Results 221 to 230 of about 17,563 (289)

Effect of gutta-percha cone-mediated ultrasonic activation on the push-out bond strength and dentinal tubule penetration of epoxy resin- and silicate-based root canal sealers: an in vitro study. [PDF]

BMC Oral Health
Kandemir B, Ozasir T, Ozasir B, Gulsahi K.   +3 more
europepmc   +1 more source

PlantGFM: A Genomic Foundation Model for Discovery and Creation of Plant Genes

Advanced Science, EarlyView.
A plant genomic foundation model pre‐trained on 12 species enables both accurate gene prediction and de novo gene design. Through AI‐human knowledge screening, seven designed sequences showed transcriptional activity in plants, with two expressing stable proteins—demonstrating the first DNA‐RNA‐protein expression of LLM‐generated genes in plants and ...
Changhao Li, Qizhe Zhang, Hanchen Chen, Kepeng Lin, Chengfang Luo, Mengying Yang, Wei Xu, Fan Yao, Jianbing Yan, Qing‐Yong Yang, Xuehai Hu   +10 more
wiley   +1 more source

Push out bond strength of resin -based endodontic sealer loaded with silver gold nanoparticles in vitro study. [PDF]

BDJ Open
Hassan N, Riad M, Ibrahim SH, Abulnoor BA, Hassan R.   +4 more
europepmc   +1 more source

How Advanced Artificial Intelligence Technologies Shape Drug–Drug and Drug–Target Interaction Modeling

Advanced Science, EarlyView.
This review explores the convergence of artificial intelligence technologies in modeling drug–drug and drug–target interactions. By evaluating advanced feature engineering, architectural innovations, and learning paradigms reveals shared evolutionary trends and critical challenges, such as cold‐start settings and shortcut learning.
Xin Sun, Tong Wang
wiley   +1 more source

Quantifying Structure–Property Relationships in Ferroelectric Polymers Toward High‐Performance Soft Robots

Advanced Science, EarlyView.
Here, we establish a quantitative relationship between the electrostriction coefficient (Q33) of FRPs and their interplanar spacing (d): Q33 = 100(Δd/d0+1) × Q33(s). Using this model, we fabricated high‐performance soft robots, including a biomimetic crawler (with a speed of 27 cm/s) and a butterfly (with a thrust‐to‐weight ratio of 0.71).
Ba Qin, Guotong Ding, Wanli Xing, Xiaoyu Yang, Wenxuan Li, Zhemin Chen, Shaobo Tan, Xiaoyong Wei, Zhicheng Zhang   +8 more
wiley   +1 more source

An in vitro assessment of push-out bond strength for four types of root canal sealers. [PDF]

Bioinformation
Babulal Patel HK, Chaudhary S, Patel P, Kubavat R, Kumbhar S, Vinod R, Jha S.   +6 more
europepmc   +1 more source

Construction of Sabatier Volcanoes for CO2 Hydrogenation to C1‐2 Oxygenates Using Data‐Efficient Machine Learning

Advanced Science, EarlyView.
A new data‐efficient framework combining DFT calculations, a neural network model, and automated graph analysis of catalytic reaction networks is proposed and applied to CO2 hydrogenation on transition metal nanoparticles. The analysis shows how efficient C2 oxygenate production requires a balance between CHx formation, C–C coupling, protonation, and ...
Mikhail V. Polynski, Sergey M. Kozlov
wiley   +1 more source

A Comparative Evaluation of Push-Out Bond Strength of Fiber-Reinforced Composite Posts Luted with Two Different Cement Systems: An <i>Ex vivo</i> Study.

J Pharm Bioallied Sci
Shahnawaz S, Shanoj RP, Nandakumar K, Juraise MC, Sudhakaran S, Shaheena R.   +5 more
europepmc   +1 more source

Improving the Push-Out Bond Strength of Fiber Posts in Diabetic Dentin: The Role of Chlorexidine Irrigation and Resin Cements. [PDF]

J Funct Biomater
Arslandaş Dinçtürk B, Şahin Mantı A, Kedici Alp C, Altuğ Yıldırım A, Kaya Mumcu A.   +4 more
europepmc   +1 more source

AI‐Physics‐Experiment Trinity for Integrated Protein Dynamics Modeling

Advanced Science, EarlyView.
This review unites experiments, physics‐based simulations, and AI as a synergistic triad for protein dynamics modeling. It highlights integrative strategies, resolves sampling and forcefield bottlenecks, and outlines challenges and future directions for accurate, interpretable conformational ensemble prediction.
Chen Shi, Minying Low, Peng Xiu, Kresten Lindorff‐Larsen, Yong Wang   +4 more
wiley   +1 more source