Feature integration
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The autonomous transcription of integrated retroviruses strongly depends on genetic and epigenetic effects of the chromatin at the site of integration. These effects are mostly suppressive and proviral activity can be finally silenced by mechanisms, such as DNA methylation and histone modifications. To address the role of the integration site at the whole-genome-scale, we performed clonal analysis of provirus silencing with an avian leucosis/sarcoma virus-based reporter vector and correlated the transcriptional silencing with the epigenomic landscape of respective integrations. We demonstrate efficient provirus silencing in human HCT116 cell line, which is strongly but not absolutely dependent on the de novo DNA methyltransferase activity, particularly of Dnmt3b. Proviruses integrated close to the transcription start sites of active genes into the regions enriched in H3K4 trimethylation display long-term stability of expression and are resistant to the transcriptional silencing after over-expression of Dnmt3a or Dnmt3b. In contrast, proviruses in the intergenic regions tend to spontaneous transcriptional silencing even in Dnmt3a(-/-) Dnmt3b(-/-) cells. The silencing of proviruses within genes is accompanied with DNA methylation of long terminal repeats, whereas silencing in intergenic regions is DNA methylation-independent. These findings indicate that the epigenomic features of integration sites are crucial for their permissivity to the proviral expression.
- MeSH
- Alpharetrovirus genetika MeSH
- DNA methyltransferasa 3A MeSH
- DNA-(cytosin-5-)methyltransferasa genetika metabolismus MeSH
- DNA-methyltransferasa 3B MeSH
- epigeneze genetická * MeSH
- genetická transkripce MeSH
- integrace viru * MeSH
- lidé MeSH
- metylace DNA * MeSH
- nádorové buněčné linie MeSH
- proviry genetika MeSH
- umlčování genů * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Názvy látek
- DNA methyltransferasa 3A MeSH
- DNA-(cytosin-5-)methyltransferasa MeSH
- DNMT3A protein, human MeSH Prohlížeč
The transcriptional activity of an integrated retroviral copy strongly depends on the adjacent host-cell DNA at the site of integration. Transcribed DNA loci as well as cis-acting sequences like enhancers or CpG islands usually permit expression of nearby integrated proviruses. In contrast, proviruses residing close to cellular silencers tend to transcriptional silencing and CpG methylation. Little is known, however, about the influence of provirus integration on the target sequence in the host genome. Here, we report interesting features of a simplified Rous sarcoma virus integrated into a non-transcribed hypermethylated DNA sequence in the Syrian hamster genome. After integration, CpG methylation of this sequence has been lost almost completely and hypomethylated DNA permits proviral transcription and hamster cell transformation by the proviral v-src oncogene. This, however, is not a stable state, and non-transformed revertants bearing transcriptionally silenced proviruses segregate with a high rate. The provirus silencing is followed by DNA methylation of both provirus regulatory regions and adjacent cellular sequences. This CpG methylation is very dense and resistant to the demethylation effects of 5-aza-2(')-deoxycytidine and/or trichostatin A. Our description exemplifies the capacity of retroviruses/retroviral vectors to overcome, at least transiently, negative position effects of DNA methylation at the site of integration.
- MeSH
- agar farmakologie MeSH
- azacytidin analogy a deriváty farmakologie MeSH
- buněčné linie MeSH
- CpG ostrůvky MeSH
- decitabin MeSH
- genetická transkripce MeSH
- geny src genetika MeSH
- histondeacetylasy metabolismus MeSH
- inhibitory enzymů farmakologie MeSH
- inhibitory syntézy proteinů farmakologie MeSH
- integrace viru * MeSH
- koncové repetice MeSH
- křečci praví MeSH
- křeček rodu Mesocricetus MeSH
- kyseliny hydroxamové farmakologie MeSH
- metylace DNA * MeSH
- modely genetické MeSH
- molekulární sekvence - údaje MeSH
- nádorové buněčné linie MeSH
- Retroviridae genetika MeSH
- siřičitany farmakologie MeSH
- zvířata MeSH
- Check Tag
- křečci praví MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Názvy látek
- agar MeSH
- azacytidin MeSH
- decitabin MeSH
- histondeacetylasy MeSH
- inhibitory enzymů MeSH
- inhibitory syntézy proteinů MeSH
- kyseliny hydroxamové MeSH
- siřičitany MeSH
- trichostatin A MeSH Prohlížeč
Health monitoring and analysis of photovoltaic (PV) systems are critical for optimizing energy efficiency, improving reliability, and extending the operational lifespan of PV power plants. Effective fault detection and monitoring are vital for ensuring the proper functioning and maintenance of these systems. PV power plants operating under fault conditions show significant deviations in current-voltage (I-V) characteristics compared to those under normal conditions. This paper introduces a diagnostic methodology for photovoltaic panels using I-V curves, enhanced by new techniques combining optimization and classification-based artificial intelligence. The research is organized into two key sections. The first section outlines the implementation of a DC/DC buck-boost converter, which is designed to extract and display real-time data from the PV system based on actual (I-V) measurements. The second section focuses on the comprehensive processing of the experimental dataset, where the Harris Hawks Optimization (HHO) algorithm is combined with machine learning methods to identify the most critical features. The HHO algorithm is combined with an advanced machine learning model, XGBoost, to accurately detect faults within the PV system. The proposed HHO-XGBoost algorithm achieves an impressive accuracy of 99.49%, outperforming other classification-based artificial intelligence methods in fault detection. In validation and comparison with previous approaches, the HHO-XGBoost model consistently outperforms established methods such as GADF-ANN, PCA-SVM, PNN, and Fuzzy Logic, achieving an overall accuracy of 98.48%. This outstanding performance confirms the model's effectiveness in accurately diagnosing PV system conditions, further validating its robustness and reliability in fault detection and classification.
In gait stability analysis, patients suffering from dysfunction problems are impacted by shifts in their dynamic balance. Monitoring the patients' progress is important for allowing physicians and patients to observe the rehabilitation process accurately. In this study, we designed a new methodology for classifying gait disorders to quantify patients' progress. The dataset in this study includes 84 measurements of 37 patients based on a physician's opinion. In this study, the system, which includes a Kinect camera to observe and store the frames of patients walking down a hallway, a key-point detector to detect the skeletal key points, and an encoder transformer classifier network integrated with generator-discriminator networks (ET-GD), is designed to evaluate the classification of gait dysfunction. The detector extracts the skeletal key points of patients. After feature engineering, the selected high-level features are fed into the proposed neural network to analyse patient movement and perform the final evaluation of gait dysfunction. The proposed network is inspired by the 1D encoder transformer, which is integrated with two main networks: a network for classification and a network to generate fake output data similar to the input data. Furthermore, we used a discriminator structure to distinguish between the actual data (input) and fake data (generated data). Due to the multi-structural networks in the proposed method, multi-loss functions need to be optimised; this increases the accuracy of the encoder transformer classifier.
- Klíčová slova
- Autoencoder, Classification, Deep learning, Discriminator, Gait disorders, Vision transformer,
- MeSH
- analýza chůze MeSH
- chůze (způsob) * MeSH
- chůze MeSH
- lidé MeSH
- neuronové sítě MeSH
- pohybové poruchy * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Feature-based molecular networking (FBMN) is a popular analysis approach for liquid chromatography-tandem mass spectrometry-based non-targeted metabolomics data. While processing liquid chromatography-tandem mass spectrometry data through FBMN is fairly streamlined, downstream data handling and statistical interrogation are often a key bottleneck. Especially users new to statistical analysis struggle to effectively handle and analyze complex data matrices. Here we provide a comprehensive guide for the statistical analysis of FBMN results, focusing on the downstream analysis of the FBMN output table. We explain the data structure and principles of data cleanup and normalization, as well as uni- and multivariate statistical analysis of FBMN results. We provide explanations and code in two scripting languages (R and Python) as well as the QIIME2 framework for all protocol steps, from data clean-up to statistical analysis. All code is shared in the form of Jupyter Notebooks ( https://github.com/Functional-Metabolomics-Lab/FBMN-STATS ). Additionally, the protocol is accompanied by a web application with a graphical user interface ( https://fbmn-statsguide.gnps2.org/ ) to lower the barrier of entry for new users and for educational purposes. Finally, we also show users how to integrate their statistical results into the molecular network using the Cytoscape visualization tool. Throughout the protocol, we use a previously published environmental metabolomics dataset for demonstration purposes. Together, the protocol, code and web application provide a complete guide and toolbox for FBMN data integration, cleanup and advanced statistical analysis, enabling new users to uncover molecular insights from their non-targeted metabolomics data. Our protocol is tailored for the seamless analysis of FBMN results from Global Natural Products Social Molecular Networking and can be easily adapted to other mass spectrometry feature detection, annotation and networking tools.
The important role of humans in the development of current ecosystems was recognized decades ago; however, the integration of history and ecology in order to inform conservation has been difficult. We identified four issues that hinder historical ecological research and considered possible solutions. First, differences in concepts and methods between the fields of ecology and history are thought to be large. However, most differences stem from miscommunication between ecologists and historians and are less substantial than is usually assumed. Cooperation can be achieved by focusing on the features ecology and history have in common and through understanding and acceptance of differing points of view. Second, historical ecological research is often hampered by differences in spatial and temporal scales between ecology and history. We argue that historical ecological research can only be conducted at extents for which sources in both disciplines have comparable resolutions. Researchers must begin by clearly defining the relevant scales for the given purpose. Third, periods for which quantitative historical sources are not easily accessible (before AD 1800) have been neglected in historical ecological research. Because data from periods before 1800 are as relevant to the current state of ecosystems as more recent data, we suggest that historical ecologists actively seek out data from before 1800 and apply analytic methods commonly used in ecology to these data. Fourth, humans are not usually considered an intrinsic ecological factor in current ecological research. In our view, human societies should be acknowledged as integral parts of ecosystems and societal processes should be recognized as driving forces of ecosystem change.
- MeSH
- ekologie * MeSH
- zachování přírodních zdrojů * MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Starting from a novel rotaxane building block with dendrimer growth sites being located at both the wheel and axle component, we realized the successful construction of a new family of rotaxane-branched dendrimers, i.e., Type III-C rotaxane-branched dendrimers, up to fourth generation as a highly branched [46]rotaxane through a controllable divergent approach. In the resultant rotaxane-branched dendrimers, the wheel components of the rotaxane units are located on the branches as well as at the branching points, making them excellent candidates to mimic the amplified collective molecular motions. Thus, taking advantage of the urea moiety inserted into the axle components of the rotaxane units as the binding sites, the addition or removal of acetate anion as stimulus endows the individual rotaxane unit a switchable feature that lead to a collective expansion-contraction motion of the integrated rotaxane-branched dendrimers, thus allowing for the remarkable and reversible size modulation. Such a three-dimensional size switching feature makes Type III-C rotaxane-branched dendrimers a very promising platform toward the fabrication of novel dynamic smart materials.
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- MeSH
- akutní lymfatická leukemie diagnóza genetika metabolismus MeSH
- diferenciační antigeny genetika metabolismus MeSH
- exprese genu MeSH
- genová přestavba * MeSH
- homeodoménové proteiny genetika MeSH
- lidé MeSH
- membránové proteiny genetika metabolismus MeSH
- nádorové biomarkery * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- dopisy MeSH
- práce podpořená grantem MeSH
- Názvy látek
- diferenciační antigeny MeSH
- DUX4L1 protein, human MeSH Prohlížeč
- homeodoménové proteiny MeSH
- membránové proteiny MeSH
- nádorové biomarkery * MeSH
BACKGROUND: Photosynthetic microalgae have been in the spotlight of biotechnological production (biofuels, lipids, etc), however, current barriers in mass cultivation of microalgae are limiting its successful industrialization. Therefore, a mathematical model integrating both the biological and hydrodynamical parts of the cultivation process may improve our understanding of relevant phenomena, leading to further optimization of the microalgae cultivation. RESULTS: We introduce a unified multidisciplinary simulation tool for microalgae culture systems, particularly the photobioreactors. Our approach describes changes of cell growth determined by dynamics of heterogeneous environmental conditions such as irradiation and mixing of the culture. Presented framework consists of (i) a simplified model of microalgae growth in a culture system (the advection-diffusion-reaction system within a phenomenological model of photosynthesis and photoinhibition), (ii) the fluid dynamics (Navier-Stokes equations), and (iii) the irradiance field description (Beer-Lambert law). To validate the method, a simple case study leading to hydrodynamically induced fluctuating light conditions was chosen. The integration of computational fluid dynamics (ANSYS Fluent) revealed the inner property of the system, the flashing light enhancement phenomenon, known from experiments. CONCLUSION: Our physically accurate model of microalgae culture naturally exhibits features of real system, can be applied to any geometry of microalgae mass cultivation and thus is suitable for biotechnological applications.
- Klíčová slova
- CFD, Flashing light enhancement, Mathematical modeling, Microalgae, Microalgae culture systems, Photosynthesis,
- MeSH
- biologické modely MeSH
- fotosyntéza * MeSH
- hydrodynamika * MeSH
- kultivační techniky * MeSH
- mikrořasy růst a vývoj fyziologie účinky záření MeSH
- počítačová simulace MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Retroviruses and retrovirus-derived vectors integrate nonrandomly into the genomes of host cells with specific preferences for transcribed genes, gene-rich regions, and CpG islands. However, the genomic features that influence the transcriptional activities of integrated retroviruses or retroviral vectors are poorly understood. We report here the cloning and characterization of avian sarcoma virus integration sites from chicken tumors. Growing progressively, dependent on high and stable expression of the transduced v-src oncogene, these tumors represent clonal expansions of cells bearing transcriptionally active replication-defective proviruses. Therefore, integration sites in our study distinguished genomic loci favorable for the expression of integrated retroviruses and gene transfer vectors. Analysis of integration sites from avian sarcoma virus-induced tumors showed strikingly nonrandom distribution, with proviruses found prevalently within or close to transcription units, particularly in genes broadly expressed in multiple tissues but not in tissue-specifically expressed genes. We infer that proviruses integrated in these genomic areas efficiently avoid transcriptional silencing and remain active for a long time during the growth of tumors. Defining the differences between unselected retroviral integration sites and sites selected for long-terminal-repeat-driven gene expression is relevant for retrovirus-mediated gene transfer and has ramifications for gene therapy.
- MeSH
- chromozomy virologie MeSH
- exprese genu MeSH
- genetická terapie metody MeSH
- genetické vektory MeSH
- integrace viru * MeSH
- kur domácí MeSH
- proviry genetika fyziologie MeSH
- ptačí sarkom virologie MeSH
- viry ptačího sarkomu genetika fyziologie MeSH
- zvířata MeSH
- Check Tag
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
