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Record W3086028255 · doi:10.1186/s12964-020-00650-6

Exosomal microRNAs derived from mesenchymal stem cells: cell-to-cell messages

2020· review· en· W3086028255 on OpenAlexaff
Kasra Asgarpour, Zahra Shojaei, Fatemeh Amiri, Jafar Ai, Maryam Mahjoubin‐Tehran, Faezeh Ghasemi, Reza Arefnezhad, Michael R. Hamblin, Hamed Mirzaei

Bibliographic record

VenueCell Communication and Signaling · 2020
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicExtracellular vesicles in disease
Canadian institutionsWestern University
FundersNational Institute of Allergy and Infectious DiseasesNational Institutes of HealthKashan University of Medical Sciences
KeywordsMesenchymal stem cellmicroRNAStem cellMicrovesiclesCellCell biologyBiologyComputational biologyGeneticsGene

Abstract

fetched live from OpenAlex

Exosomes are extracellular vesicles characterized by their size, source, release mechanism and contents. MicroRNAs (miRNAs) are single stranded non-coding RNAs transcribed from DNA. Exosomes and miRNAs are widespread in eukaryotic cells, especially in mesenchymal stem cells (MSCs). MSCs are used for tissue regeneration, and also exert paracrine, anti-inflammatory and immunomodulatory effects. However, the use of MSCs is controversial, especially in the presence or after the remission of a tumor, due to their secretion of growth factors and their migration ability. Instead of intact MSCs, MSC-derived compartments or substances could be used as practical tools for diagnosis, follow up, management and monitoring of diseases. Herein, we discuss some aspects of exosomal miRNAs derived from MSCs in the progression, diagnosis and treatment of various diseases. Video Abstract.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.004

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.027
GPT teacher head0.274
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations225
Published2020
Admission routes1
Has abstractyes

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