Objective: This study sought to elucidate the underlying hemodynamic mechanisms involved in the longitudinal propagation of acute, type-B aortic dissections. Methods: Three-dimensional patient-specific aortic geometry was reconstructed from computed tomography images of 3 cases, followed by computational fluid dynamic analysis using finite-element analysis modeling. Three models were reconstructed; the normal-aortic model (from a healthy volunteer), the visceral-involvement model (from a patient whose visceral arteries were involved) and the progression model (from a patient whose visceral arteries were intact at admission). Wall pressure distribution was analyzed in all three models. Results: In the systolic phase of a cardiac cycle, the wall pressure dropped from the proximal to the distal aorta within the true lumen. This pressure gradient was observed in all three models. A milder pressure gradient was seen in the false lumen in the visceral-involvement model, whereas the pressure in the false lumen remained almost constant in the progression model. The dyssynchrony of the pressure gradients in the true and false lumens caused an imbalance in pressure between the two lumens. Conclusion: The interluminal pressure differential may be a contributing factor in the compression of the true lumen and the cleavage force of the aortic wall, leading to the longitudinal propagation of the dissection.
Burns destroy the skin barrier and alter the resident bacterial community, thereby facilitating bacterial infection. To treat a wound infection, it is necessary to understand the changes in the wound bacterial community structure. However, traditional bacterial cultures allow the identification of only readily growing or purposely cultured bacterial species and lack the capacity to detect changes in the bacterial community. In this study, 16S rRNA gene sequencing was used to detect alterations in the bacterial community structure in deep partial-thickness burn wounds on the back of Sprague-Dawley rats. These results were then compared with those obtained from the bacterial culture. Bacterial samples were collected prior to wounding and 1, 7, 14, and 21 days after wounding. The 16S rRNA gene sequence analysis showed that the number of resident bacterial species decreased after the burn. Both resident bacterial richness and diversity, which were significantly reduced after the burn, recovered following wound healing. The dominant resident strains also changed, but the inhibition of bacterial community structure was in a non-volatile equilibrium state, even in the early stage after healing. Furthermore, the correlation between wound and environmental bacteria increased with the occurrence of burns. Hence, the 16S rRNA gene sequence analysis reflected the bacterial condition of the wounds better than the bacterial culture. 16S rRNA sequencing in the Sprague-Dawley rat burn model can provide more information for the prevention and treatment of burn infections in clinical settings and promote further development in this field.
Chemical flooding is one of enhanced oil recovery (EOR) methods. The primary mechanism of EOR of chemical flooding is interfacial tension reduction, mobility ratio improvement and wettability changes. Recent studies showed that enhancing emulsification performance was beneficial to improve oil displacement efficiency. The formation of Pickering emulsion by nanoparticles could greatly improve the emulsifying performance. Using nanoparticles stabilized emulsions for chemical EOR application is a novel method. In this study, six different types of nanoparticles were selected, including hydrophilic nano silica, modified nano silica, carbon nanotubes and bentonite, etc. The nanoparticle combine with petroleum sulfonate could form a stable emulsion. Particle wettability were measured by using contact angle measurement (OCA20). Emulsifying intensity index was measured for different nanoparticle-stabilized emulsions. The mechanisms of nanoparticle-stabilized emulsions and relationship between emulsion stability have been investigated. The influence of dispersant on nanoparticle-stabilized emulsions also has been investigated. Nanoparticles mainly play a role in improving the stability of emulsions while surfactant play a major role in enhancing the emulsifying dispersion. The wettability of solid particles was one of the most important factors that affects the stability of emulsions. Partial hydrophobic nanoparticles were much easier to form stable emulsions than hydrophilic nanoparticles. Nanoparticles could form a three-dimensional network structure, thereby the stability of the emulsion was improved. Use of surfactant to disperse nanoparticles could further improve the emulsion stability. Finally, three nanoparticles stabilized emulsion formulations were developed for chemical flooding EOR. Nanoparticle-stabilized emulsions could improve oil displacement efficiency in chemical combination flooding. This research was used to optimize chemical combination flooding formulation and has a guidance function for application of nanoparticles in chemical flooding EOR.
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