Conditions Extrêmes et Matériaux : Haute Température et Irradiation
CEMHTI - UPR3079 CNRS
utilisateur non identifié |
Login
Home
Directory
Publications
Research
Facilities
Jobs - News
Access
Past members
CERAM - M.Allix
DEFIR - P.Desgardin
MatRMag - V.Montouillout
NAFMAT - C.Ania
OR2T - O.Rozenbaum
Common Actions
High-Temperatures Facility
Particles Beams Facilities
Vibr. Spectroscopies and Planex
NMR Facility
Softwares
National and European Facilities
all the instruments
Pelletron
Positons
Performances
IBA Techniques
Implantation and Irradiation
IR-RMN in Infranalytics
PANACEA Eu
850 MHz
Diffusion
NMR
dmfit NMR
focus (IR Optics)
Levitation
Electron Microscope
XRay and Neutrons
NMR
IR emission
RAMAN
Accelerators
RAMAN in situ
RAMAN high temp.
RAMAN imaging
News@CEMHTI
Jobs@CEMHTI
Seminars@CEMHTI
View CEMHTI Publication
Return to publication search...
Ask for a reprint
email :
I am not a bot ;-)
* Give your email
2020
ACL
doi
Maxime Yon, Martine Decoville, Vincent Sarou-Kanian, Franck Fayon, Serge Birman
,
'Spatially-resolved metabolic profiling of living Drosophila in neurodegenerative conditions using 1H magic angle spinning NMR'
, Sci. Rep. 10 9516 (2020) doi:
10.1038/s41598-020-66218-z
Drosophila flies are versatile animal models for the study of gene mutations in neuronal pathologies. Their small size allows performing in vivo Magic Angle Spinning (MAS) experiments to obtain high-resolution 1H nuclear magnetic resonance (NMR) spectra. Here, we use spatially-resolved 1H high-resolution MAS NMR to investigate in vivo metabolite contents in different segments of the fly body. A comparative study of metabolic changes was performed for three neurodegenerative disorders: two cell-specific neuronal and glial models of Huntington disease (HD) and a model of glutamate excitotoxicity. It is shown that these pathologies are characterized by specific and sometimes anatomically localized variations in metabolite concentrations. In two cases, the modifications of 1H MAS NMR spectra localized in fly heads were significant enough to allow the creation of a predictive model.