Virtual tissue models

Another virtual tissue model being developed is the v-embryo. This simulation investigates teratogenesis, or the production of birth defects, resulting from chemical exposures in a pregnant woman. The model is being constructed largely from zebrafish... 

These may be produced by grouping together multiple cell models to form virtual tissue segments, or even the whole organ. The validity of such multi-cellular constructs crucially depends on whether or not they take into account the heart s fine architecture, as cardiac structure and function are tightly interrelated. 

This concept is now termed virtual soft tissue simulation and has been elegantly implemented in the latest models of the AMTI knee simulator (Figure 26.18). This implementation was combined with adaptive control in this simulator, allowing the electronics to gradually exaggerate or attenuate the cyclic actuation waveforms until the resulting measured forces and torques are closely, cycle by cycle, made to match the desired input forces and torques with the desired soft tissue model. Comprehensive quantitative studies and formal presentations of this novel system are yet to be published. 

Due to its central role in toxicant metabolism, the liver is one of the first organs being constructed in the Virtual Tissue Research Project. Physiologically based pharmacokinetic modeling, cellular systems, and molecular networks are integrated to mimic the multitude of activities performed by the liver. Once completed, this innovative project will be an invaluable resource for accessible, accurate, and responsible prediction of liver toxicity. 

To implement the Physiome Project, a lot of good science (Wolpert) and thinking (Dover) will be required. The tools that will ultimately define the success of the project are analytical models of biological processes that have predictive power - virtual cells, tissues, organs and systems. 

The individual modules of the in situ heart can be coupled together to compute a whole sequence from ventricular pressure development, coronary perfusion, tissue supply of metabolites, cell energy consumption, and electrophysiology, to contractile activity and ventricular pressure development in the subsequent beat. The starting point (here chosen as ventricular pressure development) can be freely selected, and drug effects on the system can be simulated. Inserted into a virtual torso, these models allow one to compute the spread of excitation, its cellular basis, and the consequences for an ECG under normal and pathological conditions. 

No modern studies of the human pharmacokinetics of LSD have been done, largely because human experimentation has virtually stopped. An older study that used a spectrofluorometric technique for measuring plasma concentrations of LSD was done in humans given doses of 2 Mg/kg i.v. After equilibration had occurred in about 30 min, the plasma level was between 6 and 7 ng/ml. Subsequently, plasma levels gradually fell until only a small amount of LSD was present after 8 hr. The half-life of the drug in humans was calculated to be 175 min (2). Subsequent pharmacokinetic analysis of these data indicated that plasma concentrations of LSD were explained by a two-compartment open model. Performance scores were highly correlated with concentration in the tissue (outer) compartment, which was calculated at 11.5% of body weight. The new estimation of half-life for loss of LSD from plasma, based on this model, was 103 min (47). 

As of this writing there were 23 raft proteomic analyses reported in the literature but since virtually all of these were performed in different biological systems a comprehensive picture of rafts is difficult to establish. Indeed, a single unified model of raft protein composition would be meaningless anyway since cell and tissue-type differences in rafts certainly exist. For example, TCR and BCR are expressed only in specific hematopoetic cells and would not be expected in epithelial cells. Nonetheless, the ubiquitousness of rafts suggests that there is likely a common core set of proteins that at least provide structure to the membrane subdomains. 

Tissue-level expression patterns for the target molecule were then identified (see table 14.5), and based on the level of expression, individual model components were identified based on the numbers derived in table 14.4, each pathway in each virtual patient was modified appropriately. 

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