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Lung cancer is one of the most commonly occurring malignant tumours worldwide. Although some reference methods such as X-ray, computed tomography or bronchoscope are widely used for clinical diagnosis of lung cancer, there is still a need to develop new methods for early detection of lung cancer. Especially needed are approaches that might be non-invasive and fast with high analytical precision and statistically reliable. Herein, we developed a swab "dip" test in saliva whereby swabs were analysed using attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy harnessed to principal component analysis–quadratic discriminant analysis (QDA) and variable selection techniques employing successive projections algorithm (SPA) and genetic algorithm (GA) for feature selection/extraction combined with QDA. A total of 1944 saliva samples (56 designated as lung-cancer positive and 1888 designed as controls) were obtained in a lung cancer-screening programme being undertaken in North-West England. GA-QDA models achieved, for the test set, sensitivity and specificity values of 100.0% and 99.1%, respectively. Three wavenumbers (1422 cm−1, 1546 cm−1 and 1578 cm−1) were identified using the GA-QDA model to distinguish between lung cancer and controls, including ring C–C stretching, C＝N adenine, Amide II [δ(NH), ν(CN)] and νs(COO−) (polysaccharides, pectin). These findings highlight the potential of using biospectroscopy associated with multivariate classification algorithms to discriminate between benign saliva samples and those with underlying lung cancer. [ABSTRACT FROM AUTHOR]

Background: Japanese knotweed (Reynoutria japonica var. japonica), a problematic invasive species, has a wide geographical distribution. We have previously shown the potential for attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy and chemometrics to segregate regional differentiation between Japanese knotweed plants. However, the contribution of environment to spectral differences remains unclear. Herein, the response of Japanese knotweed to varied environmental habitats has been studied. Eight unique growth environments were created by manipulation of the red: far-red light ratio (R: FR), water availability, nitrogen, and micronutrients. Their impacts on plant growth, photosynthetic parameters, and ATR-FTIR spectral profiles, were explored using chemometric techniques, including principal component analysis (PCA), linear discriminant analysis, support vector machines (SVM) and partial least squares regression. Key wavenumbers responsible for spectral differences were identified with PCA loadings, and molecular biomarkers were assigned. Partial least squared regression (PLSR) of spectral absorbance and root water potential (RWP) data was used to create a predictive model for RWP. Results: Spectra from plants grown in different environments were differentiated using ATR-FTIR spectroscopy coupled with SVM. Biomarkers highlighted through PCA loadings corresponded to several molecules, most commonly cell wall carbohydrates, suggesting that these wavenumbers could be consistent indicators of plant stress across species. R: FR most affected the ATR-FTIR spectra of intact dried leaf material. PLSR prediction of root water potential achieved an R2 of 0.8, supporting the potential use of ATR-FTIR spectrometers as sensors for prediction of plant physiological parameters. Conclusions: Japanese knotweed exhibits environmentally induced phenotypes, indicated by measurable differences in their ATR-FTIR spectra. This high environmental plasticity reflected by key biomolecular changes may contribute to its success as an invasive species. Light quality (R: FR) appears critical in defining the growth and spectral response to environment. Cross-species conservation of biomarkers suggest that they could function as indicators of plant-environment interactions including abiotic stress responses and plant health. [ABSTRACT FROM AUTHOR]

Plant hormones are important in the control of physiological and developmental processes including seed germination, senescence, flowering, stomatal aperture, and ultimately the overall growth and yield of plants. Many currently available methods to quantify such growth regulators quickly and accurately require extensive sample purification using complex analytic techniques. Herein we used ultra-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) to create and validate the prediction of hormone concentrations made using attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectral profiles of both freeze-dried ground leaf tissue and extracted xylem sap of Japanese knotweed (Reynoutria japonica) plants grown under different environmental conditions. In addition to these predictions made with partial least squares regression, further analysis of spectral data was performed using chemometric techniques, including principal component analysis, linear discriminant analysis, and support vector machines (SVM). Plants grown in different environments had sufficiently different biochemical profiles, including plant hormonal compounds, to allow successful differentiation by ATR-FTIR spectroscopy coupled with SVM. ATR-FTIR spectral biomarkers highlighted a range of biomolecules responsible for the differing spectral signatures between growth environments, such as triacylglycerol, proteins and amino acids, tannins, pectin, polysaccharides such as starch and cellulose, DNA and RNA. Using partial least squares regression, we show the potential for accurate prediction of plant hormone concentrations from ATR-FTIR spectral profiles, calibrated with hormonal data quantified by UHPLC-HRMS. The application of ATR-FTIR spectroscopy and chemometrics offers accurate prediction of hormone concentrations in plant samples, with advantages over existing approaches. [ABSTRACT FROM AUTHOR]

Diabetes mellitus (DM) is a metabolic disease with an increasing prevalence that is causing worldwide concern. The pre-diabetes stage is the only reversible stage in the patho-physiological process towards DM. Due to the limitations of traditional methods, the diagnosis and detection of DM and pre-diabetes are complicated, expensive, and time-consuming. Therefore, it would be of great benefit to develop a simple, rapid and inexpensive diagnostic test. Herein, the infrared (IR) spectra of serum samples from 111 DM patients, 111 pre-diabetes patients and 333 healthy volunteers were collected using attenuated total reflection Fourier-transform IR (ATR-FTIR) spectroscopy and this was combined with the multivariate analysis of principal component analysis linear discriminant analysis (PCA-LDA) to develop a discriminant model to verify the diagnostic potential of this approach. The study found that the accuracy of the test model established by ATR-FTIR spectroscopy combined with PCA-LDA was 97%, and the sensitivity and specificity were 100% and 100% in the control group, 94% and 98% in the pre-diabetes group, and 91% and 98% in the DM group, respectively. This indicates that this method can effectively diagnose DM and pre-diabetes, which has far-reaching clinical significance. [ABSTRACT FROM AUTHOR]

Saliva is a largely unexplored liquid biopsy that can be readily obtained noninvasively. Not dissimilar to blood plasma or serum, it contains a vast array of bioconstituents that may be associated with the absence or presence of a disease condition. Given its ease of access, the use of saliva is potentially ideal in a point-of-care screening or diagnostic test. Herein, we developed a swab "dip" test in saliva obtained from consenting patients participating in a lung cancer-screening programme being undertaken in north-west England. A total of 998 saliva samples (31 designated as lung-cancer positive and 17 as prostate-cancer positive) were taken in the order in which they entered the clinic (i.e., there was no selection of participants) during the course of this prospective screening programme. Samples (sterile Copan blue rayon swabs dipped in saliva) were analysed using attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy. In addition to unsupervised classification on resultant infrared (IR) spectra using principal component analysis (PCA), a range of feature selection/extraction algorithms were tested. Following preprocessing, the data were split between training (70% of samples, 22 lung-cancer positive versus 664 other) and test (30% of samples, 9 lung-cancer positive versus 284 other) sets. The training set was used for model construction and the test set was used for validation. The best model was the PCA-quadratic discriminant analysis (QDA) algorithm. This PCA-QDA model was built using 8 PCs (90.4% of explained variance) and resulted in 93% accuracy for training and 91% for testing, with clinical sensitivity at 100% and specificity at 91%. Additionally, for prostate cancer patients amongst the male cohort (n = 585), following preprocessing, the data were split between training (70% of samples, 12 prostate-cancer positive versus 399 other) and test (30% of samples, 5 prostate-cancer positive versus 171 other) sets. A PCA-QDA model, again the best model, was built using 5 PCs (84.2% of explained variance) and resulted in 97% accuracy for training and 93% for testing, with clinical sensitivity at 100% and specificity at 92%. These results point to a powerful new approach towards the capability to screen large cohorts of individuals in primary care settings for underlying malignant disease. [ABSTRACT FROM AUTHOR]

This study presents ATR-FTIR (attenuated total reflectance Fourier-transform infrared) spectral analysis of ex vivo oesophageal tissue including all classifications to oesophageal adenocarcinoma (OAC). The article adds further validation to previous human tissue studies identifying the potential for ATR-FTIR spectroscopy in differentiating among all classes of oesophageal transformation to OAC. Tissue spectral analysis used principal component analysis quadratic discriminant analysis (PCA-QDA), successive projection algorithm quadratic discriminant analysis (SPA-QDA), and genetic algorithm quadratic discriminant analysis (GA-QDA) algorithms for variable selection and classification. The variables selected by SPA-QDA and GA-QDA discriminated tissue samples from Barrett's oesophagus (BO) to OAC with 100% accuracy on the basis of unique spectral "fingerprints" of their biochemical composition. Accuracy test results including sensitivity and specificity were determined. The best results were obtained with PCA-QDA, where tissues ranging from normal to OAC were correctly classified with 90.9% overall accuracy (71.4–100% sensitivity and 89.5–100% specificity), including the discrimination between normal and inflammatory tissue, which failed in SPA-QDA and GA-QDA. All the models revealed excellent results for distinguishing among BO, low-grade dysplasia (LGD), high-grade dysplasia (HGD), and OAC tissues (100% sensitivities and specificities). This study highlights the need for further work identifying potential biochemical markers using ATR-FTIR in tissue that could be utilised as an adjunct to histopathological diagnosis for early detection of neoplastic changes in susceptible epithelium. [ABSTRACT FROM AUTHOR]

There is an increasing need for inexpensive and rapid screening tests in point-of-care clinical oncology settings. Herein, we develop a swab "dip" test in saliva obtained from consenting patients participating in a lung-cancer-screening programme being undertaken in North West England. In a pilot study, a total of 211 saliva samples (n = 170 benign, 41 designated cancer-positive) were randomly taken during the course of this prospective lung-cancer-screening programme. The samples (sterile Copan blue rayon swabs dipped in saliva) were analysed using attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy. An exploratory analysis using principal component analysis (PCA,) with or without linear discriminant analysis (LDA), was then undertaken. Three pairwise comparisons were undertaken including: (1) benign vs. cancer following swab analysis; (2) benign vs. cancer following swab analysis with the subtraction of dry swab spectra; and (3) benign vs. cancer following swab analysis with the subtraction of wet swab spectra. Consistent and remarkably similar patterns of clustering for the benign control vs. cancer categories, irrespective of whether the swab plus saliva sample was analysed or whether there was a subtraction of wet or dry swab spectra, was observed. In each case, MANOVA demonstrated that this segregation of categories is highly significant. A k-NN (using three nearest neighbours) machine-learning algorithm also showed that the specificity (90%) and sensitivity (75%) are consistent for each pairwise comparison. In detailed analyses, the swab as a substrate did not alter the level of spectral discrimination between benign control vs. cancer saliva samples. These results demonstrate a novel swab "dip" test using saliva as a biofluid that is highly applicable to be rolled out into a larger lung-cancer-screening programme. [ABSTRACT FROM AUTHOR]

Background: Japanese knotweed (R. japonica var japonica) is one of the world's 100 worst invasive species, causing crop losses, damage to infrastructure, and erosion of ecosystem services. In the UK, this species is an all-female clone, which spreads by vegetative reproduction. Despite this genetic continuity, Japanese knotweed can colonise a wide variety of environmental habitats. However, little is known about the phenotypic plasticity responsible for the ability of Japanese knotweed to invade and thrive in such diverse habitats. We have used attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy, in which the spectral fingerprint generated allows subtle differences in composition to be clearly visualized, to examine regional differences in clonal Japanese knotweed. Results: We have shown distinct differences in the spectral fingerprint region (1800–900 cm− 1) of Japanese knotweed from three different regions in the UK that were sufficient to successfully identify plants from different geographical regions with high accuracy using support vector machine (SVM) chemometrics. Conclusions: These differences were not correlated with environmental variations between regions, raising the possibility that epigenetic modifications may contribute to the phenotypic plasticity responsible for the ability of R. japonica to invade and thrive in such diverse habitats. [ABSTRACT FROM AUTHOR]

Benzo[a]pyrene (B[a]P) and polybrominated diphenyl ethers (PBDEs) are persistent environmental contaminants. The effects in organisms of exposures to binary mixtures of such contaminants remain obscure. Attenuated total reflection Fourier‐transform infrared (ATR‐FTIR) spectroscopy is a label‐free, non‐destructive analytical technique allowing spectrochemical analysis of macromolecular components, and alterations thereof, within tissue samples. Herein, we employed ATR‐FTIR spectroscopy to identify biomolecular changes in rat liver post‐exposure to B[a]P and BDE‐47 (2,2′,4,4′‐tetrabromodiphenyl ether) congener mixtures. Our results demonstrate that significant separation occurs between spectra of tissue samples derived from control versus exposure categories (accuracy = 87%; sensitivity = 95%; specificity = 79%). Additionally, there is significant spectral separation between exposed categories (accuracy = 91%; sensitivity = 98%; specificity = 90%). Segregation between control and all exposure categories were primarily associated with wavenumbers ranging from 1600 to 1700 cm−1. B[a]P and BDE‐47 alone, or in combination, induces liver damage in female rats. However, it is suggested that binary exposure apparently attenuates the toxic effects in rat liver of the individual contaminants. This is supported by morphological observations of liver tissue architecture on hematoxylin and eosin (H&E)‐stained liver sections. Such observations highlight the difficulties in predicting the endpoint effects in target tissues of exposures to mixtures of environmental contaminants. B[a]P or BDE‐47 alone or in combination can cause damage to the liver of female rats. We suggest that BDE‐47 and B[a]P have similar mechanisms of action in inducing liver damage in rats. It is speculated that binary exposure to these agents can result in attenuated toxic effects in rat liver compared with the effects induced following exposure to individual contaminants. [ABSTRACT FROM AUTHOR]

Ovarian cancer remains the most lethal gynaecological malignancy, as its timely detection at early stages remains elusive. Attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy of biofluids has been previously applied in pilot studies for ovarian cancer diagnosis, with promising results. Herein, these initial findings were further investigated by application of ATR-FTIR spectroscopy in a large patient cohort. Spectra were obtained by measurements of blood plasma and serum, as well as urine, from 116 patients with ovarian cancer and 307 patients with benign gynaecological conditions. A preliminary chemometric analysis revealed significant spectral differences in ovarian cancer patients without previous chemotherapy (n = 71) and those who had received neo-adjuvant chemotherapy—NACT (n = 45), so these groups were compared separately with benign controls. Classification algorithms with blind predictive model validation demonstrated that serum was the best biofluid, achieving 76% sensitivity and 98% specificity for ovarian cancer detection, whereas urine exhibited poor performance. A drop in sensitivities for the NACT ovarian cancer group in plasma and serum indicates the potential of ATR-FTIR spectroscopy to identify chemotherapy-related spectral changes. Comparisons of regression coefficient plots for identification of biomarkers suggest that glycoproteins (such as CA125) are the main classifiers for ovarian cancer detection and responsible for smaller differences in spectra between NACT patients and benign controls. This study confirms the capacity of biofluids' ATR-FTIR spectroscopy (mainly blood serum) to diagnose ovarian cancer with high accuracy and demonstrates its potential in monitoring response to chemotherapy, which is reported for the first time. [ABSTRACT FROM AUTHOR]

Meningiomas are the commonest types of tumours in the central nervous system (CNS). It is a benign type of tumour divided into three WHO grades (I, II and III) associated with tumour growth rate and likelihood of recurrence, where surgical outcomes and patient treatments are dependent on the meningioma grade and histological subtype. The development of alternative approaches based on attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy could aid meningioma grade determination and its biospectrochemical profiling in an automated fashion. Herein, ATR-FTIR in combination with chemometric techniques is employed to distinguish grade I, grade II and grade I meningiomas that re-occurred. Ninety-nine patients were investigated in this study where their formalin-fixed paraffin-embedded (FFPE) brain tissue samples were analysed by ATR-FTIR spectroscopy. Subsequent classification was performed via principal component analysis plus linear discriminant analysis (PCA-LDA) and partial least squares plus discriminant analysis (PLS-DA). PLS-DA gave the best results where grade I and grade II meningiomas were discriminated with 79% accuracy, 80% sensitivity and 73% specificity, while grade I versus grade I recurrence and grade II versus grade I recurrence were discriminated with 94% accuracy (94% sensitivity and specificity) and 97% accuracy (97% sensitivity and 100% specificity), respectively. Several wavenumbers were identified as possible biomarkers towards tumour differentiation. The majority of these were associated with lipids, protein, DNA/RNA and carbohydrate alterations. These findings demonstrate the potential of ATR-FTIR spectroscopy towards meningioma grade discrimination as a fast, low-cost, non-destructive and sensitive tool for clinical settings. [ABSTRACT FROM AUTHOR]

Diagnostic tools for the detection of early-stage oesophageal adenocarcinoma (OAC) are urgently needed. Our aim was to develop an accurate and inexpensive method using biofluids (plasma, serum, saliva or urine) for detecting oesophageal stages through to OAC (squamous; inflammatory; Barrett's; low-grade dysplasia; high-grade dysplasia; OAC) using attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy. ATR-FTIR spectroscopy coupled with variable selection methods, with successive projections or genetic algorithms (GA) combined with quadratic discriminant analysis (QDA) were employed to identify spectral biomarkers in biofluids for accurate diagnosis in a hospital setting of different stages through to OAC. Quality metrics (Accuracy, Sensitivity, Specificity and F-score) and biomarkers of disease were computed for each model. For plasma, GA-QDA models using 15 wavenumbers achieved 100% classification for four classes. For saliva, PCA-QDA models achieved 100% for the inflammatory stage and high-quality metrics for other classes. For serum, GA-QDA models achieved 100% performance for the OAC stage using 13 wavenumbers. For urine, PCA-QDA models achieved 100% performance for all classes. Selected wavenumbers using a Student's t-test (95% confidence interval) identified a differentiation of the stages on each biofluid: plasma (929 cm−1 to 1431 cm−1, associated with DNA/RNA and proteins); saliva (1000 cm−1 to 1150 cm−1, associated with DNA/RNA region); serum (1435 cm−1 to 1573 cm−1, associated with methyl groups of proteins and Amide II absorption); and, urine (1681 cm−1 to 1777 cm−1, associated with a high frequency vibration of an antiparallel β-sheet of Amide I and stretching vibration of lipids). Our methods have demonstrated excellent efficacy for a rapid, cost-effective method of diagnosis for specific stages to OAC. These findings suggest a potential diagnostic tool for oesophageal cancer and could be translated into clinical practice. [ABSTRACT FROM AUTHOR]

Metastatic brain tumors represent a significant proportion of tumors identified intraoperatively. A rapid diagnostic method, circumventing the need for histopathology studies, could prove clinically useful. As many spectroscopic studies have shown ability to differentitate between different tumor types, this technique was evaluated for use within metastatic brain tumors. Spectrochemical approaches [Raman and attenuated total reflection Fourier-transform infrared spectroscopy (ATR-FTIR) spectroscopy] were applied to determine how readily they may identify the primary site for the metastatic tumor. Metastases were from primary adenocarcinomas of lung (n = 7) and colorectum (n = 7), and for comparison, metastatic melanoma (n = 7). The objective was to determine if Raman or ATR-FTIR spectroscopy could delineate the origin of the primary tumor. The results demonstrate that there are marked similarities between the two adenocarcinoma groups and whilst Raman and ATR-FTIR can distinguish the three groups with limited success, classification accuracy is greatly improved when combining the adenocarcinoma groups. The use of such techniques in the clinical setting is more likely to be found intraoperatively, determining the presence of a tumor and suggesting the tumor class; however, traditional histopathology would still be needed to identify the primary origin of the tumor. [ABSTRACT FROM AUTHOR]

The use of cell-based assays is essential in reducing the number of vertebrates used in the investigation of chemical toxicities and in regulatory toxicology assessment. An important factor in obtaining meaningful results that can be accurately extrapolated is the use of biologically appropriate cell lines. In the present preliminary study, attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy with multivariate analysis was used to assess the fundamental biomolecular differences between a commonly used cell line, MCF-7 cells, and an environmentally relevant cell line derived from mallard ( Anas platyrhynchos) dermal fibroblasts. To better understand differences in basic cell biochemistry, the cells were analyzed in the untreated state or post exposure to polychlorinated biphenyl (PCB) and polybrominated diphenyl ester (PBDE) congeners. The main spectral peaks in spectra from both cell types were associated with cellular macromolecules, particularly proteins and lipids, but the spectra also revealed some cell-specific differences. Spectra from untreated mallard fibroblasts spectra contained a large peak associated with lipids. The cell-related differences in lipids and deoxyribonucleic acid (DNA) were also identified as regions of spectral alteration induced by PBDE and PCB exposure. Although lipid alterations were observed in post treatment spectra from both cell types, these may be of more significance to mallard fibroblasts, which may be the result of increased intracellular lipid as determined by Nile red staining. Untreated MCF-7 cell spectra contained unique peaks related to DNA and nucleic acids. The DNA-associated spectral regions were also identified as areas of considerable alteration in MCF-7 cells exposed to some congeners including PBDE 47 and PCB 153. The findings indicate that in their native state, MCF-7 and mallard cells have unique biochemical differences, which can be identified using ATR-FTIR spectroscopy. Such differences in biochemical composition may influence cell susceptibility to environmental contaminants and therefore influence the choice of cell type used in toxicology experiments. To our knowledge, the present study is the first study to analyze the biochemistry of a mallard dermal fibroblast cell line and to use ATR-FTIR spectroscopy for this purpose. Thus ATR-FTIR spectroscopy is demonstrated to be a useful tool for exploration of biomolecular variation at the cellular level and with further development, it could be used as part of a panel of cell-based assays to indicate when different results might be seen in environmental species compared with currently used cell lines. Environ Toxicol Chem 2017;36:3127-3137. © 2017 SETAC [ABSTRACT FROM AUTHOR]

This study evaluated the potential of deuteration to enhance the mechanistic information obtainable by biospectroscopy techniques in biological-cell models. These techniques were previously demonstrated to identify low-dose effects (≤nM) induced by test agents; this is of critical interest in terms of developing novel approaches to monitor environmentally-induced cell alterations. Attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy was coupled with multivariate analysis to characterize a low-dose (10−10 M) compared to a high-dose (10−6 M) exposure of benzo[a]pyrene (B[a]P) in oestrogen-responsive MCF-7 cells; these results were used as a positive control for spectroscopic detection of B[a]P-induced effects. Deuterium oxide (D2O) was then applied as part of a fixative solution and/or at low levels incorporated into growth medium prior to ATR-FTIR spectrochemical analysis. The application of D2O as an alternative solvent in spectroscopy is widespread, but D2O has never before been applied to biospectroscopic analysis of in vitro toxicology assays. This allowed comparison between deuterated- and typically-derived IR spectra, facilitating significant insights into the effects of deuteration, and suggested that the addition of D2O to biospectroscopy assays could improve understanding of low-dose effects. [ABSTRACT FROM AUTHOR]

With increasing production of carbon nanoparticles (CNPs), environmental release of these entities becomes an ever-greater inevitability. However, many questions remain regarding their impact on soil microorganisms. This study examined the effects of long or short multiwalled carbon nanotubes (MWCNTs), C60 fullerene and fullerene soot in Gram-negative bacteria. Attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy was applied to derive signature spectral fingerprints of effects. A concentration-dependent response in spectral alterations was observed for each nanoparticle type. Long or short MWCNTs and fullerene soot gave rise to similar alterations to lipids, Amide II and DNA. The extent of alteration varies with nanoparticle size, with smaller short MWCNTs resulting in greater toxicity than long MWCNTs. Fullerene soot was the least toxic. C60 results in the most distinct and largest overall alterations, notably in extensive protein alteration. This work demonstrates a novel approach for assaying and discriminating the effects of CNPs in target systems. [Copyright &y& Elsevier]

Sensor-based detection of pests and pathogens in a high throughput and non-destructive manner is essential for mitigating crop loss. Infrared (IR) sensors in the form of vibrational spectroscopy provide both biochemical information about disease, as well as a large number of variables for chemometrics. This approach is highly adaptable to most biological systems including interactions between plants and their environments. Fast-acting necrotrophic fungal pathogens present a specific group of pests with adverse effects on food production and supply and are therefore pertinent to food security. Botrytis cinerea and Solanum lycopersicum are models for the study of fungal and crop biology respectively. Herein we use a compact mid-IR spectrometer with attenuated total reflection (ATR) attachment to measure the plant-microbe interaction between S. lycopersicum and B. cinerea on leaves, in vivo of intact plants. Chemometric models including exploratory principal component analysis (PCA) solely, and as a classifier in combination with linear discriminant analysis (PCA-LDA) are applied. Fingerprint spectra (1800−900 cm−1) were excellent discriminators of plant disease in both visually symptomatic as well pre-symptomatic plants. Major biochemical alterations in leaf tissue as a result of infection are discussed. Diagnostic potential for automatic decision-making platforms is shown by high accuracy rates of 100 % for detecting plant disease at various stages of progression. [ABSTRACT FROM AUTHOR]

Expensive and time-consuming methods are currently used to identify manipulated whey protein concentrate (WPC). We tested the application of attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy to detect and quantify adulteration of WPC with wheat flour (WF). ATR-FTIR is based on the interaction between IR radiation and the molecular bonds in the samples, allowing the capture of its vibration energy and the acquisition of spectra with information that can be used to identify and quantify functional groups. WPC Samples were adulterated with different percentages of WF and spectra were collected. Amide I and II bands exhibit a decreasing protein content when more WF is added. Conversely, at the carbohydrate characteristic band (1080 cm−1), there is an increasing intensity as more WF is added. Partial least squares (PLS) regression models presented low prediction errors and high coefficients of determination. Furthermore, one of the models was chosen for a blind prediction test of 10 samples adulterated with random amounts of WF, and it could make reasonable predictions of the actual levels of adulteration. Therefore, ATR-FTIR spectroscopy coupled with multivariate analysis shows strong potential to detect adulteration in WPC with WF and the capability to quantify the added mass content. • Amide I and II bands showed decreasing intensity as more WF was added. • Carbohydrate band revealed increasing intensity with the addition of WF. • Partial Least Squares regressions resulted in high accuracy and low errors. • Blinded prediction test showed good prediction values for WF added. • ATR-FTIR spectroscopy revealed strong potential as a rapid screening test. [ABSTRACT FROM AUTHOR]

Understanding how organisms respond to trace elements is important because some are essential for normal bodily homeostasis, but can additionally be toxic at high concentrations. The inflection point for many of these elements is unknown and requires sensitive techniques capable of detecting subtle cellular changes as well as cytotoxic alterations. In this study, we treated human cells with arsenic (As), copper or selenium (Se) in a dose-response manner and used attenuated total reflection Fourier-transform infrared (ATR-FTIR) microspectroscopy combined with computational analysis to examine cellular alterations. Cell cultures were treated with Asv, Cu2+ or Seiv at concentrations ranging from 0.001mgL−1 to 1000mgL−1 and their effects were spectrochemically determined. Results show that Asv and Cu2+ induce bimodal dose-response effects on cells; this is in line with hormesis-driven responses. Lipids and proteins seem to be the main cell targets for all the elements tested; however, each compound produced a unique fingerprint of effect. Spectral biomarkers indicate that all test agents generate reactive oxygen species (ROS), which could either stimulate repair mechanisms or induce damage in cells. [ABSTRACT FROM AUTHOR]

[Display omitted] • IR spectrochemical approaches can classify subtypes of breast cancer based on spectral alterations. • IR spectroscopy may be diagnostic for accurate diagnosis and differentiation of subtypes. • IR spectroscopy has potential for application towards intraoperative management. The present study aimed to investigate whether attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy coupled with multivariate analysis could be applied to discriminate and classify among breast tumour molecular subtypes based on the unique spectral "fingerprints" of their biochemical composition. The different breast cancer tissues and normal breast tissues were collected and identified by pathology and ATR-FTIR spectroscopy respectively. The study indicates that the levels of the lipid-to-protein, nucleic acid-to-lipid, phosphate-to-carbohydrate and their secondary structure ratio, including RNA-to-DNA, Amide I-to-Amide II, and RNA-to-lipid ratios were significantly altered among the molecular subtype of breast tumour compared with normal breast tissues, which helps explain the changes in the biochemical structure of different molecular phenotypes of breast cancer. Tentatively-assigned characteristic peak ratios of infrared (IR) spectra reflect the changes of the macromolecule structure in different issues to a great extent and can be used as a potential biomarker to predict the molecular subtype of breast tumour. The present study acts as the first case study to show the successful application of IR spectroscopy in classifying subtypes of breast cancer with biochemical alterations. Therefore, the present study is likely to help to provide a new diagnostic approach for the accurate diagnosis of breast tumours and differential molecular subtypes and has the potential to be used for further intraoperative management. [ABSTRACT FROM AUTHOR]