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Jeremy P. Brockes - One of the best experts on this subject based on the ideXlab platform.

  • recurrent turnover of senescent cells during regeneration of a Complex Structure
    eLife, 2015
    Co-Authors: Hongorzul Davaapil, Jeremy P. Brockes
    Abstract:

    As humans and other mammals get older, they become less able to recover from injury or repair damage to their tissues. This happens because mammalian cells gradually lose the ability to divide to produce new cells. This process is called senescence and it helps to prevent cancer by stopping old cells that are more likely to carry harmful mutations from replicating. However the link between senescence and many age-related declines in human health has led scientists to ask whether targeting senescent cells might be one way to treat age-related conditions. Some organisms can regenerate their tissues throughout their lives; and creatures like salamanders are even able to re-grow limbs and organs if they are lost. Scientists are eager to learn how these animals are able to do this when humans are not, and answering this and related questions might help us to develop therapies that boost our ability to recover from injury or age-related diseases. Yun et al. took a closer look at senescence in salamanders and unexpectedly found that a large number of senescent cells appeared in a salamander limb as it regenerates. But, by the time the limb had completely regrown, these senescent cells had disappeared. Further experiments revealed that when normal and senescent cells are implanted into a salamander the senescent cells also quickly disappear. These findings suggest that senescent cells may possibly play a role in the regeneration process, and that salamanders have a system that can efficiently destroy these cells. Previous research had suggested that parts of the immune system, in particular cells called macrophages, help to eliminate senescent cells in some tissues. Yun et al. found that macrophages did accumulate around senescent cells in the regenerating limbs of living salamanders. And when a toxin was used to destroy the macrophages in some salamanders, the senescent cells were not cleared in the way they were in salamanders with active macrophages. Hence, macrophages are an essential part of the mechanism that eliminates senescent cells from salamander tissues. This efficient mechanism for the elimination of senescent cells could explain how salamanders are able to maintain their ability to regenerate in spite of ageing. These findings also reveal the salamander as a model system that could be used to find new ways to target senescent cells, which could be eventually used in anti-ageing therapies.

  • Recurrent turnover of senescent cells during regeneration of a Complex Structure
    eLife, 2015
    Co-Authors: Maximina H. Yun, Hongorzul Davaapil, Jeremy P. Brockes
    Abstract:

    Cellular senescence has been recently linked to the promotion of age-related pathologies, including a decline in regenerative capacity. While such capacity deteriorates with age in mammals, it remains intact in species such as salamanders, which have an extensive repertoire of regeneration and can undergo multiple episodes through their lifespan. Here we show that, surprisingly, there is a significant induction of cellular senescence during salamander limb regeneration, but that rapid and effective mechanisms of senescent cell clearance operate in normal and regenerating tissues. Furthermore, the number of senescent cells does not increase upon repetitive amputation or ageing, in contrast to mammals. Finally, we identify the macrophage as a critical player in this efficient senescent cell clearance mechanism. We propose that effective immunosurveillance of senescent cells in salamanders supports their ability to undergo regeneration throughout their lifespan.

Hongorzul Davaapil - One of the best experts on this subject based on the ideXlab platform.

  • recurrent turnover of senescent cells during regeneration of a Complex Structure
    eLife, 2015
    Co-Authors: Hongorzul Davaapil, Jeremy P. Brockes
    Abstract:

    As humans and other mammals get older, they become less able to recover from injury or repair damage to their tissues. This happens because mammalian cells gradually lose the ability to divide to produce new cells. This process is called senescence and it helps to prevent cancer by stopping old cells that are more likely to carry harmful mutations from replicating. However the link between senescence and many age-related declines in human health has led scientists to ask whether targeting senescent cells might be one way to treat age-related conditions. Some organisms can regenerate their tissues throughout their lives; and creatures like salamanders are even able to re-grow limbs and organs if they are lost. Scientists are eager to learn how these animals are able to do this when humans are not, and answering this and related questions might help us to develop therapies that boost our ability to recover from injury or age-related diseases. Yun et al. took a closer look at senescence in salamanders and unexpectedly found that a large number of senescent cells appeared in a salamander limb as it regenerates. But, by the time the limb had completely regrown, these senescent cells had disappeared. Further experiments revealed that when normal and senescent cells are implanted into a salamander the senescent cells also quickly disappear. These findings suggest that senescent cells may possibly play a role in the regeneration process, and that salamanders have a system that can efficiently destroy these cells. Previous research had suggested that parts of the immune system, in particular cells called macrophages, help to eliminate senescent cells in some tissues. Yun et al. found that macrophages did accumulate around senescent cells in the regenerating limbs of living salamanders. And when a toxin was used to destroy the macrophages in some salamanders, the senescent cells were not cleared in the way they were in salamanders with active macrophages. Hence, macrophages are an essential part of the mechanism that eliminates senescent cells from salamander tissues. This efficient mechanism for the elimination of senescent cells could explain how salamanders are able to maintain their ability to regenerate in spite of ageing. These findings also reveal the salamander as a model system that could be used to find new ways to target senescent cells, which could be eventually used in anti-ageing therapies.

  • Recurrent turnover of senescent cells during regeneration of a Complex Structure
    eLife, 2015
    Co-Authors: Maximina H. Yun, Hongorzul Davaapil, Jeremy P. Brockes
    Abstract:

    Cellular senescence has been recently linked to the promotion of age-related pathologies, including a decline in regenerative capacity. While such capacity deteriorates with age in mammals, it remains intact in species such as salamanders, which have an extensive repertoire of regeneration and can undergo multiple episodes through their lifespan. Here we show that, surprisingly, there is a significant induction of cellular senescence during salamander limb regeneration, but that rapid and effective mechanisms of senescent cell clearance operate in normal and regenerating tissues. Furthermore, the number of senescent cells does not increase upon repetitive amputation or ageing, in contrast to mammals. Finally, we identify the macrophage as a critical player in this efficient senescent cell clearance mechanism. We propose that effective immunosurveillance of senescent cells in salamanders supports their ability to undergo regeneration throughout their lifespan.

Anne Barros - One of the best experts on this subject based on the ideXlab platform.

  • A dynamic grouping model for the maintenance planning of Complex Structure systems with consideration of maintenance durations
    2016
    Co-Authors: Hai Canh Vu, Anne Barros, Phuc Do Van, Mary Ann Lundteigen
    Abstract:

    In order to facilitate an analysis for the maintenance planning, most dynamic grouping models assume that the repair time is negligible. This assumption may be unrealistic and limits the application of these models in many real situations. The main objective of this paper is to develop a dynamic grouping strategy for Complex Structure systems with taking into account the durations of repair actions. Analytical method is used instead of simulation for the evaluation of total maintenance cost. This analytical method helps to overcome the computational time problem, which often is a big problem for the maintenance optimization of systems with a large number of components. A numerical example is presented to show how the proposed grouping approach can be used for the maintenance planning of a Complex Structure system containing 12 components.

  • A comparison of different maintenance grouping strategies for multi-component systems with Complex Structure
    2015
    Co-Authors: Hai Canh Vu, Phuc Do Van, Anne Barros
    Abstract:

    To face to the Complexity of the system Structures, both dynamic and stationary grouping models have been recently developed for the maintenance of the systems with Complex Structure. In order to support the maintenance manager in making a good choice of the maintenance strategy, this paper focuses on the qualitative and quantitative comparisons of the two above grouping models (dynamic and stationary). The qualitative comparison is done according to the dynamicity of the grouping planning, the difficulty in maintenance management and organization and the Complexity of the maintenance modeling and maintenance optimization. Meanwhile, the quantitative comparison pays attention to the performance of the considered grouping models. To this end, the dynamic and stationary grouping strategies are firstly applied for the long-term maintenance planning of a substation automation system containing 11 components. The quantitative comparison is then done by using the long-term expected maintenance cost rate criteria. The results obtained show that the dynamic grouping is more powerful than the stationary grouping. However, the implementation, the maintenance modeling and the maintenance optimization of the dynamic grouping are usually more Complex in compared to the stationary grouping.

  • (MRL, τ ) grouping policy for Complex Structure systems
    2013
    Co-Authors: Hai Canh Vu, Phuc Do Van, Anne Barros
    Abstract:

    Nowadays, industrial systems are more and more larger with many components which are connected in a Complex Structure. The systems usually ask for a high investment cost (expensive components) and many preparation tasks for maintenance. With these system, a maintenance policy should take into account the Complexity of system Structures and give priority to saving the setup costs. Therefore, an intelligent grouping maintenance strategy for Complex Structure systems is developed in this paper. Under this strategy, a group of components is decided to preventively maintained (PM) at each τ (basic time interval) due to component Mean Remaining Lifetime (MRL) and component Birnbaum's measure of structural importance (IB) to save preventive setup costs. Moreover, the Complex Structures allow to economize corrective setup costs by grouping some CM actions with the PM actions at τ . The CM grouping is performed by leaving some failed units in idle state until the next PM period. This action can economize corrective setup costs, but it also leads a change of the system Structure during the system operation. Therefore, in this paper, a simulation method using Monte Carlo Simulation is developed to analyze the changes of system Structure during the system operation and calculate the average maintenance cost. A numerical example of a 6 components system is finally introduced to illustrate the use and the advantages of the proposed strategy when compared to existing methods.

  • (MRL, _) grouping policy for Complex Structure systems
    Safety Reliability and Risk Analysis, 2013
    Co-Authors: Hai Canh Vu, Phuc Do Van, Anne Barros
    Abstract:

    Nowadays, industrial systems are more and more larger with many components which are connected in a Complex Structure. The systems usually ask for a high investment cost (expensive components) and many preparation tasks for maintenance. With these system, a maintenance policy should take into account the Complexity of system Structures and give priority to saving the setup costs. Therefore, an intelligent grouping maintenance strategy for Complex Structure systems is developed in this paper. Under this strategy, a group of components is decided to Preventively Maintained (PM) at each τ (basic time interval) due to component Mean Remaining Lifetime (MRL) and component Birnbaum's measure of structural importance (I B) to save preventive setup costs. Moreover, the Complex Structures allow to economize corrective setup costs by grouping some CM actions with the PM actions at τ. The CM grouping is performed by leaving some failed units in idle state until the next PM period. This action can economize corrective setup costs, but it also leads a change of the system Structure during the system operation. Therefore, in this paper, a simulation method using Monte Carlo Simulation is developed to analyze the changes of system Structure during the system operation and calculate the average maintenance cost. A numerical example of a 6 components system is finally introduced to illustrate the use and the advantages of the proposed strategy when compared to existing methods. © 2014 Taylor & Francis Group, London..

  • Maintenance activities planning and grouping for Complex Structure systems
    2012
    Co-Authors: Hai Canh Vu, Anne Barros, Phuc Do Van, Christophe Bérenguer
    Abstract:

    This paper presents a dynamic grouping maintenance strategy for Complex systems whose Structure may lead to both positive and negative economic dependence which imply that combining maintenance activities is cheaper (or more expensive respectively) than performing maintenance on components separately. Binary Particle Swarm Optimization (BPSO) algorithm is used to find optimal grouping planning which is NP-hard combinatorial problem. The proposed grouping maintenance strategy based on the rolling horizon approach can help to update the maintenance planning by taking into account short-term information which could be changed with time. A numerical example of a 10 components system is finally introduced to illustrate the use and the advantages of the proposed approach in the maintenance optimization framework.

Phuc Do Van - One of the best experts on this subject based on the ideXlab platform.

  • A dynamic grouping model for the maintenance planning of Complex Structure systems with consideration of maintenance durations
    2016
    Co-Authors: Hai Canh Vu, Anne Barros, Phuc Do Van, Mary Ann Lundteigen
    Abstract:

    In order to facilitate an analysis for the maintenance planning, most dynamic grouping models assume that the repair time is negligible. This assumption may be unrealistic and limits the application of these models in many real situations. The main objective of this paper is to develop a dynamic grouping strategy for Complex Structure systems with taking into account the durations of repair actions. Analytical method is used instead of simulation for the evaluation of total maintenance cost. This analytical method helps to overcome the computational time problem, which often is a big problem for the maintenance optimization of systems with a large number of components. A numerical example is presented to show how the proposed grouping approach can be used for the maintenance planning of a Complex Structure system containing 12 components.

  • A comparison of different maintenance grouping strategies for multi-component systems with Complex Structure
    2015
    Co-Authors: Hai Canh Vu, Phuc Do Van, Anne Barros
    Abstract:

    To face to the Complexity of the system Structures, both dynamic and stationary grouping models have been recently developed for the maintenance of the systems with Complex Structure. In order to support the maintenance manager in making a good choice of the maintenance strategy, this paper focuses on the qualitative and quantitative comparisons of the two above grouping models (dynamic and stationary). The qualitative comparison is done according to the dynamicity of the grouping planning, the difficulty in maintenance management and organization and the Complexity of the maintenance modeling and maintenance optimization. Meanwhile, the quantitative comparison pays attention to the performance of the considered grouping models. To this end, the dynamic and stationary grouping strategies are firstly applied for the long-term maintenance planning of a substation automation system containing 11 components. The quantitative comparison is then done by using the long-term expected maintenance cost rate criteria. The results obtained show that the dynamic grouping is more powerful than the stationary grouping. However, the implementation, the maintenance modeling and the maintenance optimization of the dynamic grouping are usually more Complex in compared to the stationary grouping.

  • (MRL, τ ) grouping policy for Complex Structure systems
    2013
    Co-Authors: Hai Canh Vu, Phuc Do Van, Anne Barros
    Abstract:

    Nowadays, industrial systems are more and more larger with many components which are connected in a Complex Structure. The systems usually ask for a high investment cost (expensive components) and many preparation tasks for maintenance. With these system, a maintenance policy should take into account the Complexity of system Structures and give priority to saving the setup costs. Therefore, an intelligent grouping maintenance strategy for Complex Structure systems is developed in this paper. Under this strategy, a group of components is decided to preventively maintained (PM) at each τ (basic time interval) due to component Mean Remaining Lifetime (MRL) and component Birnbaum's measure of structural importance (IB) to save preventive setup costs. Moreover, the Complex Structures allow to economize corrective setup costs by grouping some CM actions with the PM actions at τ . The CM grouping is performed by leaving some failed units in idle state until the next PM period. This action can economize corrective setup costs, but it also leads a change of the system Structure during the system operation. Therefore, in this paper, a simulation method using Monte Carlo Simulation is developed to analyze the changes of system Structure during the system operation and calculate the average maintenance cost. A numerical example of a 6 components system is finally introduced to illustrate the use and the advantages of the proposed strategy when compared to existing methods.

  • RETRACTED ARTICLE: Predictive grouping maintenance strategy for Complex Structure systems using importance measure
    QR2MSE 2013 - Proceedings of 2013 International Conference on Quality Reliability Risk Maintenance and Safety Engineering, 2013
    Co-Authors: Kim Anh Nguyen, Antoine Grall, Phuc Do Van
    Abstract:

    The aim of this study is to propose a predictive grouping maintenance strategy for Complex Structure systems with gradually deteriorating units. The unit's conditions are inspected at regular time intervals. Preventive maintenance decision rule is mainly based on the group improvement importance measure defined as a ratio of the improvement ability on the system reliability of a group of several units divided by the total maintenance costs of the group. Economic dependencies as well as Structure dependencies between units are also investigated. A numerical example of a Complex Structure of 11-unit system is finally introduced to illustrate the uses and the advantages of the proposed maintenance strategy. © 2013 IEEE.

  • (MRL, _) grouping policy for Complex Structure systems
    Safety Reliability and Risk Analysis, 2013
    Co-Authors: Hai Canh Vu, Phuc Do Van, Anne Barros
    Abstract:

    Nowadays, industrial systems are more and more larger with many components which are connected in a Complex Structure. The systems usually ask for a high investment cost (expensive components) and many preparation tasks for maintenance. With these system, a maintenance policy should take into account the Complexity of system Structures and give priority to saving the setup costs. Therefore, an intelligent grouping maintenance strategy for Complex Structure systems is developed in this paper. Under this strategy, a group of components is decided to Preventively Maintained (PM) at each τ (basic time interval) due to component Mean Remaining Lifetime (MRL) and component Birnbaum's measure of structural importance (I B) to save preventive setup costs. Moreover, the Complex Structures allow to economize corrective setup costs by grouping some CM actions with the PM actions at τ. The CM grouping is performed by leaving some failed units in idle state until the next PM period. This action can economize corrective setup costs, but it also leads a change of the system Structure during the system operation. Therefore, in this paper, a simulation method using Monte Carlo Simulation is developed to analyze the changes of system Structure during the system operation and calculate the average maintenance cost. A numerical example of a 6 components system is finally introduced to illustrate the use and the advantages of the proposed strategy when compared to existing methods. © 2014 Taylor & Francis Group, London..

Maximina H. Yun - One of the best experts on this subject based on the ideXlab platform.

  • Recurrent turnover of senescent cells during regeneration of a Complex Structure
    eLife, 2015
    Co-Authors: Maximina H. Yun, Hongorzul Davaapil, Jeremy P. Brockes
    Abstract:

    Cellular senescence has been recently linked to the promotion of age-related pathologies, including a decline in regenerative capacity. While such capacity deteriorates with age in mammals, it remains intact in species such as salamanders, which have an extensive repertoire of regeneration and can undergo multiple episodes through their lifespan. Here we show that, surprisingly, there is a significant induction of cellular senescence during salamander limb regeneration, but that rapid and effective mechanisms of senescent cell clearance operate in normal and regenerating tissues. Furthermore, the number of senescent cells does not increase upon repetitive amputation or ageing, in contrast to mammals. Finally, we identify the macrophage as a critical player in this efficient senescent cell clearance mechanism. We propose that effective immunosurveillance of senescent cells in salamanders supports their ability to undergo regeneration throughout their lifespan.