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Record W2473212441 · doi:10.12688/f1000research.8217.1

Recent insights: mesenchymal stromal/stem cell therapy for acute respiratory distress syndrome

2016· preprint· en· W2473212441 on OpenAlexafffund
Shahd Horie, John G. Laffey

Bibliographic record

VenueF1000Research · 2016
Typepreprint
Languageen
FieldMedicine
TopicMesenchymal stem cell research
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
FundersUniversity of TorontoHealth Research Board
KeywordsARDSMesenchymal stem cellMedicineMicrovesiclesCell therapyStromal cellStem-cell therapyStem cellImmunologyInflammationParacrine signallingImmune systemCancer researchLungBioinformaticsBiologyPathologyCell biologyInternal medicinemicroRNA

Abstract

fetched live from OpenAlex

Acute respiratory distress syndrome (ARDS) causes respiratory failure, which is associated with severe inflammation and lung damage and has a high mortality and for which there is no therapy. Mesenchymal stromal/stem cells (MSCs) are adult multi-progenitor cells that can modulate the immune response and enhance repair of damaged tissue and thus may provide a therapeutic option for ARDS. MSCs demonstrate efficacy in diverse in vivo models of ARDS, decreasing bacterial pneumonia and ischemia-reperfusion-induced injury while enhancing repair following ventilator-induced lung injury. MSCs reduce the pro-inflammatory response to injury while augmenting the host response to bacterial infection. MSCs appear to exert their effects via multiple mechanisms-some are cell interaction dependent whereas others are paracrine dependent resulting from both soluble secreted products and microvesicles/exosomes derived from the cells. Strategies to further enhance the efficacy of MSCs, such as by overexpressing anti-inflammatory or pro-repair molecules, are also being investigated. Encouragingly, early phase clinical trials of MSCs in patients with ARDS are under way, and experience with these cells in trials for other diseases suggests that the cells are well tolerated. Although considerable translational challenges, such as concerns regarding cell manufacture scale-up and issues regarding cell potency and batch variability, must be overcome, MSCs constitute a highly promising potential therapy for ARDS.

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 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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.635
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.103
GPT teacher head0.396
Teacher spread0.293 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations25
Published2016
Admission routes2
Has abstractyes

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