Molecular Studies on the Interaction of Leptin With Its Receptor

Leptin is a hormonal protein involved in energy homeostasis, acting to inhibit food intake, stimulate energy expenditure and influence insulin secretion, lipo-lysis and sugar transport. Its action is mediated by a specific receptor whose activation is highly controversial. As a member of the cytokine receptor super-family, it has been predicted to be activated by ligand-induced dimerization. However, recent evidence has suggested that this receptor exists as a dimer in both ligand-free and ligand-bound states. The aim of this project was to determine the kinetics and stoichiometry of leptin receptor interaction with its ligand, using a variety of biophysical techniques, namely BiaCore and microcalorimetry. To achieve this, it was necessary to express the leptin receptor. Because the receptor cDNA was not available at the start of this project, the initial goal was to obtain the cDNA encoding the extracellular domain of the receptor by RT-PCR. The open reading frame consisting of 839 a.a. encoded by 2517 nucleotides was generated by several molecular approaches, as the mRNA is a rare species. To generate large amounts of the receptor required for microcalorimetry, Baculovirus expression system for the leptin receptor production was devel-oped. At the same time BiaCore analysis of the interaction was performed since it requires small amounts of protein, and commercially available protein could be used. BiaCore was used to measure the thermodynamics of the interaction. Hu-man or mouse receptor chimeras comprising two receptor extracellular domains fused to the Fc region of IgGI were captured on to the sensor via Protein G. The kinetics and stoichiometry of interactions with human, mouse or rat lep-tin were measured. This data demonstrated a high affinity interaction. The KD was 0.2 +/- 0.1 nM, with ka = (1.9 +/- 0.4) x10e6 M-1s-1 and kd = (4.6 +/- 0.9) x10e-4 s-1 for human leptin with its cognate receptor. The observed stoichiometry was 1:1. Little difference was observed for different species of leptin. Thus, leptin forms a very stable 1:1 complex with its receptor. This observation indicates that the leptin receptor oligomerization state is not altered during its interaction with a ligand. This contradicts the common paradigm of cytokine receptor activation. A truncated version of the leptin molecule with deleted glutamine at position 28 was also expressed in E. coli. Its affinity for human and mouse leptin receptor chimeras was analysed by BiaCore, which revealed a 10-fold decrease in affinity, indicating a possible involvement of Q28 in binding

Patient-Specific Virtual Insertion of Electrode Array for Electrical Simulations of Cochlear Implants

International audienceSensorineural hearing loss is becoming one the most common reasons of disability. Worldwide 278 million people (around 25% of people above 45 years) suffer from moderate to several hearing disorders. Cochlear implantation (CI) enables to convert sound to an electrical signal that directly stimulates the auditory nerves via the electrode array surgically placed. However, this technique is intrinsically patient-dependent and its range of outcomes is very broad. A major source of outcome variability resides in the electrode array insertion. It has been reported to be one of the most important steps in cochlear implant surgery. In this context, we propose a method for patient-specific virtual electrode insertion further used into a finite element electrical simulation, and consequently improving the planning of the surgical implantation. The anatomical parameters involved in the electrode insertion such as the curvature and the number of turns of the cochlea, make virtual insertion highly challenging. Moreover, the influence of the insertion parameters and the use of different manufactured electrode arrays increase the range of scenarios to be considered for the implantation of a given patient. To this end, the method we propose is fast, easily parameterizable and applicable to a wide range of anatomies and insertion configurations. Our method is novel for targeting automatic virtual electrode insertion. Also, it combines high-resolution imaging techniques and clinical data to be further used into a finite element study and predict implantation outcomes in humans

Virtual cochlear electrode insertion via parallel transport frame

International audienceWe present an automatic, fast and parametrizable algorithm to perform the virtual insertion of a cochlear electrode array into a pre-existent mesh of the human cochlea. Our method reorients the electrode according to the parallel transport frame, a local parameterization of the cochlear centerline directions, robust to the centerline curvature changes. It allows to control the initial roll angle and the extension of insertion from full to partial. Such a virtual insertion, chained with finite element simulations on the electrical activity of the electrode and the cochlear nerves, will enable to test in silico the effects of implant design and positioning on a given patient, and optimize these parameters accordingly

Automatic Generation of a Computational Model for Monopolar Stimulation of Cochlear Implants

International audienceCochlear implants have the potential to significantly improve severe sensorineural hearing loss. However, the outcome of this technique is highly variable and depends on patient-specific factors. We previously proposed a method for patient-specific electrical simulation after CI, which can assist in surgical planning of the CI and determination of the electrical stimulation pattern. However, the virtual implant placement and mesh generation were carried out manually and the process was not easily applied automatically for further cochlear anatomies. Moreover, in order to optimize the implant designs, it is important to develop a way to stimulate the results of the implantation in a population of virtual patients. In this work we propose an automatic framework for patient-specific electrical simulation in CI surgery. To the best of our knowledge, this is the first method proposed for patient-specific generation of hearing models which combines high-resolution imaging techniques, clinical CT data and virtual electrode insertion. Furthermore, we show that it is possible to use the computational models of virtual patients to simulate the results of the electrical activation of the implant in the cochlea and surrounding bone. This is an important step because it allows us to advance towards a complete surgical planning and implant optimization procedure

Perturbation of RNA Polymerase I transcription machinery by ablation of HEATR1 triggers the RPL5/RPL11-MDM2-p53 ribosome biogenesis stress checkpoint pathway in human cells

<p>Ribosome biogenesis is an energy consuming process which takes place mainly in the nucleolus. By producing ribosomes to fuel protein synthesis, it is tightly connected with cell growth and cell cycle control. Perturbation of ribosome biogenesis leads to the activation of p53 tumor suppressor protein promoting processes like cell cycle arrest, apoptosis or senescence. This ribosome biogenesis stress pathway activates p53 through sequestration of MDM2 by a subset of ribosomal proteins (RPs), thereby stabilizing p53. Here, we identify human HEATR1, as a nucleolar protein which positively regulates ribosomal RNA (rRNA) synthesis. Downregulation of HEATR1 resulted in cell cycle arrest in a manner dependent on p53. Moreover, depletion of HEATR1 also caused disruption of nucleolar structure and activated the ribosomal biogenesis stress pathway – RPL5 / RPL11 dependent stabilization and activation of p53. These findings reveal an important role for HEATR1 in ribosome biogenesis and further support the concept that perturbation of ribosome biosynthesis results in p53-dependent cell cycle checkpoint activation, with implications for human pathologies including cancer.</p

Towards a complete in silico assessment of the outcome of cochlear implantation surgery

Cochlear implantation (CI) surgery is a very successful technique, performed on more than 300,000 people worldwide. However, since the challenge resides in obtaining an accurate surgical planning, computational models are considered to provide such accurate tools. They allow us to plan and simulate beforehand surgical procedures in order to maximally optimize surgery outcomes, and consequently provide valuable information to guide pre-operative decisions. The aim of this work is to develop and validate computational tools to completely assess the patient-specific functional outcome of the CI surgery. A complete automatic framework was developed to create and assess computationally CI models, focusing on the neural response of the auditory nerve fibers (ANF) induced by the electrical stimulation of the implant. The framework was applied to evaluate the effects of ANF degeneration and electrode intra-cochlear position on nerve activation. Results indicate that the intra-cochlear positioning of the electrode has a strong effect on the global performance of the CI. Lateral insertion provides better neural responses in case of peripheral process degeneration, and it is recommended, together with optimized intensity levels, in order to preserve the internal structures. Overall, the developed automatic framework provides an insight into the global performance of the implant in a patient-specific way. This enables to further optimize the functional performance and helps to select the best CI configuration and treatment strategy for a given patient.This work was financially supported by the European Commission (FP7 project number 304857, HEAR-EU), Generalitat de Catalunya (PRODUCTE program, project number 2016PROD00047) and the Spanish Ministry of Economy and Competitiveness under the Maria de Maeztu Units of Excellence Programme (MDM-2015-0502)

Computational evaluation of cochlear implant surgery outcomes accounting for uncertainty and parameter variability

Cochlear implantation (CI) is a complex surgical procedure that restores hearing in patients with severe deafness. The successful outcome of the implanted device relies on a group of factors, some of them unpredictable or difficult to control. Uncertainties on the electrode array position and the electrical properties of the bone make it difficult to accurately compute the current propagation delivered by the implant and the resulting neural activation. In this context, we use uncertainty quantification methods to explore how these uncertainties propagate through all the stages of CI computational simulations. To this end, we employ an automatic framework, encompassing from the finite element generation of CI models to the assessment of the neural response induced by the implant stimulation. To estimate the confidence intervals of the simulated neural response, we propose two approaches. First, we encode the variability of the cochlear morphology among the population through a statistical shape model. This allows us to generate a population of virtual patients using Monte Carlo sampling and to assign to each of them a set of parameter values according to a statistical distribution. The framework is implemented and parallelized in a High Throughput Computing environment that enables to maximize the available computing resources. Secondly, we perform a patient-specific study to evaluate the computed neural response to seek the optimal post-implantation stimulus levels. Considering a single cochlear morphology, the uncertainty in tissue electrical resistivity and surgical insertion parameters is propagated using the Probabilistic Collocation method, which reduces the number of samples to evaluate. Results show that bone resistivity has the highest influence on CI outcomes. In conjunction with the variability of the cochlear length, worst outcomes are obtained for small cochleae with high resistivity values. However, the effect of the surgical insertion length on the CI outcomes could not be clearly observed, since its impact may be concealed by the other considered parameters. Whereas the Monte Carlo approach implies a high computational cost, Probabilistic Collocation presents a suitable trade-off between precision and computational time. Results suggest that the proposed framework has a great potential to help in both surgical planning decisions and in the audiological setting process

Computational evaluation of Cochlear implant surgery outcomes accounting for uncertainty and parameter variability

Cochlear implantation (CI) is a complex surgical procedure that restores hearing in patients with severe deafness. The successful outcome of the implanted device relies on a group of factors, some of them unpredictable or difficult to control. Uncertainties on the electrode array position and the electrical properties of the bone make it difficult to accurately compute the current propagation delivered by the implant and the resulting neural activation. In this context, we use uncertainty quantification methods to explore how these uncertainties propagate through all the stages of CI computational simulations. To this end, we employ an automatic framework, encompassing from the finite element generation of CI models to the assessment of the neural response induced by the implant stimulation. To estimate the confidence intervals of the simulated neural response, we propose two approaches. First, we encode the variability of the cochlear morphology among the population through a statistical shape model. This allows us to generate a population of virtual patients using Monte Carlo sampling and to assign to each of them a set of parameter values according to a statistical distribution. The framework is implemented and parallelized in a High Throughput Computing environment that enables to maximize the available computing resources. Secondly, we perform a patient-specific study to evaluate the computed neural response to seek the optimal post-implantation stimulus levels. Considering a single cochlear morphology, the uncertainty in tissue electrical resistivity and surgical insertion parameters is propagated using the Probabilistic Collocation method, which reduces the number of samples to evaluate. Results show that bone resistivity has the highest influence on CI outcomes. In conjunction with the variability of the cochlear length, worst outcomes are obtained for small cochleae with high resistivity values. However, the effect of the surgical insertion length on the CI outcomes could not be clearly observed, since its impact may be concealed by the other considered parameters. Whereas the Monte Carlo approach implies a high computational cost, Probabilistic Collocation presents a suitable trade-off between precision and computational time. Results suggest that the proposed framework has a great potential to help in both surgical planning decisions and in the audiological setting process.This work was partly supported by the Spanish Ministry of Economy and Competitiveness under the Maria de Maeztu Units of Excellence Program (MDM-2015-0502), by the AGAUR grant 2016-PROD-00047, the European Union Seventh Framework Program (FP7/2007-2013), Grant agreement 304857, HEAR-EU project and the QUAES Foundation Chair for Computational Technologies for Healthcare

Finite element model for patient-specific functional simulations of cochlear implants

We present an innovative image analyisis pipeline to perform/npatient-speci c biomechanical and functional simulations of the inner human/near. A high-resolution, cadaveric, mCT volumetric image portraying/nthe detailed geometry of the cochlea is converted into a mesh in order to/nbuild a Finite Element Method (FEM). The constitutive model for the/nFEM is based on a Navier-Stokes formulation for compressible Newtonian/n/nuid, coupled with an elastic solid model. The simulation includes/n/nuid-structure interactions. Further to this, the FEM mesh is deformed/nto a patient-speci c low-resolution Cone Beam CT (CBCT) dataset to/npropagate functional information to the speci c anatomy of the patient./nIllustrative results of how the FE-model responds to various acoustic/nstimuli are shown by analyzing the tonotopic mapping of the cochlear/nmembrane vibration.The research leading to HEAR-EU results has received funding from the European/nUnion Seventh Frame Programme (FP7/2007-2013) under grant agreement/nno. 30485