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The pig as an animal model for human pathologies: A proteomics perspective
Abstract
Traditional biomedical models are easy to manage in experimental facilities and allow fast and affordable basic genetic studies related to human disorders, but in some cases they do not always represent the complexity of their physiology. Translational medicine demands selected models depending on the particularities of the human disease to be investigated, reproducing as closely as possible the evolution, clinical symptoms and molecular pathways, cells or tissues involved in the dysfunction. Thus, pig models offer an alternative because of their anatomical and physiological similarities to humans and the availability of genomic, transcriptomic and, progressively more, proteomic tools for analysis of this species. Furthermore, there is a wide range of natural, selected and transgenic porcine breeds. The present review provides a summary of the applications of the pig as a model for metabolic, cardiovascular, infectious diseases, xenotransplantation and neurological disorders and an overview of the possibilities that the diverse proteomic techniques offer to study these pathologies in depth.
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Metadata
- Authors
- Bassols, A., Costa, C., Eckersall, P. D., Osada, J., Sabrià, J., & Tibau, J.
- Venue
- PROTEOMICS – Clinical Applications
- Publisher
- Wiley
- Published
- 2014-10
- Volume
- 8
- Issue
- 9-10
- Pages
- 715-731
- ISSN
- 1862-8346 (ISSN-L)
- 1862-8354
- OpenAlex
- W2013606469
- Cited by
- 254
- References
- 134
- FWCI
- 10.75
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
