13 research outputs found
Neurite: a finite difference continuum model of the electrophysiological-mechanical coupling in neurons under mechanical loading
A computational model coupling mechanics and electrophysiology in spinal cord injury
Traumatic brain injury and spinal cord injury have recently been put under the spotlight as major causes of death and disability in the developed world. Despite the important ongoing experimental and modeling campaigns aimed at understanding the mechanics of tissue and cell damage typically observed in such events, the differenti- ated roles of strain, stress and their corresponding loading rates on the damage level itself remain unclear. More specif- ically, the direct relations between brain and spinal cord tis- sue or cell damage, and electrophysiological functions are still to be unraveled. Whereas mechanical modeling efforts are focusing mainly on stress distribution and mechanistic- based damage criteria, simulated function-based damage cri- teria are still missing. Here, we propose a new multiscale model of myelinated axon associating electrophysiological impairment to structural damage as a function of strain and strain rate. This multiscale approach provides a new framework for damage evaluation directly relating neuron mechanics and electrophysiological properties, thus provid- ing a link between mechanical trauma and subsequent func- tional deficits
Uso de antibióticos y resistencia antimicrobiana en la unidad de cuidado intensivo neonatal
Neonatal sepsis constitutes one of the main causes of neonatal mortality in developing countries. Newborns, particularly premature newborns, have a higher risk of bacterial infections that result in frequent administration of antibiotics in the Neonatal Intensive Care Units (NICU), which is estimated to be as high as 70%. The clinical presentation of neonatal sepsis is nonspecific, prompting the early use of empirical antibiotic prescription to avoid adverse consequences in the patients. Its non-specificity characterizes it as a challenging diagnostic, this aspect led several authors to design strategies to determine which newborns are true candidates for antimicrobial therapy.
Microbiology is closely linked to clinical practice. Thus, knowing the most frequent bacteria associated with neonatalsepsis will be closely related to the antibiotic spectrum that should be used to treat it. Furthermore, knowledge on basic pharmacology is key inasmuch as the antimicrobial treatment is not innocuous and can be related to an increase in mortality and morbidity. Clinical course and maternal risk factors are associated with the expected responsible germs that are already described in multiple descriptive studies worldwide.
Indiscriminate use of broad-spectrum antibiotics for the management of newborn infections is leading to antibiotic resistance increase. At the same time, this is related to even higher rates of therapeutic failure with empiric antimicrobial treatment. Based on this, Antimicrobial Stewardship Programs play a determinant role to monitor the changes in local resistance to adjust and homogenize medical practice to regulate the use of antibiotics and mitigate the emergent andthreatening antimicrobial bacterial resistance.
La sepsis neonatal constituye una de las principales causas de mortalidad neonatal en los países en desarrollo. Los neonatos, en particular los prematuros, tienen un mayor riesgo de infecciones bacterianas, por lo que el manejo con antibióticos constituye la terapia más frecuente en la Unidad de Cuidado Intensivo Neonatal (UCIN), estimándose en hasta un 70%. La presentación clínica de la sepsis neonatal es inespecífica en muchas ocasiones, lo que hace que la antibioticoterapia empírica se inicie tempranamente para evitar consecuencias deletéreas para los pacientes; su inespecificidad la caracteriza como un reto diagnóstico, por lo que diferentes autores han diseñado estrategias para determinar neonatos candidatos a terapia antimicrobiana.
La microbiología permanece en contacto estrecho con la clínica ya que conocer los gérmenes frecuentemente asociados a la sepsis neonatal ayuda a determinar el espectro antibiótico a usar. De igual forma, el conocimiento de la farmacología antibiótica es clave puesto que el tratamiento antibiótico no es inocuo y puede asociarse a aumento de morbilidad o mortalidad. El tiempo de evolución y los factores de riesgo maternos están asociados a los gérmenes responsables esperados, ya descritos por múltiples estudios descriptivos a nivel mundial.
El uso indiscriminado de antibióticos de amplio espectro para el manejo de infecciones en los recién nacidos ha generado un aumento en la resistencia antibiótica, lo que a su vez lleva a tasas más altas de fallo terapéutico con el uso de las terapias antibióticas empíricas. A razón de lo anterior, los Programas de Vigilancia de Uso de Antibióticos juegan un papel determinante para monitorear el cambio en la resistencia a nivel local para ajustar y homogeneizar la práctica médica que logre regular el uso de antibióticos y mitigar la emergente resistencia bacteriana.
 
Uso de antibióticos y resistencia antimicrobiana en la unidad de cuidado intensivo neonatal
Neonatal sepsis constitutes one of the main causes of neonatal mortality in developing countries. Newborns, particularly premature newborns, have a higher risk of bacterial infections that result in frequent administration of antibiotics in the Neonatal Intensive Care Units (NICU), which is estimated to be as high as 70%. The clinical presentation of neonatal sepsis is nonspecific, prompting the early use of empirical antibiotic prescription to avoid adverse consequences in the patients. Its non-specificity characterizes it as a challenging diagnostic, this aspect led several authors to design strategies to determine which newborns are true candidates for antimicrobial therapy.
Microbiology is closely linked to clinical practice. Thus, knowing the most frequent bacteria associated with neonatalsepsis will be closely related to the antibiotic spectrum that should be used to treat it. Furthermore, knowledge on basic pharmacology is key inasmuch as the antimicrobial treatment is not innocuous and can be related to an increase in mortality and morbidity. Clinical course and maternal risk factors are associated with the expected responsible germs that are already described in multiple descriptive studies worldwide.
Indiscriminate use of broad-spectrum antibiotics for the management of newborn infections is leading to antibiotic resistance increase. At the same time, this is related to even higher rates of therapeutic failure with empiric antimicrobial treatment. Based on this, Antimicrobial Stewardship Programs play a determinant role to monitor the changes in local resistance to adjust and homogenize medical practice to regulate the use of antibiotics and mitigate the emergent andthreatening antimicrobial bacterial resistance.
La sepsis neonatal constituye una de las principales causas de mortalidad neonatal en los países en desarrollo. Los neonatos, en particular los prematuros, tienen un mayor riesgo de infecciones bacterianas, por lo que el manejo con antibióticos constituye la terapia más frecuente en la Unidad de Cuidado Intensivo Neonatal (UCIN), estimándose en hasta un 70%. La presentación clínica de la sepsis neonatal es inespecífica en muchas ocasiones, lo que hace que la antibioticoterapia empírica se inicie tempranamente para evitar consecuencias deletéreas para los pacientes; su inespecificidad la caracteriza como un reto diagnóstico, por lo que diferentes autores han diseñado estrategias para determinar neonatos candidatos a terapia antimicrobiana.
La microbiología permanece en contacto estrecho con la clínica ya que conocer los gérmenes frecuentemente asociados a la sepsis neonatal ayuda a determinar el espectro antibiótico a usar. De igual forma, el conocimiento de la farmacología antibiótica es clave puesto que el tratamiento antibiótico no es inocuo y puede asociarse a aumento de morbilidad o mortalidad. El tiempo de evolución y los factores de riesgo maternos están asociados a los gérmenes responsables esperados, ya descritos por múltiples estudios descriptivos a nivel mundial.
El uso indiscriminado de antibióticos de amplio espectro para el manejo de infecciones en los recién nacidos ha generado un aumento en la resistencia antibiótica, lo que a su vez lleva a tasas más altas de fallo terapéutico con el uso de las terapias antibióticas empíricas. A razón de lo anterior, los Programas de Vigilancia de Uso de Antibióticos juegan un papel determinante para monitorear el cambio en la resistencia a nivel local para ajustar y homogeneizar la práctica médica que logre regular el uso de antibióticos y mitigar la emergente resistencia bacteriana.
 
Large scale multiphysics modeling of neurites
Situado en el límite entre Ingeniería, Informática y Biología, la mecánica computacional de las neuronas aparece como un nuevo campo interdisciplinar que potencialmente puede ser capaz de abordar problemas clínicos desde una perspectiva diferente. Este campo es multiescala por naturaleza, yendo desde la nanoescala (como, por ejemplo, los dímeros de tubulina) a la macroescala (como, por ejemplo, el tejido cerebral), y tiene como objetivo abordar problemas que son complejos, y algunas veces imposibles, de estudiar con medios experimentales. La modelización computacional ha sido ampliamente empleada en aplicaciones Neurocientíficas tan diversas como el crecimiento neuronal o la propagación de los potenciales de acción compuestos. Sin embargo, en la mayoría de los enfoques de modelización hechos hasta ahora, la interacción entre la célula y el medio/estímulo que la rodea ha sido muy poco explorada. A pesar de la tremenda importancia de esa relación en algunos desafíos médicos—como, por ejemplo, lesiones traumáticas en el cerebro, cáncer, la enfermedad del Alzheimer—un puente que relacione las propiedades electrofisiológicas-químicas y mecánicas desde la escala molecular al nivel celular todavía no existe. Con ese objetivo, esta investigación propone un marco computacional multiescala particularizado para dos escenarios respresentativos: el crecimiento del axón y el acomplamiento electrofisiológicomecánico de las neuritas. En el primer caso, se explora la relación entre los constituyentes moleculares del axón durante su crecimiento y sus propiedades mecánicas resultantes, mientras que en el último, un estímulo mecánico provoca deficiencias funcionales a nivel celular como consecuencia de sus alteraciones electrofisiológicas-químicas. La modelización computacional empleada en este trabajo es el método de las diferencias finitas, y es implementada en un nuevo programa llamado Neurite. Aunque el método de los elementos finitos es también explorado en parte de esta investigación, el método de las diferencias finitas tiene la flexibilidad y versatilidad necesaria para implementar mode los biológicos, así como la simplicidad matemática para extenderlos a simulaciones a gran escala con un coste computacional bajo. Centrándose primero en el efecto de las propiedades electrofisiológicas-químicas sobre las propiedades mecánicas, una versión adaptada de Neurite es desarrollada para simular la polimerización de los microtúbulos en el crecimiento del axón y proporcionar las propiedades mecánicas como función de la ocupación de los microtúbulos. Después de calibrar el modelo de crecimiento del axón frente a resultados experimentales disponibles en la literatura, las características mecánicas pueden ser evaluadas durante la simulación. Las propiedades mecánicas del axón muestran variaciones dramáticas en la punta de éste, donde el cono de crecimiento soporta las señales químicas y mecánicas. Bansándose en el conocimiento ganado con el modelo de diferencias finitas, y con el objetivo de ir de 1D a 3D, este esquema preliminar pero de una naturaleza innovadora allana el camino a futuros estudios con el método de los elementos finitos. Centrándose finalmente en el efecto de las propiedades mecánicas sobre las propiedades electrofisiológicas- químicas, Neurite es empleado para relacionar las cargas mecánicas macroscópicas con las deformaciones y velocidades de deformación a escala microscópica, y simular la propagación de la señal eléctrica en las neuritas bajo carga mecánica. Las simulaciones fueron calibradas con resultados experimentales publicados en la literatura, proporcionando, por tanto, un modelo capaz de predecir las alteraciones de las funciones electrofisiológicas neuronales bajo cargas externas dañinas, y uniendo lesiones mecánicas con las correspondientes deficiencias funcionales. Para abordar simulaciones a gran escala, aunque otras arquitecturas avanzadas basadas en muchos núcleos integrados (MICs) fueron consideradas, los solvers explícito e implícito se implementaron en unidades de procesamiento central (CPU) y unidades de procesamiento gráfico (GPUs). Estudios de escalabilidad fueron llevados acabo para ambas implementaciones mostrando resultados prometedores para casos de simulaciones extremadamente grandes con GPUs. Esta tesis abre la vía para futuros modelos mecánicos con el objetivo de unir las propiedades electrofisiológicas-químicas con las propiedades mecánicas. El objetivo general es mejorar el conocimiento de las comunidades médicas y de bioingeniería sobre la mecánica de las neuronas y las deficiencias funcionales que aparecen de los daños producidos por traumatismos mecánicos, como lesiones traumáticas en el cerebro, o enfermedades neurodegenerativas como la enfermedad del Alzheimer. ABSTRACT Sitting at the interface between Engineering, Computer Science and Biology, Computational Neuron Mechanics appears as a new interdisciplinary field potentially able to tackle clinical problems from a new perspective. This field is multiscale by nature, ranging from the nanoscale (e.g., tubulin dimers) to the macroscale (e.g., brain tissue), and aims at tackling problems that are complex, and sometime impossible, to study through experimental means. Computational modeling has been widely used in different Neuroscience applications as diverse as neuronal growth or compound action potential propagation. However, in the majority of the modeling approaches done in this field to date, the interactions between the cell and its surrounding media/stimulus have been rarely explored. Despite of the tremendous importance of such relationship in several medical challenges—e.g., traumatic brain injury (TBI), cancer, Alzheimer’s disease (AD)—a bridge between electrophysiological-chemical and mechanical properties of neurons from the molecular scale to the cell level is still lacking. To this end, this research proposes a multiscale computational framework particularized for two representative scenarios: axon growth and electrophysiological-mechanical coupling of neurites. In the former case, the relation between the molecular constituents of the axon during its growth and its resulting mechanical properties is explored, whereas in the latter, a mechanical stimulus provokes functional deficits at cell level as a consequence of its electrophysiological-chemical alterations. The computational modeling approach chosen in this work is the finite difference method (FDM), and was implemented in a new program called Neurite. Although the finite element method (FEM) is also explored as part of this research, the FDM provides the necessary flexibility and versatility to implement biological models, as well as the mathematical simplicity to extend them to large scale simulations with a low computational cost. Focusing first on the effect of electrophysiological-chemical properties on the mechanical proper ties, an adaptation of Neurite was developed to simulate microtubule polymerization in axonal growth and provide the axon mechanical properties as a function of microtubule occupancy. After calibrating the axon growth model against experimental results available in the literature, the mechanical characteristics can be tracked during the simulation. The axon mechanical properties show dramatic variations at the tip of the axon, where the growth cone supports the chemical and mechanical signaling. Based on the knowledge gained from the FDM scheme, and in order to go from 1D to 3D, this preliminary yet novel scheme paves the road for future studies with FEM. Focusing then on the effect of mechanical properties on the electrophysiological-chemical properties, Neurite was used to relate macroscopic mechanical loading to microscopic strains and strain rates, and simulate the electrical signal propagation along neurites under mechanical loading. The simulations were calibrated against experimental results published in the literature, thus providing a model able to predict the alteration of neuronal electrophysiological function under external damaging load, and linking mechanical injuries to subsequent acute functional deficits. To undertake large scale simulations, although other state-of-the-art architectures based on many integrated cores (MICs) were considered, the explicit and implicit solvers were implemented for central processing units (CPUs) and graphics processing units (GPUs). Scalability studies were done for both implementations showing promising results for extremely large scale simulations with GPUs. This thesis opens the avenue for future mechanical modeling approaches aimed at linking electrophysiological- chemical properties to mechanical properties. Its overarching goal is to enhance the bioengineering and medical communities knowledge on neuronal mechanics and functional deficits arising from damages produced by direct mechanical insults, such as TBI, or neurodegenerative evolving illness, such as AD
A model of the spatially dependent mechanical properties of the axon during its growth
Neuronal growth is a complex process involving many intra- and extracellular mechanisms which are collaborating conjointly to participate to the development of the nervous system. More particularly, the early neocortical development involves the creation of a multilayered structure constituted by neuronal growth (driven by axonal or dendritic guidance cues) as well as cell migration. The underlying mechanisms of such structural lamination not only implies important biochemical changes at the intracellular level through axonal microtubule (de)polymerization and growth cone advance, but also through the directly dependent stress/stretch coupling mechanisms driving them. Efforts have recently focused on modeling approaches aimed at accounting for the effect of mechanical tension or compression on the axonal growth and subsequent soma migration. However, the reciprocal influence of the biochemical structural evolution on the mechanical properties has been mostly disregarded. We thus propose a new model aimed at providing the spatially dependent mechanical properties of the axon during its growth. Our in-house finite difference solver Neurite is used to describe the guanosine triphosphate (GTP) transport through the axon, its dephosphorylation in guanosine diphosphate (GDP), and thus the microtubules polymerization. The model is calibrated against experimental results and the tensile and bending mechanical stiffnesses are ultimately inferred from the spatially dependent microtubule occupancy. Such additional information is believed to be of drastic relevance in the growth cone vicinity, where biomechanical mechanisms are driving axonal growth and pathfinding. More specifically, the confirmation of a lower stiffness in the distal axon ultimately participates in explaining the controversy associated to the tensile role of the growth cone
Uso de Antibióticos y Resistencia Antimicrobiana en la Unidad de Cuidado Intensivo Neonatal
Neonatal sepsis constitutes one of the main causes of neonatal mortality in developing countries. Newborns, particularly premature newborns, have a higher risk of bacterial infections that result in frequent administration of antibiotics in the Neonatal Intensive Care Units (NICU), which is estimated to be as high as 70%. The clinical presentation of neonatal sepsis is nonspecific, prompting the early use of empirical antibiotic prescription to avoid adverse consequences in the patients. Its non-specificity characterizes it as a challenging diagnostic, this aspect led several authors to design strategies to determine which newborns are true candidates for antimicrobial therapy.
Microbiology is closely linked to clinical practice. Thus, knowing the most frequent bacteria associated with neonatalsepsis will be closely related to the antibiotic spectrum that should be used to treat it. Furthermore, knowledge on basic pharmacology is key inasmuch as the antimicrobial treatment is not innocuous and can be related to an increase in mortality and morbidity. Clinical course and maternal risk factors are associated with the expected responsible germs that are already described in multiple descriptive studies worldwide.
Indiscriminate use of broad-spectrum antibiotics for the management of newborn infections is leading to antibiotic resistance increase. At the same time, this is related to even higher rates of therapeutic failure with empiric antimicrobial treatment. Based on this, Antimicrobial Stewardship Programs play a determinant role to monitor the changes in local resistance to adjust and homogenize medical practice to regulate the use of antibiotics and mitigate the emergent andthreatening antimicrobial bacterial resistance.
La sepsis neonatal constituye una de las principales causas de mortalidad neonatal en los países en desarrollo. Los neonatos, en particular los prematuros, tienen un mayor riesgo de infecciones bacterianas, por lo que el manejo con antibióticos constituye la terapia más frecuente en la Unidad de Cuidado Intensivo Neonatal (UCIN), estimándose en hasta un 70%. La presentación clínica de la sepsis neonatal es inespecífica en muchas ocasiones, lo que hace que la antibioticoterapia empírica se inicie tempranamente para evitar consecuencias deletéreas para los pacientes; su inespecificidad la caracteriza como un reto diagnóstico, por lo que diferentes autores han diseñado estrategias para determinar neonatos candidatos a terapia antimicrobiana.
La microbiología permanece en contacto estrecho con la clínica ya que conocer los gérmenes frecuentemente asociados a la sepsis neonatal ayuda a determinar el espectro antibiótico a usar. De igual forma, el conocimiento de la farmacología antibiótica es clave puesto que el tratamiento antibiótico no es inocuo y puede asociarse a aumento de morbilidad o mortalidad. El tiempo de evolución y los factores de riesgo maternos están asociados a los gérmenes responsables esperados, ya descritos por múltiples estudios descriptivos a nivel mundial.
El uso indiscriminado de antibióticos de amplio espectro para el manejo de infecciones en los recién nacidos ha generado un aumento en la resistencia antibiótica, lo que a su vez lleva a tasas más altas de fallo terapéutico con el uso de las terapias antibióticas empíricas. A razón de lo anterior, los Programas de Vigilancia de Uso de Antibióticos juegan un papel determinante para monitorear el cambio en la resistencia a nivel local para ajustar y homogeneizar la práctica médica que logre regular el uso de antibióticos y mitigar la emergente resistencia bacteriana.
 
3D finite element formulation for mechanical-electrophysiological coupling in axonopathy
Traumatic injuries to the central nervous system (brain and spinal cord) have recently been put under the spotlight because of their devastating socio-economical cost. At the cellular scale, recent research efforts have focused on primary injuries by making use of models aimed at simulating mechanical deformation induced axonal electrophysiological functional deficits. The
overwhelming majority of these models only consider axonal stretching as a loading mode, while other modes of deformation such as crushing or mixed modes|highly relevant in spinal cord injury|are left unmodelled. To this end, we propose here a novel 3D finite element framework coupling mechanics and electrophysiology by considering the electrophysiological Hodgkin-
Huxley and Cable Theory models as surface boundary conditions introduced directly in the weak form, hence eliminating the need to geometrically account for the membrane in its electrophysiological contribution. After validation against numerical and experimental results, the approach is leveraged to model an idealised axonal dislocation injury. The results show that the sole consideration of induced longitudinal stretch following transverse loading of a
node of Ranvier is not necessarily enough to capture the extent of axonal electrophysiological
deficit and that the non-axisymmetric loading of the node participates to a larger extent to the subsequent damage. On the contrary, a similar transverse loading of internodal regions was not shown to significantly worsen with the additional consideration of the non-axisymmetric
loading mode.M.T.K., M.B. and A.J. acknowledge funding from the European Union's Seventh Framework Programme (FP7 20072013) ERC Grant Agreement No.306587. H.Y. would like to acknowledge China Regenerative Medicine Limited (CRMI) for funding and the EPSRC DTP (Award no. 1514540) for F.B.'s studentship
A numerical framework coupling finite element and meshless methods in sequential and parallel simulations
International audienceThe Finite Element Method (FEM) suffers from important drawbacks in problems involving excessive deformation of elements despite being universally applied to a wide range of engineering applications. While dynamic remeshing is often offered as the ideal solution, its computational cost, numerical noise and mathematical limitations in complex geometries are impeding its widespread use. Meshless methods (MM), however, by not relying on mesh connectivity, circumvent some of these limitations, while remaining computationally more expensive than the classic FEM. These problems in MM can be improved by coupling with FEM in a FEM-MM scheme, in which MM is used within sensitive regions that undergo large deformations while retaining the more efficient FEM for other less distorted regions. Here, we present a numerical framework combining the benefits of FEM and MM to study large deformation scenarios without heavily compromising on computational efficiency. In particular, the latter is maintained through two mechanisms: (1) coupling of FEM and MM discretisation schemes within one problem, which limits MM discretisation to domains that cannot be accurately modelled in FEM, and (2) a simplified MM parallelisation approach which allows for highly efficient speed-up. The proposed approach treats the problem as a quadrature point driven problem, thus making the treatment of the constitutive models, and thus the matrix and vector assembly fully method-agnostic. The MM scheme considers the maximum entropy (max-ent) approximation, in which its weak Kronecker delta property is leveraged in parallel calculations by convexifying the subdomains, and by refining meshes at the boundary in such a way that the higher density of nodes is mainly concentrated within the bulk of the domain. The latter ensures obtaining the Kronecker delta property at the boundary of the MM domain. The results, demonstrated by means of a few applications, show an excellent scalability and a good balance between accuracy and computational cost
A numerical framework coupling finite element and meshless methods in sequential and parallel simulations
peer reviewe