Article
Biochemistry & Molecular Biology
Bryan Grimes, Walter Jacob, Amanda R. Liberman, Nathan Kim, Xiaohong Zhao, Daniel C. Masison, Lois E. Greene
Summary: The Sup35 prion protein of budding yeast can undergo phase separation to form liquid droplets, which requires the involvement of the C-terminal domain and is related to stress granules. Additionally, the phase separation of Sup35 appears to be dependent on the presence of mRNA, and the condensates formed in vivo do not disassemble when the intracellular pH is increased.
Review
Biochemistry & Molecular Biology
Vitaly V. Kushnirov, Alexander A. Dergalev, Maya K. Alieva, Alexander Alexandrov
Summary: This article discusses the structure and variation of yeast prions, and how these structures affect the balance between aggregated and soluble prion proteins through interaction with molecular chaperones. It also explains how the aggregated state affects the non-prion functions of these proteins.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2022)
Article
Biology
Andrew G. Matveenko, Varvara E. Ryzhkova, Natalia A. Zaytseva, Lavrentii G. Danilov, Anastasia S. Mikhailichenko, Yury A. Barbitoff, Galina A. Zhouravleva
Summary: This study reveals that labeling prion aggregates with the red fluorescent protein mCherry may prevent accurate detection of the aggregates. In contrast, fusion with the red fluorescent protein TagRFP-T allows for reliable detection of prion aggregates.
Article
Clinical Neurology
Martin Flach, Cedric Leu, Alfonso Martinisi, Zhiva Skachokova, Stephan Frank, Markus Tolnay, Henning Stahlberg, David T. Winkler
Summary: This study investigated whether a non-human prion can promote the aggregation of tau protein. It was found that Sup35NM fibrils can promote tau aggregation and exacerbate tau pathology in transgenic mice. This suggests that non-mammalian prions present in the human microbiome may contribute to protein misfolding in neurodegenerative disorders.
ALZHEIMERS & DEMENTIA
(2022)
Article
Virology
Jane E. Dorweiler, Douglas R. Lyke, Nathan P. Lemoine, Samantha Guereca, Hannah E. Buchholz, Emily R. Legan, Claire M. Radtke, Anita L. Manogaran
Summary: This study investigates the influence of actin on the cell's ability to manage newly formed visible aggregates and the transmission of these aggregates to future generations. The results show that the movement of newly formed aggregates is random and actin independent at early stages, while the transmission of newly formed prion particles to daughter cells is limited by the actin cytoskeletal network at later stages.
Article
Biochemistry & Molecular Biology
Yu-Wen Huang, Vitaly V. Kushnirov, Chih-Yen King
Summary: The study initially suggested that mutant Hsp104(T160M) chaperone plays a role in curing many nascent [PSI+] variants by restricting their propagation in wild-type cells. However, further experiments showed that the mutant Hsp104 can also impose restrictions against emerging prion variants similar to the wild-type protein.
MOLECULAR MICROBIOLOGY
(2021)
Review
Biochemistry & Molecular Biology
Mehdi Kabani
Summary: Yeast Saccharomyces cerevisiae hosts a variety of heritable traits, mainly resulting from the conversion of cytoplasmic proteins into prion forms. These prions propagate through the fragmentation of aggregates by molecular chaperones, forming self-templating seeds. The exact nature of these propagons and their transmission from mother to daughter cells is not fully understood.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2021)
Article
Virology
Chih-Yen King
Summary: This passage discusses the replication mechanism of prions and the emergence of variants and strains. It is suggested that the heat shock protein Hsp104 can restrict strain variation, leading to the possibility that some transmutable variants may have been mistaken as faithful-propagating. By altering the strength of Hsp104 in yeast, it is found that most variants are faithful-propagating, with only a few capable of changing to limited structural types.
Review
Cell Biology
Takao Ishikawa
Summary: The baker's yeast Saccharomyces cerevisiae is widely used in life sciences research. Although yeast has limitations in neuroscience applications, yeast prions share common characteristics with mammalian prion proteins, making yeast a useful system for studying these proteins. Yeast-based assays are also cost-effective and safe for researchers, providing a valuable screening tool for potential anti-prion compounds before further testing in mammalian cell systems.
NEURAL REGENERATION RESEARCH
(2021)
Article
Plant Sciences
Katherine M. Murphy, Tyler Dowd, Ahmed Khalil, Si Nian Char, Bing Yang, Benjamin J. Endelman, Patrick M. Shih, Christopher Topp, Eric A. Schmelz, Philipp Zerbe
Summary: In maize, two major groups of specialized metabolites, kauralexins and dolabralexins, are involved in defending against pathogens, herbivores, and other stressors. This study examined the dolabralexin pathway and found new metabolites and characterized their production. Genetic analysis showed that dolabralexin biosynthesis occurs mainly in primary roots and varies across different maize lines. Loss-of-function mutants for the diterpene synthase gene ZmKSL4 demonstrated deficient dolabralexin production and exhibited altered root architecture in response to water deficit. These findings suggest that maize dolabralexins play a role in plant vigor during abiotic stress.
Review
Biochemistry & Molecular Biology
Francesca De Giorgi, Vladimir N. Uversky, Francois Ichas
Summary: The article discusses Lionel Penrose's invention of the first self-replicating mechanical device in 1957 and its function, as well as its relevance to the genesis and proliferation of amyloid fibrils. It also highlights the significance of studies on alpha-Synuclein and its similarities to prions, its fibrillization-prone domain, and its nature as an intrinsically disordered protein. Combining these discoveries with the concept of the Penrose machine, the article proposes an explanation for the emergence and spread of different alpha-Synuclein fibril strains in alpha-Synucleinopathies.
Article
Multidisciplinary Sciences
Nadejda Koloteva-Levine, Liam D. Aubrey, Ricardo Marchante, Tracey J. Purton, Jennifer R. Hiscock, Mick F. Tuite, Wei-Feng Xue
Summary: Amyloid seeds are nanometer-sized protein particles that can accelerate amyloid formation through a surface catalysis mechanism without propagating the specific amyloid conformation associated with the seeds. This allows for cross-seeded assembly reactions involving nonhomologous proteins and rationalizes the molecular mechanism of the cross-seeding phenomenon as a manifestation of aberrant surface activities by amyloid seeds.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2021)
Article
Multidisciplinary Sciences
Jacob L. Steenwyk, Megan A. Phillips, Feng Yang, Swapneeta S. Date, Todd R. Graham, Judith Berman, Chris Todd Hittinger, Antonis Rokas
Summary: The evolutionary rates of functionally related genes are often correlated. A gene coevolution network was established by studying orthologous gene pairs of budding yeast species. The network modules provide insights into cellular and genomic structure and function. Analysis of deletion mutant data reveals that the neighborhood and connectivity of orthologous genes affect fitness in diverse environments.
Article
Multidisciplinary Sciences
Yan Wang, Peng Wang, Hai-Yan Cao, Hai-Tao Ding, Hai-Nan Su, Shi-Cheng Liu, Guangfeng Liu, Xia Zhang, Chun-Yang Li, Ming Peng, Fuchuan Li, Shengying Li, Yin Chen, Xiu-Lan Chen, Yu-Zhong Zhang
Summary: This study reports the structure and collagenolytic mechanism of Vibrio collagenase VhaC, providing new insights into bacterial collagenolysis.
NATURE COMMUNICATIONS
(2022)
Review
Biochemistry & Molecular Biology
Carla E. Barraza, Clara A. Solari, Jimena Rinaldi, Lucas Ojeda, Silvia Rossi, Mark P. Ashe, Paula Portela
Summary: The study reveals that in yeast cells, the specific Tpk2 isoform is involved in the assembly of P-bodies under stress conditions through its glutamine-rich prion-like domain, playing a crucial role in mRNA turnover in cells.
BIOCHIMICA ET BIOPHYSICA ACTA-MOLECULAR CELL RESEARCH
(2021)
Article
Biology
Karla Daniela Chikani-Cabrera, Patricia Machado Bueno Fernandes, Raul Tapia-Tussell, David Leonardo Parra-Ortiz, Galdy Hernandez-Zarate, Ruby Valdez-Ojeda, Liliana Alzate-Gaviria
Summary: The recent Sargassum tides in the Mexican Caribbean have had an impact on the local ecosystem and economy, but also presented an opportunity for the production of biofuel. This study investigated the potential of converting Sargassum into biomethane, with hydrolysis being the limiting step. The combined pretreatment of hydrogen peroxide and enzymatic treatment proved to be the most effective in terms of biodegradability and methane yield, while the use of granular activated carbon did not significantly affect performance.
Article
Computer Science, Artificial Intelligence
Houda Harkat, Jose M. P. Nascimento, Alexandre Bernardino, Hasmath Farhana Thariq Ahmed
Summary: This article introduces a method for classifying fire and non-fire pixels using machine learning techniques. Feature selection is used to choose the most important features, and Support Vector Machine is used as the classifier. Experimental results show that the method achieves high accuracy and performance in fire detection.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Computer Science, Interdisciplinary Applications
David Dias, Jose Silvestre Silva, Alexandre Bernardino
Summary: This study proposes a tool for predicting the risk of road accidents. The system consists of data selection and collection, preprocessing, and the use of mining algorithms. Data from the Portuguese National Guard database covering accidents from 2019 to 2021 were analyzed. The results indicate that accidents are most concentrated between 17:00 and 20:00, and rain has the greatest impact on the probability of an accident occurring. Additionally, Fridays have the highest number of accidents compared to other days. These findings are crucial for decision makers responsible for effectively allocating traffic surveillance resources.
Article
Computer Science, Artificial Intelligence
Rui Pimentel de Figueiredo, Alexandre Bernardino
Summary: In order to efficiently explore and understand the environment, humans have developed space-variant vision mechanisms that allow them to actively attend different locations and compensate for brain limitations. Similarly, humanoid robots in everyday environments face complex tasks and limited resources, and can benefit from biologically inspired vision mechanisms for various visual tasks. This work provides an overview of state-of-the-art space-variant vision architectures for active recognition and localization tasks.
Article
Forestry
Tiago Garcia, Ricardo Ribeiro, Alexandre Bernardino
Summary: This study proposes a multilayer segmentation method based on level sets for segmenting infrared thermal images of propagating wildfires. The experimental results show that the proposed method outperforms other common unsupervised methods.
INTERNATIONAL JOURNAL OF WILDLAND FIRE
(2023)
Article
Computer Science, Cybernetics
Min Hun Lee, Daniel P. Siewiorek, Asim Smailagic, Alexandre Bernardino, Sergi Bermudez i Badia
Summary: Socially assistive robots are used to improve engagement of older adults and people with disability in health and well-being exercises. Prior work on social robot exercise coaching systems has used generic feedback, but our system provides personalized rehabilitation coaching. With therapist interviews and collaboration with post-stroke survivors, we developed an interactive social robot exercise coaching system that automatically monitors and assesses patients' exercises and generates real-time feedback for improvement. Real-world evaluation showed our system achieved comparable performance to experts in assessing exercises, with potential benefits and limitations discussed.
USER MODELING AND USER-ADAPTED INTERACTION
(2023)
Article
Environmental Sciences
Mohamed Beroho, Hamza Briak, El Khalil Cherif, Imane Boulahfa, Abdessalam Ouallali, Rachid Mrabet, Fassil Kebede, Alexandre Bernardino, Khadija Aboumaria
Summary: Modeling of land use and land cover is a crucial tool in the agricultural field, allowing us to predict future changes in land area and plan accordingly. This study aims to predict land use and land cover in a specific watershed for different time periods. The results indicate potential decreases in agricultural areas and wetlands, but an increase in forest areas, which could affect crop production and biodiversity in the watershed.
Article
Robotics
Jose Ribeiro-Gomes, Jose Gaspar, Alexandre Bernardino
Summary: This study proposes a feature tracking method based on event cameras, which combines with a visual inertial odometry system to improve tracking performance using frames, events, and inertial measurement unit information. The problem of temporal combination between high-rate IMU information and asynchronous event cameras is solved using an asynchronous probabilistic filter (UKF). Experimental results show that using event cameras for feature tracking can improve performance.
FRONTIERS IN ROBOTICS AND AI
(2023)
Article
Remote Sensing
Nuno Pessanha Santos, Victor Lobo, Alexandre Bernardino
Summary: The vast increase in computational capability has led to the application of Particle-Filter (PF)-based approaches for monocular 3D-model-based tracking. These filters rely on the computation of a usually unavailable likelihood function, which can be approximated using a similarity metric. By using temporal filtering techniques and optimization steps, better results can be achieved, especially for the symmetry of UAV models. The evaluation time of the similarity metric is also a critical concern for real-time implementation.
Article
Environmental Sciences
Houda Badda, El Khalil Cherif, Hakim Boulaassal, Miriam Wahbi, Otmane Yazidi Alaoui, Mustapha Maatouk, Alexandre Bernardino, Franco Coren, Omar El Kharki
Summary: This study proposes a method that combines remote sensing and machine learning techniques to detect burned areas in the Tangier-Tetouan-Al Hoceima (TTA) region in northern Morocco. By analyzing and studying specific locations in the region, the combination of dNBR index and other spectral indices achieved the highest accuracy, enhancing fire monitoring and response capabilities.
Article
Environmental Sciences
Tiago Marto, Alexandre Bernardino, Goncalo Cruz
Summary: This work proposes an active learning methodology for the segmentation of fire and smoke in video images. The model learns incrementally over several active learning rounds, selecting informative samples to update the training set. Using active learning in classification and segmentation tasks resulted in improved accuracy and mean intersection over union by 2%, while achieving similar results to non-active learning with fewer labeled data samples.
Article
Computer Science, Information Systems
Joao Correia, Alexandre Bernardino, Ricardo Ribeiro
Summary: Unmanned aerial vehicles (UAVs) are increasingly being used in various fields, but low-cost commercial UAVs may not have enough computational power to run state-of-the-art algorithms, impacting performance. Remote computational systems can be a solution, but they introduce latency, which is undesirable for real-time tasks. Furthermore, for simple tasks, using a local algorithm with worse performance may be acceptable to avoid latency. Hence, a method to decide which algorithm to use is crucial.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Proceedings Paper
Automation & Control Systems
Akhil John, John Van Opstal, Alexandre Bernardino
Summary: We propose a novel design for a bio-inspired robotic eye with 6 independently controlled muscles, suitable for studying the emergence of human saccadic eye movements characteristics. The design includes a spherical eye actuated by motor-driven cables to mimic the extraocular muscles, and a rotational system that is crucial for understanding the control signals of artificial and biological eyes. We present the mechanical design and simulation model of the robotic system, demonstrating its ability to perform a wide range of eye movements with appropriate characteristics.
2023 9TH INTERNATIONAL CONFERENCE ON AUTOMATION, ROBOTICS AND APPLICATIONS, ICARA
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Benjamin Kiefer, Matej Kristan, Janez Pers, Lojze Zust, Fabio Poiesi, Fabio Augusto de Alcantara Andrade, Alexandre Bernardino, Matthew Dawkins, Jenni Raitoharju, Yitong Quan, Adem Atmaca, Timon Hoefer, Qiming Zhang, Yufei Xu, Jing Zhang, Dacheng Tao, Lars Sommer, Raphael Spraul, Hangyue Zhao, Hongpu Zhang, Yanyun Zhao, Jan Lukas Augustin, Eui-Ik Jeon, Impyeong Lee, Luca Zedda, Andrea Loddo, Cecilia Di Ruberto, Sagar Verma, Siddharth Gupta, Shishir Muralidhara, Niharika Hegde, Daitao Xing, Nikolaos Evangeliou, Anthony Tzes, Vojtech Bartl, Jakub Spanhel, Adam Herout, Neelanjan Bhowmik, Toby P. Breckon, Shivanand Kundargi, Tejas Anvekar, Ramesh Ashok Tabib, Uma Mudengudi, Arpita Vats, Yang Song, Delong Liu, Yonglin Li, Shuman Li, Chenhao Tan, Long Lan, Vladimir Somers, Christophe De Vleeschouwer, Alexandre Alahi, Hsiang-Wei Huang, Cheng-Yen Yang, Jenq-Neng Hwang, Pyong-Kun Kim, Kwangju Kim, Kyoungoh Lee, Shuai Jiang, Haiwen Li, Ziqiang Zheng, Tuan-Anh Vu, Hai Nguyen-Truong, Sai-Kit Yeung, Zhuang Jia, Sophia Yang, Chih-Chung Hsu, Xiu-Yu Hou, Yu-An Jhang, Simon Yang, Mau-Tsuen Yang
Summary: The 1st Workshop on Maritime Computer Vision (MaCVi) 2023 focused on maritime computer vision for UAV and USV and organized subchallenges in areas such as object detection, tracking, obstacle segmentation, and detection. The report summarizes the main findings of the subchallenges and introduces a new benchmark called SeaDronesSee Object Detection v2. Over 130 submissions were evaluated and trends in the best-performing methodologies were assessed. The datasets, evaluation code, and leaderboard are publicly available.
2023 IEEE/CVF WINTER CONFERENCE ON APPLICATIONS OF COMPUTER VISION WORKSHOPS (WACVW)
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Goncalo Adolfo, Alexandre Bernardino, Nuria Baylina, H. Sofia Pinto
Summary: This paper investigates the automatic detection of feeding activity in the Oceanario de Lisboa Main Aquarium using various methodologies. Three methods, including Convolutional Neural Networks (CNN), motion variability, and spatial pattern analysis, were proposed. The study involved filming several videos at the aquarium and evaluating the approaches using metrics such as accuracy, precision, and recall. The results showed distinct differences in motion and fish aggregation between bottom feeding and surface feeding, with the frame difference method performing the best for bottom feeding and CNN being the most accurate for surface feeding.
2022 26TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR)
(2022)