Results 181 to 190 of about 1,914,522 (244)

Lipid Nanoparticles for the Delivery of CRISPR/Cas9 Machinery to Enable Site‐Specific Integration of CFTR and Mutation‐Agnostic Disease Rescue

Advanced Functional Materials, EarlyView.
Lipid nanoparticles (LNPs) are optimized to co‐deliver Cas9‐encoding messenger RNA (mRNA), a single guide RNA (sgRNA) targeting the endogenous cystic fibrosis transmembrane conductance regulator (CFTR) gene, and homologous linear double‐stranded donor DNA (ldsDNA) templates encoding CFTR.
Ruth A. Foley, Paul G. Ayoub, Vrishti Sinha, Colin Juett, Alicia Sanoyca, Emily C. Duggan, Lindsay E. Lathrop, Priyanka Bhatt, Kevin Coote, Beate Illek, Brigitte N. Gomperts, Donald B. Kohn, Steven J. Jonas   +12 more
wiley   +1 more source

Comparing machine learning and artificial neural network models in psychological research: a ROC-based analysis. [PDF]

Front Psychol
Leitner ML, Arendasy M.
europepmc   +1 more source

Biomass Native Structure Into Functional Carbon‐Based Catalysts for Fenton‐Like Reactions

Advanced Functional Materials, EarlyView.
This study indicates that eight biomasses with 2D flaky and 1D acicular structures influence surface O types, morphology, defects, N doping, sp2 C, and Co nanoparticles loading in three series of carbon, N‐doped carbon, and cobalt/graphitic carbon. This work identifies how these structural factors impact catalytic pathways, enhancing selective electron
Wenjie Tian, Jingkai Lin, Zhihao Tian, Selusiwe Ncube, Huayang Zhang, Emiliano Cortés, Hongqi Sun, Shaobin Wang   +7 more
wiley   +1 more source

Privacy-preserving federated prediction of health outcomes using multi-center survey data. [PDF]

BMC Med Res Methodol
Das S, Rafiei M, Kammer PT, Skou ST, Grønne DT, Roos EM, Hajek A, König HH, Ullah MS, Probul N, Baumbach J, Baumbach L.   +11 more
europepmc   +1 more source

Microporous Microgel Assemblies Facilitating the Recruitment and Osteogenic Differentiation of Progenitor Cells for Bone Regeneration

Advanced Functional Materials, EarlyView.
There is a significant need for biomaterials with well‐defined stability and bioactivity to support tissue regeneration. In this study, we developed a tunable microgel platform that enables the decoupling of stiffness from porosity, thereby promoting bone regeneration.
Silvia Pravato, Haishuo Guan, Bianca M. Carrara, Mira Jacobs, Matteo Monticelli, Lukas Moser, Thomas Moragues, Andrew J. deMello, Tomaso Zambelli, Martin Ehrbar   +9 more
wiley   +1 more source

Semi-Quantitative Detection of Borax Adulteration in Wheat Flour Based on Microwave Non-Destructive Testing and Machine Learning. [PDF]

Foods
Kang M, Yang J, Ren Y, Bai X.
europepmc   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Using machine learning to identify unique predictors of alcohol and cannabis impaired driving. [PDF]

Alcohol Clin Exp Res (Hoboken)
Calhoun BH, Hultgren BA, McCabe CJ, Rhew IC, Larimer ME, Kilmer JR, Guttmannova K.   +6 more
europepmc   +1 more source

Oral Dosed Organo‐Silica Nanoparticles Restore Glucose Homeostasis and β‐Cell Function in Diabetes Rats

Advanced Functional Materials, EarlyView.
An oral nanoplatform, MOP@T@D, which can maintain glucose homeostasis and restore islet β cells in diabetic rats is developed. It achieves efficient intestinal absorption and liver‐targeted delivery. The nanoparticle disintegrates only in response to hyperglycemia to release insulin on demand and provides antioxidant protection through selenoprotein ...
Chenxiao Chu, Mingli Wei, Che Bian, Xiaoshuang Bi, Yaxin Deng, Peifu Xiao, Jiansong Zhao, Yuying Wang, Haibing He, Jingxin Gou, Tian Yin, Xing Tang, Li Yang, Hongbo Zhang, Yu Zhang   +14 more
wiley   +1 more source

Prediction of athlete performance based on a gradient regression model. [PDF]

Sci Rep
Wei X, Liang S, Diao W.
europepmc   +1 more source