scholarly journals Quantification of the effects of antibodies on the extra- and intracellular dynamics of Salmonella enterica

2013 ◽  
Vol 10 (79) ◽  
pp. 20120866 ◽  
Author(s):  
Olivier Restif ◽  
Yun S. Goh ◽  
Matthieu Palayret ◽  
Andrew J. Grant ◽  
Trevelyan J. McKinley ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Maximum Likelihood ◽  
Fluorescence Microscopy ◽  
Relative Efficiency ◽  
Igg Subclasses ◽  
Model Parameters ◽  
Exact Role ◽  
Factors Affecting ◽  
Potential Factors

Antibodies are known to be essential in controlling Salmonella infection, but their exact role remains elusive. We recently developed an in vitro model to investigate the relative efficiency of four different human immunoglobulin G (IgG) subclasses in modulating the interaction of the bacteria with human phagocytes. Our results indicated that different IgG subclasses affect the efficacy of Salmonella uptake by human phagocytes. In this study, we aim to quantify the effects of IgG on intracellular dynamics of infection by combining distributions of bacterial numbers per phagocyte observed by fluorescence microscopy with a mathematical model that simulates the in vitro dynamics. We then use maximum likelihood to estimate the model parameters and compare them across IgG subclasses. The analysis reveals heterogeneity in the division rates of the bacteria, strongly suggesting that a subpopulation of intracellular Salmonella , while visible under the microscope, is not dividing. Clear differences in the observed distributions among the four IgG subclasses are best explained by variations in phagocytosis and intracellular dynamics. We propose and compare potential factors affecting the replication and death of bacteria within phagocytes, and we discuss these results in the light of recent findings on dormancy of Salmonella .

A Cadaverically Evaluated Dynamic FEM Model of Closed-Chain TKR Mechanics

2009 ◽  
Vol 131 (5) ◽  
Author(s):  
Joel L. Lanovaz ◽  
Randy E. Ellis
Keyword(s):  
Model Performance ◽  
Element Model ◽  
Joint Kinematics ◽  
Contact Friction ◽  
Model Parameters ◽  
Factors Affecting ◽  
Reaction Forces ◽  
Total Knee

Knowledge of the behavior and mechanics of a total knee replacement (TKR) in an in vivo environment is key to optimizing the functional outcomes of the implant procedure. Computational modeling has shown to be an important tool for investigating biomechanical variables that are difficult to address experimentally. To assist in examining TKR mechanics, a dynamic finite-element model of a TKR is presented. The objective of the study was to develop and evaluate a model that could simulate full knee motion using a physiologically consistent quadriceps action, without prescribed joint kinematics. The model included tibiofemoral (TFJs) and patellofemoral joints (PFJs), six major ligament bundles and was driven by a uni-axial representation of a quadricep muscle. An initial parameter screening analysis was performed to assess the relative importance of 31 different model parameters. This analysis showed that ligament insertion location and initial ligament strain were significant factors affecting simulated joint kinematics and loading, with the contact friction coefficient playing a lesser role and ligament stiffness having little effect. The model was then used to simulate in vitro experiments utilizing a flexed-knee-stance testing rig. General model performance was assessed by comparing simulation results with experimentally measured kinematics and tibial reaction forces collected from two implanted specimens. The simulations were able to reproduce experimental differences observed between the test specimens and were able to accurately predict trends seen in the tibial reaction loads. The simulated kinematics of the TFJ and PFJ were less consistent when compared with experimental data but still reproduced many trends.

scholarly journals Mathematical modeling quantifies ERK-activity in response to inhibition of the BRAFV600E-MEK-ERK cascade

2021 ◽  
Author(s):  
Sara Hamis ◽  
Yury Kapelyukh ◽  
Aileen McLaren ◽  
Colin J. Henderson ◽  
C. Roland Wolf ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Drug Resistance ◽  
Chemical Reactions ◽  
Molecular Mechanisms ◽  
Braf Inhibitor ◽  
Mass Action ◽  
Model Parameters ◽  
Mass Action Kinetics ◽  
Erk Activity

AbstractSimultaneous inhibition of multiple components of the BRAF-MEK-ERK cascade (vertical inhibition) has become a standard of care for treating BRAF-mutant melanoma. However, the molecular mechanisms of how vertical inhibition synergistically suppress intracellular ERK activity, and as a consequence cell proliferation, are yet to be fully elucidated.In this study, we develop a mechanistic mathematical model that describes how the mutant BRAF-inhibitor, dabrafenib, and the MEK-inhibitor, trametinib, affect signaling through the BRAFV600E-MEK-ERK cascade. We formulate a system of chemical reactions that describes cascade signaling dynamics and, using mass action kinetics, the chemical reactions are re-expressed as ordinary differential equations. Using model parameters obtained from in vitro data available in the literature, these equations are solved numerically to obtain the temporal evolution of the concentrations of the components in the signaling cascade.Our mathematical model provides a quantitative method to compute how dabrafenib and trametinib can be used in combination to synergistically inhibit ERK activity in BRAFV600E mutant melanoma cells. This work elucidates molecular mechanisms of vertical inhibition of the BRAFV600E-MEK-ERK cascade and delineates how elevated cellular BRAF concentrations generate drug resistance to dabrafenib and trametinib. In addition, the computational simulations suggest that elevated ATP levels could be a factor in drug resistance to dabrafenib. The mathematical model that is developed in this study will have generic application in the improved design of anticancer combination therapies that target BRAF-MEK-ERK pathways.

scholarly journals Lung Cancer Radiotherapy: Simulation and Analysis Based on a Multi-component Mathematical Model

2020 ◽  
Author(s):  
Wen-song Hong ◽  
Shun-guan Wang ◽  
Gang-qing Zhang
Keyword(s):  
Lung Cancer ◽  
Mathematical Model ◽  
Cancer Growth ◽  
Model Parameters ◽  
Fractionated Radiotherapy ◽  
Analysis And Evaluation ◽  
Basic Work ◽  
Near Future ◽  
Radiotherapy Treatment

Abstract Background: Lung cancer has been one of the most deadly illnesses all over the world and radiotherapy can be an effective approach for treating lung cancer. Now, mathematical model has been extended to many biomedical fields to give a hand for analysis, evaluation, prediction and optimization. Methods: In this paper, we propose a multi-component mathematical model for simulating the lung cancer growth as well as radiotherapy treatment for lung cancer. The model is digitalized and coded for computer simulation and the model parameters are fitted with many research and clinical data to provide accordant results along with the growth of lung cancer cells in vitro. Results: Some typical radiotherapy plans such as stereotactic body radiotherapy, conventional fractional radiotherapy and accelerated hypo-fractionated radiotherapy are simulated, analyzed and discussed. The results show that our mathematical model can perform the basic work for analysis and evaluation of the radiotherapy plan. Conclusion: It will be expected that in the near future, mathematical model will be a valuable tool for optimization in personalized medical treatment.

scholarly journals Understanding the drug delivery through nails: a comprehensive review

2021 ◽  
Vol 11 (4) ◽  
pp. 116-131
Author(s):  
BEDANTA BHATTACHARJEE ◽  
NIKITA DEY ◽  
DHUNUSMITA BARMAN ◽  
ARKA KARMAKAR ◽  
NASIMA AHMED
Keyword(s):  
Mathematical Model ◽  
Treatment Time ◽  
Nail Plate ◽  
Diagnostic Procedures ◽  
In Vitro Models ◽  
Permeation Enhancers ◽  
Factors Affecting ◽  
Nail Infection

The nail unit is the largest cutaneous musculo-skeletal appendage. The management of nail disorders is an onerous task owing to the disease manifestations and anatomical structure of the nail plate. The topical treatment of nail infections/disorders has been a centerpiece of nail research in the past few decades as it offers a much safer and focused alternative to conventional oral therapy. However, transungual delivery had its challenges. This necessitated a lookout for novel approaches that enhanced treatment efficacy and reduced treatment time. Moreover, curing the nail condition using topical delivery has been challenging due to the lack of a validated animal model to determine the efficacy of the formulation and to establish a mathematical model that can help in predicting the desirable attributes of the formulation and permeation of various molecules through the nail plate. This review is based on publications retrieved by a selective search in PubMed. The purpose of this review is to provide an overview of nail anatomy and its disorders, factors affecting nail delivery, diagnostic procedures, current approaches, and promising approaches to treat nail infections/disorders including nail lacquers and the role of permeation enhancers, in-vitro models. This review also covers current available treatments and treatments under clinical trial. Keywords: Musculo-skeletal, Nail infection, Transungual, Mathematical model, In-vitro models.

scholarly journals Lung Cancer Radiotherapy: Simulation and Analysis Based on a Multicomponent Mathematical Model

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Wen-song Hong ◽  
Shun-guan Wang ◽  
Gang-qing Zhang
Keyword(s):  
Lung Cancer ◽  
Mathematical Model ◽  
Optimization Methods ◽  
Model Parameters ◽  
Analysis And Evaluation ◽  
Basic Work ◽  
Near Future ◽  
Radiotherapy Treatment ◽  
Accelerated Hypofractionated Radiotherapy

Background. Lung cancer has been one of the most deadly illnesses all over the world, and radiotherapy can be an effective approach for treating lung cancer. Now, mathematical model has been extended to many biomedical fields to give a hand for analysis, evaluation, prediction, and optimization. Methods. In this paper, we propose a multicomponent mathematical model for simulating the lung cancer growth as well as radiotherapy treatment for lung cancer. The model is digitalized and coded for computer simulation, and the model parameters are fitted with many research and clinical data to provide accordant results along with the growth of lung cancer cells in vitro. Results. Some typical radiotherapy plans such as stereotactic body radiotherapy, conventional fractional radiotherapy, and accelerated hypofractionated radiotherapy are simulated, analyzed, and discussed. The results show that our mathematical model can perform the basic work for analysis and evaluation of the radiotherapy plan. Conclusion. It will be expected that in the near future, mathematical model will be a valuable tool for optimization in personalized medical treatment.

FACTORS AFFECTING THE REGENERATION OF PEPPER (CAPSICUM ANNUUM L.)

HortScience ◽  
1990 ◽  
Vol 25 (9) ◽  
pp. 1120G-1120
Author(s):  
J. L. Jacobs ◽  
C. T. Stephens
Keyword(s):  
Growth Hormone ◽  
Silver Nitrate ◽  
Callus Formation ◽  
Leaf Explants ◽  
Regeneration System ◽  
Factors Affecting ◽  
Nitrate Concentrations ◽  
Leaf Differentiation ◽  
Whole Plants

Several growth hormone combinations and silver nitrate concentrations were examined for their effect on regeneration of different pepper genotypes. Primary leaf explants from in vitro seedlings were cultured on a revised Murashige and Skoog medium supplemented with auxin, cytokinin and 1.6% glucose. Combinations of different concentrations of indole-3-acetic acid (IAA), 0-5 mg/l, and 6-benzylaminopurine (BAP), 0-5 mg/l, were tested to determine the most effective medium for shoot primordium formation. Experiments with IAA and BAP did not result in a specific growth hormone combination appropriate for regeneration of all genotypes tested. Of the silver nitrate concentrations tested, 10 mg/l resulted in the best shoot and leaf differentiation and reduced callus formation. Differences in organogenic response of individual genotypes were evaluated on a single regeneration medium. Whole plants were regenerated from 11 of 63 genotypes examined. Based on these experiments, a reproducible regeneration system for pepper was developed with a total of 500 plants regenerated to date.

Usefulness of collaboration between mathematical models and cell engineering for elucidating complex disease mechanisms and discover effective drugs

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
H Kohjitani ◽  
A Kashiwa ◽  
T Makiyama ◽  
F Toyoda ◽  
Y Yamamoto ◽  
...  
Keyword(s):  
Mathematical Model ◽  
In Silico ◽  
Complex Disease ◽  
Ion Selectivity ◽  
Public Institution ◽  
Cell Engineering ◽  
Funding Source ◽  
Patch Clamp Technique ◽  
In Silico Model

Abstract Background A missense mutation, CACNA1C-E1115K, located in the cardiac L-type calcium channel (LTCC), was recently reported to be associated with diverse arrhythmias. Several studies reported in-vivo and in-vitro modeling of this mutation, but actual mechanism and target drug of this disease has not been clarified due to its complex ion-mechanisms. Objective To reveal the mechanism of this diverse arrhythmogenic phenotype using combination of in-vitro and in-silico model. Methods and results Cell-Engineering Phase: We generated human induced pluripotent stem cell (hiPSC) from a patient carrying heterozygous CACNA1C-E1115K and differentiated into cardiomyocytes. Spontaneous APs were recorded from spontaneously beating single cardiomyocytes by using the perforated patch-clamp technique. Mathematical-Modeling Phase: We newly developed ICaL-mutation mathematical model, fitted into experimental data, including its impaired ion selectivity. Furthermore, we installed this mathematical model into hiPSC-CM simulation model. Collaboration Phase: Mutant in-silico model showed APD prolongation and frequent early afterdepolarization (EAD), which are same as in-vitro model. In-silico model revealed this EAD was mostly related to robust late-mode of sodium current occurred by Na+ overload and suggested that mexiletine is capable of reducing arrhythmia. Afterward, we applicated mexiletine onto hiPSC-CMs mutant model and found mexiletine suppress EADs. Conclusions Precise in-silico disease model can elucidate complicated ion currents and contribute predicting result of drug-testing. Funding Acknowledgement Type of funding source: Public Institution(s). Main funding source(s): Japan Society for the Promotion of Science, Grant-in-Aid for Young Scientists

scholarly journals Cytotoxic effects and tolerability of gemcitabine and axitinib in a xenograft model for c-myc amplified medulloblastoma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Stefanie Schwinn ◽  
Zeinab Mokhtari ◽  
Sina Thusek ◽  
Theresa Schneider ◽  
Anna-Leena Sirén ◽  
...  
Keyword(s):  
Fluorescence Microscopy ◽  
Tumor Growth ◽  
Intensive Therapy ◽  
Xenograft Model ◽  
Light Sheet ◽  
Tumor Control ◽  
Orthotopic Model ◽  
Group 3 ◽  
Light Sheet Fluorescence Microscopy

AbstractMedulloblastoma is the most common high-grade brain tumor in childhood. Medulloblastomas with c-myc amplification, classified as group 3, are the most aggressive among the four disease subtypes resulting in a 5-year overall survival of just above 50%. Despite current intensive therapy regimens, patients suffering from group 3 medulloblastoma urgently require new therapeutic options. Using a recently established c-myc amplified human medulloblastoma cell line, we performed an in-vitro-drug screen with single and combinatorial drugs that are either already clinically approved or agents in the advanced stage of clinical development. Candidate drugs were identified in vitro and then evaluated in vivo. Tumor growth was closely monitored by BLI. Vessel development was assessed by 3D light-sheet-fluorescence-microscopy. We identified the combination of gemcitabine and axitinib to be highly cytotoxic, requiring only low picomolar concentrations when used in combination. In the orthotopic model, gemcitabine and axitinib showed efficacy in terms of tumor control and survival. In both models, gemcitabine and axitinib were better tolerated than the standard regimen comprising of cisplatin and etoposide phosphate. 3D light-sheet-fluorescence-microscopy of intact tumors revealed thinning and rarefication of tumor vessels, providing one explanation for reduced tumor growth. Thus, the combination of the two drugs gemcitabine and axitinib has favorable effects on preventing tumor progression in an orthotopic group 3 medulloblastoma xenograft model while exhibiting a favorable toxicity profile. The combination merits further exploration as a new approach to treat high-risk group 3 medulloblastoma.

scholarly journals Silver Nanoparticles and Their Antibacterial Applications

2021 ◽  
Vol 22 (13) ◽  
pp. 7202
Author(s):  
Tamara Bruna ◽  
Francisca Maldonado-Bravo ◽  
Paul Jara ◽  
Nelson Caro
Keyword(s):  
Silver Nanoparticles ◽  
Antibacterial Agents ◽  
Multidrug Resistant ◽  
Secondary Effects ◽  
Cytotoxic Effects ◽  
Factors Affecting ◽  
Gram Positive Bacteria ◽  
Resistant Strains

Silver nanoparticles (AgNPs) have been imposed as an excellent antimicrobial agent being able to combat bacteria in vitro and in vivo causing infections. The antibacterial capacity of AgNPs covers Gram-negative and Gram-positive bacteria, including multidrug resistant strains. AgNPs exhibit multiple and simultaneous mechanisms of action and in combination with antibacterial agents as organic compounds or antibiotics it has shown synergistic effect against pathogens bacteria such as Escherichia coli and Staphylococcus aureus. The characteristics of silver nanoparticles make them suitable for their application in medical and healthcare products where they may treat infections or prevent them efficiently. With the urgent need for new efficient antibacterial agents, this review aims to establish factors affecting antibacterial and cytotoxic effects of silver nanoparticles, as well as to expose the advantages of using AgNPs as new antibacterial agents in combination with antibiotic, which will reduce the dosage needed and prevent secondary effects associated to both.

scholarly journals Advanced Static and Dynamic Fluorescence Microscopy Techniques to Investigate Drug Delivery Systems

Pharmaceutics ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 861
Author(s):  
Jacopo Cardellini ◽  
Arianna Balestri ◽  
Costanza Montis ◽  
Debora Berti
Keyword(s):  
Drug Delivery ◽  
Fluorescence Microscopy ◽  
Drug Delivery Systems ◽  
Laser Scanning ◽  
Super Resolution ◽  
Laser Scanning Confocal Microscopy ◽  
Delivery Systems ◽  
Scanning Confocal Microscopy ◽  
Biological Phenomena

In the past decade(s), fluorescence microscopy and laser scanning confocal microscopy (LSCM) have been widely employed to investigate biological and biomimetic systems for pharmaceutical applications, to determine the localization of drugs in tissues or entire organisms or the extent of their cellular uptake (in vitro). However, the diffraction limit of light, which limits the resolution to hundreds of nanometers, has for long time restricted the extent and quality of information and insight achievable through these techniques. The advent of super-resolution microscopic techniques, recognized with the 2014 Nobel prize in Chemistry, revolutionized the field thanks to the possibility to achieve nanometric resolution, i.e., the typical scale length of chemical and biological phenomena. Since then, fluorescence microscopy-related techniques have acquired renewed interest for the scientific community, both from the perspective of instrument/techniques development and from the perspective of the advanced scientific applications. In this contribution we will review the application of these techniques to the field of drug delivery, discussing how the latest advancements of static and dynamic methodologies have tremendously expanded the experimental opportunities for the characterization of drug delivery systems and for the understanding of their behaviour in biologically relevant environments.

Sign in / Sign up

Export Citation Format

Share Document