A mathematical modeling approach to assess biological control of an orange tree disease

2021 ◽  
pp. 107140
Author(s):  
Iulia Martina Bulai ◽  
Ana Cristina Esteves ◽  
Fernanda Lima ◽  
Ezio Venturino
Keyword(s):  
Mathematical Modeling ◽  
Biological Control ◽  
Tree Disease ◽  
Modeling Approach ◽  
Orange Tree

Dutch Elm Disease, a Model Tree Disease for Biological Control*

2020 ◽  
pp. 103-119
Author(s):  
Ruby J. Scheffer ◽  
Gary A. Strobel
Keyword(s):  
Biological Control ◽  
Dutch Elm Disease ◽  
Tree Disease ◽  
Model Tree

scholarly journals Complementary role of mathematical modeling in preclinical glioblastoma: differentiating poor drug delivery from drug insensitivity

2021 ◽  
Author(s):  
Javier C. Urcuyo ◽  
Susan Christine Massey ◽  
Andrea Hawkins-Daarud ◽  
Bianca-Maria Marin ◽  
Danielle M. Burgenske ◽  
...  
Keyword(s):  
Mathematical Modeling ◽  
Drug Delivery ◽  
Clinical Trials ◽  
Treatment Response ◽  
Blood Brain Barrier ◽  
Brain Barrier ◽  
Significant Heterogeneity ◽  
Current Standard ◽  
Modeling Approach ◽  
Blood Brain

AbstractGlioblastoma is the most malignant primary brain tumor with significant heterogeneity and a limited number of effective therapeutic options. Many investigational targeted therapies have failed in clinical trials, but it remains unclear if this results from insensitivity to therapy or poor drug delivery across the blood-brain barrier. Using well-established EGFR-amplified patient-derived xenograft (PDX) cell lines, we investigated this question using an EGFR-directed therapy. With only bioluminescence imaging, we used a mathematical model to quantify the heterogeneous treatment response across the three PDX lines (GBM6, GBM12, GBM39). Our model estimated the primary cause of intracranial treatment response for each of the lines, and these findings were validated with parallel experimental efforts. This mathematical modeling approach can be used as a useful complementary tool that can be widely applied to many more PDX lines. This has the potential to further inform experimental efforts and reduce the cost and time necessary to make experimental conclusions.Author summaryGlioblastoma is a deadly brain cancer that is difficult to treat. New therapies often fail to surpass the current standard of care during clinical trials. This can be attributed to both the vast heterogeneity of the disease and the blood-brain barrier, which may or may not be disrupted in various regions of tumors. Thus, while some cancer cells may develop insensitivity in the presence of a drug due to heterogeneity, other tumor areas are simply not exposed to the drug. Being able to understand to what extent each of these is driving clinical trial results in individuals may be key to advancing novel therapies. To address this challenge, we used mathematical modeling to study the differences between three patient-derived tumors in mice. With our unique approach, we identified the reason for treatment failure in each patient tumor. These results were validated through rigorous and time-consuming experiments, but our mathematical modeling approach allows for a cheaper, quicker, and widely applicable way to come to similar conclusions.

scholarly journals Cascade Synthesis of l-Homoserine Catalyzed by Lyophilized Whole Cells Containing Transaminase and Aldolase Activities: The Mathematical Modeling Approach

2021 ◽  
Author(s):  
Morana Česnik Katulić ◽  
Martina Sudar ◽  
Karel Hernández ◽  
Yuyin Qi ◽  
Simon J. Charnock ◽  
...  
Keyword(s):  
Mathematical Modeling ◽  
Whole Cells ◽  
Modeling Approach
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