Article
Gastroenterology & Hepatology
Jane J. Long, Kieranjeet Nijhar, Reed T. Jenkins, Adham Yassine, Jennifer D. Motter, Kyle R. Jackson, Stephanie Jerman, Sepideh Besharati, Robert A. Anders, Ty B. Dunn, Christopher L. Marsh, Divya Rayapati, David D. Lee, Rolf N. Barth, Kenneth J. Woodside, Benjamin Philosophe
Summary: Digital imaging software (DIS) can standardize the definition and measurement of macrovesicular steatosis (MaS) and identify phenotypes associated with good clinical outcomes. It provides reproducible quantification of steatosis, which can increase the utilization of steatotic livers.
LIVER TRANSPLANTATION
(2023)
Article
Agriculture, Multidisciplinary
Samiul Haque, Edgar Lobaton, Natalie Nelson, G. Craig Yencho, Kenneth Pecota, Russell Mierop, Michael W. Kudenov, Mike Boyette, Cranos M. Williams
Summary: The quality variation in horticultural crops significantly affects market value, but objectively characterizing subjective crop quality characteristics at production-scale remains challenging. Using sweetpotato as a case study, researchers introduced a high-throughput computer vision algorithm for quantifying shape and size characteristics, demonstrating the potential for industrial crop production big data analytics.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2021)
Article
Computer Science, Interdisciplinary Applications
Michaela Fendrock, Christine Y. Chen, Kristian J. Olson, Tim K. Lowenstein, David McGee
Summary: This study investigates and compares the textures of tufa in Mono Lake and Searles Valley. It finds that a t-Distributed Stochastic Neighbor Embedding (t-SNE) algorithm can be used to quantitatively compare the visual similarity of textures. The study provides a robust assessment of the feasibility of using Mono Lake as a modern analogue for Searles Valley and makes significant progress towards using texture as a metric for the environment in which tufa formed.
COMPUTERS & GEOSCIENCES
(2022)
Review
Gastroenterology & Hepatology
Charles E. Hill, Luca Biasiolli, Matthew D. Robson, Vicente Grau, Michael Pavlides
Summary: Chronic liver diseases are increasingly prevalent in modern society, and utilizing AI algorithms for liver MRI analysis is crucial for improving clinical decisions, automating analyses, and increasing throughput.
WORLD JOURNAL OF GASTROENTEROLOGY
(2021)
Review
Agriculture, Multidisciplinary
Harsh Pathak, C. Igathinathane, Z. Zhang, D. Archer, J. Hendrickson
Summary: The use of unmanned aerial vehicles (UAV) and computer vision algorithms in evaluating plant stand count has been reviewed in this study. It is concluded that image acquisition at an appropriate stage and height, along with suitable color space and camera imagery, can improve the accuracy of plant stand count. Other findings include the effectiveness of deep learning models and the application of direct image processing and open-source platforms. This review provides valuable guidance for farmers, producers, and researchers in selecting and employing UAV-based algorithms for plant stand count evaluation.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2022)
Article
Robotics
Vitor Guizilini, Igor Vasiljevic, Rares Ambrus, Greg Shakhnarovich, Adrien Gaidon
Summary: Self-supervised monocular depth and ego-motion estimation is a promising approach for robotics applications. This work extends the method to large-baseline multi-camera rigs and proposes a new scale-consistent evaluation metric.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Environmental Sciences
William Yamada, Wei Zhao, Matthew Digman
Summary: An automatic method using monovision un-crewed aerial vehicle imagery was developed to obtain geographic coordinates of bales, with YOLOv3 algorithm identified as the best option in terms of accuracy and speed. Lowering image quality resulted in decreased performance.
Article
Chemistry, Analytical
Husein Perez, Joseph H. M. Tah, Xin Ning, Wenfa Li
Summary: This paper proposes a pipeline for automating the measurement of as-built components using artificial intelligence and computer vision techniques. The pipeline requires a single image obtained with a stereo camera system to measure the sizes of selected objects or as-built components. The proposed solution is suitable for use in measuring the sizes of as-built components in built assets and has the potential to be integrated with building information modelling applications for progress monitoring on construction projects.
Article
Chemistry, Analytical
Sungwook Son, Ahreum Seo, Gyeongseon Eo, Kwangyeon Gill, Taesik Gong, Hyung-Sin Kim
Summary: In this paper, we propose MiCrowd, a floating population measurement system with a tiny DNNs running on MCUs. MiCrowd addresses important challenges such as privacy issues, communication costs, and extreme resource constraints on MCUs. To tackle these challenges, we designed a lightweight crowd-counting deep neural network named MiCrowdNet and carefully re-labeled a dataset for accurate on-device crowd counting.
Article
Computer Science, Artificial Intelligence
Francesco Giuliari, Geri Skenderi, Marco Cristani, Alessio Del Bue, Yiming Wang
Summary: This article proposes an end-to-end solution for object localisation in partial scenes using a Directed Spatial Commonsense Graph (D-SCG) as the scene representation. The unknown position of the object is estimated using a graph neural network that predicts relative positions and employs a sparse attentional message passing mechanism. The proposed method improves the state-of-the-art in localisation accuracy by 5.9% at a training speed 8 times faster, as evaluated on Partial ScanNet.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2023)
Article
Cardiac & Cardiovascular Systems
Eliot G. Peyster, Andrew Janowczyk, Abigail Swamidoss, Samhith Kethireddy, Michael D. Feldman, Kenneth B. Margulies
Summary: This study developed a precision medicine tool for predicting the development of cardiac allograft vasculopathy (CAV) in heart transplant recipients using computational analysis of digital pathology images. The incorporation of computationally extracted histological features greatly improved the prediction of future CAV development, enhancing the precision and personalization of treatment plans.
Review
Fisheries
Daoliang Li, Qi Wang, Xin Li, Meilin Niu, He Wang, Chunhong Liu
Summary: This paper provides an overview of machine vision models applied in fish classification, discusses specific applications of various classification methods, and explores the challenges and future research directions in the field of fish classification.
ICES JOURNAL OF MARINE SCIENCE
(2022)
Review
Agriculture, Multidisciplinary
Hua Yin, Wenlong Yi, Dianming Hu
Summary: This article provides an overview of the application of computer vision and machine learning algorithms in the mushroom industry. It discusses the current methods and limitations, and suggests potential future applications such as digital mushroom phenotype determination and high-throughput breeding based on big data. The integration of computer vision and machine learning with more efficient algorithms is expected to be a hotspot for future studies in the mushroom industry.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2022)
Article
Engineering, Chemical
Manuel Knott, Fernando Perez-Cruz, Thijs Defraeye
Summary: Image-based machine learning models can improve the efficiency of sorting and grading agricultural products. However, implementation in some regions is challenging due to decentralized and non-automated postharvest supply chains. A proposed machine learning procedure based on pre-trained Vision Transformers addresses these challenges by avoiding the need for retraining deep neural networks. Evaluation on two datasets for apple defect detection and banana ripeness estimation demonstrates competitive performance with a classification accuracy close to the best-performing Convolutional Neural Networks (CNNs), while requiring significantly fewer training samples to achieve high accuracy.
JOURNAL OF FOOD ENGINEERING
(2023)
Review
Plant Sciences
Zafar Salman, Abdullah Muhammad, Md Jalil Piran, Dongil Han
Summary: Plant diseases pose a serious threat to agriculture and the food supply chain, and deep learning has been applied to detect and identify these diseases. This survey aims to provide an overview of the advancements in machine-learning based disease detection and discuss the challenges and potential improvements. The insights from this survey will be valuable for researchers and practitioners in the field and inspire future research efforts.
FRONTIERS IN PLANT SCIENCE
(2023)
Review
Neurosciences
Carole Escartin, Elena Galea, Andras Lakatos, James P. O'Callaghan, Gabor C. Petzold, Alberto Serrano-Pozo, Christian Steinhauser, Andrea Volterra, Giorgio Carmignoto, Amit Agarwal, Nicola J. Allen, Alfonso Araque, Luis Barbeito, Ari Barzilai, Dwight E. Bergles, Gilles Bonvento, Arthur M. Butt, Wei-Ting Chen, Martine Cohen-Salmon, Colm Cunningham, Benjamin Deneen, Bart De Strooper, Blanca Diaz-Castro, Cinthia Farina, Marc Freeman, Vittorio Gallo, James E. Goldman, Steven A. Goldman, Magdalena Gotz, Antonia Gutierrez, Philip G. Haydon, Dieter H. Heiland, Elly M. Hol, Matthew G. Holt, Masamitsu Iino, Ksenia V. Kastanenka, Helmut Kettenmann, Baljit S. Khakh, Schuichi Koizumi, C. Justin Lee, Shane A. Liddelow, Brian A. MacVicar, Pierre Magistretti, Albee Messing, Anusha Mishra, Anna V. Molofsky, Keith K. Murai, Christopher M. Norris, Seiji Okada, Stephane H. R. Oliet, Joao F. Oliveira, Aude Panatier, Vladimir Parpura, Marcela Pekna, Milos Pekny, Luc Pellerin, Gertrudis Perea, Beatriz G. Perez-Nievas, Frank W. Pfrieger, Kira E. Poskanzer, Francisco J. Quintana, Richard M. Ransohoff, Miriam Riquelme-Perez, Stefanie Robel, Christine R. Rose, Jeffrey D. Rothstein, Nathalie Rouach, David H. Rowitch, Alexey Semyanov, Swetlana Sirko, Harald Sontheimer, Raymond A. Swanson, Javier Vitorica, Ina-Beate Wanner, Levi B. Wood, Jiaqian Wu, Binhai Zheng, Eduardo R. Zimmer, Robert Zorec, Michael V. Sofroniew, Alexei Verkhratsky
Summary: The article highlights the challenges and uncertainties surrounding reactive astrocytes, advocating for comprehensive research that includes assessment of multiple molecular and functional parameters, preferably in vivo, along with multivariate statistics and determination of impact on pathological hallmarks in relevant models.
NATURE NEUROSCIENCE
(2021)
Article
Hematology
Miguel A. Galindo-Campos, Nura Lutfi, Sarah Bonnin, Carlos Martinez, Talia Velasco-Hernandez, Violeta Garcia-Hernandez, Juan Martin-Caballero, Coral Ampurdanes, Ramon Gimeno, Lluis Colomo, Gael Roue, Guillaume Guilbaud, Francoise Dantzer, Pilar Navarro, Matilde Murga, Oscar Fernandez-Capetillo, Anna Bigas, Pablo Menendez, Julian E. Sale, Jose Yelamos
Summary: Dysregulation of the c-Myc oncogene is linked to aggressive tumor progression, and PARP-1 and PARP-2 have opposing influence in c-Myc-driven B-cell lymphoma. PARP-1 deficiency accelerates lymphomagenesis, while genetic deletion of PARP-2 prevents B-cell lymphoma. These findings provide important insights for the design of new PARP-centered therapeutic strategies.
Article
Biochemistry & Molecular Biology
Sebastian Canovas, Elena Ivanova, Meriem Hamdi, Fernando Perez-Sanz, Dimitrios Rizos, Gavin Kelsey, Pilar Coy
Summary: The study found that in vitro culture affects DNA methylation, and the sex-specific methylation differences in blastocysts vary in embryos from different sources. Methylation differences were more frequent in the first intron than in CpGi in promoters, and sex produced a stronger bias in the results than embryo origin.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2021)
Review
Immunology
Victor Lopez-Lopez, Fernando Perez-Sanz, Carlos de Torre-Minguela, Josefa Marco-Abenza, Ricardo Robles-Campos, Francisco Sanchez-Bueno, Jose A. Pons, Pablo Ramirez, Alberto Baroja-Mazo
Summary: Proteomics has been used in liver transplantation research to study outcomes such as ischemia-reperfusion injury (IRI) and rejection, showing a higher number of shared proteins between these two conditions. Metabolism was found to be the most enriched pathway in liver biopsy samples, IRI, and rejection, while cytokine-cytokine receptor interactions were predominant in tolerance studies.
FRONTIERS IN IMMUNOLOGY
(2021)
Article
Oncology
Maria del Carmen Turpin-Sevilla, Fernando Perez-Sanz, Jose Garcia-Solano, Patricia Sebastian-Leon, Javier Trujillo-Santos, Pablo Carbonell, Eduardo Estrada, Anne Tuomisto, Irene Herruzo, Lochlan J. Fennell, Markus J. Makinen, Edith Rodriguez-Braun, Vicki L. J. Whitehall, Ana Conesa, Pablo Conesa-Zamora
Summary: Aberrant methylation patterns at specific genome sequences (CpG) are driving forces for carcinogenesis processes. Different histological subtypes of colorectal cancer (CRC) exhibit distinct global methylation patterns, with a shift from promoter hypermethylation to genomic hypomethylation occurring at a small sequence between 250 bp and 1 Kb from the gene TSS.
Article
Clinical Neurology
Ana Belen Gamez Santiago, Carlos Manuel Martinez Caceres, Juan Jose Hernandez-Morante
Summary: This study aimed to determine the effectiveness of neuromuscular stimulation triggered by mirror therapy (MT) in older patients with post-stroke hemiplegia. The results showed that intensive MT had a significantly higher intervention effect on muscle activity and strength, as well as functionality, compared to spaced over time therapy.
EUROPEAN NEUROLOGY
(2022)
Article
Biology
Alejandro Penin-Franch, Jose Antonio Garcia-Vidal, Carlos Manuel Martinez, Pilar Escolar-Reina, Rosa M. Martinez-Ojeda, Ana Gomez, Juan M. Bueno, Francisco Minaya-Munoz, Fermin Valera-Garrido, Francesc Medina-Mirapeix, Pablo Pelegrin
Summary: The NLRP3 inflammasome plays a critical role in coordinating inflammation in response to various pathogens and damage-associated molecular patterns. This study reveals the molecular mechanism of percutaneous needle electrolysis and its beneficial effects in promoting collagen-mediated tendon regeneration in chronic tendinopathic lesions.
Article
Materials Science, Ceramics
Patricia Ros-Tarraga, Carlos M. Martinez, Miguel A. Rodriguez, Piedad N. De Aza
Summary: The elderly population is increasing, leading to an increase in bone and joint problems. Scaffold for bone tissue regeneration can solve these problems, and material selection is crucial for satisfactory results. This study designed a three-dimensional porous ceramic scaffold and analyzed its biocompatibility and osteoinductive capacity. The results suggest that it has potential applications as bone substitutes.
CERAMICS INTERNATIONAL
(2022)
Article
Cell & Tissue Engineering
David Garcia-Bernal, Miguel Blanquer, Carlos M. Martinez, Ana Garcia-Guillen, Ana M. Garcia-Hernandez, M. Carmen Alguero, Rosa Yanez, Maria L. Lamana, Jose M. Moraleda, Robert Sackstein
Summary: Mesenchymal stem/stromal cells (MSCs) have immunoregulatory properties and can be used for the treatment of inflammatory conditions and immune diseases. Through a mouse model, it was found that adipose tissue-derived MSCs (HCELL+ MSCs) can effectively recruit to the affected tissue and exert protective effects on immunopathology, reducing leukocyte infiltration and inflammatory cytokine levels, and improving survival.
NPJ REGENERATIVE MEDICINE
(2022)
Article
Gastroenterology & Hepatology
Victor Lopez-Lopez, Carlos Martinez-Caceres, Paula Gomez-Valles, Juan Cruz, Albert Caballero-Illanes, Roberto Brusadin, Asuncion Lopez-Conesa, Maria Perez, Kohei Miura, Jesus de la Pena-Moral, Ricardo Robles-Campos
Summary: The study suggests that liver regeneration with T-ALPPS does not lead to higher tumor progression or significant immunological changes in the tumor environment compared to classical TSH.