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Background: Retinoblastoma binding protein 4 (Rbbp4) is a component of transcription regulatory complexes that control cell cycle gene expression. Previous work indicated that Rbbp4 cooperates with the Rb tumor suppressor to block cell cycle entry. Here, we use genetic analysis to examine the interactions of Rbbp4, Rb, and Tp53 in zebrafish neural progenitor cell cycle regulation and survival. Results: Rbbp4 is upregulated across the spectrum of human embryonal and glial brain cancers. Transgenic rescue of rbbp4 mutant embryos shows Rbbp4 is essential for zebrafish neurogenesis. Rbbp4 loss leads to apoptosis and γ‐H2AX in the developing brain that is suppressed by tp53 knockdown or maternal zygotic deletion. Mutant retinal neural precursors accumulate in M phase and fail to initiate G0 gene expression. rbbp4; rb1 mutants show an additive effect on the number of M phase cells. In rbbp4 mutants, Tp53 acetylation is detected; however, Rbbp4 overexpression did not rescue DNA damage‐induced apoptosis. Conclusion: Rbbp4 is necessary for neural progenitor cell cycle progression and initiation of G0 independent of Rb. Tp53‐dependent apoptosis in the absence of Rbpb4 correlates with Tp53 acetylation. Together these results suggest that Rbbp4 is required for cell cycle exit and contributes to neural progenitor survival through the regulation of Tp53 acetylation. Key Findings: Rbbp4 regulates neural progenitor cell cycle independent of RbRbbp4 loss leads to Tp53 acetylation, gamma‐H2AX labeling and apoptosis in neural progenitorsSuppression of gamma‐H2AX labeling and apoptosis by Tp53 knockdown in Rbbp4 mutants indicates Rbpp4 may induce apoptosis by transcriptional activation of Tp53 independent of the DNA damage response pathway [ABSTRACT FROM AUTHOR]

The Internet of Things (smart things) is used in many sectors and applications due to recent technological advances. One of such application is in the transportation system, which is of primary use for the users to move from one place to another place. The smart devices which were embedded in vehicles are useful for the passengers to solve his/her query, wherein future vehicles will be fully automated to the advanced stage, i.e. future cars with driverless feature. These autonomous cars will help people a lot to reduce their time and increases their productivity in their respective (associated) business. In today's generation and in the near future, privacy preserving and trust will be a major concern among users and autonomous vehicles and hence, this paper will be able to provide clarity for the same. Many attempts in previous decade have provided many efficient mechanisms, but they all work only with vehicles along with a driver. However, these mechanisms are not valid and useful for future vehicles. In this paper, we will use deep learning techniques for building trust using recommender systems and Blockchain technology for privacy preserving. We also maintain a certain level of trust via maintaining the highest level of privacy among users living in a particular environment. In this research, we developed a framework that could offer maximum trust or reliable communication to users over the road network. With this, we also preserve privacy of users during traveling, i.e., without revealing identity of respective users from Trusted Third Parties or even Location Based Service in reaching a destination. Thus, Deep Learning based Blockchain Solution (DLBS) is illustrated for providing an efficient recommendation system. [ABSTRACT FROM AUTHOR]

Background: In-vitro evaluation of the resin-dentin interface using a self-etch and a total etch adhesive system bonded to moist dentin, using confocal laser scanning microscope (CLSM). Materials and Methods: A total of 40 intact non-carious human premolars stored and sterilized according to Occupational Safety and Health Administration regulations were used for the study. All the teeth, occlusal surfaces, were ground to expose the dentin. 40 teeth were then divided into two groups and treated with different adhesive system. Group 1 (20): Self-etch adhesive system and Group 2 (20); total-etch adhesive system. Rodhamine B dye was mixed with bonding agents and applied on tooth surfaces and cured. CLSM was used to examine resin/dentin interface. The values of resin tag length and thickness of the hybrid layer among the groups were compared and statistically analyzed using Mann- Whitney U-test. Results: Highest mean length of resin tag was obtained with Group I (110.4 µm) adhesives compared to Group II (35.5 µm) and the thickness of hybrid layer was highest with Group II (4.14 µm) compared with Group I (2.1 µm). A very high statistical significance (P < 0.001) was obtained among groups using Mann-Whitney U-test. Conclusion: The resin dentin interface of conventional total-etch adhesives performed better than newer self-etch adhesive system in terms of resin tag length and hybrid layer thickness. [ABSTRACT FROM AUTHOR]