Publications

Drug-coated balloon (DCB) percutaneous interventional therapy allows for durable reopening of the narrowed lumen via physical tissue expansion and local anti-restenosis drug delivery, providing an alternative to traditional uncoated balloons or a permanent indwelling implant such as a conventional metallic drug-eluting stent. While DCB-based treatment of peripheral arterial disease (PAD) has been incorporated into clinical guidelines, DCB use has been recently curtailed due to reports that showed evidence of increased mortality risk in patients treated with paclitaxel (PTX)-coated balloons. Given the United States Food and Drug Administration's 2019 consequent warning regarding PTX-eluting DCBs and the subsequent marked reduction in clinical DCB use, there is now a critical need to better understand the compositional and mechanical factors underlying DCB efficacy and safety. Most work to date on DCB refinement has focused on designing both the enabling balloon catheter and alternate coatings composed of various drugs and excipients, followed by device evaluation in preclinical and clinical studies. We contend that improvement in DCB performance will require a better understanding of the biophysical factors operative during and following balloon deployment, and moreover that the elaboration and demonstrated control of these factors are needed to address current concerns with DCB use. This article provides a perspective on the biophysical interactions that govern DCB performance and offers new design strategies for the development of next-generation DCB devices.

Purpose

Premature coronary artery bypass graft (CABG) failure has been linked to geometric, mechanical, and compositional discrepancies between host and graft tissues. Acute hemodynamic disturbances and the introduction of wall stress gradients trigger a myriad of mechanobiological processes at the anastomosis that can be associated with restenosis and graft failure. Although the origins of coronary artery disease dictate the anastomotic target, an opportunity exists for graft-vessel optimization through rationale graft selection.

Methods

Here we explored the four distinct regions of the left (L) and right (R) ITA (1 = proximal, 2 = submuscular, 3 = middle, 4 = distal), and four common target vessels in the coronary circulation including the proximal and distal left anterior descending (PLAD & DLAD), right coronary (RCA), and left circumflex (LCX) arteries. Benchtop biaxial mechanical data was used to acquire constitutive model parameters of these tissues and enable vessel-specific computational models to elucidate the mechanical consequences of 32 unique graft-target combinations.

Results

Simulations revealed the maximum principal wall stresses for the PLAD, RCA, and LCX occurred when anastomosed with LITA₁, and the maximum flow-induced shear stress occurred with LITA₄. The DLAD, on the other hand, reached stress maximums when anastomosed to LITA₄. Using a normalized objective function of simulation output variables, we found LITA₂ to be the best graft choice for both LADs, RITA₃ for the RCA, and LITA₃ for the LCX.

Conclusion

Although mechanical compatibility is just one of many factors determining bypass graft outcomes, our data suggests improvements can be made to the grafting process through vessel-specific regional optimization.

Described herein are devices and methods for performing automated and minimally invasive intramyocardial injections for cardiac repair that eliminate the need for opening the chest cavity for injections of therapeutics to the heart muscle to address heart attack, cardiomyopathy or myocardial diseases and can detect diseased tissue and deliver a specified volume of a therapeutic injectate to the region of interest.

Drug-coated balloon therapy is a minimally invasive endovascular approach to treat obstructive arterial disease, with increasing utilization in the peripheral circulation due to improved outcomes as compared to alternative interventional modalities. Broader clinical use of drug-coated balloons is limited by an incomplete understanding of device- and patient-specific determinants of treatment efficacy, including late outcomes that are mediated by postinterventional maladaptive inward arterial remodeling. To address this knowledge gap, we propose a predictive mathematical model of pressure-mediated femoral artery remodeling following drug-coated balloon deployment, with account of drug-based modulation of resident vascular cell phenotype and common patient comorbidities, namely, hypertension and endothelial cell dysfunction. Our results elucidate how postinterventional arterial remodeling outcomes are altered by the delivery of a traditional anti-proliferative drug, as well as by codelivery with an anti-contractile drug. Our findings suggest that codelivery of anti-proliferative and anti-contractile drugs could improve patient outcomes following drug-coated balloon therapy, motivating further consideration of novel payloads in next-generation devices.

Biotechnological innovations have vastly improved the capacity to perform large-scale protein studies, while the methods we have for identifying and quantifying individual proteins are still inadequate to perform protein sequencing at the single-molecule level. Nanopore-inspired systems devoted to understanding how single molecules behave have been extensively developed for applications in genome sequencing. These nanopore systems are emerging as prominent tools for protein identification, detection, and analysis, suggesting realistic prospects for novel protein sequencing. This review summarizes recent advances in biological nanopore sensors toward protein sequencing, from the identification of individual amino acids to the controlled translocation of peptides and proteins, with attention focused on device and algorithm development and the delineation of molecular mechanisms with the aid of simulations. Specifically, the review aims to offer recommendations for the advancement of nanopore-based protein sequencing from an engineering perspective, highlighting the need for collaborative efforts across multiple disciplines. These efforts should include chemical conjugation, protein engineering, molecular simulation, machine-learning-assisted identification, and electronic device fabrication to enable practical implementation in real-world scenarios.

Dementia refers to a particular group of symptoms characterized by difficulties with memory, language, problem-solving, and other thinking skills that affect a person’s ability to perform everyday activities. Alzheimer’s disease (AD) is the most common form of dementia, affecting about 6.2 million Americans aged 65 years and older. Likewise, cardiovascular diseases (CVDs) are a major cause of disability and premature death, impacting 126.9 million adults in the USA, a number that increases with age. Consequently, CVDs and cardiovascular risk factors are associated with an increased risk of AD and cognitive impairment. They share important age-related cardiometabolic and lifestyle risk factors, that make them among the leading causes of death. Additionally, there are several premises and hypotheses about the mechanisms underlying the association between AD and CVD. Although AD and CVD may be considered deleterious to health, the study of their combination constitutes a clinical challenge, and investigations to understand the mechanistic pathways for the cause-effect and/or shared pathology between these two disease constellations remains an active area of research. AD pathology is propagated by the amyloid β (Aβ) peptides. These peptides give rise to small, toxic, and soluble Aβ oligomers (SPOs) that are nonfibrillar, and it is their levels that show a robust correlation with the extent of cognitive impairment. This review will elucidate the interplay between the effects of accumulating SPOs in AD and CVDs, the resulting ER stress response, and their role in vascular dysfunction. We will also address the potential underlying mechanisms, including the possibility that SPOs are among the causes of vascular injury in CVD associated with cognitive decline. By revealing common mechanistic underpinnings of AD and CVD, we hope that novel experimental therapeutics can be designed to reduce the burden of these devastating diseases.

Cytomegalovirus (CMV) is a member of the β-herpesviruses and is ubiquitous, infecting 50%–99% of the human population depending on ethnic and socioeconomic conditions. CMV establishes lifelong, latent infections in their host. Spontaneous reactivation of CMV is usually asymptomatic, but reactivation events in immunocompromised or immunosuppressed individuals can lead to severe morbidity and mortality. Moreover, herpesvirus infections have been associated with several cardiovascular and post-transplant diseases (stroke, atherosclerosis, post-transplant vasculopathy, and hypertension). Herpesviruses, including CMV, encode viral G-protein-coupled receptors (vGPCRs) that alter the host cell by hijacking signaling pathways that play important roles in the viral life cycle and these cardiovascular diseases. In this brief review, we discuss the pharmacology and signaling properties of these vGPCRs, and their contribution to hypertension. Overall, these vGPCRs can be considered attractive targets moving forward in the development of novel hypertensive therapies.

We consider the thermal, mechanical, and chemical contact of two subsystems composed of ideal gases, both of which are not in the thermodynamic limit. After contact, the combined system is isolated, and the entropy is determined through the use of its standard connection to the phase space density (PSD), where only those microstates at a given energy value are counted. The various intensive properties of these small systems that follow from a derivative of the PSD, such as the temperature, pressure, and chemical potential (evaluated via a backward difference), while equal when the two subsystems are in equilibrium are nevertheless found not to behave in accordance with what is expected from macroscopic thermodynamics. Instead, it is the entropy, defined from its connection to the PSD, that still controls the behavior of these small (nonextensive) systems. We also analyze the contact of these two subsystems utilizing an alternative entropy definition, through its proposed connection to the phase space volume (PSV), where all microstates at or below a given energy value are counted. We show that certain key properties of these small systems obtained with the PSV either do not become equal or do not consistently describe the two subsystems when in contact, suggesting that the PSV should not be used for analyzing the behavior of small isolated systems.

In general, the present disclosure is directed to systems and methods of evaluating a subject's risk of one or more complications associated with pelvic organ prolapse surgery. The method comprising: obtaining, by a computing system comprising one or more computing devices, sample data associated with the subject; inputting, by the computing system, the sample data into a machine-learned immune response model; receiving, by the computing system as an output of the machine-learned immune response model, one or more predictions of post-surgical complications of mesh exposure through the vaginal wall associated with the subject; and performing a pelvic organ prolapse repair surgery on the subject, wherein the surgery is performed based at least in part on the one or more predictions of post-surgical complications by the machine-learned immune response model associated with a likelihood of success.

Background: Pelvic organ prolapse (POP) refers to symptomatic descent of the vaginal wall. To reduce surgical failure rates, surgical correction can be augmented with the insertion of polypropylene mesh. This benefit is offset by the risk of mesh complication, predominantly mesh exposure through the vaginal wall. If mesh placement is under consideration as part of prolapse repair, patient selection and counseling would benefit from the prediction of mesh exposure; yet, no such reliable preoperative method currently exists. Past studies indicate that inflammation and associated cytokine release is correlated with mesh complication. While some degree of mesh-induced cytokine response accompanies implantation, excessive or persistent cytokine responses may elicit inflammation and implant rejection.

Objective: Here, we explore the levels of biomaterial-induced blood cytokines from patients who have undergone POP repair surgery to (1) identify correlations among cytokine expression and (2) predict postsurgical mesh exposure through the vaginal wall.

Methods: Blood samples from 20 female patients who previously underwent surgical intervention with transvaginal placement of polypropylene mesh to correct POP were collected for the study. These included 10 who experienced postsurgical mesh exposure through the vaginal wall and 10 who did not. Blood samples incubated with inflammatory agent lipopolysaccharide, with sterile polypropylene mesh, or alone were analyzed for plasma levels of 13 proinflammatory and anti-inflammatory cytokines using multiplex assay. Data were analyzed by principal component analysis (PCA) to uncover associations among cytokines and identify cytokine patterns that correlate with postsurgical mesh exposure through the vaginal wall. Supervised machine learning models were created to predict the presence or absence of mesh exposure and probe the number of cytokine measurements required for effective predictions.

Results: PCA revealed that proinflammatory cytokines interferon gamma, interleukin 12p70, and interleukin 2 are the largest contributors to the variance explained in PC 1, while anti-inflammatory cytokines interleukins 10, 4, and 6 are the largest contributors to the variance explained in PC 2. Additionally, PCA distinguished cytokine correlations that implicate prospective therapies to improve postsurgical outcomes. Among machine learning models trained with all 13 cytokines, the artificial neural network, the highest performing model, predicted POP surgical outcomes with 83% (15/18) accuracy; the same model predicted POP surgical outcomes with 78% (14/18) accuracy when trained with just 7 cytokines, demonstrating retention of predictive capability using a smaller cytokine group.

Conclusions: This preliminary study, incorporating a sample size of just 20 participants, identified correlations among cytokines and demonstrated the potential of this novel approach to predict mesh exposure through the vaginal wall following transvaginal POP repair surgery. Further study with a larger sample size will be pursued to confirm these results. If corroborated, this method could provide a personalized medicine approach to assist surgeons in their recommendation of POP repair surgeries with minimal potential for adverse outcomes.

JMIR Perioper Med 2023;6:e40402