Ccn2a is an injury-induced matricellular factor that promotes cardiac regeneration in zebrafish.

The ability of zebrafish to heal their heart after injury makes them an attractive model for investigating the mechanisms governing the regenerative process. In this study, we show that the gene cellular communication network factor 2a (ccn2a), previously known as ctgfa, is induced in endocardial cells in the injured tissue and regulates CM proliferation and repopulation of the damaged tissue. We find that, whereas in wild-type animals, CMs track along the newly formed blood vessels that revascularize the injured tissue, in ccn2a mutants CM proliferation and repopulation are disrupted, despite apparently unaffected revascularization. In addition, we find that ccn2a overexpression enhances CM proliferation and improves the resolution of transient collagen deposition. Through loss- and gain-of-function as well as pharmacological approaches, we provide evidence that Ccn2a is necessary for and promotes heart regeneration by enhancing the expression of pro-regenerative extracellular matrix genes, and by inhibiting the chemokine receptor gene cxcr3.1 through a mechanism involving Tgfß/pSmad3 signaling. Thus, Ccn2a positively modulates the innate regenerative response of the adult zebrafish heart.

The BIORES-21 Survey: Insights Into Remote and Online Education in Biomechanics and Mechanobiology.

The COVID-19 pandemic necessitated mainstream adoption of online and remote learning approaches, which were highly advantageous yet challenging in many ways. The online modality, while teaching biomedical engineering-related topics in the areas of biomechanics, mechanobiology, and biomedical sciences, further added to the complexity faced by the faculty and students. Both the benefits and the challenges have not been explored systematically by juxtaposing experiences and reflections of both the faculty and students. Motivated by this need, we designed and conducted a systematic survey named BIORES-21, targeted toward the broader bio-engineering community. Survey responses and our inferences from survey findings cumulatively offer insight into the role of employed teaching/learning technology and challenges associated with student engagement. Survey data also provided insights on what worked and what did not, potential avenues to address some underlying challenges, and key beneficial aspects such as integration of technology and their role in improving remote teaching/learning experiences. Overall, the data presented summarize the key benefits and challenges of online learning that emerged from the experiences during the pandemic, which is valuable for the continuation of online learning techniques as in-person education operations resumed broadly across institutions, and some form of online learning seems likely to sustain and grow in the near future.

Computational Fluid Dynamic Assessment of Patients with Congenital Heart Disease from 3D Rotational Angiography.

For congenital heart disease patients, multiple imaging modalities are needed to discern anatomy and functional information such as differential blood flow. During cardiac catheterization, 3D rotational angiography (3DRA) can provide CTA-like images, enabling anatomical information and intraprocedural guidance. We seek to establish whether unique aspects of this technique can also generate quantitative functional blood flow information. We propose that systematic integration of 3DRA imaging, catheter hemodynamic information, and computational fluid dynamics (CFD), can provide quantitative information regarding blood flow dynamics and energetics, without additional imaging or procedures. We report a single center retrospective feasibility study comprising four patients with 3DRA imaging and a complete set of hemodynamic data. 3DRA was processed and segmented to reconstruct vascular regions of interest (ROI), and a computational grid for CFD modeling of blood flow through the ROI was generated. Blood flow was simulated by integrating catheter hemodynamic data to devise boundary conditions at vascular ROI inlets and outlets. The 3DRA-based workflow successfully generated key computational outputs commonly used for cardiovascular applications, including flow patterns, distribution fractions, wall shear stress. Computational outputs obtained were as detailed and resolved as those obtained from more commonly used CT or MR angiography. Accuracy was confirmed by comparing computed flow distributions with measurements for 2 cases, showing less than 2.0% error from the measured data. Systematic integration of catheter hemodynamic information, 3DRA imaging, and CFD modeling, provides an effective and feasible alternative to obtain important quantitative blood flow information and visualization, without additional imaging.

Recent Update on Nanocarrier(s) as the Targeted Therapy for Breast Cancer.

Despite ongoing advances in cancer therapy, the results for the treatment of breast cancer are not satisfactory. The advent of nanotechnology promises to be an essential tool to improve drug delivery effectiveness in cancer therapy. Nanotechnology provides an opportunity to enhance the treatment modality by preventing degradation, improving tumour targeting, and controlling drug release. Recent advances have revealed several strategies to prevent cancer metastasis using nano-drug delivery systems (NDDS). These strategies include the design of appropriate nanocarriers loaded with anti-cancer drugs that target the optimization of physicochemical properties, modulate the tumour microenvironment, and target biomimetic techniques. Nanocarriers have emerged as a preferential approach in the chemotropic treatment for breast cancer due to their pivotal role in safeguarding the therapeutic agents against degradation. They facilitate efficient drug concentration in targeted cells, surmount the resistance of drugs, and possess a small size. Nevertheless, these nanocarrier(s) have some limitations, such as less permeability across the barrier and low bioavailability of loaded drugs. To overcome these challenges, integrating external stimuli has been employed, encompassing infrared light, thermal stimulation, microwaves, and X-rays. Among these stimuli, ultrasound-triggered nanocarriers have gained significant attention due to their cost-effectiveness, non-invasive nature, specificity, ability to penetrate tissues, and capacity to deliver elevated drug concentrations to intended targets. This article comprehensively reviews recent advancements in different nanocarriers for breast cancer chemotherapy. It also delves into the associated hurdles and offers valuable insights into the prospective directions for this innovative field.

Recent Trends in Nanocarrier-Based Drug Delivery System for Prostate Cancer.

Prostate cancer remains a significant global health concern, requiring innovative approaches for improved therapeutic outcomes. In recent years, nanoparticle-based drug delivery systems have emerged as promising strategies to address the limitations of conventional cancer chemotherapy. The key trends include utilizing nanoparticles for enhancing drug delivery to prostate cancer cells. Nanoparticles have some advantages such as improved drug solubility, prolonged circulation time, and targeted delivery of drugs. Encapsulation of chemotherapeutic agents within nanoparticles allows for controlled release kinetics, reducing systemic toxicity while maintaining therapeutic efficacy. Additionally, site-specific accumulation within the prostate tumor microenvironment is made possible by the functionalization of nanocarrier with targeted ligands, improving therapeutic effectiveness. This article highlights the basics of prostate cancer, statistics of prostate cancer, mechanism of multidrug resistance, targeting approach, and different types of nanocarrier used for the treatment of prostate cancer. It also includes the applications of nanocarriers for the treatment of prostate cancer and clinical trial studies to validate the safety and efficacy of the innovative drug delivery systems. The article focused on developing nanocarrier-based drug delivery systems, with the goal of translating these advancements into clinical applications in the future.

A mesoscale agent based modeling framework for flow-mediated infection transmission in indoor occupied spaces.

The ongoing Covid-19 pandemic, and its associated public health and socioeconomic burden, has reaffirmed the necessity for a comprehensive understanding of flow-mediated infection transmission in occupied indoor spaces. This is an inherently multiscale problem, and suitable investigation approaches that can enable evidence-based decision-making for infection control strategies, interventions, and policies; will need to account for flow physics, and occupant behavior. Here, we present a mesoscale infection transmission model for human occupied indoor spaces, by integrating an agent-based human interaction model with a flow physics model for respiratory droplet dynamics and transport. We outline the mathematical and algorithmic details of the modeling framework, and demonstrate its validity using two simple simulation scenarios that verify each of the major sub-models. We then present a detailed case-study of infection transmission in a model indoor space with 60 human occupants; using a systematic set of simulations representing various flow scenarios. Data from the simulations illustrate the utility and efficacy of the devised mesoscale model in resolving flow-mediated infection transmission; and elucidate key trends in infection transmission dynamics amongst the human occupants.

Using Simulation-Based Active Learning Strategies for Teaching Biofluids Concepts.

Biofluids comprises a core topical domain for modern biomedical engineering education. Like other biomedical topic areas, biofluids education must address highly interdisciplinary and applied topics. Concept/problem-based active learning approaches can provide effective avenues to teach such diverse and applied topics. However, with the heterogeneity within biofluids topics across cellular, physiological, and/or extra-organismal scales, it is important to develop active learning content that enables students to explore concepts with appropriate context. This challenge is further complicated by the need to administer such content remotely (due to the Covid-19 pandemic). Here, we outline our design process and implementation experience for simulation-based active learning modules for a newly developed physiological biofluids course. We share the overall design approach, with two example cases of simulation-based concept exploration: (a) arterial Windkessel effects and lumped parameter hemodynamic analysis; and (b) curvature-induced helical flow in human aorta illustrated using four-dimensional (4D) flow magnetic resonance imaging (MRI). Evidence from student survey ratings, student comments and feedback, and monitoring student performance for course deliverables indicate positive student response toward these modules, and efficacy of the modules in enabling student learning. Based on our design and implementation experience, we argue that simulation-based approaches can enable active learning of biofluids through remote and online learning modalities.

Chemical and genetic rescue of an ep300 knockdown model for Rubinstein Taybi Syndrome in zebrafish.

EP300 is a member of the EP300/CBP family of lysine acetyltransferases (KATs) with multiple roles in development and physiology. Loss of EP300/CBP activity in humans causes a very rare congenital disorder called Rubinstein Taybi Syndrome (RSTS). The zebrafish genome has two co-orthologs of lysine acetyltransferase EP300 (KAT3B) in zebrafish viz. ep300a and ep300b. Chemical inhibition of Ep300 with C646, a competitive inhibitor and morpholino-based genetic knockdown of ep300a and ep300b cause defects in embryonic development reminiscent of the human RSTS syndrome. Remarkably, overexpression of Ep300a KAT domain results in near complete rescue of the jaw development defects, a characteristic feature of RSTS in human suggesting the dispensability of the protein-interaction and DNA-binding domains for at least some developmental roles of Ep300. We also perform a chemical screen and identify two inhibitors of deacetylases, CHIC35 and HDACi III, that can partially rescue the RSTS-like phenotypes. Thus, modeling rare human genetic disorders in zebrafish allows for functional understanding of the genes involved and can also yield small molecule candidates towards therapeutic goals.

Computational Assessment of the Relation Between Embolism Source and Embolus Distribution to the Circle of Willis for Improved Understanding of Stroke Etiology.

Stroke caused by an embolism accounts for about a third of all stroke cases. Understanding the source and cause of the embolism is critical for diagnosis and long-term treatment of such stroke cases. The complex nature of the transport of an embolus within large arteries is a primary hindrance to a clear understanding of embolic stroke etiology. Recent advances in medical image-based computational hemodynamics modeling have rendered increasing utility to such techniques as a probe into the complex flow and transport phenomena in large arteries. In this work, we present a novel, patient-specific, computational framework for understanding embolic stroke etiology, by combining image-based hemodynamics with discrete particle dynamics and a sampling-based analysis. The framework allows us to explore the important question of how embolism source manifests itself in embolus distribution across the various major cerebral arteries. Our investigations illustrate prominent numerical evidence regarding (i) the size/inertia-dependent trends in embolus distribution to the brain; (ii) the relative distribution of cardiogenic versus aortogenic emboli among the anterior, middle, and posterior cerebral arteries; (iii) the left versus right brain preference in cardio-emboli and aortic-emboli transport; and (iv) the source-destination relationship for embolisms affecting the brain.

Transforming Cancer Care: The Impact of AI-Driven Strategies.

AI is a critical component in healthcare, especially in the application of precision medicine where patients' characteristics, including genetic makeup, determine the treatment options that should be implemented. AI sorts big data, predicting people's reactions to specific treatments, the right combinations of drugs, and possible side effects, therefore increasing the efficiency of the treatment process and decreasing negative outcomes. This article briefly presents the ethical issues and concerns that might arise due to the integration of AI in society, such as the privacy of data, the issues of bias in the algorithms, and the issues of interpretability of the AI systems. Nevertheless, there is no doubt that AI can bring qualitative changes in cancer care based on its potential to enhance patient prognosis and reduce health care costs, as well as become a defining feature of the standard of care.

Decoding thrombosis through code: a review of computational models.

From the molecular level up to a blood vessel, thrombosis and hemostasis involves many interconnected biochemical and biophysical processes over a wide range of length and time scales. Computational modeling has gained eminence in offering insights into these processes beyond what can be obtained from in vitro or in vivo experiments, or clinical measurements. The multiscale and multiphysics nature of thrombosis has inspired a wide range of modeling approaches that aim to address how a thrombus forms and dismantles. Here, we review recent advances in computational modeling with a focus on platelet-based thrombosis. We attempt to summarize the diverse range of modeling efforts straddling the wide-spectrum of physical phenomena, length scales, and time scales; highlighting key advancements and insights from existing studies. Potential information gleaned from models is discussed, ranging from identification of thrombus-prone regions in patient-specific vasculature to modeling thrombus deformation and embolization in response to fluid forces. Furthermore, we highlight several limitations of current models, future directions in the field, and opportunities for clinical translation, to illustrate the state-of-the-art. There are a plethora of opportunity areas for which models can be expanded, ranging from topics of thromboinflammation to platelet production and clearance. Through successes demonstrated in existing studies described here, as well as continued advancements in computational methodologies and computer processing speeds and memory, in silico investigations in thrombosis are poised to bring about significant knowledge growth in the years to come.

Investigating clot-flow interactions by integrating intravital imaging with in silico modeling for analysis of flow, transport, and hemodynamic forces.

As a blood clot forms, grows, deforms, and embolizes following a vascular injury, local clot-flow interactions lead to a highly dynamic flow environment. The local flow influences transport of biochemical species relevant for clotting, and determines the forces on the clot that in turn lead to clot deformation and embolization. Despite this central role, quantitative characterization of this dynamic clot-flow interaction and flow environment in the clot neighborhood remains a major challenge. Here, we propose an approach that integrates dynamic intravital imaging with computer geometric modeling and computational flow and transport modeling to develop a unified in silico framework to quantify the dynamic clot-flow interactions. We outline the development of the methodology referred to as Intravital Integrated In Silico Modeling or IVISim, and then demonstrate the method on a sample set of simulations comprising clot formation following laser injury in two mouse cremaster arteriole injury model data: one wild-type mouse case, and one diYF knockout mouse case. Simulation predictions are verified against experimental observations of transport of caged fluorescent Albumin (cAlb) in both models. Through these simulations, we illustrate how the IVISim methodology can provide insights into hemostatic processes, the role of flow and clot-flow interactions, and enable further investigations comparing and contrasting different biological model scenarios and parameter variations.

Understanding Embolus Transport And Source To Destination Mapping Of Thromboemboli In Hemodynamics Driven By Left Ventricular Assist Device.

Left Ventricular Assist Devices (LVADs) are a key treatment option for patients with advanced heart failure, but they carry a significant risk of thromboembolic complications. While improved LVAD design, and systemic anticoagulation regimen, have helped mitigate thromboembolic risks, ischemic stroke due to adverse thromboembolic events remains a major concern with current LVAD therapies. Improved understanding of embolic events, and embolus movement to the brain, is critical to develop techniques to minimize risks of occlusive embolic events such as a stroke after LVAD implantation. Here, we address this need, and devise a quantitative in silico framework to characterize thromboembolus transport and distrbution in hemodynamics driven by an operating LVAD. We conduct systematic numerical experiments to quantify the source-to-destination transport patterns of thromboemboli as a function of: LVAD outflow graft anastomosis, LVAD operating pulse modulation, thromboembolus sizes, and origin locations of emboli. Additionally, we demonstrate how the resulting embolus distribution patterns compare and correlate with descriptors based solely on hemodynamic patterns such as helicity, vorticity, and wall shear stress. Using the concepts of size-dependent embolus-hemodynamics interactions, and two jet flow model for hemodynamics under LVAD operation as established in our prior works, we gain valuable insights on departure of thromboembolus distribution from flow distribution, and establish that our in silico model can generate deep insights into embolus dynamics which is not otherwise available from standard of care imaging and clinical data.

Evidence and Mechanisms for Embolic Stroke in Contralateral Hemispheres From Carotid Artery Sources.

BACKGROUND: Disambiguation of embolus pathogenesis in embolic strokes is often a clinical challenge. One common source of embolic stroke is the carotid arteries, with emboli originating due to plaque buildup or perioperatively during revascularization procedures. Although it is commonly thought that thromboemboli from carotid sources travel to cerebral arteries ipsilaterally, there are existing reports of contralateral embolic events that complicate embolus source destination relationship for carotid sources. Here, we hypothesize that emboli from carotid sources can travel to contralateral hemispheres and that embolus interactions with collateral hemodynamics in the circle of Willis influence this process. METHODS AND RESULTS: We use a patient-specific computational embolus-hemodynamics interaction model developed in prior works to conduct an in silico experiment spanning 4 patient vascular models, 6 circle of Willis anastomosis variants, and 3 different thromboembolus sizes released from left and right carotid artery sites. This led to a total of 144 different experiments, estimating trajectories and distribution of approximately 1.728 million embolus samples. Across all cases considered, emboli from left and right carotid sources showed nonzero contralateral transport (P value <-0.05). Contralateral movement revealed a size dependence, with smaller emboli traveling more contralaterally. Detailed analysis of embolus dynamics revealed that collateral flow routes in the circle of Willis played a role in routing emboli, and transhemispheric movement occurred through the anterior and posterior communicating arteries in the circle of Willis. CONCLUSIONS: We generated quantitative data demonstrating the complex dynamics of finite size thromboembolus particles as they interact with pulsatile arterial hemodynamics and traverse the vascular network of the circle of Willis. This leads to a nonintuitive source-destination relationship for emboli originating from carotid artery sites, and emboli from carotid sources can potentially travel to cerebral arteries on contralateral hemispheres.

Evidence And Mechanisms For Embolic Stroke In Contralateral Hemispheres From Carotid Artery Sources.

Disambiguation of embolus etiology in embolic strokes is often a clinical challenge. One common source of embolic stroke is the carotid arteries, with emboli originating due to plaque build up, or perioperatively during revascularization procedures. While it is commonly thought that thromboemboli from carotid sources travel to cerebral arteries ipsilaterally, there are existing reports of contralateral embolic events which complicate embolus source destination relationship for carotid sources. Here, we hypothesize that emboli from carotid sources can travel to contralateral hemispheres, and that embolus interactions with collateral hemodynamics in the Circle of Willis influences this process. We use a patient-specific computational embolus-hemodynamics interaction model developed in prior works to conduct an in silico experiment spanning 4 patient vascular models, 6 Circle of Willis anastomosis variants, and 3 different thromboembolus sizes released from left and right carotid artery sites. This led to a total of 144 different experiments, estimating trajectories and distribution of approximately 1.728 million embolus samples. Across all cases considered, emboli from left and right carotid sources showed non-zero contralateral transport (p value < 0.05). Contralateral movement revealed a size-dependence, with smaller emboli traveling more contralaterally. Detailed analysis of embolus dynamics revealed that collateral flow routes in Circle of Willis played a role in routing emboli, and transhemispheric movement occurred through the anterior and posterior communicating arteries in the Circle of Willis. We generated quantitative data demonstrating the complex dynamics of finite size thromboembolus particles as they interact with pulsatile arterial hemodynamics, and traverse the vascular network of the Circle of Willis. This leads to a non-intuitive source-destination relationship for emboli originating from carotid artery sites, and emboli from carotid sources can potentially travel to cerebral arteries on contralateral hemispheres.

Quantitative Assessment of Aortic Hemodynamics for Varying Left Ventricular Assist Device Outflow Graft Angles and Flow Pulsation.

Left ventricular assist devices (LVADs) comprise a primary treatment choice for advanced heart failure patients. Treatment with LVAD is commonly associated with complications like stroke and gastro-intestinal (GI) bleeding, which adversely impacts treatment outcomes, and causes fatalities. The etiology and mechanisms of these complications can be linked to the fact that LVAD outflow jet leads to an altered state of hemodynamics in the aorta as compared to baseline flow driven by aortic jet during ventricular systole. Here, we present a framework for quantitative assessment of aortic hemodynamics in LVAD flows realistic human vasculature, with a focus on quantifying the differences between flow driven by LVAD jet and the physiological aortic jet when no LVAD is present. We model hemodynamics in the aortic arch proximal to the LVAD outflow graft, as well as in the abdominal aorta away from the LVAD region. We characterize hemodynamics using quantitative descriptors of flow velocity, stasis, helicity, vorticity and mixing, and wall shear stress. These are used on a set of 27 LVAD scenarios obtained by parametrically varying LVAD outflow graft anastomosis angles, and LVAD flow pulse modulation. Computed descriptors for each of these scenarios are compared against the baseline flow, and a detailed quantitative characterization of the altered state of hemodynamics due to LVAD operation (when compared to baseline aortic flow) is compiled. These are interpreted using a conceptual model for LVAD flow that distinguishes between flow originating from the LVAD outflow jet (and its impingement on the aorta wall), and flow originating from aortic jet during aortic valve opening in normal physiological state.

The Relation Between Viscous Energy Dissipation and Pulsation for Aortic Hemodynamics Driven by a Left Ventricular Assist Device.

Left ventricular assist device (LVAD) provides mechanical circulatory support for patients with advanced heart failure. Treatment using LVAD is commonly associated with complications such as stroke and gastro-intestinal bleeding. These complications are intimately related to the state of hemodynamics in the aorta, driven by a jet flow from the LVAD outflow graft that impinges into the aorta wall. Here we conduct a systematic analyses of hemodynamics driven by an LVAD with a specific focus on viscous energy transport and dissipation. We conduct a complementary set of analysis using idealized cylindrical tubes with diameter equivalent to common carotid artery and aorta, and a patient-specific model of 27 different LVAD configurations. Results from our analysis demonstrate how energy dissipation is governed by key parameters such as frequency and pulsation, wall elasticity, and LVAD outflow graft surgical anastomosis. We find that frequency, pulsation, and surgical angles have a dominant effect, while wall elasticity has a weaker effect, in determining the state of energy dissipation. For the patient-specific scenario, we also find that energy dissipation is higher in the aortic arch and lower in the abdominal aorta, when compared to the baseline flow without an LVAD. This further illustrates the key hemodynamic role played by the LVAD outflow jet impingement, and subsequent aortic hemodynamics during LVAD operation.

Hemodynamics Indicates Differences Between Patients With And Without A Stroke Outcome After Left Ventricular Assist Device Implantation.

Stroke remains a leading cause of complications and mortality in heart failure patients treated with LVAD circulatory support. Hemodynamics plays a central role in affecting risk and etiology of stroke during LVAD support. Yet, detailed quantitative assessment of hemodynamic variables and their relation to stroke outcomes in patients with an implanted LVAD remains a challenge. We present an in silico hemodynamics analysis in a set of 12 patients on LVAD support; 6 with reported stroke outcomes and 6 without. We conducted patient-specific hemodynamics simulations for models with the LVAD outflow graft reconstructed from cardiac-gated CT images. A pre-implantation baseline flow model was virtually generated for each case by removing the LVAD outflow graft and driving flow from the aortic root. Hemodynamics was characterized using quantitative descriptors for helical flow, vortex generation, and wall shear stress. Our analysis showed higher average values for descriptors of positive helical flow, vortex generation, and wall shear stress, across the 6 cases with stroke outcomes on LVAD support, when compared with cases without stroke. When the descriptors for LVAD-driven flow were compared against estimated baseline flow pre-implantation, extent of positive helicity was higher, and vorticity and wall shear were lower in cases with stroke compared to those without. The study suggests that quantitative analysis of hemodynamics after LVAD implantation; and hemodynamic alterations from a pre-implant flow scenario, can potentially reveal hidden information linked to stroke outcomes during LVAD support. This has broad implications on understanding stroke etiology, LVAD treatment planning, surgical optimization, and efficacy assessment.

Host lung microbiota promotes malaria-associated acute respiratory distress syndrome.

Severe malaria can manifest itself with a variety of well-recognized clinical phenotypes that are highly predictive of death - severe anaemia, coma (cerebral malaria), multiple organ failure, and respiratory distress. The reasons why an infected individual develops one pathology rather than another remain poorly understood. Here we use distinct rodent models of infection to show that the host microbiota is a contributing factor for the development of respiratory distress syndrome and host mortality in the context of malaria infections (malaria-associated acute respiratory distress syndrome, MA-ARDS). We show that parasite sequestration in the lung results in sustained immune activation. Subsequent production of the anti-inflammatory cytokine IL-10 by T cells compromises microbial control, leading to severe lung disease. Notably, bacterial clearance with linezolid, an antibiotic commonly used in the clinical setting to control lung-associated bacterial infections, prevents MA-ARDS-associated lethality. Thus, we propose that the host's anti-inflammatory response to limit tissue damage can result in loss of microbial control, which promotes MA-ARDS. This must be considered when intervening against life-threatening respiratory complications.