Publications by authors named "Francis L Martin"

240 Publications

Distinguishing active from quiescent disease in ANCA-associated vasculitis using attenuated total reflection Fourier-transform infrared spectroscopy.

Sci Rep 2021 May 11;11(1):9981. Epub 2021 May 11.

Biocel UK Ltd, Hull, UK.

The current lack of a reliable biomarker of disease activity in anti-neutrophil cytoplasmic autoantibody (ANCA) associated vasculitis poses a significant clinical unmet need when determining relapsing or persisting disease. In this study, we demonstrate for the first time that attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy offers a novel and functional candidate biomarker, distinguishing active from quiescent disease with a high degree of accuracy. Paired blood and urine samples were collected within a single UK centre from patients with active disease, disease remission, disease controls and healthy controls. Three key biofluids were evaluated; plasma, serum and urine, with subsequent chemometric analysis and blind predictive model validation. Spectrochemical interrogation proved plasma to be the most conducive biofluid, with excellent separation between the two categories on PC2 direction (AUC 0.901) and 100% sensitivity (F-score 92.3%) for disease remission and 85.7% specificity (F-score 92.3%) for active disease on blind predictive modelling. This was independent of organ system involvement and current ANCA status, with similar findings observed on comparative analysis following successful remission-induction therapy (AUC > 0.9, 100% sensitivity for disease remission, F-score 75%). This promising technique is clinically translatable and warrants future larger study with longitudinal data, potentially aiding earlier intervention and individualisation of treatment.
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http://dx.doi.org/10.1038/s41598-021-89344-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8113456PMC
May 2021

Diagnostic segregation of human breast tumours using Fourier-transform infrared spectroscopy coupled with multivariate analysis: Classifying cancer subtypes.

Spectrochim Acta A Mol Biomol Spectrosc 2021 Jul 15;255:119694. Epub 2021 Mar 15.

School of Public Health, Guilin Medical University, Guilin, Guangxi, PR China. Electronic address:

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.
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http://dx.doi.org/10.1016/j.saa.2021.119694DOI Listing
July 2021

Spectrochemical determination of effects on rat liver of binary exposure to benzo[a]pyrene and 2,2',4,4'-tetrabromodiphenyl ether.

J Appl Toxicol 2021 Mar 23. Epub 2021 Mar 23.

Department of Environmental Health and Occupational Medicine, School of Public Health, Guilin Medical University, Guilin, China.

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 . 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.
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http://dx.doi.org/10.1002/jat.4165DOI Listing
March 2021

The evolving role of MUC16 (CA125) in the transformation of ovarian cells and the progression of neoplasia.

Carcinogenesis 2021 Apr;42(3):327-343

Biocel UK Ltd, Hull, UK.

MUC16 (the cancer antigen CA125) is the most commonly used serum biomarker in epithelial ovarian cancer, with increasing levels reflecting disease progression. It is a transmembrane glycoprotein with multiple isoforms, undergoing significant changes through the metastatic process. Aberrant glycosylation and cleavage with overexpression of a small membrane-bound fragment consist MUC16-related mechanisms that enhance malignant potential. Even MUC16 knockdown can induce an aggressive phenotype but can also increase susceptibility to chemotherapy. Variable MUC16 functions help ovarian cancer cells avoid immune cytotoxicity, survive inside ascites and form metastases. This review provides a comprehensive insight into MUC16 transformations and interactions, with description of activated oncogenic signalling pathways, and adds new elements on the role of its differential glycosylation. By following the journey of the molecule from pre-malignant states to advanced stages of disease it demonstrates its behaviour, in relation to the phenotypic shifts and progression of ovarian cancer. Additionally, it presents proposed differences of MUC16 structure in normal/benign conditions and epithelial ovarian malignancy.
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http://dx.doi.org/10.1093/carcin/bgab010DOI Listing
April 2021

Ultrarapid On-Site Detection of SARS-CoV-2 Infection Using Simple ATR-FTIR Spectroscopy and an Analysis Algorithm: High Sensitivity and Specificity.

Anal Chem 2021 02 22;93(5):2950-2958. Epub 2021 Jan 22.

Biocel UK Ltd., 15 Riplingham Road, West Ella, Hull HU10 6TS, U.K.

There is an urgent need for ultrarapid testing regimens to detect the severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2] infections in real-time within seconds to stop its spread. Current testing approaches for this RNA virus focus primarily on diagnosis by RT-qPCR, which is time-consuming, costly, often inaccurate, and impractical for general population rollout due to the need for laboratory processing. The latency until the test result arrives with the patient has led to further virus spread. Furthermore, latest antigen rapid tests still require 15-30 min processing time and are challenging to handle. Despite increased polymerase chain reaction (PCR)-test and antigen-test efforts, the pandemic continues to evolve worldwide. Herein, we developed a superfast, reagent-free, and nondestructive approach of attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy with subsequent chemometric analysis toward the prescreening of virus-infected samples. Contrived saliva samples spiked with inactivated γ-irradiated COVID-19 virus particles at levels down to 1582 copies/mL generated infrared (IR) spectra with a good signal-to-noise ratio. Predominant virus spectral peaks are tentatively associated with nucleic acid bands, including RNA. At low copy numbers, the presence of a virus particle was found to be capable of modifying the IR spectral signature of saliva, again with discriminating wavenumbers primarily associated with RNA. Discrimination was also achievable following ATR-FTIR spectral analysis of swabs immersed in saliva variously spiked with virus. Next, we nested our test system in a clinical setting wherein participants were recruited to provide demographic details, symptoms, parallel RT-qPCR testing, and the acquisition of pharyngeal swabs for ATR-FTIR spectral analysis. Initial categorization of swab samples into negative versus positive COVID-19 infection was based on symptoms and PCR results ( = 111 negatives and 70 positives). Following training and validation (using = 61 negatives and 20 positives) of a genetic algorithm-linear discriminant analysis (GA-LDA) algorithm, a blind sensitivity of 95% and specificity of 89% was achieved. This prompt approach generates results within 2 min and is applicable in areas with increased people traffic that require sudden test results such as airports, events, or gate controls.
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http://dx.doi.org/10.1021/acs.analchem.0c04608DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7857139PMC
February 2021

Applying Raman Microspectroscopy to Evaluate the Effects of Nutrient Cations on Alkane Bioavailability to ADP1.

Environ Sci Technol 2020 12 4;54(24):15800-15810. Epub 2020 Dec 4.

Biocel Ltd, Hull HU10 7TS, U.K.

Contamination with petroleum hydrocarbons causes extensive damage to ecological systems. On oil-contaminated sites, alkanes are major components; many indigenous bacteria can access and/or degrade alkanes. However, their ability to do so is affected by external properties of the soil, including nutrient cations. This study used Raman microspectroscopy to study how nutrient cations affect alkanes' bioavailability to ADP1 (a known degrader). Treated with Na, K, Mg, and Ca at 10 mM, was exposed to seven -alkanes (decane, dodecane, tetradecane, hexadecane, nonadecane, eicosane, and tetracosane) and one alkane mixture (mineral oil). Raman spectral analysis indicated that bioavailability of alkanes varied with carbon chain lengths, and additional cations altered the bacterial response to -alkanes. Sodium significantly increased the bacterial affinity toward decane and dodecane, and K and Mg enhanced the bioavailability of tetradecane and hexadecane. In contrast, the bacterial response was inhibited by Ca for all alkanes. Similar results were observed in mineral oil exposure. Our study employed Raman spectral assay to offer a deep insight into how nutrient cations affect the bioavailability of alkanes, suggesting that nutrient cations can play a key role in influencing the harmful effects of hydrocarbons and could be optimized to enhance the bioremediation strategy.
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http://dx.doi.org/10.1021/acs.est.0c04944DOI Listing
December 2020

A comparative analysis of different biofluids towards ovarian cancer diagnosis using Raman microspectroscopy.

Anal Bioanal Chem 2021 Jan 26;413(3):911-922. Epub 2020 Nov 26.

School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston, PR1 2HE, UK.

Biofluids, such as blood plasma or serum, are currently being evaluated for cancer detection using vibrational spectroscopy. These fluids contain information of key biomolecules, such as proteins, lipids, carbohydrates and nucleic acids, that comprise spectrochemical patterns to differentiate samples. Raman is a water-free and practically non-destructive vibrational spectroscopy technique, capable of recording spectrochemical fingerprints of biofluids with minimum or no sample preparation. Herein, we compare the performance of these two common biofluids (blood plasma and serum) together with ascitic fluid, towards ovarian cancer detection using Raman microspectroscopy. Samples from thirty-eight patients were analysed (n = 18 ovarian cancer patients, n = 20 benign controls) through different spectral pre-processing and discriminant analysis techniques. Ascitic fluid provided the best class separation in both unsupervised and supervised discrimination approaches, where classification accuracies, sensitivities and specificities above 80% were obtained, in comparison to 60-73% with plasma or serum. Ascitic fluid appears to be rich in collagen information responsible for distinguishing ovarian cancer samples, where collagen-signalling bands at 1004 cm (phenylalanine), 1334 cm (CHCH wagging vibration), 1448 cm (CH deformation) and 1657 cm (Amide I) exhibited high statistical significance for class differentiation (P < 0.001). The efficacy of vibrational spectroscopy, in particular Raman spectroscopy, combined with ascitic fluid analysis, suggests a potential diagnostic method for ovarian cancer. Raman microspectroscopy analysis of ascitic fluid allows for discrimination of patients with benign gynaecological conditions or ovarian cancer.
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http://dx.doi.org/10.1007/s00216-020-03045-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7808972PMC
January 2021

ATR-FTIR spectroscopy in blood plasma combined with multivariate analysis to detect HIV infection in pregnant women.

Sci Rep 2020 11 19;10(1):20156. Epub 2020 Nov 19.

Institute of Chemistry, Biological Chemistry and Chemometrics, Federal University of Rio Grande Do Norte, Natal, RN, 5072-970, Brazil.

The primary concern for HIV-infected pregnant women is the vertical transmission that can occur during pregnancy, in the intrauterine period, during labour or even breastfeeding. The risk of vertical transmission can be reduced by early diagnosis. Therefore, it is necessary to develop new methods to detect this virus in a quick and low-cost fashion, as colorimetric assays for HIV detection tend to be laborious and costly. Herein, attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy combined with multivariate analysis was employed to distinguish HIV-infected patients from healthy uninfected controls in a total of 120 blood plasma samples. The best sensitivity (83%) and specificity (92%) values were obtained using the genetic algorithm with linear discriminant analysis (GA-LDA). These good classification results in addition to the potential for high analytical frequency, the low cost and reagent-free nature of this method demonstrate its potential as an alternative tool for HIV screening during pregnancy.
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http://dx.doi.org/10.1038/s41598-020-77378-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7677535PMC
November 2020

Spectrochemical analysis of liquid biopsy harnessed to multivariate analysis towards breast cancer screening.

Sci Rep 2020 07 30;10(1):12818. Epub 2020 Jul 30.

Institute of Chemistry, Biological Chemistry and Chemometrics, Federal University of Rio Grande do Norte, Natal, 59072-970, Brazil.

Mortality due to breast cancer could be reduced via screening programs where preliminary clinical tests employed in an asymptomatic well-population with the objective of identifying cancer biomarkers could allow earlier referral of women with altered results for deeper clinical analysis and treatment. The introduction of well-population screening using new and less-invasive technologies as a strategy for earlier detection of breast cancer is thus highly desirable. Herein, spectrochemical analyses harnessed to multivariate classification techniques are used as a bio-analytical tool for a Breast Cancer Screening Program using liquid biopsy in the form of blood plasma samples collected from 476 patients recruited over a 2-year period. This methodology is based on acquiring and analysing the spectrochemical fingerprint of plasma samples by attenuated total reflection Fourier-transform infrared spectroscopy; derived spectra reflect intrinsic biochemical composition, generating information on nucleic acids, carbohydrates, lipids and proteins. Excellent results in terms of sensitivity (94%) and specificity (91%) were obtained using this method in comparison with traditional mammography (88-93% and 85-94%, respectively). Additional advantages such as better disease prognosis thus allowing a more effective treatment, lower associated morbidity, fewer false-positive and false-negative results, lower-cost, and higher analytical frequency make this method attractive for translation to the clinical setting.
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http://dx.doi.org/10.1038/s41598-020-69800-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7393361PMC
July 2020

A three-dimensional discriminant analysis approach for hyperspectral images.

Analyst 2020 Aug;145(17):5915-5924

School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston PR1 2HE, UK.

Raman hyperspectral imaging is a powerful technique that provides both chemical and spatial information of a sample matrix being studied. The generated data are composed of three-dimensional (3D) arrays containing the spatial information across the x- and y-axis, and the spectral information in the z-axis. Unfolding procedures are commonly employed to analyze this type of data in a multivariate fashion, where the spatial dimension is reshaped and the spectral data fits into a two-dimensional (2D) structure and, thereafter, common first-order chemometric algorithms are applied to process the data. There are only a few algorithms capable of working with the full 3D array. Herein, we propose new algorithms for 3D discriminant analysis of hyperspectral images based on a three-dimensional principal component analysis linear discriminant analysis (3D-PCA-LDA) and a three-dimensional discriminant analysis quadratic discriminant analysis (3D-PCA-QDA) approach. The analysis was performed in order to discriminate simulated and real-world data, comprising benign controls and ovarian cancer samples based on Raman hyperspectral imaging, in which 3D-PCA-LDA and 3D-PCA-QDA achieved far superior performance than classical algorithms using unfolding procedures (PCA-LDA, PCA-QDA, partial lest squares discriminant analysis [PLS-DA], and support vector machines [SVM]), where the classification accuracies improved from 66% to 83% (simulated data) and from 50% to 100% (real-world dataset) after employing the 3D techniques. 3D-PCA-LDA and 3D-PCA-QDA are new approaches for discriminant analysis of hyperspectral images multisets to provide faster and superior classification performance than traditional techniques.
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http://dx.doi.org/10.1039/d0an01328eDOI Listing
August 2020

Spectrochemical analysis in blood plasma combined with subsequent chemometrics for fibromyalgia detection.

Sci Rep 2020 07 16;10(1):11769. Epub 2020 Jul 16.

Postgraduation Program in Rehabilitation Sciences, Faculty of Health Science of Trairí, Federal University of Rio Grande do Norte, Trairí St., Santa Cruz, RN, 59200-000, Brazil.

Fibromyalgia is a rheumatologic condition characterized by multiple and chronic body pain, and other typical symptoms such as intense fatigue, anxiety and depression. It is a very complex disease where treatment is often made by non-medicated alternatives in order to alleviate symptoms and improve the patient's quality of life. Herein, we propose a method to detect patients with fibromyalgia (n = 252, 126 controls and 126 patients with fibromyalgia) through the analysis of their blood plasma using attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy in conjunction with chemometric techniques, hence, providing a low-cost, fast and accurate diagnostic approach. Different chemometric algorithms were tested to classify the spectral data; genetic algorithm with linear discriminant analysis (GA-LDA) achieved the best diagnostic results with a sensitivity of 89.5% in an external test set. The GA-LDA model identified 24 spectral wavenumbers responsible for class separation; amongst these, the Amide II (1,545 cm) and proteins (1,425 cm) were identified to be discriminant features. These results reinforce the potential of ATR-FTIR spectroscopy with multivariate analysis as a new tool to screen and detect patients with fibromyalgia in a fast, low-cost, non-destructive and minimally invasive fashion.
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http://dx.doi.org/10.1038/s41598-020-68781-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7366631PMC
July 2020

Paper Spray Ionization Mass Spectrometry as a Potential Tool for Early Diagnosis of Cervical Cancer.

J Am Soc Mass Spectrom 2020 Jul 20. Epub 2020 Jul 20.

Chemistry Institute, Federal University of Goiás, Goiánia, Brazil.

Squamous intraepithelial lesion is an abnormal growth of epithelial cells on the surface of the cervix that may lead to cervical cancer. Analytical protocols for the determination of squamous intraepithelial lesions are in high demand, since cervical cancer is the fourth most diagnosed cancer among women in the world. Here, paper spray ionization mass spectrometry (PSI-MS) is used to distinguish between healthy (negative for intraepithelial lesion or malignancy) and diseased (high-grade squamous intraepithelial lesion) blood plasmas. A total of 86 blood samples of different women (49 healthy samples, 37 diseased samples) were collected, and the plasmas were prepared. Then, 10 μL of each plasma sample was deposited onto triangular papers for PSI-MS analysis. No additional step of sample preparation was necessary. The interval-successive projection algorithm linear discriminant analysis (iSPA-LDA) was applied to the PSI mass spectra, showing six ions (mostly phospholipids) that were predictive of healthy and diseased plasmas. Values of 77% accuracy, 86% sensitivity, 80% positive predictive value (PPV), and 75% negative predictive value (NPV) were achieved. This study provides evidence that PSI-MS may potentially be used as a fast and simple analytical technique for the early diagnosis of cervical cancer.
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http://dx.doi.org/10.1021/jasms.0c00111DOI Listing
July 2020

Tutorial: multivariate classification for vibrational spectroscopy in biological samples.

Nat Protoc 2020 07 17;15(7):2143-2162. Epub 2020 Jun 17.

School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston, UK.

Vibrational spectroscopy techniques, such as Fourier-transform infrared (FTIR) and Raman spectroscopy, have been successful methods for studying the interaction of light with biological materials and facilitating novel cell biology analysis. Spectrochemical analysis is very attractive in disease screening and diagnosis, microbiological studies and forensic and environmental investigations because of its low cost, minimal sample preparation, non-destructive nature and substantially accurate results. However, there is now an urgent need for multivariate classification protocols allowing one to analyze biologically derived spectrochemical data to obtain accurate and reliable results. Multivariate classification comprises discriminant analysis and class-modeling techniques where multiple spectral variables are analyzed in conjunction to distinguish and assign unknown samples to pre-defined groups. The requirement for such protocols is demonstrated by the fact that applications of deep-learning algorithms of complex datasets are being increasingly recognized as critical for extracting important information and visualizing it in a readily interpretable form. Hereby, we have provided a tutorial for multivariate classification analysis of vibrational spectroscopy data (FTIR, Raman and near-IR) highlighting a series of critical steps, such as preprocessing, data selection, feature extraction, classification and model validation. This is an essential aspect toward the construction of a practical spectrochemical analysis model for biological analysis in real-world applications, where fast, accurate and reliable classification models are fundamental.
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http://dx.doi.org/10.1038/s41596-020-0322-8DOI Listing
July 2020

Diagnostic Biomarkers for Alzheimer's Disease Using Non-Invasive Specimens.

J Clin Med 2020 Jun 1;9(6). Epub 2020 Jun 1.

School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston PR1 2HE, UK.

Studies in the field of Alzheimer's disease (AD) have shown the emergence of biomarkers in biologic fluids that hold great promise for the diagnosis of the disease. A diagnosis of AD at a presymptomatic or early stage may be the key for a successful treatment, with clinical trials currently investigating this. It is anticipated that preventative and therapeutic strategies may be stage-dependent, which means that they have a better chance of success at a very early stage-before critical neurons are lost. Several studies have been investigating the use of cerebrospinal fluid (CSF) and blood as clinical samples for the detection of AD with a number of established core markers, such as amyloid beta (Aβ), total tau (T-tau) and phosphorylated tau (tau), being at the center of clinical research interest. The use of oral samples-including saliva and buccal mucosal cells-falls under one of the least-investigated areas in AD diagnosis. Such samples have great potential to provide a completely non-invasive alternative to current CSF and blood sampling procedures. The present work is a thorough review of the results and analytical approaches, including proteomics, metabolomics, spectroscopy and microbiome analyses that have been used for the study and detection of AD using salivary samples and buccal cells. With a few exceptions, most of the studies utilizing oral samples were performed in small cohorts, which in combination with the existence of contradictory results render it difficult to come to a definitive conclusion on the value of oral markers. Proteins such as Aβ, T-tau and tau, as well as small metabolites, were detected in saliva and have shown some potential as future AD diagnostics. Future large-cohort studies and standardization of sample preparation and (pre-)analytical factors are necessary to determine the use of these non-invasive samples as a diagnostic tool for AD.
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http://dx.doi.org/10.3390/jcm9061673DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7356561PMC
June 2020

Detecting Endometrial Cancer by Blood Spectroscopy: A Diagnostic Cross-Sectional Study.

Cancers (Basel) 2020 May 16;12(5). Epub 2020 May 16.

Division of Cancer Sciences, University of Manchester, Manchester M13 9WL, UK.

Endometrial cancer is the sixth most common cancer in women, with a rising incidence worldwide. Current approaches for the diagnosis and screening of endometrial cancer are invasive, expensive or of moderate diagnostic accuracy, limiting their clinical utility. There is a need for cost-effective and minimally invasive approaches to facilitate the early detection and timely management of endometrial cancer. We analysed blood plasma samples in a cross-sectional diagnostic accuracy study of women with endometrial cancer ( = 342), its precursor lesion atypical hyperplasia ( = 68) and healthy controls ( = 242, total = 652) using attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy and machine learning algorithms. We show that blood-based infrared spectroscopy has the potential to detect endometrial cancer with 87% sensitivity and 78% specificity. Its accuracy is highest for Type I endometrial cancer, the most common subtype, and for atypical hyperplasia, with sensitivities of 91% and 100%, and specificities of 81% and 88%, respectively. Our large-cohort study shows that a simple blood test could enable the early detection of endometrial cancer of all stages in symptomatic women and provide the basis of a screening tool in high-risk groups. Such a test has the potential not only to differentially diagnose endometrial cancer but also to detect its precursor lesion atypical hyperplasia-the early recognition of which may allow fertility sparing management and cancer prevention.
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http://dx.doi.org/10.3390/cancers12051256DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7281323PMC
May 2020

Establishing spectrochemical changes in the natural history of oesophageal adenocarcinoma from tissue Raman mapping analysis.

Anal Bioanal Chem 2020 Jul 25;412(17):4077-4087. Epub 2020 Apr 25.

School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston, PR1 2HE, UK.

Raman spectroscopy is a fast and sensitive technique able to identify molecular changes in biological specimens. Herein, we report on three cases where Raman microspectroscopy was used to distinguish normal vs. oesophageal adenocarcinoma (OAC) (case 1) and Barrett's oesophagus vs. OAC (cases 2 and 3) in a non-destructive and highly accurate fashion. Normal and OAC tissues were discriminated using principal component analysis plus linear discriminant analysis (PCA-LDA) with 97% accuracy (94% sensitivity and 100% specificity) (case 1); Barrett's oesophagus vs. OAC tissues were discriminated with accuracies ranging from 98 to 100% (97-100% sensitivity and 100% specificity). Spectral markers responsible for class differentiation were obtained through the difference-between-mean spectrum for each group and the PCA loadings, where C-O-C skeletal mode in β-glucose (900 cm), lipids (967 cm), phosphodioxy (1296 cm), deoxyribose (1456 cm) and collagen (1445, 1665 cm) were associated with normal and OAC tissue differences. Phenylalanine (1003 cm), proline/collagen (1066, 1445 cm), phospholipids (1130 cm), CH angular deformation (1295 cm), disaccharides (1462 cm) and proteins (amide I, 1672/5 cm) were associated with Barrett's oesophagus and OAC tissue differences. These findings show the potential of using Raman microspectroscopy imaging for fast and accurate diagnoses of oesophageal pathologies and establishing subtle molecular changes predisposing to adenocarcinoma in a clinical setting. Graphical abstract Graphical abstract demonstrating how oesophageal tissue is processed through Raman mapping analysis in order to detect spectral differences between stages of oesophageal transformation to adenocarcinoma.
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http://dx.doi.org/10.1007/s00216-020-02637-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7320044PMC
July 2020

Age-Related and Gender-Related Increases in Colorectal Cancer Mortality Rates in Brazil Between 1979 and 2015: Projections for Continuing Rises in Disease.

J Gastrointest Cancer 2021 Mar;52(1):280-288

Department of Genetics, University of Sao Paulo, Ribeirao Preto, Brazil.

Purpose: Brazil is the largest country in South America. Although a developing nation, birth rates have been decreasing in the last few decades, while its overall population is undergoing lifestyle changes and ageing significantly. Moreover, Brazil has had increasingly high mortality rates related to colorectal cancer (CRC). Herein, we investigated whether the Brazilian population is exhibiting increasing mortality rates related to colon cancer (CC) or rectal cancer (RC) in recent years.

Methods: We examined data from the Brazilian Federal Government from 1979 to 2015 to determine whether CRC mortality and the population ageing process may be associated.

Results: Our mathematical modelling suggests that mortality rates related to CC and RC events in the Brazilian population may increase by 79% and 66% in the next 24 years, respectively. This finding led us to explore the mortality rates for both diseases in the country, and we observed that the highest levels were in the south and southeast regions from the year 2000 onwards. CC events appear to decrease life expectancy among people during their second decade of life in recent years, whereas RC events induced decreases in life expectancy in those aged >30 years. Additionally, both CC and RC events seem to promote significant mortality rates in the male population aged > 60 years and living in the southern states.

Conclusion: Our dataset suggests that both CC and RC events may lead to a significantly increasing number of deaths in the Brazilian male population in coming years.
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http://dx.doi.org/10.1007/s12029-020-00399-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7900022PMC
March 2021

Spectrochemical identification of kanamycin resistance genes in artificial microbial communities using Clover-assay.

J Pharm Biomed Anal 2020 Mar 15;181:113108. Epub 2020 Jan 15.

School of Environment, Tsinghua University, Beijing 100084, PR China; Lancaster Environment Centre, Lancaster University, Lancaster LA1 4YQ, UK; Research Institute for Environmental Innovation (Suzhou), Tsinghua, Suzhou 215163, PR China. Electronic address:

Persistent abuse and overuse of antibiotics induces a widespread bloom of antibiotic resistance genes (ARGs) and the emergence of superbugs. A method designed to rapidly quantify ARGs in real-world scenarios is urgently needed. Here, we present an orthogonal test of heavy water and kanamycin exposure, namely, a "clover-assay", to reveal the capability of state-of-the-art Raman microspectroscopy to identify ARGs within microbial communities. This assay successfully recognizes the discriminating spectral alterations from two genetically identical strains that differ only in terms of the expression of one kanamycin resistance gene. In addition to the previously reported Raman shift at carbon-deuterium vibration bands (2,040-2,300 cm), we identify two new peak shifts (970-990 cm) and (1,110-1,130 cm) associated with deuterium labelling. Notably, the spectral alterations from 1,110-1,130 cm strongly correlate with kanamycin exposure. By introducing dispersion index (DI) and clover assay index (CAI) as indicators, this assay is able to quantify the abundance of kanamycin resistance genes within artificial microbiotas. Based on our results, the biospectral clover assay is a powerful tool for the in situ interrogation of the occurrence of ARGs within microbial communities, which displays great potential to eliminate the need for culture protocols in the future. Due to the non-destructive and non-intrusive features, this approach may therefore potentially be able to diagnose horizontal gene transfer (HGT) in real time.
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http://dx.doi.org/10.1016/j.jpba.2020.113108DOI Listing
March 2020

Spectrochemical differentiation of meningioma tumours based on attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy.

Anal Bioanal Chem 2020 Feb 21;412(5):1077-1086. Epub 2019 Dec 21.

School of Pharmacy and Biomedical Sciences, UCLan, Preston, PR1 2HE, UK.

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. Graphical abstract Attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy was used to discriminate meningioma WHO grade I, grade II and grade I recurrence tumours.
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http://dx.doi.org/10.1007/s00216-019-02332-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7007428PMC
February 2020

Raman spectroscopy as a potential diagnostic tool to analyse biochemical alterations in lung cancer.

Analyst 2020 Jan 17;145(2):385-392. Epub 2019 Dec 17.

Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.

Patient survival remains poor even after diagnosis in lung cancer cases, and the molecular events resulting from lung cancer progression remain unclear. Raman spectroscopy could be used to noninvasively and accurately reveal the biochemical properties of biological tissues on the basis of their pathological status. This study aimed at probing biomolecular changes in lung cancer, using Raman spectroscopy as a potential diagnostic tool. Herein, biochemical alterations were evident in the Raman spectra (region of 600-1800 cm) in normal and cancerous lung tissues. The levels of saturated and unsaturated lipids and the protein-to-lipid, nucleic acid-to-lipid, and protein-to-nucleic acid ratios were significantly altered among malignant tissues compared to normal lung tissues. These biochemical alterations in tissues during neoplastic transformation have profound implications in not only the biochemical landscape of lung cancer progression but also cytopathological classification. Based on this spectroscopic approach, classification methods including k-nearest neighbour (kNN) and support vector machine (SVM) were successfully applied to cytopathologically diagnose lung cancer with an accuracy approaching 99%. The present results indicate that Raman spectroscopy is an excellent tool to biochemically interrogate and diagnose lung cancer.
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http://dx.doi.org/10.1039/c9an02175bDOI Listing
January 2020

Raman spectral discrimination in human liquid biopsies of oesophageal transformation to adenocarcinoma.

J Biophotonics 2020 03 15;13(3):e201960132. Epub 2019 Dec 15.

School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston, UK.

The aim of this study was to determine whether Raman spectroscopy combined with chemometric analysis can be applied to interrogate biofluids (plasma, serum, saliva and urine) towards detecting oesophageal stages through to oesophageal adenocarcinoma [normal/squamous epithelium, inflammatory, Barrett's, low-grade dysplasia, high-grade dysplasia and oesophageal adenocarcinoma (OAC)]. The chemometric analysis of the spectral data was performed using principal component analysis, successive projections algorithm or genetic algorithm (GA) followed by quadratic discriminant analysis (QDA). The genetic algorithm quadratic discriminant analysis (GA-QDA) model using a few selected wavenumbers for saliva and urine samples achieved 100% classification for all classes. For plasma and serum, the GA-QDA model achieved excellent accuracy in all oesophageal stages (>90%). The main GA-QDA features responsible for sample discrimination were: 1012 cm (C─O stretching of ribose), 1336 cm (Amide III and CH wagging vibrations from glycine backbone), 1450 cm (methylene deformation) and 1660 cm (Amide I). The results of this study are promising and support the concept that Raman on biofluids may become a useful and objective diagnostic tool to identify oesophageal disease stages from squamous epithelium to OAC.
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http://dx.doi.org/10.1002/jbio.201960132DOI Listing
March 2020

Gene-environment interactions between GSTs polymorphisms and targeted epigenetic alterations in hepatocellular carcinoma following organochlorine pesticides (OCPs) exposure.

Environ Int 2020 01 12;134:105313. Epub 2019 Nov 12.

Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen 361102, China. Electronic address:

Exposure to environmental pollutant organochlorine pesticides (OCPs) and the role of tumour suppressor GSTs gene polymorphisms as well as epigenetic alterations have all been well reported in hepatocarcinogenesis. However, the interplay between environmental risk factors and polymorphic tumour suppressor genes or epigenetic factors in hepatocellular carcinoma (HCC) development remains ambiguous. Herein, we investigated the relationship of three GSTs polymorphisms (GSTT1 deletion, GSTM1 deletion, GSTP1 rs1695) as well as GSTP1 promoter region DNA methylation and HCC risk with a particular focus on the interaction with OCPs exposure among 90 HCC cases and 99 controls in a Chinese population. Serum samples were analysed for OCPs exposure employing gas chromatography coupled with mass selective detector (GC-MS). GSTs polymorphisms and epigenetic alterations were determined using high-resolution melting PCR (HRM PCR) and DNA sequencing. After adjusting for confounders (HBV infection, smoking, alcohol consumption, BMI, age, gender), OCPs exposure and GSTP1 methylation is significantly associated with elevated risk of HCC, while no significance is observed for GSTs polymorphisms. Moreover, the effects of OCPs exposure on HCC risk are more pronounced amongst GSTP1 (Ile/Val + Val/Val) and GSTP1 promoter methylation subjects than those who were GSTP1 (Ile/Ile) and unmethylated subjects. The interactions between OCPs exposure and GSTP1 genotype as well as GSTP1 epigenetic status are statistically significant. The current study demonstrates the importance of gene-environment interactions in the multifactorial development of HCC.
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http://dx.doi.org/10.1016/j.envint.2019.105313DOI Listing
January 2020

Phages Enter the Fight against Colorectal Cancer.

Trends Cancer 2019 10 31;5(10):577-579. Epub 2019 Aug 31.

School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston, UK.

Intestinal microbiota undergo significant changes in colorectal cancer (CRC). Zheng et al. (Nat. Biomed. Eng., 2019) observe detrimental overpopulation of Fusobacterium nucleatum in mice and patients, suppressing the beneficial butyrate-producing Clostridium butyricum. Phage-guided irinotecan-loaded dextran nanoparticles promote release of bacterial-derived butyrate, while F. nucleatum and CRC cells are eliminated. These findings describe a possible novel therapeutic strategy for CRC.
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http://dx.doi.org/10.1016/j.trecan.2019.08.002DOI Listing
October 2019

Attenuated total reflection Fourier-transform infrared spectral discrimination in human bodily fluids of oesophageal transformation to adenocarcinoma.

Analyst 2019 Dec;144(24):7447-7456

School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston PR1 2HE, UK.

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.
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http://dx.doi.org/10.1039/c9an01749fDOI Listing
December 2019

Determination of meningioma brain tumour grades using Raman microspectroscopy imaging.

Analyst 2019 Nov;144(23):7024-7031

School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston PR1 2HE, UK.

Raman spectroscopy is a powerful technique used to analyse biological materials, where spectral markers such as proteins (1500-1700 cm-1), carbohydrates (470-1200 cm-1) and phosphate groups of DNA (980, 1080-1240 cm-1) can be detected in a complex biological medium. Herein, Raman microspectroscopy imaging was used to investigate 90 brain tissue samples in order to differentiate meningioma Grade I and Grade II samples, which are the commonest types of brain tumour. Several classification algorithms using feature extraction and selection methods were tested, in which the best classification performances were achieved by principal component analysis-quadratic discriminant analysis (PCA-QDA) and successive projections algorithm-quadratic discriminant analysis (SPA-QDA), resulting in accuracies of 96.2%, sensitivities of 85.7% and specificities of 100% using both methods. A biochemical profiling in terms of spectral markers was investigated using the difference-between-mean (DBM) spectrum, PCA loadings, SPA-QDA selected wavenumbers, and the recovered imaging profiles after multivariate curve resolution alternating least squares (MCR-ALS), where the following wavenumbers were found to be associated with class differentiation: 850 cm-1 (amino acids or polysaccharides), 1130 cm-1 (phospholipid structural changes), the region between 1230-1360 cm-1 (Amide III and CH2 deformation), 1450 cm-1 (CH2 bending), and 1858 cm-1 (C[double bond, length as m-dash]O stretching). These findings highlight the potential of Raman microspectroscopy imaging for determination of meningioma tumour grades.
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http://dx.doi.org/10.1039/c9an01551eDOI Listing
November 2019

Discrimination of fresh frozen non-tumour and tumour brain tissue using spectrochemical analyses and a classification model.

Br J Neurosurg 2020 Feb 23;34(1):40-45. Epub 2019 Oct 23.

Department of Neuropathology, Royal Preston Hospital, Lancashire Teaching Hospitals NHS Trust, Preston, UK.

In order for brain tumours to be successfully treated, maximal resection is beneficial. A method to detect infiltrative tumour edges intraoperatively, improving on current methods would be clinically useful. Vibrational spectroscopy offers the potential to provide a handheld, reagent-free method for tumour detection. This study was designed to determine the ability of both Raman and Fourier-transform infrared (FTIR) spectroscopy towards differentiating between normal brain tissue, glioma or meningioma. Unfixed brain tissue, which had previously only been frozen, comprising normal, glioma or meningioma tissue was placed onto calcium fluoride slides for analysis using Raman and attenuated total reflection (ATR)-FTIR spectroscopy. Matched haematoxylin and eosin slides were used to confirm tumour areas. Analyses were then conducted to generate a classification model. This study demonstrates the ability of both Raman and ATR-FTIR spectroscopy to discriminate tumour from non-tumour fresh frozen brain tissue with 94% and 97.2% of cases correctly classified, with sensitivities of 98.8% and 100%, respectively. This decreases when spectroscopy is used to determine tumour type. The study demonstrates the ability of both Raman and ATR-FTIR spectroscopy to detect tumour tissue from non-tumour brain tissue with a high degree of accuracy. This demonstrates the ability of spectroscopy when targeted for a cancer diagnosis. However, further improvement would be required for a classification model to determine tumour type using this technology, in order to make this tool clinically viable.
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http://dx.doi.org/10.1080/02688697.2019.1679352DOI Listing
February 2020

Interrogating the Transient Selectivity of Bacterial Chemotaxis-Driven Affinity and Accumulation of Carbonaceous Substances Raman Microspectroscopy.

Front Microbiol 2019 4;10:2215. Epub 2019 Oct 4.

School of Environment, Tsinghua University, Beijing, China.

Carbonaceous substances are fundamental organic nutrients for microbial metabolism and catabolism in natural habitats. Microbial abilities to sense, accumulate, and utilize organic carbonaceous substances in the complex nutrient environment are important for their growth and ecological functions. Bacterial chemotaxis is an effective mechanism for microbial utilization of carbonaceous substances under nutrient depletion conditions. Although bacterial accumulation and utilization to individual carbonaceous substance in long-term cultivation has been well studied, their selective affinity of mixed carbonaceous substances remains to be investigated, primarily because of technical limitations of conventional methods. Herein, we applied Raman microspectroscopy to identify chemotaxis-driven affinity and accumulation of four organic carbonaceous substances (glucose, succinate, acetate, and salicylate) by three bacterial strains (, , and ). exhibited strong binding affinity toward glucose and succinate, whereas and were preferentially responsive to glucose and acetate. For the first time, bacterial transient selectivity of carbonaceous substances was studied interrogating Raman spectral alterations. Post-exposure to carbonaceous-substance mixtures, the three bacterial strains showed distinct selective behaviors. Stronger selective affinity enhanced the chemotaxis-related signal transduction in cells, whereas the carbonaceous substance signal transduction in was decreased by higher selective affinity. In , there was no specific effect of selective affinity on signal transduction. Our study suggests that Raman microspectroscopy can successfully investigate and distinguish different scenarios of bacterial competitive and transient unitization of organic carbonaceous substances.
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http://dx.doi.org/10.3389/fmicb.2019.02215DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6787638PMC
October 2019

Determination of developmental and ripening stages of whole tomato fruit using portable infrared spectroscopy and Chemometrics.

BMC Plant Biol 2019 Jun 4;19(1):236. Epub 2019 Jun 4.

Lancaster Environment Centre, Lancaster University, Bailrigg, Lancaster, LA1 4YQ, UK.

Background: Development and ripening of tomato (Solanum lycopersicum) fruit are important processes for the study of crop biology related to industrial horticulture. Versatile uses of tomato fruit lead to its harvest at various points of development from early maturity through to red ripe, traditionally indicated by parameters such as size, weight, colour, and internal composition, according to defined visual 'grading' schemes. Visual grading schemes however are subjective and thus objective classification of tomato fruit development and ripening are needed for 'high-tech' horticulture. To characterize the development and ripening processes in whole tomato fruit (cv. Moneymaker), a biospectroscopy approach is employed using compact portable ATR-FTIR spectroscopy coupled with chemometrics.

Results: The developmental and ripening processes showed unique spectral profiles, which were acquired from the cuticle-cell wall complex of tomato fruit epidermis in vivo. Various components of the cuticle including Cutin, waxes, and phenolic compounds, among others, as well as from the underlying cell wall such as celluloses, pectin and lignin like compounds among others. Epidermal surface structures including cuticle and cell wall were significantly altered during the developmental process from immature green to mature green, as well as during the ripening process. Changes in the spectral fingerprint region (1800-900 cm) were sufficient to identify nine developmental and six ripening stages with high accuracy using support vector machine (SVM) chemometrics.

Conclusions: The non-destructive spectroscopic approach may therefore be especially useful for investigating in vivo biochemical changes occurring in fruit epidermis related to grades of tomato during development and ripening, for autonomous food production/supply chain applications.
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http://dx.doi.org/10.1186/s12870-019-1852-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6549295PMC
June 2019

A human-derived prostate co-culture microtissue model using epithelial (RWPE-1) and stromal (WPMY-1) cell lines.

Toxicol In Vitro 2019 Oct 30;60:203-211. Epub 2019 May 30.

Department of Pathology and Laboratory Medicine, Brown University, Providence, RI, USA.

The development and normal function of prostate tissue depends on signalling interactions between stromal and epithelial compartments. Development of a prostate microtissue composed of these two components can help identify substance exposures that could cause adverse effects in humans as part of a non-animal risk assessment. In this study, prostate microtissues composed of human derived stromal (WPMY-1) and epithelial (RWPE-1) cell lines grown in scaffold-free hydrogels were developed and characterized using immunohistochemistry, light microscopy, and qRT-PCR. Within 5 days after seeding, the microtissues self-organized into spheroids consisting of a core of stromal WPMY-1 cells surrounded by epithelial RWPE-1 cells. The RWPE-1 layer is reflective of intermediate prostatic epithelium, expressing both characteristics of the luminal (high expression of PSA) and basal (high expression of cytokeratins 5/6 and 14) epithelial cells. The response of the microtissues to an androgen (dihydrotestosterone, DHT) and an anti-androgen (flutamide) was also investigated. Treatment with DHT, flutamide or a mixture of DHT and flutamide indicated that the morphology and self-organization of the microtissues is androgen dependent. qRT-PCR data showed that a saturating concentration of DHT increased the expression of genes coding for the estrogen receptors (ESR1 and ESR2) and decreased the expression of CYP1B1 without affecting the expression of the androgen receptor. With further development and optimization RWPE-1/WPMY-1 microtissues can play an important role in non-animal risk assessments.
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http://dx.doi.org/10.1016/j.tiv.2019.05.023DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6717042PMC
October 2019

Improving data splitting for classification applications in spectrochemical analyses employing a random-mutation Kennard-Stone algorithm approach.

Bioinformatics 2019 12;35(24):5257-5263

School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston PR1 2HE, UK.

Motivation: Data splitting is a fundamental step for building classification models with spectral data, especially in biomedical applications. This approach is performed following pre-processing and prior to model construction, and consists of dividing the samples into at least training and test sets; herein, the training set is used for model construction and the test set for model validation. Some of the most-used methodologies for data splitting are the random selection (RS) and the Kennard-Stone (KS) algorithms; here, the former works based on a random splitting process and the latter is based on the calculation of the Euclidian distance between the samples. We propose an algorithm called the Morais-Lima-Martin (MLM) algorithm, as an alternative method to improve data splitting in classification models. MLM is a modification of KS algorithm by adding a random-mutation factor.

Results: RS, KS and MLM performance are compared in simulated and six real-world biospectroscopic applications using principal component analysis linear discriminant analysis (PCA-LDA). MLM generated a better predictive performance in comparison with RS and KS algorithms, in particular regarding sensitivity and specificity values. Classification is found to be more well-equilibrated using MLM. RS showed the poorest predictive response, followed by KS which showed good accuracy towards prediction, but relatively unbalanced sensitivities and specificities. These findings demonstrate the potential of this new MLM algorithm as a sample selection method for classification applications in comparison with other regular methods often applied in this type of data.

Availability And Implementation: MLM algorithm is freely available for MATLAB at https://doi.org/10.6084/m9.figshare.7393517.v1.
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http://dx.doi.org/10.1093/bioinformatics/btz421DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6954661PMC
December 2019