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Erlinger M, Molina-Ruiz R, Brumby A, Cordas D, Hunter M, Ferreiro Arguelles C, Yus M, Owens-Walton C, Jakabek D, Shaw M, Lopez Valdes E, Looi JCL. Striatal and thalamic automatic segmentation, morphology, and clinical correlates in Parkinsonism: Parkinson's disease, multiple system atrophy and progressive supranuclear palsy. Psychiatry Res Neuroimaging 2023; 335:111719. [PMID: 37806261 DOI: 10.1016/j.pscychresns.2023.111719] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Revised: 09/20/2023] [Accepted: 09/23/2023] [Indexed: 10/10/2023]
Abstract
Parkinson's disease (PD), multisystem atrophy (MSA), and progressive supranuclear palsy (PSP) present similarly with bradykinesia, tremor, rigidity, and cognitive impairments. Neuroimaging studies have found differential changes in the nigrostriatal pathway in these disorders, however whether the volume and shape of specific regions within this pathway can distinguish between atypical Parkinsonian disorders remains to be determined. This paper investigates striatal and thalamic volume and morphology as distinguishing biomarkers, and their relationship to neuropsychiatric symptoms. Automatic segmentation to calculate volume and shape analysis of the caudate nucleus, putamen, and thalamus were performed in 18 PD patients, 12 MSA, 15 PSP, and 20 healthy controls, then correlated with clinical measures. PSP bilateral thalami and right putamen were significantly smaller than controls, but not MSA or PD. The left caudate and putamen significantly correlated with the Neuropsychiatric Inventory total score. Bilateral thalamus, caudate, and left putamen had significantly different morphology between groups, driven by differences between PSP and healthy controls. This study demonstrated that PSP patient striatal and thalamic volume and shape are significantly different when compared with controls. Parkinsonian disorders could not be differentiated on volumetry or morphology, however there are trends for volumetric and morphological changes associated with PD, MSA, and PSP.
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Affiliation(s)
- M Erlinger
- Research Centre for the Neurosciences of Ageing, Academic Unit of Psychiatry and Addiction Medicine, School of Clinical Medicine, Australian National University, Canberra, Australia.
| | | | - A Brumby
- Research Centre for the Neurosciences of Ageing, Academic Unit of Psychiatry and Addiction Medicine, School of Clinical Medicine, Australian National University, Canberra, Australia
| | - D Cordas
- Research Centre for the Neurosciences of Ageing, Academic Unit of Psychiatry and Addiction Medicine, School of Clinical Medicine, Australian National University, Canberra, Australia
| | - M Hunter
- Research Centre for the Neurosciences of Ageing, Academic Unit of Psychiatry and Addiction Medicine, School of Clinical Medicine, Australian National University, Canberra, Australia
| | | | - M Yus
- Hospital Clinico San Carlos, Madrid, Spain
| | - C Owens-Walton
- Research Centre for the Neurosciences of Ageing, Academic Unit of Psychiatry and Addiction Medicine, School of Clinical Medicine, Australian National University, Canberra, Australia
| | - D Jakabek
- Neuroscience Research Australia, Sydney, Australia
| | - M Shaw
- Hospital Clinico San Carlos, Madrid, Spain
| | | | - J C L Looi
- Research Centre for the Neurosciences of Ageing, Academic Unit of Psychiatry and Addiction Medicine, School of Clinical Medicine, Australian National University, Canberra, Australia
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Casanova-Alvarez O, Morales-Helguera A, Cabrera-Pérez MÁ, Molina-Ruiz R, Molina C. A Novel Automated Framework for QSAR Modeling of Highly Imbalanced Leishmania High-Throughput Screening Data. J Chem Inf Model 2021; 61:3213-3231. [PMID: 34191520 DOI: 10.1021/acs.jcim.0c01439] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
In silico prediction of antileishmanial activity using quantitative structure-activity relationship (QSAR) models has been developed on limited and small datasets. Nowadays, the availability of large and diverse high-throughput screening data provides an opportunity to the scientific community to model this activity from the chemical structure. In this study, we present the first KNIME automated workflow to modeling a large, diverse, and highly imbalanced dataset of compounds with antileishmanial activity. Because the data is strongly biased toward inactive compounds, a novel strategy was implemented based on the selection of different balanced training sets and a further consensus model using single decision trees as the base model and three criteria for output combinations. The decision tree consensus was adopted after comparing its classification performance to consensuses built upon Gaussian-Naı̈ve-Bayes, Support-Vector-Machine, Random-Forest, Gradient-Boost, and Multi-Layer-Perceptron base models. All these consensuses were rigorously validated using internal and external test validation sets and were compared against each other using Friedman and Bonferroni-Dunn statistics. For the retained decision tree-based consensus model, which covers 100% of the chemical space of the dataset and with the lowest consensus level, the overall accuracy statistics for test and external sets were between 71 and 74% and 71 and 76%, respectively, while for a reduced chemical space (21%) and with an incremental consensus level, the accuracy statistics were substantially improved with values for the test and external sets between 86 and 92% and 88 and 92%, respectively. These results highlight the relevance of the consensus model to prioritize a relatively small set of active compounds with high prediction sensitivity using the Incremental Consensus at high level values or to predict as many compounds as possible, lowering the level of Incremental Consensus. Finally, the workflow developed eliminates human bias, improves the procedure reproducibility, and allows other researchers to reproduce our design and use it in their own QSAR problems.
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Affiliation(s)
- Omar Casanova-Alvarez
- Departamento de Química, Facultad de Química-Farmacia, Universidad Central "Marta Abreu" de Las Villas, Santa Clara, Villa Clara 54830, Cuba
| | - Aliuska Morales-Helguera
- Centro de Bioactivos Químicos, Universidad Central "Marta Abreu" de Las Villas, Santa Clara, Villa Clara 54830, Cuba
| | - Miguel Ángel Cabrera-Pérez
- Centro de Bioactivos Químicos, Universidad Central "Marta Abreu" de Las Villas, Santa Clara, Villa Clara 54830, Cuba
| | - Reinaldo Molina-Ruiz
- Centro de Bioactivos Químicos, Universidad Central "Marta Abreu" de Las Villas, Santa Clara, Villa Clara 54830, Cuba
| | - Christophe Molina
- PIKAÏROS S.A., B03 - 2 Allée de la Clairière, 31650 Saint Orens de Gameville, France
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Agüero-Chapin G, Jiménez Y, Sánchez-Rodríguez A, Molina-Ruiz R, Vivanco O, Antunes A. DISTATIS: A Promising Framework to Integrate Distance Matrices in Molecular Phylogenetics. Curr Top Med Chem 2021; 21:599-611. [PMID: 33441066 DOI: 10.2174/1568026621666210113164605] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Revised: 12/16/2020] [Accepted: 12/21/2020] [Indexed: 11/22/2022]
Abstract
BACKGROUND Molecular phylogenetic algorithms frequently disagree with the approaches considering reproductive compatibility and morphological criteria for species delimitation. The question stems if the resulting species boundaries from molecular, reproductive and/or morphological data are definitively not reconcilable; or if the existing phylogenetic methods are not sensitive enough to agree morphological and genetic variation in species delimitation. OBJECTIVE We propose DISTATIS as an integrative framework to combine alignment-based (AB) and alignment-free (AF) distance matrices from ITS2 sequences/structures to shed light whether Gelasinospora and Neurospora are sister but independent genera. METHODS We aimed at addressing this standing issue by harmonizing genus-specific classification based on their ascospore morphology and ITS2 molecular data. To validate our proposal, three phylogenetic approaches: i) traditional alignment-based, ii) alignment-free and iii) novel distance integrative (DI)-based were comparatively evaluated on a set of Gelasinospora and Neurospora species. All considered species have been extensively characterized at both the morphological and reproductive levels and there are known incongruences between their ascospore morphology and molecular data that hampers genus-specific delimitation. RESULTS Traditional AB phylogenetic analyses fail at resolving the Gelasinospora and Neurospora genera into independent monophyletic clades following ascospore morphology criteria. In contrast, AF and DI approaches produced phylogenetic trees that could properly delimit the expected monophyletic clades. CONCLUSION The DI approach outperformed the AF one in the sense that it could also divide the Neurospora species according to their reproduction mode.
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Affiliation(s)
- Guillermin Agüero-Chapin
- CIMAR/CIIMAR, Centro Interdisciplinar de Investigacao Marinha e Ambiental & Departamento de Biologia, Faculdade de Ciencias, Universidade do Porto, Porto, Portugal
| | - Yuliana Jiménez
- Departamento de Quimica y Ciencias Exactas, Seccion de Fisicoquimica y Matematicas, Universidad Tecnica Particular de Loja (UTPL), Loja, Ecuador
| | - Aminael Sánchez-Rodríguez
- Departamento de Ciencias Biologicas, Seccion de Biotecnologia y Produccion, Universidad Tecnica Particular de Loja, Loja, Ecuador
| | - Reinaldo Molina-Ruiz
- Centro de Bioactivos Quimicos (CBQ), Universidad Central ¨Marta Abreu¨ de Las Villas, Santa Clara, Cuba
| | - Oscar Vivanco
- Departamento de Ciencias Biologicas, Seccion de Biotecnologia y Produccion, Universidad Tecnica Particular de Loja, Loja, Ecuador
| | - Agostinho Antunes
- CIMAR/CIIMAR, Centro Interdisciplinar de Investigacao Marinha e Ambiental & Departamento de Biologia, Faculdade de Ciencias, Universidade do Porto, Porto, Portugal
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Agüero-Chapin G, Galpert D, Molina-Ruiz R, Ancede-Gallardo E, Pérez-Machado G, De la Riva GA, Antunes A. Graph Theory-Based Sequence Descriptors as Remote Homology Predictors. Biomolecules 2019; 10:E26. [PMID: 31878100 PMCID: PMC7022958 DOI: 10.3390/biom10010026] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2019] [Revised: 12/16/2019] [Accepted: 12/18/2019] [Indexed: 12/23/2022] Open
Abstract
Alignment-free (AF) methodologies have increased in popularity in the last decades as alternative tools to alignment-based (AB) algorithms for performing comparative sequence analyses. They have been especially useful to detect remote homologs within the twilight zone of highly diverse gene/protein families and superfamilies. The most popular alignment-free methodologies, as well as their applications to classification problems, have been described in previous reviews. Despite a new set of graph theory-derived sequence/structural descriptors that have been gaining relevance in the detection of remote homology, they have been omitted as AF predictors when the topic is addressed. Here, we first go over the most popular AF approaches used for detecting homology signals within the twilight zone and then bring out the state-of-the-art tools encoding graph theory-derived sequence/structure descriptors and their success for identifying remote homologs. We also highlight the tendency of integrating AF features/measures with the AB ones, either into the same prediction model or by assembling the predictions from different algorithms using voting/weighting strategies, for improving the detection of remote signals. Lastly, we briefly discuss the efforts made to scale up AB and AF features/measures for the comparison of multiple genomes and proteomes. Alongside the achieved experiences in remote homology detection by both the most popular AF tools and other less known ones, we provide our own using the graphical-numerical methodologies, MARCH-INSIDE, TI2BioP, and ProtDCal. We also present a new Python-based tool (SeqDivA) with a friendly graphical user interface (GUI) for delimiting the twilight zone by using several similar criteria.
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Affiliation(s)
- Guillermin Agüero-Chapin
- CIIMAR/CIMAR, Interdisciplinary Centre of Marine and Environmental Research, University of Porto, Terminal de Cruzeiros do Porto de Leixões, Av. General Norton de Matos s/n 4450-208 Porto, Portugal
- Department of Biology, Faculty of Sciences, University of Porto, Rua do Campo Alegre, 4169-007 Porto, Portugal
| | - Deborah Galpert
- Departamento de Ciencia de la Computación. Universidad Central ¨Marta Abreu¨ de Las Villas (UCLV), Santa Clara 54830, Cuba;
| | - Reinaldo Molina-Ruiz
- Centro de Bioactivos Químicos (CBQ), Universidad Central ¨Marta Abreu¨ de Las Villas (UCLV), Santa Clara 54830, Cuba;
| | - Evys Ancede-Gallardo
- Programa de Doctorado en Fisicoquímica Molecular, Facultad de Ciencias Exactas, Universidad Andrés Bello, Av. República 239, Santiago 8370146, Chile;
| | - Gisselle Pérez-Machado
- EpiDisease S.L. Spin-Off of Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), 46980 Valencia, Spain;
| | - Gustavo A. De la Riva
- Laboratorio de Biotecnología Aplicada S. de R.L. de C.V., GRECA Inc., Carretera La Piedad-Carapán, km 3.5, La Piedad, Michoacán 59300, Mexico;
- Tecnológico Nacional de México, Instituto Tecnológico de la Piedad, Av. Ricardo Guzmán Romero, Santa Fe, La Piedad de Cavadas, Michoacán 59370, Mexico
| | - Agostinho Antunes
- CIIMAR/CIMAR, Interdisciplinary Centre of Marine and Environmental Research, University of Porto, Terminal de Cruzeiros do Porto de Leixões, Av. General Norton de Matos s/n 4450-208 Porto, Portugal
- Department of Biology, Faculty of Sciences, University of Porto, Rua do Campo Alegre, 4169-007 Porto, Portugal
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Domínguez-Pérez D, Durban J, Agüero-Chapin G, López JT, Molina-Ruiz R, Almeida D, Calvete JJ, Vasconcelos V, Antunes A. The Harderian gland transcriptomes of Caraiba andreae, Cubophis cantherigerus and Tretanorhinus variabilis, three colubroid snakes from Cuba. Genomics 2018; 111:1720-1727. [PMID: 30508561 DOI: 10.1016/j.ygeno.2018.11.026] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2018] [Revised: 10/31/2018] [Accepted: 11/27/2018] [Indexed: 01/17/2023]
Abstract
The Harderian gland is a cephalic structure, widely distributed among vertebrates. In snakes, the Harderian gland is anatomically connected to the vomeronasal organ via the nasolacrimal duct, and in some species can be larger than the eyes. The function of the Harderian gland remains elusive, but it has been proposed to play a role in the production of saliva, pheromones, thermoregulatory lipids and growth factors, among others. Here, we have profiled the transcriptomes of the Harderian glands of three non-front-fanged colubroid snakes from Cuba: Caraiba andreae (Cuban Lesser Racer); Cubophis cantherigerus (Cuban Racer); and Tretanorhinus variabilis (Caribbean Water Snake), using Illumina HiSeq2000 100 bp paired-end. In addition to ribosomal and non-characterized proteins, the most abundant transcripts encode putative transport/binding, lipocalin/lipocalin-like, and bactericidal/permeability-increasing-like proteins. Transcripts coding for putative canonical toxins described in venomous snakes were also identified. This transcriptional profile suggests a more complex function than previously recognized for this enigmatic organ.
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Affiliation(s)
- Dany Domínguez-Pérez
- CIIMAR/CIMAR, Interdisciplinary Centre of Marine and Environmental Research, University of Porto, Terminal de Cruzeiros do Porto de Leixões, Av. General Norton de Matos, s/n, Porto 4450-208, Portugal; Department of Biology, University of Porto, Rua do Campo Alegre, s/n, Porto 4169-007, Portugal.
| | - Jordi Durban
- Evolutionary and Translational Venomics Laboratory, CSIC, Jaume Roig, 11, 46010, Valencia, Spain.
| | - Guillermin Agüero-Chapin
- CIIMAR/CIMAR, Interdisciplinary Centre of Marine and Environmental Research, University of Porto, Terminal de Cruzeiros do Porto de Leixões, Av. General Norton de Matos, s/n, Porto 4450-208, Portugal; Department of Biology, University of Porto, Rua do Campo Alegre, s/n, Porto 4169-007, Portugal.
| | - Javier Torres López
- Department of Ecology and Evolutionary Biology, The University of Kansas, 1345 Jayhawk Blvd., Lawrence, Kansas 66045, USA; Faculty of Biology, University of Havana, 25 St. 455, La Habana 10400, Cuba.
| | - Reinaldo Molina-Ruiz
- Centro de Bioactivos Químicos, Universidad Central "Marta Abreu" de Las Villas, 54830 Santa Clara, Cuba.
| | - Daniela Almeida
- CIIMAR/CIMAR, Interdisciplinary Centre of Marine and Environmental Research, University of Porto, Terminal de Cruzeiros do Porto de Leixões, Av. General Norton de Matos, s/n, Porto 4450-208, Portugal; Department of Biology, University of Porto, Rua do Campo Alegre, s/n, Porto 4169-007, Portugal.
| | - Juan J Calvete
- Evolutionary and Translational Venomics Laboratory, CSIC, Jaume Roig, 11, 46010, Valencia, Spain.
| | - Vítor Vasconcelos
- CIIMAR/CIMAR, Interdisciplinary Centre of Marine and Environmental Research, University of Porto, Terminal de Cruzeiros do Porto de Leixões, Av. General Norton de Matos, s/n, Porto 4450-208, Portugal; Department of Biology, University of Porto, Rua do Campo Alegre, s/n, Porto 4169-007, Portugal.
| | - Agostinho Antunes
- CIIMAR/CIMAR, Interdisciplinary Centre of Marine and Environmental Research, University of Porto, Terminal de Cruzeiros do Porto de Leixões, Av. General Norton de Matos, s/n, Porto 4450-208, Portugal; Department of Biology, University of Porto, Rua do Campo Alegre, s/n, Porto 4169-007, Portugal.
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Galpert D, Fernández A, Herrera F, Antunes A, Molina-Ruiz R, Agüero-Chapin G. Surveying alignment-free features for Ortholog detection in related yeast proteomes by using supervised big data classifiers. BMC Bioinformatics 2018; 19:166. [PMID: 29724166 PMCID: PMC5934817 DOI: 10.1186/s12859-018-2148-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2017] [Accepted: 04/04/2018] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND The development of new ortholog detection algorithms and the improvement of existing ones are of major importance in functional genomics. We have previously introduced a successful supervised pairwise ortholog classification approach implemented in a big data platform that considered several pairwise protein features and the low ortholog pair ratios found between two annotated proteomes (Galpert, D et al., BioMed Research International, 2015). The supervised models were built and tested using a Saccharomycete yeast benchmark dataset proposed by Salichos and Rokas (2011). Despite several pairwise protein features being combined in a supervised big data approach; they all, to some extent were alignment-based features and the proposed algorithms were evaluated on a unique test set. Here, we aim to evaluate the impact of alignment-free features on the performance of supervised models implemented in the Spark big data platform for pairwise ortholog detection in several related yeast proteomes. RESULTS The Spark Random Forest and Decision Trees with oversampling and undersampling techniques, and built with only alignment-based similarity measures or combined with several alignment-free pairwise protein features showed the highest classification performance for ortholog detection in three yeast proteome pairs. Although such supervised approaches outperformed traditional methods, there were no significant differences between the exclusive use of alignment-based similarity measures and their combination with alignment-free features, even within the twilight zone of the studied proteomes. Just when alignment-based and alignment-free features were combined in Spark Decision Trees with imbalance management, a higher success rate (98.71%) within the twilight zone could be achieved for a yeast proteome pair that underwent a whole genome duplication. The feature selection study showed that alignment-based features were top-ranked for the best classifiers while the runners-up were alignment-free features related to amino acid composition. CONCLUSIONS The incorporation of alignment-free features in supervised big data models did not significantly improve ortholog detection in yeast proteomes regarding the classification qualities achieved with just alignment-based similarity measures. However, the similarity of their classification performance to that of traditional ortholog detection methods encourages the evaluation of other alignment-free protein pair descriptors in future research.
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Affiliation(s)
- Deborah Galpert
- Departamento de Ciencia de la Computación, Universidad Central ¨Marta Abreu¨ de Las Villas (UCLV), 54830, Santa Clara, Cuba
| | - Alberto Fernández
- Department of Computer Science and Artificial Intelligence, Research Center on Information and Communications Technology (CITIC-UGR), University of Granada, 18071, Granada, Spain
| | - Francisco Herrera
- Department of Computer Science and Artificial Intelligence, Research Center on Information and Communications Technology (CITIC-UGR), University of Granada, 18071, Granada, Spain
| | - Agostinho Antunes
- CIIMAR/CIMAR, Centro Interdisciplinar de Investigação Marinha e Ambiental, Universidade do Porto, Terminal de Cruzeiros do Porto de Leixões, Av. General Norton de Matos s/n 4450-208 Matosinhos, Porto, Portugal.,Departamento de Biologia, Faculdade de Ciências, Universidade do Porto, Rua do Campo Alegre, 4169-007, Porto, Portugal
| | - Reinaldo Molina-Ruiz
- Centro de Bioactivos Químicos (CBQ), Universidad Central ¨Marta Abreu¨ de Las Villas (UCLV), 54830, Santa Clara, Cuba
| | - Guillermin Agüero-Chapin
- CIIMAR/CIMAR, Centro Interdisciplinar de Investigação Marinha e Ambiental, Universidade do Porto, Terminal de Cruzeiros do Porto de Leixões, Av. General Norton de Matos s/n 4450-208 Matosinhos, Porto, Portugal. .,Departamento de Biologia, Faculdade de Ciências, Universidade do Porto, Rua do Campo Alegre, 4169-007, Porto, Portugal. .,Centro de Bioactivos Químicos (CBQ), Universidad Central ¨Marta Abreu¨ de Las Villas (UCLV), 54830, Santa Clara, Cuba.
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Pinto da Costa M, Giurgiuca A, Holmes K, Biskup E, Mogren T, Tomori S, Kilic O, Banjac V, Molina-Ruiz R, Palumbo C, Frydecka D, Kaaja J, El-Higaya E, Kanellopoulos A, Amit BH, Madissoon D, Andreou E, Uleviciute-Belena I, Rakos I, Dragasek J, Feffer K, Farrugia M, Mitkovic-Voncina M, Gargot T, Baessler F, Pantovic-Stefanovic M, De Picker L. To which countries do European psychiatric trainees want to move to and why? Eur Psychiatry 2017; 45:174-181. [PMID: 28957784 DOI: 10.1016/j.eurpsy.2017.06.010] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/27/2017] [Revised: 06/25/2017] [Accepted: 06/26/2017] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND There is a shortage of psychiatrists worldwide. Within Europe, psychiatric trainees can move between countries, which increases the problem in some countries and alleviates it in others. However, little is known about the reasons psychiatric trainees move to another country. METHODS Survey of psychiatric trainees in 33 European countries, exploring how frequently psychiatric trainees have migrated or want to migrate, their reasons to stay and leave the country, and the countries where they come from and where they move to. A 61-item self-report questionnaire was developed, covering questions about their demographics, experiences of short-term mobility (from 3 months up to 1 year), experiences of long-term migration (of more than 1 year) and their attitudes towards migration. RESULTS A total of 2281 psychiatric trainees in Europe participated in the survey, of which 72.0% have 'ever' considered to move to a different country in their future, 53.5% were considering it 'now', at the time of the survey, and 13.3% had already moved country. For these immigrant trainees, academic was the main reason they gave to move from their country of origin. For all trainees, the overall main reason for which they would leave was financial (34.4%), especially in those with lower (<500€) incomes (58.1%), whereas in those with higher (>2500€) incomes, personal reasons were paramount (44.5%). CONCLUSIONS A high number of psychiatric trainees considered moving to another country, and their motivation largely reflects the substantial salary differences. These findings suggest tackling financial conditions and academic opportunities.
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Affiliation(s)
- M Pinto da Costa
- Hospital de Magalhães Lemos, Porto, Portugal; Institute of Biomedical Sciences Abel Salazar (ICBAS), University of Porto, Porto, Portugal; Unit for Social and Community Psychiatry (WHO Collaborating Centre for Mental Health Services Development), Queen Mary University of London, London, United Kingdom.
| | - A Giurgiuca
- The Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
| | - K Holmes
- Avon and Wiltshire Mental Health Partnership Trust, Bristol, United Kingdom
| | - E Biskup
- University Hospital of Basel, Department of Internal Medicine, Basel, Switzerland; Shanghai University of Medicine and Health Sciences Basic Medical College, Shanghai, China
| | - T Mogren
- Allmänspykiatriska kliniken Falun/Säter, Säter, Sweden
| | - S Tomori
- University Hospital Center Mother Teresa, Department of Pediatrics, Tirana, Albania
| | - O Kilic
- Koc University Hospital, Department of Psychiatry, Istanbul, Turkey
| | - V Banjac
- Clinic of psychiatry, University Clinical Center of the Republic of Srpska, Banjaluka, Bosnia and Herzegovina
| | - R Molina-Ruiz
- CSM de Hospital Universitario Fundación Alcorcón, Psychiatry Department, Madrid, Spain
| | - C Palumbo
- Hospital Papa Giovanni XXIII-Bergamo (BG), Department of Psychiatry, Bergamo, Italy
| | - D Frydecka
- Department of Psychiatry, Wroclaw Medical University, Wroclaw, Poland
| | - J Kaaja
- Universiy of Tampere, Tampere, Finland
| | - E El-Higaya
- School of Medicine, National University of Ireland, Galway, Ireland
| | - A Kanellopoulos
- Mental Health Care Unit, Evgenidion Therapeftirion, National & Kapodistrian University of Athens, Greece
| | - B H Amit
- Tel Aviv University, Department of psychiatry, Geha Mental Health Center, Petach Tiqwa, Israel
| | - D Madissoon
- South-Estonian Hospital, Psychiatry Clinic, Võru, Estonia
| | - E Andreou
- Athalassa Mental Health Hospital, Mental Health Services, Nicosia, Cyprus
| | - I Uleviciute-Belena
- Clinical hospital of Vilnius, Office of primary mental health care, Vilnius, Lithuania
| | - I Rakos
- University Hospital Dubrava, Department of Psychiatry, Referral Center for the Stress-Related Disorders, Zagreb, Croatia
| | - J Dragasek
- Pavol Jozef Šafárik University, Faculty of Medicine, 1st Department of Psychiatry, Košice, Slovakia
| | - K Feffer
- Shalvata mental health center, Hod-Hasharon, Israel
| | - M Farrugia
- Mount Carmel Hospital, Triq l-Imdina, Malta
| | - M Mitkovic-Voncina
- Belgrade University School of Medicine, Institute of Mental Health, Belgrade, Serbia
| | - T Gargot
- Service de psychiatrie de l'enfant et de l'adolescent, hôpital de la Pitié-Salpêtrière, Paris, France; Equipe interaction, institut des systèmes intelligents et de la robotique, Paris, France
| | - F Baessler
- Centre for psychosocial medicine and department of general internal medicine and psychosomatics, University Hospital Heidelberg, Heidelberg, Germany
| | - M Pantovic-Stefanovic
- Department for Affective Disorders, University Clinical Center of Serbia, Belgrade, Serbia
| | - L De Picker
- Collaborative Antwerp Psychiatric Research Institute, Faculty of Medicine, University of Antwerp, Antwerp, Belgium
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Agüero-Chapin G, Sánchez-Rodríguez A, Hidalgo-Yanes PI, Pérez-Castillo Y, Molina-Ruiz R, Marchal K, Vasconcelos V, Antunes A. An alignment-free approach for eukaryotic ITS2 annotation and phylogenetic inference. PLoS One 2011; 6:e26638. [PMID: 22046320 PMCID: PMC3202569 DOI: 10.1371/journal.pone.0026638] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2011] [Accepted: 09/29/2011] [Indexed: 02/02/2023] Open
Abstract
The ITS2 gene class shows a high sequence divergence among its members that have complicated its annotation and its use for reconstructing phylogenies at a higher taxonomical level (beyond species and genus). Several alignment strategies have been implemented to improve the ITS2 annotation quality and its use for phylogenetic inferences. Although, alignment based methods have been exploited to the top of its complexity to tackle both issues, no alignment-free approaches have been able to successfully address both topics. By contrast, the use of simple alignment-free classifiers, like the topological indices (TIs) containing information about the sequence and structure of ITS2, may reveal to be a useful approach for the gene prediction and for assessing the phylogenetic relationships of the ITS2 class in eukaryotes. Thus, we used the TI2BioP (Topological Indices to BioPolymers) methodology [1], [2], freely available at http://ti2biop.sourceforge.net/ to calculate two different TIs. One class was derived from the ITS2 artificial 2D structures generated from DNA strings and the other from the secondary structure inferred from RNA folding algorithms. Two alignment-free models based on Artificial Neural Networks were developed for the ITS2 class prediction using the two classes of TIs referred above. Both models showed similar performances on the training and the test sets reaching values above 95% in the overall classification. Due to the importance of the ITS2 region for fungi identification, a novel ITS2 genomic sequence was isolated from Petrakia sp. This sequence and the test set were used to comparatively evaluate the conventional classification models based on multiple sequence alignments like Hidden Markov based approaches, revealing the success of our models to identify novel ITS2 members. The isolated sequence was assessed using traditional and alignment-free based techniques applied to phylogenetic inference to complement the taxonomy of the Petrakia sp. fungal isolate.
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Affiliation(s)
- Guillermin Agüero-Chapin
- CIMAR/CIIMAR, Centro Interdisciplinar de Investigação Marinha e Ambiental, Universidade do Porto, Porto, Portugal
- Molecular Simulation and Drug Design (CBQ), Universidad Central “Marta Abreu” de Las Villas (UCLV), Santa Clara, Cuba
- Departamento de Biologia, Faculdade de Ciências, Universidade do Porto, Porto, Portugal
| | | | - Pedro I. Hidalgo-Yanes
- Molecular Simulation and Drug Design (CBQ), Universidad Central “Marta Abreu” de Las Villas (UCLV), Santa Clara, Cuba
- Area of Microbiology, University of León, León, Spain
| | - Yunierkis Pérez-Castillo
- Molecular Simulation and Drug Design (CBQ), Universidad Central “Marta Abreu” de Las Villas (UCLV), Santa Clara, Cuba
| | - Reinaldo Molina-Ruiz
- Molecular Simulation and Drug Design (CBQ), Universidad Central “Marta Abreu” de Las Villas (UCLV), Santa Clara, Cuba
| | - Kathleen Marchal
- CMPG, Department of Microbial and Molecular Systems, KU Leuven, Leuven, Belgium
| | - Vítor Vasconcelos
- CIMAR/CIIMAR, Centro Interdisciplinar de Investigação Marinha e Ambiental, Universidade do Porto, Porto, Portugal
- Departamento de Biologia, Faculdade de Ciências, Universidade do Porto, Porto, Portugal
| | - Agostinho Antunes
- CIMAR/CIIMAR, Centro Interdisciplinar de Investigação Marinha e Ambiental, Universidade do Porto, Porto, Portugal
- Departamento de Biologia, Faculdade de Ciências, Universidade do Porto, Porto, Portugal
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Agüero-Chapin G, de la Riva GA, Molina-Ruiz R, Sánchez-Rodríguez A, Pérez-Machado G, Vasconcelos V, Antunes A. Non-linear models based on simple topological indices to identify RNase III protein members. J Theor Biol 2010; 273:167-78. [PMID: 21192951 DOI: 10.1016/j.jtbi.2010.12.019] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2010] [Revised: 11/15/2010] [Accepted: 12/13/2010] [Indexed: 01/27/2023]
Abstract
Alignment-free classifiers are especially useful in the functional classification of protein classes with variable homology and different domain structures. Thus, the Topological Indices to BioPolymers (TI2BioP) methodology (Agüero-Chapin et al., 2010) inspired in both the TOPS-MODE and the MARCH-INSIDE methodologies allows the calculation of simple topological indices (TIs) as alignment-free classifiers. These indices were derived from the clustering of the amino acids into four classes of hydrophobicity and polarity revealing higher sequence-order information beyond the amino acid composition level. The predictability power of such TIs was evaluated for the first time on the RNase III family, due to the high diversity of its members (primary sequence and domain organization). Three non-linear models were developed for RNase III class prediction: Decision Tree Model (DTM), Artificial Neural Networks (ANN)-model and Hidden Markov Model (HMM). The first two are alignment-free approaches, using TIs as input predictors. Their performances were compared with a non-classical HMM, modified according to our amino acid clustering strategy. The alignment-free models showed similar performances on the training and the test sets reaching values above 90% in the overall classification. The non-classical HMM showed the highest rate in the classification with values above 95% in training and 100% in test. Although the higher accuracy of the HMM, the DTM showed simplicity for the RNase III classification with low computational cost. Such simplicity was evaluated in respect to HMM and ANN models for the functional annotation of a new bacterial RNase III class member, isolated and annotated by our group.
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Affiliation(s)
- Guillermin Agüero-Chapin
- CIMAR/CIIMAR, Centro Interdisciplinar de Investigação Marinha e Ambiental, Universidade do Porto, Rua dos Bragas, 177, 4050-123 Porto, Portugal
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Agüero-Chapin G, Pérez-Machado G, Molina-Ruiz R, Pérez-Castillo Y, Morales-Helguera A, Vasconcelos V, Antunes A. TI2BioP: Topological Indices to BioPolymers. Its practical use to unravel cryptic bacteriocin-like domains. Amino Acids 2010; 40:431-42. [PMID: 20563611 DOI: 10.1007/s00726-010-0653-9] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2010] [Accepted: 06/02/2010] [Indexed: 02/04/2023]
Abstract
Bacteriocins are proteinaceous toxins produced and exported by both gram-negative and gram-positive bacteria as a defense mechanism. The bacteriocin protein family is highly diverse, which complicates the identification of bacteriocin-like sequences using alignment approaches. The use of topological indices (TIs) irrespective of sequence similarity can be a promising alternative to predict proteinaceous bacteriocins. Thus, we present Topological Indices to BioPolymers (TI2BioP) as an alignment-free approach inspired in both the Topological Substructural Molecular Design (TOPS-MODE) and Markov Chain Invariants for Network Selection and Design (MARCH-INSIDE) methodology. TI2BioP allows the calculation of the spectral moments as simple TIs to seek quantitative sequence-function relationships (QSFR) models. Since hydrophobicity and basicity are major criteria for the bactericide activity of bacteriocins, the spectral moments ((HP)μ(k)) were derived for the first time from protein artificial secondary structures based on amino acid clustering into a Cartesian system of hydrophobicity and polarity. Several orders of (HP)μ(k) characterized numerically 196 bacteriocin-like sequences and a control group made up of 200 representative CATH domains. Subsequently, they were used to develop an alignment-free QSFR model allowing a 76.92% discrimination of bacteriocin proteins from other domains, a relevant result considering the high sequence diversity among the members of both groups. The model showed a prediction overall performance of 72.16%, detecting specifically 66.7% of proteinaceous bacteriocins whereas the InterProScan retrieved just 60.2%. As a practical validation, the model also predicted successfully the cryptic bactericide function of the Cry 1Ab C-terminal domain from Bacillus thuringiensis's endotoxin, which has not been detected by classical alignment methods.
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Affiliation(s)
- Guillermín Agüero-Chapin
- CIMAR/CIIMAR, Centro Interdisciplinar de Investigação Marinha e Ambiental, Universidade do Porto, Rua dos Bragas, 177, 4050-123, Porto, Portugal
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Anta Tejado L, Molina-Ruiz R, Tajima-Pozo K, Yus M, Casado A, Carrasco-Perera J, Diaz-Marsá M. PW01-142 - Abnormal amygdala response in women with eating disorder: a fMRI study. Eur Psychiatry 2010. [DOI: 10.1016/s0924-9338(10)71541-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
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