3D cell aggregates amplify diffusion signals

Biophysical models can predict the behavior of cell cultures including 3D cell aggregates (3DCAs), thereby reducing the need for costly and time-consuming experiments. Specifically, mass transfer models enable studying the transport of nutrients, oxygen, signaling molecules, and drugs in 3DCA. These models require the defining of boundary conditions (BC) between the 3DCA and surrounding medium. However, accurately modeling the BC that relates the inner and outer boundary concentrations at the border between the 3DCA and the medium remains a challenge that this paper addresses using both theoretical and experimental methods. The provided biophysical analysis indicates that the concentration of molecules inside boundary is higher than that at the outer boundary, revealing an amplification factor that is confirmed by a particle-based simulator (PBS). Due to the amplification factor, the PBS confirms that when a 3DCA with a low concentration of target molecules is introduced to a culture medium with a higher concentration, the molecule concentration in the medium rapidly decreases. The theoretical model and PBS simulations were used to design a pilot experiment with liver spheroids as the 3DCA and glucose as the target molecule. Experimental results agree with the proposed theory and derived properties

Diffusive molecular communication with a spheroidal receiver for organ-on-chip systems

Realistic models of the components and processes are required for molecular communication (MC) systems. In this paper, a spheroidal receiver structure is proposed for MC that is inspired by the 3D cell cultures known as spheroids being widely used in organ-on-chip systems. A simple diffusive MC system is considered where the spheroidal receiver and a point source transmitter are in an unbounded fluid environment. The spheroidal receiver is modeled as a porous medium for diffusive signaling molecules, then its boundary conditions and effective diffusion coefficient are characterized. It is revealed that the spheroid amplifies the diffusion signal, but also disperses the signal which reduces the information communication rate. Furthermore, we analytically formulate and derive the concentration Green’s function inside and outside the spheroid in terms of infinite series-forms that are confirmed by a particle-based simulator (PBS)

Spheroidal molecular communication via diffusion : signaling between homogeneous cell aggregates

Recent molecular communication (MC) research has integrated more detailed computational models to capture the dynamics of practical biophysical systems. This paper focuses on developing realistic models for MC transceivers inspired by spheroids – three-dimensional cell aggregates commonly used in organ-on-chip experimental systems. Potential applications that can be used or modeled with spheroids include nutrient transport in organ-on-chip systems, the release of biomarkers or reception of drug molecules by cancerous tumor sites, or transceiver nanomachines participating in information exchange. In this paper, a simple diffusive MC system is considered where a spheroidal transmitter and spheroidal receiver are in an unbounded fluid environment. These spheroidal antennas are modeled as porous media for diffusive signaling molecules, then their boundary conditions and effective diffusion coefficients are characterized. Furthermore, for either a point source or spheroidal transmitter, the Green’s function for concentration (GFC) outside and inside the receiving spheroid is analytically derived and formulated in terms of an infinite series and confirmed with a particle-based simulator (PBS). The provided GFCs enable computation of the transmitted and received signals in the proposed spheroidal communication system. This study shows that the porous structure of the receiving spheroid amplifies diffusion signals but also disperses them, thus there is a trade-off between porosity and information transmission rate. Furthermore, the results reveal that the porous arrangement of the transmitting spheroid not only disperses the received signal but also attenuates it in comparison to a point source transmitter. System performance is also evaluated in terms of the bit error rate (BER). Decreasing the porosity of the receiving spheroid is shown to enhance the system performance. Conversely, reducing the porosity of the transmitting spheroid can adversely affect system performance..

Induction of human cytochrome P450 enzymes : Predictive in vitro models and rifampicin induction in vivo

The cytochrome P450 (P450) enzymes comprise the most important enzyme system with regard to phase I metabolism of drugs. Induction of P450s can result in decreased plasma concentrations of the drug itself or a coadminstered drug, followed by lack of effect. In the present study different in vitro models have been investigated for their ability to predict P450 induction in humans. It was found that human liver slices respond to prototypical inducers, although the model is not applicable to screening of large sets of compounds. High throughput screening can however be performed in a reporter gene assay. The study showed that results from a PXR reporter gene assay could be used to classify compounds as CYP3A in vivo inducers or non-inducers when relating in vivo AUC to PXR EC50 values. Subsequently it was shown that instead of EC50 values, the concentration giving a 2-fold increase of baseline levels (F2 values) could be used for the classification of compounds. A new cell line, HepaRG cells, was also investigated for prediction of P450 induction. Results from experiments in HepaRG cells did not only classify compounds as inducers or non-inducers, but gave a strong correlation (R2=0.863) to in vivo CYP3A induction, and could hence be used to quantitatively predict the extent of CYP3A induction in vivo. In addition, the drug metabolising properties of the HepaRG cells were evaluated. Stable mRNA expression of drug metabolising enzymes, transporters, and liver specific factors in HepaRG cells were shown for up to six weeks in culture. Although the mRNA expression of drug metabolising P450s were lower in HepaRG cells as compared to human hepatocytes, the relative levels of the P450s were similar. The HepaRG cells could thus be used not only for induction studies but also for investigation of metabolic pattern of drugs and new chemical entities. Furthermore, the in vivo induction of P450s by three different daily doses (20, 100, and 500 mg) of rifampicin was investigated. Rifampicin is perhaps the most well documented CYP3A inducer in vivo, and is used as a positive control in induction studies in vitro. Rifampicin is also an inducer of CYP1A, CYP2B6, and CYP2C enzymes. By the use of the Karolinska cocktail, the response of four P450s could be investigated at one time point in the same subject. CYP1A2 and CYP2C9 were induced after 500 mg rifampicin daily, and CYP2C19 after 100 mg rifampicin daily. A strong 4-fold induction of CYP3A4 was seen at 500 mg rifampicin daily for both quinine/3 -hydroxyquinine and 4ß-hydroxycholesterol measurements (p<0.001). CYP3A4 was also induced at the two lower doses of rifampicin measured by either of these two markers (p<0.01). A strong correlation (Spearman rank rs=0.71; 95% C.I.=0.52-0.90; p<0.001; n=22) of the two CYP3A4 markers indicates that the cholesterol metabolite 4β-hydroxycholesterol could be used as an endogenous marker for CYP3A4 induction. By the use of 4β-hydroxycholesterol, CYP3A4 induction can be investigated concurrently with the pharmacokinetics of the drug candidate in vivo, and no separate CYP3A induction study is needed

Spheroidal Molecular Communication via Diffusion:Signaling Between Homogeneous Cell Aggregates

Recent molecular communication (MC) research has integrated more detailed computational models to capture the dynamics of practical biophysical systems. This paper focuses on developing realistic models for MC transceivers inspired by spheroids – three-dimensional cell aggregates commonly used in organ-on-chip experimental systems. Potential applications that can be used or modeled with spheroids include nutrient transport in organ-on-chip systems, the release of biomarkers or reception of drug molecules by cancerous tumor sites, or transceiver nanomachines participating in information exchange. In this paper, a simple diffusive MC system is considered where a spheroidal transmitter and spheroidal receiver are in an unbounded fluid environment. These spheroidal antennas are modeled as porous media for diffusive signaling molecules, then their boundary conditions and effective diffusion coefficients are characterized. Furthermore, for either a point source or spheroidal transmitter, the Green’s function for concentration (GFC) outside and inside the receiving spheroid is analytically derived and formulated in terms of an infinite series and confirmed with a particle-based simulator (PBS). The provided GFCs enable computation of the transmitted and received signals in the proposed spheroidal communication system. This study shows that the porous structure of the receiving spheroid amplifies diffusion signals but also disperses them, thus there is a trade-off between porosity and information transmission rate. Furthermore, the results reveal that the porous arrangement of the transmitting spheroid not only disperses the received signal but also attenuates it in comparison to a point source transmitter. System performance is also evaluated in terms of the bit error rate (BER). Decreasing the porosity of the receiving spheroid is shown to enhance the system performance. Conversely, reducing the porosity of the transmitting spheroid can adversely affect system performance

Integrated experimental-computational analysis of a HepaRG liver-islet microphysiological system for human-centric diabetes research

Microphysiological systems (MPS) are powerful tools for emulating human physiology and replicating disease progression in vitro. MPS could be better predictors of human outcome than current animal models, but mechanistic interpretation and in vivo extrapolation of the experimental results remain significant challenges. Here, we address these challenges using an integrated experimental-computational approach. This approach allows for in silico representation and predictions of glucose metabolism in a previously reported MPS with two organ compartments (liver and pancreas) connected in a closed loop with circulating medium. We developed a computational model describing glucose metabolism over 15 days of culture in the MPS. The model was calibrated on an experiment-specific basis using data from seven experiments, where HepaRG single-liver or liver-islet cultures were exposed to both normal and hyperglycemic conditions resembling high blood glucose levels in diabetes. The calibrated models reproduced the fast (i.e. hourly) variations in glucose and insulin observed in the MPS experiments, as well as the long-term (i.e. over weeks) decline in both glucose tolerance and insulin secretion. We also investigated the behaviour of the system under hypoglycemia by simulating this condition in silico, and the model could correctly predict the glucose and insulin responses measured in new MPS experiments. Last, we used the computational model to translate the experimental results to humans, showing good agreement with published data of the glucose response to a meal in healthy subjects. The integrated experimental-computational framework opens new avenues for future investigations toward disease mechanisms and the development of new therapies for metabolic disorders.Funding Agencies|Swedish Research Council [2018-05418, 2018-03319]; CENIIT [15.09]; Swedish Foundation for Strategic Research [ITM17-0245]; SciLifeLab/KAW; Knut and Alice Wallenberg Foundation [2020.0182]; H2020 project PRECISE4Q [777107]; Swedish Fund for Research without Animal Experiments [F2019-0010]; ELLIIT [2020-A12]</p