scholarly journals Allometric Scaling of physiologically-relevant organoids

2019 ◽  
Author(s):  
Chiara Magliaro ◽  
Andrea Rinaldo ◽  
Arti Ahluwalia
Keyword(s):  
Computational Models ◽  
Allometric Scaling ◽  
Power Scaling ◽  
Delivery Methods ◽  
Allometric Exponent ◽  
Metabolic Scaling ◽  
Mature Brain ◽  
Using Data ◽  
Mass Dependent

AbstractThe functional and structural resemblance of organoids to mammalian organs suggests that they might follow the same allometric scaling rules. However, despite their remarkable likeness to downscaled organs, non-luminal organoids are often reported to possess necrotic cores due to oxygen diffusion limits. To assess their potential as physiologically relevant in vitro models, we determined the range of organoid masses in which quarter power scaling as well as a minimum threshold oxygen concentration is maintained. Using data on brain organoids as a reference, computational models were developed to estimate oxygen consumption and diffusion at different stages of growth. The results show that mature brain (or other non-luminal) organoids generated using current protocols must lie within a narrow range of masses to maintain both quarter power scaling and viable cores. However, micro-fluidic oxygen delivery methods could be designed to widen this range, ensuring a minimum viable oxygen threshold throughout the constructs and mass dependent metabolic scaling. The results provide new insights into the significance of the allometric exponent in systems without a resource-supplying network and may be used to guide the design of more predictive and physiologically relevant in vitro models, providing an effective alternative to animals in research.

Electrophysiological characterization and computational models of HVC neurons in the zebra finch

2013 ◽  
Vol 110 (5) ◽  
pp. 1227-1245 ◽  
Author(s):  
Arij Daou ◽  
Matthew T. Ross ◽  
Frank Johnson ◽  
Richard L. Hyson ◽  
Richard Bertram
Keyword(s):  
Computational Models ◽  
Premotor Cortex ◽  
Brain Slices ◽  
Ionic Currents ◽  
Proper Name ◽  
Using Data ◽  
Electrophysiological Characterization

The nucleus HVC (proper name) within the avian analog of mammal premotor cortex produces stereotyped instructions through the motor pathway leading to precise, learned vocalization by songbirds. Electrophysiological characterization of component HVC neurons is an important requirement in building a model to understand HVC function. The HVC contains three neural populations: neurons that project to the RA (robust nucleus of arcopallium), neurons that project to Area X (of the avian basal ganglia), and interneurons. These three populations are interconnected with specific patterns of excitatory and inhibitory connectivity, and they fire with characteristic patterns both in vivo and in vitro. We performed whole cell current-clamp recordings on HVC neurons within brain slices to examine their intrinsic firing properties and determine which ionic currents are responsible for their characteristic firing patterns. We also developed conductance-based models for the different neurons and calibrated the models using data from our brain slice work. These models were then used to generate predictions about the makeup of the ionic currents that are responsible for the different responses to stimuli. These predictions were then tested and verified in the slice using pharmacological manipulations. The model and the slice work highlight roles of a hyperpolarization-activated inward current ( Ih), a low-threshold T-type Ca2+ current ( ICa-T), an A-type K+ current ( IA), a Ca2+-activated K+ current ( ISK), and a Na+-dependent K+ current ( IKNa) in driving the characteristic neural patterns observed in the three HVC neuronal populations. The result is an improved characterization of the HVC neurons responsible for song production in the songbird.

scholarly journals Effect of Pulsatility on the Transport of Thrombin in an Idealized Cerebral Aneurysm Geometry

Symmetry ◽  
2022 ◽  
Vol 14 (1) ◽  
pp. 133
Author(s):  
Struan Hume ◽  
Jean-Marc Ilunga Tshimanga ◽  
Patrick Geoghegan ◽  
Arnaud G. Malan ◽  
Wei Hua Ho ◽  
...  
Keyword(s):  
Computational Model ◽  
Steady Flow ◽  
Cerebral Aneurysm ◽  
Computational Models ◽  
Cerebral Aneurysms ◽  
Scalar Function ◽  
Aneurysm Wall ◽  
Aneurysm Thrombosis ◽  
Using Data

Computational models of cerebral aneurysm thrombosis are designed for use in research and clinical applications. A steady flow assumption is applied in many of these models. To explore the accuracy of this assumption a pulsatile-flow thrombin-transport computational fluid dynamics (CFD) model, which uses a symmetrical idealized aneurysm geometry, was developed. First, a steady-flow computational model was developed and validated using data from an in vitro experiment, based on particle image velocimetry (PIV). The experimental data revealed an asymmetric flow pattern in the aneurysm. The validated computational model was subsequently altered to incorporate pulsatility, by applying a data-derived flow function at the inlet boundary. For both the steady and pulsatile computational models, a scalar function simulating thrombin generation was applied at the aneurysm wall. To determine the influence of pulsatility on thrombin transport, the outputs of the steady model were compared to the outputs of the pulsatile model. The comparison revealed that in the pulsatile case, an average of 10.2% less thrombin accumulates within the aneurysm than the steady case for any given time, due to periodic losses of a significant amount of thrombin-concentrated blood from the aneurysm into the parent vessel’s bloodstream. These findings demonstrate that pulsatility may change clotting outcomes in cerebral aneurysms.

Total weak acid concentration and effective dissociation constant of nonvolatile buffers in human plasma

2001 ◽  
Vol 91 (3) ◽  
pp. 1364-1371 ◽  
Author(s):  
Peter D. Constable
Keyword(s):  
Dissociation Constant ◽  
Human Plasma ◽  
Total Concentration ◽  
Weak Acid ◽  
Strong Ion Difference ◽  
Acid Base ◽  
Horse Plasma ◽  
Using Data ◽  
Species Specific

The strong ion approach provides a quantitative physicochemical method for describing the mechanism for an acid-base disturbance. The approach requires species-specific values for the total concentration of plasma nonvolatile buffers (Atot) and the effective dissociation constant for plasma nonvolatile buffers ( K a), but these values have not been determined for human plasma. Accordingly, the purpose of this study was to calculate accurate Atot and K a values using data obtained from in vitro strong ion titration and CO2tonometry. The calculated values for Atot (24.1 mmol/l) and K a (1.05 × 10−7) were significantly ( P < 0.05) different from the experimentally determined values for horse plasma and differed from the empirically assumed values for human plasma (Atot = 19.0 meq/l and K a = 3.0 × 10−7). The derivatives of pH with respect to the three independent variables [strong ion difference (SID), Pco 2, and Atot] of the strong ion approach were calculated as follows: [Formula: see text] [Formula: see text], [Formula: see text]where S is solubility of CO2 in plasma. The derivatives provide a useful method for calculating the effect of independent changes in SID+, Pco 2, and Atot on plasma pH. The calculated values for Atot and K a should facilitate application of the strong ion approach to acid-base disturbances in humans.

scholarly journals Biological scaling in green algae: the role of cell size and geometry

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Helena Bestová ◽  
Jules Segrestin ◽  
Klaus von Schwartzenberg ◽  
Pavel Škaloud ◽  
Thomas Lenormand ◽  
...  
Keyword(s):  
Growth Rate ◽  
Population Growth ◽  
Population Growth Rate ◽  
Internal Diffusion ◽  
Scaling Exponent ◽  
Power Scaling ◽  
Nutrient Distribution ◽  
Metabolic Scaling ◽  
Key Factor ◽  
Size And Morphology

AbstractThe Metabolic Scaling Theory (MST), hypothesizes limitations of resource-transport networks in organisms and predicts their optimization into fractal-like structures. As a result, the relationship between population growth rate and body size should follow a cross-species universal quarter-power scaling. However, the universality of metabolic scaling has been challenged, particularly across transitions from bacteria to protists to multicellulars. The population growth rate of unicellulars should be constrained by external diffusion, ruling nutrient uptake, and internal diffusion, operating nutrient distribution. Both constraints intensify with increasing size possibly leading to shifting in the scaling exponent. We focused on unicellular algae Micrasterias. Large size and fractal-like morphology make this species a transitional group between unicellular and multicellular organisms in the evolution of allometry. We tested MST predictions using measurements of growth rate, size, and morphology-related traits. We showed that growth scaling of Micrasterias follows MST predictions, reflecting constraints by internal diffusion transport. Cell fractality and density decrease led to a proportional increase in surface area with body mass relaxing external constraints. Complex allometric optimization enables to maintain quarter-power scaling of population growth rate even with a large unicellular plan. Overall, our findings support fractality as a key factor in the evolution of biological scaling.

scholarly journals Enhanced Piezoelectric Fibered Extracellular Matrix to Promote Cardiomyocyte Maturation and Tissue Formation: A 3D Computational Model

Biology ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 135
Author(s):  
Pau Urdeitx ◽  
Mohamed H. Doweidar
Keyword(s):  
Extracellular Matrix ◽  
Cell Migration ◽  
Computational Models ◽  
Cell Junctions ◽  
Tissue Formation ◽  
Cardiac Muscle Cells ◽  
Cell Processes ◽  
Electrical Stimuli ◽  
Cell Cell

Mechanical and electrical stimuli play a key role in tissue formation, guiding cell processes such as cell migration, differentiation, maturation, and apoptosis. Monitoring and controlling these stimuli on in vitro experiments is not straightforward due to the coupling of these different stimuli. In addition, active and reciprocal cell–cell and cell–extracellular matrix interactions are essential to be considered during formation of complex tissue such as myocardial tissue. In this sense, computational models can offer new perspectives and key information on the cell microenvironment. Thus, we present a new computational 3D model, based on the Finite Element Method, where a complex extracellular matrix with piezoelectric properties interacts with cardiac muscle cells during the first steps of tissue formation. This model includes collective behavior and cell processes such as cell migration, maturation, differentiation, proliferation, and apoptosis. The model has employed to study the initial stages of in vitro cardiac aggregate formation, considering cell–cell junctions, under different extracellular matrix configurations. Three different cases have been purposed to evaluate cell behavior in fibered, mechanically stimulated fibered, and mechanically stimulated piezoelectric fibered extra-cellular matrix. In this last case, the cells are guided by the coupling of mechanical and electrical stimuli. Accordingly, the obtained results show the formation of more elongated groups and enhancement in cell proliferation.

scholarly journals Model-Informed Optimization of a Pediatric Clinical Pharmacokinetic Trial of a New Spironolactone Liquid Formulation

Pharmaceutics ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 849
Author(s):  
Manasa Tatipalli ◽  
Vijay Kumar Siripuram ◽  
Tao Long ◽  
Diana Shuster ◽  
Galina Bernstein ◽  
...  
Keyword(s):  
Pharmacokinetic Model ◽  
Allometric Scaling ◽  
Pediatric Patients ◽  
Reference Product ◽  
Population Pharmacokinetic ◽  
Liquid Formulation ◽  
Sampling Schemes ◽  
Quantitative Pharmacology ◽  
Using Data ◽  
Drug Pharmacokinetics

Quantitative pharmacology brings important advantages in the design and conduct of pediatric clinical trials. Herein, we demonstrate the application of a model-based approach to select doses and pharmacokinetic sampling scenarios for the clinical evaluation of a novel oral suspension of spironolactone in pediatric patients with edema. A population pharmacokinetic model was developed and qualified for spironolactone and its metabolite, canrenone, using data from adults and bridged to pediatrics (2 to <17 years old) using allometric scaling. The model was then used via simulation to explore different dosing and sampling scenarios. Doses of 0.5 and 1.5 mg/kg led to target exposures (i.e., similar to 25 and 100 mg of the reference product in adults) in all the reference pediatric ages (i.e., 2, 6, 12 and 17 years). Additionally, two different sampling scenarios were delineated to accommodate patients into sparse sampling schemes informative to characterize drug pharmacokinetics while minimizing phlebotomy and burden to participating children.

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 Mending a broken heart: In vitro, in vivo and in silico models of congenital heart disease

2021 ◽  
Vol 14 (3) ◽  
pp. dmm047522
Author(s):  
Abdul Jalil Rufaihah ◽  
Ching Kit Chen ◽  
Choon Hwai Yap ◽  
Citra N. Z. Mattar
Keyword(s):  
Congenital Heart Disease ◽  
Heart Disease ◽  
Congenital Heart ◽  
Computational Models ◽  
Developing Heart ◽  
Heterogenous Group ◽  
In Silico Models ◽  
Large Animals

ABSTRACTBirth defects contribute to ∼0.3% of global infant mortality in the first month of life, and congenital heart disease (CHD) is the most common birth defect among newborns worldwide. Despite the significant impact on human health, most treatments available for this heterogenous group of disorders are palliative at best. For this reason, the complex process of cardiogenesis, governed by multiple interlinked and dose-dependent pathways, is well investigated. Tissue, animal and, more recently, computerized models of the developing heart have facilitated important discoveries that are helping us to understand the genetic, epigenetic and mechanobiological contributors to CHD aetiology. In this Review, we discuss the strengths and limitations of different models of normal and abnormal cardiogenesis, ranging from single-cell systems and 3D cardiac organoids, to small and large animals and organ-level computational models. These investigative tools have revealed a diversity of pathogenic mechanisms that contribute to CHD, including genetic pathways, epigenetic regulators and shear wall stresses, paving the way for new strategies for screening and non-surgical treatment of CHD. As we discuss in this Review, one of the most-valuable advances in recent years has been the creation of highly personalized platforms with which to study individual diseases in clinically relevant settings.

scholarly journals Computational Models Using Multiple Machine Learning Algorithms for Predicting Drug Hepatotoxicity with the DILIrank Dataset

2020 ◽  
Author(s):  
Robert Ancuceanu ◽  
Marilena Viorica Hovanet ◽  
Adriana Iuliana Anghel ◽  
Florentina Furtunescu ◽  
Monica Neagu ◽  
...  
Keyword(s):  
Machine Learning ◽  
Liver Injury ◽  
Computational Models ◽  
Liver Toxicity ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Drug Induced ◽  
Reference Drug ◽  
Drug Induced Liver Injury

Drug induced liver injury (DILI) remains one of the challenges in the safety profile of both authorized drugs and candidate drugs and predicting hepatotoxicity from the chemical structure of a substance remains a challenge worth pursuing, being also coherent with the current tendency for replacing non-clinical tests with in vitro or in silico alternatives. In 2016 a group of researchers from FDA published an improved annotated list of drugs with respect to their DILI risk, constituting &ldquo;the largest reference drug list ranked by the risk for developing drug-induced liver injury in humans&rdquo;, DILIrank. This paper is one of the few attempting to predict liver toxicity using the DILIrank dataset. Molecular descriptors were computed with the Dragon 7.0 software, and a variety of feature selection and machine learning algorithms were implemented in the R computing environment. Nested (double) cross-validation was used to externally validate the models selected. A number of 78 models with reasonable performance have been selected and stacked through several approaches, including the building of multiple meta-models. The performance of the stacked models was slightly superior to other models published. The models were applied in a virtual screening exercise on over 100,000 compounds from the ZINC database and about 20% of them were predicted to be non-hepatotoxic.

scholarly journals METABOLIC SCALING REGULARITY IN AQUATIC ECOSYSTEMS

2012 ◽  
Vol 27 (2) ◽  
pp. 13
Author(s):  
L. A. Salcido -Guevara ◽  
F. Arreguín -Sánchez ◽  
L. Palmeri ◽  
A. Barausse
Keyword(s):  
Aquatic Ecosystems ◽  
Major Axis ◽  
Ecosystem Metabolism ◽  
Power Scaling ◽  
Metabolic Scaling ◽  
Relevant Role ◽  
Geographic Differences ◽  
Reduced Major Axis ◽  
Distribución Geográfica ◽  
Trophic Models

We tested the hypothesis that ecosystem metabolism follows a quarter power scaling relation, analogous to organisms. Logarithm of Biomass/Production (B/P) to Trophic Level (TL) relationship was estimated to 98 trophic models of aquatic ecosystems. A normal distribution of the slopes gives a modal value of 0.64, which was significantly different of the theoretical value of 0.75 (p0.05). We also tested for error in both variables, Log (B/P) and TL, through a Reduced Major Axis regression with similar results, with a modal value of 0.756 (p>0.05). We also explored a geographic distribution showing no significant relation (p>0.05) to latitude and between different regions of the world. We conclude that: a) ecosystem metabolism follows the quarter-power scaling rule; b) transfer efficiency between TL plays a relevant role characterizing local attributes to ecosystem metabolism; and c) there is neither latitudinal nor geographic differences. These findings confirm the existence of a metabolic scaling regularity in aquatic ecosystems. Regularidad del escalamiento metabólico en ecosistemas acuáticos Se contrastó la hipótesis de que el metabolismo de un ecosistema sigue una relación de escalamiento análoga a la existente en los organismos. La relación entre el logaritmo de la razón Producción/Biomasa (B/P) y el nivel trófico (TL) se estimó para 98 modelos tróficos de los ecosistemas acuáticos. Una distribución normal de las pendientes de esta relación produjo un valor modal de 0.64 que es significativamente diferente del valor teórico de 0.75 (p0.05) similar al teórico esperado. También se contrastó la hipótesis de existencia de error en ambas variables, logaritmo (B/P) y TL, a través de la técnica de regresión denominada “Reduced Major Axis”, con resultados similares según el valor modal de 0.756, sin diferencia estadísticamente significativa (p>0.05) del valor teórico. Se exploró la existencia de algún patrón en la distribución geográfica, sin obtenerse relación significativa (p>0.05) con la latitud, o con diferentes regiones del mundo. Las conclusiones son: a) el metabolismo del ecosistema sigue la regla de escalamiento metabólico de 3/4; b) la eficiencia de la transferencia entre TL desempeña un papel relevante, representando los atributos locales del metabolismo del ecosistema; c) no hay una diferencias latitudinal o geográfica. Estos resultados confirman la existencia de una regularidad en el escalamiento metabólico en ecosistemas acuáticos.

Sign in / Sign up

Export Citation Format

Share Document