Evidence map›Paper›PMID 36559202›Full record

ReviewPharmaceutics2022

Design of Nanoparticles in Cancer Therapy Based on Tumor Microenvironment Properties.

Bita Mahdavi Firouzabadi, Maria Rosa Gigliobianco, Joice Maria Joseph, Roberta Censi, Piera Di Martino

Abstract readReview
In one paragraph

Review in Pharmaceutics, 2022. 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. Review
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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.

Bita Mahdavi FirouzabadiSchool of Pharmacy, University of Camerino, CHiP Chemistry Interdisciplinary Project, Via Madonna delle Carceri, 62032 Camerino, Italy.
Maria Rosa GigliobiancoPercuros B.V., Zernikedreef 8, 2333 CL Leiden, The Netherlands.
Joice Maria JosephSchool of Pharmacy, University of Camerino, CHiP Chemistry Interdisciplinary Project, Via Madonna delle Carceri, 62032 Camerino, Italy.ORCID 0000-0002-0929-5867
Roberta CensiSchool of Pharmacy, University of Camerino, CHiP Chemistry Interdisciplinary Project, Via Madonna delle Carceri, 62032 Camerino, Italy.
Piera Di MartinoSchool of Pharmacy, University of Camerino, CHiP Chemistry Interdisciplinary Project, Via Madonna delle Carceri, 62032 Camerino, Italy.ORCID 0000-0002-7657-3556

Funding

European Commission H2020-MSCA-RISE-2017-Cancer (grant number 777682); H2020-MSCA-ITN-2020-CAST (grant number 857894)
6 · The paper itself

Abstract

Cancer is one of the leading causes of death worldwide, and battling cancer has always been a challenging subject in medical sciences. All over the world, scientists from different fields of study try to gain a deeper knowledge about the biology and roots of cancer and, consequently, provide better strategies to fight against it. During the past few decades, nanoparticles (NPs) have attracted much attention for the delivery of therapeutic and diagnostic agents with high efficiency and reduced side effects in cancer treatment. Targeted and stimuli-sensitive nanoparticles have been widely studied for cancer therapy in recent years, and many more studies are ongoing. This review aims to provide a broad view of different nanoparticle systems with characteristics that allow them to target diverse properties of the tumor microenvironment (TME) from nanoparticles that can be activated and release their cargo due to the specific characteristics of the TME (such as low pH, redox, and hypoxia) to nanoparticles that can target different cellular and molecular targets of the present cell and molecules in the TME.

Indexed as

cancer therapynanoparticlesnano-systemstumor microenvironment

Identifiers

PMID36559202
PMCPMC9785496

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.