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Changes in histone lysine acetylation, but not DNA methylation during facultative hibernation in Syrian hamster liver

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Epigenetics Communications 2024年第1期4卷 1-14页

作者： Oosterhof, Marloes M. Coussement, Louis van Pijkeren, Alienke Kwiatkowski, Marcel Zwinderman, Martijn R. H. Dekker, Frank J. de Meyer, Tim Reitsema, Vera A. Bischoff, Rainer Guryev, Victor Bouma, Hjalmar R. Henning, Rob H. Rots, Marianne G. Department of Clinical Pharmacy and Pharmacology University of Groningen University Medical Center Groningen Groningen The Netherlands Department of Pathology and Medical Biology University of Groningen University Medical Center Groningen Groningen The Netherlands Department of Data Analysis and Mathematical Modelling Faculty of Bioscience Engineering Ghent University Ghent Belgium Department of Analytical Biochemistry Groningen Research Institute of Pharmacy University of Groningen Groningen The Netherlands Institute of Biochemistry and Center for Molecular Biosciences Innsbruck University of Innsbruck Innsbruck Austria Department of Pharmacokinetics Toxicology and Targeting Groningen Research Institute of Pharmacy University of Groningen Groningen The Netherlands Department of Chemical and Pharmaceutical Biology Groningen Research Institute of Pharmacy University of Groningen Groningen The Netherlands European Research Institute for the Biology of Ageing Groningen The Netherlands Department of Internal Medicine University of Groningen University Medical Center Groningen Groningen The Netherlands

Hibernation (torpor) is a strategy to survive extreme environmental conditions, associated with a significant decrease in metabolism and body temperature. The inducibility by the environment of torpor for facultative hibernators designates epigenetic mechanisms as likely candidates for regulation. Therefore, we set out to unravel epigenetics in the liver of a facultative hibernator, Syrian hamster (Mesocricetus auratus), sampled at different phases during hibernation, by assessing the expression of epigenetic writer and eraser enzymes, histone acetylation dynamics, and DNA methylation levels. Expression of epigenetic writers/erasers confirmed previously reported results obtained in obligatory hibernators, but might point to a mechanism specific for facultative hibernators, e.g., differential expression of histone acetyltransferases (HATs; KAT6A, KAT6B, KAT7, and KAT13D/CLOCK). These findings were in accordance with observed changes in histone H3 and H4 acetylation changes. Overall histone deacetylase (HDAC) activity was highest in torpor. No differences were detected in DNA methylation throughout all phases. Our study thus points to histone acetylation as an important player in facultative hamster hibernation, which may underlie the orchestration of gene expression changes throughout hibernation.

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A complete description of the dynamics of legal outer-totalistic affine continuous cellular automata

Research Square

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Research Square 2021年

作者： Wolnik, Barbara Dembowski, Marcin Augustynowicz, Antonii De Baets, Bernard Gdansk University Poland Institute of Mathematics Faculty of Mathematics Physics and Informatics University of Gdańsk Gdańsk80-308 Poland KERMIT Department of Data Analysis and Mathematical Modelling Ghent University Gent9000 Belgium

This paper presents an investigation into the evolution and dynamics of the simplest generalization of binary cellular automata: Affine Continuous Cellular Automata (ACCAs), with [0, 1] as state set and local rules that are affine in each variable. The focus lies on legal outer-totalistic ACCAs, an interesting class of dynamical systems that show some properties that do not occur in the binary case. A unique combination of computer simulations (sometimes quite advanced) and a panoply of analytical methods allow to lay bare the dynamics of each and every one of these cellular automata. The results show that in the class of ACCAs considered, one can observe all types of sensitivity: sensitivity to the change of the number of cells in the grid, sensitivity to slight changes in the parameters of a local rule and sensitivity to the change of a single value in an initial configuration. © 2021, CC BY.

关键词： Cellular automata

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Investigating time series classification techniques for rapid pathogen identification with single-cell MALDI-TOF mass spectrum data 31

Investigating time series classification techniques for rapi...

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31st Benelux Conference on Artificial Intelligence and the 28th Belgian Dutch Conference on Machine Learning, BNAIC/BENELEARN 2019

作者： Papagiannopoulou, Christina Parchen, René Waegeman, Willem Department of Data Analysis and Mathematical Modelling Ghent University Ghent Belgium BiosparQ B.V. Leiden Netherlands

Matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF-MS) is a well-known technology, widely used in species identification. Specifically, MALDI-TOF-MS is applied on samples that usually include bacterial cells, generating representative signals for the various bacterial species. However, for a reliable identification result, a significant amount of biomass is required. For most samples used for diagnostics of infectious diseases, the sample volume is extremely low to obtain the required amount of biomass. Therefore, amplification of the bacterial load is performed by a culturing phase. If the MALDI process could be applied to individual bacteria, it would be possible to circumvent the need for culturing and isolation, accelerating the whole process. In this work, we briefly describe an implementation of a MALDI-TOF MS procedure in a setting of individual cells and we demonstrate the use of the produced data for the application of pathogen identification. The identification of pathogens (bacterial species) is performed by using machine learning algorithms on the generated single-cell signals. The high predictive performance of the machine learning models indicates that the produced bacterial signatures constitute an informative representation, helpful in distinguishing the different bacterial species. In addition, we reformulate the bacterial species identification problem as a time series classification task by considering the intensity sequences of a given spectrum as time series values. Experimental results show that algorithms originally introduced for time series analysis are beneficial in modelling observations of single-cell MALDI-TOF MS. © 2019 for this paper by its authors.

关键词： Mass spectrometry

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A COMPARATIVE SURVEY OF VISION TRANSFORMERS FOR FEATURE EXTRACTION IN TEXTURE analysis

arXiv

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arXiv 2024年

作者： Scabini, Leonardo Sacilotti, Andre Zielinski, Kallil M. Ribas, Lucas C. De Baets, Bernard Bruno, Odemir M. São Carlos Institute of Physics University of São Paulo SP São Carlos13560-970 Brazil Institute of Mathematics and Computer Sciences University of São Paulo SP São Carlos135666-590 Brazil Institute of Biosciences Humanities and Exact Sciences São Paulo State University São José do Rio Preto15054-000 Brazil KERMIT Department of Data Analysis and Mathematical Modelling Ghent University Coupure links 653 Ghent9000 Belgium

Texture, a significant visual attribute in images, has been extensively investigated across various image recognition applications. Convolutional Neural Networks (CNNs), which have been successful in many computer vision tasks, are currently among the best texture analysis approaches. On the other hand, Vision Transformers (ViTs) have been surpassing the performance of CNNs on tasks such as object recognition, causing a paradigm shift in the field. However, ViTs have so far not been scrutinized for texture recognition, hindering a proper appreciation of their potential in this specific setting. For this reason, this work explores various pre-trained ViT architectures when transferred to tasks that rely on textures. We review 21 different ViT variants and perform an extensive evaluation and comparison with CNNs and hand-engineered models on several tasks, such as assessing robustness to changes in texture rotation, scale, and illumination, and distinguishing color textures, material textures, and texture attributes. The goal is to understand the potential and differences among these models when directly applied to texture recognition, using pre-trained ViTs primarily for feature extraction and employing linear classifiers for evaluation. We also evaluate their efficiency, which is one of the main drawbacks in contrast to other methods. Our results show that ViTs generally outperform both CNNs and hand-engineered models, especially when using stronger pre-training and tasks involving in-the-wild textures (images from the internet). We highlight the following promising models: ViT-B with DINO pre-training, BeiTv2, and the Swin architecture, as well as the EfficientFormer as a low-cost alternative. In terms of efficiency, although having a higher number of GFLOPs and parameters, ViT-B and BeiT(v2) can achieve a lower feature extraction time on GPUs compared to ResNet50. © 2024, CC BY-NC-SA.

关键词： Textures

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Automated Artemia detection and length measurement using deep convolutional networks 31

Automated Artemia detection and length measurement using dee...

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31st Benelux Conference on Artificial Intelligence and the 28th Belgian Dutch Conference on Machine Learning, BNAIC/BENELEARN 2019

作者： Wang, Gang De Baets, Bernard KERMIT Department of Data Analysis and Mathematical Modelling Ghent University Coupure links 653 GentB-9000 Belgium

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457 Comparative whole metagenome sequencing analysis in psoriasis capitis patients and healthy individuals

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Journal of Investigative Dermatology 2024年第8期144卷 S79-S79页

作者： B. De Pessemier C. López S. Taelman A. Stockman J. Lambert T. Van de Wiele C. Callewaert CMET Ghent University Ghent Belgium Data Analysis and Mathematical Modelling Ghent University Ghent Belgium Biolizard Ghent Belgium Dermatology AZ Delta Torhout Belgium Department of Head & Skin Ghent University Ghent Belgium

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Cellular automata can really solve the parity problem

arXiv

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arXiv 2025年

作者： Wolnik, Barbara Nenca, Anna Balbi, Pedro Paulo De Baets, Bernard Institute of Mathematics Faculty of Mathematics Physics and Informatics University of Gdańsk Gdańsk80-308 Poland Institute of Informatics Faculty of Mathematics Physics and Informatics University of Gdańsk Gdańsk80-308 Poland Faculdade de Computação e Informática Universidade Presbiteriana Mackenzie Rua da Consolação 896 Consolação SP São Paulo01302-907 Brazil KERMIT Department of Data Analysis and Mathematical Modelling Faculty of Bioscience Engineering Ghent University Coupure links 653 GentB-9000 Belgium

Determining properties of an arbitrary binary sequence is a challenging task if only local processing is allowed. Among these properties, the determination of the parity of 1s by distributed consensus has been a recurring endeavour in the context of automata networks. In its most standard formulation, a one-dimensional cellular automaton rule should process any odd-sized cyclic configuration and lead the lattice to converge to the homogeneous fixed point of 0s if the parity of 1s is even and to the homogeneous fixed point of 1s, otherwise. The only known solution to this problem with a single rule was given by Betel, de Oliveira and Flocchini (coined BFO rule after the authors’ initials). However, three years later the authors of the BFO rule realised that the rule would fail for some specific configuration and proposed a computationally sound fix, but a proof could not be worked out. Here we provide another fix to the BFO rule along with a full proof, therefore reassuring that a single-rule solution to the problem really does exist. © 2025, CC BY.

关键词： Binary sequences

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Best practices for estimating and reporting epidemiological delay distributions of infectious diseases using public health surveillance and healthcare data

arXiv

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arXiv 2024年

作者： Charniga, Kelly Park, Sang Woo Akhmetzhanov, Andrei R. Cori, Anne Dushoff, Jonathan Funk, Sebastian Gostic, Katelyn M. Linton, Natalie M. Lison, Adrian Overton, Christopher E. Pulliam, Juliet R.C. Ward, Thomas Cauchemez, Simon Abbott, Sam Mathematical Modelling of Infectious Diseases Unit Institut Pasteur Université Paris Cité CNRS UMR 2000 Paris France Department of Ecology and Evolutionary Biology Princeton University PrincetonNJ United States College of Public Health National Taiwan University Taipei Taiwan MRC Centre for Global Infectious Disease Analysis School of Public Health Imperial College London London United Kingdom Departments of Mathematics & Statistics and Biology McMaster University HamiltonON Canada Department of Biology McMaster University HamiltonON Canada M. G. DeGroote Institute for Infectious Disease Research McMaster University HamiltonON Canada Department of Infectious Disease Epidemiology and Dynamics London School of Hygiene & Tropical Medicine London United Kingdom Centre for Mathematical Modelling of Infectious Diseases London School of Hygiene & Tropical Medicine London United Kingdom Center for Forecasting and Outbreak Analytics U.S. Centers for Disease Control and Prevention AtlantaGA United States Graduate School of Medicine Hokkaido University Sapporo-shi Hokkaido Japan Department of Biosystems Science and Engineering ETH Zurich Zurich Switzerland Department of Mathematical Sciences University of Liverpool Liverpool United Kingdom All Hazards Intelligence Infectious Disease Modelling Team Data Analytics and Surveillance UK Health Security Agency United Kingdom Department of Mathematics University of Manchester Manchester United Kingdom

Epidemiological delays, such as incubation periods, serial intervals, and hospital lengths of stay, are among key quantities in infectious disease epidemiology that inform public health policy and clinical practice. This information is used to inform mathematical and statistical models, which in turn can inform control strategies. There are three main challenges that make delay distributions difficult to estimate. First, the data are commonly censored (e.g., symptom onset may only be reported by date instead of the exact time of day). Second, delays are often right truncated when being estimated in real time (not all events that have occurred have been observed yet). Third, during a rapidly growing or declining outbreak, overrepresentation or underrepresentation, respectively, of recently infected cases in the data can lead to bias in estimates. Studies that estimate delays rarely address all these factors and sometimes report several estimates using different combinations of adjustments, which can lead to conflicting answers and confusion about which estimates are most accurate. In this work, we formulate a checklist of best practices for estimating and reporting epidemiological delays with a focus on the incubation period and serial interval. We also propose strategies for handling common biases and identify areas where more work is needed. Our recommendations can help improve the robustness and utility of reported estimates and provide guidance for the evaluation of estimates for downstream use in transmission models or other analyses. Copyright © 2024, The Authors. All rights reserved.

关键词： Diseases

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Investigating the trade-off between infections and social interactions using a compact model of endemic infections on networks

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Mathematics in Medical and Life Sciences 2025年第1期2卷

作者： Bunlang Thatchai Christopher E. Overton Thomas House a Department of Mathematics School of Natural Sciences The University of Manchester Manchester UK b Department of Mathematical Sciences School of Physical Sciences University of Liverpool Liverpool UKc Modelling Division Analysis and Intelligence Assessment Chief Data Officer Group UK Health Security Agency London UK

This paper is part of a special issue on Behavioural *** many epidemiological and ecological contexts, there is a trade-off between infections and interactions. This arises because the links between individuals capable of spreading infections are also often associated with beneficial activities. Here, we consider how the presence of explicit network structure changes the optimal solution of a class of infection-interaction trade-offs. In order to do this, we develop and analyse a low-dimensional dynamical system approximating the network SIS epidemic. We find that network structure in the form of heterogeneous numbers of contacts can have a significant impact on the optimal number of contacts that comes out of a trade-off *** LANGUAGE SUMMARYHumans and other species benefit from interacting with each other, but at the same time such contact can spread infection. This can lead to a trade-off between the costs and benefits of contact. Here, we develop a parsimonious mathematical model of susceptible-infectious-susceptible (SIS) epidemic dynamics on a social contact network. We then use this to investigate the impacts of the structure of such contact networks on infection-interaction trade-offs given different models of benefits. We find that in many cases the quantitative and qualitative impacts of contact network structure are important for quantifying these trade-offs.

关键词： Susceptible-infective-susceptible model pairwise approximation endemic equilibrium random graph benefit of individual interaction cost-benefit analysis

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Parsimonious time series models on air pollution index in Malaysia: A comparative study

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AIP Conference Proceedings 2024年第1期3150卷

作者： Loh Jun Heng Nurulkamal Masseran Department of Mathematical Sciences Faculty of Science and Technology Universiti Kebangsaan Malaysia 43600 UKM Bangi Selangor Malaysia Center for Modelling and Data Analysis (DELTA) Faculty of Science and Technology Universiti Kebangsaan Malaysia 43600 UKM Bangi Selangor Malaysia.

A statistical modeling of air pollution index data can provide useful information about the characteristics and behaviors of air pollution events. This study evaluates the performance of the three parsimonious time series model on API data in Malaysia, which are: autoregressive integrated moving average, seasonal autoregressive integrated moving average, fuzzy time series, and artificial neural networks. A case study involving the analysis and modeling of API data for 16 locations in Malaysia is conducted. Results show that the API values fall between good and moderate levels. Some large fluctuations of the APIs are found to be mainly due to haze events. Modeling results indicate that the ARIMA method is highly applicable to the accurate prediction of API values in most cases. Nevertheless, the other forecasting methods could serve as good alternatives because of their similar performance to the ARIMA method.

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