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1. Variations in mechanical stiffness alter microvascular sprouting and stability in a PEG hydrogel model of idiopathic pulmonary fibrosis

   https://doi.org/10.1111/micc.12817  

   Leonard‐Duke, Julie ; Bruce, Anthony C. ; Peirce, Shayn M. ; Taite, Lakeshia J. ( May 2023 , Microcirculation)

   Microvascular remodeling is governed by biomechanical and biochemical cues which are dysregulated in idiopathic pulmonary fibrosis. Understanding how these cues impact endothelial cell‐pericyte interactions necessitates a model system in which both variables can be independently and reproducibly modulated. In this study we develop a tunable hydrogel‐based angiogenesis assay to study how varying angiogenic growth factors and environmental stiffness affect sprouting and vessel organization.

   Lungs harvested from mice were cut into 1 mm long segments then cultured on hydrogels having one of seven possible stiffness and growth factor combinations. Time course, brightfield, and immunofluorescence imaging were used to observe and quantify sprout formation.

   Our assay was able to support angiogenesis in a comparable manner to Matrigel in soft 2 kPa gels while enabling tunability to study the effects of stiffness on sprout formation. Matrigel and 2 kPa groups contained significantly more samples with sprouts when compared to the stiffer 10 and 20 kPa gels. Growth factor treatment did not have as obvious an effect, although the 20 kPa PDGF + FGF‐treated group had significantly longer vessels than the vascular endothelial growth factor‐treated group.

   We have developed a novel, tunable hydrogel assay for the creation of lung explant vessel organoids which can be modulated to study the impact of specific environmental cues on vessel formation and maturation.

    

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2. Distinct time courses and mechanics of right ventricular hypertrophy and diastolic stiffening in a male rat model of pulmonary arterial hypertension

   https://doi.org/10.1152/ajpheart.00046.2021  

   Kwan, Ethan D. ; Vélez-Rendón, Daniela ; Zhang, Xiaoyan ; Mu, Hao ; Patel, Megh ; Pursell, Erica ; Stowe, Jennifer ; Valdez-Jasso, Daniela ( October 2021 , American Journal of Physiology-Heart and Circulatory Physiology)

   Although pulmonary arterial hypertension (PAH) leads to right ventricle (RV) hypertrophy and structural remodeling, the relative contributions of changes in myocardial geometric and mechanical properties to systolic and diastolic chamber dysfunction and their time courses remain unknown. Using measurements of RV hemodynamic and morphological changes over 10 wk in a male rat model of PAH and a mathematical model of RV mechanics, we discriminated the contributions of RV geometric remodeling and alterations of myocardial material properties to changes in systolic and diastolic chamber function. Significant and rapid RV hypertrophic wall thickening was sufficient to stabilize ejection fraction in response to increased pulmonary arterial pressure by week 4 without significant changes in systolic myofilament activation. After week 4, RV end-diastolic pressure increased significantly with no corresponding changes in end-diastolic volume. Significant RV diastolic chamber stiffening by week 5 was not explained by RV hypertrophy. Instead, model analysis showed that the increases in RV end-diastolic chamber stiffness were entirely attributable to increased resting myocardial material stiffness that was not associated with significant myocardial fibrosis or changes in myocardial collagen content or type. These findings suggest that whereas systolic volume in this model of RV pressure overload is stabilized by early RV hypertrophy, diastolic dilation is prevented by subsequent resting myocardial stiffening. NEW & NOTEWORTHY Using a novel combination of hemodynamic and morphological measurements over 10 wk in a male rat model of PAH and a mathematical model of RV mechanics, we found that compensated systolic function was almost entirely explained by RV hypertrophy, but subsequently altered RV end-diastolic mechanics were primarily explained by passive myocardial stiffening that was not associated with significant collagen extracellular matrix accumulation. 

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3. Assessing the Comparative Effects of Storm-Relative Helicity Components within Right-Moving Supercell Environments

   https://doi.org/10.1175/JAS-D-22-0253.1  

   Goldacker, Nicholas A. ; Parker, Matthew D. ( December 2023 , Journal of the Atmospheric Sciences)

   Supercell thunderstorms develop low-level rotation via tilting of environmental horizontal vorticity (ω_h) by the updraft. This rotation induces dynamic lifting that can stretch near-surface vertical vorticity into a tornado. Low-level updraft rotation is generally thought to scale with 0–500 m storm-relative helicity (SRH): the combination of storm-relative flow, |SRF|, |ω_h|, and cosϕ(whereϕis the angle betweenSRFandω_h). It is unclear how much influence each component of SRH has in intensifying the low-level mesocyclone. This study surveys these three components using self-organizing maps (SOMs) to distill 15 906 proximity soundings for observed right-moving supercells. Statistical analyses reveal the component most highly correlated to SRH and to streamwise vorticity (ω_s) in the observed profiles is |ω_h|. Furthermore, |ω_h| and |SRF| are themselves highly correlated due to their shared dependence on the hodograph length. The representative profiles produced by the SOMs were combined with a common thermodynamic profile to initialize quasi-realistic supercells in a cloud model. The simulations reveal that, across a range of real-world profiles, intense low-level mesocyclones are most closely linked toω_handSRF, while the angle between them appears to be mostly inconsequential.

   About three-fourths of all tornadoes are produced by rotating thunderstorms (supercells). When the part of the storm near cloud base (approximately 1 km above the ground) rotates more strongly, the chance of a tornado dramatically increases. The goal of this study is to identify the simplest characteristic(s) of the environmental wind profile that can be used to forecast the likelihood of strong cloud-base rotation. This study concludes that the most important ingredients for storm rotation are the magnitudes of the horizontal vertical wind shear between the surface and 500 m and the storm inflow wind, irrespective of their relative directions. This finding may lead to improved operational identification of environments favoring tornado formation.

    

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4. Sensitivity analysis and uncertainty quantification of 1‐D models of pulmonary hemodynamics in mice under control and hypertensive conditions

   https://doi.org/10.1002/cnm.3242  

   Colebank, Mitchel J. ; Umar Qureshi, M. ; Olufsen, Mette S. ( September 2019 , International Journal for Numerical Methods in Biomedical Engineering)

   Pulmonary hypertension (PH), defined as an elevated mean blood pressure in the main pulmonary artery (MPA) at rest, is associated with vascular remodeling of both large and small arteries. PH has several sub‐types that are all linked to high mortality rates. In this study, we use a one‐dimensional (1‐D) fluid dynamics model driven by in vivo measurements of MPA flow to understand how model parameters and network size influence MPA pressure predictions in the presence of PH. We compare model predictions with in vivo MPA pressure measurements from a control and a hypertensive mouse and analyze results in three networks of increasing complexity, extracted from micro‐computed tomography (micro‐CT) images. We introduce global scaling factors for boundary condition parameters and perform local and global sensitivity analysis to calculate parameter influence on model predictions of MPA pressure and correlation analysis to determine a subset of identifiable parameters. These are inferred using frequentist optimization and Bayesian inference via the Delayed Rejection Adaptive Metropolis (DRAM) algorithm. Frequentist and Bayesian uncertainty is computed for model parameters and MPA pressure predictions. Results show that MPA pressure predictions are most sensitive to distal vascular resistance and that parameter influence changes with increasing network complexity. Our outcomes suggest that PH leads to increased vascular stiffness and decreased peripheral compliance, congruent with clinical observations.

    

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5. Deep phenotyping of cardiac function in heart transplant patients using cardiovascular system models

   https://doi.org/10.1113/JP279393  

   Colunga, Amanda L. ; Kim, Karam G. ; Woodall, N. Payton ; Dardas, Todd F. ; Gennari, John H. ; Olufsen, Mette S. ; Carlson, Brian E. ( June 2020 , The Journal of Physiology)

   Right heart catheterization data from clinical records of heart transplant patients are used to identify patient‐specific models of the cardiovascular system.

   These patient‐specific cardiovascular models represent a snapshot of cardiovascular function at a given post‐transplant recovery time point.

   This approach is used to describe cardiac function in 10 heart transplant patients, five of which had multiple right heart catheterizations allowing an assessment of cardiac function over time.

   These patient‐specific models are used to predict cardiovascular function in the form of right and left ventricular pressure‐volume loops and ventricular power, an important metric in the clinical assessment of cardiac function.

   Outcomes for the longitudinally tracked patients show that our approach was able to identify the one patient from the group of five that exhibited post‐transplant cardiovascular complications.

   Heart transplant patients are followed with periodic right heart catheterizations (RHCs) to identify post‐transplant complications and guide treatment. Post‐transplant positive outcomes are associated with a steady reduction of right ventricular and pulmonary arterial pressures, toward normal levels of right‐side pressure (about 20 mmHg) measured by RHC. This study shows that more information about patient progression is obtained by combining standard RHC measures with mechanistic computational cardiovascular system models. The purpose of this study is twofold: to understand how cardiovascular system models can be used to represent a patient's cardiovascular state, and to use these models to track post‐transplant recovery and outcome. To obtain reliable parameter estimates comparable within and across datasets, we use sensitivity analysis, parameter subset selection, and optimization to determine patient‐specific mechanistic parameters that can be reliably extracted from the RHC data. Patient‐specific models are identified for 10 patients from their first post‐transplant RHC, and longitudinal analysis is carried out for five patients. Results of the sensitivity analysis and subset selection show that we can reliably estimate seven non‐measurable quantities; namely, ventricular diastolic relaxation, systemic resistance, pulmonary venous elastance, pulmonary resistance, pulmonary arterial elastance, pulmonary valve resistance and systemic arterial elastance. Changes in parameters and predicted cardiovascular function post‐transplant are used to evaluate the cardiovascular state during recovery of five patients. Of these five patients, only one showed inconsistent trends during recovery in ventricular pressure–volume relationships and power output. At the four‐year post‐transplant time point this patient exhibited biventricular failure along with graft dysfunction while the remaining four exhibited no cardiovascular complications.

    

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