Error Propagation in the Simulation of Atherosclerotic Plaque Growth and the Prediction of Atherosclerotic Disease Progression

Assessments of coronary artery disease can be achieved using non-invasive computed tomography coronary angiography (CTCA). CTCA can be further used for the 3D reconstruction of the coronary arteries and the development of computational models. However, image acquisition and arterial reconstruction introduce an error which can be propagated, affecting the computational results and the accuracy of diagnostic and prognostic models. In this work, we investigate the effect of an imaging error, propagated to a diagnostic index calculated using computational modelling of blood flow and then to prognostic models based on plaque growth modelling or binary logistic predictive modelling. The analysis was performed utilizing data from 20 patients collected at two time points with interscan period of six years. The collected data includes clinical and risk factors, biological and biohumoral data, and CTCA imaging. The results demonstrated that the error propagated and may have significantly affected some of the final outcomes. The calculated propagated error seemed to be minor for shear stress, but was major for some variables of the plaque growth model. In parallel, in the current analysis SmartFFR was not considerably affected, with the limitation of only one case located into the gray zone.

Multicellular spatial model of RNA virus replication and interferon responses reveals factors controlling plaque growth dynamics

Respiratory viruses present major public health challenges, as evidenced by the 1918 Spanish Flu, the 1957 H2N2, 1968 H3N2, and 2009 H1N1 influenza pandemics, and the ongoing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. Severe RNA virus respiratory infections often correlate with high viral load and excessive inflammation. Understanding the dynamics of the innate immune response and its manifestations at the cell and tissue levels is vital to understanding the mechanisms of immunopathology and to developing strain-independent treatments. Here, we present a novel spatialized multicellular computational model of RNA virus infection and the type-I interferon-mediated antiviral response that it induces within lung epithelial cells. The model is built using the CompuCell3D multicellular simulation environment and is parameterized using data from influenza virus-infected cell cultures. Consistent with experimental observations, it exhibits either linear radial growth of viral plaques or arrested plaque growth depending on the local concentration of type I interferons. The model suggests that modifying the activity of signaling molecules in the JAK/STAT pathway or altering the ratio of the diffusion lengths of interferon and virus in the cell culture could lead to plaque growth arrest. The dependence of plaque growth arrest on diffusion lengths highlights the importance of developing validated spatial models of cytokine signaling and the need for in vitro measurement of these diffusion coefficients. Sensitivity analyses under conditions leading to continuous or arrested plaque growth found that plaque growth is more sensitive to variations of most parameters and more likely to have identifiable model parameters when conditions lead to plaque arrest. This result suggests that cytokine assay measurements may be most informative under conditions leading to arrested plaque growth. The model is easy to extend to include SARS-CoV-2-specific mechanisms or to use as a component in models linking epithelial cell signaling to systemic immune models.

Comparison of Herbal and Non-Herbal Dental Pasta Effectiveness Towards Children's Dental Plaque Index

Dental plaque is formed from biofilm that coats the surface of the teeth and is an indicator of dental and oral hygiene. One way to control plaque is by brushing your teeth. Herbal toothpaste is expected to inhibit plaque growth because it is related to the ability of herbal ingredients to inhibit microbial growth. This study aims to determine the comparison of the effectiveness of herbal and non-herbal toothpaste on reducing the plaque index in children aged 15-18 years (WHO). This type of research is experimental with pretest-postest group design on 30 respondents obtained by total sampling method and divided into 2 groups. A total of 15 respondents in the first group used herbal toothpaste and 15 respondents in the second group used non-herbal toothpaste. The plaque index is measured based on the Loe and Silness plaque index. Paired t test was used to determine the difference in dental plaque index before and after treatment. The results showed that there were significant differences in the dental plaque index on the use of herbal and non-herbal toothpaste for children aged 15-18 years. Keywords: plaque index, herbal toothpaste, non herbal toothpaste

Accumulation of saposin in dystrophic neurites is linked to impaired lysosomal functions in Alzheimer’s disease brains

Neuritic plaques in Alzheimer’s disease (AD) brains refer to β-amyloid (Aβ) plaques surrounded by dystrophic neurites (DNs), activated microglia and reactive astrocytes. Most recently, we showed that DNs form sequentially in three layers during plaque growth. Although lysosomal proteins such as LAMP1 are found in DNs, it is not clear how many and how early lysosomal proteins are involved in forming neuritic plaques. To answer this unmet question, we examined APP knock-in (APPNL-G-F), 5xFAD and APP/PS1ΔE9 mouse brains and found that the lysosomal activator proteins saposins (SAPs) and LAMP1 were accumulated to surround Aβ plaques at the earliest stage, namely the 1st layer of DNs. Noticeably, lysosomal hydrolases were not detectable in these early DNs, suggesting that DNs at this early stage likely enrich dysfunctional lysosomes. In old AD mouse brains and in the later stage of human AD brains, SAP-C+-DNs and LAMP1+-DNs were gradually reduced in concomitant with the growth of amyloid plaques. Remarkably, the observed LAMP1 immunoreactivity near plaques in aged AD mouse and human brains were actually associated with disease-associated microglia rather than neuronal sources, likely reflecting more severely impaired lysosomal functions in neurons. Western blot analyses showed increased levels of SAP-C in AD mouse brains, and Aβ oligomers induced elevated levels of SAP-C in cellular assays. The elevated protein levels of SAP-C in AD mouse brains during plaque growth potentially contributed lysosomal membrane leakage and loss of hydrolases. Together, our study indicates that lysosomal functions are impaired by being entrapped in DNs early during plaque growth, and this may viciously facilitate growth of amyloid plaques.

Study of the Influence of Plaque Growth and Hydrostatic Properties in an Atherosclerotic Artery, for the Prevention of Arterial Wall Damage: Application to Vascular Diseases

The objective of this work is to prevent damage of the arterial wall, using a theoretical model of hyperelastic, anisotropic, and dynamic behavior of the human arterial. This work is mainly focused on the properties of the hydrostatic stress and the evolution of stenosis. This work is mainly focused on the properties of the hydrostatic stress and the evolution of stenosis in order to understand the effect of the size of the plaque deposit, the loss of elasticity of the wall, and the increase in the density of the blood on the mechanical behavior of the human arterial wall. The great contribution of this work shows us that increasing the size of the plaque also increases arterial stress, and the radial growth of the plaque is very dangerous compared to the longitudinal growth. Furthermore, atherosclerosis promotes the loss of elasticity of the arterial wall and increases the density of blood mass. Indeed, all these subsequent phenomena increase arterial stress. All the results are in good agreement with the expected result of the literature and could play an important role in the diagnosis of the patient with an arterial injury. It will also help the doctor and the surgeon to make a good clinical decision and good treatment planning.

Phage susceptibility testing and infectious titer determination through wide-field lensless monitoring of phage plaque growth

The growing number of drug-resistant bacterial infections worldwide is driving renewed interest in phage therapy. Based on the use of a personalized cocktail composed of highly specific bacterial viruses, this therapy relies on a range of tests on agar media to determine the most active phage on a given bacterial target (phage susceptibility testing), or to isolate new lytic phages from an environmental sample (enrichment of phage banks). However, these culture-based techniques are still solely interpreted through direct visual detection of plaques. The main objective of this work is to investigate computer-assisted methods in order to ease and accelerate diagnosis in phage therapy but also to study phage plaque growth kinetics. For this purpose, we designed a custom wide-field lensless imaging device, which allows continuous monitoring over a very large area sensor (3.3 cm2). Here we report bacterial susceptibility to Staphylococcus aureus phage in 3 hr and estimation of infectious titer in 8 hr 20 min. These are much shorter time-to-results than the 12 to 24 hours traditionally needed, since naked eye observation and counting of phage plaques is still the most widely used technique for susceptibility testing prior to phage therapy. Moreover, the continuous monitoring of the samples enables the study of plaque growth kinetics, which enables a deeper understanding of the interaction between phage and bacteria. Finally, thanks to the 4.3 μm resolution, we detect phage-resistant bacterial microcolonies of Klebsiella pneumoniae inside the boundaries of phage plaques and thus show that our prototype is also a suitable device to track phage resistance. Lensless imaging is therefore an all-in-one method that could easily be implemented in cost-effective and compact devices in phage laboratories to help with phage therapy diagnosis.

Multicellular Spatial Model of RNA Virus Replication and Interferon Responses Reveals Factors Controlling Plaque Growth Dynamics

Respiratory viruses present major health challenges, as evidenced by the 2009 influenza pandemic and the ongoing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. Severe RNA virus respiratory infections often correlate with high viral load and excessive inflammation. Understanding the dynamics of the innate immune response and its manifestation at the cell and tissue levels are vital to understanding the mechanisms of immunopathology and developing improved, strain independent treatments. Here, we present a novel spatialized multicellular spatial computational model of two principal components of tissue infection and response: RNA virus replication and type-I interferon mediated antiviral response to infection within lung epithelial cells. The model is parameterized using data from influenza virus infected cell cultures and, consistent with experimental observations, exhibits either linear radial growth of viral plaques or arrested plaque growth depending on the local concentration of type I interferons. Modulating the phosphorylation of STAT or altering the ratio of the diffusion constants of interferon and virus in the cell culture could lead to plaque growth arrest. The dependence of arrest on diffusion constants highlights the importance of developing validated spatial models of cytokine signaling and the need for in vitro experiments to measure these diffusion constants. Sensitivity analyses were performed under conditions creating both continuous plaque growth and arrested plaque growth. Findings suggest that plaque growth and cytokine assay measurements should be collected during arrested plaque growth, as the model parameters are significantly more sensitive and more likely to be identifiable. The model’s metrics replicate experimental immunostaining imaging and titer based sampling assays. The model is easy to extend to include SARS-CoV-2-specific mechanisms as they are discovered or to include as a component linking epithelial cell signaling to systemic immune models.