N-cadherin and ß1 integrin coordinately regulate growth plate cartilage architecture.

Spatial and temporal regulation of chondrocyte maturation in the growth plate drives growth of many bones. One essential event to generate the ordered cell array characterizing growth plate cartilage is the formation of chondrocyte columns in the proliferative zone via 90-degree rotation of daughter cells to align with the long axis of the bone. Previous studies have suggested crucial roles for cadherins and integrin ß1 in column formation. The purpose of this study was to determine the relative contributions of cadherin- and integrin-mediated cell adhesion in column formation. Here we present new mechanistic insights generated by application of live time-lapse confocal microscopy of cranial base explant cultures, robust genetic mouse models, and new quantitative methods to analyze cell behavior. We show that conditional deletion of either the cell-cell adhesion molecule Cdh2 or the cell-matrix adhesion molecule Itgb1 disrupts column formation. Compound mutants were used to determine a potential reciprocal regulatory interaction between the two adhesion surfaces and identified that defective chondrocyte rotation in a N-cadherin mutant was restored by a heterozygous loss of integrin ß1. Our results support a model for which integrin ß1, and not N-cadherin, drives chondrocyte rotation and for which N-cadherin is a potential negative regulator of integrin ß1 function.

Extracellular mechanotransduction.

We highlight the force-sensing function of extracellular matrix and present a complementary mechanotransduction paradigm.

Utilizing the Fourth Dimension for Patient Education in Cardiovascular Surgery.

The complex 3-dimensional (3D) anatomy of the cardiovascular system presents a steep learning obstacle to patients in understanding cardiovascular diseases and surgical procedures. Although 3D printed models have become popular in surgical education, 2D cross-sections remain standard in clinical practice owing to costs and availability. In this report, we demonstrate how the free 3D modeling software Meshmixer can be used to add a fourth dimension to patient education by exploiting interactive 3D modeling. This report serves as proof of concept for the feasibility and potential utility of interactive 3D modeling as an inexpensive tool for cardiovascular surgery patient education.

Steered molecular dynamic simulations reveal Marfan syndrome mutations disrupt fibrillin-1 cbEGF domain mechanosensitive calcium binding.

Marfan syndrome (MFS) is a highly variable genetic connective tissue disorder caused by mutations in the calcium binding extracellular matrix glycoprotein fibrillin-1. Patients with the most severe form of MFS (neonatal MFS; nMFS) tend to have mutations that cluster in an internal region of fibrillin-1 called the neonatal region. This region is predominantly composed of eight calcium-binding epidermal growth factor-like (cbEGF) domains, each of which binds one calcium ion and is stabilized by three highly conserved disulfide bonds. Crucially, calcium plays a fundamental role in stabilizing cbEGF domains. Perturbed calcium binding caused by cbEGF domain mutations is thus thought to be a central driver of MFS pathophysiology. Using steered molecular dynamics (SMD) simulations, we demonstrate that cbEGF domain calcium binding decreases under mechanical stress (i.e. cbEGF domains are mechanosensitive). We further demonstrate the disulfide bonds in cbEGF domains uniquely orchestrate protein unfolding by showing that MFS disulfide bond mutations markedly disrupt normal mechanosensitive calcium binding dynamics. These results point to a potential mechanosensitive mechanism for fibrillin-1 in regulating extracellular transforming growth factor beta (TGFB) bioavailability and microfibril integrity. Such mechanosensitive "smart" features may represent novel mechanisms for mechanical hemostasis regulation in extracellular matrix that are pathologically activated in MFS.

Computational fluid dynamics: a primer for congenital heart disease clinicians.

Computational fluid dynamics has become an important tool for studying blood flow dynamics. As an in-silico collection of methods, computational fluid dynamics is noninvasive and provides numerical values for the most important parameters of blood flow, such as velocity and pressure that are crucial in hemodynamic studies. In this primer, we briefly explain the basic theory and workflow of the two most commonly applied computational fluid dynamics techniques used in the congenital heart disease literature: the finite element method and the finite volume method. We define important terminology and include specific examples of how using these methods can answer important clinical questions in congenital cardiac surgery planning and perioperative patient management.

Predictors of Abdominal Aortic Aneurysm Risks.

Computational biomechanics via finite element analysis (FEA) has long promised a means of assessing patient-specific abdominal aortic aneurysm (AAA) rupture risk with greater efficacy than current clinically used size-based criteria. The pursuit stems from the notion that AAA rupture occurs when wall stress exceeds wall strength. Quantification of peak (maximum) wall stress (PWS) has been at the cornerstone of this research, with numerous studies having demonstrated that PWS better differentiates ruptured AAAs from non-ruptured AAAs. In contrast to wall stress models, which have become progressively more sophisticated, there has been relatively little progress in estimating patient-specific wall strength. This is because wall strength cannot be inferred non-invasively, and measurements from excised patient tissues show a large spectrum of wall strength values. In this review, we highlight studies that investigated the relationship between biomechanics and AAA rupture risk. We conclude that combining wall stress and wall strength approximations should provide better estimations of AAA rupture risk. However, before personalized biomechanical AAA risk assessment can become a reality, better methods for estimating patient-specific wall properties or surrogate markers of aortic wall degradation are needed. Artificial intelligence methods can be key in stratifying patients, leading to personalized AAA risk assessment.

Perioperative risk factors associated with ICU intervention following select neurosurgical procedures.

BACKGROUND/OBJECTIVE: Following cranial neurosurgical procedures, intensive care unit (ICU) admission is routine; however, our institution's growing referral network has led to more frequent bed shortages. Consequently, there are increased requests to transfer our postoperative patients out of the ICU early in the monitoring window. We aimed to find risk factors to prioritize which postoperative neurosurgical patients that should remain in the unit. PATIENTS AND METHODS: An unmatched case-control study was conducted following retrospective chart review of patients who underwent common cranial procedures between August 2015 and June 2016 at our institution. Patients receiving postoperative ICU intervention were defined as cases. Several perioperative events were investigated for association with postoperative ICU level care. Individual risk factors were analyzed using Chi-squared tests for categorical variables (reported as odds ratio) and independent sample two tailed t-tests for continuous variables. Regression models were used for multivariate analysis. RESULTS: We identified 282 patients who met inclusion criteria, with 148 cases and 134 controls and no statistically significant differences between group demographics. Elective cases carried an odds ratio (OR 0.12, 95 % CI 0.05-0.26, p < 0.001), suggesting decreased likelihood of postoperative intensivist intervention. Single variable analysis showed ICU level of care was more more likely with general anesthesia (OR 3.72, 95 % CI 1.90-7.25, p < 0.001) and American Society of Anesthesiologists (ASA) class IV patients (OR 3.28, 95 % CI 1.59-6.78, p < 0.001). Continuous variables (blood loss and operative time) both demonstrated statistically significant differences (p < 0.001) between case and control groups with higher blood loss (100 ± 167 mL) and operative times (245 ± 119 min) seen in the ICU intervention group. Our regression model identified non-elective cases, operative time, and blood loss having associations with postoperative intensivist intervention. CONCLUSION: Growing demand for ICU beds at our institution has us looking for more objective data guiding decisions on lower-risk patients who could transfer early out of the ICU in times of overcapacity. Elective endovascular aneurysm treatment and DBS are cranial procedures least likely to receive postoperative ICU level intervention. Consideration to procedural blood loss of 100 cc or more and operative time greater than 4 h should also be given as these risk factors were associated with more likely needing postoperative ICU intervention. These results should not spur drastic changes in ICU protocols, but continued quality improvement projects should investigate these correlations to add more objective data for ICU utilization.

Intraluminal thrombus is associated with early rupture of abdominal aortic aneurysm.

BACKGROUND: The implications of intraluminal thrombus (ILT) in abdominal aortic aneurysm (AAA) are currently unclear. Previous studies have demonstrated that ILT provides a biomechanical advantage by decreasing wall stress, whereas other studies have associated ILT with aortic wall weakening. It is further unclear why some aneurysms rupture at much smaller diameters than others. In this study, we sought to explore the association between ILT and risk of AAA rupture, particularly in small aneurysms. METHODS: Patients were retrospectively identified and categorized by maximum aneurysm diameter and rupture status: small (<60 mm) or large (≥60 mm) and ruptured (rAAA) or nonruptured (non-rAAA). Three-dimensional AAA anatomy was digitally reconstructed from computed tomography angiograms for each patient. Finite element analysis was then performed to calculate peak wall stress (PWS) and mean wall stress (MWS) using the patient's systolic blood pressure. AAA geometric properties, including normalized ILT thickness (mean ILT thickness/maximum diameter) and % volume (100 × ILT volume/total AAA volume), were also quantified. RESULTS: Patients with small rAAAs had PWS of 123 ± 51 kPa, which was significantly lower than that of patients with large rAAAs (242 ± 130 kPa; P = .04), small non-rAAAs (204 ± 60 kPa; P < .01), and large non-rAAAs (270 ± 106 kPa; P < .01). Patients with small rAAAs also had lower MWS (44 ± 14 kPa vs 82 ± 20 kPa; P < .02) compared with patients with large non-rAAAs. ILT % volume and normalized ILT thickness were greater in small rAAAs (68% ± 11%; 0.16 ± 0.04 mm) compared with small non-rAAAs (53% ± 16% [P = .02]; 0.11 ± 0.04 mm [P < .01]) and large non-rAAAs (57% ± 12% [P = .02]; 0.12 ± 0.03 mm [P < .01]). Increased ILT % volume was associated with both decreased MWS and decreased PWS. CONCLUSIONS: This study found that although increased ILT is associated with lower MWS and PWS, it is also associated with aneurysm rupture at smaller diameters and lower stress. Therefore, the protective biomechanical advantage that ILT provides by lowering wall stress seems to be outweighed by weakening of the AAA wall, particularly in patients with small rAAAs. This study suggests that high ILT burden may be a surrogate marker of decreased aortic wall strength and a characteristic of high-risk small aneurysms.

Mechanical Concepts Applied in Congenital Heart Disease and Cardiac Surgery.

All biological processes are governed by principles of physics that dictate the pathophysiology and even the treatment of congenital heart diseases. In this review, basic concepts such as flow, pressure, resistance, and velocity are introduced, followed by more complex laws that describe the relationship between these variables and the disease processes. Finally, physical phenomena such as turbulence, steal and runoff phenomenon, and energy loss are discussed. By application of these principles, one can accurately quantify modifications undertaken to treat diseases, for example, the size of a patch that augments a vessel and the angle of an anastomosis to allow a certain flow.