Wallerian degeneration in the optic nerve stretch-injury model of traumatic brain injury: a stereological analysis.

Patients with chronic traumatic encephalopathy (CTE) show loss of central white matter, central gray matter, and cortical gray matter with increasing post-traumatic survival. The majority of experimental studies using animals have, however, discussed only the ultrastructural pathophysiology of injured central white matter leading to secondary axotomy and the formation of axonal terminal bulbs. Using the stretch-injured optic nerve model in adult guinea pigs, the present study provides novel quantitative data concerning Wallerian degeneration of disconnected axonal fragments following secondary axotomy out to 12 weeks after injury to an optic nerve. The time course of Wallerian degeneration at the level of an individual nerve fiber is comparable to that reported in earlier studies over 48 h to two weeks after secondary axotomy. But only a relatively small proportion of nerve fibers within the optic tract degenerate via Wallerian degeneration during the first two weeks. Rather, examples of each of the three stages of Wallerian degeneration-acute axonal degeneration, latency of the distal axonal segment, and granular fragmentation-occur within the optic tract across the entire experimental survival of 12 weeks used in the present study. This data suggests that some nerve fibers initiate Wallerian degeneration days and weeks after the initial time of mechanical injury to an optic nerve. The number of intact nerve fibers continues to fall over at least three months after injury in the stretch-injury model of traumatic axonal injury. It is suggested that these novel findings relate to the mechanism(s) whereby central white matter volume decreases over months and years in CTE patients.

Evaluating home range techniques: use of Global Positioning System (GPS) collar data from chacma baboons.

Global Positioning System (GPS) collars have revolutionized the field of spatial ecology, but to date, few primate studies have used them. We fitted a free-ranging, semi-habituated, juvenile male chacma baboon (Papio hamadryas ursinus) with an automatic self-releasing GPS collar and tracked his movements for 359 days. The collar captured 4254 fixes out of 5719 programmed opportunities, a 74.4 % acquisition rate, suggesting that the collar effectively tracked this baboon in a variety of habitat types. Of the data points captured, 73.7 % were three-dimensional fixes, and of these fixes, 66.9 % were highly accurate, having a dilution of precision of less than four. We calculated home range using three protocols with three estimation methods: minimum convex polygon, fixed kernel-density estimation (KDE), and fixed r local convex hull. Using all data points and the 95 % contour, these methods created home range estimations ranging from 10.8 to 23.1 km(2) for this baboon troop. Our results indicate that the KDE output using all data locations most accurately represented our data set, as it created a continuous home range boundary that excluded unused areas and outlying, potentially exploratory data points while including all seven sleeping sites and a movement corridor. However, home range estimations generated from KDE varied from 15.4 to 18.8 km(2) depending on the smoothing parameter used. Our results demonstrated that the ad hoc smoothing parameter selection technique was a better method for our data set than either the least squares cross-validation or biased cross-validation techniques. Our results demonstrate the need for primatologists to develop a standardized reporting method which documents the tool, screening protocol, and smoothing parameter used in the creation of home range estimations in order to make comparisons that are meaningful.