7 research outputs found

    Investigating optimum sample preparation for infrared spectroscopic serum diagnostics

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    Biofluids, such as serum and plasma, represent an ideal medium for the diagnosis of disease due to their ease of collection, that can be performed worldwide, and their fundamental involvement in human function. The ability to diagnose disease rapidly with high sensitivity and specificity is essential to exploit advances in new treatments, in addition the ability to rapidly profile disease without the need for large scale medical equipment (e.g. MRI, CT) would enable closer patient monitoring with reductions in mortality and morbidity. Due to these reasons vibrational spectroscopy has been investigated as a diagnostic tool and has shown great promise for serum spectroscopic diagnostics. However, the optimum sample preparation, optimum sampling mode and the effect of sample preparation on the serum spectrum are unknown. This paper examines repeatability and reproducibility of attenuated total reflection (ATR) compared to transmission sampling modes and their associated serum sample preparation with spectral standard deviation of 0.0015 (post pre-processing) achievable for both sampling modes proving the collection of robust spectra. In addition this paper investigates the optimum serum sample dilution factor for use in high throughput transmission mode analysis with a 3-fold dilution proving optimum and shows the use of ATR and transmission mode spectroscopy to illuminate similar discriminatory differences in a patient study. These fundamental studies provide proof of robust spectral collection that will be required to enable clinical translation of serum spectroscopic diagnostics

    Developing and understanding biofluid vibrational spectroscopy : a critical review

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    Vibrational spectroscopy can provide rapid, label-free, and objective analysis for the clinical domain. Spectroscopic analysis of biofluids such as blood components (e.g. serum and plasma) and others in the proximity of the diseased tissue or cell (e.g. bile, urine, and sputum) offers non-invasive diagnostic/monitoring possibilities for future healthcare that are capable of rapid diagnosis of diseases via specific spectral markers or signatures. Biofluids offer an ideal diagnostic medium due to their ease and low cost of collection and daily use in clinical biology. Due to the low risk and in vasiveness of their collection they are widely welcomed by patients as a diagnostic medium. This review under scores recent research within the field of biofluid spectroscopy and its use in myriad pat hologies such as cancer and infectious diseases. It highlights current progresses, advents, and pitfalls within the field and discusses future spectroscopic clinical potentials for diagnostics. The requirements and issues surrounding clinical translation are also considered

    Rapid pre-symptomatic diagnosis of sepsis by vibrational spectroscopy

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    Le sepsis est une dĂ©rĂ©gulation de la rĂ©ponse de l’hĂŽte Ă  une infection, associĂ© Ă  un dysfonctionnement des organes engageant le pronostic vital du patient. Plus de 30 millions de cas et 5 millions de dĂ©cĂšs sont estimĂ©s par an dans le monde. Le diagnostic du sepsis est basĂ© sur des signes cliniques non spĂ©cifiques et la longue procĂ©dure d’identification des pathogĂšnes responsables de l’infection. L’objectif de cette Ă©tude est de dĂ©velopper et d’évaluer le potentiel de la spectroscopie vibrationnelle appliquĂ©e au sĂ©rum pour amĂ©liorer le diagnostic du sepsis. Les dĂ©fis inhĂ©rents Ă  la nature de l’échantillon et Ă  la technique de mĂȘme que certains paramĂštres prĂ©-analytiques ont Ă©tĂ© Ă©valuĂ©s pour assurer la qualitĂ© des donnĂ©es. Les variations de contenu en eau des Ă©chantillons aprĂšs sĂ©chage pouvant affecter la discrimination des donnĂ©es, ont Ă©tĂ© corrigĂ©es en testant diffĂ©rentes mĂ©thodes. Enfin, des sĂ©rums de patients septicĂ©miques (n=380) collectĂ©s avant chirurgie et jusqu’à 3 jours avant et le jour du diagnostic ont Ă©tĂ© analysĂ©s. Les Ă©chantillons du groupe contrĂŽle (n=353) collectĂ©s suivant la mĂȘme cinĂ©tique, provenant de patients ayant un profil similaire en termes d’ñge, de sexe, de procĂ©dure chirurgicale subie mais n’ayant pas dĂ©veloppĂ© de sepsis et des Ă©chantillons (n=180) de patients atteints d’un syndrome de rĂ©ponse inflammatoire systĂ©mique collectĂ©s avant chirurgie et le jour du diagnostic ont Ă©galement Ă©tĂ© analysĂ©s. Les donnĂ©es acquises ont Ă©tĂ© exploitĂ©es par mĂ©thodes chimiomĂ©triques pour discriminer des zones spectrales reflĂ©tant des diffĂ©rences de composition molĂ©culaire avec des sensibilitĂ©s et spĂ©cificitĂ©s supĂ©rieures Ă  70% malgrĂ© l’influence de l’eau rĂ©siduelle.Sepsis is a dysregulated host response to an infection that causes life-threatening organ dysfunction. Each year, over 30 million cases and 5 million deaths are estimated worldwide. Diagnosis of sepsis is based on non-specific clinical signs and time consuming positive identification of the causative pathogen. The objective of this study is to develop and evaluate the potential of vibrational spectroscopy applied to human serum to improve diagnosis of sepsis. Challenges of serum spectroscopy inherent to the sample nature and preparation as well as to the technique have been assessed to determine the most suitable methodological approach. Then, some aspects of the pre-analytical phase have been addressed in order to standardise protocols in sample handling and preparation for spectral acquisitions to ensure quality and reproducibility of spectral data collected. Different methods have been tested to correct water content variations in dried serum, which can impact on data discrimination. Finally, based upon the developed methodology, patient serum samples (n=380) collected before surgery, up to 3 days before sepsis diagnosis, and on the day of sepsis diagnosis have been analysed. Control serum samples (n=353) from age/ sex/ procedure-matched patients who did not go on to develop sepsis have been also analysed over similar timeframes post-surgery as well as samples (n=180) from patients with systemic inflammatory response syndrome. Spectral data acquired have been interrogated by chemometric methods to identify spectral zones reflecting differences in molecular composition allowing discrimination with over 70% of sensitivities and specificities despite water interferences

    Investigating pre‐analytical requirements for serum and plasma based infrared spectro‐diagnostic

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    International audienceRadiation therapy (RT) is used to treat approximately 50% of all cancer patients. However, RT causes a wide range of adverse late effects that can affect a patient's quality of life. There are currently no predictive assays in clinical use to identify patients at risk of normal tissue radiation toxicity. This study aimed to investigate the potential of Fourier transform infrared (FTIR) spectroscopy for monitoring radiotherapeutic response. Blood plasma was acquired from 53 prostate cancer patients at five different time points: prior to treatment, after hormone treatment, at the end of radiotherapy, two months post radiotherapy and eight months post radiotherapy. FTIR spectra were recorded from plasma samples at all time points and the data was analysed using MATLAB software. Discrimination was observed between spectra recorded at baseline versus follow up time points, as well as between spectra from patients showing minimal and severe acute and late toxicity using principal component analysis. A partial least squares discriminant analysis model achieved sensitivity and specificity rates ranging from 80% to 99%. This technology may have potential to monitor radiotherapeutic response in prostate cancer patients using non-invasive blood plasma samples and could lead to individualised patient radiotherapy

    An infrared spectral biomarker accurately predicts neurodegenerative disease class in the absence of overt symptoms.

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    Although some neurodegenerative diseases can be identified by behavioral characteristics relatively late in disease progression, we currently lack methods to predict who has developed disease before the onset of symptoms, when onset will occur, or the outcome of therapeutics. New biomarkers are needed. Here we describe spectral phenotyping, a new kind of biomarker that makes disease predictions based on chemical rather than biological endpoints in cells. Spectral phenotyping uses Fourier Transform Infrared (FTIR) spectromicroscopy to produce an absorbance signature as a rapid physiological indicator of disease state. FTIR spectromicroscopy has over the past been used in differential diagnoses of manifest disease. Here, we report that the unique FTIR chemical signature accurately predicts disease class in mouse with high probability in the absence of brain pathology. In human cells, the FTIR biomarker accurately predicts neurodegenerative disease class using fibroblasts as surrogate cells
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