Evidence map›Paper›PMID 38931839›Full record

ArticlePharmaceutics2024

Structural Optimization of Carboxy-Terminal Phenylalanine-Modified Dendrimers for T-Cell Association and Model Drug Loading.

Hiroya Shiba, Tomoka Hirose, Akinobu Sakai, Ikuhiko Nakase, Akikazu Matsumoto, Chie Kojima

Abstract read
In one paragraph

Article in Pharmaceutics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
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.

Hiroya ShibaDepartment of Applied Chemistry, Graduate School of Engineering, Osaka Metropolitan University, 1-1 Gakuen-cho, Naka-ku, Sakai 599-8531, Osaka, Japan.
Tomoka HiroseDepartment of Applied Chemistry, Graduate School of Engineering, Osaka Metropolitan University, 1-1 Gakuen-cho, Naka-ku, Sakai 599-8531, Osaka, Japan.
Akinobu SakaiDepartment of Applied Chemistry, Graduate School of Engineering, Osaka Metropolitan University, 1-1 Gakuen-cho, Naka-ku, Sakai 599-8531, Osaka, Japan.
Ikuhiko NakaseDepartment of Biological Science, Graduate School of Science, Osaka Metropolitan University, 1-1 Gakuen-cho, Naka-ku, Sakai 599-8531, Osaka, Japan.
Akikazu MatsumotoDepartment of Applied Chemistry, Graduate School of Engineering, Osaka Metropolitan University, 1-1 Gakuen-cho, Naka-ku, Sakai 599-8531, Osaka, Japan.
Chie KojimaDepartment of Applied Chemistry, Graduate School of Engineering, Osaka Metropolitan University, 1-1 Gakuen-cho, Naka-ku, Sakai 599-8531, Osaka, Japan.ORCID 0000-0002-2208-5784

Funding

Japan Society for the Promotion of Science KAKENHI JP19H05714Japan Society for the Promotion of Science KAKENHI JP20H05232Japan Society for the Promotion of Science KAKENHI JP22H04556Japan Society for the Promotion of Science KAKENHI JP24K01558Osaka Metropolitan University 2022 and 2023Takeda Science Foundation 2021089630
6 · The paper itself

Abstract

Dendrimers are potent nanocarriers in drug delivery systems because their structure can be precisely controlled. We previously reported that polyamidoamine (PAMAM) dendrimers that were modified with 1,2-cyclohexanedicarboxylic acid (CHex) and phenylalanine (Phe), PAMAM-CHex-Phe, exhibited an effective association with various immune cells, including T-cells. In this study, we synthesized various carboxy-terminal Phe-modified dendrimers with different linkers using phthalic acid and linear dicarboxylic acids to determine the association of these dendrimers with Jurkat cells, a T-cell model. PAMAM-

Indexed as

dendrimerdrug delivery systemencapsulationphenylalanineT-cells

Identifiers

PMID38931839
PMCPMC11206903

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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.