Article
Chemistry, Analytical
Guangyu Liu, Yujuan Hua, Ronda Gras, Jim Luong
Summary: An analytical strategy utilizing discrete frequency infrared imaging technique was developed to improve sample throughput in microplastic analysis. The concept demonstration study achieved high identification rates with a reduced scanning area, demonstrating the potential of this technique to enhance sample throughput.
ANALYTICAL CHEMISTRY
(2022)
Article
Instruments & Instrumentation
Qi Cheng, Yongzheng Zhu, Kaifei Deng, Zhiqiang Qin, Jianhua Zhang, Ji Zhang, Ping Huang, Changwu Wan
Summary: The diagnosis of pulmonary fat embolism is important in forensic medicine, but conventional histological analysis has limitations. This study developed an infrared imaging method based on unlabeled tissue sections to identify pulmonary fat emboli.
APPLIED SPECTROSCOPY
(2022)
Article
Instruments & Instrumentation
Saumya Tiwari, Kianoush Falahkheirkhah, Georgina Cheng, Rohit Bhargava
Summary: This study aims to assess the tumor grade of colorectal cancer using FT-IR imaging. A deep learning classifier was developed to estimate the tumor grade based on IR absorption, and the effectiveness of this method was validated on an independent cohort. The study demonstrates that combining molecular information from FT-IR imaging with morphometry could lead to the development of clinically relevant grade prediction models.
APPLIED SPECTROSCOPY
(2022)
Article
Automation & Control Systems
Carmen Bedia, Angels Sierra, Roma Tauler
Summary: Chemical imaging aims to characterize molecular patterns in tissues or surfaces, providing valuable insights in biomedicine. A new chemometrics approach was proposed for simultaneous multimodal chemical imaging analysis, revealing interesting patterns in tissue and potential new insights into drug sensitivity. The study utilized spectral imaging techniques and multivariate curve resolution to extract high-resolution chemical information from different tissue samples, demonstrating the power of this approach in analyzing complex spectral data sets.
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
(2021)
Article
Chemistry, Applied
Renata Rozylo, Monika Szymanska-Chargot, Urszula Gawlik-Dziki, Dariusz Dziki
Summary: The present study successfully prepared blue colored powders from cornflower petals through low temperature aqueous extraction and freeze-drying microencapsulation with 10% stabilizer mixture. The addition of 2% guar gum to maltodextrin was found to be the most optimal, significantly increasing process efficiency. The blue powders exhibited high antioxidant activity and total phenolic content.
Article
Chemistry, Physical
Amine Ouaket, Anas Chraka, Ihssane Raissouni, Mohamed Amin El Amrani, Mohamed Berrada, Noureddine Knouzi
Summary: In this study, the molecule C1 was synthesized and its structural properties, reactivity properties, and antioxidant activity were investigated. The results showed agreement between experimental and computational data.
JOURNAL OF MOLECULAR STRUCTURE
(2022)
Article
Instruments & Instrumentation
Jingjing Xia, Weixin Xu, Yanjie Li, Gaowei Li, Xiangyun Wang, Yanmei Xiong, Shungeng Min
Summary: The public concern and increasing awareness of pesticide quality and authenticity has led to the development of a novel strategy combining FT-IR analysis and rapid authentication of pesticide. A pesticide IR spectral database including 604 pesticide standards was established. A pre-treatment method that can eliminate the negative effect of pesticide formulation on similarity estimation was proposed. The proposed strategy resulted in a 90% accuracy rate and a 3.33% error rate for pesticide samples.
INFRARED PHYSICS & TECHNOLOGY
(2022)
Article
Chemistry, Physical
S. Selvakumari, C. Venkataraju, S. Muthu, Ahmad Irfan, A. Saral
Summary: In this study, the upgraded geometrical structure, electronic and vibrational features of 5-chloro-2-hydroxypyridine were investigated using the B3LYP method with 6-311++G (d, p) basis set. Various molecular properties such as FT-IR and FT-Raman spectra, interaction energy, and electron density were analyzed. Additionally, drug likeness, environmental toxicity properties, and molecular docking were conducted to assess the compound's properties.
JOURNAL OF MOLECULAR LIQUIDS
(2021)
Article
Chemistry, Physical
K. L. Andrew Chan, Anton S. Shalygin, Oleg N. Martyanov, Tom Welton, Sergei G. Kazarian
Summary: High throughput macro ATR-FTIR spectroscopic imaging was used for in situ characterization of 14 ionic liquids under controlled environments. The study found that the structure of the cation and anion in the ionic liquids significantly influenced the absorption of toluene and water, providing valuable insights for the application of ionic liquids.
JOURNAL OF MOLECULAR LIQUIDS
(2021)
Article
Medicine, Research & Experimental
Sonja Koivukoski, Umair Khan, Pekka Ruusuvuori, Leena Latonen
Summary: Tissue structures, phenotypes, and pathology are investigated using histology, but chemical staining has drawbacks. This study explores unstained tissue imaging for virtual staining, showing that thinner sections perform better. The study suggests that whole slide unstained microscopy can be a fast and feasible approach for virtual staining while preserving the tissue for subsequent use.
LABORATORY INVESTIGATION
(2023)
Article
Chemistry, Physical
R. Bhavani, N. Kanagathara, M. K. Marchewka, J. Janczak
Summary: The current research investigates the structural and spectroscopic characterization of the products formed in the aqueous solution of hydrazine and maleic acid. Both experimental and theoretical methods are used to analyze the structure and vibrational spectra. The study also explores the molecule's charge transfer and nonlinear attributes.
JOURNAL OF MOLECULAR STRUCTURE
(2023)
Article
Spectroscopy
Elisa Fardelli, Annalisa D'Arco, Stefano Lupi, Daniela Billi, Ralf Moeller, Mariangela Cestelli Guidi
Summary: In recent decades, Mars has been extensively studied as a potential host for life through on-site missions and observations. Space Agencies have conducted experiments on living organisms to understand their behavior in extraterrestrial conditions and to develop techniques for identifying biosignatures remotely. This study focused on the radioresistant cyanobacterium Chroococcidiopsis, investigating its response to radiation stress using Raman spectroscopy, Fourier Transform InfraRed (FT-IR) and Terahertz Time Domain spectroscopy (THz-TDs), which demonstrated the suitability of these techniques for future space missions.
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
(2023)
Article
Chemistry, Physical
A. Ram Kumar, S. Selvaraj, K. S. Jayaprakash, S. Gunasekaran, S. Kumaresan, J. Devanathan, K. A. Selvam, L. Ramadass, M. Mani, P. Rajkumar
Summary: The spectroscopic properties of syringaldehyde were studied using FT IR, FT Raman, and NMR techniques, as well as high-level quantum chemical calculations. The molecular properties of syringaldehyde were investigated to confirm its structure, and both experimental and theoretical findings were in complete agreement.
JOURNAL OF MOLECULAR STRUCTURE
(2021)
Article
Chemistry, Physical
M. Sathish, L. Rajasekaran, D. Shanthi, N. Kanagathara, S. Sarala, S. Muthu
Summary: The study utilized quantum mechanical calculations to determine the structural and spectroscopic parameters of the Indole-3-carboxylic acid (I3CA) molecule, revealing its antimicrobial and anticancer properties.
JOURNAL OF MOLECULAR STRUCTURE
(2021)
Article
Chemistry, Physical
N. Kanagathara, F. MaryAnjalin, V. Ragavendran, D. Dhanasekaran, R. Usha, R. Gowri Shankar Rao, M. K. Marchewka
Summary: This study investigated the structure and properties of aniline with arsenic acid molecular complex, revealing charge transfer and intermolecular interactions. Various analyses and calculations were performed on the compound, laying a foundation for further research.
JOURNAL OF MOLECULAR STRUCTURE
(2021)
Article
Oncology
Sepideh Azarianpour, German Corredor, Kaustav Bera, Patrick Leo, Pingfu Fu, Paula Toro, Amy Joehlin-Price, Mojgan Mokhtari, Haider Mahdi, Anant Madabhushi
Summary: This study presents a computational approach for characterizing the architecture and interplay of tumor-infiltrating lymphocytes (TILs) in gynecological cancer. The results show that the computed features are prognostic in different treatment types and are closely associated with central biological processes that impact tumor progression.
JOURNAL FOR IMMUNOTHERAPY OF CANCER
(2022)
Article
Gastroenterology & Hepatology
Prathyush Chirra, Anamay Sharma, Kaustav Bera, H. Matthew Cohn, Jacob A. Kurowski, Katelin Amann, Marco-Jose Rivero, Anant Madabhushi, Cheng Lu, Rajmohan Paspulati, Sharon L. Stein, Jeffrey A. Katz, Satish E. Viswanath, Maneesh Dave
Summary: Radiomic features extracted from magnetic resonance enterography are associated with the need for surgery in Crohn's disease patients at risk of complications, and when combined with clinical variables and radiological assessment, they can accurately predict the time to surgery.
INFLAMMATORY BOWEL DISEASES
(2023)
Article
Oncology
Shayan Monabbati, Patrick Leo, Kaustav Bera, Claire W. Michael, Behtash G. Nezami, Aparna Harbhajanka, Anant Madabhushi
Summary: This study used computational image analysis to predict the presence of pancreatic and biliary tract adenocarcinoma on digitized brush cytology specimens. By extracting nuclear morphological and texture features and training machine learning classifiers, the researchers successfully improved the sensitivity and specificity of diagnosis.
Article
Medicine, Research & Experimental
Kianoush Falahkheirkhah, Saumya Tiwari, Kevin Yeh, Sounak Gupta, Loren Herrera-Hernandez, Michael R. McCarthy, Rafael E. Jimenez, John C. Cheville, Rohit Bhargava
Summary: A pathologist's examination of tissue on glass slides is the gold standard for tissue diagnostics, but obtaining expert-level annotated images is expensive. This study presents a generative adversarial network model that synthesizes pathology images, which performed similarly to real data. Furthermore, the ability for a user to generate deepfake histologic images using a simple markup of sematic labels is demonstrated.
LABORATORY INVESTIGATION
(2023)
Article
Computer Science, Artificial Intelligence
Yufei Zhou, Can Koyuncu, Cheng Lu, Rainer Grobholz, Ian Katz, Anant Madabhushi, Andrew Janowczyk
Summary: Deep learning performs well in computational pathology tasks but struggles with domain shift on whole slide images generated at external test sites. To address this, researchers propose using off-target organs from the test site for calibration, effectively mitigating the domain shift and improving the robustness of the model for skin cancer classification.
MEDICAL IMAGE ANALYSIS
(2023)
Article
Oncology
Robert Serafin, Can Koyuncu, Weisi Xie, Hongyi Huang, Adam K. Glaser, Nicholas P. Reder, Andrew Janowczyk, Lawrence D. True, Anant Madabhushi, Jonathan T. C. Liu
Summary: Previous studies have shown that computational analysis of 2D histology images can improve prognostication of prostate cancer outcomes. This study expands on previous work by exploring the prognostic value of 3D shape-based nuclear features in prostate cancer. The results suggest that these features are associated with cancer aggressiveness and could be valuable for decision-support tools.
JOURNAL OF PATHOLOGY
(2023)
Article
Chemistry, Multidisciplinary
Jian Wang, Necip B. Uner, Scott Edwin Dubowsky, Matthew P. Confer, Rohit Bhargava, Yunyan Sun, Yuting Zhou, R. Mohan Sankaran, Jeffrey S. Moore
Summary: The formation of carbon-carbon bonds by pinacol coupling of aldehydes and ketones can be achieved using solvated electrons generated via a plasma-liquid process. Selectivity over the competing reduction to the alcohol requires careful control over mass transport. The generality of this method is demonstrated with various substrates, and a reaction-diffusion model and ab initio calculations provide insights into the mechanism. This study opens the possibility of a metal-free, electrically-powered, sustainable method for reductive organic reactions.
JOURNAL OF THE AMERICAN CHEMICAL SOCIETY
(2023)
Article
Chemistry, Analytical
Sudipta S. Mukherjee, Rohit Bhargava
Summary: Infrared (IR) spectroscopic imaging provides spatially resolved molecular absorption spectra, and this study introduces a fast and reliable method based on a phasor representation of spectra. The method is applicable for rapid data exploration and analysis of IR imaging data, and shows potential in biomedical tissue imaging.
ANALYTICAL CHEMISTRY
(2023)
Review
Oncology
Jeppe Thagaard, Glenn Broeckx, David B. Page, Chowdhury Arif Jahangir, Sara Verbandt, Zuzana Kos, Rajarsi Gupta, Reena Khiroya, Khalid Abduljabbar, Gabriela Acosta Haab, Balazs Acs, Guray Akturk, Jonas S. Almeida, Isabel Alvarado-Cabrero, Mohamed Amgad, Farid Azmoudeh-Ardalan, Sunil Badve, Nurkhairul Bariyah Baharun, Eva Balslev, Enrique R. Bellolio, Vydehi Bheemaraju, Kim R. M. Blenman, Luciana Botinelly Mendonca Fujimoto, Najat Bouchmaa, Octavio Burgues, Alexandros Chardas, Maggie U. Cheang, Francesco Ciompi, Lee A. D. Cooper, An Coosemans, German Corredor, Anders B. Dahl, Flavio Luis Dantas Portela, Frederik Deman, Sandra Demaria, Johan Dore Hansen, Sarah N. Dudgeon, Thomas Ebstrup, Mahmoud Elghazawy, Claudio Fernandez-Martin, Stephen B. Fox, William M. Gallagher, Jennifer M. Giltnane, Sacha Gnjatic, Paula Gonzalez-Ericsson, Anita Grigoriadis, Niels Halama, Matthew G. Hanna, Aparna Harbhajanka, Steven N. Hart, Johan Hartman, Soren Hauberg, Stephen Hewitt, Akira Hida, Hugo M. Horlings, Zaheed Husain, Evangelos Hytopoulos, Sheeba Irshad, Emiel A. M. Janssen, Mohamed Kahila, Tatsuki R. Kataoka, Kosuke Kawaguchi, Durga Kharidehal, Andrey Khramtsov, Umay Kiraz, Pawan Kirtani, Liudmila L. Kodach, Konstanty Korski, Aniko Kovacs, Anne-Vibeke Laenkholm, Corinna Lang-Schwarz, Denis Larsimont, Jochen K. Lennerz, Marvin Lerousseau, Xiaoxian Li, Amy Ly, Anant Madabhushi, Sai K. Maley, Vidya Manur Narasimhamurthy, Douglas K. Marks, Elizabeth S. McDonald, Ravi Mehrotra, Stefan Michiels, Fayyaz ul Amir Afsar Minhas, Shachi Mittal, David A. Moore, Shamim Mushtaq, Hussain Nighat, Thomas Papathomas, Frederique Penault-Llorca, Rashindrie D. Perera, Christopher J. Pinard, Juan Carlos Pinto-Cardenas, Giancarlo Pruneri, Lajos Pusztai, Arman Rahman, Nasir Mahmood Rajpoot, Bernardo Leon Rapoport, Tilman T. Rau, Jorge S. Reis-Filho, Joana M. Ribeiro, David Rimm, Anne Roslind, Anne Vincent-Salomon, Manuel Salto-Tellez, Joel Saltz, Shahin Sayed, Ely Scott, Kalliopi P. Siziopikou, Christos Sotiriou, Albrecht Stenzinger, Maher A. Sughayer, Daniel Sur, Susan Fineberg, Fraser Symmans, Sunao Tanaka, Timothy Taxter, Sabine Tejpar, Jonas Teuwen, E. Aubrey Thompson, Trine Tramm, William T. Tran, Jeroen van Der Laak, Paul J. van Diest, Gregory E. Verghese, Giuseppe Viale, Michael Vieth, Noorul Wahab, Thomas Walter, Yannick Waumans, Hannah Y. Wen, Wentao Yang, Yinyin Yuan, Reena Md Zin, Sylvia Adams, John Bartlett, Sibylle Loibl, Carsten Denkert, Peter Savas, Sherene Loi, Roberto Salgado, Elisabeth Specht Stovgaard
Summary: The clinical significance of tumor-immune interaction in breast cancer has been established. Tumor-infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple-negative and HER2-positive breast cancer. The use of machine learning (ML) to automatically evaluate TILs has shown promising results. However, there are challenges in implementing this in trial and routine clinical management, including technical slide issues, ML and image analysis aspects, data challenges, and validation issues.
JOURNAL OF PATHOLOGY
(2023)
Review
Oncology
David B. Page, Glenn Broeckx, Chowdhury Arif Jahangir, Chowdhury Jahangir, Sara Verbandt, Rajarsi R. Gupta, Jeppe Thagaard, Reena Khiroya, Zuzana Kos, Khalid Abduljabbar, Gabriela Acosta Haab, Balazs Acs, Jonas S. Almeida, Isabel Alvarado-Cabrero, Farid Azmoudeh-Ardalan, Sunil Badve, Nurkhairul Bariyah Baharun, Enrique R. Bellolio, Vydehi Bheemaraju, Kim R. M. Blenman, Luciana Botinelly Mendonca Fujimoto, Octavio Burgues, Maggie Chon U. Cheang, Francesco Ciompi, Lee A. D. Cooper, An Coosemans, German Corredor, Flavio Luis Dantas Portela, Frederik Deman, Sandra Demaria, Sarah N. Dudgeon, Mahmoud Elghazawy, Scott Ely, Claudio Fernandez-Martin, Susan Fineberg, Stephen B. Fox, William M. Gallagher, Jennifer M. Giltnane, Sacha Gnjatic, Paula Gonzalez-Ericsson, Anita Grigoriadis, Niels Halama, Matthew G. Hanna, Aparna Harbhajanka, Alexandros Hardas, Steven N. Hart, Johan Hartman, Stephen Hewitt, Akira Hida, Hugo M. Horlings, Zaheed Husain, Evangelos Hytopoulos, Sheeba Irshad, Emiel A. M. Janssen, Mohamed Kahila, Tatsuki R. Kataoka, Kosuke Kawaguchi, Durga Kharidehal, Andrey Khramtsov, Umay Kiraz, Pawan Kirtani, Liudmila L. Kodach, Konstanty Korski, Aniko Kovacs, Anne-Vibeke Laenkholm, Corinna Lang-Schwarz, Denis Larsimont, Jochen K. Lennerz, Marvin Lerousseau, Xiaoxian Li, Amy Ly, Anant Madabhushi, Sai K. Maley, Vidya Manur Narasimhamurthy, Douglas K. Marks, Elizabeth S. McDonald, Ravi Mehrotra, Stefan Michiels, Fayyaz ul Amir Afsar Minhas, Shachi Mittal, David A. Moore, Shamim Mushtaq, Hussain Nighat, Thomas Papathomas, Frederique Penault-Llorca, Rashindrie D. Perera, Christopher J. Pinard, Juan Carlos Pinto-Cardenas, Giancarlo Pruneri, Lajos Pusztai, Arman Rahman, Nasir Mahmood Rajpoot, Bernardo Leon Rapoport, Tilman T. Rau, Jorge S. Reis-Filho, Joana M. Ribeiro, David Rimm, Anne-Vincent Salomon, Manuel Salto-Tellez, Joel Saltz, Shahin Sayed, Kalliopi P. Siziopikou, Christos Sotiriou, Albrecht Stenzinger, Maher A. Sughayer, Daniel Sur, Fraser Symmans, Sunao Tanaka, Timothy Taxter, Sabine Tejpar, Jonas Teuwen, E. Aubrey Thompson, Trine Tramm, William T. Tran, Jeroen van Der Laak, Paul J. van Diest, Gregory E. Verghese, Giuseppe Viale, Michael Vieth, Noorul Wahab, Thomas Walter, Yannick Waumans, Hannah Y. Wen, Wentao Yang, Yinyin Yuan, Sylvia Adams, John Mark Seaverns Bartlett, Sibylle Loibl, Carsten Denkert, Peter Savas, Sherene Loi, Roberto Salgado, Elisabeth Specht Stovgaard, Guray Akturk, Najat Bouchmaa
Summary: Modern histologic imaging platforms combined with machine learning methods offer new opportunities for studying the spatial distribution of immune cells in the tumor microenvironment. However, there is currently no standardized method for describing or analyzing spatial immune cell data, and most previous spatial analyses have been simplistic. In this review, two approaches (raster versus vector-based) for reporting and analyzing spatial data are outlined, along with a summary of reported spatial immune cell metrics and their prognostic associations in various cancers. Two well-described clinical biomarkers, the breast cancer stromal tumor infiltrating lymphocytes score and the colon cancer Immunoscore, are also discussed, along with potential research opportunities to improve the clinical utility of these spatial biomarkers.
JOURNAL OF PATHOLOGY
(2023)
Article
Oncology
Abhishek Midya, Amogh Hiremath, Jacob Huber, Vidya Sankar Viswanathan, Danly Omil-Lima, Amr Mahran, Leonardo K. Bittencourt, Sree Harsha Tirumani, Lee Ponsky, Rakesh Shiradkar, Anant Madabhushi
Summary: The objective of this study was to quantify radiomic changes in prostate cancer progression on serial MRI among patients on active surveillance and evaluate their association with pathologic progression on biopsy. The study found that delta radiomics were more strongly associated with upgrade events compared to other clinical variables, and the combination of delta radiomics with baseline clinical variables showed the strongest association with biopsy upgrade prediction.
FRONTIERS IN ONCOLOGY
(2023)
Article
Oncology
Mohammadhadi Khorrami, Vidya Sakar Viswanathan, Priyanka Reddy, Nathaniel Braman, Siddharth Kunte, Amit Gupta, Jame Abraham, Alberto J. Montero, Anant Madabhushi
Summary: Imaging texture biomarkers before and after CDK4/6i therapy can predict early response and overall survival in MBC patients with liver metastases. Radiomic features can predict a lack of response earlier than standard anatomic/RECIST 1.1 assessment, highlighting the need for further study and clinical validation.
Article
Pathology
Chuheng Chen, Cheng Lu, Vidya Viswanathan, Brandon Maveal, Bhunesh Maheshwari, Joseph Willis, Anant Madabhushi
Summary: This study uses computer-extracted histomorphometric features to identify the primary site of origin for liver metastases. It found that features related to nuclear and peri-nuclear shape were the most important in classifying different metastatic tumors. Additionally, attention maps generated by a deep learning network can provide a composite feature similarity heat map between primary tumors and their associated metastases.
JOURNAL OF PATHOLOGY CLINICAL RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Zelin Zhang, Sara Arabyarmohammadi, Patrick Leo, Howard Meyerson, Leland Metheny, Jun Xu, Anant Madabhushi
Summary: This article introduces a segmentation model based on conditional generative adversarial network for efficient segmentation of myeloblasts from slides of AML patients. Through validation experiments, it is confirmed that this method has better segmentation performance than other deep learning models, and prognostic models for predicting the risk of recurrence in AML patients have been constructed using the segmentation results.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Urology & Nephrology
Yijiang Chen, Jarcy Zee, Andrew R. Janowczyk, Jeremy Rubin, Paula Toro, Kyle J. Lafata, Laura H. Mariani, Lawrence B. Holzman, Jeffrey B. Hodgin, Anant Madabhushi, Laura Barisoni
Summary: Computational image analysis enables quantification of PTC attributes and the discovery of a previously unrecognized PTC biomarker (aspect ratio) associated with clinical outcome.