Evidence map›Paper›PMID 24127747›Full record

ArticleBiomacromolecules2013

Electrospun blends of gelatin and gelatin-dendrimer conjugates as a wound-dressing and drug-delivery platform.

Alpana A Dongargaonkar, Gary L Bowlin, Hu Yang

Abstract read
In one paragraph

Article in Biomacromolecules, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
–field-weighted citation impact
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

23 citing papers in PubMed.

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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

3 authors.

Alpana A DongargaonkarDepartment of Biomedical Engineering, Virginia Commonwealth University , 401 West Main Street, Richmond, Virginia 23284, United States.
Gary L Bowlin
Hu Yang

Funding

VCU Neuroscience Center Core GrantP30NS047463 · NINDS · VIRGINIA COMMONWEALTH UNIVERSITY · PI POVLISHOCK, JOHN T · 2003 to 2013
$5.0M
NINDS NIH HHS 5P30NS047463NINDS NIH HHS P30 NS047463
6 · The paper itself

Abstract

In this work, we report a new nanofiber construct based on electrospun blends of gelatin and gelatin-dendrimer conjugates. Highly branched star-shaped polyamidoamine (PAMAM) dendrimer G3.5 was covalently conjugated to gelatin via EDC/NHS chemistry. Blends of gelatin and gelatin-dendrimer conjugates mixed with various loading levels of silver acetate (0, 0.83, 1.65, and 3.30% w/w) were successfully electrospun into nanofiber constructs (NCs). The NCs were further converted into semi-interpenetrating networks (sIPNs) with photoreactive polyethylene glycol diacrylate (Mn = 575 g mol(-1)) (PEG DA575). They were characterized in terms of fiber morphology, diameter, pore size, permeability, degradation, and mechanical properties. The resulting sIPN NCs retained nanofiber morphology, possessed similar fiber diameters to counterpart NCs, and gained improved structural stability. The sIPN NCs also showed good swelling capacity owing to porous structures and were permeable to aqueous solutions. Silver-containing sIPN NCs allowed sustained silver release and showed antimicrobial activity against two common types of pathogens, Staphylococcus aureus and Pseudomonas aeruginosa. Incorporation of dendrimers into the gelatin nanofibers through covalent conjugation not only expands drug loading capacity of nanofiber constructs but also provides tremendous flexibility for developing multifunctional electrospun dressing materials.

Indexed as

BandagesDrug Delivery SystemsAnti-Bacterial AgentsBiocompatible MaterialsDendrimersGelatinKineticsMicrobial Sensitivity TestsMolecular StructurePorosityPseudomonas aeruginosaSilverStaphylococcus aureusWound HealingAnti-Bacterial AgentsBiocompatible MaterialsDendrimersGelatinPAMAM StarburstSilver

Identifiers

PMID24127747
PMCPMC3886127

What OpenQuestion holds

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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.