Renewed interest in dynamic simulation models of biomolecular systems has arisen from advances in genome-wide measurement and applications of such models in biotechnology and synthetic biology. In particular, genome-scale models of cellular metabolism beyond the steady state are required in order to represent transient and dynamic regulatory properties of the system. Development of such whole-cell models requires new modelling approaches. Here, we propose the energy-based bond graph methodology, which integrates stoichiometric models with thermodynamic principles and kinetic modelling. We demonstrate how the bond graph approach intrinsically enforces thermodynamic constraints, provides a modular approach to modelling, and gives a basis for estimation of model parameters leading to dynamic models of biomolecular systems. The approach is illustrated using a well-established stoichiometric model of and published experimental data.
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http://dx.doi.org/10.1098/rsif.2021.0478 | DOI Listing |
Langmuir
January 2025
Department of Materials Science and Engineering, University of Delaware, Newark, Delaware 19716, United States.
We synthesized rigid, macromolecular brushes with well-defined and quantized brush lengths on a gold nanoparticle substrate by using a macromolecular "grafting from" approach. The macromonomers used in these brushes were thiol- and maleimide-functionalized peptide coiled coil "bundlemers" that fold into discrete 4 nm × 2 nm (length × diameter) cylindrical nanoparticles. With each added peptide macromonomer layer, brush thickness increased by approximately the length of a single bundlemer nanoparticle.
View Article and Find Full Text PDFBJUI Compass
January 2025
OncoAssure Ltd, NovaUCD Dublin Ireland.
Objectives: This study aimed to clinically validate the six-gene prognostic molecular clinical risk score (MCRS) for the prediction of aggressive prostate cancer in diagnostic biopsy tissue.
Methods: MCRS was evaluated in prostate biopsy tissue from a Swedish cohort of men with prostate cancer (UPCA, = 100). The primary outcome of adverse pathology and secondary outcomes of high primary Gleason (≥G4) and high pathological T-stage (≥T3) were assessed by likelihood ratio statistics and area under the receiver operating characteristic curves from logistic regression models; time to biochemical recurrence was assessed by likelihood ratio statistics and C-indexes from Cox proportional hazard regression models.
J R Soc Interface
January 2025
SSM- School for Advanced Studies Via Mezzocannone 4, Naples 80138, Italy.
This article presents the first implementation of a proportional-integral-derivative (PID) biomolecular controller within a consortium of different cell populations, aimed at robust regulation of biological processes. By leveraging the modularity and cooperative dynamics of multiple engineered cell populations, we develop a comprehensive analysis of the performance and robustness of P, PD, PI and PID control architectures. Our theoretical findings, validated through experiments using the BSim agent-based simulation platform for bacterial populations, demonstrate the robustness and effectiveness of our multicellular PID control strategy.
View Article and Find Full Text PDFInvest New Drugs
January 2025
UCD School of Medicine, Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland.
Background: Since MYC is one of the most frequently altered driver genes involved in cancer formation, it is a potential target for new anti-cancer therapies. Historically, however, MYC has proved difficult to target due to the absence of a suitable crevice for binding potential low molecular weight drugs.
Objective: The aim of this study was to evaluate a novel molecular glue, dubbed GT19630, which degrades both MYC and GSPT1, for the treatment of breast cancer.
Cell Rep Methods
January 2025
Department of Nutrition, University of California, Davis, Davis, CA 95616, USA. Electronic address:
High-density lipoprotein (HDL) particle diameter distribution is informative in the diagnosis of many conditions, including Alzheimer's disease (AD). However, obtaining an accurate HDL size measurement is challenging. We demonstrated the utility of measuring the diameter of more than 1,800,000 HDL particles with the deep learning model YOLOv7 (you only look once) from micrographs of 183 HDL samples, including patients with dementia or normal cognition (controls).
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