scholarly journals Investigating the Role of Hypoxia-Induced Migration in Glioblastoma Growth Rates

2019 ◽  
Author(s):  
Lee Curtin ◽  
Andrea Hawkins-Daarud ◽  
Kristoffer G. van der Zee ◽  
Kristin R. Swanson ◽  
Markus R. Owen
Keyword(s):  
Cell Migration ◽  
Migration Rate ◽  
Wave Speed ◽  
Primary Brain Tumor ◽  
Hypoxic Cell ◽  
Migration Rates ◽  
Eigenvector Analysis ◽  
Key Variables ◽  
The Impact ◽  
Eigenvalue And Eigenvector

AbstractWe analyze the wave-speed of the Proliferation Invasion Hypoxia Necrosis Angiogenesis (PIHNA) model that was previously created and applied to simulate the growth and spread of glioblastoma (GBM), a particularly aggressive primary brain tumor. We extend the PIHNA model by allowing for different hypoxic and normoxic cell migration rates and study the impact of these differences on the wave-speed dynamics. Through this analysis, we find key variables that drive the outward growth of the simulated GBM. We find a minimum tumor wave-speed for the model; this depends on the migration and proliferation rates of the normoxic cells and is achieved under certain conditions on the migration rates of the normoxic and hypoxic cells. If the hypoxic cell migration rate is greater than the normoxic cell migration rate above a threshold, the wave-speed increases above the predicted minimum. This increase in wave-speed is explored through an eigenvalue and eigenvector analysis of the linearized PIHNA model, which yields an expression for this threshold. The PIHNA model suggests that an inherently faster-diffusing hypoxic cell population can drive the outward growth of a GBM as a whole, and that this effect is more prominent for faster proliferating tumors that recover relatively slowly from a hypoxic phenotype.

Site determination and application of LTBP-1, a molecule related to atherosclerosis, involved in cell migration

Impact ◽  
2021 ◽  
Vol 2021 (6) ◽  
pp. 24-25
Author(s):  
Seisuke Mimori
Keyword(s):  
Coronary Artery Disease ◽  
Cell Migration ◽  
Coronary Artery ◽  
Mechanism Of Action ◽  
Clinical Medicine ◽  
Associate Professor ◽  
Migration Rates ◽  
Artery Disease ◽  
The Impact ◽  
Underlying Processes

The two strands of treatment available for coronary artery disease and associated pathologies are pharmaceutical and physical. However, these treatments are typically only available too late to help tackle the early underlying processes. Better understanding of the underlying processes is key to the development of preventative solutions. One of the key processes understanding coronary problems is atherosclerosis, which is when arteries lose elasticity. Associate Professor Seisuke Mimori, Department of Clinical Medicine, Chiba Institute of Science, Japan, is examining the underlying biochemistry of atherosclerosis. Professor Tetsuto Kanzaki has succeeded in cloning a protein called LTBP-1 and, under his direction, Seisuke has created a mutant of the protein and is analysing it. He intends to produce variants of LTBP-1 in order to investigate the function of various domains of the protein. This will involve firstly producing and isolating the protein and its variants in sufficient quantities. Then, he will test cell migration rates through an assay that he and the team have designed. This will enable the researchers to clarify exactly how LTBP-1 functions. In the future, Seisuke and the team will investigate the exact mechanism of action of the domains involved and explore the impact of LTBP-1 on the relevant organs and cells.

scholarly journals Intermediate Migration Yields Optimal Adaptation in Structured, Asexual Populations

2014 ◽  
Author(s):  
Arthur Covert III ◽  
Claus O Wilke
Keyword(s):  
Genetic Variation ◽  
Gene Flow ◽  
Migration Rate ◽  
Appreciable Effect ◽  
Migration Rates ◽  
Optimal Migration ◽  
Digital Organisms ◽  
Asexual Populations ◽  
The Impact

Most evolving populations are subdivided into multiple subpopulations connected to each other by varying levels of gene flow. However, how population structure and gene flow (i.e., migration) affect adaptive evolution is not well understood. Here, we studied the impact of migration on asexually reproducing evolving computer programs (digital organisms). We found that digital organisms evolve the highest fitness values at intermediate migration rates, and we tested three hypotheses that could potentially explain this observation: (i) migration promotes passage through fitness valleys, (ii) migration increases genetic variation, and (iii) migration reduces clonal interference through a process called “leapfrogging”. We found that migration had no appreciable effect on the number of fitness valleys crossed and that genetic variation declined monotonously with increasing migration rates, instead of peaking at the optimal migration rate. However, the number of leapfrogging events, in which a superior beneficial mutation emerges on a genetic background that predates the previously best genotype in the population, did peak at the optimal migration rate. We thus conclude that in structured, asexual populations intermediate migration rates allow for optimal exploration of multiple, distinct fitness peaks, and thus yield the highest long-term adaptive success.

scholarly journals Brain drain and brain gain in Russia: Analyzing international migration of researchers by discipline using Scopus bibliometric data 1996–2020

2021 ◽  
Author(s):  
Alexander Subbotin ◽  
Samin Aref
Keyword(s):  
Brain Drain ◽  
Policy Development ◽  
Donor Country ◽  
International Mobility ◽  
Science System ◽  
Migration Rates ◽  
Net Migration ◽  
Novel Approach ◽  
Five Disciplines ◽  
The Impact

AbstractWe study international mobility in academia, with a focus on the migration of published researchers to and from Russia. Using an exhaustive set of over 2.4 million Scopus publications, we analyze all researchers who have published with a Russian affiliation address in Scopus-indexed sources in 1996–2020. The migration of researchers is observed through the changes in their affiliation addresses, which altered their mode countries of affiliation across different years. While only 5.2% of these researchers were internationally mobile, they accounted for a substantial proportion of citations. Our estimates of net migration rates indicate that while Russia was a donor country in the late 1990s and early 2000s, it has experienced a relatively balanced circulation of researchers in more recent years. These findings suggest that the current trends in scholarly migration in Russia could be better framed as brain circulation, rather than as brain drain. Overall, researchers emigrating from Russia outnumbered and outperformed researchers immigrating to Russia. Our analysis on the subject categories of publication venues shows that in the past 25 years, Russia has, overall, suffered a net loss in most disciplines, and most notably in the five disciplines of neuroscience, decision sciences, mathematics, biochemistry, and pharmacology. We demonstrate the robustness of our main findings under random exclusion of data and changes in numeric parameters. Our substantive results shed light on new aspects of international mobility in academia, and on the impact of this mobility on a national science system, which have direct implications for policy development. Methodologically, our novel approach to handling big data can be adopted as a framework of analysis for studying scholarly migration in other countries.

scholarly journals Cell migration guided by long-lived spatial memory

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Joseph d’Alessandro ◽  
Alex Barbier--Chebbah ◽  
Victor Cellerin ◽  
Olivier Benichou ◽  
René Marc Mège ◽  
...  
Keyword(s):  
Cell Migration ◽  
Spatial Memory ◽  
Large Scale ◽  
Single Cells ◽  
Environmental Perturbations ◽  
Motile Cells ◽  
Unicellular Organisms ◽  
Biochemical Signals ◽  
The Impact ◽  
Cell Trajectories

AbstractLiving cells actively migrate in their environment to perform key biological functions—from unicellular organisms looking for food to single cells such as fibroblasts, leukocytes or cancer cells that can shape, patrol or invade tissues. Cell migration results from complex intracellular processes that enable cell self-propulsion, and has been shown to also integrate various chemical or physical extracellular signals. While it is established that cells can modify their environment by depositing biochemical signals or mechanically remodelling the extracellular matrix, the impact of such self-induced environmental perturbations on cell trajectories at various scales remains unexplored. Here, we show that cells can retrieve their path: by confining motile cells on 1D and 2D micropatterned surfaces, we demonstrate that they leave long-lived physicochemical footprints along their way, which determine their future path. On this basis, we argue that cell trajectories belong to the general class of self-interacting random walks, and show that self-interactions can rule large scale exploration by inducing long-lived ageing, subdiffusion and anomalous first-passage statistics. Altogether, our joint experimental and theoretical approach points to a generic coupling between motile cells and their environment, which endows cells with a spatial memory of their path and can dramatically change their space exploration.

scholarly journals Modeling Building Stock Development

2021 ◽  
Vol 13 (2) ◽  
pp. 723
Author(s):  
Antti Kurvinen ◽  
Arto Saari ◽  
Juhani Heljo ◽  
Eero Nippala
Keyword(s):  
Model Development ◽  
Housing Demand ◽  
Quality Data ◽  
Building Stock ◽  
Test Arena ◽  
Climate Targets ◽  
Wide Range ◽  
Key Variables ◽  
The Impact

It is widely agreed that dynamics of building stocks are relatively poorly known even if it is recognized to be an important research topic. Better understanding of building stock dynamics and future development is crucial, e.g., for sustainable management of the built environment as various analyses require long-term projections of building stock development. Recognizing the uncertainty in relation to long-term modeling, we propose a transparent calculation-based QuantiSTOCK model for modeling building stock development. Our approach not only provides a tangible tool for understanding development when selected assumptions are valid but also, most importantly, allows for studying the sensitivity of results to alternative developments of the key variables. Therefore, this relatively simple modeling approach provides fruitful grounds for understanding the impact of different key variables, which is needed to facilitate meaningful debate on different housing, land use, and environment-related policies. The QuantiSTOCK model may be extended in numerous ways and lays the groundwork for modeling the future developments of building stocks. The presented model may be used in a wide range of analyses ranging from assessing housing demand at the regional level to providing input for defining sustainable pathways towards climate targets. Due to the availability of high-quality data, the Finnish building stock provided a great test arena for the model development.

Upstream and downstream morphodynamic influence in simulated and real meandering rivers

2021 ◽  
Author(s):  
Hossein amini ◽  
Guido Zolezzi ◽  
Federico Monegaglia ◽  
Emanuele Olivetti ◽  
Marco Tubino
Keyword(s):  
Migration Rate ◽  
Machine Learning Techniques ◽  
Stochastic Gradient Descent ◽  
Support Vector ◽  
Lateral Migration ◽  
Remotely Sensed Data ◽  
Meandering Rivers ◽  
Meandering River ◽  
Migration Rates ◽  
Meander Migration

<p>This study investigates the dependency of meander lateral migration rates on the spatial distribution of channel centerline curvature in both synthetic and real meandering rivers. It employs Machine Learning techniques (hereafter ML) to relate observed local lateral meander migration rates with the local and the upstream/downstream values of the centerline curvature. To achieve this goal, it was primarily essential to identify the feasibility of using ML in the meandering river's morphodynamics. We then determined the ability of ML to predict the excess near bank velocity based a set of input data using different regression techniques (linear and polynomial, Stochastic Gradient Descent, Multi-Layer Perceptron, and Support Vector Machine). We then moved forward to study the upstream-downstream influence on local migration rate. Synthetic meandering river planforms, as obtained through the planform evolution model of Bogoni et al. (2017), which is based on Zolezzi and Seminara (2001) meander flow model, were used as test cases for the calibration and check of the different adopted ML algorithms. The calibrated algorithms were then applied to multi-temporal information on meander planform dynamics obtained through the PyRiS software (Monegaglia et al., 2018), to quantify to which extent the upstream and downstream distribution of meander centerline curvature affects the local meander migration rate in real rivers.</p><p>References </p><p>1- Zolezzi, G., & Seminara, G. (2001b). Downstream and upstream influence in river meandering. Part 1. General theory and application overdeepening. Journal of Fluid Mechanics, 438(September 2015), 183–211. https://doi.org/10.1017/S002211200100427X</p><p>2- Monegaglia, F., Zolezzi, G., Güneralp, I., Henshaw, A. J., & Tubino, M. (2018). Automated extraction of meandering river morphodynamics from multitemporal remotely sensed data. In Environmental Modelling & Software (Vol. 105, pp. 171–186). https://doi.org/10.1016/j.envsoft.2018.03.028</p><p>3- Bogoni, M., Putti, M., & Lanzoni, S. (2017). Modeling meander morphodynamics over self-formed heterogeneous floodplains. In Water Resources Research (Vol. 53, Issue 6, pp. 5137–5157). https://doi.org/10.1002/2017wr020726</p><p>4- Benozzo, D.,  Olivetti, E., Avesani, P. (2017). Supervised Estimation of Granger-Based Causality between Time series. In Frontiers in Neuroinformatics. </p><p>https://doi.org/10.3389/fninf.2017.00068 </p><p>5- Sharma A., Kiciman, E. (2020). DoWhy: An End-to-End library for Causal Inference. arXiv preprint arXiv:2011.04216. </p><p>https://arxiv.org/abs/2011.04216</p>

Study of sand wave migration over five years as observed in two windfarm development areas, and the implications for building on moving substrates in the North Sea

2014 ◽  
Vol 105 (4) ◽  
pp. 241-249 ◽  
Author(s):  
Ken P. Games ◽  
David I. Gordon
Keyword(s):  
Case Studies ◽  
Large Scale ◽  
Oil And Gas ◽  
Sand Wave ◽  
Sand Waves ◽  
Migration Rates ◽  
The North ◽  
The North Sea ◽  
Wave Migration ◽  
The Impact

ABSTRACTSand waves are well known indicators of a mobile seabed. What do we expect of these features in terms of migration rates and seabed scour? We discuss these effects on seabed structures, both for the Oil and Gas and the Windfarm Industries, and consider how these impact on turbines and buried cables. Two case studies are presented. The first concerns a windfarm with a five-year gap between the planning survey and a subsequent cable route and environmental assessment survey. This revealed large-scale movements of sand waves, with the displacement of an isolated feature of 155 m in five years. Secondly, another windfarm development involved a re-survey, again over a five-year period, but after the turbines had been installed. This showed movements of sand waves of ∼50 m in five years. Observations of the scour effects on the turbines are discussed. Both sites revealed the presence of barchans. Whilst these have been extensively studied on land, there are few examples of how they behave in the marine environment. The two case studies presented show that mass transport is potentially much greater than expected and that this has implications for choosing turbine locations, the effect of scour, and the impact these sediment movements are likely to have on power cables.

scholarly journals Amikacin Suppresses Human Breast Cancer Cell MDA-MB-231 Migration and Invasion

Toxics ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 108
Author(s):  
Yun-Hsin Wang ◽  
Yau-Hung Chen ◽  
Wen-Hao Shen
Keyword(s):  
Wound Healing ◽  
Cell Migration ◽  
Western Blotting ◽  
Bacterial Infections ◽  
Aminoglycoside Antibiotic ◽  
Migration And Invasion ◽  
Interacting Protein ◽  
Migration Rates ◽  
Thioredoxin Interacting Protein ◽  
Sirna Knockdown

(1) Background: Amikacin is an aminoglycoside antibiotic used for treating gram-negative bacterial infections in cancer patients. In this study, our aims are to investigate the migratory inhibition effects of amikacin in human MDA-MB-231 cells. (2) Methods: We used a wound-healing assay, trans-well analysis, Western blotting, immunostaining and siRNA knockdown approaches to investigate how amikacin influenced MDA-MB-231 cell migration and invasion. (3) Results: Wound healing showed that the MDA-MB-231 cell migration rates decreased to 44.4% in the presence of amikacin. Trans-well analysis showed that amikacin treatment led to invasion inhibition. Western blotting demonstrated that amikacin induced thioredoxin-interacting protein (TXNIP) up-regulation. TXNIP was knocked down using siRNA in MDA-MB-231 cell. Using immunostaining analysis, we found that inhibition of TXNIP expression led to MDA-MB-231 pseudopodia extension; however, amikacin treatment attenuated the cell extension formation. (4) Conclusions: We observed inhibition of migration and invasion in MDA-MB-231 cells treated with amikacin. This suggests inhibition might be mediated by up-regulation of TXNIP.

scholarly journals Cell migration driven by long-lived spatial memory

2021 ◽  
Author(s):  
Joseph d’Alessandro ◽  
Alex Barbier-Chebbah ◽  
Victor Cellerin ◽  
Olivier Bénichou ◽  
René-Marc Mège ◽  
...  
Keyword(s):  
Cell Migration ◽  
Spatial Memory ◽  
Large Scale ◽  
Single Cells ◽  
Environmental Perturbations ◽  
Motile Cells ◽  
Unicellular Organisms ◽  
Biochemical Signals ◽  
The Impact ◽  
Cell Trajectories

Many living cells actively migrate in their environment to perform key biological functions – from unicellular organisms looking for food to single cells such as fibroblasts, leukocytes or cancer cells that can shape, patrol or invade tissues. Cell migration results from complex intracellular processes that enable cell self-propulsion 1,2, and has been shown to also integrate various chemical or physical extracellular signals 3,4,5. While it is established that cells can modify their environment by depositing biochemical signals or mechanically remodeling the extracellular matrix, the impact of such self-induced environmental perturbations on cell trajectories at various scales remains unexplored. Here, we show that cells remember their path: by confining cells on 1D and 2D micropatterned surfaces, we demonstrate that motile cells leave long-lived physicochemical footprints along their way, which determine their future path. On this basis, we argue that cell trajectories belong to the general class of self-interacting random walks, and show that self-interactions can rule large scale exploration by inducing long-lived ageing, subdiffusion and anomalous first-passage statistics. Altogether, our joint experimental and theoretical approach points to a generic coupling between motile cells and their environment, which endows cells with a spatial memory of their path and can dramatically change their space exploration.

scholarly journals Viscoelasticity and cell jamming state transition

2021 ◽  
Author(s):  
Ivana Pajic-Lijakovic ◽  
Milan Milivojevic
Keyword(s):  
Residual Stress ◽  
Wound Healing ◽  
Cell Migration ◽  
State Transition ◽  
State Transitions ◽  
Collective Cell Migration ◽  
Biological Processes ◽  
Cell Mobility ◽  
Controversial Topic ◽  
The Impact

Although collective cell migration (CCM) is a highly coordinated migratory mode, perturbations in the form of jamming state transitions and vice versa often occur even in 2D. These perturbations are involved in various biological processes, such as embryogenesis, wound healing and cancer invasion. CCM induces accumulation of cell residual stress which has a feedback impact to cell packing density. Density-mediated change of cell mobility influences the state of viscoelasticity of multicellular systems and on that base the jamming state transition. Although a good comprehension of how cells collectively migrate by following molecular rules has been generated, the impact of cellular rearrangements on cell viscoelasticity remains less understood. Thus, considering the density driven evolution of viscoelasticity caused by reduction of cell mobility could result in a powerful tool in order to address the contribution of cell jamming state transition in CCM and help to understand this important but still controversial topic. In addition, five viscoelastic states gained within three regimes: (1) convective regime, (2) conductive regime, and (3) damped-conductive regime was discussed based on the modeling consideration with special emphasis of jamming and unjamming states.

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