Biomechanics & remodeling of PGS-derived tissue engineered arteries

Issued as final reportNational Science Foundation (U.S.

Contractile force is enhanced in Aortas from pendrin null mice due to stimulation of angiotensin II-dependent signaling.

Pendrin is a Cl-/HCO3- exchanger expressed in the apical regions of renal intercalated cells. Following pendrin gene ablation, blood pressure falls, in part, from reduced renal NaCl absorption. We asked if pendrin is expressed in vascular tissue and if the lower blood pressure observed in pendrin null mice is accompanied by reduced vascular reactivity. Thus, the contractile responses to KCl and phenylephrine (PE) were examined in isometrically mounted thoracic aortas from wild-type and pendrin null mice. Although pendrin expression was not detected in the aorta, pendrin gene ablation changed contractile protein abundance and increased the maximal contractile response to PE when normalized to cross sectional area (CSA). However, the contractile sensitivity to this agent was unchanged. The increase in contractile force/cross sectional area observed in pendrin null mice was due to reduced cross sectional area of the aorta and not from increased contractile force per vessel. The pendrin-dependent increase in maximal contractile response was endothelium- and nitric oxide-independent and did not occur from changes in Ca2+ sensitivity or chronic changes in catecholamine production. However, application of 100 nM angiotensin II increased force/CSA more in aortas from pendrin null than from wild type mice. Moreover, angiotensin type 1 receptor inhibitor (candesartan) treatment in vivo eliminated the pendrin-dependent changes contractile protein abundance and changes in the contractile force/cross sectional area in response to PE. In conclusion, pendrin gene ablation increases aorta contractile force per cross sectional area in response to angiotensin II and PE due to stimulation of angiotensin type 1 receptor-dependent signaling. The angiotensin type 1 receptor-dependent increase in vascular reactivity may mitigate the fall in blood pressure observed with pendrin gene ablation

All-sky search for gravitational-wave bursts in the second joint LIGO-Virgo run

We present results from a search for gravitational-wave bursts in the data collected by the LIGO and Virgo detectors between July 7, 2009 and October 20, 2010: data are analyzed when at least two of the three LIGO-Virgo detectors are in coincident operation, with a total observation time of 207 days. The analysis searches for transients of duration < 1 s over the frequency band 64-5000 Hz, without other assumptions on the signal waveform, polarization, direction or occurrence time. All identified events are consistent with the expected accidental background. We set frequentist upper limits on the rate of gravitational-wave bursts by combining this search with the previous LIGO-Virgo search on the data collected between November 2005 and October 2007. The upper limit on the rate of strong gravitational-wave bursts at the Earth is 1.3 events per year at 90% confidence. We also present upper limits on source rate density per year and Mpc^3 for sample populations of standard-candle sources. As in the previous joint run, typical sensitivities of the search in terms of the root-sum-squared strain amplitude for these waveforms lie in the range 5 10^-22 Hz^-1/2 to 1 10^-20 Hz^-1/2. The combination of the two joint runs entails the most sensitive all-sky search for generic gravitational-wave bursts and synthesizes the results achieved by the initial generation of interferometric detectors.Comment: 15 pages, 7 figures: data for plots and archived public version at https://dcc.ligo.org/cgi-bin/DocDB/ShowDocument?docid=70814&version=19, see also the public announcement at http://www.ligo.org/science/Publication-S6BurstAllSky

A mathematical model of vascular and hemodynamics changes in early and late forms of preeclampsia

Abstract Preeclampsia–eclampsia syndrome is a leading cause of maternal mortality. The precise etiology of preeclampsia is still not well‐defined and different forms exist, including early and late forms or preeclampsia, which may arise via distinctly different mechanisms. Low‐dose aspirin administered at the end of the first trimester in women identified as high risk has been shown to reduce the incidence of early, but not late, preeclampsia; however, current risk factors show only fair predictive capability. There is a pressing need to develop accurate descriptions for the different forms of preeclampsia. This paper presents 1D fluid, solid, growth, and remodeling models for pregnancies complicated with early and late forms of preeclampsia. Simulations affirm a broad set of literature results that early forms of preeclampsia are characterized by elevated uterine artery pulsatility index (UA‐PI) and total peripheral resistance (TPR) and lower cardiac output (CO), with modestly increased mean arterial blood pressure (MAP) in the first half of pregnancy, with elevation of TPR and MAP beginning at 20 weeks. Conversely, late forms of preeclampsia are characterized by only slightly elevated UA‐PI and normal pre‐term TPR, and slightly elevated MAP and CO throughout pregnancy, with increased TPR and MAP beginning after 34 weeks. Results suggest that preexisting arterial stiffness may be elevated in women that develop both early forms and late forms of preeclampsia; however, data that verify these results are lacking in the literature. Pulse wave velocity increases in early‐ and late‐preeclampsia, coincident with increases in blood pressure; however, these increases are mainly due to the strain‐stiffening response of larger arteries, rather than arterial remodeling‐derived changes in material properties. These simulations affirm that early forms of preeclampsia may be associated with abnormal placentation, whereas late forms may be more closely associated with preexisting maternal cardiovascular factors; simulations also highlight several critical gaps in available data

Fast and Simple Statistical Shape Analysis of Pregnant Women Using Radial Deformation of a Cylindrical Template

Non-rigid deformation of a template to fit 3D scans of human subjects is widely used to develop statistical models of 3D human shapes and poses. Complex optimization problems must be solved to use these models to parameterize scans of pregnant women, thus limiting their use in antenatal point-of-care tools in low-resource settings. Moreover, these models were developed using datasets that did not contain any 3D scans of pregnant women. In this study, we developed a statistical shape model of the torso of pregnant women at greater than 36 weeks of gestation using fast and simple vertex-based deformation of a cylindrical template constrained along the radial direction. The 3D scans were pre-processed to remove noisy outlier points and segment the torso based on anatomical landmarks. A cylindrical template mesh $T$ was then fitted onto the segmented scan of the torso by moving each vertex of $T$ in the direction of the radial vector. This process is computationally inexpensive taking only 14.80 seconds to deform a template with 9090 vertices. Principal component analysis (PCA) was performed on the deformed vertex co-ordinates to find the directions of maximum variance. The first 10 principal vectors of our model explained 79.03&#x0025; of the total variance and reconstructed unseen scans with a mean error of 2.43 cm. We also used the PCA weights of the first 10 principal vectors to accurately predict anthropometric measurements of the pregnant women

Constructing growth evolution laws of arteries via reinforcement learning

Growth evolution laws, which mathematically describe how living tissues change their shape and properties in response to external stimuli, are required for modeling arterial growth. Tradition-ally, specific forms of growth laws are devised by domain experts. Since in vivo animal studies usually provide limited experimental data, generalization and inference are often employed to prescribe the functional form of growth laws. In this work, we employed the finite growth theory and developed a reinforcement learning (RL) approach to construct growth evolution laws by formulating the arterial growth problem under the framework of the Markov decision process (MDP). To maintain homeostatic stress levels in an optimal manner, RL agents were employed to determine stress-modulated anisotropic growth evolution at each time step. We illustrate the capabilities of the RL-based growth laws in two representative applications: 1) predicting ho-mogenous growth of a thin-walled artery in response to hypertensive blood pressure, and 2) generating residual stress with heterogeneous growth in a thick-walled bi-layer aorta via distributed growth policies. Experimental data, where available, were used to compare expert -prescribed and RL-based growth laws. Our results demonstrated the capabilities of RL to effec-tively control the growth processes in response to hypertension, and the predictions are in good agreement with experimental observations. In particular, the RL growth laws captured the reduction of in vivo axial stretch without using experimental data for training. Moreover, the distributed RL growth policies achieved residual stress generation in a collaborative manner, which may pave the way for implementation in a finite element setting. This study sheds light on a new avenue to uncover growth evolution laws via RL, perhaps reducing the need for large experimental datasets and expert intelligence during growth law construction