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Record W3203866006 · doi:10.1002/jev2.12141

Mesenchymal stromal cell extracellular vesicles as therapy for acute and chronic respiratory diseases: A meta‐analysis

2021· review· en· W3203866006 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Extracellular Vesicles · 2021
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicExtracellular vesicles in disease
Canadian institutionsChildren's Hospital of Eastern OntarioOttawa HospitalUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsMedicineMesenchymal stem cellMeta-analysisInternal medicineStrictly standardized mean differenceSubgroup analysisOncologyConfidence intervalPathology

Abstract

fetched live from OpenAlex

Preclinical studies suggest mesenchymal stromal cell extracellular vesicles (MSC-EVs) reduce inflammation and improve organ function in lung diseases; however, an objective analysis of all available data is needed prior to translation. Using rigorous meta-research methods, we determined the effectiveness of MSC-EVs for preclinical respiratory diseases and identified experimental conditions that may further refine this therapy. A systematic search of MEDLINE/Embase identified 1167 records. After screening, 52 articles were included for data extraction and evaluated for risk of bias and quality of reporting in study design. A random effects meta-analysis was conducted for acute lung injury (ALI; N = 23), bronchopulmonary dysplasia (BPD; N = 8) and pulmonary arterial hypertension (PAH; N = 7). Subgroup analyses identified EV methods/characteristics that may be associated with improved efficacy. Data is presented as standardized mean differences (SMD) or risk ratios (RR) with 95% confidence intervals (CI). For ALI, MSC-EVs markedly reduced lung injury (SMD -4.33, CI -5.73 to -2.92), vascular permeability (SMD -2.43, CI -3.05 to -1.82), and mortality (RR 0.39, CI 0.22 to 0.68). Small EVs were more consistently effective than large EVs whereas no differences were observed between tissue sources, immunocompatibility or isolation techniques. For BPD, alveolarization was improved by MSC-EVs (SMD -1.45, CI -2.08 to -0.82) with small EVs more consistently beneficial then small/large EVs. In PAH, right ventricular systolic pressure (SMD -4.16, CI -5.68 to -2.64) and hypertrophy (SMD -2.80, CI -3.68 to -1.91) were significantly attenuated by EVs. In BPD and PAH, EVs isolated by ultracentrifugation demonstrated therapeutic benefit whereas tangential flow filtration (N = 2) displayed minimal efficacy. Lastly, risk of bias and quality of reporting for experimental design were consistently unclear across all studies. Our findings demonstrate clear potential of MSC-EVs to be developed as therapy for acute and chronic lung diseases. However, greater transparency in research design and direct comparisons of isolation technique and EV subtypes are needed to generate robust evidence to guide clinical translation. Protocol Registration: PROSPERO CRD42020145334.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.710
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.009
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.040
GPT teacher head0.340
Teacher spread0.300 · 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