Evidence map›Paper›PMID 38276484›Full record

ReviewPharmaceutics2023

Cell Membrane-Derived Nanovehicles for Targeted Therapy of Ischemic Stroke: From Construction to Application.

Cui Hao, Ma Sha, Yang Ye, Chengxiao Wang

Open access · goldAbstract readReview
In one paragraph

Review in Pharmaceutics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.0field-weighted citation impact, top 13% 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

10 citing papers in PubMed, 13 citations in OpenAlex.

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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

4 authors at 2 institutions in 1 country.

Cui HaoSchool of Life Science and Technology, Kunming University of Science and Technology, Kunming 650500, China.
Ma ShaSchool of Life Science and Technology, Kunming University of Science and Technology, Kunming 650500, China.
Yang YeSchool of Life Science and Technology, Kunming University of Science and Technology, Kunming 650500, China.
Chengxiao WangSchool of Life Science and Technology, Kunming University of Science and Technology, Kunming 650500, China.
Kunming University of Science and Technology · CNYunnan Metallurgical Group (China) · CN

Funding

National Natural Science Foundation of China 81760642; 82060645 and 82260698the Key Natural Science Foundation of Yunnan Province 202101AT070099the Key R&D Project of Yunnan Provincial Science and Technology Department 202003AC100013
6 · The paper itself

Abstract

Ischemic stroke (IS) is a prevalent form of stroke and a leading cause of mortality and disability. Recently, cell membrane-derived nanovehicles (CMNVs) derived from erythrocytes, thrombocytes, neutrophils, macrophages, neural stem cells, and cancer cells have shown great promise as drug delivery systems for IS treatment. By precisely controlling drug release rates and targeting specific sites in the brain, CMNVs enable the reduction in drug dosage and minimization of side effects, thus significantly enhancing therapeutic strategies and approaches for IS. While there are some reviews regarding the applications of CMNVs in the treatment of IS, there has been limited attention given to important aspects such as carrier construction, structural design, and functional modification. Therefore, this review aims to address these key issues in CMNVs preparation, structural composition, modification, and other relevant aspects, with a specific focus on targeted therapy for IS. Finally, the challenges and prospects in this field are discussed.

Indexed as

biomimetic systemscell membranesformulationischemic strokereview

Identifiers

PMID38276484
PMCPMC10819970
OpenAlexW4389979040

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.