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Navigating the Immunological Crossroads: Mesenchymal Stem/Stromal Cells as Architects of Inflammatory Harmony in Tissue-Engineered Constructs

2024· review· en· W4396955393 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

VenueBioengineering · 2024
Typereview
Languageen
FieldMedicine
TopicMesenchymal stem cell research
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMesenchymal stem cellStromal cellImmune systemParacrine signallingRegeneration (biology)Stem cellRegenerative medicineMicrocarrierMedicineInflammationImmunologyBiologyCell biologyCancer researchCellInternal medicine

Abstract

fetched live from OpenAlex

In the dynamic landscape of tissue engineering, the integration of tissue-engineered constructs (TECs) faces a dual challenge-initiating beneficial inflammation for regeneration while avoiding the perils of prolonged immune activation. As TECs encounter the immediate reaction of the immune system upon implantation, the unique immunomodulatory properties of mesenchymal stem/stromal cells (MSCs) emerge as key navigators. Harnessing the paracrine effects of MSCs, researchers aim to craft a localized microenvironment that not only enhances TEC integration but also holds therapeutic promise for inflammatory-driven pathologies. This review unravels the latest advancements, applications, obstacles, and future prospects surrounding the strategic alliance between MSCs and TECs, shedding light on the immunological symphony that guides the course of regenerative medicine.

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), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.869
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.004
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 head0.050
GPT teacher head0.367
Teacher spread0.318 · 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