Article
Spectroscopy
Siqi Gao, Yamin Lin, Xin Zhao, Jiamin Gao, Shusen Xie, Wei Gong, Yun Yu, Juqiang Lin
Summary: Surface-enhanced Raman spectroscopy (SERS) is an ultrasensitive, non-invasive, and rapid detection technology for cancer diagnosis. In this study, a novel blood serum analysis strategy using coffee ring effect-assisted label-free SERS was developed for cancer screening. By combining PLS-SVM algorithm with serum SERS detection, an ideal diagnostic accuracy of 100% could be achieved for differentiating cancers from the normal group.
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
(2022)
Article
Biochemistry & Molecular Biology
Qingxia Zhu, Xinhang Li, Dan Li, Feng Lu, Yunli Zhao, Yongfang Yuan
Summary: This study aimed to develop a procedure for detecting carbamazepine (CBZ) in serum using surface-enhanced Raman spectroscopy (SERS) with the assistance of the coffee-ring effect. Silver nanoparticles deposited onto silicon wafers were used as the SERS-active material. The detection procedure allowed for the fast determination of CBZ in serum samples within a concentration range of 2.5-40 μg/mL, matching the range of drug concentrations in the serum after oral medication. The developed method is anticipated to be a potential tool for monitoring other drug concentrations.
Article
Food Science & Technology
Cinthia de Carvalho Couto, Otniel Freitas-Silva, Edna Maria Morais Oliveira, Clara Sousa, Susana Casal
Summary: In this study, near-infrared (NIR) spectroscopy and chemometrics were successfully used to detect common adulterants in roasted ground arabica coffee. The technique could discriminate pure samples from adulterated ones, including single and multiple adulterations. Additionally, NIR spectroscopy showed potential for geographical discrimination of arabica coffees.
Article
Medical Laboratory Technology
Teresa Lapa, Ricardo N. M. J. Pascoa, Filipe Coimbra, Pedro S. Gomes
Summary: This study evaluated the effectiveness of mid-infrared spectroscopy in identifying the reticular form of OLP. The results showed that MIR spectroscopy was able to discriminate between OLP patients and controls. The findings suggest that MIR spectroscopy could be an innovative, non-invasive, low cost, and sensitive technique for identifying OLP.
CLINICA CHIMICA ACTA
(2022)
Review
Chemistry, Analytical
Sultan Aitekenov, Alisher Sultangaziyev, Perizat Abdirova, Lyailya Yussupova, Abduzhappar Gaipov, Zhandos Utegulov, Rostislav Bukasov
Summary: This review discusses the applications of infrared, Raman/SERS, and Brillouin spectroscopies in medical diagnostics and detection of biomarkers in biofluids. These optical sensing techniques are non-contact, noninvasive, rapid, accurate, label-free, and affordable. However, there are still challenges that need to be overcome for their widespread use in routine clinical diagnostics. The review also summarizes recent advancements and provides insights on the use of vibrational spectroscopy for medical diagnostics, including the detection of various health conditions. A critical comparison between SERS and FTIR methods reveals that SERS has higher sensitivity for biomarkers in biofluids, making it advantageous for the early detection of diseases such as cancer or viral infections.
CRITICAL REVIEWS IN ANALYTICAL CHEMISTRY
(2022)
Article
Chemistry, Analytical
Samantha H. Rutherford, Christopher D. M. Hutchison, Gregory M. Greetham, Anthony W. Parker, Alison Nordon, Matthew J. Baker, Neil T. Hunt
Summary: The study demonstrates that ultrafast 2D-IR spectroscopy can directly measure protein-drug binding in blood serum samples, enabling the detection and differentiation of drug-containing samples and providing structural insight and quantitative information on protein-drug binding.
ANALYTICAL CHEMISTRY
(2023)
Article
Chemistry, Multidisciplinary
Rene Breuch, Daniel Klein, Cassandra Moers, Eleni Siefke, Claudia Wickleder, Peter Kaul
Summary: Hydrophilic surface-enhanced Raman spectroscopy (SERS) substrates were prepared by coating aluminium plates with TiO2 and AuNPs, improving the distribution of AuNPs and enhancing the SERS signal. The morphology of the substrates improved the uniformity of particle distribution.
Article
Biochemical Research Methods
Panagiotis Giamougiannis, Camilo L. M. Morais, Rita Grabowska, Katherine M. Ashton, Nicholas J. Wood, Pierre L. Martin-Hirsch, Francis L. Martin
Summary: The study compared the performance of blood plasma, serum, and ascitic fluid in ovarian cancer detection using Raman microspectroscopy. Ascitic fluid showed the best class separation in both unsupervised and supervised discrimination approaches, with higher classification accuracies, sensitivities, and specificities compared to plasma or serum. The presence of collagen information in ascitic fluid was found to be responsible for distinguishing ovarian cancer samples, making it a potential diagnostic method for ovarian cancer.
ANALYTICAL AND BIOANALYTICAL CHEMISTRY
(2021)
Article
Chemistry, Analytical
Weiyi Pang, Yu Xing, Camilo L. M. Morais, Qiufeng Lao, Shengle Li, Zipeng Qiao, You Li, Maneesh N. Singh, Valerio G. Barauna, Francis L. Martin, Zhiyong Zhang
Summary: Diabetes mellitus (DM) is a metabolic disease that is of increasing global concern. The diagnosis and detection of DM and pre-diabetes are currently complicated, expensive, and time-consuming. In this study, a discriminant model was developed using attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy combined with principal component analysis linear discriminant analysis (PCA-LDA), which resulted in a high accuracy rate of 97% for diagnosing DM and pre-diabetes. This approach has significant clinical implications for intervention and risk reduction.
Article
Chemistry, Analytical
Valery Liamtsau, Guangliang Liu, Alexander N. Morozov, Alexander M. Mebel, Yong Cai
Summary: This study developed a theoretical framework to describe the CRE-driven separation process of small molecules and applied it to SERS analysis. By combining the CRE theory and the XDLVO theory, the classic chromatographic theory was adapted to CRE-driven nanochromatography.
Article
Chemistry, Analytical
Michel Rocha Baqueta, Patricia Valderrama, Enrique Anastacio Alves, Juliana Azevedo Lima Pallone, Federico Marini
Summary: Robusta Amazonico is a popular Amazonian coffee in Brazil, recently registered as a geographical indication. NIR spectroscopy is used to authenticate its production by indigenous people. Benchtop and portable NIR instruments were compared, with the best models providing accuracy rates of 96% and 92% respectively.
Article
Chemistry, Analytical
Michel Rocha Baqueta, Aline Coqueiro, Paulo Henrique Marco, Patricia Valderrama
Summary: The study successfully evaluated cup profiles in roasted and ground coffee blends at an industrial scale using handheld NIR spectroscopy combined with partial least squares with discriminant analysis. The model showed high sensitivity and specificity, making it a promising methodology for assisting coffee professionals in making decisions during cup evaluation tests.
Article
Chemistry, Physical
Malika Talantikite, Nadege Leray, Sylvie Durand, Celine Moreau, Bernard Cathala
Summary: The evaporation of a droplet containing a suspension of cellulose nanocrystals leads to the formation of a birefringent coffee ring pattern. Addition of a hydrosoluble biopolymer, arabinoxylan, results in the appearance of a Maltese cross pattern due to concentration increase and gelation of the CNC/AX mixture. A novel catalytic activity detection assay based on viscosity change was developed using this pattern, which is simple, fast, sensitive, and does not require complex analytical devices.
JOURNAL OF COLLOID AND INTERFACE SCIENCE
(2021)
Article
Food Science & Technology
Jamille Carvalho Souza, Celio Pasquini, Maria C. Hespanhol
Summary: The study evaluated two low-cost, miniaturized near-infrared (NIR) spectrophotometers in assessing several traits of commercial ground roasted coffee. The results show that these instruments have the potential to characterize coffee qualitatively and quantitatively, with a certain ability for discrimination and prediction.
Article
Chemistry, Physical
Naoto Ohtsubo, Syun Gohda, Kazuma Gotoh, Satoshi Sato, Yasuhiro Yamada
Summary: In this study, it was found that 1,5-naphthyridine had the highest percentage of pyridinic nitrogen (80%) and the highest pyridinic-nitrogen content (12.4 at%) after carbonization at 873 K among six relatively inexpensive precursors with pyridinic N and two-fused rings. Unlike precursors with three-or more-fused rings, 1,5-naphthyridine with two-fused rings retained C-H groups next to pyridinic nitrogen after carbonization, indicating different carbonization mechanisms.
Article
Instruments & Instrumentation
James M. Cameron, Christopher Rinaldi, Samantha H. Rutherford, Alexandra Sala, Ashton G. Theakstone, Matthew J. Baker
Summary: This review paper discusses the advancements in biomedical Raman and infrared spectroscopy, as well as the challenges towards utilizing these technologies as reliable clinical tools. Despite the potential shown in proof-of-concept studies, there are still barriers such as technical limitations, lack of understanding of clinical pathways, and funding applications that need to be addressed in order for vibrational spectroscopy to be clinically effective. The current outlook emphasizes the need for overcoming these hurdles in order to push spectroscopic technologies towards medical diagnostics and various clinical applications in the future.
APPLIED SPECTROSCOPY
(2022)
Article
Oncology
Alexandra Sala, James M. Cameron, Cerys A. Jenkins, Hugh Barr, Loren Christie, Justin J. A. Conn, Thomas R. Jeffry Evans, Dean A. Harris, David S. Palmer, Christopher Rinaldi, Ashton G. Theakstone, Matthew J. Baker
Summary: Pancreatic tumors are difficult to detect early, and current diagnostic tests are not specific. This study used infrared spectroscopy to distinguish pancreatic cancers from healthy and symptomatic controls, showing high detection rates. Simple, minimally invasive, and accurate approaches can aid in early detection of pancreatic cancer and improve patient prognosis and quality of life.
Article
Chemistry, Medicinal
Jonathan G. M. Conn, James W. Carter, Justin J. A. Conn, Vigneshwari Subramanian, Andrew Baxter, Ola Engkvist, Antonio Llinas, Ekaterina L. Ratkova, Stephen D. Pickett, James L. McDonagh, David S. Palmer
Summary: Accurate prediction of solubility is highly desirable in the field of chemical sciences. In 2019, the American Chemical Society organized a Solubility Challenge to evaluate the state of the art in this area. This article describes the development of two models submitted to the challenge, based on computationally inexpensive molecular descriptors and traditional machine learning algorithms. The performance of these models is compared to more advanced algorithms and larger training data sets, revealing potential areas for improvement in solubility prediction models.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2023)
Article
Oncology
James M. Cameron, Alexandra Sala, Georgios Antoniou, Paul M. Brennan, Holly J. Butler, Justin J. A. Conn, Siobhan Connal, Tom Curran, Mark G. Hegarty, Rose G. Mchardy, Daniel Orringer, David S. Palmer, Benjamin R. Smith, Matthew J. Baker
Summary: A rapid and low-cost blood test using Fourier transform infrared spectroscopy and machine-learning algorithms has been developed to detect multiple types of cancer reliably.
BRITISH JOURNAL OF CANCER
(2023)
Article
Chemistry, Analytical
Georgios Antoniou, Justin J. A. Conn, Benjamin R. Smith, Paul M. Brennan, Matthew J. Baker, David S. Palmer
Summary: Attenuated total reflectance (ATR)-Fourier transform infrared (FTIR) spectroscopy combined with machine learning techniques can be used for early detection of brain cancer in clinical practice. The transformation of the time domain signal to a frequency domain spectrum via a discrete Fourier transform is a key step in acquiring an IR spectrum. Applying an inverse Fourier transform to frequency domain data and utilizing Recurrent Neural Networks (RNNs), a deep learning model is developed to differentiate between brain cancer and control in 1438 patients. The best performing model achieves an AUC of 0.97 with sensitivity and specificity of 0.91, outperforming the model trained on frequency domain data.
Article
Chemistry, Physical
Daniel J. Fowles, David S. Palmer
Summary: Simultaneous calculation of entropies, enthalpies, and free energies has long been a challenge in computational chemistry. Recently, a new method called pyRISM-CNN was proposed, which combines the 1D-RISM solver with a deep learning-based free energy functional to predict solvation free energy. This method shows significant improvement in prediction accuracy compared to the standard 1D-RISM theory.
PHYSICAL CHEMISTRY CHEMICAL PHYSICS
(2023)
Meeting Abstract
Oncology
Alexandra Sala, James M. Cameron, Cerys A. Jenkins, Hugh Barr, Loren Christie, Justin J. Conn, Thomas (Jeff) R. Evans, Dean A. Harris, David S. Palmer, Christopher Rinaldi, Ashton G. Theakstone, Matthew J. Baker
Meeting Abstract
Oncology
Alexandra Sala, James M. Cameron, Cerys A. Jenkins, Hugh Barr, Loren Christie, Justin J. Conn, Thomas (Jeff) R. Evans, Dean A. Harris, David S. Palmer, Christopher Rinaldi, Ashton G. Theakstone, Matthew J. Baker
Meeting Abstract
Oncology
Alexandra Sala, Ashton G. Theakstone, Paul M. Brennan, Michael D. Jenkinson, Samantha J. Mills, Khaja Syed, Christopher Rinaldi, Yun Xu, Royston Goodacre, Holly J. Butler, David S. Palmer, Benjamin R. Smith, Matthew J. Baker
Meeting Abstract
Oncology
Alexandra Sala, Ashton G. Theakstone, Paul M. Brennan, Michael D. Jenkinson, Samantha J. Mills, Khaja Syed, Christopher Rinaldi, Yun Xu, Royston Goodacre, Holly J. Butler, David S. Palmer, Benjamin R. Smith, Matthew J. Baker
Meeting Abstract
Oncology
James M. Cameron, Alexandra Sala, Georgios Antoniou, Paul M. Brennan, Justin J. A. Conn, Siobhan Connal, David S. Palmer, Benjamin R. Smith, Matthew J. Baker
Meeting Abstract
Oncology
James M. Cameron, Paul M. Brennan, Georgios Antoniou, Holly J. Butler, Loren Christie, Justin J. A. Conn, Tom Curran, Ewan Gray, Mark G. Hegarty, Michael Jenkinson, Daniel Orringer, David S. Palmer, Alexandra Sala, Benjamin R. Smith, Matthew J. Baker
Meeting Abstract
Oncology
James M. Cameron, Alexandra Sala, Georgios Antoniou, Paul M. Brennan, Justin J. A. Conn, Siobhan Connal, David S. Palmer, Benjamin R. Smith, Matthew J. Baker
Meeting Abstract
Oncology
James M. Cameron, Paul M. Brennan, Georgios Antoniou, Holly J. Butler, Loren Christie, Justin J. A. Conn, Tom Curran, Ewan Gray, Mark G. Hegarty, Michael Jenkinson, Daniel Orringer, David S. Palmer, Alexandra Sala, Benjamin R. Smith, Matthew J. Baker
Article
Oncology
James M. Cameron, Paul M. Brennan, Georgios Antoniou, Holly J. Butler, Loren Christie, Justin J. A. Conn, Tom Curran, Ewan Gray, Mark G. Hegarty, Michael D. Jenkinson, Daniel Orringer, David S. Palmer, Alexandra Sala, Benjamin R. Smith, Matthew J. Baker
Summary: The simple and non-invasive blood test facilitates triage and radiographic diagnosis of brain tumor patients while providing reassurance to healthy patients. Minimizing time to diagnosis would allow for the earlier identification of brain tumor patients, enabling more effective and less morbid surgical and adjuvant care.
NEURO-ONCOLOGY ADVANCES
(2022)
