Effect of Sonic Application of Self-etch Adhesives on Bonding Fiber Posts to Root Canal Dentin.

PURPOSE: To evaluate the effect of sonic application of 5 different self-etch adhesives on the push-out bond strength of fiber posts in root canals. MATERIALS AND METHODS: In a preliminary test, 24 teeth were treated with manual and sonically assisted bonding, then a composite cylinder was built up to test the shear bond strength as a proof of principle. In the main test, 120 root canals were endodontically prepared and divided into 10 groups: 5 self-etch adhesives (Futurabond DC, Futurabond M, Futurabond U, Optibond XTR, Universalbond), each applied under manual and sonic application modes. After insertion of the fiber posts using the specific adhesive and a dual-curing composite, the teeth were sectioned and the push-out test was performed. The specimens were analyzed by light and scanning electron microscopy. Statistical analysis was performed using the Shapiro-Wilk test, one-way ANOVA and the Tamhane test. RESULTS: Sonic application of self-etch adhesive systems did not increase the bond strength of fiber posts in root canals. In general, the bond strength decreased from the coronal to the apical part of the root canal, irrespective of the applied method. The best post retention was achieved with Futurabond U and Optibond XTR. CONCLUSION: Sonic application of self-etch adhesives did not improve the fiber post retention in the root canal and can therefore not be recommended. Nevertheless, sonic application of etch-and-rinse adhesives can increase the bond strength to coronal dentin.

Functional organization of information flow in the corticospinal pathway.

Transmission of information in the corticospinal (CS) route constitutes the fundamental infrastructure for voluntary actions. The anatomy of this pathway has been studied extensively, but there is little direct evidence regarding its functional organization. Here we explored the areal specificity of CS connections by studying two related questions: the functional significance of the parallel, motor, and premotor CS pathways; and the way in which finger-related motor commands are handled by this pathway. We addressed these questions by recording from primary motor (M1) and premotor cortical sites in primates (Maccaca fascicularis) performing a motor task, while measuring the evoked intraspinal unit response to single pulse cortical stimulation. Stimulation in M1 evoked spinal neuronal responses more frequently than stimulation in premotor cortex. The number of muscles excited by M1 stimulation was higher than the number excited by premotor stimulation. Within subregions of M1 finger-related sites were sparsely connected with intermediate zone interneurons and tended to affect the ventrally located motoneurons directly. These results suggest that, despite the parallel anatomical organization, the flow of motor commands is predominantly relayed via M1 to downstream elements. The functional impact of premotor cortex is weak, possibly due to inhibitory systems that can shape the flow of information in the CS pathway. Finally, the difference in spinal processing of finger versus wrist-related motor commands points to a different motor control strategy of finger versus wrist movements.

Adsorption and reaction of sub-monolayer films of an ionic liquid on Cu(111).

The reactive interaction of the ionic liquid 1-butyl-1-methylpyrrolidinium bis(trifluoromethylsulfonyl)imide [BMP][TFSA] with Cu(111) was investigated by scanning tunnelling microscopy (STM) and X-ray photoelectron spectroscopy (XPS) under ultrahigh vacuum (UHV) conditions. Decomposition between 300 K and 350 K is manifested by changes in the surface structure monitored with STM. XPS reveals that mainly the [TFSA] anion is decomposed.

Physicochemical vs. Vibrational Descriptors for Prediction of Odor Receptor Responses.

Responses of olfactory receptors (ORs) can be predicted by applying machine learning methods on a multivariate encoding of an odorant's chemical structure. Physicochemical descriptors that encode features of the molecular graph are a popular choice for such an encoding. Here, we explore the EVA descriptor set, which encodes features derived from the vibrational spectrum of a molecule. We assessed the performance of Support Vector Regression (SVR) and Random Forest Regression (RFR) to predict the gradual response of Drosophila ORs. We compared a 27-dimensional variant of the EVA descriptor against a set of 1467 descriptors provided by the eDragon software package, and against a 32-dimensional subset thereof that has been proposed as the basis for an odor metric consisting of 32 descriptors (HADDAD). The best prediction performance was reproducibly achieved using SVR on the highest-dimensional feature set. The low-dimensional EVA and HADDAD feature sets predicted odor-OR interactions with similar accuracy. Adding charge and polarizability information to the EVA descriptor did not improve the results but rather decreased predictive power. Post-hoc in vivo measurements confirmed these results. Our findings indicate that EVA provides a meaningful low-dimensional representation of odor space, although EVA hardly outperformed "classical" descriptor sets.