Evidence map›Paper›PMID 31240399›Full record

ArticleJournal of materials science. Materials in medicine2019

A self-cleaning, mechanically robust membrane for minimizing the foreign body reaction: towards extending the lifetime of sub-Q glucose biosensors.

A Kristen Means, Ping Dong, Fred J Clubb, Molly C Friedemann, Lydia E Colvin, Courtney A Shrode, Gerard L Coté, Melissa A Grunlan

Open access · greenAbstract read
In one paragraph

Article in Journal of materials science. Materials in medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.2field-weighted citation impact, top 23% 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

10 citing papers in PubMed, 22 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Flexible Temperature Sensors.Frontiers in chemistry · 2021
    Review
  10. 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

8 authors at 1 institution in 1 country.

A Kristen MeansDepartment of Materials Science & Engineering, Texas A&M University, College Station, TX, 77843-3003, USA.
Ping DongDepartment of Biomedical Engineering, Texas A&M University, College Station, TX, 77843-3120, USA.
Fred J ClubbDepartment of Biomedical Engineering, Texas A&M University, College Station, TX, 77843-3120, USA.
Molly C FriedemannDepartment of Veterinary Pathobiology, Texas A&M University, College Station, TX, 77843-4467, USA.
Lydia E ColvinDepartment of Biomedical Engineering, Texas A&M University, College Station, TX, 77843-3120, USA.
Courtney A ShrodeDepartment of Biomedical Engineering, Texas A&M University, College Station, TX, 77843-3120, USA.
Gerard L CotéDepartment of Biomedical Engineering, Texas A&M University, College Station, TX, 77843-3120, USA.
Melissa A GrunlanDepartment of Materials Science & Engineering, Texas A&M University, College Station, TX, 77843-3003, USA. mgrunlan@tamu.edu.ORCID http://orcid.org/0000-0002-5428-0461
Texas A&M University · US

Funding

A Self-Cleaning Membrane to Extend the Lifetime of an Implanted Glucose BiosensorR01DK095101 · NIDDK · TEXAS ENGINEERING EXPERIMENT STATION · PI GRUNLAN, MELISSA · 2012 to 2016
$1.6M
NIDDK NIH HHS R01 DK095101
6 · The paper itself

Abstract

Long-term, subcutaneously implanted continuous glucose biosensors have the potential to improve diabetes management and reduce associated complications. However, the innate foreign body reaction (FBR) both alters the local glucose concentrations in the surrounding tissues and compromises glucose diffusion to the biosensor due to the recruitment of high-metabolizing inflammatory cells and the formation of a dense, collagenous fibrous capsule. Minimizing the FBR has mainly focused on "passively antifouling" materials that reduce initial cellular attachment, including poly(ethylene glycol) (PEG). Instead, the membrane reported herein utilizes an "actively antifouling" or "self-cleaning" mechanism to inhibit cellular attachment through continuous, cyclic deswelling/reswelling in response to normal temperature fluctuations of the subcutaneous tissue. This thermoresponsive double network (DN) membrane is based on N-isopropylacrylamide (NIPAAm) and 2-acrylamido-2-methylpropane sulfonic acid (AMPS) (75:25 and 100:0 NIPAAm:AMPS in the 1st and 2nd networks, respectively; "DN-25%"). The extent of the FBR reaction of a subcutaneously implanted DN-25% cylindrical membrane was evaluated in rodents in parallel with a PEG-diacrylate (PEG-DA) hydrogel as an established benchmark biocompatible control. Notably, the DN-25% implants were more than 25× stronger and tougher than the PEG-DA implants while maintaining a modulus near that of subcutaneous tissue. From examining the FBR at 7, 30 and 90 days after implantation, the thermoresponsive DN-25% implants demonstrated a rapid healing response and a minimal fibrous capsule (~20-25 µm), similar to the PEG-DA implants. Thus, the dynamic self-cleaning mechanism of the DN-25% membranes represents a new approach to limit the FBR while achieving the durability necessary for long-term implantable glucose biosensors.

Indexed as

Biosensing TechniquesBlood Glucose Self-MonitoringMembranes, ArtificialAcrylamidesAlkanesulfonatesAnimalsBiocompatible MaterialsBlood GlucoseCollagenForeign-Body ReactionHydrogelsInflammationMaleMaterials TestingPolyethylene GlycolsRats2-acrylamido-2-methylpropanesulfonateAcrylamidesAlkanesulfonatesBiocompatible MaterialsBlood GlucoseCollagenHydrogelsMembranes, ArtificialN-isopropylacrylamidepoly(ethylene glycol)diacrylatePolyethylene GlycolsBiocompatibilityDouble networkHydrogelPNIPAAmThermoresponsive

Identifiers

PMID31240399
PMCPMC6988489
OpenAlexW2956011699

What OpenQuestion holds

Textmetadata
LicenceTDM
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.