Zobrazeno 1 - 10
of 28
pro vyhledávání: '"Amina Eladdadi"'
Autor:
Ling Wang, Joshua Goldwag, Megan Bouyea, Jonathan Barra, Kailie Matteson, Niva Maharjan, Amina Eladdadi, Mark J. Embrechts, Xavier Intes, Uwe Kruger, Margarida Barroso
Publikováno v:
iScience, Vol 26, Iss 7, Pp 107229- (2023)
Summary: Genomics and proteomics have been central to identify tumor cell populations, but more accurate approaches to classify cell subtypes are still lacking. We propose a new methodology to accurately classify cancer cells based on their organelle
Externí odkaz:
https://doaj.org/article/17d2e068044a44cfb444625275b68a72
Autor:
Yassine Kasmi, Tina Blancke, Erik Eschbach, Benita Möckel, Laura Casas, Matthias Bernreuther, Pedro Nogueira, Gertrud Delfs, Samira Kadhim, Timo Meißner, Marcellus Rödiger, Amina Eladdadi, Christoph Stransky, Reinhold Hanel
Publikováno v:
Frontiers in Marine Science, Vol 10 (2023)
The assessment of fish stocks is often dependent on scientific trawl fisheries surveys, which are both invasive and costly. The analysis of environmental DNA (eDNA) from water samples is regarded as a non-invasive and cost-effective alternative, but
Externí odkaz:
https://doaj.org/article/be4d4b9a10b74d45b2236e36b799acb0
Publikováno v:
Mathematical Biosciences and Engineering, Vol 19, Iss 5, Pp 4429-4457 (2022)
Combining chimeric antigen receptor T (CAR-T) cells with oncolytic viruses (OVs) has recently emerged as a promising treatment approach in preclinical studies that aim to alleviate some of the barriers faced by CAR-T cell therapy. In this study, we a
Externí odkaz:
https://doaj.org/article/1b157c9d2a8941b690bdb351eafe518a
Publikováno v:
Journal of Biological Dynamics, Vol 14, Iss 1, Pp 454-478 (2020)
In this paper, we apply a new approach to a special class of discrete time evolution models and establish a solid mathematical foundation to analyse them. We propose new single and multi-species evolutionary competition models using the evolutionary
Externí odkaz:
https://doaj.org/article/ff5458b0b2254fd0815ebd7a87d19f53
Publikováno v:
Journal of Biological Dynamics, Vol 11, Iss 1, Pp 244-274 (2017)
Chemovirotherapy is a combination therapy with chemotherapy and oncolytic viruses. It is gaining more interest and attracting more attention in the clinical setting due to its effective therapy and potential synergistic interactions against cancer. I
Externí odkaz:
https://doaj.org/article/3d313740b8874450a725d773781fd1f6
Publikováno v:
Letters in Biomathematics, Vol 5, Iss 0, Pp S1-S5 (2018)
Externí odkaz:
https://doaj.org/article/d296e20c662a431794fab9ce3acf7d67
Publikováno v:
Letters in Biomathematics, Vol 5, Iss 0, Pp S178-S200 (2018)
In this paper, we present a mathematical model at the cellular level of the tumour–immune competition mediated by the cytokines. The model consists of a system of nonlinear differential equations describing the intracellular interactions between th
Externí odkaz:
https://doaj.org/article/90b07e67c0084bef987ddbcfb731a82d
Publikováno v:
PLoS ONE, Vol 12, Iss 9, p e0184347 (2017)
In the present paper, we address by means of mathematical modeling the following main question: How can oncolytic virus infection of some normal cells in the vicinity of tumor cells enhance oncolytic virotherapy? We formulate a mathematical model des
Externí odkaz:
https://doaj.org/article/80bec6d7c70846e59c2bdd3b59cc4150
Publikováno v:
Journal of Biological Dynamics, Vol 14, Iss 1, Pp 454-478 (2020)
In this paper, we apply a new approach to a special class of discrete time evolution models and establish a solid mathematical foundation to analyse them. We propose new single and multi-species evolutionary competition models using the evolutionary
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5e15732569ce422d93a7e834d6e9b423
https://doi.org/10.1080/17513758.2020.1772997
https://doi.org/10.1080/17513758.2020.1772997
Publikováno v:
Gene Reports. 27:101633
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3c6ab71b101081f0987444699fed61e9
https://doi.org/10.1016/j.genrep.2022.101633
https://doi.org/10.1016/j.genrep.2022.101633