The movement disorder in Parkinson's disease results from the selective degeneration of a small group of dopaminergic neurons in the substantia nigra pars compacta region of the brain. A number of exploratory studies using human fetal tissue allografts have suggested that transplantation of dopaminergic neurons may become an effective treatment for patients with Parkinson's disease and the difficulty in obtaining human fetal tissue has generated interest in finding corresponding non-human donor cells. Here we report a post-mortem histological analysis of fetal pig neural cells that were placed unilaterally into the caudate-putamen brain region of a patient suffering from Parkinson's disease. Long-term (over seven months) graft survival was found and the presence of pig dopaminergic neurons and other pig neural and glial cells is documented. Pig neurons extended axons from the graft sites into the host brain. Furthermore, other graft derived cells were observed several millimeters from the implantation sites. Markers for human microglia and T-cells showed only low reactivity in direct proximity to the grafts. This is the first documentation of neural xenograft survival in the human brain and of appropriate growth of non-human dopaminergic neurons for a potential therapeutic response in Parkinson's disease.

The Clock Drawing Test – a simple pencil and paper test – has been used for more than 50 years as a screening tool to differentiate normal individuals from those with cognitive impairment, and has proven useful in helping to diagnose cognitive dysfunction associated with neurological disorders such as Alzheimer’s disease, Parkinson’s disease, and other dementias and conditions. We have been administering the test using a digitizing ballpoint pen that reports its position with considerable spatial and temporal precision, making available far more detailed data about the subject’s performance. Using pen stroke data from these drawings categorized by our software, we designed and computed a large collection of features, then explored the tradeoffs in performance and interpretability in classifiers built using a number of different subsets of these features and a variety of different machine learning techniques. We used traditional machine learning methods to build prediction models that achieve high accuracy. We operationalized widely used manual scoring systems so that we could use them as benchmarks for our models. We worked with clinicians to define guidelines for model interpretability, and constructed sparse linear models and rule lists designed to be as easy to use as scoring systems currently used by clinicians, but more accurate. While our models will require additional testing for validation, they offer the possibility of substantial improvement in detecting cognitive impairment earlier than currently possible, a development with considerable potential impact in practice.

Unilateral transplantation of porcine embryonic VM cells into PD patients was well tolerated with no evidence of transmission of porcine endogenous retrovirus. Changes in standardized clinical PD rating measures were variable, similar to the results of the first trials of unilateral human embryonic allografts that transplanted small amounts of tissue.

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