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1.
Trends Plant Sci ; 2024 Apr 16.
Artigo em Inglês | MEDLINE | ID: mdl-38641475

RESUMO

Understanding the complex relationships between plants, their microbiomes, and environmental changes is crucial for improving growth and survival, especially for long-lived tree species. Trees, like other plants, maintain close associations with a multitude of microorganisms on and within their tissues, forming a 'holobiont'. However, a comprehensive framework for detailed tree-microbiome dynamics, and the implications for climate adaptation, is currently lacking. This review identifies gaps in the existing literature, emphasizing the need for more research to explore the coevolution of the holobiont and the full extent of climate change impact on tree growth and survival. Advancing our knowledge of plant-microbial interactions presents opportunities to enhance tree adaptability and mitigate adverse impacts of climate changes on trees.

2.
Biomed Res Int ; 2015: 659651, 2015.
Artigo em Inglês | MEDLINE | ID: mdl-26425549

RESUMO

Most hosts harbor multiple pathogens at the same time in disease epidemiology. Multiple pathogens have the potential for interaction resulting in negative impacts on host fitness or alterations in pathogen transmission dynamics. In this paper we develop a mathematical model describing the dynamics of HIV-malaria coinfection. Additionally, we extended our model to examine the role treatment (of malaria and HIV) plays in altering populations' dynamics. Our model consists of 13 interlinked equations which allow us to explore multiple aspects of HIV-malaria transmission and treatment. We perform qualitative analysis of the model that includes positivity and boundedness of solutions. Furthermore, we evaluate the reproductive numbers corresponding to the submodels and investigate the long term behavior of the submodels. We also consider the qualitative dynamics of the full model. Sensitivity analysis is done to determine the impact of some chosen parameters on the dynamics of malaria. Finally, numerical simulations illustrate the potential impact of the treatment scenarios and confirm our analytical results.


Assuntos
Coinfecção/terapia , Infecções por HIV/terapia , Malária/terapia , Modelos Biológicos , Número Básico de Reprodução , Simulação por Computador , Progressão da Doença , Infecções por HIV/epidemiologia , Humanos , Prevalência
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