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| Titel: |
Modeling early Parkinson's disease pathology with chronic low dose MPTP treatment |
| Auteur: |
Korecka, Joanna A. Eggers, Ruben Swaab, Dick F. Bossers, Koen Verhaagen, Joost |
| Verschenen in: |
Restorative neurology and neuroscience |
| Paginering: | Jaargang 31 (2012) nr. 2 pagina's 155-167 |
| Jaar: |
2012-12-27 |
| Inhoud: |
Purpose: Parkinson's disease (PD) is a movement disorder mainly characterized by progressive neurodegeneration of dopaminergic (DAergic) neurons in the substantia nigra (SN). As yet, unknown molecular changes contribute to the development of PD leading to a great need for in vivo models that herald this disorder. Here we characterize an animal model presenting early PD pathology. Methods: Young, adult C57/BL6 mice were treated for five weeks twice a week with 15 mg/kg 1-methyl-4-phenyl1,2,3,6-tetrahydropyridine (MPTP) in combination with 250 mg/kg probenecid. During the treatment mice were tested on their dopamine dependent movement skills. The integrity of their nigrostriatal system was examined through immunohistochemical studies. Results: During the treatment, mice developed dopamine-dependent movement deficits induced by loss of tyrosine hydroxylase (TH) positive nigrostriatal axon terminals. Immunohistochemical study identified astrogliosis and microgliosis in the SN but no decrease of TH immunostaining, demonstrating lack of DAergic neuron degeneration. We also observed formation of α-synuclein inclusion bodies in the SN. Conclusions: The combined features of this MPTP model appear to represent an early neurotoxic cellular stress to the SN neurons bearing a striking resemblance to the early stages of PD neuropathology. This model might prove very useful to investigate early neurodegenerative events in the nigrostriatal DAergic system and to study the effects of potential treatment strategies counteracting the early PD cellular changes. |
| Uitgever: |
IOS Press |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
Details van artikel 8 van 11 gevonden artikelen
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