Overcoming the Challenges to Enhancing Experimental Plant Biology With Computational Modeling.

The study of complex biological systems necessitates computational modeling approaches that are currently underutilized in plant biology. Many plant biologists have trouble identifying or adopting modeling methods to their research, particularly mechanistic mathematical modeling. Here we address challenges that limit the use of computational modeling methods, particularly mechanistic mathematical modeling. We divide computational modeling techniques into either pattern models (e.g., bioinformatics, machine learning, or morphology) or mechanistic mathematical models (e.g., biochemical reactions, biophysics, or population models), which both contribute to plant biology research at different scales to answer different research questions. We present arguments and recommendations for the increased adoption of modeling by plant biologists interested in incorporating more modeling into their research programs. As some researchers find math and quantitative methods to be an obstacle to modeling, we provide suggestions for easy-to-use tools for non-specialists and for collaboration with specialists. This may especially be the case for mechanistic mathematical modeling, and we spend some extra time discussing this. Through a more thorough appreciation and awareness of the power of different kinds of modeling in plant biology, we hope to facilitate interdisciplinary, transformative research.

Incidence of spinal epidural lipomatosis in patients with spinal stenosis.

INRODUCTION: Spinal Epidural Lipomatosis (SEL) is believed to be a rare disorder. The incidence and prevalence of clinically symptomatic SEL in patients with spinal stenosis has never been reported in the literature. Our study aims to determine the prevalence, incidence, and associated risk factors of SEL in patients with the diagnosis of spinal stenosis. METHODS: This is a retrospective study. We reviewed the charts of 831 patients with the diagnosis of spinal stenosis over a 30 month period. All patients had spinal MRIs. Grading of SEL was performed using the Borré method. RESULTS: 52 patients (21 female and 31 male) had symptomatic moderate and severe SEL. We found a prevalence of 6.26% and an annual incidence of 2.5%. SEL was most commonly seen at L5-S1 level. 27% had received corticosteroids. All SEL patients were overweight and 79% were obese. CONCLUSIONS: SEL is not uncommon in patients with spinal stenosis. SEL should be considered as a possible diagnosis in those with symptoms of spinal stenosis especially in those with associated risk factors.