Neuroendovascular procedures have led to breakthroughs in the treatment of ischemic stroke, intracranial aneurysms, and intracranial arteriovenous malformations. Due to these substantial successes, there is continuous development of novel and refined therapeutic approaches. Large animal models feature various conceptual advantages in translational research, which makes them appealing for the development of novel endovascular treatments. However, the availability and role of large animal models have not been systematically described so far. Based on comprehensive research in two databases, this systematic review describes current large animal models in neuroendovascular research including their primary use. It may therefore serve as a compact compendium for researchers entering the field or looking for opportunities to refine study concepts. It also describes particular applications for ischemic stroke and aneurysm therapy, as well as for the treatment of arteriovenous malformations. It focuses on most promising study designs and readout parameters, as well as on important pitfalls in endovascular translational research including ways to circumvent them.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6421248 | PMC |
http://dx.doi.org/10.1177/0271678X19827446 | DOI Listing |
Cytotherapy
November 2024
Department of Translational and Precision Medicine, University of Rome, Rome, Italy. Electronic address:
Cellular and gene therapy (CGT) products have emerged as a popular approach in regenerative medicine, showing promise in treating various pancreatic and liver diseases in numerous clinical trials. Before these therapies can be tested in human clinical trials, it is essential to evaluate their safety and efficacy in relevant animal models. Such preclinical testing is often required to obtain regulatory approval for investigational new drugs.
View Article and Find Full Text PDFEnviron Sci Pollut Res Int
January 2025
Faculty of Geography, Lomonosov Moscow State University, 119991, Moscow, Russia.
The content of 39 metals and metalloids (MMs) in submicron road dust (PM fraction) was studied in the traffic zone, residential courtyards with parking lots, and on pedestrian roads in parks in Moscow. The geochemical profiles of PM vary slightly between different types of roads and courtyards but differ significantly from those in parks. In Moscow, compared to other cities worldwide, submicron road dust contains less As, Sb, Mo, Cr, Cd, Sn, Tl, Ca, Rb, La, Y, U, but more Cu, Zn, Co, Fe, Mn, Ti, Zr, Al, V.
View Article and Find Full Text PDFCommun Biol
January 2025
Department of Ecology and Evolutionary Biology, University of Colorado Boulder, Boulder, CO, USA.
Symbioses are major drivers of organismal diversification and phenotypic innovation. However, how long-term symbioses shape whole genome evolution in metazoans is still underexplored. Here, we use a giant clam (Tridacna maxima) genome to demonstrate how symbiosis has left complex signatures in an animal's genome.
View Article and Find Full Text PDFSci Rep
January 2025
Dipartimento di Medicina Veterinaria e delle Produzioni Animali, Università degli Studi di Napoli Federico II, Naples, Italy.
BPV1, BPV2, BPV13, and BPV14 are all genotypes of bovine delta papillomaviruses (δPV), of which the first three cause infections in horses and are associated with equine sarcoids. However, BPV14 infection has never been reported in equine species. In this study, we examined 58 fresh and thawed commercial semen samples from healthy stallions.
View Article and Find Full Text PDFNat Commun
January 2025
Key Laboratory of Healthy Mariculture for the East China Sea, Ministry of Agriculture and Rural Affairs & Fisheries college, Jimei University, Xiamen, Fujian, People's Republic of China.
Deep phenotyping can enhance the power of genetic analysis, including genome-wide association studies (GWAS), but the occurrence of missing phenotypes compromises the potential of such resources. Although many phenotypic imputation methods have been developed, the accurate imputation of millions of individuals remains challenging. In the present study, we have developed a multi-phenotype imputation method based on mixed fast random forest (PIXANT) by leveraging efficient machine learning (ML)-based algorithms.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!