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Crown shapes in mammalian teeth vary considerably from species to species, and morphological characters in crown shape have been used to identify species. Cusp pattern is one of the characters in crown shape. In the processes governing the formation of cusp pattern, the Shh pathway has been implicated as an important player. Suppression of Shh signaling activity in vitro in explant assays appears to induce supernumerary cusp formation in wild-type tooth germs. However, the in vivo role of Shh signaling in cusp pattern formation and the molecular mechanisms by which Shh regulates cusp patterning are not clear. Here, through in vivo phenotypic analyses of mice in which Shh activity was suppressed and compared with wild-type mice, we characterized differences in the location, number, incidence, and shape of supernumerary cusps in molars at embryonic day 15.5. We found that the distances between cusps were reduced in molars of Shh activity–suppressed mice in vivo. These findings confirm and extend the previous idea that Shh acts as an inhibitor in the reaction-diffusion model for cusp pattern formation by negatively regulating the intercuspal distance. We uncovered a significant reduction of expression level of Sostdc1, which encodes a secreted modulator of Wnt signaling, after suppression of Shh activity. The supernumerary cusp formation in Sostdc1−/− mice and compound Sostdc1 and Lrp mutant mice indicates a strong association between Wnt and Shh signaling pathways in cusp patterning. In further support of this idea, there is a high degree of similarity in the supernumerary cusp patterns of mice lacking Sostdc1 or Shh at embryonic day 15.5. These results suggest that Shh plays an inhibitory role in cusp pattern formation by modulating Wnt signaling through the positive regulation of Sostdc1.

Supplemental material, DS_10.1177_0022034518803095 for Shh Plays an Inhibitory Role in Cusp Patterning by Regulation of Sostdc1 by J. Kim, Y. Ahn, D. Adasooriya, E.J. Woo, H.J. Kim, K.S. Hu, R. Krumlauf and S.W. Cho in Journal of Dental Research

The apparent resistance of a finite-thickness layer measured with a four-electrode plunge probe depends on the electrode insertion depth, electrode spacing, and layer thickness, as well as the resistivity ratio of an underlying layer. A physical model consisting of air, a saline solution layer, and an agar layer simulates the real situation of resistivity measurement. The saline layer represents the finite-thickness layer whose resistivity is to be measured by a plunge electrode probe, and the agar layer represents an underlying perturbing layer. A micropositioner controls the insertion depth of the four electrodes into the saline solution. With the apparent resistance measured on a semi-infinite-thickness layer of saline solution as standard, measurement results show decreasing apparent resistance and increasing error with increasing electrode insertion depth. This information is important for correct measurement of myocardial resistivity in vivo and in vitro.

We propose the use of electrical impedance tomography (EIT) imaging techniques in the measurement of lung resistivity for detection and monitoring of apnea and edema. In EIT, we inject currents into a subject using multiple electrodes and measure boundary voltages to reconstruct a cross-sectional image of internal resistivity distribution. We found that a simplified, therefore fast, version of the impedance imaging method can be used for detection and monitoring of apnea and edema. We have showed the feasibility of this method through computer simulations and human experiments. We speculate that the EIT imaging technique will be more reliable than the current impedance apnea monitoring method, since we are monitoring the change of internal lung resistivity. However, more study is required to verify that this method performs better in the presence of motion artifact than the conventional two-electrode impedance apnea monitoring method. Future work should include experiments which carefully simulate different kinds of motion artifacts.

An electrical impedance tomography (EIT) system that uses the optimal current method to inject currents and the regularized Newton-Raphson algorithm to reconstruct an image of resistivity distribution is discussed. Iterative methods to derive the optimal current patterns through iterative physical measurements are developed. Direct methods to first determine the resistance matrix of a resistivity distribution through a set of current bases is injected and the measured voltage responses are stored. This permits iterative reconstruction techniques to operate on the stored data without requiring lengthy data taking from the object and reduces the effects of motion artifacts. The direct methods have superior performance as compared to the iterative methods in both optimal current and voltage generation. The results obtained with three sets of current bases are studied. >

We propose a measurement method using Walsh functions in 32-electrode electrical impedance tomography. By injecting currents in spatial Walsh function patterns, we use the simplicity of pulse type injection and yield the optimal SNR or distinguishability of sinusoidal injection. Once we measure boundary voltage data for the injection of all 31 patterns of Walsh functions, we can compute all 31 optimal current pattems. We can also synthesize the voltage data due to the injection of the optimal current patterns without actually injecting the optimal current patterns.

Static image reconstruction in electrical impedance tomopphy (EIT) using iterative algorithms requires a large computation time. We developed an improved NewtonRaphson (N-R) method which is more efficient, robust, and easily parallelizable. In order to check the feasibility of parallel computation in EIT, we implemented the algorithm on a parallel computer system. The results show a reduction in the computation time within a certain hiit as we increase the number of processors. We conclude that the improved N-R method is highly parallelizable and the use of parallel computers such as Transputers may solve the computational problems in static impedance imaging.

The use of compound electrodes to improve the conditioning and sensitivity of an electrical impedance tomography imaging system is described. Effects of electrode-skin contact impedance are discussed and a model is proposed. Reconstructed static images from phantoms are shown. >

A 32-electrode, 12-bit electrical impedance tomograph (EIT) which is capable of injecting optimal patterns of currents into an object to achieve maximum distinguishability is presented. The software for the system is described, and static images reconstructed from a circular 2-D phantom are shown. The EIT software consists of four parts: the interactive graphical finite-element mesh generator; the sparse linear system equation solver including node renumbering schemes; the calculation of the optimal patterns of injection current and the implementations of the EIT image reconstruction algorithms; and image display and postprocessing. >

An electrical impedance tomography (EIT) method is considered in which 32 electrodes are placed around the thorax, currents are injected, and voltages are measured to reconstruct a cross-sectional image of resistivity. The authors solve the forward problem using the finite-element method (FEM). The number of elements determines the spatial resolution of the resistivity image. An adaptive current-injection method to provide an optimal current distribution is used. The modified Newton-Raphson method is used as the reconstruction algorithm. The authors use sparse matrix techniques with node renumbering methods to minimize the computation time. >

An investigation has been made of multiple-electrode system to monitor the impedance changes corresponding to volume changes of the urinary bladder, using a finite-element model of the human body. The authors used an adaptive method for determining the optimal currents which would provide maximal impedance changes. They present simulation results and discuss the relationships between impedance change and the number and placement of the electrodes. >