Evidence map›Paper›PMID 31890339›Full record

ArticleJournal of pharmaceutical analysis2019

FITC labeling of human insulin and transport of FITC-insulin conjugates through MDCK cell monolayer.

Darshana Shah, Yuxing Guo, Joseph Ocando, Jun Shao

Open access · goldAbstract read
In one paragraph

Article in Journal of pharmaceutical analysis, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
1.1field-weighted citation impact, top 22% 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

17 citing papers in PubMed, 45 citations in OpenAlex.

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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

4 authors at 1 institution in 1 country.

Darshana ShahAvion Pharmaceuticals, 1880 McFarland Parkway, Suite 110-B, Alpharetta, GA, 30005, USA.
Yuxing GuoDepartment of Pharmaceutical Sciences, College of Pharmacy and Health Sciences, St. John's University, 8000 Utopia Parkway, Queens, NY, 11439, USA.
Joseph OcandoDepartment of Pharmaceutical Sciences, College of Pharmacy and Health Sciences, St. John's University, 8000 Utopia Parkway, Queens, NY, 11439, USA.
Jun ShaoDepartment of Pharmaceutical Sciences, College of Pharmacy and Health Sciences, St. John's University, 8000 Utopia Parkway, Queens, NY, 11439, USA.
St. John's University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fluorescein isothiocyanate-labeled insulin (FITC-insulin) has been widely used for bioanalytical applications. Due to the high cost of commercial FITC-insulin and tedious labeling procedures described in the literature, there is still a need to develop a cost effective, reliable and quick labeling method for insulin. The purpose of the present work was to develop a quick and affordable method for FITC labeling of human insulin and to determine the effect of different conjugations of FITC to human insulin on its permeability through the MDCK cell monolayer. FITC labeling of insulin gives mono-, di- or tri-conjugates depending on the reaction time and the molar ratio of FITC:insulin. Mono-conjugate with unlabeled insulin, mixture of di- and tri-conjugate, and tri-conjugate with very little amount of di-conjugate were synthesized in less than 4 h. Degree of conjugation had an effect on the permeability of insulin through the MDCK cell monolayer. Mono-conjugate had higher permeability than the unlabeled insulin due to increase in partition coefficient. However, tri-conjugate showed lower permeability than the unlabeled insulin due to the increase in molecular weight.

Indexed as

ConjugatesFITC labelingInsulinMDCK cellsMono-conjugateTri-conjugate

Identifiers

PMID31890339
PMCPMC6931083
OpenAlexW2970793190

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.