scholarly journals Exploring the effect of biological delays in kinetic models of influenza within a host or cell culture

2021 ◽  
Author(s):  
Benjamin P Holder ◽  
Catherine A. A. Beauchemin
Keyword(s):  
Differential Equation ◽  
Experimental Data ◽  
Influenza Infection ◽  
Biologically Relevant ◽  
Differential Equation Models ◽  
Viral Yield ◽  
Infection Parameters ◽  
Delay Differential

Background For a typical influenza infection in vivo, viral titers over time are characterized by 1–2 days of exponential growth followed by an exponential decay. This simple dynamic can be reproduced by a broad range of mathematical models which makes model selection and the extraction of biologically-relevant infection parameters from experimental data difficult. Results We analyze in vitro experimental data from the literature, specifically that of single-cycle viral yield experiments, to narrow the range of realistic models of infection. In particular, we demonstrate the viability of using a normal or lognormal distribution for the time a cell spends in a given infection state (e.g., the time spent by a newly infected cell in the latent state before it begins to produce virus), while exposing the shortcomings of ordinary differential equation models which implicitly utilize exponential distributions and delay-differential equation models with fixed-length delays. Conclusions By fitting published viral titer data from challenge experiments in human volunteers, we show that alternative models can lead to different estimates of the key infection parameters.

scholarly journals Exploring the effect of biological delays in kinetic models of influenza within a host or cell culture

2021 ◽  
Author(s):  
Benjamin P Holder ◽  
Catherine A. A. Beauchemin
Keyword(s):  
Differential Equation ◽  
Experimental Data ◽  
Influenza Infection ◽  
Biologically Relevant ◽  
Differential Equation Models ◽  
Viral Yield ◽  
Infection Parameters ◽  
Delay Differential

Background For a typical influenza infection in vivo, viral titers over time are characterized by 1–2 days of exponential growth followed by an exponential decay. This simple dynamic can be reproduced by a broad range of mathematical models which makes model selection and the extraction of biologically-relevant infection parameters from experimental data difficult. Results We analyze in vitro experimental data from the literature, specifically that of single-cycle viral yield experiments, to narrow the range of realistic models of infection. In particular, we demonstrate the viability of using a normal or lognormal distribution for the time a cell spends in a given infection state (e.g., the time spent by a newly infected cell in the latent state before it begins to produce virus), while exposing the shortcomings of ordinary differential equation models which implicitly utilize exponential distributions and delay-differential equation models with fixed-length delays. Conclusions By fitting published viral titer data from challenge experiments in human volunteers, we show that alternative models can lead to different estimates of the key infection parameters.

scholarly journals Conifers Phytochemicals: A Valuable Forest with Therapeutic Potential

Molecules ◽  
2021 ◽  
Vol 26 (10) ◽  
pp. 3005
Author(s):  
Kanchan Bhardwaj ◽  
Ana Sanches Silva ◽  
Maria Atanassova ◽  
Rohit Sharma ◽  
Eugenie Nepovimova ◽  
...  
Keyword(s):  
Experimental Data ◽  
Potential Role ◽  
Therapeutic Potential ◽  
Fungal Infections ◽  
Cell Damage ◽  
Cancer Growth ◽  
Naturally Occurring ◽  
Antioxidant Effects

Conifers have long been recognized for their therapeutic potential in different disorders. Alkaloids, terpenes and polyphenols are the most abundant naturally occurring phytochemicals in these plants. Here, we provide an overview of the phytochemistry and related commercial products obtained from conifers. The pharmacological actions of different phytochemicals present in conifers against bacterial and fungal infections, cancer, diabetes and cardiovascular diseases are also reviewed. Data obtained from experimental and clinical studies performed to date clearly underline that such compounds exert promising antioxidant effects, being able to inhibit cell damage, cancer growth, inflammation and the onset of neurodegenerative diseases. Therefore, an attempt has been made with the intent to highlight the importance of conifer-derived extracts for pharmacological purposes, with the support of relevant in vitro and in vivo experimental data. In short, this review comprehends the information published to date related to conifers’ phytochemicals and illustrates their potential role as drugs.

scholarly journals Maximum Likelihood Inference for Univariate Delay Differential Equation Models with Multiple Delays

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-14
Author(s):  
Ahmed A. Mahmoud ◽  
Sarat C. Dass ◽  
Mohana S. Muthuvalu ◽  
Vijanth S. Asirvadam
Keyword(s):  
Differential Equation ◽  
Maximum Likelihood ◽  
Delay Differential Equation ◽  
Information Matrix ◽  
Likelihood Inference ◽  
Multiple Delays ◽  
Unknown Parameters ◽  
Differential Equation Models ◽  
Delay Differential ◽  
Initial Starting

This article presents statistical inference methodology based on maximum likelihoods for delay differential equation models in the univariate setting. Maximum likelihood inference is obtained for single and multiple unknown delay parameters as well as other parameters of interest that govern the trajectories of the delay differential equation models. The maximum likelihood estimator is obtained based on adaptive grid and Newton-Raphson algorithms. Our methodology estimates correctly the delay parameters as well as other unknown parameters (such as the initial starting values) of the dynamical system based on simulation data. We also develop methodology to compute the information matrix and confidence intervals for all unknown parameters based on the likelihood inferential framework. We present three illustrative examples related to biological systems. The computations have been carried out with help of mathematical software: MATLAB® 8.0 R2014b.

scholarly journals Redox Polymers for Tissue Engineering

2021 ◽  
Vol 3 ◽  
Author(s):  
Binbin Z. Molino ◽  
Junji Fukuda ◽  
Paul J. Molino ◽  
Gordon G. Wallace
Keyword(s):  
Tissue Engineering ◽  
Conducting Polymers ◽  
Polymeric Materials ◽  
Redox Polymers ◽  
Design Synthesis ◽  
Materials Development ◽  
Biologically Relevant ◽  
Fundamental Properties

This review will focus on the targeted design, synthesis and application of redox polymers for use in regenerative medicine and tissue engineering. We define redox polymers to encompass a variety of polymeric materials, from the multifunctional conjugated conducting polymers to graphene and its derivatives, and have been adopted for use in the engineering of several types of stimulus responsive tissues. We will review the fundamental properties of organic conducting polymers (OCPs) and graphene, and how their properties are being tailored to enhance material - biological interfacing. We will highlight the recent development of high-resolution 3D fabrication processes suitable for biomaterials, and how the fabrication of intricate scaffolds at biologically relevant scales is providing exciting opportunities for the application of redox polymers for both in-vitro and in-vivo tissue engineering. We will discuss the application of OCPs in the controlled delivery of bioactive compounds, and the electrical and mechanical stimulation of cells to drive behaviour and processes towards the generation of specific functional tissue. We will highlight the relatively recent advances in the use of graphene and the exploitation of its physicochemical and electrical properties in tissue engineering. Finally, we will look forward at the future of organic conductors in tissue engineering applications, and where the combination of materials development and fabrication processes will next unite to provide future breakthroughs.

scholarly journals Phospholipid and cation activation of chimaeric choline/ethanolamine phosphotransferases

1996 ◽  
Vol 313 (3) ◽  
pp. 729-735 ◽  
Author(s):  
Christopher R. McMASTER ◽  
Sherry C. MORASH ◽  
Robert M. BELL
Keyword(s):  
Tertiary Structure ◽  
Feedback Inhibition ◽  
Head Group ◽  
Biologically Relevant ◽  
Activation Domains ◽  
Cation Activation ◽  
Absolute Requirement ◽  
Insight Into

The Saccharomyces cerevisiae CPT1 and EPT1 genes encode for a cholinephosphotransferase (CPT) and choline/ ethanolaminephosphotransferase, respectively. Both Cpt1p and Ept1p activities display an absolute requirement for cations and phospholipids. A mixed-micelle assay was employed to determine cation and lipid activators of parental and chimaeric Cpt1p/ Ept1p enzymes to gain insight into their mechanism(s) of activation. Mg2+, Mn2+ and Co2+ were the only cations capable of activating Cpt1p and Ept1p in vitro. Kinetic data revealed that only Mg2+ is present in appropriate amounts to activate CPT activity in vivo. The two enzymes displayed distinct activation profiles on the basis of their relative affinities for Mg2+, Mn2+ and Co2+. This allowed the use of chimaeric enzymes to determine the mechanism of cation activation. Cations do not activate Cpt1p or Ept1p by complexing with the substrate, CDP-choline, but instead bind to disparate regions within the enzymes themselves. Cpt1p and Ept1p also displayed distinct phospholipid activation profiles. Phospholipid activation required a phosphate and/or glycero-phosphoester linkage, with the phospho-head group moiety positioned at the surface of the micelle. Assays with parental and chimaeric Cpt1p/Ept1p constructs revealed that the phospholipid binding/activation domains are not located within linear segments of the protein, but instead are contained within distinct and separate regions of the proteins that require an intact tertiary structure for formation. Phosphatidylcholine (and its structural analogue sphingomyelin) were the best lipid activators of Cpt1p, the main biologically relevant CPT activity in S. cerevisiae. Hence CPT displays product activation. Because phosphatidylcholine is an efficient activator of CPT activity (and hence Cpt1p is not subject to feedback inhibition by its product), Cpt1p is incapable of functioning as a direct monitor of membrane phosphatidylcholine composition.

Biocontrol properties of some agricultural waste extracts on three nematode species in in vitro and in vivo conditions

Nematology ◽  
2019 ◽  
Vol 21 (8) ◽  
pp. 837-846
Author(s):  
Ali Roshan-Bakhsh ◽  
Ebrahim Pourjam ◽  
Mahdi Ayyari ◽  
Majid Pedram
Keyword(s):  
Faba Bean ◽  
Agricultural Waste ◽  
Ethanolic Extract ◽  
Nematode Species ◽  
Nematicidal Activity ◽  
Leaf Extracts ◽  
Tomato Root ◽  
Infection Parameters

Summary Extracts of nine agricultural wastes prepared with five different solvents were assessed for their potential nematicidal activity against three nematode species, Aphelenchus avenae, Meloidogyne incognita and Pratylenchus neglectus, in in vitro condition. The 50% v/v hydro-ethanolic extracts showed the highest performance for two tested plant wastes of cabbage leaves and faba bean pods. These two extracts were tested on nematodes in three different concentrations. The highest in vitro nematistatic activity was recorded for 3000 and 1500 ppm of cabbage leaf extracts by 100% paralysis of all three nematode species after 48 h, and the highest nematicidal activity was recorded for the above-mentioned extract by 25-100% mortality depending on nematode species and extract concentration. A 14-94% mortality was recorded for all three species of nematodes after treatment with faba bean pod hydro-ethanolic extract in in vitro conditions. Hatching inhibition and repellent activity of cabbage leaf and faba bean pod extracts were observed in P. neglectus and M. incognita. In vivo assays confirmed the in vitro results when both of the extracts showed moderate to high inhibition of nematode population development and nematode infection parameters on tomato root system in pot experiments.

Human Mn-superoxide dismutase inactivation by peroxynitrite: a paradigm of metal-catalyzed tyrosine nitration in vitro and in vivo

Metallomics ◽  
2018 ◽  
Vol 10 (5) ◽  
pp. 679-695 ◽  
Author(s):  
Verónica Demicheli ◽  
Diego M. Moreno ◽  
Rafael Radi
Keyword(s):  
Superoxide Dismutase ◽  
Active Site ◽  
Enzyme Inactivation ◽  
Tyrosine Nitration ◽  
Post Translational Modification ◽  
Biologically Relevant ◽  
Metal Catalyzed

Nitration of human MnSOD at active site Tyr34 represents a biologically-relevant oxidative post-translational modification that causes enzyme inactivation.

scholarly journals The Role of Dimensionality in Understanding Granuloma Formation

Computation ◽  
2018 ◽  
Vol 6 (4) ◽  
pp. 58 ◽  
Author(s):  
Simeone Marino ◽  
Caitlin Hult ◽  
Paul Wolberg ◽  
Jennifer Linderman ◽  
Denise Kirschner
Keyword(s):  
Experimental Data ◽  
Large Scale ◽  
Bacterial Load ◽  
Computational Cost ◽  
Granuloma Formation ◽  
In Silico Studies ◽  
Cellular Recruitment ◽  
2D And 3D

Within the first 2–3 months of a Mycobacterium tuberculosis (Mtb) infection, 2–4 mm spherical structures called granulomas develop in the lungs of the infected hosts. These are the hallmark of tuberculosis (TB) infection in humans and non-human primates. A cascade of immunological events occurs in the first 3 months of granuloma formation that likely shapes the outcome of the infection. Understanding the main mechanisms driving granuloma development and function is key to generating treatments and vaccines. In vitro, in vivo, and in silico studies have been performed in the past decades to address the complexity of granuloma dynamics. This study builds on our previous 2D spatio-temporal hybrid computational model of granuloma formation in TB (GranSim) and presents for the first time a more realistic 3D implementation. We use uncertainty and sensitivity analysis techniques to calibrate the new 3D resolution to non-human primate (NHP) experimental data on bacterial levels per granuloma during the first 100 days post infection. Due to the large computational cost associated with running a 3D agent-based model, our major goal is to assess to what extent 2D and 3D simulations differ in predictions for TB granulomas and what can be learned in the context of 3D that is missed in 2D. Our findings suggest that in terms of major mechanisms driving bacterial burden, 2D and 3D models return very similar results. For example, Mtb growth rates and molecular regulation mechanisms are very important both in 2D and 3D, as are cellular movement and modulation of cell recruitment. The main difference we found was that the 3D model is less affected by crowding when cellular recruitment and movement of cells are increased. Overall, we conclude that the use of a 2D resolution in GranSim is warranted when large scale pilot runs are to be performed and if the goal is to determine major mechanisms driving infection outcome (e.g., bacterial load). To comprehensively compare the roles of model dimensionality, further tests and experimental data will be needed to expand our conclusions to molecular scale dynamics and multi-scale resolutions.

Sign in / Sign up

Export Citation Format

Share Document