Evidence map›Paper›PMID 28362408›Full record

ArticleJournal of visualized experiments : JoVE2017

In Vitro Imaging and Quantification of the Drug Targeting Efficiency of Fluorescently Labeled GnRH Analogues.

József Murányi, Attila Varga, Bianka Gurbi, Pál Gyulavári, Gábor Mező, Tibor Vántus

Open access · bronzeAbstract readVideo-Audio Media
In one paragraph

Article in Journal of visualized experiments : JoVE, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 97% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

6 authors at 2 institutions in 1 country.

József MurányiMTA-SE Pathobiochemistry Research Group, Semmelweis University; Department of Medical Chemistry, Molecular Biology and Pathobiochemistry, Semmelweis University; muranyi.jozsef@med.semmelweis-univ.hu.
Attila VargaMTA-SE Pathobiochemistry Research Group, Semmelweis University.
Bianka GurbiMTA-SE Pathobiochemistry Research Group, Semmelweis University.
Pál GyulaváriMTA-SE Pathobiochemistry Research Group, Semmelweis University.
Gábor MezőMTA-ELTE Research Group of Peptide Chemistry, Eötvös Loránd University.
Tibor VántusDepartment of Medical Chemistry, Molecular Biology and Pathobiochemistry, Semmelweis University.
Semmelweis University · HUEötvös Loránd University · HU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

GnRH analogues are effective targeting moieties and able to deliver anticancer agents selectively into malignant tumor cells which highly express GnRH receptors. However, the quantitative analysis of GnRH analogues' cellular uptake and the investigated cell types in GnRH-based drug delivery systems are currently limited. Previously introduced, selectively labeled fluorescent GnRH I, -II and -III derivatives provide great detectability, and they have suitable chemical properties for reproducible and robust experiments. We also found that the appropriate up-to-date methods with these labeled GnRH analogues could offer novel information about the GnRH-based drug delivery systems. This manuscript introduces some simple and fast experiments regarding the cellular uptake of [D-Lys

Indexed as

Antineoplastic AgentsCell LineDrug Delivery SystemsFlow CytometryGonadotropin-Releasing HormoneHumansProtein PrecursorsReceptors, LHRHAntineoplastic AgentsGonadotropin-Releasing HormoneLHRH, His(5)-Trp(7)-Tyr(8)-progonadoliberin IProtein PrecursorsReceptors, LHRH

Identifiers

PMID28362408
PMCPMC5409304
OpenAlexW2599520641

What OpenQuestion holds

Textmetadata
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.