrasound transducer (1.1MHz) and a high-speed camera. The 19F-NMR based method showed that the fluorine signal correlated accurately with the perfluorocarbon concentration. Using this correlation, we were able to quantify the perfluorocarbon core of nanodroplets. This method was used to assess the content of the perfluorocarbon of the nanodroplets in solutions over time. It was found that perfluoropentane nanodroplets lost their content faster and at higher ratio compared to perfluorohexane nanodroplets. The high-speed camera showed that these nanodroplets have similar cavitation with commercial microbubbles. Nanodroplet characterisation should include perfluorocarbon concentration assessment as critical information for their development

The application of autofluorescence lifetime metrology to the study of heart failure models and heart disease

Autofluorescence spectroscopy offers a promising label-free approach to characterise biological samples and has already shown diagnostic potential in a number of medical applications, although study of myocardium has been relatively limited. A number of myocardial molecules display autofluorescence, including those involved in energetics, e.g. NADH and flavoproteins, as well as structural molecules, e.g. collagen. This thesis discusses the application of a custom-built single point fibre-optic probe-based instrumentation for time-resolved spectrofluorometry utilising spectrally resolved time-correlated single photon counting detection (TCSPC) and white light reflectometry to the investigation of models of heart failure, both ex vivo and in vivo. Heart failure (HF) is a pathophysiological state in which an abnormality of cardiac function causes failure of the heart to pump blood at a rate commensurate with the requirements of the metabolising tissues. It affects 1-2% of the population rising to greater than 10% aged over 70 years. Despite recent therapeutic advances, annualized mortality can still approach 10%. HF results from a myocardial injury (e.g. myocardial infarction, chemotherapy) causing loss of myocytes, and maladaptive changes in surviving myocytes and extracellular matrix by ‘pathological remodelling’. That HF is characterized by structural and energetic changes was the principal motivation for the creation of an instrument to investigate changes in myocardial autofluorescence signature in disease states in vivo. If the signatures associated with known pathological diagnoses could be ascertained, such a technique could perform ‘virtual biopsy’ to aid diagnosis. This thesis describes the application of autofluorescence technique to an ex vivo Langendorff-heart to characterise the changes in autofluorescence signature with controlled insults of glucose deprivation and hypoxia. Additionally, it reports for the first-time the characterization of the autofluorescence lifetime signature in vivo at different time points in an established rat post-myocardial infarction heart failure. The thesis describes development of in vivo intravenous doxorubicin chemotherapy-cardiomyopathy heart failure model (DOX-HF) and subsequent characterization of in vivo autofluorescence signature. This investigation prompted development of a clinically viable instrument and the progress to date is described.Open Acces

Stability of β-lactam antibiotics in bacterial growth media

Laboratory assays such as MIC tests assume that antibiotic molecules are stable in the chosen growth medium-but rapid degradation has been observed for antibiotics including β-lactams under some conditions in aqueous solution. Degradation rates in bacterial growth medium are less well known. Here, we develop a 'delay time bioassay' that provides a simple way to estimate antibiotic stability in bacterial growth media, using only a plate reader and without the need to measure the antibiotic concentration directly. We use the bioassay to measure degradation half-lives of the β-lactam antibiotics mecillinam, aztreonam and cefotaxime in widely-used bacterial growth media based on MOPS and Luria-Bertani (LB) broth. We find that mecillinam degradation can occur rapidly, with a half-life as short as 2 hours in MOPS medium at 37°C and pH 7.4, and 4-5 hours in LB, but that adjusting the pH and temperature can increase its stability to a half-life around 6 hours without excessively perturbing growth. Aztreonam and cefotaxime were found to have half-lives longer than 6 hours in MOPS medium at 37°C and pH 7.4, but still shorter than the timescale of a typical minimum inhibitory concentration (MIC) assay. Taken together, our results suggest that care is needed in interpreting MIC tests and other laboratory growth assays for β-lactam antibiotics, since there may be significant degradation of the antibiotic during the assay