Evidence map›Paper›PMID 37560540›Full record

ReviewFrontiers in bioengineering and biotechnology2023

T Cell engineering for cancer immunotherapy by manipulating mechanosensitive force-bearing receptors.

Lingzhu Zhao, Guoqing Zhao, Jinteng Feng, Zheng Zhang, Jiayu Zhang, Hui Guo, Min Lin

Abstract readReview
In one paragraph

Review in Frontiers in bioengineering and biotechnology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 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

7 authors.

Lingzhu ZhaoThe Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China.
Guoqing ZhaoThe Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China.
Jinteng FengBioinspired Engineering and Biomechanics Center (BEBC), Xi'an Jiaotong University, Xi'an, China.
Zheng ZhangThe Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China.
Jiayu ZhangThe Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China.
Hui GuoDepartment of Medical Oncology, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Min LinThe Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

T cell immune responses are critical for in both physiological and pathological processes. While biochemical cues are important, mechanical cues arising from the microenvironment have also been found to act a significant role in regulating various T cell immune responses, including activation, cytokine production, metabolism, proliferation, and migration. The immune synapse contains force-sensitive receptors that convert these mechanical cues into biochemical signals. This phenomenon is accepted in the emerging research field of immunomechanobiology. In this review, we provide insights into immunomechanobiology, with a specific focus on how mechanosensitive receptors are bound and triggered, and ultimately resulting T cell immune responses.

Indexed as

cancer immunotherapyimmunoengineeringmechanobiology of T cellmechanosensitive receptorsT cell activation

Identifiers

PMID37560540
PMCPMC10407658

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.