Hokkaido University

About: Hokkaido University is a education organization based out in Sapporo, Hokkaidô, Japan. It is known for research contribution in the topics: Population & Catalysis. The organization has 53925 authors who have published 115403 publications receiving 2651647 citations. The organization is also known as: Hokudai & Hokkaidō daigaku.

Effects of Dentin Depth and Cavity Configuration on Bond Strength

Abstract: During polymerization of resin composites, shrinkage stresses compete with resin-dentin bonds in a manner that can cause failure of the bond, depending upon the configuration of the cavity, its depth, and the restorative technique. The hypothesis tested in this study was that the effect of cavity configuration (C) and remaining dentin thickness (RDT) influence resin bond strength to the dentin of Class I cavity floors. The occlusal enamel was ground to expose a flat superficial dentin surface as a control (superficial dentin, C-factor = 1) in human extracted third molars. Cavities 3 mm long x 4 mm wide were prepared to a depth 2 mm below the ground dentin surfaces (deep dentin within cavity floor, C-factor = 3). To assess the relationship between C-factor and RDT, we removed the walls of cavities, making a deep flat surface for bonding (deep dentin, C-factor = 1). The teeth were restored with either Clearfil Liner Bond II (LB II), One-Step (OS), or Super-Bond D Liner (DL), followed by Clearfil Photo Posterior resin composite. After 24 hrs' storage in water, the teeth were sectioned vertically into 3 or 4 slabs (0.7 mm thick) and trimmed for the micro-tensile bond test so that we could determine the strength of the resin bonds to the pulpal floor. All groups gave high bond strengths to superficial dentin, but OS and DL gave significantly lower bond strengths to flat deep dentin when the C-factor was 1. When the C-factor was increased to 3 by the creation of a three-dimensional cavity preparation, the bond strengths of all materials fell (range, 21 to 35%), but the difference was significant (p < 0.05) only with DL. SEM observations of failure patterns showed that specimens with high bond strengths tended to exhibit cohesive failures within the hybrid layer, while specimens exhibiting low bond strengths showed failures at the top of the hybrid layer. Some adhesives do not bond well to deep dentin, making them more susceptible to polymerization shrinkage stress that develops in cavities with high C-factors.

Striatal and Tegmental Neurons Code Critical Signals for Temporal-Difference Learning of State Value in Domestic Chicks

Abstract: To ensure survival, animals must update the internal representations of their environment in a trial-and-error fashion. Psychological studies of associative learning and neurophysiological analyses of dopaminergic neurons have suggested that this updating process involves the temporal-difference (TD) method in the basal ganglia network. However, the way in which the component variables of the TD method are implemented at the neuronal level is unclear. To investigate the underlying neural mechanisms, we trained domestic chicks to associate color cues with food rewards. We recorded neuronal activities from the medial striatum or tegmentum in a freely behaving condition and examined how reward omission changed neuronal firing. To compare neuronal activities with the signals assumed in the TD method, we simulated the behavioral task in the form of a finite sequence composed of discrete steps of time. The three signals assumed in the simulated task were the prediction signal, the target signal for updating, and the TD-error signal. In both the medial striatum and tegmentum, the majority of recorded neurons were categorized into three types according to their fitness for three models, though these neurons tended to form a continuum spectrum without distinct differences in the firing rate. Specifically, two types of striatal neurons successfully mimicked the target signal and the prediction signal. A linear summation of these two types of striatum neurons was a good fit for the activity of one type of tegmental neurons mimicking the TD-error signal. The present study thus demonstrates that the striatum and tegmentum can convey the signals critically required for the TD method. Based on the theoretical and neurophysiological studies, together with tract-tracing data, we propose a novel model to explain how the convergence of signals represented in the striatum could lead to the computation of TD error in tegmental dopaminergic neurons.