Modeling the diffusion of D-2-hydroxyglutarate from IDH1 mutant gliomas in the central nervous system

Background

Among diffusely infiltrative gliomas in adults, 20%-30% contain a point mutation in isocitrate dehydrogenase 1 (IDH1mut), which increases production of D-2-hydroxyglutarate (D2HG). This is so efficient that D2HG often reaches 30 mM within IDH1mut gliomas. Yet, while up to 100 µM D2HG can be detected in the circulating cerebrospinal fluid of IDH1mut glioma patients, the exposure of nonneoplastic cells within and surrounding an IDH1mut glioma to D2HG is unknown and difficult to measure directly.

Methods

Conditioned medium from patient-derived wild type IDH1 (IDH1wt) and IDH1mut glioma cells was analyzed for D2HG by liquid chromatography-mass spectrometry (LC-MS). Mathematical models of D2HG release and diffusion around an IDH1mut glioma were independently generated based on fluid dynamics within the brain and on previously reported intratumoral and cerebrospinal D2HG concentrations.

Results

LC-MS analysis indicates that patient-derived IDH1mut glioma cells release 3.7-97.0 pg D2HG per cell per week. Extrapolating this to an average-sized tumor (30 mL glioma volume and 1 × 108 cells/mL tumor), the rate of D2HG release by an IDH1mut glioma (SA) is estimated at 3.2-83.0 × 10-12 mol/mL/sec. Mathematical models estimate an SA of 2.9-12.9 × 10-12 mol/mL/sec, within the range of the in vitro LC-MS data. In even the most conservative of these models, the extracellular concentration of D2HG exceeds 3 mM within a 2 cm radius from the center of an IDH1mut glioma.

Conclusions

The microenvironment of an IDH1mut glioma is likely being exposed to high concentrations of D2HG, in the low millimolar range. This has implications for understanding how D2HG affects nonneoplastic cells in an IDH1mut glioma.

Starling forces drive intracranial water exchange during normal and pathological states

AIM

To quantify the exchange of water between cerebral compartments, specifically blood, tissue, perivascular pathways, and cerebrospinal fluid-filled spaces, on the basis of experimental data and to propose a dynamic global model of water flux through the entire brain to elucidate functionally relevant fluid exchange phenomena.

METHODS

The mechanistic computer model to predict brain water shifts is discretized by cerebral compartments into nodes. Water and species flux is calculated between these nodes across a network of arcs driven by Hagen-Poiseuille flow (blood), Darcy flow (interstitial fluid transport), and Starling's Law (transmembrane fluid exchange). Compartment compliance is accounted for using a pressure-volume relationship to enforce the Monro-Kellie doctrine. This nonlinear system of differential equations is solved implicitly using MATLAB software.

RESULTS

The model predictions of intraventricular osmotic injection caused a pressure rise from 10 to 22 mmHg, followed by a taper to 14 mmHg over 100 minutes. The computational results are compared to experimental data with R2=0.929. Moreover, simulated osmotic therapy of systemic (blood) injection reduced intracranial pressure from 25 to 10 mmHg. The modeled volume and intracranial pressure changes following cerebral edema agree with experimental trends observed in animal models with R2=0.997.

CONCLUSION

The model successfully predicted time course and the efficacy of osmotic therapy for clearing cerebral edema. Furthermore, the mathematical model implicated the perivascular pathways as a possible conduit for water and solute exchange. This was a first step to quantify fluid exchange throughout the brain.

Large-scale subject-specific cerebral arterial tree modeling using automated parametric mesh generation for blood flow simulation

In this paper, we present a novel technique for automatic parametric mesh generation of subject-specific cerebral arterial trees. This technique generates high-quality and anatomically accurate computational meshes for fast blood flow simulations extending the scope of 3D vascular modeling to a large portion of cerebral arterial trees. For this purpose, a parametric meshing procedure was developed to automatically decompose the vascular skeleton, extract geometric features and generate hexahedral meshes using a body-fitted coordinate system that optimally follows the vascular network topology. To validate the anatomical accuracy of the reconstructed vasculature, we performed statistical analysis to quantify the alignment between parametric meshes and raw vascular images using receiver operating characteristic curve. Geometric accuracy evaluation showed an agreement with area under the curves value of 0.87 between the constructed mesh and raw MRA data sets. Parametric meshing yielded on-average, 36.6% and 21.7% orthogonal and equiangular skew quality improvement over the unstructured tetrahedral meshes. The parametric meshing and processing pipeline constitutes an automated technique to reconstruct and simulate blood flow throughout a large portion of the cerebral arterial tree down to the level of pial vessels. This study is the first step towards fast large-scale subject-specific hemodynamic analysis for clinical applications.

Design and first results of CytoBuoy: a wireless flow cytometer for in situ analysis of marine and fresh waters

BACKGROUND

The high costs of microscopical determination and counting of phytoplankton often limit sampling frequencies below an acceptable level for the monitoring of dynamic ecosystems. Although having a limited discrimination power, flow cytometry allows the analysis of large numbers of samples to a level that is sufficient for many basic monitoring jobs. For this purpose, flow cytometers should not be restricted to research laboratories. We report here on the development of an in situ flow cytometer for autonomous operation inside a small moored buoy or on other platforms.

METHODS AND RESULTS

Operational specifications served a wide range of applications in the aquatic field. Specific conditions had to be met with respect to the operation platform and autonomy. A small, battery-operated flow cytometer resulted, requiring no external sheath fluid supply. Because it was designed to operate in a buoy, we call it CytoBuoy. Sampling, analysis, and radio transmission of the data proceed automatically at user-defined intervals. A powerful feature is the acquisition and radio transmission of full detector pulse shapes of each particle. This provides valuable morphological information for particles larger than the 5-microm laser focus.

CONCLUSIONS

CytoBuoy allows on-line in situ particle analysis, estimation of phytoplankton biomass, and discrimination between different phytoplankton groups. This will increase the applicability of flow cytometry in the field of environmental monitoring.