Header

UZH-Logo

Maintenance Infos

New Technologies to Investigate Neuropeptides at Scale


Patriarchi, Tommaso (2022). New Technologies to Investigate Neuropeptides at Scale. ACS Chemical Neuroscience, 13(16):2353-2355.

Abstract

Neuropeptides are some of the most elusive molecules to monitor in neuroscience. Detecting their release and spread in brain tissue requires the development and use of advanced technologies that enable specific neuropeptide measurements with high spatial and temporal resolution. This Viewpoint highlights some of the emerging tools and techniques that are already advancing our knowledge of neuropeptide physiology and discusses possible future developments.

Abstract

Neuropeptides are some of the most elusive molecules to monitor in neuroscience. Detecting their release and spread in brain tissue requires the development and use of advanced technologies that enable specific neuropeptide measurements with high spatial and temporal resolution. This Viewpoint highlights some of the emerging tools and techniques that are already advancing our knowledge of neuropeptide physiology and discusses possible future developments.

Statistics

Citations

Altmetrics

Downloads

1 download since deposited on 03 Aug 2022
0 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Journal Article, refereed, further contribution
Communities & Collections:04 Faculty of Medicine > Institute of Pharmacology and Toxicology
07 Faculty of Science > Institute of Pharmacology and Toxicology
Dewey Decimal Classification:570 Life sciences; biology
610 Medicine & health
Uncontrolled Keywords:Cell Biology, Cognitive Neuroscience, Physiology, Biochemistry, General Medicine, G-protein coupled receptors, Neuropeptides, fluorescent proteins, imaging, optogenetics
Language:English
Date:17 August 2022
Deposited On:03 Aug 2022 10:38
Last Modified:28 Nov 2023 02:44
Publisher:American Chemical Society (ACS)
ISSN:1948-7193
OA Status:Closed
Publisher DOI:https://doi.org/10.1021/acschemneuro.2c00394
PubMed ID:35894205
Project Information:
  • : FunderUniversity of Zurich
  • : Grant ID
  • : Project Title