Huntington's disease (HD) is an inherited neurodegenerative disease caused by expansion of a polyglutamine tract in the huntingtin protein. Transcriptional dysregulation has been implicated in HD pathogenesis. Here, we report that huntingtin interacts with the transcriptional activator Sp1 and coactivator TAFII130. Coexpression of Sp1 and TAFII130 in cultured striatal cells from wild-type and HD transgenic mice reverses the transcriptional inhibition of the dopamine D2 receptor gene caused by mutant huntingtin, as well as protects neurons from huntingtin-induced cellular toxicity. Furthermore, soluble mutant huntingtin inhibits Sp1 binding to DNA in postmortem brain tissues of both presymptomatic and affected HD patients. Understanding these early molecular events in HD may provide an opportunity to interfere with the effects of mutant huntingtin before the development of disease symptoms.

This paper presents the results of a pilot study to assess the feasibility of using accelerometer data to estimate the severity of symptoms and motor complications in patients with Parkinson's disease. A support vector machine (SVM) classifier was implemented to estimate the severity of tremor, bradykinesia and dyskinesia from accelerometer data features. SVM-based estimates were compared with clinical scores derived via visual inspection of video recordings taken while patients performed a series of standardized motor tasks. The analysis of the video recordings was performed by clinicians trained in the use of scales for the assessment of the severity of Parkinsonian symptoms and motor complications. Results derived from the accelerometer time series were analyzed to assess the effect on the estimation of clinical scores of the duration of the window utilized to derive segments (to eventually compute data features) from the accelerometer data, the use of different SVM kernels and misclassification cost values, and the use of data features derived from different motor tasks. Results were also analyzed to assess which combinations of data features carried enough information to reliably assess the severity of symptoms and motor complications. Combinations of data features were compared taking into consideration the computational cost associated with estimating each data feature on the nodes of a body sensor network and the effect of using such data features on the reliability of SVM-based estimates of the severity of Parkinsonian symptoms and motor complications.

We describe a novel mechanism for vital fluorescent dye entry into sensory cells and neurons: permeation through ion channels. In addition to the slow conventional uptake of styryl dyes by endocytosis, small styryl dyes such as FM1-43 rapidly and specifically label hair cells in the inner ear by entering through open mechanotransduction channels. This labeling can be blocked by pharmacological or mechanical closing of the channels. This phenomenon is not limited to hair cell transduction channels, because human embryonic kidney 293T cells expressing the vanilloid receptor (TRPV1) or a purinergic receptor (P2X₂) rapidly take up FM1-43 when those receptor channels are opened and not when they are pharmacologically blocked. This channel permeation mechanism can also be used to label many sensory cell typesin vivo. A single subcutaneous injection of FM1-43 (3 mg/kg body weight) in mice brightly labels hair cells, Merkel cells, muscle spindles, taste buds, enteric neurons, and primary sensory neurons within the cranial and dorsal root ganglia, persisting for several weeks. The pattern of labeling is specific; nonsensory cells and neurons remain unlabeled. The labeling of the sensory neurons requires dye entry through the sensory terminal, consistent with permeation through the sensory channels. This suggests that organic cationic dyes are able to pass through a number of different sensory channels. The bright and specific labeling with styryl dyes provides a novel way to study sensory cells and neuronsin vivoandin vitro,and it offers new opportunities for visually assaying sensory channel function.