Investigating centrifugal filtration of serum-based FTIR spectroscopy for the stratification of brain tumours.

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 sample preparation is required.

Vibrational Spectroscopy for the Triage of Traumatic Brain Injury Computed Tomography Priority and Hospital Admissions.

Computed tomography (CT) brain imaging is routinely used to support clinical decision-making in patients with traumatic brain injury (TBI). Only 7% of scans, however, demonstrate evidence of TBI. The other 93% of scans contribute a significant cost to the healthcare system and a radiation risk to patients. There may be better strategies to identify which patients, particularly those with mild TBI, are at risk of deterioration and require hospital admission. We introduce a blood serum liquid biopsy that utilizes attenuated total reflectance (ATR)-Fourier transform infrared (FTIR) spectroscopy with machine learning algorithms as a decision-making tool to identify which patients with mild TBI will most likely present with a positive CT scan. Serum samples were obtained from patients (n = 298) patients who had acquired a TBI and were enrolled in CENTER-TBI and from asymptomatic control patients (n = 87). Injury patients (all severities) were stratified against non-injury controls. The cohort with mild TBI was further examined by stratifying those who had at least one CT abnormality against those who had no CT abnormalities. The test performed exceptionally well in classifications of patients with mild injury versus non-injury controls (sensitivity = 96.4% and specificity = 98.0%) and also provided a sensitivity of 80.2% when stratifying mild patients with at least one CT abnormality against those without. The results provided illustrate the test ability to identify four of every five CT abnormalities and show great promise to be introduced as a triage tool for CT priority in patients with mild TBI.

Liquid Biopsy for Pancreatic Cancer Detection Using Infrared Spectroscopy.

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 samples, and cancer versus symptomatic non-malignant control samples, 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.

Emission from the working and counter electrodes under co-reactant electrochemiluminescence conditions.

We present a new approach to explore the potential-dependent multi-colour co-reactant electrochemiluminescence (ECL) from multiple luminophores. The potentials at both the working and counter electrodes, the current between these electrodes, and the emission over cyclic voltammetric scans were simultaneously measured for the ECL reaction of Ir(ppy)3 and either [Ru(bpy)3]2+ or [Ir(df-ppy)2(ptb)]+, with tri-n-propylamine as the co-reactant. The counter electrode potential was monitored by adding a differential electrometer module to the potentiostat. Plotting the data against the applied working electrode potential and against time provided complementary depictions of their relationships. Photographs of the ECL at the surface of the two electrodes were taken to confirm the source of the emissions. This provided a new understanding of these multifaceted ECL systems, including the nature of the counter electrode potential and the possibility of eliciting ECL at this electrode, a mechanism-based rationalisation of the interactions of different metal-complex luminophores, and a previously unknown ECL pathway for the Ir(ppy)3 complex at negative potentials that was observed even in the absence of the co-reactant.

Rapid Spectroscopic Liquid Biopsy for the Universal Detection of Brain Tumours.

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.

Biofluid diagnostics by FTIR spectroscopy: A platform technology for cancer detection.

Fourier Transform Infrared Spectroscopy (FTIR) has been largely employed by scientific researchers to improve diagnosis and treatment of cancer, using various biofluids and tissues. The technology has proved to be easy to use, rapid and cost-effective for analysis on human blood serum to discriminate between cancer versus healthy control samples. The high sensitivity and specificity achievable during samples classification aided by machine learning algorithms, offers an opportunity to transform cancer referral pathways, as it has been demonstrated in a unique and recent prospective clinical validation study on brain tumours. We herein highlight the importance of early detection in cancer research using FTIR, discussing the technique, the suitability of serum for analysis and previous studies, with special focus on pre-clinical factors and clinical translation requirements and development.

'Cathodic' electrochemiluminescence of [Ru(bpy)3]2+ and tri-n-propylamine confirmed as emission at the counter electrode.

A new approach to examine electrochemiluminescence (ECL), in which the potentials at both the working and counter electrodes are measured and the emitted light is detected by a photomultiplier tube, camera and then a charge-coupled device (CCD) spectrometer, provides unequivocal evidence that the purported cathodic ECL of [Ru(bpy)3]2+ and tri-n-propylamine actually arises from anodic reactions at the counter electrode.

Chemiluminescence detection of MDMA in street drug samples using tris(2,2'-bipyridine)ruthenium(III).

Tris(2,2'-bipyridine)ruthenium(II) chemiluminescence was investigated for the detection of 3,4-methylenedioxymethamphetamine (MDMA) and several related compounds in street drug samples. 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 samples. 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 samples. This is the first report of tris(2,2'-bipyridine)ruthenium(II) chemiluminescence for the detection of MDMA and related amphetamine derivatives.