Objective: The present study investigated the ability of a chlorhexidine (CHX)-containing primer (0.2% aqueous solution) to inhibit dentinal enzymes, preserve the hybrid layer (HL) and remain within the HL, after 10 years of aging in artificial saliva at 37°C.

Methods: Non-carious extracted molars were assigned to two groups, cut into slabs exposing middle/deep dentin, etched and bonded with Adper Scotchbond 1XT (SB1XT) with or without 0.2% CHX aqueous solution pretreatment. Composite build-ups were made, and the specimens were cut in 1-mm thick bonded sticks. In situ zymography was performed on freshly prepared specimens (T) and specimens aged for 10 years (T) at 37°C in artificial saliva, to investigate endogenous gelatinolytic activity within the HL. At T, specimens were also decalcified and embedded in epoxy resin for TEM analysis. Micro-Raman spectroscopy was performed at T and T to evaluate the chemical profiles in intertubular dentin and the HL.

Results: In situ zymography showed less pronounced enzymatic activity in the CHX-pretreated group (p<0.05) regardless of aging, maintaining a similar level of fluorescence at T and T (p>0.05). TEM results showed that 98% of the HL had been degraded in the control group, while 95% of the HL was intact in the experimental group. Moreover, all the Raman spectra peaks assigned to CHX could be identified only in the CHX-pretreated group (T and T).

Significance: In vitro, CHX remains in the HL after 10 years with its inhibitory effect preserved. This may be the underlying factor for HL preservation after this long aging period.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.dental.2020.03.009DOI Listing

Publication Analysis

Top Keywords

hybrid layer
8
aqueous solution
8
artificial saliva
8
situ zymography
8
chx-pretreated group
8
chlorhexidine preserves
4
preserves hybrid
4
layer vitro
4
vitro 10-years
4
10-years aging
4

Similar Publications

Miniaturization of next-generation active neural implants requires novel micro-packaging solutions that can maintain their long-term coating performance in the body. This work presents two thin-film coatings and evaluates their biostability and in vivo performance over a 7-month animal study. To evaluate the coatings on representative surfaces, two silicon microchips with different surface microtopography are used.

View Article and Find Full Text PDF

Metallic Zn is a promising anode for high-safety, low-cost, and large-scale energy storage systems. However, it is strongly hindered by unstable electrode/electrolyte interface issues, including zinc dendrite, corrosion, passivation, and hydrogen evolution reactions. In this work, an in situ interface protection strategy is established by turning the corrosion/passivation byproducts (zinc hydroxide sulfates, ZHSs) into a stable hybrid protection layer.

View Article and Find Full Text PDF

Deep learning has revolutionized electroencephalograph (EEG) decoding, with convolutional neural networks (CNNs) being a predominant tool. However, CNNs struggle with long-term dependencies in sequential EEG data. Models like long short-term memory and transformers improve performance but still face challenges of computational efficiency and long sequences.

View Article and Find Full Text PDF

Investigating the intrinsic top-down dynamics of deep generative models.

Sci Rep

January 2025

Department of General Psychology and Padova Neuroscience Center, University of Padova, Padova, Italy.

Hierarchical generative models can produce data samples based on the statistical structure of their training distribution. This capability can be linked to current theories in computational neuroscience, which propose that spontaneous brain activity at rest is the manifestation of top-down dynamics of generative models detached from action-perception cycles. A popular class of hierarchical generative models is that of Deep Belief Networks (DBNs), which are energy-based deep learning architectures that can learn multiple levels of representations in a completely unsupervised way exploiting Hebbian-like learning mechanisms.

View Article and Find Full Text PDF

The PSO-IFAH optimization algorithm for transient electromagnetic inversion.

PLoS One

January 2025

Department of Electrical and Computer Engineering, The University of Tulsa, Tulsa, OK, United States of America.

As a non-contact method, the transient electromagnetic (TEM) method has the characteristics of high efficiency, small impact of device, no limitation of site range, and high resolution, and is a hot topic in current research. However, the research on the refined data processing method of TEM is lag, which seriously restricts the application in superficial engineering investigation and is a key problem that needs to be solved urgently. The particle swarm optimization (PSO) algorithm and firefly algorithm (FA) were successful swarm intelligence algorithms inspired by nature.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!