Human Dental Pulp Fibroblasts Express the “Cold-sensing” Transient Receptor Potential Channels TRPA1 and TRPM8

Introduction: Transient receptor potential (TRP) channels comprise a group of nonselective calcium-permeable cationic channels, which are polymodal sensors of environmental stimuli such as thermal changes and chemicals. TRPM8 and TRPA1 are cold-sensing TRP channels activated by moderate cooling and noxious cold temperatures, respectively. Both receptors have been identified in trigeminal ganglion neurones, and their expression in nonneuronal cells is now the focus of much interest. The aim of this study was to investigate the molecular and functional expression of TRPA1 and TRPM8 in dental pulp fibroblasts.
Methods: Human dental pulp fibroblasts were derived from healthy molar teeth. Gene and protein expression was determined by polymerase chain reaction and Western blotting. Cellular localization was investigated by immunohistochemistry, and TRP functionality was determined by Ca2+ microfluorimetry.
Results: Polymerase chain reaction and Western blotting showed gene and protein expression of both TRPA1 and TRPM8 in fibroblast cells in culture. Immunohistochemistry studies showed that TRPA1 and TRPM8 immunoreactivity co-localized with the human fibroblast surface protein. In Ca2+ microfluorimetry studies designed to determine the functionality of TRPA1 and TRPM8 in pulp fibroblasts, we showed increased intracellular calcium ([Ca2+]i) in response to the TRPM8 agonist menthol, the TRPA1 agonist cinnamaldehyde, and to cool and noxious cold stimuli, respectively. The responses to agonists and thermal stimuli were blocked in the presence of specific TRPA1 and TRPM8 antagonists.
Conclusions: Human dental pulp fibroblasts express TRPA1 and TRPM8 at the molecular, protein, and functional levels, indicating a possible role for fibroblasts in mediating cold responses in human teeth.

A comparison of four extraction methods for substance P, neurokinin A and calcitonin gene-related peptide from human dental pulp tissue

Measuring neuropeptides in biological tissues by radioimmunoassay requires efficient extraction that maintains their immunoreactivity. Many different methods for extraction have been described, but there is little information on optimal extraction methods for individual neuropeptides from human dental pulp tissue. The aim was therefore to identify an effective extraction procedure for three pulpal neuropeptides: substance P. neurokinin A and calcitonin gene-related peptide. Tissue was obtained from 20 pulps taken from teeth freshly extracted for orthodontic reasons. The pulp samples were divided into four equal groups and different extraction methods were used for each group. Boiling whole pulp in acetic acid gave the highest overall yield and, in addition, offered an easy and rapid means of pulp tissue processing. The use of protease inhibitors did not increase the recovery of the immunoreactive neuropeptides but did provide the best combination of maximal recoveries and minimal variability. These results should be useful for planning the extraction of these neuropeptides from human pulp tissue in future studies. (C) 1999 Elsevier Science Ltd. All rights reserved.

Adaptation and Reintegration of Proprioceptive Information in Young and Older Adults' Postural Control

We investigated age-related changes in adaptation and sensory reintegration in postural control without vision. In two sessions, participants adapted their posture to sway reference and to reverse sway reference conditions, the former reducing (near eliminating) and the latter enhancing (near doubling) proprioceptive information for posture by means of support-surface rotations in proportion to body sway. Participants stood on a stable platform for 3 min (baseline) followed by 18 min of sway reference or reverse sway reference (adaptation) and finally again on a stable platform for 3 min (reintegration). Results showed that when inaccurate proprioception was introduced, anterior-posterior (AP) sway path length increased in comparable levels in the two age groups. During adaptation, young and older adults reduced postural sway at the same rate. On restoration of the stable platform in the reintegration phase, a sizeable aftereffect of increased AP path length was observed in both groups, which was greater in magnitude and duration for older adults. In line with linear feedback models of postural control, spectral analyses showed that this aftereffect differed between the two platform conditions. In the sway-referenced condition, a switch from low- to high-frequency COP sway marked the transition from reduced to normal proprioceptive information. The opposite switch was observed in the reverse sway referenced condition. Our findings illustrate age-related slowing in participants' postural control adjustments to sudden changes in environmental conditions. Over and above differences in postural control, our results implicate sensory reweighting as a specific mechanism highly sensitive to age-related decline.

Prediction-Based Power-Performance Adaptation of Multithreaded Scientific Codes

Computing has recently reached an inflection point with the introduction of multicore processors. On-chip thread-level parallelism is doubling approximately every other year. Concurrency lends itself naturally to allowing a program to trade performance for power savings by regulating the number of active cores; however, in several domains, users are unwilling to sacrifice performance to save power. We present a prediction model for identifying energy-efficient operating points of concurrency in well-tuned multithreaded scientific applications and a runtime system that uses live program analysis to optimize applications dynamically. We describe a dynamic phase-aware performance prediction model that combines multivariate regression techniques with runtime analysis of data collected from hardware event counters to locate optimal operating points of concurrency. Using our model, we develop a prediction-driven phase-aware runtime optimization scheme that throttles concurrency so that power consumption can be reduced and performance can be set at the knee of the scalability curve of each program phase. The use of prediction reduces the overhead of searching the optimization space while achieving near-optimal performance and power savings. A thorough evaluation of our approach shows a reduction in power consumption of 10.8 percent, simultaneous with an improvement in performance of 17.9 percent, resulting in energy savings of 26.7 percent.