Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11099952 | PMC |
| http://dx.doi.org/10.1523/ENEURO.0193-24.2024 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Direct SERS Detection of Folic Acid Using Modified Graphene Oxide-Gold Nanobowl Composites.
ACS Omega
December 2024
Faculty of Chemistry, University of Warsaw, Warsaw 02-093, Poland.
Gold nanobowls (AuNBs) synthesized by the template-free method were deposited on graphene oxide (GO) to obtain an ultrasensitive surface enhanced Raman spectroscopy (SERS) platform for folic acid (FA) detection. GO was conditioned in aqueous solutions at various pH values to optimize the adsorption of the FA molecule and the intensity of the SERS signal. It was found that the conditioning procedure influences the orientation of FA on the SERS supports and the quality of the spectra in result.
View Article and Find Full Text PDFCompromising tyrosine hydroxylase function extends and blunts the temporal profile of reinforcement by dopamine neurons in .
J Neurosci
January 2025
Leibniz Institute for Neurobiology (LIN), Department of Genetics of Learning and Memory, Magdeburg, 39118 Germany
For a proper representation of the causal structure of the world, it is adaptive to consider both evidence for and evidence against causality. To take punishment as an example, the causality of a stimulus is unlikely if there is a temporal gap before punishment is received, but causality is credible if the stimulus immediately precedes punishment. In contrast, causality can be ruled out if the punishment occurred first.
View Article and Find Full Text PDFRNADiffFold: generative RNA secondary structure prediction using discrete diffusion models.
Brief Bioinform
November 2024
Hangzhou Institute of Medicine, Chinese Academy of Sciences, Hangzhou 310018, Zhejiang, China.
Ribonucleic acid (RNA) molecules are essential macromolecules that perform diverse biological functions in living beings. Precise prediction of RNA secondary structures is instrumental in deciphering their complex three-dimensional architecture and functionality. Traditional methodologies for RNA structure prediction, including energy-based and learning-based approaches, often depict RNA secondary structures from a static perspective and rely on stringent a priori constraints.
View Article and Find Full Text PDFAlphaFold Meets De Novo Drug Design: Leveraging Structural Protein Information in Multitarget Molecular Generative Models.
J Chem Inf Model
November 2024
Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333CC Leiden, The Netherlands.
Article Synopsis
- * The study benchmarks this transformer model against existing models, finding that utilizing AlphaFold protein representations leads to better clustering and model performance compared to raw amino acid sequences, especially in low-data situations.
- * The model successfully generates diverse and potentially active molecules that resemble known ligands while ensuring novelty, and showcases the significance of data augmentation in improving generative model performance.
Variable gain DNA nanostructure charge amplifiers for biosensing.
Nanoscale
November 2024
Microsystems and Nanotechnology Division, National Institute of Standards and Technology, Gaithersburg, MD 20899, USA.
Electronic measurements of engineered nanostructures comprised solely of DNA (DNA origami) enable new signal conditioning modalities for use in biosensing. DNA origami, designed to take on arbitrary shapes and allow programmable motion triggered by conjugated biomolecules, have sufficient mass and charge to generate a large electrochemical signal. Here, we demonstrate the ability to electrostatically control the DNA origami conformation, and thereby the resulting signal amplification, when the structure binds a nucleic acid analyte.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!