A Hybrid Model for Cardiac Perfusion: Coupling a Discrete Coronary Arterial Tree Model with a Continuous Porous-Media Flow Model of the Myocardium.

This paper presents a novel hybrid approach for the computational modeling of cardiac perfusion, combining a discrete model of the coronary arterial tree with a continuous porous-media flow model of the myocardium. The constructive constrained optimization (CCO) algorithm captures the detailed topology and geometry of the coronary arterial tree network, while Poiseuille's law governs blood flow within this network. Contrast agent dynamics, crucial for cardiac MRI perfusion assessment, are modeled using reaction-advection-diffusion equations within the porous-media framework. The model incorporates fibrosis-contrast agent interactions and considers contrast agent recirculation to simulate myocardial infarction and Gadolinium-based late-enhancement MRI findings. Numerical experiments simulate various scenarios, including normal perfusion, endocardial ischemia resulting from stenosis, and myocardial infarction. The results demonstrate the model's efficacy in establishing the relationship between blood flow and stenosis in the coronary arterial tree and contrast agent dynamics and perfusion in the myocardial tissue. The hybrid model enables the integration of information from two different exams: computational fractional flow reserve (cFFR) measurements of the heart coronaries obtained from CT scans and heart perfusion and anatomy derived from MRI scans. The cFFR data can be integrated with the discrete arterial tree, while cardiac perfusion MRI data can be incorporated into the continuum part of the model. This integration enhances clinical understanding and treatment strategies for managing cardiovascular disease.

Simulation of the Perfusion of Contrast Agent Used in Cardiac Magnetic Resonance: A Step Toward Non-invasive Cardiac Perfusion Quantification.

This work presents a new mathematical model to describe cardiac perfusion in the myocardium as acquired by cardiac magnetic resonance (CMR) perfusion exams. The combination of first pass (or contrast-enhanced CMR) and late enhancement CMR is a widely used non-invasive exam that can identify abnormal perfused regions of the heart via the use of a contrast agent (CA). The exam provides important information to the diagnosis, management, and prognosis of ischemia and infarct: perfusion on different regions, the status of microvascular structures, the presence of fibrosis, and the relative volume of extracellular space. This information is obtained by inferring the spatiotemporal dynamics of the contrast in the myocardial tissue from the acquired images. The evaluation of these physiological parameters plays an important role in the assessment of myocardial viability. However, the nature of cardiac physiology poses great challenges in the estimation of these parameters. Briefly, these are currently estimated qualitatively via visual inspection of images and comparison of relative brightness between different regions of the heart. Therefore, there is a great urge for techniques that can help to quantify cardiac perfusion. In this work, we propose a new mathematical model based on multidomain flow in porous media. The model is based on a system of partial differential equations. Darcy's law is used to obtain the pressure and velocity distribution. CA dynamics is described by reaction-diffusion-advection equations in the intravascular space and in the interstitial space. The interaction of fibrosis and the CA is also considered. The new model treats the domains as anisotropic media and imposes a closed loop of intravascular flow, which is necessary to reproduce the recirculation of the CA. The model parameters were adjusted to reproduce clinical data. In addition, the model was used to simulate different scenarios: normal perfusion; endocardial ischemia due to stenosis in a coronary artery in the epicardium; and myocardial infarct. Therefore, the computational model was able to correlate anatomical features, stenosis and the presence of fibrosis, with functional ones, cardiac perfusion. Altogether, the results suggest that the model can support the process of non-invasive cardiac perfusion quantification.

Effects of left ventricle wall thickness uncertainties on cardiac mechanics.

Computational models of the heart have reached a level of maturity that enables sophisticated patient-specific simulations and hold potential for important applications in diagnosis and therapy planning. However, such clinical use puts strict demands on the reliability and accuracy of the models and requires the sensitivity of the model predictions due to errors and uncertainty in the model inputs to be quantified. The models typically contain a large number of parameters, which are difficult to measure and therefore associated with considerable uncertainty. Additionally, patient-specific geometries are usually constructed by semi-manual processing of medical images and must be assumed to be a potential source of model uncertainty. In this paper, we assess the model accuracy by considering the impact of geometrical uncertainties, which typically occur in image-based computational geometries. An approach based on 17 AHA segments diagram is used to consider uncertainties in wall thickness and also in the material properties and fiber orientation, and we perform a comprehensive uncertainty quantification and sensitivity analysis based on polynomial chaos expansions. The quantities considered include stress, strain and global deformation parameters of the left ventricle. The results indicate that important quantities of interest may be more affected by wall thickness, and highlight the need for accurate geometry reconstructions in patient-specific cardiac mechanics models.

Development of a Computational Model of Abscess Formation.

In some bacterial infections, the immune system cannot eliminate the invading pathogen. In these cases, the invading pathogen is successful in establishing a favorable environment to survive and persist in the host organism. For example, S. aureus bacteria survive in organ tissues employing a set of mechanisms that work in a coordinated and highly regulated way allowing: (1) efficient impairment of the immune response; and (2) protection from the immune cells and molecules. S. aureus secretes several proteins including coagulases and toxins that drive abscess formation and persistence. Unless staphylococcal abscesses are surgically drained and treated with antibiotics, disseminated infection and septicemia produce a lethal outcome. Within this context, this paper develops a simple mathematical model of abscess formation incorporating characteristics that we judge important for an abscess to be formed. Our aim is to build a mathematical model that reproduces some characteristics and behaviors that are observed in the process of abscess formation.

A qualitatively validated mathematical-computational model of the immune response to the yellow fever vaccine.

BACKGROUND: Although a safe and effective yellow fever vaccine was developed more than 80 years ago, several issues regarding its use remain unclear. For example, what is the minimum dose that can provide immunity against the disease? A useful tool that can help researchers answer this and other related questions is a computational simulator that implements a mathematical model describing the human immune response to vaccination against yellow fever. METHODS: This work uses a system of ten ordinary differential equations to represent a few important populations in the response process generated by the body after vaccination. The main populations include viruses, APCs, CD8+ T cells, short-lived and long-lived plasma cells, B cells and antibodies. RESULTS: In order to qualitatively validate our model, four experiments were carried out, and their computational results were compared to experimental data obtained from the literature. The four experiments were: a) simulation of a scenario in which an individual was vaccinated against yellow fever for the first time; b) simulation of a booster dose ten years after the first dose; c) simulation of the immune response to the yellow fever vaccine in individuals with different levels of naïve CD8+ T cells; and d) simulation of the immune response to distinct doses of the yellow fever vaccine. CONCLUSIONS: This work shows that the simulator was able to qualitatively reproduce some of the experimental results reported in the literature, such as the amount of antibodies and viremia throughout time, as well as to reproduce other behaviors of the immune response reported in the literature, such as those that occur after a booster dose of the vaccine.

A New Age-Structured Multiscale Model of the Hepatitis C Virus Life-Cycle During Infection and Therapy With Direct-Acting Antiviral Agents.

The dynamics of hepatitis C virus (HCV) RNA during translation and replication within infected cells were added to a previous age-structured multiscale mathematical model of HCV infection and treatment. The model allows the study of the dynamics of HCV RNA inside infected cells as well as the release of virus from infected cells and the dynamics of subsequent new cell infections. The model was used to fit in vitro data and estimate parameters characterizing HCV replication. This is the first model to our knowledge to consider both positive and negative strands of HCV RNA with an age-structured multiscale modeling approach. Using this model we also studied the effects of direct-acting antiviral agents (DAAs) in blocking HCV RNA intracellular replication and the release of new virions and fit the model to in vivo data obtained from HCV-infected subjects under therapy.

Toxicological effects of copper oxide nanoparticles on the growth rate, photosynthetic pigment content, and cell morphology of the duckweed Landoltia punctata.

Recently, the application of copper oxide nanoparticles (CuO-NPs) has increased considerably, primarily in scientific and industrial fields. However, studies to assess their health risks and environmental impacts are scarce. Therefore, the present study aims to evaluate the toxicological effects of CuO-NPs on the duckweed species Landoltia punctata, which was used as a test organism. To accomplish this, duckweed was grown under standard procedures according to ISO DIS 20079 and exposed to three different concentrations of CuO-NPs (0.1, 1.0, and 10.0 g L(-1)), with one control group (without CuO-NPs). The toxicological effects were measured based on growth rate inhibition, changes in the plant's morphology, effects on ultrastructure, and alterations in photosynthetic pigments. The morphological and ultrastructural effects were evaluated by electronic, scanning and light microscopic analysis, and CuO-NPs were characterized using transmission electron microscopy (TEM), zeta potential, and superficial area methods of analysis. This analysis was performed to evaluate nanoparticle size and form in solution and sample stability. The results showed that CuO-NPs affected morphology more significantly than growth rate. L. punctata also showed the ability to remove copper ions. However, for this plant to be representative within the trophic chain, the biomagnification of effects must be assessed.

Bioabsorption of cadmium, copper and lead by the red macroalga Gelidium floridanum: physiological responses and ultrastructure features.

Heavy metals, such as lead, copper, cadmium, zinc, and nickel, are among the most common pollutants found in both industrial and urban effluents. High concentrations of these metals cause severe toxic effects, especially to organisms living in the aquatic ecosystem. Cadmium (Cd), lead (Pb) and copper (Cu) are the heavy metals most frequently implicated as environmental contaminants, and they have been shown to affect development, growth, photosynthesis and respiration, and morphological cell organization in seaweeds. This paper aimed to evaluate the effects of 50µM and 100µM of Cd, Pb and Cu on growth rates, photosynthetic pigments, biochemical parameters and ultrastructure in Gelidium floridanum. To accomplish this, apical segments of G. floridanum were individually exposed to the respective heavy metals over a period of 7 days. Plants exposed to Cd, Cu and Pb showed discoloration of thallus pigmentation, chloroplast alteration, especially degeneration of thylakoids, and decrease in photosynthetic pigments, such as chlorophyll a and phycobiliproteins, in samples treated with Cd and Cu. Moreover, cell wall thickness and the volume of plastoglobuli increased. X-ray microanalysis detected Cd, Cu and Pb absorption in the cell wall. The results indicate that Cd, Pb and Cu negatively affect metabolic performance and cell ultrastructure in G. floridanum and that Cu was more toxic than either Pb or Cd.

Changes in ultrastructure and cytochemistry of the agarophyte Gracilaria domingensis (Rhodophyta, Gracilariales) treated with cadmium.

The agarophyte macroalgae Gracilaria domingensis (Kützing) Sonder ex Dickie is widely distributed along the Brazilian coast. While this species produces agarana, it is more important in the human diet. Therefore, the present study aimed to evaluate the biological effects of cadmium on its morphology and cellular organization. To accomplish this, the effects of cadmium in apical segments of G. domingensis were examined in vitro. Over a period of 16 days, the segments were cultivated and exposed to photosynthetically active radiation (PAR) at 80 µmol photons m(-2) s(-1), with cadmium treatments in doses of 100, 200 and 300 µM. The samples were processed for light, transmission and scanning electron microscopy. Histochemical analyses included Toluidine Blue for acidic polysaccharides, Coomassie Brilliant Blue for total protein, and Periodic Acidic Schiff for neutral polysaccharides. In all cadmium treatments, cytochemical analysis showed 1) metachromatic granulation in vacuole and lenticular thickness of the cell wall, 2) a higher concentration of cytoplasmic organelles, and 3) an increase in the number of floridean starch grains. Cadmium also caused changes in the ultrastructure of cortical and subcortical cells, including increased cell wall thickness and vacuole volume, as well as the destruction of chloroplast internal organization and increased number of plastoglobuli. In addition, treated plants showed a gradual increase in surface roughness, apparently the result of cadmium absorption. Taken together, these findings strongly suggested that cadmium negatively affects the agarophyte G. domingensis, posing a threat to the vitality of this plant species as a supplement in the human diet.

Effects of natural radiation, photosynthetically active radiation and artificial ultraviolet radiation-B on the chloroplast organization and metabolism of Porphyra acanthophora var. brasiliensis (Rhodophyta, Bangiales).

We undertook a study of Porphyra acanthophora var. brasiliensis to determine its responses under ambient conditions, photosynthetically active radiation (PAR), and PAR+UVBR (ultraviolet radiation-B) treatment, focusing on changes in ultrastructure, and cytochemistry. Accordingly, control ambient samples were collected in the field, and two different treatments were performed in the laboratory. Plants were exposed to PAR at 60 µmol photons m-2 s-1 and PAR + UVBR at 0.35 W m-2 for 3 h per day during 21 days of in vitro cultivation. Confocal laser scanning microscopy analysis of the vegetative cells showed single stellate chloroplast in ambient and PAR samples, but in PAR+UVBR-exposed plants, the chloroplast showed alterations in the number and form of arms. Under PAR+UVBR treatment, the thylakoids of the chloroplasts were disrupted, and an increase in the number of plastoglobuli was observed, in addition to mitochondria, which appeared with irregular, disrupted morphology compared to ambient and PAR samples. After UVBR exposure, the formation of carpospores was also observed. Plants under ambient conditions, as well as those treated with PAR and PAR+UVBR, all showed different concentrations of enzymatic response, including glutathione peroxidase and reductase activity. In summary, the present study demonstrates that P. acanthophora var. brasiliensis shows the activation of distinct mechanisms against natural radiation, PAR and PAR+UVBR.

Automatic code generation for solvers of cardiac cellular membrane dynamics in GPUs.

The modeling of the electrical activity of the heart is of great medical and scientific interest, as it provides a way to get a better understanding of the related biophysical phenomena, allows the development of new techniques for diagnoses and serves as a platform for drug tests. However, due to the multi-scale nature of the underlying processes, the simulations of the cardiac bioelectric activity are still a computational challenge. In addition to that, the implementation of these computer models is a time consuming and error prone process. In this work we present a tool for prototyping ordinary differential equations (ODEs) in the area of cardiac modeling that aim to provide the automatic generation of high performance solvers tailored to the new hardware architecture of the graphic processing units (GPUs). The performance of these automatic solvers was evaluated using four different cardiac myocyte models. The GPU version of the solvers were between 75 and 290 times faster than the CPU versions.