Evidence map›Paper›PMID 34683947›Full record

ReviewPharmaceutics2021

Thermoresponsive Chitosan-Grafted-Poly(

Lorenzo Marsili, Michele Dal Bo, Federico Berti, Giuseppe Toffoli

Abstract readReview
In one paragraph

Review in Pharmaceutics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Recent developments in chitosan based microgels and their hybrids.International journal of biological macromolecules · 2024
    Review
  4. Article
  5. Review
  6. Immunogenicity of inactivatedIranian journal of basic medical sciences · 2022
    Article
  7. 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

4 authors.

Lorenzo MarsiliDepartment of Chemical and Pharmaceutical Sciences, University of Trieste, Via Licio Giorgieri 1, 34127 Trieste, Italy.
Michele Dal BoExperimental and Clinical Pharmacology Unit, CRO National Cancer Institute IRCCS, Via Franco Gallini 2, 33081 Aviano, Italy.ORCID 0000-0001-8668-7621
Federico BertiDepartment of Chemical and Pharmaceutical Sciences, University of Trieste, Via Licio Giorgieri 1, 34127 Trieste, Italy.ORCID 0000-0001-5608-3798
Giuseppe ToffoliExperimental and Clinical Pharmacology Unit, CRO National Cancer Institute IRCCS, Via Franco Gallini 2, 33081 Aviano, Italy.ORCID 0000-0002-5323-4762

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microgels can be considered soft, porous and deformable particles with an internal gel structure swollen by a solvent and an average size between 100 and 1000 nm. Due to their biocompatibility, colloidal stability, their unique dynamicity and the permeability of their architecture, they are emerging as important candidates for drug delivery systems, sensing and biocatalysis. In clinical applications, the research on responsive microgels is aimed at the development of "smart" delivery systems that undergo a critical change in conformation and size in reaction to a change in environmental conditions (temperature, magnetic fields, pH, concentration gradient). Recent achievements in biodegradable polymer fabrication have resulted in new appealing strategies, including the combination of synthetic and natural-origin polymers with inorganic nanoparticles, as well as the possibility of controlling drug release remotely. In this review, we provide a literature review on the use of dual and multi-responsive chitosan-grafted-poly-(

Indexed as

biodegradable polymersdrug deliverymicrogelssmart delivery systemsthermoresponsivity

Identifiers

PMID34683947
PMCPMC8539247

What OpenQuestion holds

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LicenceCC BY
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.