In this work, we describe three simple modifications to carbon electrodes that were found to improve the detection of an exemplar neurotransmitter (dopamine) in the presence of physiological interferents (ascorbic acid and/or uric acid). First, the electro-oxidation of ascorbic acid, as a pretreatment, at boron-doped diamond electrode (BDE) interfaces is studied. This treatment did suppress the detection of ascorbic acid oxidation signal, but only in a manner suitable for single-use detection of high concentrations of dopamine (i.e., > 1 μM). Second, the hydrogenation of BDE by electrochemical cathodic treatment and plasma hydrogenation was investigated. Large cathodic, applied potentials (i.e., > - 5 V) and hydrogen plasma pretreatment of BDE lead to the partial and complete oxidization of ascorbic acid before dopamine, respectively. The consequence at hydrogen-plasma treated BDE is the complete electrochemical separation of these two species without any typical catalytic reactions between the analytes. Third, the modification of glassy carbon electrodes with carbon black nanoparticles is explored. This modification enables the simultaneous detection of ascorbic acid, dopamine and uric acid, significantly enhancing the sensitivity of dopamine. Dopamine was best detected using the unconventional route of detecting 5,6-dihydroxyindole, which is made possible by use of carbon-black nanoparticles. The potential of all three studied modifications to be of electroanalytical use is highlighted throughout this work.

The recently developed automated, high-throughput monopolar REIMS platform is suited for the identification of clinically important microorganisms. Although already comparable to the previously reported bipolar forceps method, optimization of the geometry of monopolar electrodes, at the heart of the system, holds the most scope for further improvements to be made. For this, sharp tip and round shaped electrodes were optimized to maximize species-level classification accuracy. Following optimization of the distance between the sample contact point and tube inlet with the sharp tip electrodes, the overall cross-validation accuracy improved from 77% to 93% in negative and from 33% to 63% in positive ion detection modes, compared with the original 4 mm distance electrode. As an alternative geometry, round tube shaped electrodes were developed. Geometry optimization of these included hole size, number, and position, which were also required to prevent plate pick-up due to vacuum formation. Additional features, namely a metal “X”-shaped insert and a pin in the middle were included to increase the contact surface with a microbial biomass to maximize aerosol production. Following optimization, cross-validation scores showed improvement in classification accuracy from 77% to 93% in negative and from 33% to 91% in positive ion detection modes. Supervised models were also built, and after the leave 20% out cross-validation, the overall classification accuracy was 98.5% in negative and 99% in positive ion detection modes. This suggests that the new generation of monopolar REIMS electrodes could provide substantially improved species level identification accuracies in both polarity detection modes. Graphical abstract Electronic supplementary materialThe online version of this article (10.1007/s13361-017-1818-5) contains supplementary material, which is available to authorized users.

Introduction: Delays in the diagnosis and treatment of endometrial cancer negatively impact patient survival. The aim of this study was to establish whether rapid evaporative ionisation mass spectrometry using the iKnife can accurately distinguish between normal and malignant endometrial biopsy tissue samples in real time, enabling point-of-care (POC) diagnoses. Methods: Pipelle biopsy samples were obtained from consecutive women needing biopsies for clinical reasons. A Waters G2-XS Xevo Q-Tof mass spectrometer was used in conjunction with a modified handheld diathermy (collectively called the ‘iKnife’). Each tissue sample was processed with diathermy, and the resultant surgical aerosol containing ionic lipid species was then analysed, producing spectra. Principal component analyses and linear discriminant analyses were performed to determine variance in spectral signatures. Leave-one-patient-out cross-validation was used to test the diagnostic accuracy. Results: One hundred and fifty patients provided Pipelle biopsy samples (85 normal, 59 malignant, 4 hyperplasia and 2 insufficient), yielding 453 spectra. The iKnife differentiated between normal and malignant endometrial tissues on the basis of differential phospholipid spectra. Cross-validation revealed a diagnostic accuracy of 89% with sensitivity, specificity, positive predictive value and negative predictive value of 85%, 93%, 94% and 85%, respectively. Conclusions: This study is the first to use the iKnife to identify cancer in endometrial Pipelle biopsy samples. These results are highly encouraging and suggest that the iKnife could be used in the clinic to provide a POC diagnosis.

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