Evidence map›Paper›PMID 38491394›Full record

ReviewInflammation and regeneration2024

Designer cell therapy for tissue regeneration.

Noyuri Zama, Satoshi Toda

Open access · goldAbstract readReview
In one paragraph

Review in Inflammation and regeneration, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.8field-weighted citation impact, top 25% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Article
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

2 authors at 1 institution in 1 country.

Noyuri ZamaWPI Nano Life Science Institute (WPI-NanoLSI), Kanazawa University, Kakuma-machi, Kanazawa , 920-1192, Japan.
Satoshi TodaWPI Nano Life Science Institute (WPI-NanoLSI), Kanazawa University, Kakuma-machi, Kanazawa , 920-1192, Japan. satoshi.toda@staff.kanazawa-u.ac.jp.ORCID http://orcid.org/0000-0003-4997-9558
Kanazawa University · JP

Funding

Japan Agency for Medical Research and Development 22bm0704048h0003Japan Agency for Medical Research and Development 23ama221318s0101Japan Society for the Promotion of Science 21H05291Ministry of Education, Culture, Sports, Science and Technology World Premier International Research Center Initiative (WPI)Precursory Research for Embryonic Science and Technology JPMJPR2147
6 · The paper itself

Abstract

Cancer cell therapy, particularly chimeric antigen receptor (CAR) T-cell therapy for blood cancers, has emerged as a powerful new modality for cancer treatment. Therapeutic cells differ significantly from conventional drugs, such as small molecules and biologics, as they possess cellular information processing abilities to recognize and respond to abnormalities in the body. This capability enables the targeted delivery of therapeutic factors to specific locations and times. Various types of designer cells have been developed and tested to overcome the shortcomings of CAR T cells and expand their functions in the treatment of solid tumors. In particular, synthetic receptor technologies are a key to designing therapeutic cells that specifically improve tumor microenvironment. Such technologies demonstrate great potential for medical applications to regenerate damaged tissues as well that are difficult to cure with conventional drugs. In this review, we introduce recent developments in next-generation therapeutic cells for cancer treatment and discuss the application of designer therapeutic cells for tissue regeneration.

Indexed as

Cell engineeringCell therapySynthetic receptorTissue microenvironmentTissue regeneration

Identifiers

PMID38491394
PMCPMC10941617
OpenAlexW4392850428

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.