Review
Instruments & Instrumentation
Ricardo Fernandes dos Santos, Maria Paraskevaidi, Kassio M. G. Lima
Summary: One of the biggest challenges in Alzheimer's disease (AD) diagnosis is the development of high-performance and minimally invasive tools that can be used in real-time. Biospectroscopic techniques coupled with chemometrics have shown potential in identifying pathological changes in AD before symptoms appear.
APPLIED SPECTROSCOPY REVIEWS
(2023)
Article
Health Care Sciences & Services
Francis L. Martin, Camilo L. M. Morais, Andrew W. Dickinson, Tarek Saba, Thomas Bongers, Maneesh N. Singh, Danielle Bury
Summary: Saliva can be used as a liquid biopsy for screening lung cancer and prostate cancer. By analyzing the bioconstituents in saliva samples using infrared spectroscopy and principal component analysis, a highly accurate model can be built for the detection of these cancers in primary care settings.
JOURNAL OF PERSONALIZED MEDICINE
(2023)
Article
Spectroscopy
Taha Lilo, Camilo L. M. Morais, Katherine M. Ashton, Charles Davis, Timothy P. Dawson, Francis L. Martin, Jane Alder, Gareth Roberts, Arup Ray, Nihal Gurusinghe
Summary: Meningiomas, the most common benign brain tumors, are classified into different grades based on their growth rate and recurrence risk. Accurately determining the tumor grade is crucial for surgical outcomes and patient treatment. Researchers have developed a spectrochemical imaging technique called Raman hyperspectral imaging, which can effectively differentiate between grade I and grade II meningioma samples. This technique shows great potential for real-time assessment of meningioma grade during surgery.
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
(2022)
Article
Chemistry, Analytical
Haolan Yang, Liangying Bao, Yifei Liu, Shuting Luo, Fengyan Zhao, Guangyu Chen, Fang Liu
Summary: This study proposes a multi-dimensional analysis method utilizing Fourier-transform mid-infrared spectroscopy and diode-array near-infrared spectroscopy in combination with chemometric techniques, successfully identifying and quantifying salt-adulterated honeysuckle. Through the PLS-DA model, the authentication of different levels of salt adulteration in honeysuckle samples was achieved, with optimal PLS regression models obtained by synergy interval PLS and backward interval PLS algorithms.
MICROCHEMICAL JOURNAL
(2021)
Article
Automation & Control Systems
Nikolas Mateus Pereira de Souza, Brenda Hunter Machado, Licerio Vicente Padoin, Daniel Pra, Andre Poisl Fay, Mayara de Arruda Tomaz, Valeriano Antonio Corbellini, Alexandre Rieger
Summary: Attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy was used as a rapid and non-invasive bioscreening tool for breast cancer detection in blood plasma. Three PLS-ANNDA models were created to differentiate cancer from non-cancer subjects, group molecular subtypes, and individually discriminate subtypes. Significant spectral differences were found in four intervals for molecular subtypes and control. The peak at 1739 cm-1 was the most sensitive for breast cancer screening. ATR-FTIR coupled with PLS-ANNDA shows promise as a screening option for breast cancer.
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
(2023)
Article
Food Science & Technology
Yeison Fernando Barrios-Rodriguez, Cristhian Andres Rojas Reyes, Joan Sebastian Triana Campos, Joel Giron-Hernandez, Juan Rodriguez-Gamir
Summary: This study complemented the sensory evaluation of Specialty coffee using FTIR and chemometrics, which effectively discriminated and identified different post-harvest treatments for green beans, medium roast coffee, and dark roast coffee.
LWT-FOOD SCIENCE AND TECHNOLOGY
(2021)
Article
Food Science & Technology
Ali Ali Redha, Faye Langston, Geoffrey R. Nash, John R. Bows, Luciana Torquati, Michael J. Gidley, Daniel Cozzolino
Summary: This study evaluates the application of mid-infrared spectroscopy for the determination of glucosinolates (GSLs) in commercial broccoli. The results showed that MIR spectroscopy can be used to determine some specific GSLs in broccoli. The models developed demonstrated that the variations in broccoli composition can influence the cross-validation models for GSLs.
INTERNATIONAL JOURNAL OF FOOD SCIENCE AND TECHNOLOGY
(2023)
Article
Polymer Science
Maria Laura Tummino, Christoforos Chrimatopoulos, Maddalena Bertolla, Cinzia Tonetti, Vasilios Sakkas
Summary: This study proposes a simple approach combining infrared spectroscopy with chemometrics for the recognition of polyamide 6.9 samples. Chemometric tools, including PCA and PLS-DA, were used to create a predictive model that could assess the polyamide type of unknown samples. The proposed hybrid methodology showed a great classification accuracy of 88.89% for unknown samples.
Article
Food Science & Technology
Yao Ma, Lu Tian, Xiaona Wang, Chen Huang, Mingjing Tian, Anzhi Wei
Summary: This study reveals the variations in chemical components and contents of different prickly ash species from different plantations, as well as the dominating alkylamides in prickly ash pericarps. It also identifies ZP-amide D as a potential indicator to distinguish prickly ash species and determines the key factors affecting pericarp alkylamide profiling, such as longitude and aluminum content in soils.
Article
Biochemistry & Molecular Biology
Ali Khorramifar, Mansour Rasekh, Hamed Karami, James A. Covington, Sayed M. Derakhshani, Jose Ramos, Marek Gancarz
Summary: This study investigated five potato varieties using an electronic nose and chemometric methods, measuring various parameters and establishing regression models. The results indicated specific relationships among different potato varieties, sugar, and carbohydrates. The accuracy in predicting sugar and carbohydrates varied among different potato varieties.
Review
Food Science & Technology
Huiwen Yu, Lili Guo, Mourad Kharbach, Wenjie Han
Summary: NIRS is a fast and powerful analytical tool in the food industry, with multi-way analysis showing potential for solving complex data problems. The combination of multi-way analysis with NIRS in the food industry is expected to turn data into operational knowledge and improve the reliability of food analyses.
Review
Plant Sciences
Alonso Zavafer, Marilyn C. Ball
Summary: Raman spectroscopy is a non-invasive technique that enables the chemical characterization of plant material without destroying it. It allows for the analysis of the chemical composition of plants at different scales and offers opportunities for studying plant physiology.
FUNCTIONAL PLANT BIOLOGY
(2023)
Article
Chemistry, Applied
Taiz Alana Minetto, Beatriz Denardi Franca, Gabriel da Silva Dariz, Emiliano Amarante Veiga, Alessandro Cazonatto Galvao, Weber da Silva Robazza
Summary: This study demonstrates the applicability of electrochemical impedance spectroscopy in identifying urea adulteration in milk, and provides a specific method for its application.
Article
Food Science & Technology
Qiao Pei, Yongxiang Liu, Shaobing Peng
Summary: The fatty acid composition in walnut kernels can be used to distinguish different walnut varieties and quality levels, providing important information for quality assessments and detection of possible adulterations in the market.
Article
Spectroscopy
Le Wang, Xiuhuan Wang, Xiaoyun Liu, Yu Wang, Xueyang Ren, Ying Dong, Ruolan Song, Jiamu Ma, Qiqi Fan, Jing Wei, AXiang Yu, Lanzhen Zhang, Gaimei She
Summary: NIR spectroscopy combined with chemometrics tools was used for fast discrimination and quantification of Curcumae Radix from four botanical origins. HPLC was employed to develop a method for simultaneous determination of six bioactive compounds in Curcumae Radix. A support vector machine regression (SVMR) model successfully predicted the content of germacrone.
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
(2021)
Article
Agriculture, Multidisciplinary
Thiago Feliph Silva Fernandes, Raissa Vanessa de Oliveira Silva, Daniel Lucas Dantas de Freitas, Alex Guimaraes Sanches, Maryelle Barros da Silva, Luis Carlos Cunha Junior, Kassio Gomes de Lima, Gustavo Henrique de Almeida Teixeira
Summary: This study verifies the feasibility of using near infrared spectroscopy as a non-destructive method to determine the sex types in papaya trees. By collecting spectra from seeds and leaves, it was possible to accurately determine the sex types using multivariate techniques.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2022)
Article
Multidisciplinary Sciences
Daniel L. D. Freitas, Ana F. S. Peres, Lidiane G. Silva, Joao V. M. Mariz, Marcos G. Santos, Rayanne S. P. Morais, Camilo L. M. Morais, Francis L. Martin, Daniel A. Pascoal, Juliana D. de A. S. Camargo, Janaina C. O. Crispim, Kassio M. G. Lima
Summary: The prevention of mother-to-child transmission programs in Brazil have seen success, as access to antiretroviral therapy during pregnancy has led to a reduction in new infections among children. By utilizing near-infrared spectroscopy, pregnant women with and without HIV infection can be quickly and accurately differentiated, offering a new perspective on investigating vertical transmission and providing a potential low-cost screening tool for fast HIV detection.
SCIENTIFIC REPORTS
(2021)
Article
Multidisciplinary Sciences
Marcelo V. S. Alves, Lanaia I. L. Maciel, Ruver R. F. Ramalho, Leomir A. S. Lima, Boniek G. Vaz, Camilo L. M. Morais, Joao O. S. Passos, Rodrigo Pegado, Kassio M. G. Lima
Summary: A proposed analytical method using mass spectrometry for detecting fibromyalgia individuals demonstrated 100% accuracy in sample prediction through exploratory and supervised analysis algorithms, making it a simple, reliable and fast tool for clinical diagnosis of Fibromyalgia.
SCIENTIFIC REPORTS
(2021)
Article
Medicine, General & Internal
Alexandros Laios, Raissa Vanessa De Oliveira Silva, Daniel Lucas Dantas De Freitas, Yong Sheng Tan, Gwendolyn Saalmink, Albina Zubayraeva, Racheal Johnson, Angelika Kaufmann, Mohammed Otify, Richard Hutson, Amudha Thangavelu, Tim Broadhead, David Nugent, Georgios Theophilou, Kassio Michell Gomes de Lima, Diederick De Jong
Summary: Machine Learning algorithms were utilized to develop a predictive score for CCU admission in patients with advanced stage HGSOC. Linear and quadratic discriminant ML methods showed higher prediction accuracies compared to logistic regression. Pre-treatment albumin and other intra-operative factors were identified as significant prediction features.
JOURNAL OF CLINICAL MEDICINE
(2022)
Article
Biochemistry & Molecular Biology
Adam D. Morris, Daniel L. D. Freitas, Kassio M. G. Lima, Lauren Floyd, Mark E. Brady, Ajay P. Dhaygude, Anthony W. Rowbottom, Francis L. Martin
Summary: This study evaluated the application of machine learning and Raman spectroscopy for the automated computational detection of disease activity in ANCA-associated glomerulonephritis. The results showed that spectral data from tissue samples were able to accurately discriminate disease activity, while corresponding spectrochemical changes in paired urine samples were limited.
Article
Chemistry, Applied
Anne B. F. Camara, Keverson G. De Oliveira, Marfran C. D. Santos, Ramoni R. S. De Lima, Kassio M. G. De lima, Luciene S. De Carvalho
Summary: The feasibility of infrared spectroscopy combined with chemometrics for predicting the antioxidant activity of pomegranate and clove extracts was evaluated in this study. The results showed that this method achieved good accuracy and low residuals compared to the standard DPPH method. The MCR-ALS combined with NIR data was particularly effective, with high R2 values and low RMSEP. This technique also allowed for the recovery of pure spectral profiles and identification of interferents, making it a valuable tool for the food industry.
Article
Parasitology
Marfran C. D. Santos, Jorge L. S. Viana, Joelma D. Monteiro, Renato C. M. Freire, Daniel L. D. Freitas, Ingrid M. Camara, Gigliane J. S. da Silva, Renata A. Gama, Joselio M. G. Araujo, Kassio M. G. Lima
Summary: Entomological surveillance is one of the most important steps in preventing arboviruses. This study used near infrared (NIR) and mid infrared (MIR) spectra to build chemometric models that can differentiate between dengue-infected and non-infected Aedes aegypti mosquitoes. The models based on NIR spectra and Genetic Algorithm (GA) achieved better classification results. The findings have important applications in the field of entomological surveillance and prevention of dengue vectors.
Article
Parasitology
Hellyda K. T. de Andrade Silva, Taciano M. Barbosa, Marfran C. D. Santos, Lidiane G. Silva, Leomir A. S. de Lima, Camilo L. M. Morais, Tatiana C. Bicudo, Renata A. Gama, Kassio M. G. Lima
Summary: This study evaluated the use of near infrared spectroscopy (NIRS) and chemometric methods to separate fly specimens into taxonomic categories and understand their taxonomic relationship. The results showed that NIRS is efficient in identifying the family and genera of flies, providing quick evidence for species identification.
Article
Biochemical Research Methods
Anne B. F. Camara, Wellington J. O. da Silva, Heloise O. M. A. Moura, Natanny K. N. Silva, Kassio M. G. de Lima, Luciene S. de Carvalho
Summary: This research successfully detected and quantified the contamination of kerosene solvent in private aircraft jet fuel using a chemometric methodology combined with spectroscopic techniques, and developed a fast, low-cost, and efficient process for quality control.
ANALYTICAL AND BIOANALYTICAL CHEMISTRY
(2022)
Article
Parasitology
Hellyda K. T. de Andrade Silva, Taciano M. Barbosa, Marfran C. D. Santos, Jessica T. Jales, Antonio M. U. de Araujo, Camilo L. M. Morais, Leomir A. S. de Lima, Tatiana C. Bicudo, Renata A. Gama, Pablo Alves Marinho, Kassio M. G. Lima
Summary: The study used attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy to detect toxic substances in fly larvae from decomposing carcasses, which can assist criminal experts in determining the cause of death in suspected poisoning cases.
Review
Instruments & Instrumentation
Ricardo Fernandes dos Santos, Maria Paraskevaidi, Kassio M. G. Lima
Summary: One of the biggest challenges in Alzheimer's disease (AD) diagnosis is the development of high-performance and minimally invasive tools that can be used in real-time. Biospectroscopic techniques coupled with chemometrics have shown potential in identifying pathological changes in AD before symptoms appear.
APPLIED SPECTROSCOPY REVIEWS
(2023)
Article
Multidisciplinary Sciences
Tales Gomes da Silva, Camilo L. M. Morais, Marfran C. D. Santos, Leomir A. S. de Lima, Raysa Vanessa de Medeiros Freitas, Ricardo Oliveira Guerra, Kassio M. G. Lima
Summary: This study used mid-infrared spectroscopy combined with chemometric techniques to identify osteosarcopenia based on blood serum samples. The results showed that the infrared spectroscopy of blood samples has the potential to identify osteosarcopenia in a simple, fast, and objective way.
SCIENTIFIC REPORTS
(2023)
Article
Multidisciplinary Sciences
Marcelo V. S. Alves, Lanaia I. L. Maciel, Joao O. S. Passos, Camilo L. M. Morais, Marfran C. D. dos Santos, Leomir A. S. Lima, Boniek G. Vaz, Rodrigo Pegado, Kassio M. G. Lima
Summary: This study chemically analyzed blood plasma samples from patients with and without fibromyalgia, combined with symptoms used in the diagnosis of this disease. Spectral data were organized into datasets and submitted to multivariate classification, resulting in good discrimination between controls and fibromyalgia samples. The results confirmed the technique as a good analytical tool for fibromyalgia detection and provided theoretical support for further studies on fibromyalgia diagnosis.
SCIENTIFIC REPORTS
(2023)
Article
Oncology
Alexandros Laios, Daniel Lucas Dantas De Freitas, Gwendolyn Saalmink, Yong Sheng Tan, Racheal Johnson, Albina Zubayraeva, Sarika Munot, Richard Hutson, Amudha Thangavelu, Tim Broadhead, David Nugent, Evangelos Kalampokis, Kassio Michell Gomes de Lima, Georgios Theophilou, Diederick De Jong
Summary: This study developed a novel predictive LOS score based on artificial intelligence for advanced-stage high-grade serous ovarian cancer patients following cytoreductive surgery. By using machine learning and deep learning methods, key factors affecting LOS were accurately identified.
Article
Multidisciplinary Sciences
Ricardo Fernandes dos Santos, Maria Paraskevaidi, David M. A. Mann, David Allsop, Marfran C. D. Santos, Camilo L. M. Morais, Kassio M. G. Lima
Summary: This study utilizes fluorescence spectroscopy and machine learning to diagnose Alzheimer's disease (AD) using blood plasma samples. The classification models show satisfactory results, indicating the potential of a rapid, low-cost, and minimally invasive blood-based AD diagnosis method.
SCIENTIFIC REPORTS
(2022)
