Article
Spectroscopy
Patryk Stec, Joanna Dudala, Aleksandra Wandzilak, Pawel Wrobel, Lukasz Chmura, Magdalena Szczerbowska-Boruchowska
Summary: Ovarian cancer is a deadly disease that is difficult to diagnose and treat, partly due to late diagnosis. In this study, infrared microspectroscopy was used to analyze the biomolecular composition of ovarian tissues. Paraffin-embedded preparations of tissues were used, but the paraffin absorbs infrared radiation, making it difficult to analyze the samples. Deparaffinization was performed before analysis, but the extent to which it affected the biomolecular composition was unclear. Results showed that deparaffinization led to changes in the composition, but classification of tissues based on FTIR measurements was still possible.
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
(2023)
Article
Oncology
Carlos A. Meza Ramirez, Helen Stringfellow, Raj Naik, Emma J. Crosbie, Maria Paraskevaidi, Ihtesham U. Rehman, Pierre Martin-Hirsch
Summary: This study explores the potential of a non-invasive test for early detection of endometrial cancer, utilizing urine samples analysis and infrared spectroscopy technology to identify and predict spectral biomarkers for cancer detection.
Article
Biochemical Research Methods
Panagiotis Giamougiannis, Camilo L. M. Morais, Brice Rodriguez, Nicholas J. Wood, Pierre L. Martin-Hirsch, Francis L. Martin
Summary: This study confirms the capacity of biofluids' ATR-FTIR spectroscopy (mainly blood serum) to diagnose ovarian cancer with high accuracy and demonstrates its potential in monitoring response to chemotherapy, which is reported for the first time. Serum was found to be the best biofluid for ovarian cancer detection, achieving 76% sensitivity and 98% specificity, while urine exhibited poor performance. The decrease in sensitivities for the NACT ovarian cancer group in plasma and serum indicates the potential of ATR-FTIR spectroscopy to identify chemotherapy-related spectral changes.
ANALYTICAL AND BIOANALYTICAL CHEMISTRY
(2021)
Article
Energy & Fuels
Chao Chen, Rui Liang, Shaige Xia, Donghao Hou, Bore Abdoulaye, Junyu Tao, Beibei Yan, Zhanjun Cheng, Guanyi Chen
Summary: This study proposes a fast characterization method for biodiesel using attenuated total reflection Fourier-transform infrared spectroscopy and machine learning models. The method achieved high accuracy and correlation in predicting the characteristics of biodiesel, such as unsaturated group content and ester content. The findings of this study could lead to a simple and efficient approach for characterizing biodiesel properties.
Article
Chemistry, Analytical
Camelia Berghian-Grosan, Ariana Raluca Hategan, Maria David, Dana Alina Magdas
Summary: Honey adulteration is a significant concern globally, and the use of artificial intelligence in food recognition models has shown promise in improving detection accuracy. This study proposes a new approach using ATR-FTIR spectroscopy and machine learning algorithms to detect colza honey addition in acacia honey and identify the presence of sunflower honey in linden samples. The developed models achieved an accuracy of 94.4% in detecting colza-acacia mixture and 90.7% in identifying linden-sunflower honey blend.
MICROCHEMICAL JOURNAL
(2023)
Article
Multidisciplinary Sciences
Helina Heino, Lassi Rieppo, Tuija Mannisto, Mikko J. Sillanpaa, Vesa Mantynen, Simo Saarakkala
Summary: ATR-FTIR spectroscopy coupled with machine learning-based PLS-DA was used to study the detection of SARS-CoV-2 from nasopharyngeal swab samples. The results indicate that the ATR-FTIR spectrum contains specific information for SARS-CoV-2 infection, but the diagnostic performance is moderate.
SCIENTIFIC REPORTS
(2022)
Article
Medicine, Legal
Xiangyan Zhang, Jiao Xiao, Fengqin Yang, Hongke Qu, Chengxin Ye, Sile Chen, Yadong Guo
Summary: This study aims to develop a rapid, sensitive, and non-destructive auxiliary approach for postmortem diagnosis of SCD by combining spectral features of blood samples and pathological changes, and constructing an SCD postmortem diagnosis model using artificial intelligence algorithms. Results showed that the SVM algorithm based on spectral biomarkers demonstrated the highest accuracy.
INTERNATIONAL JOURNAL OF LEGAL MEDICINE
(2023)
Article
Green & Sustainable Science & Technology
Chao Chen, Rui Liang, Yadong Ge, Jian Li, Beibei Yan, Zhanjun Cheng, Junyu Tao, Zhenyu Wang, Meng Li, Guanyi Chen
Summary: This study proposes a fast characterization method of bio-oil using attenuated total reflection flourier transformed infrared spectroscopy (ATR-FTIR) and machine learning models. The results show that principal component analysis (PCA) preprocessing can significantly improve the overall performance of the support vector regression (SVR) model for bio-oil characteristic prediction.
Article
Multidisciplinary Sciences
H. Lee, D. Lee, J. M. Seo
Summary: This study collected and analyzed paint from an actual site of ship collision, comparing paint traces of the damaged ship and the ship suspected to be responsible for the collision through various chemical analysis methods. The ship responsible for the collision could be identified by performing a comparative analysis of the extracted paint.
SCIENTIFIC REPORTS
(2021)
Article
Multidisciplinary Sciences
Rosario Javier-Astete, Jessenia Melo, Jorge Jimenez-Davalos, Gaston Zolla
Summary: This study validated a model for the classification of wood species and a universal model for the rapid determination of cellulose, hemicellulose, and lignin using FTIR spectroscopy coupled with chemometrics. The results showed that the full spectra can be used to differentiate different species and identify infrared peaks associated with cellulose, hemicellulose, and lignin. In addition, the full spectra helped build a three species universal model for quantifying the principal wood chemical components. Therefore, the study demonstrated that FTIR-ATR, together with chemometrics, is a reliable method for discriminating wood species and determining wood chemical composition.
SCIENTIFIC REPORTS
(2023)
Article
Chemistry, Analytical
Waseem Ahmed, Aneesh Vincent Veluthandath, David J. Rowe, Jens Madsen, Howard W. Clark, Anthony D. Postle, James S. Wilkinson, Ganapathy Senthil Murugan
Summary: The study demonstrated the use of ATR-FTIR combined with machine learning as a point-of-care diagnostic platform for nRDS, providing a method to detect and quantify biomarkers with an interpretable mid-infrared spectrum.
Article
Food Science & Technology
Isabel Cristina de Santana Alves Tolentino, Josane Cardim de Jesus, Daniele Gomes Conceicao, Rebeca Rodrigues Vieira Onelli, Lucas Caiafa Cardoso Reis, Leandro Soares Santos, Sibelli Passini Barbosa Ferra
Summary: Mid-infrared spectroscopy and chemometric techniques were used to verify the authenticity of commercial prato cheeses. Analysis of the samples showed that 16 commercial samples overlapped with mozzarella cheese and 4 overlapped with prato cheese. Discriminant methods yielded classification rates above 84%. These techniques efficiently differentiated and classified the samples, indicating that commercial samples were likely not authentic prato cheese.
INTERNATIONAL DAIRY JOURNAL
(2023)
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
Biochemical Research Methods
Shuyan Zhang, Swetha Vasudevan, Sonia Peng Hwee Tan, Malini Olivo
Summary: This paper proposes a novel approach for rapid breast cancer diagnosis using attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy. The technique allows direct analysis of tissue samples, saving time and resources compared to traditional methods. By analyzing the spectroscopic data with machine-learning models, accurate classification of cancerous and non-cancerous tissues can be achieved. The study demonstrates the potential of the proposed method for breast cancer diagnosis with a sensitivity of 74.2% and specificity of 78.3%.
JOURNAL OF BIOPHOTONICS
(2023)
Article
Environmental Sciences
Yu Xing, Jing Li, Jingjing Yang, Junyi Li, Weiyi Pang, Francis L. Martin, Li Xu
Summary: This study used spectrochemical techniques to investigate the cytotoxicity of nanoplastics with different surface charges in HepG2 cells. The results showed that all three types of nanoplastics caused biomolecular alterations in cells, affecting cellular lipids, proteins, amino acids, and genetic material. Surface modifications were found to lead to cellular biochemical changes and adverse biological effects, with PS-NH2 exhibiting higher toxicity compared to PS or PS-COOH.
ENVIRONMENTAL POLLUTION
(2023)
Article
Physics, Applied
B. Dekel, A. Katzir
APPLIED PHYSICS LETTERS
(2010)
Article
Oncology
Ayelet Zlotogorski-Hurvitz, Ben Zion Dekel, Dov Malonek, Ran Yahalom, Marilena Vered
JOURNAL OF CANCER RESEARCH AND CLINICAL ONCOLOGY
(2019)
Meeting Abstract
Oncology
Ilan Bruchim, Dov Malonek, Ben Zion Dekel, Renat Reens Carmel, Gabi Groisman, Mordechai Hallak
JOURNAL OF CLINICAL ONCOLOGY
(2019)
Article
Obstetrics & Gynecology
Nardin Aslih, Ben Zion Dekel, Dov Malonek, Medeia Michaeli, Diana Polotov, Einat Shalom-Paz
Summary: This study aims to investigate whether mid-infrared attenuated total reflection (MIR ATR) spectroscopy combined with machine learning methods can be used as an additional tool to predict embryo quality and IVF treatment outcomes. The results showed that MIR ATR technology can better select embryos based on the characteristics of absorbance peaks in the culture media and the differences in metabolite secretions. Machine learning techniques also offered a high pregnancy prediction value for day 3 embryos.
REPRODUCTIVE BIOMEDICINE ONLINE
(2023)
Meeting Abstract
Obstetrics & Gynecology
E. Shalom-Paz, A. Bilgory, N. Aslih, Y. Atzmon, Y. Shibli, D. Estrada, S. Haimovich, B. Z. Dekel, D. Malonek
HUMAN REPRODUCTION
(2021)
Meeting Abstract
Obstetrics & Gynecology
N. Aslih, E. Shalom-Paz, D. Molenik, B. Z. Dekel
HUMAN REPRODUCTION
(2021)
Meeting Abstract
Oncology
I. Bruchim, D. Malonekc, G. Groisman, R. Reens Carmel, M. Hallak, D. Ben Zion
INTERNATIONAL JOURNAL OF GYNECOLOGICAL CANCER
(2019)
Proceedings Paper
Computer Science, Artificial Intelligence
B. Dekel, A. Zilberman, N. Blaunstein, Y. Cohen, M. B. Sergeev, L. L. Varlamova, G. S. Polishchuk
INNOVATION IN MEDICINE AND HEALTHCARE 2016
(2016)
Article
Optics
BZ Dekel, A Katzir
Article
Optics
B Dekel, A Katzir
Article
Optics
B Dekel, Z Barkay, A Katzir
OPTICS COMMUNICATIONS
(2001)
Article
Spectroscopy
B. Z. Dekel, Y. Cohen, M. Feldman
Summary: This study aimed to investigate the spectroscopic characteristics of phenylalanine in the NIR spectral range as a preliminary step towards developing an in vivo method for determining phenylalanine in newborn babies' blood. The results of in vitro experiments showed absorption bands in the NIR spectral range assigned to overtones of C-H, N-H, and O-H, demonstrating the potential of NIR/VIS spectroscopy as an alternative to routine methods for determining phenylketonuria.
JOURNAL OF APPLIED SPECTROSCOPY
(2021)