Evidence map›Paper›PMID 28210618›Full record

ArticleFrontiers in molecular biosciences2017

An Optimized Procedure for the Site-Directed Labeling of NGF and proNGF for Imaging Purposes.

Pierluigi Di Matteo, Mariantonietta Calvello, Stefano Luin, Laura Marchetti, Antonino Cattaneo

Open access · goldAbstract read
In one paragraph

Article in Frontiers in molecular biosciences, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.4field-weighted citation impact, top 41% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Effect of Chemical Vapor Deposition WSFrontiers in neuroscience · 2020
    Article
  6. Article
  7. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 1 country.

Pierluigi Di MatteoBioSNS Laboratory, Scuola Normale Superiore and Istituto di Neuroscienze - CNR Pisa, Italy.
Mariantonietta CalvelloBioSNS Laboratory, Scuola Normale Superiore and Istituto di Neuroscienze - CNR Pisa, Italy.
Stefano LuinNEST Laboratory, Scuola Normale Superiore and Istituto Nanoscienze - CNR Pisa, Italy.
Laura MarchettiBioSNS Laboratory, Scuola Normale Superiore and Istituto di Neuroscienze - CNRPisa, Italy; Center for Nanotechnology Innovation@NEST, Istituto Italiano di TecnologiaPisa, Italy.
Antonino CattaneoBioSNS Laboratory, Scuola Normale Superiore and Istituto di Neuroscienze - CNR Pisa, Italy.
Scuola Normale Superiore · ITCenter for Nanotechnology Innovation · ITIstituto Nanoscienze · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Neurotrophins are growth factors of fundamental importance for the development, survival and maintenance of different neuronal and non-neuronal populations. Over the years, the use of labeled neurotrophins has helped in the study of their biological functions, leading to a better understanding of the processes that regulate their transport, traffic, and signaling. However, the diverse and heterogeneous neurotrophin labeling strategies adopted so far have often led to poorly reproducible protocols and sometimes conflicting conclusions. Here we present a robust, reliable, and fast method to obtain homogeneous preparations of fluorescent proNGF and NGF with 1:1 labeling stoichiometry. This strategy is well suited for several applications, ranging from advanced imaging techniques such as

Indexed as

fluorescent NGFfluorescent proNGFneurotrophins labelingneurotrophins purificationsignaling endosome

Identifiers

PMID28210618
PMCPMC5288393
OpenAlexW2585242204

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.