RESUMEN
Cerebral gas embolism is a serious consequence of diving. It is associated with decompression sickness and is assumed to cause severe neurological dysfunction. A mathematical model previously developed to calculate embolism absorption time based on in vivo bubble geometry is used in which various conditions of hyperbaric therapy are considered. Effects of varying external pressure and inert gas concentrations in the breathing mixtures, according to US Navy and Royal Navy diving treatment tables, are predicted. Recompression alone is calculated to reduce absorption times of a 50-nl bubble by up to 98% over the untreated case. Lowering the inhaled inert gas concentration from 67.5% to 50% reduces absorption time by 37% at a given pressure. Bubbles formed after diving and decompression with He are calculated to absorb up to 73% faster than bubbles created after diving and decompression with air, regardless of the recompression gas breathed. This model is a useful alternative to impractical clinical trials in assessing which initial step in hyperbaric therapy is most effective in eliminating cerebral gas embolisms should they occur.
Asunto(s)
Embolia Aérea/terapia , Oxigenoterapia Hiperbárica , Embolia Intracraneal/terapia , Modelos Teóricos , Absorción , Aire , Humanos , Gases Nobles/química , Oxígeno/química , Presión , Factores de TiempoRESUMEN
Multifocal cerebrovascular gas embolism occurs frequently during cardiopulmonary bypass and is thought to cause postoperative neurological dysfunction in large numbers of patients. We developed a mathematical model to predict the absorption time of intravascular gas embolism, accounting for the bubble geometry observed in vivo. We modeled bubbles as cylinders with hemispherical end caps and solved the resulting governing gas transport equations numerically. We validated the model using data obtained from video-microscopy measurements of bubbles in the intact cremaster microcirculation of anesthetized male Wistar rats. The theoretical model with the use of in vivo geometry closely predicted actual absorption times for experimental intravascular gas embolisms and was more accurate than a model based on spherical shape. We computed absorption times for cerebrovascular gas embolism assuming a range of bubble geometries, initial volumes, and parameters relevant to brain blood flow. Results of the simulations demonstrated absorption time maxima and minima based on initial geometry, with several configurations taking as much as 50% longer to be absorbed than would a comparable spherical bubble.
Asunto(s)
Embolia Aérea/metabolismo , Modelos Cardiovasculares , Absorción , Animales , Simulación por Computador , Predicción , Masculino , Microcirculación , Músculo Esquelético/irrigación sanguínea , Ratas , Ratas Wistar , Factores de TiempoRESUMEN
Adhesion, spreading, and focal contact formation of primary bone-derived cells on quartz surfaces grafted with a 15 amino acid peptide that contained a -RGD-(-Arg-Gly-Asp-) sequence unique to bone sialoprotein was investigated. The peptide surfaces were fabricated by using a heterbifunctional crosslinker, sulfosuccinimidyal 4-(N-maleimidomethyl)cyclohexane-1-carboxylate, to link the peptide to amine functionalized quartz surfaces. Contact angle measurements, spectroscopic ellipsometry, and X-ray photoelectron spectroscopy were used to confirm the chemistry and thickness of the overlayers. A radial flow apparatus was used to characterize cell detachment from peptide-grafted surfaces. After 20 min of cell incubation, the strength of cell adhesion was significantly (p < 0.05) higher on the -RGD- compared to -RGE- (control) surfaces. Furthermore, the mean area of cells contacting the -RGD- was significantly (p < 0.05) higher than -RGE- surfaces. Vinculin staining showed formation of small focal contact patches on the periphery of bone cells incubated for 2 h on the -RGD- surfaces; however, few or no focal contacts were formed by cells seeded on the -RGE-grafted surfaces. The methods of peptide immobilization utilized in this study can be applied to implants, biosensors, and diagnostic devices that require specificity in cell adhesion.