A hybrid in vitro in silico framework for albuterol delivery through an adult ventilator circuit to a patient-specific lung airway model

2021 ◽  
pp. 105844
Author(s):  
Rahul R. Rajendran ◽  
Sathyanand Kumaran ◽  
Arindam Banerjee ◽  
Ariel Berlinski
2011 ◽  
Vol 133 (4) ◽  
Author(s):  
Ethan O. Kung ◽  
Andrea S. Les ◽  
Francisco Medina ◽  
Ryan B. Wicker ◽  
Michael V. McConnell ◽  
...  

The purpose of this study is to validate numerical simulations of flow and pressure in an abdominal aortic aneurysm (AAA) using phase-contrast magnetic resonance imaging (PCMRI) and an in vitro phantom under physiological flow and pressure conditions. We constructed a two-outlet physical flow phantom based on patient imaging data of an AAA and developed a physical Windkessel model to use as outlet boundary conditions. We then acquired PCMRI data in the phantom while it operated under conditions mimicking a resting and a light exercise physiological state. Next, we performed in silico numerical simulations and compared experimentally measured velocities, flows, and pressures in the in vitro phantom to those computed in the in silico simulations. There was a high degree of agreement in all of the pressure and flow waveform shapes and magnitudes between the experimental measurements and simulated results. The average pressures and flow split difference between experiment and simulation were all within 2%. Velocity patterns showed good agreement between experimental measurements and simulated results, especially in the case of whole-cycle averaged comparisons. We demonstrated methods to perform in vitro phantom experiments with physiological flows and pressures, showing good agreement between numerically simulated and experimentally measured velocity fields and pressure waveforms in a complex patient-specific AAA geometry.


2020 ◽  
Vol 48 (12) ◽  
pp. 2950-2964
Author(s):  
Mirko Bonfanti ◽  
Gaia Franzetti ◽  
Shervanthi Homer-Vanniasinkam ◽  
Vanessa Díaz-Zuccarini ◽  
Stavroula Balabani

AbstractThe optimal treatment of Type-B aortic dissection (AD) is still a subject of debate, with up to 50% of the cases developing late-term complications requiring invasive intervention. A better understanding of the patient-specific haemodynamic features of AD can provide useful insights on disease progression and support clinical management. In this work, a novel in vitro and in silico framework to perform personalised studies of AD, informed by non-invasive clinical data, is presented. A Type-B AD was investigated in silico using computational fluid dynamics (CFD) and in vitro by means of a state-of-the-art mock circulatory loop and particle image velocimetry (PIV). Both models not only reproduced the anatomical features of the patient, but also imposed physiologically-accurate and personalised boundary conditions. Experimental flow rate and pressure waveforms, as well as detailed velocity fields acquired via PIV, are extensively compared against numerical predictions at different locations in the aorta, showing excellent agreement. This work demonstrates how experimental and numerical tools can be developed in synergy to accurately reproduce patient-specific AD blood flow. The combined platform presented herein constitutes a powerful tool for advanced haemodynamic studies for a range of vascular conditions, allowing not only the validation of CFD models, but also clinical decision support, surgical planning as well as medical device innovation.


Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Fanette Chassagne ◽  
Sujatha Buddhe ◽  
Lester C Permut ◽  
David MCMULLAN ◽  
Stephen P Seslar ◽  
...  

Introduction: Coarctation of the aorta is a congenital malformation of the proximal descending aorta that results in severe narrowing of the vessel lumen. It causes significant changes in the aortic hemodynamics, including reduced blood flow and an increased pressure gradient in this area of the vasculature. When this congenital cardiac malformation is associated with aortic arch hypoplasia, a two step-surgery is proposed: first, an end-to-end anastomosis in performed to remove all the ductal tissue surrounding the coarctation, and then the aorta is longitudinally incised and patched to increase its diameter. The design of the patch, based on the surgeon’s experience, is done in the OR. A combined in silico and in vitro approach is proposed to test the possibility of a priori design of the patch. This approach would also open the door to optimization of the patch to restore physiological hemodynamics in the aorta. Methods & Results: CFD simulations of the hemodynamics in the pre-treatment aortic arch were created from the segmentation of patients’ images who received surgical treatment at Seattle Children’s Hospital. In vivo hemodynamics data were used as boundary conditions for the simulation. The design of the patch was created via an in-house code and was based on surgeons’ input: the locations of the start and the end of the lumen enlargement and the length of the aortic segment to be resected. The optimization of the patch design was performed by comparing the simulated hemodynamics (pressure drop, endothelial shear stress, size of the recirculation region, ...) before and after the patch repair. The optimized patch design was then used by the surgeon to perform the in vitro surgical treatment on a physical model of the patient’s anatomy, made in a translucent silicon rubber. The repaired anatomical model was scanned by X-ray microtomography and cast in an optically clear silicone. Time-resolved particle image velocimetry measurements were performed to characterize the post-treatment hemodynamics, and compared to the results of the CFD simulation. Conclusions: This unique in silico and in vitro approach allows surgeons to perform different repairs on patient-specific physical in vitro models and to optimize the design of the patch prior to starting the surgery.


2021 ◽  
Author(s):  
Deeann Wallis ◽  
Andre Leier ◽  
Marc Moore ◽  
Michael Daniel ◽  
Hui Liu ◽  
...  

Abstract We investigated the feasibility of utilizing an exon skipping approach as a genotype-dependent therapeutic for neurofibromatosis type 1 (NF1) by determining which NF1 exons might be skipped while maintaining neurofibromin function. Human neurofibromin is well-known as a GTPase activating protein (GAP), but outside of its GAP-related domain (GRD), it is unclear how critical other regions are for function. Initial in silico analysis predicted exons that can be skipped with minimal loss of neurofibromin function. Utilizing a novel Nf1 cDNA system, we performed a functional screen to determine the effects of exon skipping on in vitro neurofibromin expression and GRD function. Loss of single exons 12, 17, 25, 41, 47, or 52 maintained significant GRD function in at least two Ras activity assays. Exons 18/19, 20 and 28 are critical for GRD function; deletion of exons 20, 41, or 47 led to significantly lower levels of neurofibromin. As suggested by in silico analysis, skipping of exons 17 or 52 resulted in both the highest neurofibromin levels and the greatest suppression of Ras activity. Assessment of NF1 patient databases indicates that pathogenic variants resulting in deletion or skipping of exons 17, 25, and 52 have not been reported; and truncating pathogenic variants in each exon account for ~0.91, 0.94, and 0.25% of unrelated NF1 cases, respectively. Hence, we designed antisense phosphodiamitate morpholino oligos (PMOs) to skip exon 17 and evaluated them in human cell lines that we generated via CRISPR/Cas9 with a patient-specific truncating pathogenic variant, c.1885G>A. We down-selected oligos that efficiently caused skipping of exon 17 and restored NF1 expression and function. Further, homozygous deletion of exon 17 in a novel mouse model is compatible with viable and grossly healthy animals with normal lifespan and no tumor development, providing proof-of-concept that exon 17 is not essential for murine neurofibromin function. Mild phenotypes observed include abnormal nesting behavior and lymphoid hyperplasia with increased numbers of both B- and T-cells. Hence, exon skipping should be further investigated as a therapeutic approach for NF1 patients with treatment of individuals with pathogenic variants in exon 17.


2019 ◽  
pp. 1-11 ◽  
Author(s):  
Sara Hamis ◽  
Gibin G. Powathil ◽  
Mark A.J. Chaplain

Cancers present with high variability across patients and tumors; thus, cancer care, in terms of disease prevention, detection, and control, can highly benefit from a personalized approach. For a comprehensive personalized oncology practice, this personalization should ideally consider data gathered from various information levels, which range from the macroscale population level down to the microscale tumor level, without omission of the central patient level. Appropriate data mined from each of these levels can significantly contribute in devising personalized treatment plans tailored to the individual patient and tumor. Mathematical models of solid tumors, combined with patient-specific tumor profiles, present a unique opportunity to personalize cancer treatments after detection using a bottom-up approach. Here, we discuss how information harvested from mathematical models and from corresponding in silico experiments can be implemented in preclinical and clinical applications. To conceptually illustrate the power of these models, one such model is presented, and various pertinent tumor and treatment scenarios are demonstrated in silico. The presented model, specifically a multiscale, hybrid cellular automaton, has been fully validated in vitro using multiple cell-line–specific data. We discuss various insights provided by this model and other models like it and their role in designing predictive tools that are both patient, and tumor specific. After refinement and parametrization with appropriate data, such in silico tools have the potential to be used in a clinical setting to aid in treatment protocols and decision making.


2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
M.-E. Oraiopoulou ◽  
E. Tzamali ◽  
G. Tzedakis ◽  
A. Vakis ◽  
J. Papamatheakis ◽  
...  

The application of accurate cancer predictive algorithms validated with experimental data is a field concerning both basic researchers and clinicians, especially regarding a highly aggressive form of cancer, such as Glioblastoma. In an aim to enhance prediction accuracy in realistic patient-specific environments, accounting for both inter- and intratumoral heterogeneity, we use patient-derived Glioblastoma cells from different patients. We focus on cell proliferation using in vitro experiments to estimate cell doubling times and sizes for established primary Glioblastoma cell lines. A preclinically driven mathematical model parametrization is accomplished by taking into account the experimental measurements. As a control cell line we use the well-studied U87MG cells. Both in vitro and in silico results presented support that the variance between tumor staging can be attributed to the differential proliferative capacity of the different Glioblastoma cells. More specifically, the intratumoral heterogeneity together with the overall proliferation reflected in both the proliferation rate and the mechanical cell contact inhibition can predict the in vitro evolution of different Glioblastoma cell lines growing under the same conditions. Undoubtedly, additional imaging techniques capable of providing spatial information of tumor cell physiology and microenvironment will enhance our understanding regarding Glioblastoma nature and verify and further improve our predictability.


Author(s):  
Markus Boel ◽  
Oscar J. Abilez ◽  
Ahmed N Assar ◽  
Christopher K. Zarins ◽  
Ellen Kuhl

Author(s):  
Jaynthy C. ◽  
N. Premjanu ◽  
Abhinav Srivastava

Cancer is a major disease with millions of patients diagnosed each year with high mortality around the world. Various studies are still going on to study the further mechanisms and pathways of the cancer cell proliferation. Fucosylation is one of the most important oligosaccharide modifications involved in cancer and inflammation. In cancer development increased core fucosylation by FUT8 play an important role in cell proliferation. Down regulation of FUT8 expression may help cure lung cancer. Therefore the computational study based on the down regulation mechanism of FUT8 was mechanised. Sapota fruit extract, containing 4-Ogalloylchlorogenic acid was used as the inhibitor against FUT-8 as target and docking was performed using in-silico tool, Accelrys Discovery Studio. There were several conformations of the docked result, and conformation 1 showed 80% dock score between the ligand and the target. Further the amino acids of the inhibitor involved in docking were studied using another tool, Ligplot. Thus, in-silico analysis based on drug designing parameters shows that the fruit extract can be studied further using in-vitro techniques to know its pharmacokinetics.


2019 ◽  
Author(s):  
Filip Fratev ◽  
Denisse A. Gutierrez ◽  
Renato J. Aguilera ◽  
suman sirimulla

AKT1 is emerging as a useful target for treating cancer. Herein, we discovered a new set of ligands that inhibit the AKT1, as shown by in vitro binding and cell line studies, using a newly designed virtual screening protocol that combines structure-based pharmacophore and docking screens. Taking together with the biological data, the combination of structure based pharamcophore and docking methods demonstrated reasonable success rate in identifying new inhibitors (60-70%) proving the success of aforementioned approach. A detail analysis of the ligand-protein interactions was performed explaining observed activities.<br>


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