Evidence map›Paper›PMID 36277335›Full record

ReviewFrontiers in chemistry2022

Light-activated nanomaterials for tumor immunotherapy.

Fang Wang, Huijuan Duan, Weizhe Xu, Gang Sheng, Zhaogang Sun, Hongqian Chu

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in chemistry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.7field-weighted citation impact, top 37% 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

4 citing papers in PubMed, 8 citations in OpenAlex.

  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

6 authors at 2 institutions in 1 country.

Fang WangTranslational Medicine Center, Beijing Chest Hospital, Capital Medical University, Beijing, China.
Huijuan DuanTranslational Medicine Center, Beijing Chest Hospital, Capital Medical University, Beijing, China.
Weizhe XuTranslational Medicine Center, Beijing Chest Hospital, Capital Medical University, Beijing, China.
Gang ShengTranslational Medicine Center, Beijing Chest Hospital, Capital Medical University, Beijing, China.
Zhaogang SunTranslational Medicine Center, Beijing Chest Hospital, Capital Medical University, Beijing, China.
Hongqian ChuTranslational Medicine Center, Beijing Chest Hospital, Capital Medical University, Beijing, China.
Beijing Chest Hospital · CNCapital Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tumor immunotherapy mainly relies on activating the immune system to achieve antitumor treatment. However, the present tumor immunotherapy used in the clinic showed low treatment efficacy with high systematic toxicity. To overcome the shortcomings of traditional drugs for immunotherapy, a series of antitumor immunotherapies based on nanomaterials have been developed to enhance the body's antitumor immune response and reduce systematic toxicity. Due to the noninvasiveness, remote controllability, and high temporal and spatial resolution of light, photocontrolled nanomaterials irradiated by excitation light have been widely used in drug delivery and photocontrolled switching. This review aims to highlight recent advances in antitumor immunotherapy based on photocontrolled nanomaterials. We emphasized the advantages of nanocomposites for antitumor immunotherapy and highlighted the latest progress of antitumor immunotherapy based on photoactivated nanomaterials. Finally, the challenges and future prospects of light-activated nanomaterials in antitumor immunity are discussed.

Indexed as

antitumor immunityimmunotherapylight-activatednanomaterialssynergistic therapy

Identifiers

PMID36277335
PMCPMC9585221
OpenAlexW4303045313

What OpenQuestion holds

Textmetadata
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.