Distinct patterns of dyskinetic and dystonic features following D1 or D2 receptor stimulation in a mouse model of parkinsonism.

L-DOPA-induced dyskinesia (LID) is a significant complication of dopamine replacement therapy in Parkinson's disease (PD), and the specific role of different dopamine receptors in this disorder is poorly understood. We set out to compare patterns of dyskinetic behaviours induced by the systemic administration of L-DOPA and D1 or D2 receptor (D1R, D2R) agonists in mice with unilateral 6-hydroxydopamine lesions. Mice were divided in four groups to receive increasing doses of L-DOPA, a D1R agonist (SKF38393), a D2/3 agonist (quinpirole), or a selective D2R agonist (sumanirole). Axial, limb and orofacial abnormal involuntary movements (AIMs) were rated using a well-established method, while dystonic features were quantified in different body segments using a new rating scale. Measures of abnormal limb and trunk posturing were extracted from high-speed videos using a software for markerless pose estimation (DeepLabCut). While L-DOPA induced the full spectrum of dyskinesias already described in this mouse model, SKF38393 induced mostly orofacial and limb AIMs. By contrast, both of the D2-class agonists (quinpirole, sumanirole) induced predominantly axial AIMs. Dystonia ratings revealed that these agonists elicited marked dystonic features in trunk/neck, forelimbs, and hindlimbs, which were overall more severe in sumanirole-treated mice. Accordingly, sumanirole induced pronounced axial bending and hindlimb divergence in the automated video analysis. In animals treated with SKF38393, the only appreciable dystonic-like reaction consisted in sustained tail dorsiflexion and stiffness. We next compared the effects of D1R or D2R selective antagonists in L-DOPA-treated mice, where only the D2R antagonist had a significant effect on dystonic features. Taken together these results indicate that the dystonic components of LID are predominantly mediated by the D2R.

A Transient Survival Model of Alteration of Electrophysiological Properties Due to Amyloid Beta Toxicity Based on SH-SY5Y Cell Line.

BACKGROUND: Accumulation of toxic strands of amyloid beta (AB), which cause neurofibrillary tangles and, ultimately, cell death, is suspected to be the main culprit behind clinical symptoms of Alzheimer's disease. Although the mechanism of cell death due to AB accumulation is well known, the intermediate phase between the start of accumulation and cell death is less known and investigated, partially due to technical challenges in identifying partially affected cells. OBJECTIVE: First, we aimed to establish an in vitro model that would show resilience against AB toxicity. Then we used morphological, molecular and electrophysiological assays to investigate how the characteristics of the surviving cells changed after AB toxicity. METHODS: To investigate this phase, we used differentiation of SH-SY5Y neuroblastoma stem cells by Retinoic Acid (RA) and Brain Derived Neurotrophic Factor (BDNF) to establish an in vitro model which would be able to demonstrate various levels of resistance to AB toxicity. We utilized fluorescent microscopy and whole cell patch clamp recordings to investigate behavior of the model. RESULTS: We observed significantly higher morphological resilience against AB toxicity in cells which were differentiated by both Retinoic Acid and Brain Derived Neurotrophic Factor compared to Retinoic Acid only. However, the electrophysiological properties of the Retinoic Acid + Brain-Derived Neurotrophic Factor differentiated cells were significantly altered after AB treatment. CONCLUSION: We established a transient survival model for AB toxicity and observed the effects of AB on transmembrane currents of differentiated neurons.

Tracking Rats in Operant Conditioning Chambers Using a Versatile Homemade Video Camera and DeepLabCut.

Operant conditioning chambers are used to perform a wide range of behavioral tests in the field of neuroscience. The recorded data is typically based on the triggering of lever and nose-poke sensors present inside the chambers. While this provides a detailed view of when and how animals perform certain responses, it cannot be used to evaluate behaviors that do not trigger any sensors. As such, assessing how animals position themselves and move inside the chamber is rarely possible. To obtain this information, researchers generally have to record and analyze videos. Manufacturers of operant conditioning chambers can typically supply their customers with high-quality camera setups. However, these can be very costly and do not necessarily fit chambers from other manufacturers or other behavioral test setups. The current protocol describes how to build an inexpensive and versatile video camera using hobby electronics components. It further describes how to use the image analysis software package DeepLabCut to track the status of a strong light signal, as well as the position of a rat, in videos gathered from an operant conditioning chamber. The former is a great aid when selecting short segments of interest in videos that cover entire test sessions, and the latter enables analysis of parameters that cannot be obtained from the data logs produced by the operant chambers.