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3,993 results on '"Silva, Sara"'

53. Glucocorticoid receptor-dependent therapeutic efficacy of tauroursodeoxycholic acid in preclinical models of spinocerebellar ataxia type 3

Author

Duarte-Silva, Sara, Da Silva, Jorge Diogo, Monteiro-Fernandes, Daniela, Costa, Marta Daniela, Neves-Carvalho, Andreia, Raposo, Mafalda, Soares-Cunha, Carina, Correia, Joana S., Nogueira- Goncalves, Goncalo, Fernandes, Henrique S., Oliveira, Stephanie, Ferreira-Fernandes, Ana Rita, Rodrigues, Fernando, Pereira-Sousa, Joana, Vilasboas-Campos, Daniela, Guerreiro, Sara, Campos, Jonas, Meireles- Costa, Liliana, Rodrigues, Cecilia M.P., Cabantous, Stephanie, Sousa, Sergio F., Lima, Manuela, Teixeira-Castro, Andreia, and Maciel, Patricia

Subjects
Thermo Fisher Scientific Inc., Medical research -- Models -- Health aspects, Medicine, Experimental -- Models -- Health aspects, Nematoda -- Models -- Health aspects, Scientific equipment and supplies industry -- Health aspects -- Models, Corticosteroids -- Health aspects -- Models, Spinocerebellar ataxia -- Models -- Health aspects, Bile acids -- Models -- Health aspects, Genes -- Models -- Health aspects, Proteolysis -- Health aspects -- Models, Nervous system diseases -- Health aspects -- Models, Health care industry
Abstract

Spinocerebellar ataxia type 3 (SCA3) is an adult-onset neurodegenerative disease caused by a polyglutamine expansion in the ataxin-3 (ATXN3) gene. No effective treatment is available for this disorder, other than symptom-directed approaches. Bile acids have shown therapeutic efficacy in neurodegenerative disease models. Here, we pinpointed tauroursodeoxycholic acid (TUDCA) as an efficient therapeutic, improving the motor and neuropathological phenotype of SCA3 nematode and mouse models. Surprisingly, transcriptomic and functional in vivo data showed that TUDCA acts in neuronal tissue through the glucocorticoid receptor (GR), but independently of its canonical receptor, the farnesoid X receptor (FXR). TUDCA was predicted to bind to the GR, in a similar fashion to corticosteroid molecules. GR levels were decreased in disease-affected brain regions, likely due to increased protein degradation as a consequence of ATXN3 dysfunction being restored by TUDCA treatment. Analysis of a SCA3 clinical cohort showed intriguing correlations between the peripheral expression of GR and the predicted age at disease onset in presymptomatic subjects and FKBP5 expression with disease progression, suggesting this pathway as a potential source of biomarkers for future study. We have established a novel in vivo mechanism for the neuroprotective effects of TUDCA in SCA3 and propose this readily available drug for clinical trials in SCA3 patients., Introduction Neurodegenerative diseases are currently considered a growing epidemic in the aging population (1, 2), still lacking effective therapeutic options. For those disorders with an identified genetic cause, research has [...]

Published
2024
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54. The gut microbiota contributes to the pathogenesis of anorexia nervosa in humans and mice

Author

Fan, Yong, Støving, René Klinkby, Berreira Ibraim, Samar, Hyötyläinen, Tuulia, Thirion, Florence, Arora, Tulika, Lyu, Liwei, Stankevic, Evelina, Hansen, Tue Haldor, Déchelotte, Pierre, Sinioja, Tim, Ragnarsdottir, Oddny, Pons, Nicolas, Galleron, Nathalie, Quinquis, Benoît, Levenez, Florence, Roume, Hugo, Falony, Gwen, Vieira-Silva, Sara, Raes, Jeroen, Clausen, Loa, Telléus, Gry Kjaersdam, Bäckhed, Fredrik, Oresic, Matej, Ehrlich, S. Dusko, and Pedersen, Oluf

Published
2023
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60. Antibody agonists trigger immune receptor signaling through local exclusion of receptor-type protein tyrosine phosphatases

Author

Lippert, Anna H., Paluch, Christopher, Gaglioni, Meike, Vuong, Mai T., McColl, James, Jenkins, Edward, Fellermeyer, Martin, Clarke, Joseph, Sharma, Sumana, Moreira da Silva, Sara, Akkaya, Billur, Anzilotti, Consuelo, Morgan, Sara H., Jessup, Claire F., Körbel, Markus, Gileadi, Uzi, Leitner, Judith, Knox, Rachel, Chirifu, Mami, Huo, Jiandong, Yu, Susan, Ashman, Nicole, Lui, Yuan, Wilkinson, Ian, Attfield, Kathrine E., Fugger, Lars, Robertson, Nathan J., Lynch, Christopher J., Murray, Lynne, Steinberger, Peter, Santos, Ana Mafalda, Lee, Steven F., Cornall, Richard J., Klenerman, David, and Davis, Simon J.

Published
2024
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62. Prosocial Tendencies Measure Validation for Portuguese Late Adolescents

Author

Costa, Marisa, Veríssimo, Lurdes, Barbosa, Mariana, Ribeiro, Luísa Mota, Silva, Sara, and Carlo, Gustavo

Abstract

The Prosocial Tendencies Measure (PTM; Carlo & Randall, 2002) is widely used for assessing prosocial tendencies. Assuming that there are differences in prosocial behavior between adolescents and adults, the current study aimed to further validate the Portuguese version of the PTM for adolescents. This instrument assesses six different types of prosocial tendencies – altruism, anonymous, dire, emotional, compliant and public. Designed to confirm this structure with Portuguese adolescents, this study collected a total of 1313 high school students’ prosocial behaviors perceptions. Confirmatory factor analysis corroborated the six-factor structure of the original validation. Furthermore, considering the students’ school year and gender, invariance analysis was executed and attested the PTM’s configural, metric (partially for gender) and scalar (partially for school year and gender) invariance. These findings further demonstrate that the Portuguese version of the PTM is reliable, enhancing the utility of this instrument to assess prosocial behaviors in adolescence.

Published
2022

63. Plotting time: On the usage of CNNs for time series classification

Author

Rodrigues, Nuno M., Batista, João E., Trujillo, Leonardo, Duarte, Bernardo, Giacobini, Mario, Vanneschi, Leonardo, and Silva, Sara

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence
Abstract

We present a novel approach for time series classification where we represent time series data as plot images and feed them to a simple CNN, outperforming several state-of-the-art methods. We propose a simple and highly replicable way of plotting the time series, and feed these images as input to a non-optimized shallow CNN, without any normalization or residual connections. These representations are no more than default line plots using the time series data, where the only pre-processing applied is to reduce the number of white pixels in the image. We compare our method with different state-of-the-art methods specialized in time series classification on two real-world non public datasets, as well as 98 datasets of the UCR dataset collection. The results show that our approach is very promising, achieving the best results on both real-world datasets and matching / beating the best state-of-the-art methods in six UCR datasets. We argue that, if a simple naive design like ours can obtain such good results, it is worth further exploring the capabilities of using image representation of time series data, along with more powerful CNNs, for classification and other related tasks.

Published
2021

64. Feature Selection on Epistatic Problems Using Genetic Algorithms with Nested Classifiers

Author

Carvalho, Pedro, Ribeiro, Bruno, Rodrigues, Nuno M., Batista, João E., Vanneschi, Leonardo, Silva, Sara, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Correia, João, editor, Smith, Stephen, editor, and Qaddoura, Raneem, editor

Published
2023
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65. Beyond the Norm: Epidemiology of Irritable Bowel Syndrome and Mental Health Among Sexual and Gender-Diverse Young Adults in a Large Representative Cohort

Author

Voorspoels, Wouter, Proost, Sebastian, Mortier, Philippe, Kiekens, Glenn, Alonso, Jordi, Raes, Jeroen, Falony, Gwen, Vieira-Silva, Sara, van Oudenhove, Lukas, Cuijpers, Pim, Auerbach, Randy P., Bootsma, Erik, Jansen, Leontien, Van Den Houte, Karen, Kessler, Ronald C., Tack, Jan, and Bruffaerts, Ronny

Published
2024
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66. Rigorous Donor Selection for Fecal Microbiota Transplantation in Active Ulcerative Colitis: Key Lessons From a Randomized Controlled Trial Halted for Futility

Author

Caenepeel, Clara, Deleu, Sara, Vazquez Castellanos, Jorge Francisco, Arnauts, Kaline, Braekeleire, Sara, Machiels, Kathleen, Baert, Filip, Mana, Fazia, Pouillon, Lieven, Hindryckx, Pieter, Lobaton, Triana, Louis, Edouard, Franchimont, Denis, Verstockt, Bram, Ferrante, Marc, Sabino, João, Vieira-Silva, Sara, Falony, Gwen, Raes, Jeroen, and Vermeire, Séverine

Published
2024
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70. Improving the Detection of Burnt Areas in Remote Sensing using Hyper-features Evolved by M3GP

Author

Batista, João E. and Silva, Sara

Subjects
Computer Science - Machine Learning, Electrical Engineering and Systems Science - Image and Video Processing, Statistics - Machine Learning
Abstract

One problem found when working with satellite images is the radiometric variations across the image and different images. Intending to improve remote sensing models for the classification of burnt areas, we set two objectives. The first is to understand the relationship between feature spaces and the predictive ability of the models, allowing us to explain the differences between learning and generalization when training and testing in different datasets. We find that training on datasets built from more than one image provides models that generalize better. These results are explained by visualizing the dispersion of values on the feature space. The second objective is to evolve hyper-features that improve the performance of different classifiers on a variety of test sets. We find the hyper-features to be beneficial, and obtain the best models with XGBoost, even if the hyper-features are optimized for a different method.

Published
2020

71. A Study of Fitness Landscapes for Neuroevolution

Author

Rodrigues, Nuno M., Silva, Sara, and Vanneschi, Leonardo

Subjects
Computer Science - Neural and Evolutionary Computing, Computer Science - Machine Learning
Abstract

Fitness landscapes are a useful concept to study the dynamics of meta-heuristics. In the last two decades, they have been applied with success to estimate the optimization power of several types of evolutionary algorithms, including genetic algorithms and genetic programming. However, so far they have never been used to study the performance of machine learning algorithms on unseen data, and they have never been applied to neuroevolution. This paper aims at filling both these gaps, applying for the first time fitness landscapes to neuroevolution and using them to infer useful information about the predictive ability of the method. More specifically, we use a grammar-based approach to generate convolutional neural networks, and we study the dynamics of three different mutations to evolve them. To characterize fitness landscapes, we study autocorrelation and entropic measure of ruggedness. The results show that these measures are appropriate for estimating both the optimization power and the generalization ability of the considered neuroevolution configurations., Comment: IEE CEC submission

Published
2020

72. Ensemble Genetic Programming

Author

Rodrigues, Nuno M., Batista, João E., and Silva, Sara

Subjects
Computer Science - Neural and Evolutionary Computing, Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

Ensemble learning is a powerful paradigm that has been usedin the top state-of-the-art machine learning methods like Random Forestsand XGBoost. Inspired by the success of such methods, we have devel-oped a new Genetic Programming method called Ensemble GP. The evo-lutionary cycle of Ensemble GP follows the same steps as other GeneticProgramming systems, but with differences in the population structure,fitness evaluation and genetic operators. We have tested this method oneight binary classification problems, achieving results significantly betterthan standard GP, with much smaller models. Although other methodslike M3GP and XGBoost were the best overall, Ensemble GP was able toachieve exceptionally good generalization results on a particularly hardproblem where none of the other methods was able to succeed., Comment: eurogp 2020 submission

Published
2020

75. Large-scale association analyses identify host factors influencing human gut microbiome composition

Author

Kurilshikov, Alexander, Medina-Gomez, Carolina, Bacigalupe, Rodrigo, Radjabzadeh, Djawad, Wang, Jun, Demirkan, Ayse, Le Roy, Caroline I, Raygoza Garay, Juan Antonio, Finnicum, Casey T, Liu, Xingrong, Zhernakova, Daria V, Bonder, Marc Jan, Hansen, Tue H, Frost, Fabian, Rühlemann, Malte C, Turpin, Williams, Moon, Jee-Young, Kim, Han-Na, Lüll, Kreete, Barkan, Elad, Shah, Shiraz A, Fornage, Myriam, Szopinska-Tokov, Joanna, Wallen, Zachary D, Borisevich, Dmitrii, Agreus, Lars, Andreasson, Anna, Bang, Corinna, Bedrani, Larbi, Bell, Jordana T, Bisgaard, Hans, Boehnke, Michael, Boomsma, Dorret I, Burk, Robert D, Claringbould, Annique, Croitoru, Kenneth, Davies, Gareth E, van Duijn, Cornelia M, Duijts, Liesbeth, Falony, Gwen, Fu, Jingyuan, van der Graaf, Adriaan, Hansen, Torben, Homuth, Georg, Hughes, David A, Ijzerman, Richard G, Jackson, Matthew A, Jaddoe, Vincent WV, Joossens, Marie, Jørgensen, Torben, Keszthelyi, Daniel, Knight, Rob, Laakso, Markku, Laudes, Matthias, Launer, Lenore J, Lieb, Wolfgang, Lusis, Aldons J, Masclee, Ad AM, Moll, Henriette A, Mujagic, Zlatan, Qibin, Qi, Rothschild, Daphna, Shin, Hocheol, Sørensen, Søren J, Steves, Claire J, Thorsen, Jonathan, Timpson, Nicholas J, Tito, Raul Y, Vieira-Silva, Sara, Völker, Uwe, Völzke, Henry, Võsa, Urmo, Wade, Kaitlin H, Walter, Susanna, Watanabe, Kyoko, Weiss, Stefan, Weiss, Frank U, Weissbrod, Omer, Westra, Harm-Jan, Willemsen, Gonneke, Payami, Haydeh, Jonkers, Daisy MAE, Arias Vasquez, Alejandro, de Geus, Eco JC, Meyer, Katie A, Stokholm, Jakob, Segal, Eran, Org, Elin, Wijmenga, Cisca, Kim, Hyung-Lae, Kaplan, Robert C, Spector, Tim D, Uitterlinden, Andre G, Rivadeneira, Fernando, Franke, Andre, Lerch, Markus M, Franke, Lude, Sanna, Serena, D’Amato, Mauro, and Pedersen, Oluf

Subjects
Microbiology, Biological Sciences, Genetics, Human Genome, Biotechnology, Clinical Research, Digestive Diseases, Nutrition, 2.1 Biological and endogenous factors, Aetiology, Oral and gastrointestinal, Adolescent, Adult, Bifidobacterium, Child, Child, Preschool, Cohort Studies, Female, Gastrointestinal Microbiome, Genetic Variation, Genome-Wide Association Study, Humans, Lactase, Linkage Disequilibrium, Male, Mendelian Randomization Analysis, Metabolism, Quantitative Trait Loci, RNA, Ribosomal, 16S, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

To study the effect of host genetics on gut microbiome composition, the MiBioGen consortium curated and analyzed genome-wide genotypes and 16S fecal microbiome data from 18,340 individuals (24 cohorts). Microbial composition showed high variability across cohorts: only 9 of 410 genera were detected in more than 95% of samples. A genome-wide association study of host genetic variation regarding microbial taxa identified 31 loci affecting the microbiome at a genome-wide significant (P

Published
2021

81. A synthesis of bacterial and archaeal phenotypic trait data.

Author

Madin, Joshua S, Nielsen, Daniel A, Brbic, Maria, Corkrey, Ross, Danko, David, Edwards, Kyle, Engqvist, Martin KM, Fierer, Noah, Geoghegan, Jemma L, Gillings, Michael, Kyrpides, Nikos C, Litchman, Elena, Mason, Christopher E, Moore, Lisa, Nielsen, Søren L, Paulsen, Ian T, Price, Nathan D, Reddy, TBK, Richards, Matthew A, Rocha, Eduardo PC, Schmidt, Thomas M, Shaaban, Heba, Shukla, Maulik, Supek, Fran, Tetu, Sasha G, Vieira-Silva, Sara, Wattam, Alice R, Westfall, David A, and Westoby, Mark

Subjects
Bacteria, Archaea, Ecosystem, Phenotype, Genome, Bacterial, Genome, Archaeal
Abstract

A synthesis of phenotypic and quantitative genomic traits is provided for bacteria and archaea, in the form of a scripted, reproducible workflow that standardizes and merges 26 sources. The resulting unified dataset covers 14 phenotypic traits, 5 quantitative genomic traits, and 4 environmental characteristics for approximately 170,000 strain-level and 15,000 species-aggregated records. It spans all habitats including soils, marine and fresh waters and sediments, host-associated and thermal. Trait data can find use in clarifying major dimensions of ecological strategy variation across species. They can also be used in conjunction with species and abundance sampling to characterize trait mixtures in communities and responses of traits along environmental gradients.

Published
2020

82. Deficiency in classical nonhomologous end-joining–mediated repair of transcribed genes is linked to SCA3 pathogenesis

Author

Chakraborty, Anirban, Tapryal, Nisha, Venkova, Tatiana, Mitra, Joy, Vasquez, Velmarini, Sarker, Altaf H, Duarte-Silva, Sara, Huai, Weihan, Ashizawa, Tetsuo, Ghosh, Gourisankar, Maciel, Patricia, Sarkar, Partha S, Hegde, Muralidhar L, Chen, Xu, and Hazra, Tapas K

Subjects
Biochemistry and Cell Biology, Biomedical and Clinical Sciences, Biological Sciences, Neurodegenerative, Rare Diseases, Brain Disorders, Neurosciences, Genetics, 2.1 Biological and endogenous factors, Aetiology, Neurological, Aged, 80 and over, Animals, Animals, Genetically Modified, Ataxin-3, Brain, Cell Line, DNA Breaks, Double-Stranded, DNA End-Joining Repair, DNA Repair Enzymes, Disease Models, Animal, Drosophila, Female, Gene Knockdown Techniques, Humans, Induced Pluripotent Stem Cells, Machado-Joseph Disease, Male, Mice, Middle Aged, Mutation, Peptides, Phosphotransferases (Alcohol Group Acceptor), RNA Polymerase II, RNA, Small Interfering, Repressor Proteins, ATXN3, DNA double-strand break repair, PNKP, RNA-templated TC-NHEJ, spinocerebellar ataxia type-3
Abstract

Spinocerebellar ataxia type 3 (SCA3) is a dominantly inherited neurodegenerative disease caused by CAG (encoding glutamine) repeat expansion in the Ataxin-3 (ATXN3) gene. We have shown previously that ATXN3-depleted or pathogenic ATXN3-expressing cells abrogate polynucleotide kinase 3'-phosphatase (PNKP) activity. Here, we report that ATXN3 associates with RNA polymerase II (RNAP II) and the classical nonhomologous end-joining (C-NHEJ) proteins, including PNKP, along with nascent RNAs under physiological conditions. Notably, ATXN3 depletion significantly decreased global transcription, repair of transcribed genes, and error-free double-strand break repair of a 3'-phosphate-containing terminally gapped, linearized reporter plasmid. The missing sequence at the terminal break site was restored in the recircularized plasmid in control cells by using the endogenous homologous transcript as a template, indicating ATXN3's role in PNKP-mediated error-free C-NHEJ. Furthermore, brain extracts from SCA3 patients and mice show significantly lower PNKP activity, elevated p53BP1 level, more abundant strand-breaks in the transcribed genes, and degradation of RNAP II relative to controls. A similar RNAP II degradation is also evident in mutant ATXN3-expressing Drosophila larval brains and eyes. Importantly, SCA3 phenotype in Drosophila was completely amenable to PNKP complementation. Hence, salvaging PNKP's activity can be a promising therapeutic strategy for SCA3.

Published
2020

88. Lippia grata essential oil complexed with β-cyclodextrin ameliorates biochemical and behavioral deficits in an animal model of progressive parkinsonism

Author

Beserra-Filho, Jose Ivo A., Maria-Macêdo, Amanda, Silva-Martins, Suellen, Custódio-Silva, Ana Cláudia, Soares-Silva, Beatriz, Silva, Sara Pereira, Lambertucci, Rafael Herling, de Souza Araújo, Adriano Antunes, Lucchese, Angélica Maria, Quintans-Júnior, Lucindo J., Santos, José Ronaldo, Silva, Regina H., and Ribeiro, Alessandra M.

Published
2022
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98. ALTERAÇÕES LABORATORIAIS NA SÍNDROME DE HAFF

Author

Conceição, Suyanne de Paiva da, primary, Soares, Vitória Alves, additional, Carneiro, Ellen Laryssa da Costa, additional, Silva, Cleicielle Magalhães, additional, Silva, Sara dos Santos, additional, and Serra, Mariana Barreto, additional

Published
2023
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99. The Supervised Semantic Similarity Toolkit

Author

Sousa, Rita T., Silva, Sara, Pesquita, Catia, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Groth, Paul, editor, Rula, Anisa, editor, Schneider, Jodi, editor, Tiddi, Ilaria, editor, Simperl, Elena, editor, Alexopoulos, Panos, editor, Hoekstra, Rinke, editor, Alam, Mehwish, editor, Dimou, Anastasia, editor, and Tamper, Minna, editor

Published
2022
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100. SLUG: Feature Selection Using Genetic Algorithms and Genetic Programming

Author

Rodrigues, Nuno M., Batista, João E., La Cava, William, Vanneschi, Leonardo, Silva, Sara, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Medvet, Eric, editor, Pappa, Gisele, editor, and Xue, Bing, editor

Published
2022
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