Computational modeling of left ventricular flow using PC-CMR-derived four-dimensional wall motion.

Intracardiac hemodynamics plays a crucial role in the onset and development of cardiac and valvular diseases. Simulations of blood flow in the left ventricle (LV) have provided valuable insight into assessing LV hemodynamics. While fully coupled fluid-solid modelings of the LV remain challenging due to the complex passive-active behavior of the LV wall myocardium, the integration of imaging-driven quantification of structural motion with computational fluid dynamics (CFD) modeling in the LV holds the promise of feasible and clinically translatable characterization of patient-specific LV hemodynamics.

In-silico heart model phantom to validate cardiac strain imaging.

The quantification of cardiac strains as structural indices of cardiac function has a growing prevalence in clinical diagnosis. However, the highly heterogeneous four-dimensional (4D) cardiac motion challenges accurate "regional" strain quantification and leads to sizable differences in the estimated strains depending on the imaging modality and post-processing algorithm, limiting the translational potential of strains as incremental biomarkers of cardiac dysfunction. There remains a crucial need for a feasible benchmark that successfully replicates complex 4D cardiac kinematics to determine the reliability of strain calculation algorithms.

In-silico heart model phantom to validate cardiac strain imaging.

The quantification of cardiac strains as structural indices of cardiac function has a growing prevalence in clinical diagnosis. However, the highly heterogeneous four-dimensional (4D) cardiac motion challenges accurate "regional" strain quantification and leads to sizable differences in the estimated strains depending on the imaging modality and post-processing algorithm, limiting the translational potential of strains as incremental biomarkers of cardiac dysfunction. There remains a crucial need for a feasible benchmark that successfully replicates complex 4D cardiac kinematics to determine the reliability of strain calculation algorithms.

Building Digital Twins for Cardiovascular Health: From Principles to Clinical Impact.

The past several decades have seen rapid advances in diagnosis and treatment of cardiovascular diseases and stroke, enabled by technological breakthroughs in imaging, genomics, and physiological monitoring, coupled with therapeutic interventions. We now face the challenge of how to (1) rapidly process large, complex multimodal and multiscale medical measurements; (2) map all available data streams to the trajectories of disease states over the patient's lifetime; and (3) apply this information for optimal clinical interventions and outcomes. Here we review new advances that may address these challenges using digital twin technology to fulfill the promise of personalized cardiovascular medical practice.

Complete spatiotemporal quantification of cardiac motion in mice through enhanced acquisition and super-resolution reconstruction.

The quantification of cardiac motion using cardiac magnetic resonance imaging (CMR) has shown promise as an early-stage marker for cardiovascular diseases. Despite the growing popularity of CMR-based myocardial strain calculations, measures of complete spatiotemporal strains (i.e.

Early adverse physiological event detection using commercial wearables: challenges and opportunities.

Data from commercial off-the-shelf (COTS) wearables leveraged with machine learning algorithms provide an unprecedented potential for the early detection of adverse physiological events. However, several challenges inhibit this potential, including (1) heterogeneity among and within participants that make scaling detection algorithms to a general population less precise, (2) confounders that lead to incorrect assumptions regarding a participant's healthy state, (3) noise in the data at the sensor level that limits the sensitivity of detection algorithms, and (4) imprecision in self-reported labels that misrepresent the true data values associated with a given physiological event. The goal of this study was two-fold: (1) to characterize the performance of such algorithms in the presence of these challenges and provide insights to researchers on limitations and opportunities, and (2) to subsequently devise algorithms to address each challenge and offer insights on future opportunities for advancement.

Metal-Organic Framework as a New Type of Magnetothermally-Triggered On-Demand Release Carrier.

The development of external stimuli-controlled payload systems has been sought after with increasing interest toward magnetothermally-triggered drug release (MTDR) carriers due to their non-invasive features. However, current MTDR carriers present several limitations, such as poor heating efficiency caused by the aggregation of iron oxide nanoparticles (IONPs) or the presence of antiferromagnetic phases which affect their efficiency. Herein, a novel MTDR carrier is developed using a controlled encapsulation method that fully fixes and confines IONPs of various sizes within the metal-organic frameworks (MOFs).

Disrupted Stiffness Ratio Alters Nuclear Mechanosensing.

The ability of endothelial cells to sense and respond to dynamic changes in blood flow is critical for vascular homeostasis and cardiovascular health. The mechanical and geometric properties of the nuclear and cytoplasmic compartments affect mechanotransduction. We hypothesized that alterations to these parameters have resulting mechanosensory consequences.

Physics-informed neural networks for modeling physiological time series for cuffless blood pressure estimation.

The bold vision of AI-driven pervasive physiological monitoring, through the proliferation of off-the-shelf wearables that began a decade ago, has created immense opportunities to extract actionable information for precision medicine. These AI algorithms model input-output relationships of a system that, in many cases, exhibits complex nature and personalization requirements. A particular example is cuffless blood pressure estimation using wearable bioimpedance.

Continuous cuffless blood pressure monitoring with a wearable ring bioimpedance device.

Smart rings provide unique opportunities for continuous physiological measurement. They are easy to wear, provide little burden in comparison to other smart wearables, are suitable for nocturnal settings, and can be sized to provide ideal contact between the sensors and the skin at all times. Continuous measuring of blood pressure (BP) provides essential diagnostic and prognostic value for cardiovascular health management.

Physics-Informed Neural Networks for Modeling Physiological Time Series: A Case Study with Continuous Blood Pressure.

The bold vision of AI-driven pervasive physiological monitoring, through the proliferation of off-the-shelf wearables that began a decade ago, has created immense opportunities to extract actionable information for precision medicine. These AI algorithms model the input-output relationships of a system that, in many cases, exhibits complex nature and personalization requirements. A particular example is cuffless blood pressure estimation using wearable bioimpedance.

Migrant agricultural workers: a comparative analysis of both policy and COVID-19 response in Thailand, Italy, and Canada.

International migrant workers play an increasingly important role in the global economy and labor markets. As of 2017, there were 164 million migrant workers around the world, representing 4.7% of all workers.

Competing reasons, incomplete preferences, and framing effects.

The quasi-cyclical preferences that Bermúdez ascribes to Agamemnon and others in analogous situations do not best represent them. I offer two alternative accounts. One works best if the preference ordering is taken to be the agent's personal betterness ordering of acts; the other works best if it is taken to provide a summary of the agent's dispositions to act.

Blood Pressure Estimation using a Single Channel Bio-Impedance Ring Sensor.

The demand for non-obtrusive, accurate, and continuous blood pressure (BP) monitoring systems is becoming more prevalent with the realization of its significance in preventable cardiovascular disease (CVD) globally. Current cuff-based standards are bulky, uncomfortable, and are limited to discrete recording periods. Wearable sensor technologies such as those using optical photoplethysmography (PPG) have been used to develop blood pressure estimation models through a variety of methods.

Liquid Drug Delivery Approaches for the Treatment of Occlusive Arterial Disease: A Systematic Review.

Objective: Local Liquid drug (LLD) delivery devices have recently emerged as a novel approach to treat peripheral arterial disease. This systemic review aims to identify and evaluate the clinical utility of the most commonly used delivery devices.

Methods: A systemic review was performed using the Medical Subjects Heading terms of "drug delivery," "liquid," "local," and "cardiovascular disease" in PubMed, Google Scholar, and Scopus.

At the nexus of science, engineering, and medicine: Pasteur's quadrant reconsidered.

There has been a sea change in the scientific world, advanced even more rapidly by the recent compounded public crises. Accelerated discovery, and impact from such discoveries have come from convergence approaches across disciplines, sectors, institutions, and the multiple communities seeking the common goal of innovations that transform. The classic simultaneous pursuit of fundamental understanding and application has been termed  Pasteur's quadrant, where use-inspired basic research occurs.

Dynamic Tumor-Specific MHC-II Immuno-PET Predicts the Efficacy of Checkpoint Inhibitor Immunotherapy in Melanoma.

Despite the advance of immunotherapy, only a small subset of patients gains long-term survival benefit. This fact represents a compelling rationale to develop immuno-PET imaging that can predict tumor response to immunotherapy. An increasing number of studies have shown that tumor-specific major histocompatibility complex II (tsMHC-II) is associated with improved responses to targeted immunotherapy.

Precision delivery of liquid therapy into the arterial wall for the treatment of peripheral arterial disease.

Perfusion catheters have recently emerged as a novel approach to deliver liquid anti-proliferative agents into flow obstructed arterial segments. The purpose of this study was to determine the impact of luminal delivery pressure on liquid drug penetration into the vessel wall. An ex vivo model using harvested porcine carotid arteries and a two-dimensional computational model were utilized to determine the impact of delivery pressure of liquid therapy into the arterial wall.

On the pragmatic and epistemic virtues of inference to the best explanation.

In a series of papers over the past twenty years, and in a new book, Igor Douven (sometimes in collaboration with Sylvia Wenmackers) has argued that Bayesians are too quick to reject versions of inference to the best explanation that cannot be accommodated within their framework. In this paper, I survey their worries and attempt to answer them using a series of pragmatic and purely epistemic arguments that I take to show that Bayes' Rule really is the only rational way to respond to your evidence.

The Limitless Future of RNA Therapeutics.

Recent advances in the generation, purification and cellular delivery of RNA have enabled development of RNA-based therapeutics for a broad array of applications. RNA therapeutics comprise a rapidly expanding category of drugs that will change the standard of care for many diseases and actualize personalized medicine. These drugs are cost effective, relatively simple to manufacture, and can target previously undruggable pathways.

RNA therapeutics for cardiovascular disease.

Purpose Of Review: The development of mRNA vaccines against coronavirus disease 2019 has brought worldwide attention to the transformative potential of RNA-based therapeutics. The latter is essentially biological software that can be rapidly designed and generated, with an extensive catalog of applications. This review aims to highlight the mechanisms of action by which RNA-based drugs can affect specific gene targets and how RNA drugs can be employed to treat cardiovascular disease, with the focus on the therapeutics being evaluated in clinical trials.

Achieving healthy human longevity: A global grand challenge.

With continued advances in science and technology, there is great potential to extend our healthspan as we age.