Many quantitative sensory testing methods have been developed for assessing peripheral nerve functions, but these testing devices require electrode contact or direct attachment on the body surface. Thus, this is the major disadvantage when testing individuals with necrosis or infection. To solve this problem, we developed a new system for the measurement of sensory function using two kinds of air jet; steady flow and pulsatile flow. This system is an easy and objective method for detecting the perception threshold without contact material on the skin surface. The purpose of this study was to evaluate the accuracy and utility of the new system. By stimulating the skin surface with two kinds of air jet, the perception threshold is calculated from the pulsatile dynamic pressure [Pa] and the steady flow [mL/s]. This study was performed on 24 healthy volunteers (15 males and 9 females, aged 20-23 years), and the perception threshold was measured using the new system. The perception thresholds for the steady flow and the dynamic pressure were 51±20mL/s and 285±282Pa, respectively, in the right forearm. The steady flows in the right middle finger tip, the left forearm and the left middle finger tip were 58±33mL/s, 56±15mL/s and 62±26mL/s, respectively. Similarly, the dynamic pressures in the right middle finger tip, the left forearm and the left middle finger tip were 392±225Pa, 263±264Pa and 399±190Pa, respectively. However, the perception thresholds measured against the steady flow and the dynamic pressure did not show a significant correlation. Although many issues remain to be solved, the new device is effective for assessing peripheral nerve function by stimulating at an appropriate distance (4mm to 11mm) from the tip of the nozzle. Further studies in subjects with a wide age range and in patients are required to improve the sensitivity of measuring the perception threshold.
When trypsinized cells are seeded on a substrate, the initially spherical cells adhere to the substrate and spread extensively over time. During this process, focal adhesions (FAs), which are large protein complexes organized at the basal surface of cells, physically connect actin filaments to the extracellular matrix and play crucial roles in cellular morphology and signaling. However, the dynamics of substrate adhesion and morphological changes of the spherical cells remain unknown. In this study, we plated MC3T3-E1 osteoblast-like cells, which had been cell cycle-synchronized by serum starvation, to fibronectin-coated glass bottom dishes, and cultured for 10 min to 24 h to observe changes in FA morphology by measuring the cell area (Acell) and FA morphological parameters including mean area of each FA (AFA), number of FAs per cell (NFA), and total area of FAs per cell (TAFA). Subsequently, we investigated the size dependence of FA dynamics. We also analyzed FA density (DFA), size (SFA) and shape index (SIFA) to compare the morphology between FAs that are underneath the nucleus to the morphology of FAs outside the nucleus. We found that Acell, AFA, NFA and TAFA increased continuously until 60 min post-plating. Acell continued to increase after 60 min, while AFA, NFA and TAFA showed complex changes over time. The percentage of small FAs was the highest early during adhesion (20 min) and decreased over time, while the percentage of moderate-to-large FAs increased until 1 h. After 1h, the percentages of small and middle FAs showed little changes, while the percentage of large FAs decreased gradually. These complex changes may reflect cellular demand for FAs. FAs underneath the nuclei were generally smaller than those outside the nuclei during the observed period. The density of FAs increased after 6 h, and FA shape became rounder after 3 h. These differences may be caused by regional differences in FA function: FAs underneath the nucleus may connect the nucleus to the substrate, while those outside the nucleus may connect the whole cell body to the substrate. We confirmed that FAs underwent time-dependent morphological changes during the adhesion process, including changes in size and position.
Most hemiplegic patients stand up using their unaffected leg. For this reason, it is necessary for patients to learn to decrease the use of the unaffected leg and to increase the use of the affected leg while standing up. The purpose of this study was to develop a motion support system to help patients increase the use of the affected leg while standing up and to confirm the effectiveness of the new system by conducting a standing experiment in a hemiplegic patient. The new system provides visual motor information for each leg by measuring the floor reaction force (FRF) while standing up. Furthermore, the system supports sit-to-stand motion when FRF of the affected leg increases more than the threshold calculated from unassisted standing motions. A basic experiment confirmed that the FRF sensor can measure the FRF of each leg separately. The standing experiment was performed in a volunteer in order to confirm that the patient can increase the use of the affected leg by using the system. The results showed that while standing up, the usage ratio of the affected side increased by 11.4% and that of the unaffected side decreased by 55.9%. In addition, FRF of the affected leg while standing with the system was 239N, and FRF without the system was 175N. These results suggest that the new system is effective in helping hemiplegic patients to increase the use of the affected leg.
Intrinsic optical signal (OIS) imaging technique is widely used in neuroscience research because it permits high resolution brain mapping without introducing molecular probes into the brain. However, low signal-to-noise ratio (S/N) of OIS is a serious problem that has to be resolved. So far, many algorithms have been developed to improve S/N. However, most of them require repeated acquisition of stimulus-to-response data and are therefore not suitable for OIS that express spontaneous activity of the brain. To overcome this problem, we developed an independent component analysis (ICA)-based algorithm for reduction of light source noise from OIS. The algorithm is based on a model of mixing mechanism of light source noise. It automatically determines the number of independent components and finds the component corresponding to light source noise based on similarity of power spectral densities. The noise component is removed by projecting the measured OIS onto the subspace orthogonal to the subspace spanned by the estimated noise component. Although usability of the algorithm was demonstrated by applying to real OIS data, some parameters were not optimized and quantitative performance was not clarified. In this study, we evaluated the noise reduction ability of the system by conducting performance test using synthetic OIS data containing light source noise. First, we identified the optimal parameter value for binning processing, which is applied prior to the noise reduction algorithm, based on accuracy of estimation of noise component. Second, we showed that reduction of light source noise by 10-20 dB was achieved under optimal conditions. These results indicate superiority of the algorithm and suggest its usefulness in improving S/N of real OIS data expressing spontaneous activity of the brain.