The Effect of Inflow Cannula Angle on the Intraventricular Flow Field of the Left Ventricular Assist Device-Assisted Heart: An In Vitro Flow Visualization Study.

Previous studies have identified left ventricular assist device (LVAD) inflow cannula (IC) malposition as a significant risk for pump thrombosis. Thrombus development is a consequence of altered flow dynamics, which can produce areas of flow stasis or high shear that promote coagulation. The goal of this study was to measure the effect of IC orientation on the left ventricle (LV) flow field using a mock circulatory loop, and identify flow-based indices that are sensitive measures of cannula malposition. Experimental studies were performed with a customized silicone model of the dilated LV and the EVAHEART Centrifugal LVAS (Evaheart, Inc.; Houston TX). The velocity field of the LV midplane was measured for a transparent IC oriented parallel to and rotated 15° toward the septum under matched hemodynamic conditions. Vortex structures were analyzed and localized stasis calculated within the IC and combined with a map of normalized pulsatile velocity. The velocity fields revealed increased apical stasis and lower pulsatility with a small angulation of the IC. A significant change in vortex dynamics with the angled IC was observed, doubling the size of the counterclockwise (CCW) vortex while reducing the kinetic energy provided by LVAD support. A significant decrease in average and systolic velocities within the IC was found with cannula angulation, suggesting an increased resistance that affects primarily systolic flow and is worsened with increased LVAD support. These common echocardiographic indices offer the opportunity for immediate clinical application during ramp study assessment. Optimized IC positioning may be determined preoperatively using imaging techniques to develop patient-specific surgical recommendations.

Analysis of the molecular networks in androgen dependent and independent prostate cancer revealed fragile and robust subsystems.

Androgen ablation therapy is currently the primary treatment for metastatic prostate cancer. Unfortunately, in nearly all cases, androgen ablation fails to permanently arrest cancer progression. As androgens like testosterone are withdrawn, prostate cancer cells lose their androgen sensitivity and begin to proliferate without hormone growth factors. In this study, we constructed and analyzed a mathematical model of the integration between hormone growth factor signaling, androgen receptor activation, and the expression of cyclin D and Prostate-Specific Antigen in human LNCaP prostate adenocarcinoma cells. The objective of the study was to investigate which signaling systems were important in the loss of androgen dependence. The model was formulated as a set of ordinary differential equations which described 212 species and 384 interactions, including both the mRNA and protein levels for key species. An ensemble approach was chosen to constrain model parameters and to estimate the impact of parametric uncertainty on model predictions. Model parameters were identified using 14 steady-state and dynamic LNCaP data sets taken from literature sources. Alterations in the rate of Prostatic Acid Phosphatase expression was sufficient to capture varying levels of androgen dependence. Analysis of the model provided insight into the importance of network components as a function of androgen dependence. The importance of androgen receptor availability and the MAPK/Akt signaling axes was independent of androgen status. Interestingly, androgen receptor availability was important even in androgen-independent LNCaP cells. Translation became progressively more important in androgen-independent LNCaP cells. Further analysis suggested a positive synergy between the MAPK and Akt signaling axes and the translation of key proliferative markers like cyclin D in androgen-independent cells. Taken together, the results support the targeting of both the Akt and MAPK pathways. Moreover, the analysis suggested that direct targeting of the translational machinery, specifically eIF4E, could be efficacious in androgen-independent prostate cancers.

A test of highly optimized tolerance reveals fragile cell-cycle mechanisms are molecular targets in clinical cancer trials.

Robustness, a long-recognized property of living systems, allows function in the face of uncertainty while fragility, i.e., extreme sensitivity, can potentially lead to catastrophic failure following seemingly innocuous perturbations. Carlson and Doyle hypothesized that highly-evolved networks, e.g., those involved in cell-cycle regulation, can be resistant to some perturbations while highly sensitive to others. The "robust yet fragile" duality of networks has been termed Highly Optimized Tolerance (HOT) and has been the basis of new lines of inquiry in computational and experimental biology. In this study, we tested the working hypothesis that cell-cycle control architectures obey the HOT paradigm. Three cell-cycle models were analyzed using monte-carlo sensitivity analysis. Overall state sensitivity coefficients, which quantify the robustness or fragility of a given mechanism, were calculated using a monte-carlo strategy with three different numerical techniques along with multiple parameter perturbation strategies to control for possible numerical and sampling artifacts. Approximately 65% of the mechanisms in the G1/S restriction point were responsible for 95% of the sensitivity, conversely, the G2-DNA damage checkpoint showed a much stronger dependence on a few mechanisms; approximately 32% or 13 of 40 mechanisms accounted for 95% of the sensitivity. Our analysis predicted that CDC25 and cyclin E mechanisms were strongly implicated in G1/S malfunctions, while fragility in the G2/M checkpoint was predicted to be associated with the regulation of the cyclin B-CDK1 complex. Analysis of a third model containing both G1/S and G2/M checkpoint logic, predicted in addition to mechanisms already mentioned, that translation and programmed proteolysis were also key fragile subsystems. Comparison of the predicted fragile mechanisms with literature and current preclinical and clinical trials suggested a strong correlation between efficacy and fragility. Thus, when taken together, these results support the working hypothesis that cell-cycle control architectures are HOT networks and establish the mathematical estimation and subsequent therapeutic exploitation of fragile mechanisms as a novel strategy for anti-cancer lead generation.