Evidence map›Paper›PMID 32365938›Full record

ReviewNanomaterials (Basel, Switzerland)2020

Chitosan Nanoparticles for Therapy and Theranostics of Hepatocellular Carcinoma (HCC) and Liver-Targeting.

Maria Cristina Bonferoni, Elisabetta Gavini, Giovanna Rassu, Marcello Maestri, Paolo Giunchedi

Abstract readReview
In one paragraph

Review in Nanomaterials (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing 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

34 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

5 authors.

Maria Cristina BonferoniDepartment of Drug Sciences, University of Pavia, 27100 Pavia, Italy.ORCID 0000-0002-1194-9372
Elisabetta GaviniDepartment of Chemistry and Pharmacy, University of Sassari, 07100 Sassari, Italy.ORCID 0000-0002-0499-9419
Giovanna RassuDepartment of Chemistry and Pharmacy, University of Sassari, 07100 Sassari, Italy.ORCID 0000-0001-6268-8179
Marcello MaestriIRCCS Policlinico San Matteo Foundation, General Surgery, 27100 Pavia, Italy.ORCID 0000-0002-5693-9151
Paolo GiunchediDepartment of Chemistry and Pharmacy, University of Sassari, 07100 Sassari, Italy.ORCID 0000-0002-2471-1355

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chitosan nanoparticles are well-known delivery systems widely used as polymeric carriers in the field of nanomedicine. Chitosan is a carbohydrate of natural origin: it is a biodegradable, biocompatible, mucoadhesive, polycationic polymer and it is endowed with penetration enhancer properties. Furthermore, it can be easily derivatized. Hepatocellular carcinoma (HCC) represents a remarkable health problem because current therapies, that include surgery, liver transplantation, trans-arterial embolization, chemoembolization and chemotherapy, present significant limitations due to the high risk of recurrence, to a lack of drug selectivity and to other serious side effects. Therefore, there is the need for new therapeutic strategies and for improving the liver-targeting to HCC. Nanomedicine consists in the use of nanoscale carriers as delivery systems to target and deliver drugs and/or diagnostic agents to specific organs or tissues. Chitosan and its derivatives can be successfully used in the preparation of nanoparticles that, for their peculiar surface-properties, can specifically interact with liver tumor, by passive and active targeting. This review concerns the use of chitosan nanoparticles for the therapy and theranostics of HCC and liver-targeting.

Indexed as

chitosanHCChepatic surgeryliver-targetingnanoparticlestheranostics

Identifiers

PMID32365938
PMCPMC7279387

What OpenQuestion holds

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Registered trials

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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.