scholarly journals Multiscale modeling of twitch contractions in cardiac trabeculae

2021 ◽  
Vol 153 (3) ◽  
Author(s):  
Srboljub M. Mijailovich ◽  
Momcilo Prodanovic ◽  
Corrado Poggesi ◽  
Michael A. Geeves ◽  
Michael Regnier
Keyword(s):  
Computational Models ◽  
Thick Filament ◽  
Complex Problem ◽  
Muscle Twitch ◽  
Experimental Conditions ◽  
Single Experiment ◽  
Complex Interactions ◽  
Filament Activation ◽  
Sarcomere Proteins ◽  
Insight Into

Understanding the dynamics of a cardiac muscle twitch contraction is complex because it requires a detailed understanding of the kinetic processes of the Ca2+ transient, thin-filament activation, and the myosin–actin cross-bridge chemomechanical cycle. Each of these steps has been well defined individually, but understanding how all three of the processes operate in combination is a far more complex problem. Computational modeling has the potential to provide detailed insight into each of these processes, how the dynamics of each process affect the complexity of contractile behavior, and how perturbations such as mutations in sarcomere proteins affect the complex interactions of all of these processes. The mechanisms involved in relaxation of tension during a cardiac twitch have been particularly difficult to discern due to nonhomogeneous sarcomere lengthening during relaxation. Here we use the multiscale MUSICO platform to model rat trabecular twitches. Validation of computational models is dependent on being able to simulate different experimental datasets, but there has been a paucity of data that can provide all of the required parameters in a single experiment, such as simultaneous measurements of force, intracellular Ca2+ transients, and sarcomere length dynamics. In this study, we used data from different studies collected under similar experimental conditions to provide information for all the required parameters. Our simulations established that twitches either in an isometric sarcomere or in fixed-length, multiple-sarcomere trabeculae replicate the experimental observations if models incorporate a length–tension relationship for the nonlinear series elasticity of muscle preparations and a scheme for thick-filament regulation. The thick-filament regulation assumes an off state in which myosin heads are parked onto the thick-filament backbone and are unable to interact with actin, a state analogous to the super-relaxed state. Including these two mechanisms provided simulations that accurately predict twitch contractions over a range of different conditions.

Correlational Methods for Analysis of Dance Movements

2011 ◽  
Vol 29 (supplement) ◽  
pp. 283-304 ◽  
Author(s):  
Timothy R. Brick ◽  
Steven M. Boker
Keyword(s):  
Motion Capture ◽  
Mirror Symmetry ◽  
Cross Correlation ◽  
The Other ◽  
Free Form ◽  
Motion Capture Data ◽  
Complex Interactions ◽  
Dance Movements ◽  
Time Lagged ◽  
Insight Into

Among the qualities that distinguish dance from other types of human behavior and interaction are the creation and breaking of synchrony and symmetry. The combination of symmetry and synchrony can provide complex interactions. For example, two dancers might make very different movements, slowing each time the other sped up: a mirror symmetry of velocity. Examining patterns of synchrony and symmetry can provide insight into both the artistic nature of the dance, and the nature of the perceptions and responses of the dancers. However, such complex symmetries are often difficult to quantify. This paper presents three methods – Generalized Local Linear Approximation, Time-lagged Autocorrelation, and Windowed Cross-correlation – for the exploration of symmetry and synchrony in motion-capture data as is it applied to dance and illustrate these with examples from a study of free-form dance. Combined, these techniques provide powerful tools for the examination of the structure of symmetry and synchrony in dance.

scholarly journals Ecotoxicological Assessment of Microplastics in Freshwater Sources—A Review

Water ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 56
Author(s):  
Martina Miloloža ◽  
Dajana Kučić Grgić ◽  
Tomislav Bolanča ◽  
Šime Ukić ◽  
Matija Cvetnić ◽  
...  
Keyword(s):  
Complex Problem ◽  
Living Standards ◽  
Way Of Life ◽  
Inorganic Pollutants ◽  
Ecotoxicological Assessment ◽  
Characterization Methods ◽  
Special Concern ◽  
Micro Organisms ◽  
Insight Into

High living standards and a comfortable modern way of life are related to an increased usage of various plastic products, yielding eventually the generation of an increased amount of plastic debris in the environment. A special concern is on microplastics (MPs), recently classified as contaminants of emerging concern (CECs). This review focuses on MPs’ adverse effects on the environment based on their bioactivity. Hence, the main topic covered is MPs’ ecotoxicity on various aquatic (micro)organisms such as bacteria, algae, daphnids, and fish. The cumulative toxic effects caused by MPs and adsorbed organic/inorganic pollutants are presented and critically discussed. Since MPs’ bioactivity, including ecotoxicity, is strongly influenced by their properties (e.g., types, size, shapes), the most common classification of MPs types present in freshwater are provided, along with their main characteristics. The review includes also the sources of MPs discharge in the environment and the currently available characterization methods for monitoring MPs, including identification and quantification, to obtain a broader insight into the complex problem caused by the presence of MPs in the environment.

scholarly journals Methane and Inflammation - A Review (Fight Fire with Fire)

2019 ◽  
Vol 7 (1) ◽  
Author(s):  
Marietta Zita Poles ◽  
László Juhász ◽  
Mihály Boros
Keyword(s):  
Stress Responses ◽  
Nitrosative Stress ◽  
Ischemia Reperfusion ◽  
Signalling Pathways ◽  
Experimental Conditions ◽  
Neuroprotective Effects ◽  
Oxidative And Nitrosative Stress ◽  
Carbohydrate Fermentation ◽  
Insight Into

AbstractMammalian methanogenesis is regarded as an indicator of carbohydrate fermentation by anaerobic gastrointestinal flora. Once generated by microbes or released by a non-bacterial process, methane is generally considered to be biologically inactive. However, recent studies have provided evidence for methane bioactivity in various in vivo settings. The administration of methane either in gas form or solutions has been shown to have anti-inflammatory and neuroprotective effects in an array of experimental conditions, such as ischemia/reperfusion, endotoxemia and sepsis. It has also been demonstrated that exogenous methane influences the key regulatory mechanisms and cellular signalling pathways involved in oxidative and nitrosative stress responses. This review offers an insight into the latest findings on the multi-faceted organ protective activity of exogenous methane treatments with special emphasis on its versatile effects demonstrated in sepsis models.

scholarly journals Agent Based Models of Polymicrobial Biofilms and the Microbiome—A Review

2021 ◽  
Vol 9 (2) ◽  
pp. 417
Author(s):  
Sherli Koshy-Chenthittayil ◽  
Linda Archambault ◽  
Dhananjai Senthilkumar ◽  
Reinhard Laubenbacher ◽  
Pedro Mendes ◽  
...  
Keyword(s):  
Species Interactions ◽  
Computational Models ◽  
Human Microbiome ◽  
Agent Based Modeling ◽  
Autonomous Agent ◽  
Agent Based Models ◽  
Agent Based ◽  
Complex Interactions ◽  
Mucosal Surfaces ◽  
Living Organisms

The human microbiome has been a focus of intense study in recent years. Most of the living organisms comprising the microbiome exist in the form of biofilms on mucosal surfaces lining our digestive, respiratory, and genito-urinary tracts. While health-associated microbiota contribute to digestion, provide essential nutrients, and protect us from pathogens, disturbances due to illness or medical interventions contribute to infections, some that can be fatal. Myriad biological processes influence the make-up of the microbiota, for example: growth, division, death, and production of extracellular polymers (EPS), and metabolites. Inter-species interactions include competition, inhibition, and symbiosis. Computational models are becoming widely used to better understand these interactions. Agent-based modeling is a particularly useful computational approach to implement the various complex interactions in microbial communities when appropriately combined with an experimental approach. In these models, each cell is represented as an autonomous agent with its own set of rules, with different rules for each species. In this review, we will discuss innovations in agent-based modeling of biofilms and the microbiota in the past five years from the biological and mathematical perspectives and discuss how agent-based models can be further utilized to enhance our comprehension of the complex world of polymicrobial biofilms and the microbiome.

Current trends in mathematical modeling of tumor–microenvironment interactions: a survey of tools and applications

2010 ◽  
Vol 235 (4) ◽  
pp. 411-423 ◽  
Author(s):  
Katarzyna A Rejniak ◽  
Lisa J McCawley
Keyword(s):  
Mathematical Modeling ◽  
Protein Interactions ◽  
Computational Models ◽  
Chemical Species ◽  
Tumor Stroma ◽  
Cellular Functions ◽  
Complex Interactions ◽  
Expanding Population

In its simplest description, a tumor is comprised of an expanding population of transformed cells supported by a surrounding microenvironment termed the tumor stroma. The tumor microcroenvironment has a very complex composition, including multiple types of stromal cells, a dense network of various extracellular matrix (ECM) fibers interpenetrated by the interstitial fluid and gradients of several chemical species that either are dissolved in the fluid or are bound to the ECM structure. In order to study experimentally such complex interactions between multiple players, cancer is dissected and considered at different scales of complexity, such as protein interactions, biochemical pathways, cellular functions or whole organism studies. However, the integration of information acquired from these studies into a common description is as difficult as the disease itself. Computational models of cancer can provide cancer researchers with invaluable tools that are capable of integrating the complexity into organizing principles as well as suggesting testable hypotheses. We will focus in this Minireview on mathematical models in which the whole cell is a main modeling unit. We will present a current stage of such cell-focused mathematical modeling incorporating different stromal components and their interactions with growing tumors, and discuss what modeling approaches can be undertaken to complement the in vivo and in vitro experimentation.

scholarly journals Dislocation Loop Generation Differences between Thin Films and Bulk in EFDA Pure Iron under Self-Ion Irradiation at 20 MeV

Metals ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 2000
Author(s):  
Marcelo Roldán ◽  
Fernando José Sánchez ◽  
Pilar Fernández ◽  
Christophe J. Ortiz ◽  
Adrián Gómez-Herrero ◽  
...  
Keyword(s):  
Thin Films ◽  
Computational Models ◽  
Defect Formation ◽  
Ion Irradiation ◽  
Damage Zone ◽  
High Energy ◽  
Model Material ◽  
Dislocation Nucleation ◽  
Dislocation Loops ◽  
Experimental Conditions

In the present investigation, high-energy self-ion irradiation experiments (20 MeV Fe+4) were performed on two types of pure Fe samples to evaluate the formation of dislocation loops as a function of material volume. The choice of model material, namely EFDA pure Fe, was made to emulate experiments simulated with computational models that study defect evolution. The experimental conditions were an ion fluence of 4.25 and 8.5 × 1015 ions/cm2 and an irradiation temperature of 350 and 450 °C, respectively. First, the ions pass through the samples, which are thin films of less than 100 nm. With this procedure, the formation of the accumulated damage zone, which is the peak where the ions stop, and the injection of interstitials are prevented. As a result, the effect of two free surfaces on defect formation can be studied. In the second type of experiments, the same irradiations were performed on bulk samples to compare the creation of defects in the first 100 nm depth with the microstructure found in the whole thickness of the thin films. Apparent differences were found between the thin foil irradiation and the first 100 nm in bulk specimens in terms of dislocation loops, even with a similar primary knock-on atom (PKA) spectrum. In thin films, the most loops identified in all four experimental conditions were b ±a0<100>{200} type with sizes of hundreds of nm depending on the experimental conditions, similarly to bulk samples where practically no defects were detected. These important results would help validate computational simulations about the evolution of defects in alpha iron thin films irradiated with energetic ions at large doses, which would predict the dislocation nucleation and growth.

scholarly journals Minimally Invasive Technologies for Treatment of HTS and Keloids: Fractional Laser

2020 ◽  
pp. 279-285
Author(s):  
M. Tretti Clementoni ◽  
E. Azzopardi
Keyword(s):  
Minimally Invasive ◽  
Burn Injury ◽  
State Of The Art ◽  
Skin Grafting ◽  
Complex Problem ◽  
Fractional Laser ◽  
Thickness Skin ◽  
Split Thickness Skin Grafting ◽  
Insight Into

AbstractThis chapter presents a state-of-the-art insight into the use of fractional laser for the management of this complex problem. In particular, we focus on the management of complex scars such as those occurring post-burn injury and split-thickness skin grafting.

scholarly journals Altered acrylic acid concentrations in hard and soft corals exposed to deteriorating water conditions

FACETS ◽  
2017 ◽  
Vol 2 (1) ◽  
pp. 531-544 ◽  
Author(s):  
Lori S.H. Westmoreland ◽  
Jennifer N. Niemuth ◽  
Hanna S. Gracz ◽  
Michael K. Stoskopf
Keyword(s):  
Acrylic Acid ◽  
Marine Algae ◽  
Soft Coral ◽  
Resonance Spectroscopy ◽  
Additional Insight ◽  
Experimental Conditions ◽  
Animal Metabolism ◽  
Reef Decline ◽  
Reliable Marker ◽  
Insight Into

A reliable marker of early coral response to environmental stressors can help guide decision-making to mitigate global coral reef decline by detecting problems before the development of clinically observable disease. We document the accumulation of acrylic acid in two divergent coral taxa, stony small polyp coral ( Acropora sp.) and soft coral ( Lobophytum sp.), in response to deteriorating water quality characterized by moderately increased ammonia (0.25 ppm) and phosphate (0.15 ppm) concentrations and decreased calcium (360 ppm) concentration, using nuclear magnetic resonance spectroscopy (NMR)-based metabolomic techniques. Changes in acrylic acid concentration in polyp tissues free of zooxanthellae suggest that acrylic acid could be a product of animal metabolism and not exclusively a metabolic by-product of the osmolyte dimethylsulfoniopropionate (DMSP) in marine algae or bacteria. Our findings build on previously documented depletions of acrylic acid in wild coral potentially correlated to temperature stress and provide additional insight into approaches to further characterize the nature of the metabolic accumulation of acrylic acid under controlled experimental conditions.

scholarly journals Analysis of computational codon usage models and their association with translationally slow codons

2020 ◽  
Author(s):  
Gabriel Wright ◽  
Anabel Rodriguez ◽  
Jun Li ◽  
Patricia L. Clark ◽  
Tijana Milenković ◽  
...  
Keyword(s):  
Codon Usage ◽  
Computational Models ◽  
Selective Pressure ◽  
Synonymous Codon ◽  
Ground Truth ◽  
Protein Translation ◽  
Weak Correlation ◽  
Experimental Conditions ◽  
Synonymous Codons ◽  
Genome Wide

AbstractImproved computational modeling of protein translation rates, including better prediction of where translational slowdowns along an mRNA sequence may occur, is critical for understanding co-translational folding. Because codons within a synonymous codon group are translated at different rates, many computational translation models rely on analyzing synonymous codons. Some models rely on genome-wide codon usage bias (CUB), believing that globally rare and common codons are the most informative of slow and fast translation, respectively. Others use the CUB observed only in highly expressed genes, which should be under selective pressure to be translated efficiently (and whose CUB may therefore be more indicative of translation rates). No prior work has analyzed these models for their ability to predict translational slowdowns. Here, we evaluate five models for their association with slowly translated positions as denoted by two independent ribosome footprint (RFP) count experiments from S. cerevisiae, because RFP data is often considered as a “ground truth” for translation rates across mRNA sequences. We show that all five considered models strongly associate with the RFP data and therefore have potential for estimating translational slowdowns. However, we also show that there is a weak correlation between RFP counts for the same genes originating from independent experiments, even when their experimental conditions are similar. This raises concerns about the efficacy of using current RFP experimental data for estimating translation rates and highlights a potential advantage of using computational models to understand translation rates instead.

Data Mining in Gene Expression Analysis

2008 ◽  
pp. 1643-1673
Author(s):  
Jilin Han ◽  
Le Gruenwald ◽  
Tyrrell Conway
Keyword(s):  
Gene Expression ◽  
Data Mining ◽  
Biological Information ◽  
Future Research ◽  
Gene Expression Data Analysis ◽  
Experimental Conditions ◽  
Single Experiment ◽  
Important Approach ◽  
Future Research Directions ◽  
Gene Expression Levels

The study of gene expression levels under defined experimental conditions is an important approach to understand how a living cell works. High-throughput microarray technology is a very powerful tool for simultaneously studying thousands of genes in a single experiment. This revolutionary technology results in an extensive amount of data, which raises an important question: how to extract meaningful biological information from these data? In this chapter, we survey data mining techniques that have been used for clustering, classification and association rules for gene expression data analysis. In addition, we provide a comprehensive list of currently available commercial and academic data mining software together with their features. Lastly, we suggest future research directions.

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