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Related Experiment Video

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Sustained Administration of β-cell Mitogens to Intact Mouse Islets Ex Vivo Using Biodegradable Poly(lactic-co-glycolic acid) Microspheres
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Non inflammatory boronate based glucose-responsive insulin delivery systems.

Indrani Dasgupta1, Eric A Tanifum, Mayank Srivastava

  • 1School of Biomedical Informatics, The University of Texas Health Sciences Center at Houston, Houston, Texas, United States of America.

Plos One
|January 25, 2012
PubMed
Summary

Researchers developed new glucose-sensitive liposome agglomerates using boronic acids, replacing toxic ConcanavalinA. These Agglomerated Vesicle Technologies (AVT) release insulin in response to glucose levels.

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Area of Science:

  • Biomaterials Science
  • Drug Delivery Systems
  • Nanotechnology

Background:

  • ConcanavalinA (ConA) was previously used for liposome agglomeration but has toxic and inflammatory effects in vivo.
  • There is a need for non-inflammatory, glucose-sensitive cross-linkers for advanced drug delivery systems.

Purpose of the Study:

  • To screen boronic acids as non-inflammatory alternatives to ConA for creating glucose-sensitive liposome agglomerates.
  • To develop Agglomerated Vesicle Technology (AVT) for triggered insulin release.

Main Methods:

  • Screening of boronic acids for inflammatory potential, cytotoxicity, and glucose-binding.
  • Conjugation of lead boronic acid compounds to insulin-encapsulating nanoparticles.
  • Formation of AVTs via sugar-boronate ester linkages.
  • In vitro testing for glucose-triggered insulin release.

Main Results:

  • Boronic acids were identified as effective, non-inflammatory cross-linkers.
  • AVTs demonstrated triggered insulin release at physiologically relevant glucose concentrations (10-40 mmol/L).
  • The system showed responsiveness to multiple glucose spikes over several hours.

Conclusions:

  • Boronic acid-based AVTs offer a promising, non-inflammatory alternative to ConA for glucose-sensitive insulin delivery.
  • The release rate of insulin is controllable by glucose concentration.
  • This technology has potential for improved diabetes management through smart insulin delivery.