1
|
Li X, Zeng P, Wu X, Yang X, Lin J, Liu P, Wang Y, Diao Y. ResD-Net: A model for rapid prediction of antioxidant activity in gentian root using FT-IR spectroscopy. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 310:123848. [PMID: 38266602 DOI: 10.1016/j.saa.2024.123848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/24/2023] [Revised: 01/02/2024] [Accepted: 01/03/2024] [Indexed: 01/26/2024]
Abstract
Gentian, an herb resource known for its antioxidant properties, has garnered significant attention. However, existing methods are time-consuming and destructive for assessing the antioxidant activity in gentian root samples. In this study, we propose a method for swiftly predicting the antioxidant activity of gentian root using FT-IR spectroscopy combined with chemometrics. We employed machine learning and deep learning models to establish the relationship between FT-IR spectra and DPPH free radical scavenging activity. The results of model fitting reveal that the deep learning model outperforms the machine learning model. The model's performance was enhanced by incorporating the Double-Net and residual connection strategy. The enhanced model, named ResD-Net, excels in feature extraction and also avoids gradient vanishing. The ResD-Net model achieves an R2 of 0.933, an RMSE of 0.02, and an RPD of 3.856. These results support the accuracy and applicability of this method for rapidly predicting antioxidant activity in gentian root samples.
Collapse
Affiliation(s)
- Xiaokun Li
- School of Medicine, Huaqiao University, Quanzhou 362021, China
| | - Pan Zeng
- School of Medicine, Huaqiao University, Quanzhou 362021, China
| | - Xunxun Wu
- School of Medicine, Huaqiao University, Quanzhou 362021, China
| | - Xintong Yang
- School of Medicine, Huaqiao University, Quanzhou 362021, China
| | - Jingcang Lin
- Quanzhou Medical College, Quanzhou 362000, China
| | - Peizhong Liu
- School of Medicine, Huaqiao University, Quanzhou 362021, China; Quanzhou Medical College, Quanzhou 362000, China
| | - Yuanzhong Wang
- Institute of Medicinal Plants, Yunnan Academy of Agricultural Sciences, Kunming, China
| | - Yong Diao
- School of Medicine, Huaqiao University, Quanzhou 362021, China.
| |
Collapse
|
2
|
Wasim M, Ghaffar U, Javed MR, Nawaz H, Majeed MI, Ijaz A, Ishtiaq S, Rehman N, Razaq R, Younas S, Bano A, Kanwal N, Imran M. Surface-Enhanced Raman Spectroscopy for Monitoring the Biochemical Changes Due to DNA Mutations Induced by CRISPR-Cas9 Genome Editing in the Aspergillus niger Fungus. ACS OMEGA 2024; 9:15202-15209. [PMID: 38585125 PMCID: PMC10993282 DOI: 10.1021/acsomega.3c09563] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 01/22/2024] [Accepted: 03/04/2024] [Indexed: 04/09/2024]
Abstract
In this study, surface-enhanced Raman spectroscopy (SERS) technique, along with principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA), is used as a simple, quick, and cost-effective analysis method for identifying biochemical changes occurring due to induced mutations in the Aspergillus niger fungus strain. The goal of this study is to identify the biochemical changes in the mutated fungal cells (cell mass) as compared to the control/nonmutated cells. Furthermore, multivariate data analysis tools, including PCA and PLS-DA, are used to further confirm the differentiating SERS spectral features among fungal samples. The mutations are caused in A. niger by the clustered regularly interspaced palindromic repeat CRISPR-Cas9 genomic editing method to improve their biotechnological potential for the production of cellulase enzyme. SERS was employed to detect the changes in the cells of mutated A. niger fungal strains, including one mutant producing low levels of an enzyme and another mutant producing high levels of the enzyme as a result of mutation as compared with an unmutated fungal strain as a control sample. The distinctive features of SERS corresponding to nucleic acids and proteins appear at 546, 622, 655, 738, 802, 835, 959, 1025, 1157, 1245, 1331, 1398, and 1469 cm-1. Furthermore, PLS-DA is used to confirm the 89% accuracy, 87.7% precision, 87% sensitivity, and 88.9% specificity of this method, and the value of the area under the curve (AUROC) is 0.67. It has been shown that surface-enhanced Raman spectroscopy is an effective method for identifying and differentiating biochemical changes in genome-modified fungal samples.
Collapse
Affiliation(s)
- Muhammad Wasim
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Usman Ghaffar
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Muhammad Rizwan Javed
- Biocatalysis
and Protein Engineering Research Group (BPERG), Department of Bioinformatics
and Biotechnology, Government College University
Faisalabad (GCUF), Allama
Iqbal Road, Faisalabad 38000, Pakistan
| | - Haq Nawaz
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Muhammad Irfan Majeed
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Anam Ijaz
- Biocatalysis
and Protein Engineering Research Group (BPERG), Department of Bioinformatics
and Biotechnology, Government College University
Faisalabad (GCUF), Allama
Iqbal Road, Faisalabad 38000, Pakistan
| | - Shazra Ishtiaq
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Nimra Rehman
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Rabeea Razaq
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Sobia Younas
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Aqsa Bano
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Naeema Kanwal
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Muhammad Imran
- Department
of Chemistry, Faculty of Science, King Khalid
University, P.O. Box 9004, Abha 61413, Saudi Arabia
| |
Collapse
|
3
|
Li YP, Lu TY, Huang FR, Zhang WM, Chen ZQ, Guang PW, Deng LY, Yang XH. Differential diagnosis of Crohn's disease and intestinal tuberculosis based on ATR-FTIR spectroscopy combined with machine learning. World J Gastroenterol 2024; 30:1377-1392. [PMID: 38596500 PMCID: PMC11000079 DOI: 10.3748/wjg.v30.i10.1377] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 01/02/2024] [Accepted: 02/06/2024] [Indexed: 03/14/2024] Open
Abstract
BACKGROUND Crohn's disease (CD) is often misdiagnosed as intestinal tuberculosis (ITB). However, the treatment and prognosis of these two diseases are dramatically different. Therefore, it is important to develop a method to identify CD and ITB with high accuracy, specificity, and speed. AIM To develop a method to identify CD and ITB with high accuracy, specificity, and speed. METHODS A total of 72 paraffin wax-embedded tissue sections were pathologically and clinically diagnosed as CD or ITB. Paraffin wax-embedded tissue sections were attached to a metal coating and measured using attenuated total reflectance fourier transform infrared spectroscopy at mid-infrared wavelengths combined with XGBoost for differential diagnosis. RESULTS The results showed that the paraffin wax-embedded specimens of CD and ITB were significantly different in their spectral signals at 1074 cm-1 and 1234 cm-1 bands, and the differential diagnosis model based on spectral characteristics combined with machine learning showed accuracy, specificity, and sensitivity of 91.84%, 92.59%, and 90.90%, respectively, for the differential diagnosis of CD and ITB. CONCLUSION Information on the mid-infrared region can reveal the different histological components of CD and ITB at the molecular level, and spectral analysis combined with machine learning to establish a diagnostic model is expected to become a new method for the differential diagnosis of CD and ITB.
Collapse
Affiliation(s)
- Yuan-Peng Li
- College of Physical Science and Technology, Guangxi Normal University, Guilin, Guangxi 541004, China
| | - Tian-Yu Lu
- Department of Gastroenterology, The Affiliated Hospital of South University of Science and Technology, Shenzhen 518000, Guangdong Province, China
| | - Fu-Rong Huang
- Department of Optoelectronic Engineering, Jinan University, Guangzhou 510632, Guangdong Province, China
| | - Wei-Min Zhang
- Department of Gastroenterology, Integrated Hospital of Traditional Chinese Medicine, Southern Medical University, Guangzhou 510632, Guangdong Province, China
| | - Zhen-Qiang Chen
- Department of Optoelectronic Engineering, Jinan University, Guangzhou 510632, Guangdong Province, China
| | - Pei-Wen Guang
- Department of Optoelectronic Engineering, Jinan University, Guangzhou 510632, Guangdong Province, China
| | - Liang-Yu Deng
- Department of Optoelectronic Engineering, Jinan University, Guangzhou 510632, Guangdong Province, China
| | - Xin-Hao Yang
- Department of Optoelectronic Engineering, Jinan University, Guangzhou 510632, Guangdong Province, China
| |
Collapse
|
4
|
Mehmood N, Akram MW, Majeed MI, Nawaz H, Aslam MA, Naman A, Wasim M, Ghaffar U, Kamran A, Nadeem S, Kanwal N, Imran M. Surface-enhanced Raman spectroscopy for the characterization of bacterial pellets of Staphylococcus aureus infected by bacteriophage. RSC Adv 2024; 14:5425-5434. [PMID: 38348301 PMCID: PMC10859908 DOI: 10.1039/d3ra07575c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Accepted: 01/12/2024] [Indexed: 02/15/2024] Open
Abstract
Drug-resistant pathogenic bacteria are a major cause of infectious diseases in the world and they have become a major threat through the reduced efficacy of developed antibiotics. This issue can be addressed by using bacteriophages, which can kill lethal bacteria and prevent them from causing infections. Surface-enhanced Raman spectroscopy (SERS) is a promising technique for studying the degradation of infectious bacteria by the interaction of bacteriophages to break the vicious cycle of drug-resistant bacteria and help to develop chemotherapy-independent remedial strategies. The phage (viruses)-sensitive Staphylococcus aureus (S. aureus) bacteria are exposed to bacteriophages (Siphoviridae family) in the time frame from 0 min (control) to 50 minutes with intervals of 5 minutes and characterized by SERS using silver nanoparticles as SERS substrate. This allows us to explore the effects of the bacteriophages against lethal bacteria (S. aureus) at different time intervals. The differentiating SERS bands are observed at 575 (C-C skeletal mode), 620 (phenylalanine), 649 (tyrosine, guanine (ring breathing)), 657 (guanine (COO deformation)), 728-735 (adenine, glycosidic ring mode), 796 (tyrosine (C-N stretching)), 957 (C-N stretching (amide lipopolysaccharides)), 1096 (PO2 (nucleic acid)), 1113 (phenylalanine), 1249 (CH2 of amide III, N-H bending and C-O stretching (amide III)), 1273 (CH2, N-H, C-N, amide III), 1331 (C-N stretching mode of adenine), 1373 (in nucleic acids (ring breathing modes of the DNA/RNA bases)) and 1454 cm-1 (CH2 deformation of saturated lipids), indicating the degradation of bacteria and replication of bacteriophages. Multivariate data analysis was performed by employing principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) to study the biochemical differences in the S. aureus bacteria infected by the bacteriophage. The SERS spectral data sets were successfully differentiated by PLS-DA with 94.47% sensitivity, 98.61% specificity, 94.44% precision, 98.88% accuracy and 81.06% area under the curve (AUC), which shows that at 50 min interval S. aureus bacteria is degraded by the replicating bacteriophages.
Collapse
Affiliation(s)
- Nasir Mehmood
- Department of Chemistry, University of Agriculture Faisalabad Faisalabad (38000) Pakistan
| | - Muhammad Waseem Akram
- Department of Chemistry, University of Agriculture Faisalabad Faisalabad (38000) Pakistan
| | - Muhammad Irfan Majeed
- Department of Chemistry, University of Agriculture Faisalabad Faisalabad (38000) Pakistan
| | - Haq Nawaz
- Department of Chemistry, University of Agriculture Faisalabad Faisalabad (38000) Pakistan
| | - Muhammad Aamir Aslam
- Institute of Microbiology, Faculty of Veterinary, University of Agriculture Faisalabad Faisalabad (38000) Pakistan
| | - Abdul Naman
- Department of Chemistry, University of Agriculture Faisalabad Faisalabad (38000) Pakistan
| | - Muhammad Wasim
- Department of Chemistry, University of Agriculture Faisalabad Faisalabad (38000) Pakistan
| | - Usman Ghaffar
- Department of Chemistry, University of Agriculture Faisalabad Faisalabad (38000) Pakistan
| | - Ali Kamran
- Department of Chemistry, University of Agriculture Faisalabad Faisalabad (38000) Pakistan
| | - Sana Nadeem
- Department of Chemistry, University of Agriculture Faisalabad Faisalabad (38000) Pakistan
| | - Naeema Kanwal
- Department of Chemistry, University of Agriculture Faisalabad Faisalabad (38000) Pakistan
| | - Muhammad Imran
- Department of Chemistry, Faculty of Science, King Khalid University P.O. Box 9004 Abha (61413) Saudi Arabia
| |
Collapse
|
5
|
Lao Q, Yang L, Liu S, Ma X, Tan D, Li J, Liao B, Wei Y, Pang W, Morais CLM, Liu H. Effects of Benzo ( a) Pyrene and 2,2',4,4'-Tetrabromodiphenyl Ether Exposure on the Thyroid Gland in Rats by Attenuated Total Reflection Fourier-Transform Infrared Spectroscopy. ACS OMEGA 2024; 9:4317-4323. [PMID: 38313510 PMCID: PMC10831854 DOI: 10.1021/acsomega.3c05819] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/13/2023] [Revised: 12/23/2023] [Accepted: 01/04/2024] [Indexed: 02/06/2024]
Abstract
Benzo[a]pyrene (B[a]P) and 2,2',4,4'-tetrabromodiphenyl ether (BDE-47) are widespread environmental pollutants and can destroy thyroid function. We assessed the biochemical changes in the thyroid tissue of rats exposed to B[a]P and BDE-47 using attenuated total reflection Fourier-transform infrared spectroscopy combined with support vector machine(SVM). After B[a]P and BDE-47 treatment in rats, the structure of thyroid follicles was destroyed and epithelial cells were necrotic, indicating that B[a]P and BDE-47 may lead to changes of the thyroid morphology of the rats. These damages are mainly related to C=O stretch vibrations of lipids (1743 cm-1), as well as the secondary structure of proteins [amide I (1645 cm-1) and amide II (1550 cm-1)], and carbohydrates [C-OH (1138 cm-1), C-O (1106 cm-1, 1049 cm-1, 991 cm-1), C-C (1106 cm-1) stretching] and collagen (phosphodiester stretching at 922 cm-1) vibration modes. When SVM was used for classification, there was a substantial separation between the control and the exposure groups (accuracy = 96%; sensitivity = 98%; specificity = 87%), and there was also a major separation between the exposed groups (accuracy = 93%; sensitivity = 94%; and specificity = 92%).
Collapse
Affiliation(s)
- QiuFeng Lao
- Guangxi
Key Laboratory of Environmental Exposomics and Entire Lifecycle Heath, Guilin Medical University, Guilin, Guangxi 541199, China
- School
of Public Health, Guilin Medical University, Guilin, Guangxi 541199, China
- Liuzhou
People’s Hospital, Liuzhou, Guangxi 545006, China
| | - LiJun Yang
- Guangxi
Key Laboratory of Environmental Exposomics and Entire Lifecycle Heath, Guilin Medical University, Guilin, Guangxi 541199, China
- School
of Public Health, Guilin Medical University, Guilin, Guangxi 541199, China
| | - ShuZhen Liu
- Guangxi
Key Laboratory of Environmental Exposomics and Entire Lifecycle Heath, Guilin Medical University, Guilin, Guangxi 541199, China
- School
of Public Health, Guilin Medical University, Guilin, Guangxi 541199, China
| | - XiaoJun Ma
- Guangxi
Key Laboratory of Environmental Exposomics and Entire Lifecycle Heath, Guilin Medical University, Guilin, Guangxi 541199, China
- School
of Public Health, Guilin Medical University, Guilin, Guangxi 541199, China
| | - DeChan Tan
- Guangxi
Key Laboratory of Environmental Exposomics and Entire Lifecycle Heath, Guilin Medical University, Guilin, Guangxi 541199, China
- School
of Public Health, Guilin Medical University, Guilin, Guangxi 541199, China
| | - JinBo Li
- Guangxi
Key Laboratory of Environmental Exposomics and Entire Lifecycle Heath, Guilin Medical University, Guilin, Guangxi 541199, China
- School
of Public Health, Guilin Medical University, Guilin, Guangxi 541199, China
| | - BaoYi Liao
- Guangxi
Key Laboratory of Environmental Exposomics and Entire Lifecycle Heath, Guilin Medical University, Guilin, Guangxi 541199, China
- School
of Public Health, Guilin Medical University, Guilin, Guangxi 541199, China
| | - YuanFeng Wei
- Guangxi
Key Laboratory of Environmental Exposomics and Entire Lifecycle Heath, Guilin Medical University, Guilin, Guangxi 541199, China
- School
of Public Health, Guilin Medical University, Guilin, Guangxi 541199, China
| | - WeiYi Pang
- Guangxi
Key Laboratory of Environmental Exposomics and Entire Lifecycle Heath, Guilin Medical University, Guilin, Guangxi 541199, China
| | - Camilo L. M. Morais
- Center
for Education, Science and Technology of the Inhamuns Region, State University of Ceará, Tauá 63660-000, Brazil
| | - Hui Liu
- Guangxi
Key Laboratory of Environmental Exposomics and Entire Lifecycle Heath, Guilin Medical University, Guilin, Guangxi 541199, China
- School
of Public Health, Guilin Medical University, Guilin, Guangxi 541199, China
| |
Collapse
|
6
|
Gozdzialski L, Hutchison A, Wallace B, Gill C, Hore D. Toward automated infrared spectral analysis in community drug checking. Drug Test Anal 2024; 16:83-92. [PMID: 37248686 DOI: 10.1002/dta.3520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Revised: 05/13/2023] [Accepted: 05/16/2023] [Indexed: 05/31/2023]
Abstract
The body of knowledge surrounding infrared spectral analysis of drug mixtures continues to grow alongside the physical expansion of drug checking services. Technicians trained in the analysis of spectroscopic data are essential for reasons that go beyond the accuracy of the analytical results. Significant barriers faced by people who use drugs in engaging with drug checking services include the speed and accuracy of the results, and the availability and accessibility of the service. These barriers can be overcome by the automation of interpretations. A random forest model for the detection of two compounds, MDA and fluorofentanyl, was trained and optimized with drug samples acquired at a community drug checking site. This resulted in a 79% true positive and 100% true negative rate for MDA, and 61% true positive and 97% true negative rate for fluorofentanyl. The trained models were applied to selected drug samples to demonstrate a proposed workflow for interpreting and validating model predictions. The detection of MDA was demonstrated on three mixtures: (1) MDMA and MDA, (2) MDA and dimethylsulfone, and (3) fentanyl, etizolam, and benzocaine. The classification of fluorofentanyl was applied to a drug mixture containing fentanyl, fluorofentanyl, 4-anilino-N-phenethylpiperidine, caffeine, and mannitol. Feature importance was calculated using shapely additive explanations to better explain the model predictions and k-nearest neighbors was used for visual comparison to labelled training data. This is a step toward building appropriate trust in computer-assisted interpretations in order to promote their use in a harm reduction context.
Collapse
Affiliation(s)
- Lea Gozdzialski
- Department of Chemistry, University of Victoria, Victoria, British Columbia, Canada
| | - Abby Hutchison
- Canadian Institute for Substance Use Research, University of Victoria, Victoria, British Columbia, Canada
- School of Public Health and Social Policy, University of Victoria, Victoria, British Columbia, Canada
| | - Bruce Wallace
- Canadian Institute for Substance Use Research, University of Victoria, Victoria, British Columbia, Canada
- School of Social Work, University of Victoria, Victoria, British Columbia, Canada
| | - Chris Gill
- Department of Chemistry, University of Victoria, Victoria, British Columbia, Canada
- Canadian Institute for Substance Use Research, University of Victoria, Victoria, British Columbia, Canada
- Department of Chemistry, Applied Environmental Research Laboratories (AERL), Vancouver Island University, Nanaimo, British Columbia, Canada
- Department of Chemistry, Simon Fraser University, Burnaby, British Columbia, Canada
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, USA
| | - Dennis Hore
- Canadian Institute for Substance Use Research, University of Victoria, Victoria, British Columbia, Canada
- Department of Computer Science, University of Victoria, Victoria, British Columbia, Canada
| |
Collapse
|
7
|
Kim SY, Shin SY, Saeed M, Ryu JE, Kim JS, Ahn J, Jung Y, Moon JM, Choi CH, Choi HK. Prediction of Clinical Remission with Adalimumab Therapy in Patients with Ulcerative Colitis by Fourier Transform-Infrared Spectroscopy Coupled with Machine Learning Algorithms. Metabolites 2023; 14:2. [PMID: 38276292 PMCID: PMC10818421 DOI: 10.3390/metabo14010002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 12/06/2023] [Accepted: 12/12/2023] [Indexed: 01/27/2024] Open
Abstract
We aimed to develop prediction models for clinical remission associated with adalimumab treatment in patients with ulcerative colitis (UC) using Fourier transform-infrared (FT-IR) spectroscopy coupled with machine learning (ML) algorithms. This prospective, observational, multicenter study enrolled 62 UC patients and 30 healthy controls. The patients were treated with adalimumab for 56 weeks, and clinical remission was evaluated using the Mayo score. Baseline fecal samples were collected and analyzed using FT-IR spectroscopy. Various data preprocessing methods were applied, and prediction models were established by 10-fold cross-validation using various ML methods. Orthogonal partial least squares-discriminant analysis (OPLS-DA) showed a clear separation of healthy controls and UC patients, applying area normalization and Pareto scaling. OPLS-DA models predicting short- and long-term remission (8 and 56 weeks) yielded area-under-the-curve values of 0.76 and 0.75, respectively. Logistic regression and a nonlinear support vector machine were selected as the best prediction models for short- and long-term remission, respectively (accuracy of 0.99). In external validation, prediction models for short-term (logistic regression) and long-term (decision tree) remission performed well, with accuracy values of 0.73 and 0.82, respectively. This was the first study to develop prediction models for clinical remission associated with adalimumab treatment in UC patients by fecal analysis using FT-IR spectroscopy coupled with ML algorithms. Logistic regression, nonlinear support vector machines, and decision tree were suggested as the optimal prediction models for remission, and these were noninvasive, simple, inexpensive, and fast analyses that could be applied to personalized treatments.
Collapse
Affiliation(s)
- Seok-Young Kim
- College of Pharmacy, Chung-Ang University, Seoul 06974, Republic of Korea; (S.-Y.K.); (M.S.); (J.E.R.); (J.-S.K.); (J.A.); (Y.J.)
| | - Seung Yong Shin
- Department of Internal Medicine, College of Medicine, Chung-Ang University, Seoul 06973, Republic of Korea; (S.Y.S.); (J.M.M.)
| | - Maham Saeed
- College of Pharmacy, Chung-Ang University, Seoul 06974, Republic of Korea; (S.-Y.K.); (M.S.); (J.E.R.); (J.-S.K.); (J.A.); (Y.J.)
| | - Ji Eun Ryu
- College of Pharmacy, Chung-Ang University, Seoul 06974, Republic of Korea; (S.-Y.K.); (M.S.); (J.E.R.); (J.-S.K.); (J.A.); (Y.J.)
| | - Jung-Seop Kim
- College of Pharmacy, Chung-Ang University, Seoul 06974, Republic of Korea; (S.-Y.K.); (M.S.); (J.E.R.); (J.-S.K.); (J.A.); (Y.J.)
| | - Junyoung Ahn
- College of Pharmacy, Chung-Ang University, Seoul 06974, Republic of Korea; (S.-Y.K.); (M.S.); (J.E.R.); (J.-S.K.); (J.A.); (Y.J.)
| | - Youngmi Jung
- College of Pharmacy, Chung-Ang University, Seoul 06974, Republic of Korea; (S.-Y.K.); (M.S.); (J.E.R.); (J.-S.K.); (J.A.); (Y.J.)
| | - Jung Min Moon
- Department of Internal Medicine, College of Medicine, Chung-Ang University, Seoul 06973, Republic of Korea; (S.Y.S.); (J.M.M.)
| | - Chang Hwan Choi
- Department of Internal Medicine, College of Medicine, Chung-Ang University, Seoul 06973, Republic of Korea; (S.Y.S.); (J.M.M.)
| | - Hyung-Kyoon Choi
- College of Pharmacy, Chung-Ang University, Seoul 06974, Republic of Korea; (S.-Y.K.); (M.S.); (J.E.R.); (J.-S.K.); (J.A.); (Y.J.)
| |
Collapse
|
8
|
Condino F, Crocco MC, Pirritano D, Petrone A, Del Giudice F, Guzzi R. A Linear Predictor Based on FTIR Spectral Biomarkers Improves Disease Diagnosis Classification: An Application to Multiple Sclerosis. J Pers Med 2023; 13:1596. [PMID: 38003911 PMCID: PMC10672539 DOI: 10.3390/jpm13111596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 11/02/2023] [Accepted: 11/09/2023] [Indexed: 11/26/2023] Open
Abstract
Multiple sclerosis (MS) is a neurodegenerative disease of the central nervous system that can lead to long-term disability. The diagnosis of MS is not simple and requires many instrumental and clinical tests. Sampling easily collected biofluids using spectroscopic approaches is becoming of increasing interest in the medical field to integrate and improve diagnostic procedures. Here we present a statistical approach where we combine a number of spectral biomarkers derived from the ATR-FTIR spectra of blood plasma samples of healthy control subjects and MS patients, to obtain a linear predictor useful for discriminating between the two groups of individuals. This predictor provides a simple tool in which the contribution of different molecular components is summarized and, as a result, the sensitivity (80%) and specificity (93%) of the identification are significantly improved compared to those obtained with typical classification algorithms. The strategy proposed can be very helpful when applied to the diagnosis of diseases whose presence is reflected in a minimal way in the analyzed biofluids (blood and its derivatives), as it is for MS as well as for other neurological disorders.
Collapse
Affiliation(s)
- Francesca Condino
- Department of Economics, Statistics and Finance ”Giovanni Anania”, University of Calabria, 87036 Rende, Italy;
| | - Maria Caterina Crocco
- STAR Research Infrastructure, University of Calabria, 87036 Rende, Italy;
- Department of Physics, Molecular Biophysics Laboratory, University of Calabria, 87036 Rende, Italy
| | - Domenico Pirritano
- SOC Neurologia, Azienda Ospedaliero-Universitaria Renato Dulbecco, 88100 Catanzaro, Italy;
- UOC Neurologia, Azienda Ospedaliera dell’Annunziata, 87100 Cosenza, Italy; (A.P.); (F.D.G.)
| | - Alfredo Petrone
- UOC Neurologia, Azienda Ospedaliera dell’Annunziata, 87100 Cosenza, Italy; (A.P.); (F.D.G.)
| | - Francesco Del Giudice
- UOC Neurologia, Azienda Ospedaliera dell’Annunziata, 87100 Cosenza, Italy; (A.P.); (F.D.G.)
- SOC Neurologia, Ospedale Jazzolino, Azienda Ospedaliera Provinciale, 89900 Vibo Valentia, Italy
| | - Rita Guzzi
- STAR Research Infrastructure, University of Calabria, 87036 Rende, Italy;
- CNR-NANOTEC, Department of Physics, University of Calabria, 87036 Rende, Italy
| |
Collapse
|
9
|
Dou J, Dawuti W, Li J, Zhao H, Zhou R, Zhou J, Lin R, Lü G. Rapid detection of serological biomarkers in gallbladder carcinoma using fourier transform infrared spectroscopy combined with machine learning. Talanta 2023; 259:124457. [PMID: 36989965 DOI: 10.1016/j.talanta.2023.124457] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 03/10/2023] [Accepted: 03/12/2023] [Indexed: 03/29/2023]
Abstract
Gallbladder cancer (GBC) is the most common malignant tumour of the biliary tract. GBC is difficult to diagnose and treat at an early stage because of the lack of effective serum markers and typical symptoms, resulting in low survival rates. This study aimed to investigate the applicability of dried serum Fourier-transform infrared (FTIR) spectroscopy combined with machine learning algorithms to correctly differentiate patients with GBC from patients with gallbladder disease (GBD), cholangiocarcinoma (CCA), hepatocellular carcinoma (HCC) and healthy individuals. The differentiation between healthy individuals and GBC serum was better using principal component analysis (PCA) and linear discriminant analysis (LDA) for six spectral regions, especially in the protein (1710-1475 cm-1) and combined (1710-1475 + 1354-980 cm-1) region. However, the PCA-LDA model poorly differentiated GBC from GBD, CCA, and HCC in serum spectra. We evaluated the PCA- LDA, PCA-support vector machine (SVM), and radial basis kernel function support vector machine (RBF-SVM) models for GBC diagnosis and found that the RBF-SVM model performed the best, with 88.24-95% accuracy, 95.83% sensitivity, and 78.38-94.44% specificity in the 1710-1475 + 1354-980 cm-1 region. This study demonstrated that serum FTIR spectroscopy combined with the RBF-SVM algorithm has great clinical potential for GBC screening.
Collapse
|
10
|
Amin MO, Al-Hetlani E, Lednev IK. Discrimination of smokers and nonsmokers based on the analysis of fingermarks for forensic purposes. Microchem J 2023. [DOI: 10.1016/j.microc.2023.108466] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
|
11
|
Theakstone AG, Brennan PM, Jenkinson MD, Goodacre R, Baker MJ. Investigating centrifugal filtration of serum-based FTIR spectroscopy for the stratification of brain tumours. PLoS One 2023; 18:e0279669. [PMID: 36800340 PMCID: PMC9937474 DOI: 10.1371/journal.pone.0279669] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 01/31/2023] [Indexed: 02/18/2023] Open
Abstract
Discrimination of brain cancer versus non-cancer patients using serum-based attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy diagnostics was first developed by Hands et al with a reported sensitivity of 92.8% and specificity of 91.5%. Cameron et al. then went on to stratifying between specific brain tumour types: glioblastoma multiforme (GBM) vs. primary cerebral lymphoma with a sensitivity of 90.1% and specificity of 86.3%. Expanding on these studies, 30 GBM, 30 lymphoma and 30 non-cancer patients were selected to investigate the influence on test performance by focusing on specific molecular weight regions of the patient serum. Membrane filters with molecular weight cut offs of 100 kDa, 50 kDa, 30 kDa, 10 kDa and 3 kDa were purchased in order to remove the most abundant high molecular weight components. Three groups were classified using both partial least squares-discriminate analysis (PLS-DA) and random forest (RF) machine learning algorithms; GBM versus non-cancer, lymphoma versus non-cancer and GBM versus lymphoma. For all groups, once the serum was filtered the sensitivity, specificity and overall balanced accuracies decreased. This illustrates that the high molecular weight components are required for discrimination between cancer and non-cancer as well as between tumour types. From a clinical application point of view, this is preferable as less sample preparation is required.
Collapse
Affiliation(s)
- Ashton G. Theakstone
- Department of Pure and Applied Chemistry, University of Strathclyde, Glasgow, United Kingdom
| | - Paul M. Brennan
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Michael D. Jenkinson
- The Walton Centre NHS Foundation Trust, Liverpool, United Kingdom
- Department of Pharmacology & Therapeutics, University of Liverpool, Liverpool, United Kingdom
| | - Royston Goodacre
- Department of Biochemistry and Systems Biology, University of Liverpool, Liverpool, United Kingdom
| | - Matthew J. Baker
- Dxcover Limited, Glasgow, United Kingdom
- Faculty of Clinical and Biomedical Sciences, University of Central Lancashire, Preston, United Kingdom
- * E-mail: ,
| |
Collapse
|
12
|
Antoniou G, Conn JJA, Smith BR, Brennan PM, Baker MJ, Palmer DS. Recurrent neural networks for time domain modelling of FTIR spectra: application to brain tumour detection. Analyst 2023; 148:1770-1776. [PMID: 36967685 DOI: 10.1039/d2an02041f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/29/2023]
Abstract
A recurrent neural network trained on time domain data can accurately identify brain tumours from serum spectral data.
Collapse
Affiliation(s)
- Georgios Antoniou
- Dxcover Limited, Suite RC534, Royal College Building, 204 George Street, Glasgow G1 1XW, UK
| | - Justin J A Conn
- Dxcover Limited, Suite RC534, Royal College Building, 204 George Street, Glasgow G1 1XW, UK
| | - Benjamin R Smith
- Dxcover Limited, Suite RC534, Royal College Building, 204 George Street, Glasgow G1 1XW, UK
| | - Paul M Brennan
- Translational Neurosurgery, Centre for Clinical Brain Sciences, University of Edinburgh, Midlothian, Edinburgh EH4 2XU, UK
| | - Matthew J Baker
- Dxcover Limited, Suite RC534, Royal College Building, 204 George Street, Glasgow G1 1XW, UK
- School of Medicine, Faculty of Clinical and Biomedical Sciences, University of Central Lancashire, Preston PR1 2HE, UK
| | - David S Palmer
- Dxcover Limited, Suite RC534, Royal College Building, 204 George Street, Glasgow G1 1XW, UK
- Department of Pure and Applied Chemistry, University of Strathclyde, Glasgow G1 1XL, UK.
| |
Collapse
|
13
|
Rapid and sensitive detection of esophageal cancer by FTIR spectroscopy of serum and plasma. Photodiagnosis Photodyn Ther 2022; 40:103177. [PMID: 36602070 DOI: 10.1016/j.pdpdt.2022.103177] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2022] [Revised: 10/21/2022] [Accepted: 10/26/2022] [Indexed: 11/11/2022]
Abstract
Fourier transform infrared (FTIR) spectroscopy, as a platform technology for cancer detection, must be up to the challenge of clinical transformation. To this end, detection of esophageal squamous cell carcinoma (ESCC) was hereby explored using serum and plasma scrape-coated on barium fluoride (BaF2) disk by transmission FTIR method, and the classification model was built using six multivariate statistical analyses, including support vector machine (SVM), principal component linear discriminant analysis (PC-LDA), decision tree (DT), k-nearest neighbor (KNN) classification, ensemble algorithms (EA) and partial least squares for discriminant analysis (PLS-DA). All statistical analyses methods demonstrated that late-stage cancer could be well classified from healthy people employing either serum or plasma with different anticoagulants. Resulting PC-LDA model differentiated late-stage cancer from normal group with an accuracy of 99.26%, a sensitivity of 98.53%, and a specificity of 100%. The accuracy and sensitivity reached 97.08% and 91.43%, respectively for early-stage cancer discrimination from normal group. This pilot exploration demonstrated that transmission FTIR provided a rapid, cost effective and sensitive method for ESCC diagnosis using either serum or plasma.
Collapse
|
14
|
Agustika DK, Mercuriani I, Purnomo CW, Hartono S, Triyana K, Iliescu DD, Leeson MS. Fourier transform infrared spectrum pre-processing technique selection for detecting PYLCV-infected chilli plants. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2022; 278:121339. [PMID: 35537256 DOI: 10.1016/j.saa.2022.121339] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 04/12/2022] [Accepted: 04/29/2022] [Indexed: 06/14/2023]
Abstract
Pre-processing is a crucial step in analyzing spectra from Fourier transform infrared (FTIR) spectroscopy because it can reduce unwanted noise and enhance system performance. Here, we present the results of pre-processing technique optimization to facilitate the detection of pepper yellow leaf curl virus (PYLCV)-infected chilli plants using FTIR spectroscopy. Optimization of a range of pre-processing techniques was undertaken, namely baseline correction, normalization (standard normal variate, vector, and min-max), and de-noising (Savitzky-Golay (SG) smoothing, 1st and 2 derivatives). The pre-processing was applied to the mid-infrared spectral range (4000 - 400 cm-1) and the biofingerprint region (1800 - 900 cm-1) then the discrete wavelet transform (DWT) was used for dimension reduction. The pre-processed data were then used as an input for classification using a multilayer perceptron neural network, a support vector machine, and linear discriminant analysis. The pre-processing method with the highest classification model accuracy was selected for the further use in the processing. It was seen that only the SG 1st derivative method applied to both wavenumber ranges could produce 100% accuracy. This result was supported by principal component analysis clustering. Thus, we have demonstrated that by using the right pre-processing technique, classification success can be increased, and the process simplified by optimization and minimization of the technique used.
Collapse
Affiliation(s)
- Dyah K Agustika
- School of Engineering, University of Warwick, Coventry CV4 7AL, UK; Department of Physics Education, Universitas Negeri Yogyakarta, Yogyakarta, 55281 Indonesia.
| | - Ixora Mercuriani
- Department of Biology Education, Universitas Negeri Yogyakarta, Yogyakarta, 55281 Indonesia
| | - Chandra W Purnomo
- Department of Chemical Engineering, Universitas Gadjah Mada, Sekip Utara Yogyakarta, 55281 Indonesia
| | - Sedyo Hartono
- Department of Plant Protection, Faculty of Agriculture, Universitas Gadjah Mada. Jl, Flora 1, Bulaksumur, Sleman 55281, Yogyakarta
| | - Kuwat Triyana
- Department of Physics, Universitas Gadjah Mada, Sekip Utara Yogyakarta, 55281 Indonesia
| | - Doina D Iliescu
- School of Engineering, University of Warwick, Coventry CV4 7AL, UK
| | - Mark S Leeson
- School of Engineering, University of Warwick, Coventry CV4 7AL, UK.
| |
Collapse
|
15
|
Németh ZI, Németh KE, Rákosa R. Effect of ATR sample holder on the FT-IR spectrum of polypropylene foil. INTERNATIONAL JOURNAL OF POLYMER ANALYSIS AND CHARACTERIZATION 2022. [DOI: 10.1080/1023666x.2022.2121491] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
Affiliation(s)
| | | | - Rita Rákosa
- Spectrometry Laboratory, Ingvesting Team Ltd, Sopron, Hungary
| |
Collapse
|
16
|
Sala A, Cameron JM, Jenkins CA, Barr H, Christie L, Conn JJA, Evans TRJ, Harris DA, Palmer DS, Rinaldi C, Theakstone AG, Baker MJ. Liquid Biopsy for Pancreatic Cancer Detection Using Infrared Spectroscopy. Cancers (Basel) 2022; 14:3048. [PMID: 35804820 PMCID: PMC9264892 DOI: 10.3390/cancers14133048] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Revised: 06/16/2022] [Accepted: 06/20/2022] [Indexed: 12/04/2022] Open
Abstract
Pancreatic cancer claims over 460,000 victims per year. The carbohydrate antigen (CA) 19-9 test is the blood test used for pancreatic cancer's detection; however, its levels can be raised in symptomatic patients with other non-malignant diseases, or with other tumors in the surrounding area. Attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy has demonstrated exceptional potential in cancer diagnostics, and its clinical implementation could represent a significant step towards early detection. This proof-of-concept study, investigating the use of ATR-FTIR spectroscopy on dried blood serum, focused on the discrimination of both cancer versus healthy control samples, and cancer versus symptomatic non-malignant control samples, as a novel liquid biopsy approach for pancreatic cancer diagnosis. Machine learning algorithms were applied, achieving results of up to 92% sensitivity and 88% specificity when discriminating between cancers (n = 100) and healthy controls (n = 100). An area under the curve (AUC) of 0.95 was obtained through receiver operating characteristic (ROC) analysis. Balanced sensitivity and specificity over 75%, with an AUC of 0.83, were achieved with cancers (n = 35) versus symptomatic controls (n = 35). Herein, we present these results as demonstration that our liquid biopsy approach could become a simple, minimally invasive, and reliable diagnostic test for pancreatic cancer detection.
Collapse
Affiliation(s)
- Alexandra Sala
- Department of Pure and Applied Chemistry, University of Strathclyde, Thomas Graham Building, Glasgow G1 1XL, UK; (A.S.); (L.C.); (D.S.P.)
- Dxcover Limited, Royal College Building, Glasgow G1 1XW, UK; (J.M.C.); (J.J.A.C.)
| | - James M. Cameron
- Dxcover Limited, Royal College Building, Glasgow G1 1XW, UK; (J.M.C.); (J.J.A.C.)
| | - Cerys A. Jenkins
- Swansea University Medical School, Swansea University, Swansea SA2 8PP, UK;
| | - Hugh Barr
- Gloucestershire Hospitals NHS Foundation Trust, Gloucester GL1 2EL, UK;
| | - Loren Christie
- Department of Pure and Applied Chemistry, University of Strathclyde, Thomas Graham Building, Glasgow G1 1XL, UK; (A.S.); (L.C.); (D.S.P.)
- Dxcover Limited, Royal College Building, Glasgow G1 1XW, UK; (J.M.C.); (J.J.A.C.)
| | - Justin J. A. Conn
- Dxcover Limited, Royal College Building, Glasgow G1 1XW, UK; (J.M.C.); (J.J.A.C.)
| | | | - Dean A. Harris
- Singleton Hospital, Swansea Bay University Local Health Board, Swansea SA2 8QA, UK;
| | - David S. Palmer
- Department of Pure and Applied Chemistry, University of Strathclyde, Thomas Graham Building, Glasgow G1 1XL, UK; (A.S.); (L.C.); (D.S.P.)
- Dxcover Limited, Royal College Building, Glasgow G1 1XW, UK; (J.M.C.); (J.J.A.C.)
| | - Christopher Rinaldi
- Department of Pure and Applied Chemistry, University of Strathclyde, The Technology and Innovation Centre, Glasgow G1 1RD, UK; (C.R.); (A.G.T.)
| | - Ashton G. Theakstone
- Department of Pure and Applied Chemistry, University of Strathclyde, The Technology and Innovation Centre, Glasgow G1 1RD, UK; (C.R.); (A.G.T.)
| | - Matthew J. Baker
- Dxcover Limited, Royal College Building, Glasgow G1 1XW, UK; (J.M.C.); (J.J.A.C.)
| |
Collapse
|
17
|
Woods FER, Jenkins CA, Jenkins RA, Chandler S, Harris DA, Dunstan PR. Optimised Pre-Processing of Raman Spectra for Colorectal Cancer Detection Using High-Performance Computing. APPLIED SPECTROSCOPY 2022; 76:496-507. [PMID: 35255720 DOI: 10.1177/00037028221088320] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Spectral pre-processing is an essential step in data analysis for biomedical diagnostic applications of Raman spectroscopy, allowing the removal of undesirable spectral contributions that could mask biological information used for diagnosis. However, due to the specificity of pre-processing for a given sample type and the vast number of potential pre-processing combinations, optimisation of pre-processing via a manual "trial and error" format is often time intensive with no guarantee that the chosen method is optimal for the sample type. Here we present the use of high-performance computing (HPC) to trial over 2.4 million pre-processing permutations to demonstrate the optimisation on the pre-processing of human serum Raman spectra for colorectal cancer detection. The effect of varying pre-processing order, using extended multiplicative scatter correction, spectral smoothing, baseline correction, binning and normalization was considered. Permutations were assessed on their ability to detect patients with disease using a random forest (RF) algorithm trained with 102 patients (510 spectra) and independently tested with a set of 439 patients (1317 spectra) in a primary care patient cohort. Optimising via HPC enables improved performance in diagnostic abilities, with sensitivity increasing by 14.6%, specificity increasing by 6.9%, positive predictive value increasing by 3.4%, and negative predictive value increasing by 2.4% when compared to a standard pre-processing optimisation. Ultimate values of these metrics are very important for diagnostic adoption, and once diagnostics demonstrate good accuracy these types of optimisations can make a significant difference to roll-out of a test and demonstrating advantages over existing tests. We also provide tips/recommendations for pre-processing optimisation without the use of HPC. From the HPC permutations, recommendations for appropriate parameter constraints for conducting a more basic pre-processing optimisation are also detailed, thus helping model development for researchers not having access to HPC.
Collapse
Affiliation(s)
| | | | - Rhys A Jenkins
- Blackett Laboratory, 4615Imperial College London, London, UK
| | | | - Dean A Harris
- Medical School, 151375Swansea University, Swansea, UK
- Department of Colorectal Surgery, 97701Morriston Hospital, Swansea, Wales, UK
| | | |
Collapse
|
18
|
Cameron JM, Brennan PM, Antoniou G, Butler HJ, Christie L, Conn JJA, Curran T, Gray E, Hegarty MG, Jenkinson MD, Orringer D, Palmer DS, Sala A, Smith BR, Baker MJ. Clinical validation of a spectroscopic liquid biopsy for earlier detection of brain cancer. Neurooncol Adv 2022; 4:vdac024. [PMID: 35316978 PMCID: PMC8934542 DOI: 10.1093/noajnl/vdac024] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Abstract
Background
Diagnostic delays impact the quality of life and survival of patients with brain tumors. Earlier and expeditious diagnoses in these patients are crucial to reducing the morbidities and mortalities associated with brain tumors. A simple, rapid blood test that can be administered easily in a primary care setting to efficiently identify symptomatic patients who are most likely to have a brain tumor would enable quicker referral to brain imaging for those who need it most.
Methods
Blood serum samples from 603 patients were prospectively collected and analyzed. Patients either had non-specific symptoms that could be indicative of a brain tumor on presentation to the Emergency Department, or a new brain tumor diagnosis and referral to the neurosurgical unit, NHS Lothian, Scotland. Patient blood serum samples were analyzed using the Dxcover®Brain Cancer liquid biopsy. This technology utilizes infrared spectroscopy combined with a diagnostic algorithm to predict the presence of intracranial disease.
Results
Our liquid biopsy approach reported an area under the receiver operating characteristic curve of 0.8. The sensitivity-tuned model achieves a 96% sensitivity with 45% specificity (NPV 99.3%) and identified 100% of glioblastoma multiforme patients. When tuned for a higher specificity, the model yields sensitivity of 47% with 90% specificity (PPV 28.4%).
Conclusions
This simple, non-invasive blood test facilitates the triage and radiographic diagnosis of brain tumor patients, while providing reassurance to healthy patients. Minimizing time to diagnosis would facilitate identification of brain tumor patients at an earlier stage, enabling more effective, less morbid surgical and adjuvant care.
Collapse
Affiliation(s)
- James M Cameron
- Dxcover Ltd , Suite RC534, Royal College Building, 204 George Street, Glasgow, G1 1XW, UK
| | - Paul M Brennan
- Translational Neurosurgery, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Georgios Antoniou
- Dxcover Ltd , Suite RC534, Royal College Building, 204 George Street, Glasgow, G1 1XW, UK
| | - Holly J Butler
- Dxcover Ltd , Suite RC534, Royal College Building, 204 George Street, Glasgow, G1 1XW, UK
| | - Loren Christie
- Dxcover Ltd , Suite RC534, Royal College Building, 204 George Street, Glasgow, G1 1XW, UK
| | - Justin J A Conn
- Dxcover Ltd , Suite RC534, Royal College Building, 204 George Street, Glasgow, G1 1XW, UK
| | - Tom Curran
- Children’s Mercy Research Institute at the Children’s Mercy Hospital, Kansas City, KS, USA
| | - Ewan Gray
- Independent Health Economics Consultant, Edinburgh, UK
| | - Mark G Hegarty
- Dxcover Ltd , Suite RC534, Royal College Building, 204 George Street, Glasgow, G1 1XW, UK
| | - Michael D Jenkinson
- Institute of Translational Medicine, University of Liverpool & The Walton Centre NHS Foundation Trust, Lower Lane, Liverpool, L9 7LJ, UK
| | - Daniel Orringer
- Department of Neurosurgery, New York University Grossman School of Medicine, New York, NY 10018, USA
| | - David S Palmer
- Dxcover Ltd , Suite RC534, Royal College Building, 204 George Street, Glasgow, G1 1XW, UK
| | - Alexandra Sala
- Dxcover Ltd , Suite RC534, Royal College Building, 204 George Street, Glasgow, G1 1XW, UK
- Department of Pure and Applied Chemistry, Thomas Graham Building, 295 Cathedral Street, University of Strathclyde, Glasgow G11XL, UK
| | - Benjamin R Smith
- Dxcover Ltd , Suite RC534, Royal College Building, 204 George Street, Glasgow, G1 1XW, UK
| | - Matthew J Baker
- Dxcover Ltd , Suite RC534, Royal College Building, 204 George Street, Glasgow, G1 1XW, UK
| |
Collapse
|
19
|
Yang S, Zhang Q, Yang H, Shi H, Dong A, Wang L, Yu S. Progress in infrared spectroscopy as an efficient tool for predicting protein secondary structure. Int J Biol Macromol 2022; 206:175-187. [PMID: 35217087 DOI: 10.1016/j.ijbiomac.2022.02.104] [Citation(s) in RCA: 52] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Revised: 02/14/2022] [Accepted: 02/17/2022] [Indexed: 12/21/2022]
Abstract
Infrared (IR) spectroscopy is a highly sensitive technique that provides complete information on chemical compositions. The IR spectra of proteins or peptides give rise to nine characteristic IR absorption bands. The amide I bands are the most prominent and sensitive vibrational bands and widely used to predict protein secondary structures. The interference of H2O absorbance is the greatest challenge for IR protein secondary structure prediction. Much effort has been made to reduce/eliminate the interference of H2O, simplify operation steps, and increase prediction accuracy. Progress in sampling and equipment has rendered the Fourier transform infrared (FTIR) technique suitable for determining the protein secondary structure in broader concentration ranges, greatly simplifying the operating steps. This review highlights the recent progress in sample preparation, data analysis, and equipment development of FTIR in A/T mode, with a focus on recent applications of FTIR spectroscopy in the prediction of protein secondary structure. This review also provides a brief introduction of the progress in ATR-FTIR for predicting protein secondary structure and discusses some combined IR methods, such as AFM-based IR spectroscopy, that are used to analyze protein structural dynamics and protein aggregation.
Collapse
Affiliation(s)
- Shouning Yang
- Zhejiang Provincial Key Laboratory of Advanced Mass Spectrometry and Molecular Analysis, Institute of Mass Spectrometry, School of Material Science and Chemical Engineering, Ningbo University, Ningbo, Zhejiang 315211, China
| | | | - Huayan Yang
- Zhejiang Provincial Key Laboratory of Advanced Mass Spectrometry and Molecular Analysis, Institute of Mass Spectrometry, School of Material Science and Chemical Engineering, Ningbo University, Ningbo, Zhejiang 315211, China
| | - Haimei Shi
- Zhejiang Provincial Key Laboratory of Advanced Mass Spectrometry and Molecular Analysis, Institute of Mass Spectrometry, School of Material Science and Chemical Engineering, Ningbo University, Ningbo, Zhejiang 315211, China
| | - Aichun Dong
- Department of Chemistry and Biochemistry, University of Northern Colorado, Greeley, CO, USA.
| | - Li Wang
- Kweichow Moutai Group, Renhuai, Guizhou 564501, China.
| | - Shaoning Yu
- Zhejiang Provincial Key Laboratory of Advanced Mass Spectrometry and Molecular Analysis, Institute of Mass Spectrometry, School of Material Science and Chemical Engineering, Ningbo University, Ningbo, Zhejiang 315211, China.
| |
Collapse
|
20
|
Nascimento MC, Marcarini WD, Folli GS, da Silva Filho WG, Barbosa LL, Paulo EH, Vassallo PF, Mill JG, Barauna V, Martin FL, de Castro ER, Romão W, Filgueiras PR. Noninvasive Diagnostic for COVID-19 from Saliva Biofluid via FTIR Spectroscopy and Multivariate Analysis. Anal Chem 2022; 94:2425-2433. [PMID: 35076208 PMCID: PMC8805707 DOI: 10.1021/acs.analchem.1c04162] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Accepted: 01/13/2022] [Indexed: 01/22/2023]
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused the worst global health crisis in living memory. The reverse transcription polymerase chain reaction (RT-qPCR) is considered the gold standard diagnostic method, but it exhibits limitations in the face of enormous demands. We evaluated a mid-infrared (MIR) data set of 237 saliva samples obtained from symptomatic patients (138 COVID-19 infections diagnosed via RT-qPCR). MIR spectra were evaluated via unsupervised random forest (URF) and classification models. Linear discriminant analysis (LDA) was applied following the genetic algorithm (GA-LDA), successive projection algorithm (SPA-LDA), partial least squares (PLS-DA), and a combination of dimension reduction and variable selection methods by particle swarm optimization (PSO-PLS-DA). Additionally, a consensus class was used. URF models can identify structures even in highly complex data. Individual models performed well, but the consensus class improved the validation performance to 85% accuracy, 93% sensitivity, 83% specificity, and a Matthew's correlation coefficient value of 0.69, with information at different spectral regions. Therefore, through this unsupervised and supervised framework methodology, it is possible to better highlight the spectral regions associated with positive samples, including lipid (∼1700 cm-1), protein (∼1400 cm-1), and nucleic acid (∼1200-950 cm-1) regions. This methodology presents an important tool for a fast, noninvasive diagnostic technique, reducing costs and allowing for risk reduction strategies.
Collapse
Affiliation(s)
- Márcia
H. C. Nascimento
- Chemometrics
Laboratory of the Center of Competence in Petroleum Chemistry −
NCQP, Universidade Federal do Espírito
Santo (UFES), Vitória, Espírito Santo 29075-910, Brazil
| | - Wena D. Marcarini
- Department
of Physiological Sciences, Universidade
Federal do Espírito Santo (UFES), Vitória, Espírito Santo 29040-090, Brazil
| | - Gabriely S. Folli
- Chemometrics
Laboratory of the Center of Competence in Petroleum Chemistry −
NCQP, Universidade Federal do Espírito
Santo (UFES), Vitória, Espírito Santo 29075-910, Brazil
| | - Walter G. da Silva Filho
- Department
of Physiological Sciences, Universidade
Federal do Espírito Santo (UFES), Vitória, Espírito Santo 29040-090, Brazil
| | - Leonardo L. Barbosa
- Department
of Physiological Sciences, Universidade
Federal do Espírito Santo (UFES), Vitória, Espírito Santo 29040-090, Brazil
| | - Ellisson Henrique
de Paulo
- Chemometrics
Laboratory of the Center of Competence in Petroleum Chemistry −
NCQP, Universidade Federal do Espírito
Santo (UFES), Vitória, Espírito Santo 29075-910, Brazil
| | - Paula F. Vassallo
- Clinical
Hospital, Universidade Federal de Minas
Gerais, Belo Horizonte, Minas Gerais 31270-901, Brazil
| | - José G. Mill
- Department
of Physiological Sciences, Universidade
Federal do Espírito Santo (UFES), Vitória, Espírito Santo 29040-090, Brazil
| | - Valério
G. Barauna
- Department
of Physiological Sciences, Universidade
Federal do Espírito Santo (UFES), Vitória, Espírito Santo 29040-090, Brazil
| | | | - Eustáquio
V. R. de Castro
- Chemometrics
Laboratory of the Center of Competence in Petroleum Chemistry −
NCQP, Universidade Federal do Espírito
Santo (UFES), Vitória, Espírito Santo 29075-910, Brazil
| | - Wanderson Romão
- Instituto
Federal de Educação, Ciência
e Tecnologia do Espírito Santo, Vila Velha 29106-010, Brazil
| | - Paulo R. Filgueiras
- Chemometrics
Laboratory of the Center of Competence in Petroleum Chemistry −
NCQP, Universidade Federal do Espírito
Santo (UFES), Vitória, Espírito Santo 29075-910, Brazil
| |
Collapse
|
21
|
Meyvisch P, Gurdebeke PR, Vrielinck H, Neil Mertens K, Versteegh G, Louwye S. Attenuated Total Reflection (ATR) Micro-Fourier Transform Infrared (Micro-FT-IR) Spectroscopy to Enhance Repeatability and Reproducibility of Spectra Derived from Single Specimen Organic-Walled Dinoflagellate Cysts. APPLIED SPECTROSCOPY 2022; 76:235-254. [PMID: 34494488 DOI: 10.1177/00037028211041172] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
The chemical composition of recent and fossil organic-walled dinoflagellate cyst walls and its diversity is poorly understood and analyses on single microscopic specimens are rare. A series of infrared spectroscopic experiments resulted in the proposition of a standardized attenuated total reflection micro-Fourier transform infrared-based method that allows the collection of robust data sets consisting of spectra from individual dinocysts. These data sets are largely devoid of nonchemical artifacts inherent to other infrared spectrochemical methods, which have typically been used to study similar specimens in the past. The influence of sample preparation, specimen morphology and size and spectral data processing steps is also assessed within this methodological framework. As a result, several guidelines are proposed which facilitate the collection and qualitative interpretation of highly reproducible and repeatable spectrochemical data. These, in turn, pave the way for a systematic exploration of dinocyst chemistry and its assessment as a chemotaxonomical tool or proxy.
Collapse
Affiliation(s)
| | | | - Henk Vrielinck
- Department of Solid-State Sciences, Ghent University, Ghent, Belgium
| | | | - Gerard Versteegh
- Marine Biochemistry Group, Alfred-Wegener-Institute, Bremerhaven, Germany
| | | |
Collapse
|
22
|
Holden CA, Bailey JP, Taylor JE, Martin F, Beckett P, McAinsh M. Know your enemy: Application of ATR-FTIR spectroscopy to invasive species control. PLoS One 2022; 17:e0261742. [PMID: 34995300 PMCID: PMC8740966 DOI: 10.1371/journal.pone.0261742] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Accepted: 12/08/2021] [Indexed: 11/29/2022] Open
Abstract
Extreme weather and globalisation leave our climate vulnerable to invasion by alien species, which have negative impacts on the economy, biodiversity, and ecosystem services. Rapid and accurate identification is key to the control of invasive alien species. However, visually similar species hinder conservation efforts, for example hybrids within the Japanese Knotweed complex.We applied the novel method of ATR-FTIR spectroscopy combined with chemometrics (mathematics applied to chemical data) to historic herbarium samples, taking 1580 spectra in total. Samples included five species from within the interbreeding Japanese Knotweed complex (including three varieties of Japanese Knotweed), six hybrids and five species from the wider Polygonaceae family. Spectral data from herbarium specimens were analysed with several chemometric techniques: support vector machines (SVM) for differentiation between plant types, supported by ploidy levels; principal component analysis loadings and spectral biomarkers to explore differences between the highly invasive Reynoutria japonica var. japonica and its non-invasive counterpart Reynoutria japonica var. compacta; hierarchical cluster analysis (HCA) to investigate the relationship between plants within the Polygonaceae family, of the Fallopia, Reynoutria, Rumex and Fagopyrum genera.ATR-FTIR spectroscopy coupled with SVM successfully differentiated between plant type, leaf surface and geographical location, even in herbarium samples of varying age. Differences between Reynoutria japonica var. japonica and Reynoutria japonica var. compacta included the presence of two polysaccharides, glucomannan and xyloglucan, at higher concentrations in Reynoutria japonica var. japonica than Reynoutria japonica var. compacta. HCA analysis indicated that potential genetic linkages are sometimes masked by environmental factors; an effect that can either be reduced or encouraged by altering the input parameters. Entering the absorbance values for key wavenumbers, previously highlighted by principal component analysis loadings, favours linkages in the resultant HCA dendrogram corresponding to expected genetic relationships, whilst environmental associations are encouraged using the spectral fingerprint region.The ability to distinguish between closely related interbreeding species and hybrids, based on their spectral signature, raises the possibility of using this approach for determining the origin of Japanese knotweed infestations in legal cases where the clonal nature of plants currently makes this difficult and for the targeted control of species and hybrids. These techniques also provide a new method for supporting biogeographical studies.
Collapse
Affiliation(s)
- Claire Anne Holden
- Lancaster Environment Centre, Lancaster University, Lancaster, United Kingdom
| | - John Paul Bailey
- Department of Genetics and Genome Biology, Leicester University, Leicester, United Kingdom
| | | | | | | | - Martin McAinsh
- Lancaster Environment Centre, Lancaster University, Lancaster, United Kingdom
| |
Collapse
|
23
|
Holden CA, Morais CLM, Taylor JE, Martin FL, Beckett P, McAinsh M. Regional differences in clonal Japanese knotweed revealed by chemometrics-linked attenuated total reflection Fourier-transform infrared spectroscopy. BMC PLANT BIOLOGY 2021; 21:522. [PMID: 34753418 PMCID: PMC8579538 DOI: 10.1186/s12870-021-03293-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Accepted: 10/19/2021] [Indexed: 06/13/2023]
Abstract
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.
Collapse
Affiliation(s)
- Claire A Holden
- Lancaster Environment Centre, Lancaster University, Lancaster, UK.
| | - Camilo L M Morais
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston, UK
| | - Jane E Taylor
- Lancaster Environment Centre, Lancaster University, Lancaster, UK
| | | | | | - Martin McAinsh
- Lancaster Environment Centre, Lancaster University, Lancaster, UK
| |
Collapse
|
24
|
Theakstone AG, Brennan PM, Jenkinson MD, Mills SJ, Syed K, Rinaldi C, Xu Y, Goodacre R, Butler HJ, Palmer DS, Smith BR, Baker MJ. Rapid Spectroscopic Liquid Biopsy for the Universal Detection of Brain Tumours. Cancers (Basel) 2021; 13:cancers13153851. [PMID: 34359751 PMCID: PMC8345395 DOI: 10.3390/cancers13153851] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 07/22/2021] [Accepted: 07/29/2021] [Indexed: 11/16/2022] Open
Abstract
Simple Summary Due to the non-specific symptoms of brain cancer (e.g., headaches or memory changes), gliomas will often remain undetected until they are larger or at a higher grade, reducing the patient’s likelihood of a good clinical outcome. Earlier detection and diagnosis of brain tumours is vital to improve patient outcomes, leading to safer surgeries and earlier treatments. A liquid biopsy for brain tumour would prove revolutionary however in order to detect disease earlier the liquid biopsy needs to be able to detect smaller tumours; and current liquid biopsies perform worse when detecting smaller or earlier stage tumours. Here, for the first time, we confirm the applicability of a validated spectroscopic liquid biopsy approach to detect both small and low-grade gliomas proving that the spectroscopic liquid biopsy approach is insensitive to tumour volume unlike other liquid biopsies. Abstract Background: To support the early detection and diagnosis of brain tumours we have developed a rapid, cost-effective and easy to use spectroscopic liquid biopsy based on the absorbance of infrared radiation. We have previously reported highly sensitive results of our approach which can discriminate patients with a recent brain tumour diagnosis and asymptomatic controls. Other liquid biopsy approaches (e.g., based on tumour genetic material) report a lower classification accuracy for early-stage tumours. In this manuscript we present an investigation into the link between brain tumour volume and liquid biopsy test performance. Methods: In a cohort of 177 patients (90 patients with high-grade glioma (glioblastoma (GBM) or anaplastic astrocytoma), or low-grade glioma (astrocytoma, oligoastrocytoma and oligodendroglioma)) tumour volumes were calculated from magnetic resonance imaging (MRI) investigations and patients were split into two groups depending on MRI parameters (T1 with contrast enhancement or T2/FLAIR (fluid-attenuated inversion recovery)). Using attenuated total reflection (ATR)-Fourier transform infrared (FTIR) spectroscopy coupled with supervised learning methods and machine learning algorithms, 90 tumour patients were stratified against 87 control patients who displayed no symptomatic indications of cancer, and were classified as either glioma or non-glioma. Results: Sensitivities, specificities and balanced accuracies were all greater than 88%, the area under the curve (AUC) was 0.98, and cancer patients with tumour volumes as small as 0.2 cm3 were correctly identified. Conclusions: Our spectroscopic liquid biopsy approach can identify gliomas that are both small and low-grade showing great promise for deployment of this technique for early detection and diagnosis.
Collapse
Affiliation(s)
- Ashton G. Theakstone
- Technology and Innovation Centre, Department of Pure and Applied Chemistry, University of Strathclyde, Glasgow G1 1RD, UK;
- Correspondence: (A.G.T.); (M.J.B.); Tel.: +44-141-444-7343 (A.G.T.); +44-141-548-4700 (M.J.B.)
| | - Paul M. Brennan
- Translational Neurosurgery, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK;
| | - Michael D. Jenkinson
- The Walton Centre NHS Foundation Trust, Lower Lane, Liverpool L9 7LJ, UK; (M.D.J.); (S.J.M.); (K.S.)
- Department of Pharmacology & Therapeutics, Institute of System, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, UK
| | - Samantha J. Mills
- The Walton Centre NHS Foundation Trust, Lower Lane, Liverpool L9 7LJ, UK; (M.D.J.); (S.J.M.); (K.S.)
| | - Khaja Syed
- The Walton Centre NHS Foundation Trust, Lower Lane, Liverpool L9 7LJ, UK; (M.D.J.); (S.J.M.); (K.S.)
| | - Christopher Rinaldi
- Technology and Innovation Centre, Department of Pure and Applied Chemistry, University of Strathclyde, Glasgow G1 1RD, UK;
| | - Yun Xu
- Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, UK; (Y.X.); (R.G.)
| | - Royston Goodacre
- Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, UK; (Y.X.); (R.G.)
| | - Holly J. Butler
- Dxcover Limited, 204 George Street, Glasgow G1 1XW, UK; (H.J.B.); (D.S.P.); (B.R.S.)
| | - David S. Palmer
- Dxcover Limited, 204 George Street, Glasgow G1 1XW, UK; (H.J.B.); (D.S.P.); (B.R.S.)
- Department of Pure and Applied Chemistry, University of Strathclyde, Thomas Graham Building, Glasgow G1 1XL, UK
| | - Benjamin R. Smith
- Dxcover Limited, 204 George Street, Glasgow G1 1XW, UK; (H.J.B.); (D.S.P.); (B.R.S.)
| | - Matthew J. Baker
- Dxcover Limited, 204 George Street, Glasgow G1 1XW, UK; (H.J.B.); (D.S.P.); (B.R.S.)
- Correspondence: (A.G.T.); (M.J.B.); Tel.: +44-141-444-7343 (A.G.T.); +44-141-548-4700 (M.J.B.)
| |
Collapse
|
25
|
Brennan PM, Butler HJ, Christie L, Hegarty MG, Jenkinson MD, Keerie C, Norrie J, O'Brien R, Palmer DS, Smith BR, Baker MJ. Early diagnosis of brain tumours using a novel spectroscopic liquid biopsy. Brain Commun 2021; 3:fcab056. [PMID: 33997782 PMCID: PMC8111062 DOI: 10.1093/braincomms/fcab056] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Revised: 02/15/2021] [Accepted: 02/17/2021] [Indexed: 12/05/2022] Open
Abstract
Early diagnosis of brain tumours is challenging and a major unmet need. Patients with brain tumours most often present with non-specific symptoms more commonly associated with less serious diagnoses, making it difficult to determine which patients to prioritize for brain imaging. Delays in diagnosis affect timely access to treatment, with potential impacts on quality of life and survival. A test to help identify which patients with non-specific symptoms are most likely to have a brain tumour at an earlier stage would dramatically impact on patients by prioritizing demand on diagnostic imaging facilities. This clinical feasibility study of brain tumour early diagnosis was aimed at determining the accuracy of our novel spectroscopic liquid biopsy test for the triage of patients with non-specific symptoms that might be indicative of a brain tumour, for brain imaging. Patients with a suspected brain tumour based on assessment of their symptoms in primary care can be referred for open access CT scanning. Blood samples were prospectively obtained from 385 of such patients, or patients with a new brain tumour diagnosis. Samples were analysed using our spectroscopic liquid biopsy test to predict presence of disease, blinded to the brain imaging findings. The results were compared to the patient’s index brain imaging delivered as per standard care. Our test predicted the presence of glioblastoma, the most common and aggressive brain tumour, with 91% sensitivity, and all brain tumours with 81% sensitivity, and 80% specificity. Negative predictive value was 95% and positive predictive value 45%. The reported levels of diagnostic accuracy presented here have the potential to improve current symptom-based referral guidelines, and streamline assessment and diagnosis of symptomatic patients with a suspected brain tumour.
Collapse
Affiliation(s)
- Paul M Brennan
- Translational Neurosurgery, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Holly J Butler
- ClinSpec Diagnostics Limited, Royal College Building, Glasgow G1 1XW, UK
| | - Loren Christie
- ClinSpec Diagnostics Limited, Royal College Building, Glasgow G1 1XW, UK
| | - Mark G Hegarty
- ClinSpec Diagnostics Limited, Royal College Building, Glasgow G1 1XW, UK
| | - Michael D Jenkinson
- Institute of Translational Medicine, University of Liverpool & The Walton Centre NHS Foundation Trust, Liverpool L9 7LJ, UK
| | - Catriona Keerie
- Edinburgh Clinical Trials Unit, Usher Institute-University of Edinburgh, Edinburgh EH16 4UX, UK
| | - John Norrie
- Edinburgh Clinical Trials Unit, Usher Institute-University of Edinburgh, Edinburgh EH16 4UX, UK
| | - Rachel O'Brien
- Emergency Medicine Research Group (EMERGE), Royal Infirmiry of Edinburgh, Edinburgh EH16 4SA, UK
| | - David S Palmer
- ClinSpec Diagnostics Limited, Royal College Building, Glasgow G1 1XW, UK.,Department of Pure and Applied Chemistry, Thomas Graham Building, University of Strathclyde, Glasgow G11XL, UK
| | - Benjamin R Smith
- ClinSpec Diagnostics Limited, Royal College Building, Glasgow G1 1XW, UK
| | - Matthew J Baker
- ClinSpec Diagnostics Limited, Royal College Building, Glasgow G1 1XW, UK
| |
Collapse
|
26
|
Elkadi OA, Hassan R, Elanany M, Byrne HJ, Ramadan MA. Identification of Aspergillus species in human blood plasma by infrared spectroscopy and machine learning. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2021; 248:119259. [PMID: 33307345 DOI: 10.1016/j.saa.2020.119259] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Revised: 11/14/2020] [Accepted: 11/24/2020] [Indexed: 06/12/2023]
Abstract
Invasive Aspergillosis is a challenging infection that requires convenient, efficient, and cost-effective diagnostics. This study addresses the potential of infrared spectroscopy to satisfy this clinical need with the aid of machine learning. Two models, based on Partial Least Squares-Discriminant Analysis (PLS-DA), have been trained by a set of infrared spectral data of 9 Aspergillus-spiked and 7 Aspergillus-free plasma samples, and a set of 200 spectral data simulated by oversampling these 16 samples. Two further models have also been trained by the same sets but with auto-scaling performed prior to PLS-DA. These models were assessed using 45 mock samples, simulating the challenging samples of patients at risk of Invasive Aspergillosis, including the presence of drugs (9 tested) and other common pathogens (5 tested) as potential confounders. The simple model shows good prediction performance, yielding a total accuracy of 84.4%, while oversampling and autoscaling improved this accuracy to 93.3%. The results of this study have shown that infrared spectroscopy can identify Aspergillus species in blood plasma even in presence of potential confounders commonly present in blood of patients at risk of Invasive Aspergillosis.
Collapse
Affiliation(s)
- Omar Anwar Elkadi
- Department of Microbiology and Immunology, Faculty of Pharmacy, Cairo University, Cairo, Egypt; Dar Elsalam Cancer Center, Cairo, Egypt.
| | - Reem Hassan
- Department of Clinical Pathology, Faculty of Medicine, Cairo University, Cairo, Egypt.
| | - Mervat Elanany
- Department of Clinical Pathology, Faculty of Medicine, Cairo University, Cairo, Egypt.
| | - Hugh J Byrne
- FOCAS Research Institute, Technological University Dublin, City Campus, Dublin, Ireland.
| | - Mohammed A Ramadan
- Department of Microbiology and Immunology, Faculty of Pharmacy, Cairo University, Cairo, Egypt.
| |
Collapse
|
27
|
Theakstone AG, Rinaldi C, Butler HJ, Cameron JM, Confield LR, Rutherford SH, Sala A, Sangamnerkar S, Baker MJ. Fourier‐transform infrared spectroscopy of biofluids: A practical approach. TRANSLATIONAL BIOPHOTONICS 2021. [DOI: 10.1002/tbio.202000025] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Affiliation(s)
- Ashton G. Theakstone
- WestCHEM, Department of Pure and Applied Chemistry Technology and Innovation Centre Glasgow UK
| | - Christopher Rinaldi
- WestCHEM, Department of Pure and Applied Chemistry Technology and Innovation Centre Glasgow UK
| | | | | | - Lily Rose Confield
- WestCHEM, Department of Pure and Applied Chemistry Technology and Innovation Centre Glasgow UK
- CDT Medical Devices, Department of Biomedical Engineering Wolfson Centre Glasgow UK
| | - Samantha H. Rutherford
- WestCHEM, Department of Pure and Applied Chemistry Technology and Innovation Centre Glasgow UK
| | - Alexandra Sala
- WestCHEM, Department of Pure and Applied Chemistry Technology and Innovation Centre Glasgow UK
- ClinSpec Diagnostics Ltd, Royal College Building Glasgow UK
| | - Sayali Sangamnerkar
- WestCHEM, Department of Pure and Applied Chemistry Technology and Innovation Centre Glasgow UK
| | - Matthew J. Baker
- WestCHEM, Department of Pure and Applied Chemistry Technology and Innovation Centre Glasgow UK
- ClinSpec Diagnostics Ltd, Royal College Building Glasgow UK
| |
Collapse
|
28
|
Kelani KM, Rezk MR, Monir HH, ElSherbiny MS, Eid SM. FTIR combined with chemometric tools (fingerprinting spectroscopy) in comparison to HPLC: which strategy offers more opportunities as a green analytical chemistry technique for pharmaceutical analysis. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2020; 12:5893-5907. [PMID: 33290449 DOI: 10.1039/d0ay01749c] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Fourier transform infrared spectroscopy (FTIR) is a widespread technique that can provide a chemical signature (fingerprints) of solid, liquid, or gas samples with a wide range of analytical applications. High-performance liquid chromatography (HPLC) is a leading analytical strategy for pharmaceutical analysis. Here we present a side-by-side comparison of the potential of these techniques for quantitative analysis of pharmaceutical active ingredient combinations in light of green analytical chemistry (GAC) principles. The methods were successfully applied for the analysis of ketoprofen (KTP)/hyoscine (HYS) and benzocaine (BENZ)/dextromethorphan HBr (DEX) in their binary mixtures and pharmaceutical preparations. In FTIR analysis, calibration models were constructed based on partial least squares regression (PLSR) with satisfactory regression coefficients (r2) of 0.9998, 0.9994, 0.9855, and 0.9895 for KTP, HYS, DEX, and BENZ, respectively, over a wide linearity range (10-100, 10-100, 5-75, and 10-100 μg mL-1) that covers the concentration ratios in the market samples. External validation using a validation set and internal validation using leave-one-out-cross-validation calculations were performed, and small root-mean-square-error-of-cross-validation (RMSECV) values were obtained indicating the good resolving power of the models. The same performance was obtained using the HPLC method for separation of the same mixtures with r2 equal to 0.9998, 0.9999, 0.9998, and 0.9998 over linear ranges of 50-1000, 10-200, 5-100, and 5-100 μg mL-1 for KTP, HYS, DEX, and BENZ, respectively. The HPLC methods were validated following ICH guidelines with good recovery percentages in the range of 98-100%. The statistical comparison of the FTIR and HPLC methods for analysis showed almost the same results with good applicability towards commercial dosage forms. Concerning the twelve GAC principles, a detailed comparison was performed to highlight the opportunities of each technique. FTIR-PLSR analysis showed superior performance as it allows for less solvent consumption, portability, less generated waste, short operating time, less operation cost, less energy consumption, and more operator safety and it is easily coupled with chemometric tools. Besides, FTIR is a direct analytical technique that can be used for the analysis of samples in all the physical forms (solid, liquid, and gas) without modifications.
Collapse
Affiliation(s)
- Khadiga M Kelani
- Analytical Chemistry Department, Faculty of Pharmacy, Cairo University, El-Kasr El-Aini Street, ET-11562 Cairo, Egypt
| | | | | | | | | |
Collapse
|
29
|
Locke A, Fitzgerald S, Mahadevan-Jansen A. Advances in Optical Detection of Human-Associated Pathogenic Bacteria. Molecules 2020; 25:E5256. [PMID: 33187331 PMCID: PMC7696695 DOI: 10.3390/molecules25225256] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2020] [Revised: 11/04/2020] [Accepted: 11/06/2020] [Indexed: 02/06/2023] Open
Abstract
Bacterial infection is a global burden that results in numerous hospital visits and deaths annually. The rise of multi-drug resistant bacteria has dramatically increased this burden. Therefore, there is a clinical need to detect and identify bacteria rapidly and accurately in their native state or a culture-free environment. Current diagnostic techniques lack speed and effectiveness in detecting bacteria that are culture-negative, as well as options for in vivo detection. The optical detection of bacteria offers the potential to overcome these obstacles by providing various platforms that can detect bacteria rapidly, with minimum sample preparation, and, in some cases, culture-free directly from patient fluids or even in vivo. These modalities include infrared, Raman, and fluorescence spectroscopy, along with optical coherence tomography, interference, polarization, and laser speckle. However, these techniques are not without their own set of limitations. This review summarizes the strengths and weaknesses of utilizing each of these optical tools for rapid bacteria detection and identification.
Collapse
Affiliation(s)
- Andrea Locke
- Vanderbilt Biophotonics Center, Nashville, TN 37232, USA; (A.L.); (S.F.)
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37232, USA
| | - Sean Fitzgerald
- Vanderbilt Biophotonics Center, Nashville, TN 37232, USA; (A.L.); (S.F.)
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37232, USA
| | - Anita Mahadevan-Jansen
- Vanderbilt Biophotonics Center, Nashville, TN 37232, USA; (A.L.); (S.F.)
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37232, USA
| |
Collapse
|
30
|
Stratifying Brain Tumour Histological Sub-Types: The Application of ATR-FTIR Serum Spectroscopy in Secondary Care. Cancers (Basel) 2020; 12:cancers12071710. [PMID: 32605100 PMCID: PMC7408619 DOI: 10.3390/cancers12071710] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2020] [Revised: 06/19/2020] [Accepted: 06/25/2020] [Indexed: 12/17/2022] Open
Abstract
Patients living with brain tumours have the highest average years of life lost of any cancer, ultimately reducing average life expectancy by 20 years. Diagnosis depends on brain imaging and most often confirmatory tissue biopsy for histology. The majority of patients experience non-specific symptoms, such as headache, and may be reviewed in primary care on multiple occasions before diagnosis is made. Sixty-two per cent of patients are diagnosed on brain imaging performed when they deteriorate and present to the emergency department. Histological diagnosis from invasive surgical biopsy is necessary prior to definitive treatment, because imaging techniques alone have difficulty in distinguishing between several types of brain cancer. However, surgery itself does not necessarily control tumour growth, and risks morbidity for the patient. Due to their similar features on brain scans, glioblastoma, primary central nervous system lymphoma and brain metastases have been known to cause radiological confusion. Non-invasive tests that support stratification of tumour subtype would enhance early personalisation of treatment selection and reduce the delay and risks associated with surgery for many patients. Techniques involving vibrational spectroscopy, such as attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy, have previously demonstrated analytical capabilities for cancer diagnostics. In this study, infrared spectra from 641 blood serum samples obtained from brain cancer and control patients have been collected. Firstly, we highlight the capability of ATR-FTIR to distinguish between healthy controls and brain cancer at sensitivities and specificities above 90%, before defining subtle differences in protein secondary structures between patient groups through Amide I deconvolution. We successfully differentiate several types of brain lesions (glioblastoma, meningioma, primary central nervous system lymphoma and metastasis) with balanced accuracies >80%. A reliable blood serum test capable of stratifying brain tumours in secondary care could potentially avoid surgery and speed up the time to definitive therapy, which would be of great value for both neurologists and patients.
Collapse
|
31
|
Paluszkiewicz C, Pięta E, Woźniak M, Piergies N, Koniewska A, Ścierski W, Misiołek M, Kwiatek WM. Saliva as a first-line diagnostic tool: A spectral challenge for identification of cancer biomarkers. J Mol Liq 2020. [DOI: 10.1016/j.molliq.2020.112961] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
|
32
|
Biofluid diagnostics by FTIR spectroscopy: A platform technology for cancer detection. Cancer Lett 2020; 477:122-130. [DOI: 10.1016/j.canlet.2020.02.020] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Revised: 01/31/2020] [Accepted: 02/14/2020] [Indexed: 12/19/2022]
|
33
|
Bel'skaya LV, Sarf EA, Solomatin DV. Age and Gender Characteristics of the Infrared Spectra of Normal Human Saliva. APPLIED SPECTROSCOPY 2020; 74:536-543. [PMID: 31617400 DOI: 10.1177/0003702819885958] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
The comparison of the characteristics of the infrared (IR) spectra of saliva of healthy volunteers was carried out based on gender and age. It is shown that statistically significant differences between male and female groups are observed for the absorption bands of proteins and lipids. At the same time, the absorbance of the bands assigned to proteins and nucleic acids is higher for males, whereas the absorbance of the bands assigned to lipids is higher in the group of females. It is established that the correlation relationships of the characteristics of the spectra and age are weakly expressed. Thus, when forming the criteria of the norm and pathology for saliva, it is necessary to take into account the gender of the subjects, while there are no strict requirements for taking into account age periodization. Nevertheless, the revealed patterns are valid only for the composition of the saliva of healthy volunteers, the extension of the results to groups of patients with various diseases, as well as other biological fluids, requires additional testing.
Collapse
Affiliation(s)
- Lyudmila V Bel'skaya
- Department of Biology and Biological Education, Omsk State Pedagogical University, Omsk, Russian Federation
| | - Elena A Sarf
- Department of Biology and Biological Education, Omsk State Pedagogical University, Omsk, Russian Federation
| | - Denis V Solomatin
- Department of Mathematics and Mathematics Teaching Methods, Omsk State Pedagogical University, Omsk, Russian Federation
| |
Collapse
|
34
|
Cameron JM, Butler HJ, Smith BR, Hegarty MG, Jenkinson MD, Syed K, Brennan PM, Ashton K, Dawson T, Palmer DS, Baker MJ. Developing infrared spectroscopic detection for stratifying brain tumour patients: glioblastoma multiforme vs. lymphoma. Analyst 2020; 144:6736-6750. [PMID: 31612875 DOI: 10.1039/c9an01731c] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Over a third of brain tumour patients visit their general practitioner more than five times prior to diagnosis in the UK, leading to 62% of patients being diagnosed as emergency presentations. Unfortunately, symptoms are non-specific to brain tumours, and the majority of these patients complain of headaches on multiple occasions before being referred to a neurologist. As there are currently no methods in place for the early detection of brain cancer, the affected patients' average life expectancy is reduced by 20 years. These statistics indicate that the current pathway is ineffective, and there is a vast need for a rapid diagnostic test. Attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy is sensitive to the hallmarks of cancer, as it analyses the full range of macromolecular classes. The combination of serum spectroscopy and advanced data analysis has previously been shown to rapidly and objectively distinguish brain tumour severity. Recently, a novel high-throughput ATR accessory has been developed, which could be cost-effective to the National Health Service in the UK, and valuable for clinical translation. In this study, 765 blood serum samples have been collected from healthy controls and patients diagnosed with various types of brain cancer, contributing to one of the largest spectroscopic studies to date. Three robust machine learning techniques - random forest, partial least squares-discriminant analysis and support vector machine - have all provided promising results. The novel high-throughput technology has been validated by separating brain cancer and non-cancer with balanced accuracies of 90% which is comparable to the traditional fixed diamond crystal methodology. Furthermore, the differentiation of brain tumour type could be useful for neurologists, as some are difficult to distinguish through medical imaging alone. For example, the highly aggressive glioblastoma multiforme and primary cerebral lymphoma can appear similar on magnetic resonance imaging (MRI) scans, thus are often misdiagnosed. Here, we report the ability of infrared spectroscopy to distinguish between glioblastoma and lymphoma patients, at a sensitivity and specificity of 90.1% and 86.3%, respectively. A reliable serum diagnostic test could avoid the need for surgery and speed up time to definitive chemotherapy and radiotherapy.
Collapse
Affiliation(s)
- James M Cameron
- WestCHEM, Department of Pure and Applied Chemistry, Technology and Innovation Centre, University of Strathclyde, 99 George St, Glasgow, G1 1RD, UK.
| | | | | | | | | | | | | | | | | | | | | |
Collapse
|
35
|
Butler HJ, Brennan PM, Cameron JM, Finlayson D, Hegarty MG, Jenkinson MD, Palmer DS, Smith BR, Baker MJ. Development of high-throughput ATR-FTIR technology for rapid triage of brain cancer. Nat Commun 2019; 10:4501. [PMID: 31594931 PMCID: PMC6783469 DOI: 10.1038/s41467-019-12527-5] [Citation(s) in RCA: 96] [Impact Index Per Article: 19.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2019] [Accepted: 09/16/2019] [Indexed: 12/22/2022] Open
Abstract
Non-specific symptoms, as well as the lack of a cost-effective test to triage patients in primary care, has resulted in increased time-to-diagnosis and a poor prognosis for brain cancer patients. A rapid, cost-effective, triage test could significantly improve this patient pathway. A blood test using attenuated total reflection (ATR)-Fourier transform infrared (FTIR) spectroscopy for the detection of brain cancer, alongside machine learning technology, is advancing towards clinical translation. However, whilst the methodology is simple and does not require extensive sample preparation, the throughput of such an approach is limited. Here we describe the development of instrumentation for the analysis of serum that is able to differentiate cancer and control patients at a sensitivity and specificity of 93.2% and 92.8%. Furthermore, preliminary data from the first prospective clinical validation study of its kind are presented, demonstrating how this innovative technology can triage patients and allow rapid access to imaging.
Collapse
Affiliation(s)
- Holly J Butler
- WestCHEM, Department of Pure and Applied Chemistry, University of Strathclyde, Technology and Innovation Centre, 99 George Street, Glasgow, G1 1RD, UK. .,ClinSpec Diagnostics Limited, University of Strathclyde, Technology and Innovation Centre, 99 George Street, Glasgow, G1 1RD, UK.
| | - Paul M Brennan
- Translational Neurosurgery, Department of Clinical Neurosciences, Western General Hospital, Edinburgh, EH4 2XU, UK
| | - James M Cameron
- WestCHEM, Department of Pure and Applied Chemistry, University of Strathclyde, Technology and Innovation Centre, 99 George Street, Glasgow, G1 1RD, UK
| | - Duncan Finlayson
- WestCHEM, Department of Pure and Applied Chemistry, University of Strathclyde, Technology and Innovation Centre, 99 George Street, Glasgow, G1 1RD, UK
| | - Mark G Hegarty
- ClinSpec Diagnostics Limited, University of Strathclyde, Technology and Innovation Centre, 99 George Street, Glasgow, G1 1RD, UK
| | - Michael D Jenkinson
- Institute of Translational Medicine, University of Liverpool & The Walton Centre NHS Foundation Trust, Lower Lane, Fazakerley, Liverpool, L9 7LJ, UK
| | - David S Palmer
- WestCHEM, Department of Pure and Applied Chemistry, University of Strathclyde, Technology and Innovation Centre, 99 George Street, Glasgow, G1 1RD, UK.,ClinSpec Diagnostics Limited, University of Strathclyde, Technology and Innovation Centre, 99 George Street, Glasgow, G1 1RD, UK
| | - Benjamin R Smith
- WestCHEM, Department of Pure and Applied Chemistry, University of Strathclyde, Technology and Innovation Centre, 99 George Street, Glasgow, G1 1RD, UK
| | - Matthew J Baker
- WestCHEM, Department of Pure and Applied Chemistry, University of Strathclyde, Technology and Innovation Centre, 99 George Street, Glasgow, G1 1RD, UK. .,ClinSpec Diagnostics Limited, University of Strathclyde, Technology and Innovation Centre, 99 George Street, Glasgow, G1 1RD, UK.
| |
Collapse
|