Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
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 +7 more
wiley +1 more source
Ilama VHH as a Substitute for Rabbit Polyclonal Antibodies in ELISpot Application. [PDF]
Reynas C +3 more
europepmc +1 more source
Ice Lithography: Recent Progress Opens a New Frontier of Opportunities
This review focuses on recent advancements in ice lithography, including breakthroughs in compatible precursors and substrates, processes and applications, hardware, and digital methods. Moreover, it offers a roadmap to uncover innovation opportunities for ice lithography in fields such as biological, nanoengineering and microsystems, biophysics and ...
Bingdong Chang +9 more
wiley +1 more source
Positive feedback regulation between USP8 and Hippo/YAP axis drives triple-negative breast cancer progression. [PDF]
Li X +9 more
europepmc +1 more source
We introduce a nucleic acid nanoparticle (NANP) platform designed to be rrecognized by the human innate immune system in a regulated manner. By changing chemical composition while maintaining constant architectural parameters, we identify key determinants of immunorecognition enabling the rational design of NANPs with tunable immune activation profiles
Martin Panigaj +21 more
wiley +1 more source
Development of a split-toxin CRISPR screening platform to systematically identify regulators of human myoblast fusion. [PDF]
Zhang H +13 more
europepmc +1 more source
Peptide Sequencing With Single Acid Resolution Using a Sub‐Nanometer Diameter Pore
To sequence a single molecule of Aβ1−42–sodium dodecyl sulfate (SDS), the aggregate is forced through a sub‐nanopore 0.4 nm in diameter spanning a 4.0 nm thick membrane. The figure is a visual molecular dynamics (VMD) snapshot depicting the translocation of Aβ1−42–SDS through the pore; only the peptide, the SDS, the Na+ (yellow/green) and Cl− (cyan ...
Apurba Paul +8 more
wiley +1 more source
Chromosome-level genome assembly of the predatory stink bug, Eocanthecona furcellata (Wolff). [PDF]
Hu QL, Zhuo JC, Zhang CX.
europepmc +1 more source
Link Analysis of National Science Digital Library Network Nodes: A Linked Open Data
Kutty Kumar
openalex +1 more source

