Computer simulation of glioma growth and morphology.

Despite major advances in the study of glioma, the quantitative links between intra-tumor molecular/cellular properties, clinically observable properties such as morphology, and critical tumor behaviors such as growth and invasiveness remain unclear, hampering more effective coupling of tumor physical characteristics with implications for prognosis and therapy. Although molecular biology, histopathology, and radiological imaging are employed in this endeavor, studies are severely challenged by the multitude of different physical scales involved in tumor growth, i.e., from molecular nanoscale to cell microscale and finally to tissue centimeter scale. Consequently, it is often difficult to determine the underlying dynamics across dimensions. New techniques are needed to tackle these issues. Here, we address this multi-scalar problem by employing a novel predictive three-dimensional mathematical and computational model based on first-principle equations (conservation laws of physics) that describe mathematically the diffusion of cell substrates and other processes determining tumor mass growth and invasion. The model uses conserved variables to represent known determinants of glioma behavior, e.g., cell density and oxygen concentration, as well as biological functional relationships and parameters linking phenomena at different scales whose specific forms and values are hypothesized and calculated based on in vitro and in vivo experiments and from histopathology of tissue specimens from human gliomas. This model enables correlation of glioma morphology to tumor growth by quantifying interdependence of tumor mass on the microenvironment (e.g., hypoxia, tissue disruption) and on the cellular phenotypes (e.g., mitosis and apoptosis rates, cell adhesion strength). Once functional relationships between variables and associated parameter values have been informed, e.g., from histopathology or intra-operative analysis, this model can be used for disease diagnosis/prognosis, hypothesis testing, and to guide surgery and therapy. In particular, this tool identifies and quantifies the effects of vascularization and other cell-scale glioma morphological characteristics as predictors of tumor-scale growth and invasion.

Computer simulation of glioma growth and morphology.

Despite major advances in the study of glioma, the quantitative links between intra-tumor molecular/cellular properties, clinically observable properties such as morphology, and critical tumor behaviors such as growth and invasiveness remain unclear, hampering more effective coupling of tumor physical characteristics with implications for prognosis and therapy. Although molecular biology, histopathology, and radiological imaging are employed in this endeavor, studies are severely challenged by the multitude of different physical scales involved in tumor growth, i.e., from molecular nanoscale to cell microscale and finally to tissue centimeter scale. Consequently, it is often difficult to determine the underlying dynamics across dimensions. New techniques are needed to tackle these issues. Here, we address this multi-scalar problem by employing a novel predictive three-dimensional mathematical and computational model based on first-principle equations (conservation laws of physics) that describe mathematically the diffusion of cell substrates and other processes determining tumor mass growth and invasion. The model uses conserved variables to represent known determinants of glioma behavior, e.g., cell density and oxygen concentration, as well as biological functional relationships and parameters linking phenomena at different scales whose specific forms and values are hypothesized and calculated based on in vitro and in vivo experiments and from histopathology of tissue specimens from human gliomas. This model enables correlation of glioma morphology to tumor growth by quantifying interdependence of tumor mass on the microenvironment (e.g., hypoxia, tissue disruption) and on the cellular phenotypes (e.g., mitosis and apoptosis rates, cell adhesion strength). Once functional relationships between variables and associated parameter values have been informed, e.g., from histopathology or intra-operative analysis, this model can be used for disease diagnosis/prognosis, hypothesis testing, and to guide surgery and therapy. In particular, this tool identifies and quantifies the effects of vascularization and other cell-scale glioma morphological characteristics as predictors of tumor-scale growth and invasion.

Influence of blood contamination on bond strength of a self-etching system.

OBJECTIVES: To detect the influence of blood contamination (BC) on the bond strength (BS) of a self-etching bonding system (SES) to enamel and dentine. METHODS: 25 human molars were longitudinally sectioned on the mesio-distal axis in order to obtain 50 specimens, which were embedded in acrylic resin. At first, the specimens were ground to expose a flat surface of enamel, and a bond strength test was performed. Afterwards, the samples were ground again in order to obtain a flat surface of dentine. Ten groups (total: n=100) were assigned according to substrate (enamel and dentine), step in the bonding sequence when contamination occurred (before the acidic primer and after the bonding resin), and contamination treatment (dry or rinse and dry procedure). Fresh human blood was introduced either before or after SES application (Clearfil SE Bond) and treated with air drying, or by rinsing and drying following application. Composite resin (Filtek Z-250,3M ESPE) was applied as inverted, truncated cured cones that were debonded in tension. RESULTS: The mean tensile BS values (MPa) for enamel/dentine were 19.4/23.0 and 17.1/10.0 for rinse-and-dry treatment (contamination before and after SES, respectively); while the measurements for the dry treatment, 16.2/23.3 and 0.0/0.0 contamination before and after SES, respectively. CONCLUSIONS: It was determined that blood contamination impaired adhesion to enamel and dentine when it occurred after bond light curing. Among the tested contamination treatments, the rinse-and-dry treatment produced the highest bond strength with BC after SES application, but it was not sufficient to recover the BS in the contamination-free group.