CREB-binding protein (CBP) is a transcriptional co-activator which is required by many transcription factors. Rubinstein-Taybi syndrome (RTS), which is an autosomal dominant syndrome characterized by abnormal pattern formation, is associated with mutations in the human CBP gene. Various abnormalities occur at high frequency in the skeletal system of heterozygous Cbp-deficient mice, but some features of RTS such as cardiac anomalies do not, suggesting that some symptoms of RTS are caused by a dominant-negative mechanism. Here we report the characterization of homozygous Cbp-deficient mice. Homozygous mutants died around E10.5-E12.5, apparently as a result of massive hemorrhage caused by defective blood vessel formation in the central nervous system, and exhibited apparent developmental retardation as well as delays in both primitive and definitive hematopoiesis. Cbp-deficient embryos exhibited defective neural tube closure which was similar to those observed in twist-deficient embryos. However, a decrease in the level of twist expression was not observed in Cbp-deficient embryos. Anomalous heart formation, a feature of RTS patients and mice mutated in the CBP-related molecule, p300, was not observed in Cbp-deficient embryos. Since both Cbp and p300 are ubiquitously expressed in embryonic tissues including the developing heart, these results suggest that cardiac anomalies observed in RTS patients may be caused by a dominant negative effect of mutant CBP.
Mouse newborns find their mother’s nipples and suckle milk by themselves. It has been argued which sense organ they use when locating their mother’s nipples to suckle milk. Olfactory or tactile sensory systems are primary candidates. In the present study, we investigated the trigeminal-whisker sensory and olfactory systems in genetic arhinencephaly mouse embryos (Pdn/Pdn). Pdn/Pdn newborns do not suckle milk and die within 1 day after birth. Dysfunction of nipple-searching behavior was clear in Pdn/Pdn newborns. Pdn/Pdn newborns had a complete developmental failure in the olfactory nerve projection to the central nervous system and no olfactory bulb architecture. The trigeminal-whisker system was intact in this strain. From the results of these experiments, it was suggested that the olfactory system is essential for nipple-searching behavior and suckling milk and that the trigeminal-whisker system is not able to substitute for the lack of olfactory input in mouse newborns.
Non invasive fractional flow reserve derived from CT coronary angiography (CT-FFR) has to date been typically performed using the principles of fluid analysis in which a lumped parameter coronary vascular bed model is assigned to represent the impedance of the downstream coronary vascular networks absent in the computational domain for each coronary outlet. This approach may have a number of limitations. It may not account for the impact of the myocardial contraction and relaxation during the cardiac cycle, patient-specific boundary conditions for coronary artery outlets and vessel stiffness. We have developed a novel approach based on 4D-CT image tracking (registration) and structural and fluid analysis, to address these issues. In our approach, we analyzed the deformation variation of vessels and the volume variation of vessels, primarily from 70% to 100% of cardiac phase, to better define boundary conditions and stiffness of vessels. We used a statistical estimation method based on a hierarchical Bayes model to integrate 4D-CT measurements and structural and fluid analysis data. Under these analysis conditions, we performed structural and fluid analysis to determine pressure, flow rate and CT-FFR. The consistency of this method has been verified by a comparison of 4D-CT-FFR analysis results derived from five clinical 4D-CT datasets with invasive measurements of FFR. Additionally, phantom experiments of flexible tubes with/without stenosis using pulsating pumps, flow sensors and pressure sensors were performed. Our results show that the proposed 4D-CT-FFR analysis method has the potential to accurately estimate the effect of coronary artery stenosis on blood flow.
Non invasive fractional flow reserve derived from CT coronary angiography (CT-FFR) has to date been typically performed using the principles of computational fluid analysis in which a lumped parameter coronary vascular bed model is assigned to represent the impedance of the downstream coronary vascular networks absent in the computational domain for each coronary outlet. This approach may have a number of limitations. It may not account for the impact of the myocardial contraction and relaxation during the cardiac cycle, patient-specific boundary conditions for coronary artery outlets and vessel stiffness. We have developed a novel approach based on 4D-CT image tracking (registration) and structural and fluid analysis based on one dimensional mechanical model, to address these issues. In our approach, we analyzed the deformation variation of vessels and the volume variation of vessels to better define boundary conditions and stiffness of vessels. We focused on the blood flow and vessel deformation of coronary arteries and aorta near coronary arteries in the diastolic cardiac phase from 70% to 100 %. The blood flow variation of coronary arteries relates to the deformation of vessels, such as expansion and contraction of the cross-sectional area, during this period where resistance is stable, pressure loss is approximately proportional to flow. We used a statistical estimation method based on a hierarchical Bayes model to integrate 4D-CT measurements and structural and fluid analysis data. Under these analysis conditions, we performed structural and fluid analysis to determine pressure, flow rate and CT-FFR. Furthermore, the reduced-order model based on fluid analysis was studied in order to shorten the computational time for 4D-CT-FFR analysis. The consistency of this method has been verified by a comparison of 4D-CT-FFR analysis results derived from five clinical 4D-CT datasets with invasive measurements of FFR. Additionally, phantom experiments of flexible tubes with and without stenosis using pulsating pumps, flow sensors and pressure sensors were performed. Our results show that the proposed 4D-CT-FFR analysis method has the potential to accurately estimate the effect of coronary artery stenosis on blood flow.
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