BackgroundMineral trioxide aggregate (MTA) is widely used for pulp-capping procedures in permanent teeth and as a gold standard material in endodontics. The aim of the study was to investigate the effect of MTA on cell viability and apoptosis when MTA is directly in contact with Stem Cells from Human Exfoliated Deciduous Teeth (SHEDs).MethodsMTA was mixed and coated in the bottom of a 24-well plate. SHEDs collected and cultured from normal exfoliated human deciduous teeth (passages 3–4) were seeded on square cover glasses. The glasses with seeded SHEDs were incubated in the plates with or without MTA coating. They were divided into four groups: MTA direct contact, direct control, MTA indirect contact, and indirect control. After 1, 2 and 3 days of culturing, cell morphology was observed and cell viability was assessed by the WST-1 cell cytotoxicity assay. TUNEL assay, immunofluorescent labeling and western blot analysis were used to study the effects of MTA on SHEDs apoptosis.ResultsMTA impaired cell viability of SHEDs in 1, 2 and 3 days, and the effect of direct contact was more severe. Cell apoptosis with positive Annexin V and TUNEL staining was noted when there was direct contact with MTA. Western blot analysis revealed that Bcl-2 and Bcl-xL decreased after SHEDs were in contact with MTA.ConclusionsThis study shows that direct contact with 1 week post-set MTA significantly decreases the viability of SHEDs and induced cell apoptosis. The results suggest that there is a possible cytotoxic effect of pulp tissue when there is direct contact with MTA. Different responses would be expected due to the strong alkaline characteristics of fresh mixed MTA.
The Bayer and RGBW color filter array (CFA) raw images, denoted by I Bayer and I RGB , respectively, have been widely used in consumer markets. In the demosaicking-first compression scheme, chroma subsampling is necessary prior to compressing I RGB and I RGBW . Several linear interpolationbased chroma subsampling methods have been developed for I Bayer , but no nonlinear interpolation-based chroma subsampling methods have targeted the above two CFA image types simultaneously. In this paper, we first propose a nonlinear interpolation-based, namely the cubic convolution interpolation-based (CCIbased), 2×2 block-distortion function for each 2×2 CFA block B CbCr . Next, using the Cauchy-Schwarz inequality, we prove that the proposed block-distortion function is a convex function in the real domain, which further serves as the base of the initial subsampled chroma solution. Then, a CCI-based iterative method is proposed to improve the initial subsampled chroma solution. The results of comprehensive experimental tests using Bayer and RGBW CFA images created from the three RGB full-color datasets, namely IMAX, SCI (screen content images), and CI (classical images), demonstrate that on the Versatile Video Coding (VVC) platform VTM-11.0, the proposed method achieves substantial quality enhancement and quality-bitrate tradeoff merits of the reconstructed Bayer and RGBW CFA images compared with existing chroma subsampling methods. INDEX TERMSBayer color filter array (CFA) image, Chroma subsampling, Convex block-distortion function, Demosaicking, Quality-bitrate tradeoff, Quality enhancement, RGBW CFA image.
Everolimus suppressed the proliferation and migration of RPE cells in vitro. Oral everolimus (0.5 mg/day) suppressed the expression of mTOR and RPS6 in the retina, but showed no effect in suppressing experimental PVR.
The success of many computer vision and pattern recognition applications depends on matching local features on two or more images. Because the initial correspondence set—i.e., the set of the initial feature pairs—is often contaminated by mismatches, removing mismatches is a necessary task prior to image matching. In this paper, we first propose a fast geometry histogram-based (GH-based) mismatch removal strategy to construct a reduced correspondence set Creduced,GH from the initial correspondence set Cini. Next, we propose an effective cooperative random sample consensus (COOSAC) method for remote sensing image matching. COOSAC consists of a RANSAC, called RANSACini working on Cini, and a tiny RANSAC, called RANSACtiny,GH working on a randomly selected subset of Creduced,GH. In RANSACtiny,GH, an iterative area constraint-based sampling strategy is proposed to estimate the model solution of Ctiny,GH until the specified confidence level is reached, and then RANSACini utilizes the estimated model solution of Ctiny,GH to calculate the inlier rate of Cini. COOSAC repeats the above cooperation between RANSACtiny,GH and RANSACini until the specified confidence level is reached, reporting the resultant model solution of Cini. For convenience, our image matching method is called the GH-COOSAC method. Based on several testing datasets, thorough experimental results demonstrate that the proposed GH-COOSAC method achieves lower computational cost and higher matching accuracy benefits when compared with the state-of-the-art image matching methods.
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