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Ahluwalia, A. D.

Publications and source records attributed to Ahluwalia, A. D..

2 recordsLinked to original sources

Variability in single-cell oxygen consumption kinetics

We combined microfabricated devices with multiparameter identification algorithms to probe the variability in size-dependent oxygen consumption parameters of single human hepatic cells. We demonstrate that single cells exhibit an oxygen-dependent metabolic rate, typical of Michaelis-Menten kinetics, and that their maximal oxygen consumption is significantly lower than that of monolayers or 3D hepatic cell aggregates. Notably, we found that clusters of two or more cells competing for a limited oxygen supply reduced their maximal single-cell consumption rate, highlighting their ability to adapt to local resource availability and the presence of nearby cells. Next, we used our high-throughput approach to characterize the covariance of size and oxygen consumption within a cell population. The results show that cooperative behaviour emerges in cell clusters, and that single-cell size and metabolism can be described by a lognormal joint probability density. Our study thus serves as a foundation to connect the metabolic activity of single human hepatocytes to their tissue-or organ-level metabolism as well as describe its size-related variability through scaling laws.

bioengineering↗

An integrated pipeline and multi-model graphical user interface for accurate nano-dosimetry

Accurate dosing of nanoparticles is crucial for risk assessment and for their safe use in medical and other applications. Although it is well-known that nanoparticles sediment, diffuse and aggregate as they move through a fluid, and that therefore the effective dose perceived by cells may not necessarily be that initially administered, dose quantification remains a challenge. This is because to date, methods for accurate dose estimation are difficult to implement, involving precise characterization of the nanomaterial and the exposure system as well as complex mathematical operations. Here we present a pipeline for accurate nano-dosimetry of engineered nanoparticles on cell monolayers, based on an easy-to-use graphical software - DosiGUI - which integrates two well-established particokinetic and particodynamic models. DosiGUI is an open source tool which was developed to facilitate nano-dosimetrics. The pipeline includes methods for determining the stickiness index which describes the affinity between nanoparticles and cells. Our results show that accurate estimations of the effective dose cannot prescind from rigorous characterization of the stickiness index, which depends on both nanoparticle characteristics and cell type.

pharmacology and toxicology↗