ORCID Profile
0000-0001-8754-5094
Current Organisation
University Of Strathclyde
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Publisher: SAGE Publications
Date: 23-09-2021
DOI: 10.1177/00037028211021846
Abstract: This Focal Point Review paper discusses the developments of biomedical Raman and infrared spectroscopy, and the recent strive towards these technologies being regarded as reliable clinical tools. The promise of vibrational spectroscopy in the field of biomedical science, alongside the development of computational methods for spectral analysis, has driven a plethora of proof-of-concept studies which convey the potential of various spectroscopic approaches. Here we report a brief review of the literature published over the past few decades, with a focus on the current technical, clinical, and economic barriers to translation, namely the limitations of many of the early studies, and the lack of understanding of clinical pathways, health technology assessments, regulatory approval, clinical feasibility, and funding applications. The field of biomedical vibrational spectroscopy must acknowledge and overcome these hurdles in order to achieve clinical efficacy. Current prospects have been overviewed with comment on the advised future direction of spectroscopic technologies, with the aspiration that many of these innovative approaches can ultimately reach the frontier of medical diagnostics and many clinical applications.
Publisher: Royal Society of Chemistry (RSC)
Date: 2021
DOI: 10.1039/D1SC01236C
Abstract: Exploration of potential-dependent, multi-colour co-reactant electrochemiluminescence from multiple luminophores at the working and counter electrodes reveals new pathways to emission.
Publisher: Elsevier BV
Date: 05-2020
Publisher: Wiley
Date: 24-01-2021
Abstract: Biofluid spectroscopy is an emerging technology in the field of clinical investigation, providing a simple way to extract diagnostic and observational information from easy to acquire s les. Infrared spectroscopy is well suited to analyse a large range of biofluid s les, including blood and its derivatives, due to flexible s ling modes and high sensitivity to subtle biological changes. As the technology advances towards the clinic, factors influencing successful clinical translation are becoming apparent. Here, we provide a tutorial for effective biofluid spectroscopy study design, discussing s le and instrument parameters, as well as clinical considerations. The aim is to present the current understanding of clinical translation in the field of biofluid spectroscopy, and to facilitate other clinical applications to advance to the clinic. image
Publisher: MDPI AG
Date: 30-07-2021
Abstract: Background: To support the early detection and diagnosis of brain tumours we have developed a rapid, cost-effective and easy to use spectroscopic liquid biopsy based on the absorbance of infrared radiation. We have previously reported highly sensitive results of our approach which can discriminate patients with a recent brain tumour diagnosis and asymptomatic controls. Other liquid biopsy approaches (e.g., based on tumour genetic material) report a lower classification accuracy for early-stage tumours. In this manuscript we present an investigation into the link between brain tumour volume and liquid biopsy test performance. Methods: In a cohort of 177 patients (90 patients with high-grade glioma (glioblastoma (GBM) or anaplastic astrocytoma), or low-grade glioma (astrocytoma, oligoastrocytoma and oligodendroglioma)) tumour volumes were calculated from magnetic resonance imaging (MRI) investigations and patients were split into two groups depending on MRI parameters (T1 with contrast enhancement or T2/FLAIR (fluid-attenuated inversion recovery)). Using attenuated total reflection (ATR)-Fourier transform infrared (FTIR) spectroscopy coupled with supervised learning methods and machine learning algorithms, 90 tumour patients were stratified against 87 control patients who displayed no symptomatic indications of cancer, and were classified as either glioma or non-glioma. Results: Sensitivities, specificities and balanced accuracies were all greater than 88%, the area under the curve (AUC) was 0.98, and cancer patients with tumour volumes as small as 0.2 cm3 were correctly identified. Conclusions: Our spectroscopic liquid biopsy approach can identify gliomas that are both small and low-grade showing great promise for deployment of this technique for early detection and diagnosis.
Publisher: Informa UK Limited
Date: 23-01-2019
Publisher: Royal Society of Chemistry (RSC)
Date: 2019
DOI: 10.1039/C9CC03201K
Abstract: Monitoring emission and potentials at both the working and counter electrodes provides new insight into a proposed cathodic electrochemiluminescence system.
Publisher: Wiley
Date: 09-03-2015
DOI: 10.1002/DTA.1780
Abstract: Tris(2,2'-bipyridine)ruthenium(II) chemiluminescence was investigated for the detection of 3,4-methylenedioxymeth hetamine (MDMA) and several related compounds in street drug s les. Optimization using flow injection analysis showed that the selectivity of the reagent can be targeted towards the detection of secondary amines by altering the pH of the reaction environment. The greater selectivity of this mode of detection, compared to UV-absorbance, reduces the probability of false positive results from interfering compounds. The detection limit for MDMA under these conditions was 0.48 μM. A HPLC method incorporating post-column tris(2,2'-bipyridine)ruthenium(II) chemiluminescence detection was applied to the determination of MDMA in five street drug s les. The results obtained were in good agreement with quantification performed using traditional UV-absorbance detection, which demonstrates the viability of this method for confirmatory analysis of drug s les. This is the first report of tris(2,2'-bipyridine)ruthenium(II) chemiluminescence for the detection of MDMA and related hetamine derivatives.
Publisher: Elsevier BV
Date: 07-2020
Publisher: MDPI AG
Date: 21-06-2022
Abstract: Pancreatic cancer claims over 460,000 victims per year. The carbohydrate antigen (CA) 19-9 test is the blood test used for pancreatic cancer’s detection however, its levels can be raised in symptomatic patients with other non-malignant diseases, or with other tumors in the surrounding area. Attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy has demonstrated exceptional potential in cancer diagnostics, and its clinical implementation could represent a significant step towards early detection. This proof-of-concept study, investigating the use of ATR-FTIR spectroscopy on dried blood serum, focused on the discrimination of both cancer versus healthy control s les, and cancer versus symptomatic non-malignant control s les, as a novel liquid biopsy approach for pancreatic cancer diagnosis. Machine learning algorithms were applied, achieving results of up to 92% sensitivity and 88% specificity when discriminating between cancers (n = 100) and healthy controls (n = 100). An area under the curve (AUC) of 0.95 was obtained through receiver operating characteristic (ROC) analysis. Balanced sensitivity and specificity over 75%, with an AUC of 0.83, were achieved with cancers (n = 35) versus symptomatic controls (n = 35). Herein, we present these results as demonstration that our liquid biopsy approach could become a simple, minimally invasive, and reliable diagnostic test for pancreatic cancer detection.
Publisher: Royal Society of Chemistry (RSC)
Date: 2021
DOI: 10.1039/D0AY01991G
Abstract: The development of spectroscopic point-of-care devices has the potential to revolutionise clinical diagnostics by rapidly producing actionable results that enable earlier patient diagnosis.
Publisher: Elsevier BV
Date: 04-2020
Publisher: Springer Science and Business Media LLC
Date: 06-03-2020
Publisher: Public Library of Science (PLoS)
Date: 17-02-2023
DOI: 10.1371/JOURNAL.PONE.0279669
Abstract: Discrimination of brain cancer versus non-cancer patients using serum-based attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy diagnostics was first developed by Hands et al with a reported sensitivity of 92.8% and specificity of 91.5%. Cameron et al . then went on to stratifying between specific brain tumour types: glioblastoma multiforme (GBM) vs. primary cerebral lymphoma with a sensitivity of 90.1% and specificity of 86.3%. Expanding on these studies, 30 GBM, 30 lymphoma and 30 non-cancer patients were selected to investigate the influence on test performance by focusing on specific molecular weight regions of the patient serum. Membrane filters with molecular weight cut offs of 100 kDa, 50 kDa, 30 kDa, 10 kDa and 3 kDa were purchased in order to remove the most abundant high molecular weight components. Three groups were classified using both partial least squares-discriminate analysis (PLS-DA) and random forest (RF) machine learning algorithms GBM versus non-cancer, lymphoma versus non-cancer and GBM versus lymphoma. For all groups, once the serum was filtered the sensitivity, specificity and overall balanced accuracies decreased. This illustrates that the high molecular weight components are required for discrimination between cancer and non-cancer as well as between tumour types. From a clinical application point of view, this is preferable as less s le preparation is required.
Publisher: Cold Spring Harbor Laboratory
Date: 14-12-2022
DOI: 10.1101/2022.12.14.22283465
Abstract: Discrimination of brain cancer versus non-cancer patients using serum-based attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy diagnostics was first developed by Hands et al . Cameron et al . then went on to stratifying between specific brain tumour types: glioblastoma multiforme (GBM) vs. primary cerebral lymphoma. Expanding on these studies, 30 GBM, 30 lymphoma and 30 non-cancer patients were selected to investigate the influence on test performance by focusing on specific molecular weight regions of the patient serum. Membrane filters with molecular weight cut offs of 100 kDa, 50 kDa, 30 kDa, 10 kDa and 3 kDa were purchased in order to remove the most abundant high molecular weight components. Three groups were classified using both partial least squares-discriminate analysis (PLS-DA) and random forest (RF) machine learning algorithms GBM versus non-cancer, lymphoma versus non-cancer and GBM versus lymphoma. For all groups, once the serum was filtered the sensitivity, specificity and overall balanced accuracies decreased. This illustrates that the high molecular weight components are required for discrimination between cancer and non-cancer as well as between tumour types. From a clinical application point of view, this is preferable as less s le preparation is required.
Location: United Kingdom of Great Britain and Northern Ireland
Location: Australia
No related grants have been discovered for Ashton Theakstone.