No abstract

We developed a measure of pericyte/endothelial interaction, the desmin ensheathment ratio (DER), using the intermediate filament desmin as an indicator of pericyte ensheathment and have examined the DER in normal retinal vascular development and in the kitten retinopathy of prematurity (ROP) model. We also examined the role of mural cells in the pathogenesis of ROP. Postnatal day 1 to 45 kitten retinae were labeled for desmin, alpha-smooth muscle actin (SMA), and isolectin-B4. Newborn kittens exposed to hyperoxia and then returned to room air for 0 to 40 days (dRA) were similarly labeled. The ratio of desmin to lectin labeling on confocal images yielded the DER. Ultrastructural studies showed that mural cells were present on even the most primitive vessels. During normal development, immature vascular beds had DERs of 0.3 to 0.6 whereas mature beds, which predominated by postnatal day 28, had DERs greater than 0.9. Immature pericytes and smooth muscle cells did not prevent hyperoxia-induced vessel regression. During the vasoproliferative stage of ROP, the DERs of intra- and preretinal vessels ranged between 0.2 and 0.5. In the recovery stage, the DER increased in parallel with regression of pathology, reaching 0.9 at 34 dRA. Stabilization of the DER by the fifth postnatal week was temporally coincident with the development of resistance to hyperoxia-induced vessel regression previously reported in the kitten. These observations lead us to suggest that a DER of 0.9 represents a vascular stability threshold and that a low DER observed during ROP raises the possibility that mural cell abnormalities play a key role in the pathogenesis of ROP.

Symptoms of voice disorder may range from slight hoarseness to complete loss of voice; from modest vocal effort to uncomfortable neck pain. But even minor symptoms may still impact personal and especially professional lives. While early detection and diagnosis can ameliorate that effect, to date, we are still largely missing reliable and valid data to help us better screen for voice disorders. In our previous study, we started to address this gap in research by introducing an ambulatory voice monitoring system using surface electromyography (sEMG) and a robust algorithm (HiGUSSS) for pattern recognition of vocal gestures. Here, we expand on that work by further analyzing a larger set of simulated vocal dysfunctions. Our goal is to demonstrate that such a system has the potential to recognize and detect real vocal dysfunctions from multiple individuals with high accuracy under both intra and intersubject conditions. The proposed system relies on four sEMG channels to simultaneously process various patterns of sEMG activation in the search for maladaptive laryngeal activity that may lead to voice disorders. In the results presented here, our pattern recognition algorithm detected from two to ten different classes of sEMG patterns of muscle activation with an accuracy as high as 99%, depending on the subject and the testing conditions.

No abstract