Results 101 to 110 of about 165,078 (298)

Genome‐Wide CRISPR Screen Reveals PIK3CA Inhibition Enhances Lipid Nanoparticle‐Mediated siRNA Delivery

Advanced Science, EarlyView.
A genome‐wide CRISPR screen and identifies PIK3CA as a key regulator of lipid nanoparticle (LNP) uptake is performed. Modulating PIK3CA with small‐molecule inhibitor BAY1082439 enhanced LNP uptake, siRNA delivery, and gene silencing in a variety of epithelial cells, and improved therapeutic outcomes in vivo.
Wenhan Wang, Kangfu Chen, Zongjie Wang
wiley   +1 more source

Key determinants of university dropout: academic, economic, and psychosocial factors in student retention

Frontiers in Education
IntroductionUniversity dropout remains a persistent challenge in higher education, reflecting structural tensions between inclusivity, student retention, and educational equity.
Alejandro Valencia-Arias, Julio César Valera Aredo, Jackeline Valencia, Sebastián Cardona-Acevedo, Juan Camilo Patiño-Vanegas, Hernán Uribe Bedoya   +5 more
doaj   +1 more source

An Examination of Student Disengagement and Reengagement from an Alternative High School [PDF]

, 2019
Each year, 20% of U.S. students drop out of high school (Balfanz, Bridgeland, Bruce, & Fox, 2013). There is an abundance of research on student behaviors from researchers who explored the process of student disengagement from school (Bowers, Sprott ...
Flores, Marina Escamilla, Graham Brown, Casey   +1 more
core   +1 more source

NanoLoop: A Deep Learning Framework Leveraging Nanopore Sequencing for Chromatin Loop Prediction

Advanced Science, EarlyView.
Chromatin loops are central to gene regulation and 3D genome organization. Leveraging Nanopore sequencing's ability to jointly capture DNA sequence and methylation, we present NanoLoop, the first framework for genome‐wide chromatin loop prediction using Nanopore data.
Wenjie Huang, Li Tang, Matthew C. Hill, Yonghao Zhang, Jun Xie, Min Li   +5 more
wiley   +1 more source

Data‐Driven Feedback Identifies Focused Ultrasound Exposure Regimens for Improved Nanotheranostic Targeting of the Brain

Advanced Science, EarlyView.
Machine learning models predict in real time the onset of harmful microbubble collapse during microbubble‐enhanced focused ultrasound (MB‐FUS) and enable dynamic adjustment of sonication to prevent cavitation‐induced damage. This predictive control expands the safe operating window for bloodbrain barrier opening, enhancing nanoparticle delivery and ...
Hohyun Lee, Victor Menezes, Shiqin Zeng, Chulyong Kim, Cynthia M. Baseman, Jae Hyun Kim, Samhita Padmanabhan, Pranav Premdas, Naima Djeddar, Anton Bryksin, Nikhil Pandey, Pavlos Anastasiadis, Anthony J. Kim, Tobey J. MacDonald, Chetan Bettegowda, Graeme F. Woodworth, Felix J. Herrmann, Costas Arvanitis   +17 more
wiley   +1 more source

Factors, Prediction, Explainability, and Simulating University Dropout Through Machine Learning: A Systematic Review, 2012–2024

Computation
College dropout represents a significant challenge for universities, and despite advances in machine learning technologies, predicting dropout remains a complex task.
Mauricio Quimiz-Moreira, Rosa Delgadillo, Jorge Parraga-Alava, Nelson Maculan, David Mauricio   +4 more
doaj   +1 more source

The Effects of Interrupted Enrollment on Graduation from College: Racial, Income, and Ability Differences [PDF]

We present a multiple spells-competing risks model of stopout, dropout, reenrollment, and graduation behavior. We find that students who experience an initial stopout are more likely to experience subsequent stopouts (occurrence dependence) and be less ...
Brian P. McCall, Dennis A. Ahlburg, Stephen L. DesJardins   +2 more
core  

State Opportunities for Reconnecting Young Adults to Education, Skills Training and Employment [PDF]

, 2013
"An alarmingly large number of young adults have disconnected from traditional education or skills training pathways, often without obtaining a basic high school credential.
Barry Shaffer
core  

Generating Dynamic Structures Through Physics‐Based Sampling of Predicted Inter‐Residue Geometries

Advanced Science, EarlyView.
While static structure prediction has been revolutionized, modeling protein dynamics remains elusive. trRosettaX2‐Dynamics is presented to address this challenge. This framework leverages a Transformer‐based network to predict inter‐residue geometric constraints, guiding conformation generation via physics‐based iterative sampling. The resulting method
Chenxiao Xiang, Wenkai Wang, Zhenling Peng, Jianyi Yang   +3 more
wiley   +1 more source

Analysis of Engineering Students Dropout in E-learning: E-IUST Case Study

آموزش مهندسی ایران, 2010
This paper reviews the educational dropout rate in e-learning system and its causes. Literature review indicates that the dropout rate in e-learning is more than traditional learning.
Mohammad ali Rostaminezhad, Naser Mozayani   +1 more
doaj   +1 more source