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Tom Vinestock

Publications and source records attributed to Tom Vinestock.

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PyOMES: an open-source framework for biochemical process modelling

PyOMES is a Python-based, Open-source Modelling Environment for (bio)chemical process Simulation that aims to simplify the modelling of dynamic (including steady state) processes. This is done in a generalied, modular way to facilitate modelling a broad range of biological, chemical, and biochemical systems under a single modelling framework. PyOMES has been built to be accessible to a broad range of users - ranging from those with little modelling experience, such as experimentalists and students, through to more experienced power-users. Here, an introduction is provided to the PyOMES software including a summary of the design, architecture and vision. Use cases are then provided to demonstrate applicability of PyOMES to a number of (bio)chemical process modelling scenarios. Comparisons of predictions against existing benchmark software (i.e. PHREEQC) demonstrate the robustness of the package. Finally, a summary is provided of future directions for the PyOMES package - highlighting its establishment as a unified modelling framework and its potential for community-driven improvement as future developments.

q-bio.QM

Valorisation of Fermentation Side-Stream for Waste-to-Mycoprotein: Nutrient Composition, Metabolic Insights and Process Optimisation

Fermentation-derived side streams represent an underutilised resource for sustainable protein production. This study investigates the potential of centrate from industrial Fusarium venenatum fermentation as a nutrient source for fungal biomass generation. Following compositional characterisation, a synthetic centrate medium was formulated and evaluated using a Box-Behnken design combined with response surface methodology. Across 46 experimental runs, cell dry weight (CDW) ranged from 0.22 to 3.87 g per liter, demonstrating a strong dependence on nutrient composition. Ammonia and glucose were identified as the dominant factors influencing biomass production, with significant nonlinear effects. The model predicted a maximum CDW of 4.17 g per liter under optimised conditions, which was experimentally validated at 3.99 g per liter. Carbon conversion efficiency reached up to 29.02%, indicating effective substrate utilisation. These findings demonstrate that fermentation-derived centrate can support substantial fungal growth, while highlighting its potential to enhance nutrient recovery and influence the biochemical composition of sustainable mycoprotein.

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