Dataset Information

Herbal Medicine Characterization Perspectives Using Advanced FTIR Sample Techniques - Diffuse Reflectance (DRIFT) and Photoacoustic Spectroscopy (PAS).

ABSTRACT: This study demonstrates the significant potential of the Fourier transform infrared spectroscopy (FTIR) sampling methods: cantilever-enhanced Fourier transform infrared photoacoustic spectroscopy (FTIR PAS) and diffuse reflectance infrared spectroscopy (FTIR DRIFT) in the field of herbal medicines (HM). In the present work we investigated DRIFT and PAS sampling methods because they do not require sample preparation, samples may be opaque or dark, require small amounts, both liquid and solid samples can be measured, and solid samples can be analyzed on a small scale. Experiments conducted prove high sensitivity, reproducibility and capability in combination with an unsupervised multivariate analysis technique to discriminate important characteristics of HM, such as the identification of plant parts, differentiation of samples by types, and determination of the concentration of extractable compounds in HM.

SUBMITTER: Brangule A

PROVIDER: S-EPMC7182013 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Herbal Medicine Characterization Perspectives Using Advanced FTIR Sample Techniques - Diffuse Reflectance (DRIFT) and Photoacoustic Spectroscopy (PAS).

Brangule Agnese A Šukele Renāte R Bandere Dace D

Frontiers in plant science 20200417

This study demonstrates the significant potential of the Fourier transform infrared spectroscopy (FTIR) sampling methods: cantilever-enhanced Fourier transform infrared photoacoustic spectroscopy (FTIR PAS) and diffuse reflectance infrared spectroscopy (FTIR DRIFT) in the field of herbal medicines (HM). In the present work we investigated DRIFT and PAS sampling methods because they do not require sample preparation, samples may be opaque or dark, require small amounts, both liquid and solid samp ...[more]

PMID: 32362902

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Project description:BACKGROUND:The topical HIV prevention (microbicides) field is in acute need of a method to rapidly and objectively measure adherence to product use in clinical trials. Infrared (IR) spectroscopy has been used in many pharmaceutical and forensic applications but has yet to be applied to adherence monitoring. In this study, we report on efforts to test the feasibility of using IR spectroscopy as a means to measure residual active or placebo vaginal product, semen exposure and vaginal insertion from a single swab. METHODS:A portable IR spectrometer equipped with diamond attenuated total reflectance (ATR) was used to capture spectra of unused vs. vaginally-used swabs, vaginal swabs containing semen, and vaginal swabs to which either tenofovir-containing or matching placebo products (vaginal gel or insert) were added. Spectral data obtained from swabs placed directly on the spectrometer were divided into calibration and testing sets for developing and validating discriminant models set up to provide yes/no predictions of: vaginal vs. non-vaginal use, presence vs. no presence of each test product, and presence vs. no presence of semen. Further validation of models was performed using vaginal swabs collected from a clinical study evaluating vaginally administered placebo insert formulations. RESULTS:For each discriminant model developed to predict vaginal vs. non-vaginal use, presence vs. no presence of each test product, and presence vs. no presence of semen, classified validation samples not included in the model development were correctly identified into their respective classes with minimal prediction error. Clinically obtained vaginal swabs collected 15-60 minutes after placebo insert use were also correctly identified, further validating the models. CONCLUSION:Our findings demonstrate the proof of concept that IR spectroscopy can be a method for rapid detection and characterization of microbicide products and biological fluids present in vaginal swabs. This novel method has potential to support real-time, on-site adherence monitoring in clinical or field settings.

Project description:This work investigates the application of reflectance Fourier transform infrared (FTIR) microscopic imaging for rapid, and non-invasive detection and classification between Bacillus subtilis and Escherichia coli cell suspensions dried onto metallic substrates (stainless steel (STS) and aluminium (Al) slides) in the optical density (OD) concentration range of 0.001 to 10. Results showed that reflectance FTIR of samples with OD lower than 0.1 did not present an acceptable spectral signal to enable classification. Two modelling strategies were devised to evaluate model performance, transferability and consistency among concentration levels. Modelling strategy 1 involves training the model with half of the sample set, consisting of all concentrations, and applying it to the remaining half. Using this approach, for the STS substrate, the best model was achieved using support vector machine (SVM) classification, providing an accuracy of 96% and Matthews correlation coefficient (MCC) of 0.93 for the independent test set. For the Al substrate, the best SVM model produced an accuracy and MCC of 91% and 0.82, respectively. Furthermore, the aforementioned best model built from one substrate was transferred to predict the bacterial samples deposited on the other substrate. Results revealed an acceptable predictive ability when transferring the STS model to samples on Al (accuracy = 82%). However, the Al model could not be adapted to bacterial samples deposited on STS (accuracy = 57%). For modelling strategy 2, models were developed using one concentration level and tested on the other concentrations for each substrate. Results proved that models built from samples with moderate (1 OD) concentration can be adapted to other concentrations with good model generalization. Prediction maps revealed the heterogeneous distribution of biomolecules due to the coffee ring effect. This work demonstrated the feasibility of applying FTIR to characterise spectroscopic fingerprints of dry bacterial cells on substrates of relevance for food processing.

Dataset Information

Herbal Medicine Characterization Perspectives Using Advanced FTIR Sample Techniques - Diffuse Reflectance (DRIFT) and Photoacoustic Spectroscopy (PAS).

Publications

Herbal Medicine Characterization Perspectives Using Advanced FTIR Sample Techniques - Diffuse Reflectance (DRIFT) and Photoacoustic Spectroscopy (PAS).

Similar Datasets

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