Search results for "FAP"
showing 10 items of 30 documents
Coexpresión de NG2/GFAP tras la diferenciación en células transfectadas con las mutaciones de GFAP y en células procedentes de gliomas indiferenciados
2020
Resumen: Introducción: La enfermedad de Alexander es una enfermedad rara causada por mutaciones en el gen que codifica la proteína glial ácida fibrilar (GFAP). En un estudio previo hemos observado que la diferenciación de neuroesferas transfectadas con estas mutaciones genera un tipo celular que comparte la expresión de GFAP y NG2. Objetivos: Determinar el efecto de las mutaciones en marcadores moleculares en comparación con células de glioma diferenciados que expresan simultáneamente GFAP y NG2. Métodos: Se utilizaron muestras de glioblastoma humana (GLM) y neuroesferas procedentes de rata transfectadas con mutaciones de GFAP para el análisis de la expresión tras diferenciación de GFAP y N…
Somatic copy number alterations are associated with EGFR amplification and shortened survival in patients with primary glioblastoma.
2019
Glioblastoma (GBM) is the most common malignant primary tumor of the central nervous system. With no effective therapy, the prognosis for patients is terrible poor. It is highly heterogeneous and EGFR amplification is its most frequent molecular alteration. In this light, we aimed to examine the genetic heterogeneity of GBM and to correlate it with the clinical characteristics of the patients. For that purpose, we analyzed the status of EGFR and the somatic copy number alterations (CNAs) of a set of tumor suppressor genes and oncogenes. Thus, we found GBMs with high level of EGFR amplification, low level and with no EGFR amplification. Highly amplified tumors showed histological features of…
Transthyretin familial amyloid polyneuropathy (TTR‐FAP): Parameters for early diagnosis
2017
Abstract Background Familial transthyretin amyloidosis is a life‐threatening disease presenting with sensorimotor and autonomic polyneuropathy. Delayed diagnosis has a detrimental effect on treatment and prognosis. To facilitate diagnosis, we analyzed data patterns of patients with transthyretin familial amyloid polyneuropathy (TTR‐FAP) and compared them to polyneuropathies of different etiology for clinical and electrophysiological discriminators. Methods Twenty‐four patients with TTR‐FAP and 48 patients with diabetic polyneuropathy (dPNP) were investigated (neurological impairment score NIS; neurological disability score NDS) in a cross‐sectional design. Both groups were matched for gende…
Cellular Response to Spinal Cord Injury in Regenerative and Non-Regenerative Stages in Xenopus Laevis
2020
Abstract Background The efficient regenerative abilities at larvae stages followed by a non-regenerative response after metamorphosis in froglets makes Xenopus an ideal model organism to understand the cellular responses leading to spinal cord regeneration. Methods We compared the cellular response to spinal cord injury between the regenerative and non-regenerative stages of Xenopus laevis. For this analysis, we used electron microscopy, immunofluorescence and histological staining of the extracellular matrix. We generated two transgenic lines: i) the reporter line with the zebrafish GFAP regulatory regions driving the expression of EGFP, and ii) a cell specific inducible ablation line with…
Alexander Disease Mutations Produce Cells with Coexpression of Glial Fibrillary Acidic Protein and NG2 in Neurosphere Cultures and Inhibit Differenti…
2017
Background Alexander disease (AxD) is a rare disease caused by mutations in the gene encoding glial fibrillary acidic protein (GFAP). The disease is characterized by presence of GFAP aggregates in the cytoplasm of astrocytes and loss of myelin. Objectives Determine the effect of AxD-related mutations on adult neurogenesis. Methods We transfected different types of mutant GFAP into neurospheres using the nucleofection technique. Results We find that mutations may cause coexpression of GFAP and NG2 in neurosphere cultures, which would inhibit the differentiation of precursors into oligodendrocytes and thus explain the myelin loss occurring in the disease. Transfection produces cells that diff…
GEOV1: LAI, FAPAR essential climate variables and FCOVER global time series capitalizing over existing products. Part 2: Validation and intercomparis…
2013
International audience; This paper describes the scientific validation of the first version of global biophysical products (i.e., leaf area index, fraction of absorbed photosynthetically active radiation and fraction of vegetation cover), namely GEOV1, developed in the framework of the geoland-2/BioPar core mapping service at 1 km spatial resolution and 10-days temporal frequency. The strategy follows the recommendations of the CEOS/WGCV Land Product Validation for LAI global products validation. Several criteria of performance were evaluated, including continuity, spatial and temporal consistency, dynamic range of retrievals, statistical analysis per biome type, precision and accuracy. The…
Targeting fibroblast activation protein (FAP): next generation PET radiotracers using squaramide coupled bifunctional DOTA and DATA5m chelators
2020
Abstract Background Fibroblast activation protein (FAP) is a proline selective serine protease that is overexpressed in tumor stroma and in lesions of many other diseases that are characterized by tissue remodeling. In 2014, a most potent FAP-inhibitor (referred to as UAMC1110) with low nanomolar FAP-affinity and high selectivity toward related enzymes such as prolyl oligopeptidase (PREP) and the dipeptidyl-peptidases (DPPs): DPP4, DPP8/9 and DPP2 were developed. This inhibitor has been adopted recently by other groups to create radiopharmaceuticals by coupling bifunctional chelator-linker systems. Here, we report squaric acid containing bifunctional DATA5m and DOTA chelators relied on UAMC…
Climate Data Records of Vegetation Variables from Geostationary SEVIRI/MSG Data: Products, Algorithms and Applications
2019
The scientific community requires long-term data records with well-characterized uncertainty and suitable for modeling terrestrial ecosystems and energy cycles at regional and global scales. This paper presents the methodology currently developed in EUMETSAT within its Satellite Application Facility for Land Surface Analysis (LSA SAF) to generate biophysical variables from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on board MSG 1-4 (Meteosat 8-11) geostationary satellites. Using this methodology, the LSA SAF generates and disseminates at a time a suite of vegetation products, such as the leaf area index (LAI), the fraction of the photosynthetically active radiation absorbed …
NG2 and GFAP co-expression after differentiation in cells transfected with mutant GFAP and in undifferentiated glioma cells
2020
Introduction: Alexander disease is a rare disorder caused by mutations in the gene coding for glial fibrillary acidic protein (GFAP). In a previous study, differentiation of neurospheres transfected with these mutations resulted in a cell type that expresses both GFAP and NG2. Objective: To determine the effect of molecular marker mutations in comparison to undifferentiated glioma cells simultaneously expressing GFAP and NG2. Methods: We used samples of human glioblastoma (GBM) and rat neurospheres transfected with GFAP mutations to analyse GFAP and NG2 expression after differentiation. We also performed an immunocytochemical analysis of neuronal differentiation for both cell types and dete…
Integrating Domain Knowledge in Data-Driven Earth Observation With Process Convolutions
2022
The modelling of Earth observation data is a challenging problem, typically approached by either purely mechanistic or purely data-driven methods. Mechanistic models encode the domain knowledge and physical rules governing the system. Such models, however, need the correct specification of all interactions between variables in the problem and the appropriate parameterization is a challenge in itself. On the other hand, machine learning approaches are flexible data-driven tools, able to approximate arbitrarily complex functions, but lack interpretability and struggle when data is scarce or in extrapolation regimes. In this paper, we argue that hybrid learning schemes that combine both approa…