A Predictive Analysis of Wall Stress in Abdominal Aortic Aneurysms Using a Neural Network Model.

Rupture risk assessment of abdominal aortic aneurysms (AAAs) by means of quantifying wall stress is a common biomechanical strategy. However, the clinical translation of this approach has been greatly limited due to the complexity associated with the computational tools required for its implementation. Thus, being able to estimate wall stress using nonbiomechanical markers that can be quantified as a direct outcome of clinical image segmentation would be advantageous in improving the potential implementation of said strategy. In the present work, we investigated the use of geometric indices to predict patient-specific AAA wall stress by means of a novel neural network (NN) modeling approach. We conducted a retrospective review of existing clinical images of two patient groups: 98 asymptomatic and 50 symptomatic AAAs. The images were subject to a protocol consisting of image segmentation, processing, volume meshing, finite element modeling, and geometry quantification, from which 53 geometric indices and the spatially averaged wall stress (SAWS) were calculated. SAWS estimated from finite element analysis was considered the gold standard for the predictions. We developed feed-forward NN models composed of an input layer, two dense layers, and an output layer using Keras, a deep learning library in python. The NN models were trained, tested, and validated independently for both AAA groups using all geometric indices, as well as a reduced set of indices resulting from a variable reduction procedure. We compared the performance of the NN models with two standard machine learning algorithms (MARS: multivariate adaptive regression splines and GAM: generalized additive model) and a linear regression model (GLM: generalized linear model). With the reduced sets of indices, the NN-based approach exhibited the highest mean goodness-of-fit (for the symptomatic group 0.71 and for the asymptomatic group 0.79) and lowest mean relative error (17% for both groups). In contrast, MARS yielded a mean goodness-of-fit of 0.59 for the symptomatic group and 0.77 for the asymptomatic group, with relative errors of 17% for the symptomatic group and 22% for the asymptomatic group. GAM had a mean goodness-of-fit of 0.70 for the symptomatic group and 0.80 for the asymptomatic group, with relative errors of 16% for the symptomatic group and 20% for the asymptomatic group. GLM did not perform as well as the other algorithms, with a mean goodness-of-fit of 0.53 for the symptomatic group and 0.70 for the asymptomatic group, with relative errors of 19% for the symptomatic group and 23% for the asymptomatic group. Nevertheless, the NN models required a reduced set of 15 and 13 geometric indices to predict SAWS for the symptomatic and asymptomatic AAA groups, respectively. This was in contrast to the reduced set of nine and eight geometric indices required to predict SAWS with the MARS and GAM algorithms for each AAA group, respectively. The use of NN modeling represents a promising alternative methodology for the estimation of AAA wall stress using geometric indices as surrogates, in lieu of finite element modeling. The performance metrics of NN models are expected to improve with significantly larger group sizes, given the suitability of NN modeling for "big data" applications.

Morphological Analysis of the Right Ventricular Endocardial Wall in Pulmonary Hypertension.

Pulmonary hypertension (PH) is a chronic progressive disease diagnosed when the pressure in the main pulmonary artery, assessed by right heart catheterization (RHC), is greater than 25 mmHg. Changes in the pulmonary vasculature due to the high pressure yield an increase in the right ventricle (RV) afterload. This starts a remodeling process during which the ventricle exhibits changes in shape and eventually fails. RV models were obtained from the segmentation of cardiac magnetic resonance images at baseline and 1-year follow-up for a pilot study that involved 12 PH and 7 control subjects. The models were used to create surface meshes of the geometry and to compute the principal, mean, and Gaussian curvatures. Ten global curvature indices were calculated for each of the RV endocardial wall reconstructions at the end-diastolic volume (EDV) and end-systolic volume (ESV) phases of the cardiac cycle. Statistical analysis of the data was performed to discern if there are significant differences in the curvature indices between controls and the PH group, as well as between the baseline and follow-up phases for the PH subjects. Six curvature indices, namely, the Gaussian curvature at ESV, the mean curvature at EDV and ESV, the L2-norm of the mean curvature at ESV, and the L2-norm of the major principal curvature at EDV and ESV, were found to be significantly different between controls and PH subjects (p < 0.05). We infer that these geometry measures could be used as indicators of RV endocardial wall morphology changes. Two global parameters, the Gaussian and mean curvatures at ESV, showed significant changes at the one-year follow-up for the PH subjects (p < 0.05). The aforementioned geometry measures to assess changes in RV shape could be used as part of a noninvasive computational tool to aid clinicians in PH diagnostic and progression assessment, and to evaluate the effectiveness of treatment.

A Comparative Study of Biomechanical and Geometrical Attributes of Abdominal Aortic Aneurysms in the Asian and Caucasian Populations.

In this work, we provide a quantitative assessment of the biomechanical and geometric features that characterize abdominal aortic aneurysm (AAA) models generated from 19 Asian and 19 Caucasian diameter-matched AAA patients. 3D patient-specific finite element models were generated and used to compute peak wall stress (PWS), 99th percentile wall stress (99th WS), and spatially averaged wall stress (AWS) for each AAA. In addition, 51 global geometric indices were calculated, which quantify the wall thickness, shape, and curvature of each AAA. The indices were correlated with 99th WS (the only biomechanical metric that exhibited significant association with geometric indices) using Spearman's correlation and subsequently with multivariate linear regression using backward elimination. For the Asian AAA group, 99th WS was highly correlated (R2 = 0.77) with three geometric indices, namely tortuosity, intraluminal thrombus volume, and area-averaged Gaussian curvature. Similarly, 99th WS in the Caucasian AAA group was highly correlated (R2 = 0.87) with six geometric indices, namely maximum AAA diameter, distal neck diameter, diameter-height ratio, minimum wall thickness variance, mode of the wall thickness variance, and area-averaged Gaussian curvature. Significant differences were found between the two groups for ten geometric indices; however, no differences were found for any of their respective biomechanical attributes. Assuming maximum AAA diameter as the most predictive metric for wall stress was found to be imprecise: 24% and 28% accuracy for the Asian and Caucasian groups, respectively. This investigation reveals that geometric indices other than maximum AAA diameter can serve as predictors of wall stress, and potentially for assessment of aneurysm rupture risk, in the Asian and Caucasian AAA populations.

Quantitative Analysis of Tissue Damage Evolution in Porcine Liver With Interrupted Mechanical Testing Under Tension, Compression, and Shear.

In this study, the damage evolution of liver tissue was quantified at the microstructural level under tensile, compression, and shear loading conditions using an interrupted mechanical testing method. To capture the internal microstructural changes in response to global deformation, the tissue samples were loaded to different strain levels and chemically fixed to permanently preserve the deformed tissue geometry. Tissue microstructural alterations were analyzed to quantify the accumulated damages, with damage-related parameters such as number density, area fraction, mean area, and mean nearest neighbor distance (NND). All three loading states showed a unique pattern of damage evolution, in which the damages were found to increase in number and size, but decrease in NND as strain level increased. To validate the observed damage features as true tissue microstructural damages, more samples were loaded to the above-mentioned strain levels and then unloaded back to their reference state, followed by fixation. The most major damage-relevant features at higher strain levels remained after the release of the external loading, indicating the occurrence of permanent inelastic deformation. This study provides a foundation for future structure-based constitutive material modeling that can capture and predict the stress-state dependent damage evolution in liver tissue.

Etiology, pathophysiology and biomarkers of interstitial cystitis/painful bladder syndrome.

PURPOSE: Interstitial cystitis/painful bladder syndrome (IC/PBS) is a chronic pain syndrome and a chronic inflammatory condition prevalent in women that leads to urgency, sleep disruption, nocturia and pain in the pelvic area, to the detriment of the sufferer's quality of life. The aim of this review is to highlight the newest diagnostic strategies and potential therapeutic techniques. METHODS: A comprehensive literature review was performed on MEDLINE, PubMed, and Cochrane databases gathering all literature about "Interstitial cystitis" and "Painful Bladder Syndrome". Visual analogue scales, epidemiological strategies, pain questionnaires and similar techniques were not included in this literature survey. RESULTS: The etiology, exact diagnosis and epidemiology of IC/PBS are still not clearly understood. To date, its prevalence is estimated to be in the range of 45 per 100,000 women and 8 per 100,000 men, whereas joint prevalence in both sexes is 10.6 cases per 100,000. There are no "gold standards" in the diagnosis or detection of IC/PBS, therefore, several etiological theories were investigated, such as permeability, glycosaminoglycans, mast cell, infection and neuroendocrine theory to find new diagnostic strategies and potential biomarkers. CONCLUSION: Due to the fact that this disease is of an intricate nature, and that many of its symptoms overlap with other concomitant diseases, it could be suggested to classify the patients with emphasis on the phenotype, as well as their symptom clusters, to tailor the diagnostic and management choices according to the observed biomarkers.

Biomechanical Testing and Histologic Examination of Intradermal Skin Closure in Dogs Using Barbed Suture Device and Non-Barbed Monofilament Suture.

OBJECTIVE: To compare the biomechanical strength and histologic features of 3-0 Glycomer™ 631 barbed suture (V-LOC™ 90 Absorbable Wound Closure Device, Covidien, Mansfield, MA) to non-barbed 3-0 Glycomer™ 631 suture (Biosyn™, Covidien) for intradermal skin wound closure in the dog. STUDY DESIGN: Randomized, factorial, in vivo. ANIMALS: Eighteen purpose-bred, mature male, and female hound dogs. METHODS: Eighteen adult hound dogs were randomly assigned to 1 of 3 groups designated by postoperative day of assessment. Six skin incisions were made along the dorsum in the thoracolumbar region of each dog with an equal number (n=3) randomly assigned to closure with barbed or non-barbed suture. Six dogs were euthanatized on postoperative days 3, 10, and 14, respectively. Two additional incisions were made on each dog after euthanasia for baseline data (Day 0). The skin incision specimens were harvested for biomechanical testing and histologic evaluation. RESULTS: Non-barbed closure had significantly higher maximum load at failure (P<.001) and stiffness (P<.001) than barbed closure regardless of day. The average tissue reaction score was significantly higher for barbed closure (P=.008), regardless of day. Suturing time for barbed closures was significantly shorter. There was no significant difference in frequency of complications between closures. CONCLUSION: Barbed Glycomer™ 631 closures had a significantly lower maximum load at failure and stiffness, and higher average tissue reaction scores, but showed no difference in short term outcome for intradermal closure of dorsally located skin incisions in dogs.

Morphologic Evaluation of Post-implanted Monofilament Polypropylene Mesh Utilizing a Novel Technique with Scanning Electron Microscopy Quantification.

Polypropylene mesh has been shown to shrink up to 50%; however, little is known about other changes that may occur while it is implanted. It is unclear whether such changes have clinical impact; nonetheless, knowledge of such can ultimately affect the technique of implantation and may affect outcomes. The objective of this study was to evaluate surgically explanted mesh after two years implantation for evidence of change in morphology using scanning electron microscopy (SEM). Secondly, we describe a novel technique for quantifying such changes with intentions for future validation. SEM imaging was conducted and mesh changes were visualized. SEM images revealed deep surface cracks both transverse and longitudinal, flaking and peeling of fibers, as well as fibrosis. Microstructural quantification of cracks was also completed. The fraction of transverse cracked area to whole surface area was 24.2%. Average crack length range was 0.58 to 71.46 µm and average crack thickness range was 0.99 to 25.46 µm. Polypropylene mesh is subject to structural changes after surgical implantation. It is important to investigate how these processes impact clinical outcomes. Validated techniques of quantifying such changes can prove useful in future research and aid in development of the ideal graft.

In Vitro Pharmacological Modulation of PIEZO1 Channels in Frontal Cortex Neuronal Networks.

PIEZO1 is a mechanosensitive ion channel expressed in various organs, including but not limited to the brain, heart, lungs, kidneys, bone, and skin. PIEZO1 has been implicated in astrocyte, microglia, capillary, and oligodendrocyte signaling in the mammalian cortex. Using murine embryonic frontal cortex tissue, we examined the protein expression and functionality of PIEZO1 channels in cultured networks leveraging substrate-integrated microelectrode arrays (MEAs) with additional quantitative results from calcium imaging and whole-cell patch-clamp electrophysiology. MEA data show that the PIEZO1 agonist Yoda1 transiently enhances the mean firing rate (MFR) of single units, while the PIEZO1 antagonist GsMTx4 inhibits both spontaneous activity and Yoda1-induced increase in MFR in cortical networks. Furthermore, calcium imaging experiments revealed that Yoda1 significantly increased the frequency of calcium transients in cortical cells. Additionally, in voltage clamp experiments, Yoda1 exposure shifted the cellular reversal potential towards depolarized potentials consistent with the behavior of PIEZO1 as a non-specific cation-permeable channel. Our work demonstrates that murine frontal cortical neurons express functional PIEZO1 channels and quantifies the electrophysiological effects of channel activation in vitro. By quantifying the electrophysiological effects of PIEZO1 activation in vitro, our study establishes a foundation for future investigations into the role of PIEZO1 in neurological processes and potential therapeutic applications targeting mechanosensitive channels in various physiological contexts.

Planar amorphous silicon carbide microelectrode arrays for chronic recording in rat motor cortex.

Chronic implantation of intracortical microelectrode arrays (MEAs) capable of recording from individual neurons can be used for the development of brain-machine interfaces. However, these devices show reduced recording capabilities under chronic conditions due, at least in part, to the brain's foreign body response (FBR). This creates a need for MEAs that can minimize the FBR to possibly enable long-term recording. A potential approach to reduce the FBR is the use of MEAs with reduced cross-sectional geometries. Here, we fabricated 4-shank amorphous silicon carbide (a-SiC) MEAs and implanted them into the motor cortex of seven female Sprague-Dawley rats. Each a-SiC MEA shank was 8 µm thick by 20 µm wide and had sixteen sputtered iridium oxide film (SIROF) electrodes (4 per shank). A-SiC was chosen as the fabrication base for its high chemical stability, good electrical insulation properties, and amenability to thin film fabrication. Electrochemical analysis and neural recordings were performed weekly for 4 months. MEAs were characterized pre-implantation in buffered saline and in vivo using electrochemical impedance spectroscopy and cyclic voltammetry at 50 mV/s and 50,000 mV/s. Neural recordings were analyzed for single unit activity. At the end of the study, animals were sacrificed for immunohistochemical analysis. We observed statistically significant, but small, increases in 1 and 30 kHz impedance values and 50,000 mV/s charge storage capacity over the 16-week implantation period. Slow sweep 50 mV/s CV and 1 Hz impedance did not significantly change over time. Impedance values increased from 11.6 MΩ to 13.5 MΩ at 1 Hz, 1.2 MΩ-2.9 MΩ at 1 kHz, and 0.11 MΩ-0.13 MΩ at 30 kHz over 16 weeks. The median charge storage capacity of the implanted electrodes at 50 mV/s was 58.1 mC/cm2 on week 1 and 55.9 mC/cm2 on week 16, and at 50,000 mV/s, 4.27 mC/cm2 on week 1 and 5.93 mC/cm2 on week 16. Devices were able to record neural activity from 92% of all active channels at the beginning of the study, At the study endpoint, a-SiC devices were still recording single-unit activity on 51% of electrochemically active electrode channels. In addition, we observed that the signal-to-noise ratio experienced a small decline of -0.19 per week. We also classified observed units as fast and slow repolarizing based on the trough-to-peak time. Although the overall presence of single units declined, fast and slow repolarizing units declined at a similar rate. At recording electrode depth, immunohistochemistry showed minimal tissue response to the a-SiC devices, as indicated by statistically insignificant differences in activated glial cell response between implanted brains slices and contralateral sham slices at 150 µm away from the implant location, as evidenced by GFAP staining. NeuN staining revealed the presence of neuronal cell bodies close to the implantation site, again statistically not different from a contralateral sham slice. These results warrant further investigation of a-SiC MEAs for future long-term implantation neural recording studies.

Isolation of the murine Glut1 deficient thalamocortical circuit: wavelet characterization and reverse glucose dependence of low and gamma frequency oscillations.

Glucose represents the principal brain energy source. Thus, not unexpectedly, genetic glucose transporter 1 (Glut1) deficiency (G1D) manifests with encephalopathy. G1D seizures, which constitute a prominent disease manifestation, often prove refractory to medications but may respond to therapeutic diets. These seizures are associated with aberrant thalamocortical oscillations as inferred from human electroencephalography and functional imaging. Mouse electrophysiological recordings indicate that inhibitory neuron failure in thalamus and cortex underlies these abnormalities. This provides the motivation to develop a neural circuit testbed to characterize the mechanisms of thalamocortical synchronization and the effects of known or novel interventions. To this end, we used mouse thalamocortical slices on multielectrode arrays and characterized spontaneous low frequency oscillations and less frequent 30-50 Hz or gamma oscillations under near-physiological bath glucose concentration. Using the cortical recordings from layer IV among other regions recorded, we quantified oscillation epochs via an automated wavelet-based algorithm. This method proved analytically superior to power spectral density, short-time Fourier transform or amplitude-threshold detection. As expected from human observations, increased bath glucose reduced the lower frequency oscillations while augmenting the gamma oscillations, likely reflecting strengthened inhibitory neuron activity, and thus decreasing the low:high frequency ratio (LHR). This approach provides an ex vivo method for the evaluation of mechanisms, fuels, and pharmacological agents in a crucial G1D epileptogenic circuit.

Isolation of the murine Glut1 deficient thalamocortical circuit: wavelet characterization and reverse glucose dependence of low and gamma frequency oscillations.

Glucose represents the principal brain energy source. Thus, not unexpectedly, genetic glucose transporter 1 (Glut1) deficiency (G1D) manifests with encephalopathy. G1D seizures, which constitute a prominent disease manifestation, often prove refractory to medications but may respond to therapeutic diets. These seizures are associated with aberrant thalamocortical oscillations as inferred from human electroencephalography and functional imaging. Mouse electrophysiological recordings indicate that inhibitory neuron failure in thalamus and cortex underlies these abnormalities. This provides the motivation to develop a neural circuit testbed to characterize the mechanisms of thalamocortical synchronization and the effects of known or novel interventions. To this end, we used mouse thalamocortical slices on multielectrode arrays and characterized spontaneous low frequency oscillations and less frequent 30-50 Hz or gamma oscillations under near-physiological bath glucose concentration. Using the cortical recordings from layer IV, we quantified oscillation epochs via an automated wavelet-based algorithm. This method proved analytically superior to power spectral density, short-time Fourier transform or amplitude-threshold detection. As expected from human observations, increased bath glucose reduced the lower frequency oscillations while augmenting the gamma oscillations, likely reflecting strengthened inhibitory neuron activity. This approach provides an ex vivo method for the evaluation of mechanisms, fuels, and pharmacological agents in a crucial G1D epileptogenic circuit.

Maintenance of pig brain function under extracorporeal pulsatile circulatory control (EPCC).

Selective vascular access to the brain is desirable in metabolic tracer, pharmacological and other studies aimed to characterize neural properties in isolation from somatic influences from chest, abdomen or limbs. However, current methods for artificial control of cerebral circulation can abolish pulsatility-dependent vascular signaling or neural network phenomena such as the electrocorticogram even while preserving individual neuronal activity. Thus, we set out to mechanically render cerebral hemodynamics fully regulable to replicate or modify native pig brain perfusion. To this end, blood flow to the head was surgically separated from the systemic circulation and full extracorporeal pulsatile circulatory control (EPCC) was delivered via a modified aorta or brachiocephalic artery. This control relied on a computerized algorithm that maintained, for several hours, blood pressure, flow and pulsatility at near-native values individually measured before EPCC. Continuous electrocorticography and brain depth electrode recordings were used to evaluate brain activity relative to the standard offered by awake human electrocorticography. Under EPCC, this activity remained unaltered or minimally perturbed compared to the native circulation state, as did cerebral oxygenation, pressure, temperature and microscopic structure. Thus, our approach enables the study of neural activity and its circulatory manipulation in independence of most of the rest of the organism.

The International Natural Product Sciences Taskforce (INPST) and the power of Twitter networking exemplified through #INPST hashtag analysis.

BACKGROUND: The development of digital technologies and the evolution of open innovation approaches have enabled the creation of diverse virtual organizations and enterprises coordinating their activities primarily online. The open innovation platform titled "International Natural Product Sciences Taskforce" (INPST) was established in 2018, to bring together in collaborative environment individuals and organizations interested in natural product scientific research, and to empower their interactions by using digital communication tools. METHODS: In this work, we present a general overview of INPST activities and showcase the specific use of Twitter as a powerful networking tool that was used to host a one-week "2021 INPST Twitter Networking Event" (spanning from 31st May 2021 to 6th June 2021) based on the application of the Twitter hashtag #INPST. RESULTS AND CONCLUSION: The use of this hashtag during the networking event period was analyzed with Symplur Signals (https://www.symplur.com/), revealing a total of 6,036 tweets, shared by 686 users, which generated a total of 65,004,773 impressions (views of the respective tweets). This networking event's achieved high visibility and participation rate showcases a convincing example of how this social media platform can be used as a highly effective tool to host virtual Twitter-based international biomedical research events.

Characterization of Active Electrode Yield for Intracortical Arrays: Awake versus Anesthesia.

Intracortical microelectrode arrays are used for recording neural signals at single-unit resolution and are promising tools for studying brain function and developing neuroprosthetics. Research is being done to increase the chronic performance and reliability of these probes, which tend to decrease or fail within several months of implantation. Although recording paradigms vary, studies focused on assessing the reliability and performance of these devices often perform recordings under anesthesia. However, anesthetics-such as isoflurane-are known to alter neural activity and electrophysiologic function. Therefore, we compared the neural recording performance under anesthesia (2% isoflurane) followed by awake conditions for probes implanted in the motor cortex of both male and female Sprague-Dawley rats. While the single-unit spike rate was significantly higher by almost 600% under awake compared to anesthetized conditions, we found no difference in the active electrode yield between the two conditions two weeks after surgery. Additionally, the signal-to-noise ratio was greater under anesthesia due to the noise levels being nearly 50% greater in awake recordings, even though there was a 14% increase in the peak-to-peak voltage of distinguished single units when awake. We observe that these findings are similar for chronic time points as well. Our observations indicate that either anesthetized or awake recordings are acceptable for studies assessing the chronic reliability and performance of intracortical microelectrode arrays.

Experimental aortic aneurysm severity and growth depend on topical elastase concentration and lysyl oxidase inhibition.

Abdominal aortic aneurysm (AAA) formation and expansion is highly complex and multifactorial, and the improvement of animal models is an important step to enhance our understanding of AAA pathophysiology. In this study, we explore our ability to influence aneurysm growth in a topical elastase plus ß-Aminopropionitrile (BAPN) mouse model by varying elastase concentration and by altering the cross-linking capability of the tissue. To do so, we assess both chronic and acute effects of elastase concentration using volumetric ultrasound. Our results suggest that the applied elastase concentration affects initial elastin degradation, as well as long-term vessel expansion. Additionally, we assessed the effects of BAPN by (1) removing it to restore the cross-linking capability of tissue after aneurysm formation and (2) adding it to animals with stable aneurysms to interrupt cross-linking. These results demonstrate that, even after aneurysm formation, lysyl oxidase inhibition remains necessary for continued expansion. Removing BAPN reduces the aneurysm growth rate to near zero, resulting in a stable aneurysm. In contrast, adding BAPN causes a stable aneurysm to expand. Altogether, these results demonstrate the ability of elastase concentration and BAPN to modulate aneurysm growth rate and severity. The findings open several new areas of investigation in a murine model that mimics many aspects of human AAA.

A comparative biomechanical analysis of term fetal membranes in human and domestic species.

OBJECTIVE: The purpose of this study was to biomechanically characterize and compare human, porcine, equine, and ovine fetal membranes. STUDY DESIGN: Noncontact metrology was used for topographic analyses. Uniaxial tensile testing was performed to resolve specific biomechanical values. Puncture force and radial stresses were determined with biaxial puncture testing. Microstructure and surface tortuosity were analyzed histologically. RESULTS: Equine and human membranes sustained larger magnitude loading, but ovine and porcine membranes exhibited stronger material properties. Biaxial puncture validated uniaxial results; human and equine groups accommodated the largest loads but lowest stresses. Equine membranes were mostly vascularized; tortuosity was highest in porcine membranes. Species' gestation length was correlated positively with membrane thickness. CONCLUSION: The anatomy of placentation and length of species gestation show distinct relationships to membrane biomechanics. Unlike other species, human fetal membranes do not compensate for structural weakness with a thicker membrane. This finding may explain the high incidence of preterm premature rupture of membranes in humans.

Cerebral aneurysm rupture status classification using statistical and machine learning methods.

Morphological characterization and fluid dynamics simulations were carried out to classify the rupture status of 71 (36 unruptured, 35 ruptured) patient specific cerebral aneurysms using a machine learning approach together with statistical techniques. Eleven morphological and six hemodynamic parameters were evaluated individually and collectively for significance as rupture status predictors. The performance of each parameter was inspected using hypothesis testing, accuracy, confusion matrix, and the area under the receiver operating characteristic curve. Overall, the size ratio exhibited the best performance, followed by the diastolic wall shear stress, and systolic wall shear stress. The prediction capability of all 17 parameters together was evaluated using eight different machine learning algorithms. The logistic regression achieved the highest accuracy (0.75), whereas the random forest had the highest area under curve value among all the classifiers (0.82), surpassing the performance exhibited by the size ratio. Hence, we propose the random forest model as a tool that can help improve the rupture status prediction of cerebral aneurysms.

Patient-Specific Computational Analysis of Hemodynamics in Adult Pulmonary Hypertension.

Pulmonary hypertension (PH) is a progressive disease characterized by elevated pressure and vascular resistance in the pulmonary arteries. Nearly 250,000 hospitalizations occur annually in the US with PH as the primary or secondary condition. A definitive diagnosis of PH requires right heart catheterization (RHC) in addition to a chest computed tomography, a walking test, and others. While RHC is the gold standard for diagnosing PH, it is invasive and posseses inherent risks and contraindications. In this work, we characterized the patient-specific pulmonary hemodynamics in silico for diverse PH WHO groups. We grouped patients on the basis of mean pulmonary arterial pressure (mPAP) into three disease severity groups: at-risk ([Formula: see text], denoted with A), mild ([Formula: see text], denoted with M), and severe ([Formula: see text], denoted with S). The pulsatile flow hemodynamics was simulated by evaluating the three-dimensional Navier-Stokes system of equations using a flow solver developed by customizing OpenFOAM libraries (v5.0, The OpenFOAM Foundation). Quasi patient-specific boundary conditions were implemented using a Womersley inlet velocity profile and transient resistance outflow conditions. Hemodynamic indices such as spatially averaged wall shear stress ([Formula: see text]), wall shear stress gradient ([Formula: see text]), time-averaged wall shear stress ([Formula: see text]), oscillatory shear index ([Formula: see text]), and relative residence time ([Formula: see text]), were evaluated along with the clinical metrics pulmonary vascular resistance ([Formula: see text]), stroke volume ([Formula: see text]) and compliance ([Formula: see text]), to assess possible spatiotemporal correlations. We observed statistically significant decreases in [Formula: see text], [Formula: see text], and [Formula: see text], and increases in [Formula: see text] and [Formula: see text] with disease severity. [Formula: see text] was moderately correlated with [Formula: see text] and [Formula: see text] at the mid-notch stage of the cardiac cycle when these indices were computed using the global pulmonary arterial geometry. These results are promising in the context of a long-term goal of identifying computational biomarkers that can serve as surrogates for invasive diagnostic protocols of PH.

Pentagalloyl Glucose-Laden Poly(lactide-co-glycolide) Nanoparticles for the Biomechanical Extracellular Matrix Stabilization of an In Vitro Abdominal Aortic Aneurysm Model.

The suppression of abdominal aortic aneurysm (AAA) growth by nonsurgical therapy is currently not an option, and AAA is considered an irreversible destructive disease. The formation and development of AAA is associated with the progressive deterioration of the aortic wall. Infiltrated macrophages and resident vascular smooth muscle cells oversecrete matrix metalloproteinases (MMPs), which cause the loss of crucial aortic extracellular matrix (ECM) components, thus weakening the aortic wall. Stabilization of the aortic ECM could enable the development of novel therapeutic options for preventing and reducing AAA progression. In the present work, we studied the biochemical and biomechanical interactions of pentagalloyl glucose (PGG) on mouse C2C12 myoblast cells. PGG is a naturally occurring ECM-stabilizing polyphenolic compound that has been studied in various applications, including vascular health, with promising results. With its known limitations of systemic administration, we also studied the administration of PGG when encapsulated within poly(lactide-co-glycolide) (PLGA) nanoparticles (NPs). Treatment with collagenase and elastase enzymes was used to mimic a pathway of degenerative effects seen in the pathogenesis of human AAA. PGG and PLGA(PGG) NPs were added to enzyme-treated cells in either a suppressive or preventative scenario. Biomolecular interactions were analyzed through cell viability, cell adhesion, reactive oxygen species (ROS) production, and MMP-2 and MMP-9 secretion. Biomechanical properties were studied through atomic force microscopy and quartz crystal microbalance with dissipation. Our results suggest that PGG or PLGA(PGG) NPs caused minor to no cytotoxic effects on the C2C12 cells. Both PGG and PLGA(PGG) NPs showed reduction in ROS and MMP-2 secretion if administered after enzymatic ECM degradation. A quantitative comparison of Young's moduli showed a significant recovery in the elastic properties of the cells treated with PGG or PLGA(PGG) NPs after enzymatic ECM degradation. This work provides preliminary support for the use of a pharmacological therapy for AAA treatment.