Evidence map›Paper›PMID 36355289›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2023

Extracellular Vesicle Isolation and Characterization for Applications in Cartilage Tissue Engineering and Osteoarthritis Therapy.

Alexander Otahal, Andrea De Luna, Ali Mobasheri, Stefan Nehrer

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2023. 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
1.0field-weighted citation impact, top 23% 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, 2 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

4 authors at 2 institutions in 2 countries.

Alexander OtahalCenter for Regenerative Medicine, University For Continuing Education, Krems, Austria.
Andrea De LunaCenter for Regenerative Medicine, University For Continuing Education, Krems, Austria.
Ali MobasheriDepartment of Regenerative Medicine, State Research Institute Centre for Innovative Medicine, Vilnius, Lithuania. ali.mobasheri@oulu.fi.
Stefan NehrerCenter for Regenerative Medicine, University For Continuing Education, Krems, Austria. stefan.nehrer@donau-uni.ac.at.
Universität für Weiterbildung Krems · ATState Research Institute Centre for Innovative Medicine · LT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Extracellular vesicles (EVs) have the capacity for use in cartilage tissue engineering by stimulating tissue repair and microenvironmental reprogramming. This makes them ideal candidates for treating focal cartilage defects and cartilage degeneration in osteoarthritis (OA). Observational studies have reported beneficial biological effects of EVs, such as inhibition of inflammation, enhanced extracellular matrix deposition, and reduced cartilage degradation. Isolation of EVs derived from different source materials such as conditioned cell culture media or biofluids is essential to attribute observed biological effects to EVs as genuine effectors. This chapter presents a density- and a size-based method as well as a combination of both for isolation of EVs from conditioned cell culture media or biofluids. In addition, three methods for characterization of isolated EVs are suggested based on physical properties, protein profiling, and ultrastructural morphology.

Indexed as

Extracellular VesiclesOsteoarthritisCartilageChondrocytesCulture Media, ConditionedExtracellular MatrixHumansTissue EngineeringCulture Media, ConditionedCartilage defectChondrocyteExtracellular vesicleImmunomodulationOsteoarthritisRegeneration

Identifiers

PMID36355289
OpenAlexW4308861759

What OpenQuestion holds

Textmetadata
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.