Evidence map›Paper›PMID 29323870›Full record

ReviewBioconjugate chemistry2018

Cell Membrane Bioconjugation and Membrane-Derived Nanomaterials for Immunotherapy.

Peter Y Li, Zhiyuan Fan, Hao Cheng

Abstract readReview
In one paragraph

Review in Bioconjugate chemistry, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

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  14. Biohybrid Nanosystems for Cancer Treatment: Merging the Best of Two Worlds.Advances in experimental medicine and biology · 2021
    Article
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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

3 authors.

Peter Y LiDepartment of Materials Science and Engineering , Drexel University , Philadelphia , Pennsylvania 19104 , United States.
Zhiyuan FanDepartment of Materials Science and Engineering , Drexel University , Philadelphia , Pennsylvania 19104 , United States.
Hao ChengDepartment of Materials Science and Engineering , Drexel University , Philadelphia , Pennsylvania 19104 , United States.ORCID 0000-0003-3661-1519

Funding

Injectable Biomaterial Scaffold for Inducing Antigen-Specific ToleranceR21AI133372 · NIAID · DREXEL UNIVERSITY · PI BLANKENHORN, ELIZABETH P, CHENG, HAO · 2017 to 2018
$430k
NIAID NIH HHS R21 AI133372
6 · The paper itself

Abstract

Cell membrane engineering, including live cell membrane bioconjugation and cell membrane-derived nanomaterials is a highly promising strategy to modulate immune responses for treating diseases. Many cell membrane engineering methods have potential for translation for human clinical use in the near future. In this Topical Review, we summarize the cell membrane conjugation strategies that have been investigated for cancer immunotherapy, the prevention of immune rejection to donor cells and tissues, and the induction of antigen-specific tolerance in autoimmune diseases. Additionally, cell membrane-derived or membrane-coated nanomaterials are an emerging class of nanomaterials that is attracting significant attention in the field of nanomedicine. Some of these nanomaterials have been employed to elicit immune responses against cancer, toxins, and bacteria, although their application in establishing immune tolerance has not been explored. In addition to discussing potential problems, we provide our perspectives for promising future directions.

Indexed as

AnimalsAutoimmune DiseasesBacterial InfectionsBacterial VaccinesBiocompatible MaterialsCancer VaccinesCell MembraneChemistry Techniques, SyntheticGraft RejectionHumansImmune ToleranceImmunotherapyNanomedicineNanostructuresNeoplasmsBacterial VaccinesBiocompatible MaterialsCancer Vaccines

Identifiers

PMID29323870
PMCPMC5916811

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.