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Record W2563726344 · doi:10.1158/1538-7445.am2015-1804

Abstract 1804: The role of adipose derived stromal cells for reversal of radiation fibrosis

2015· article· en· W2563726344 on OpenAlexaff
Xiao Dong Zhao, Ju Hee Lee, Kenneth W. Yip, Laurie Ailles, Fei‐Fei Liu

Bibliographic record

VenueCancer Research · 2015
Typearticle
Languageen
FieldMedicine
TopicMesenchymal stem cell research
Canadian institutionsPediatric Oncology GroupPublic Health OntarioOntario Institute for Cancer ResearchUniversity of WaterlooUniversity of Toronto
Fundersnot available
KeywordsFibrosisAdipose tissueMedicineTransplantationStromal cellPathologyMesenchymal stem cellWound healingExtracellular matrixCancer researchInternal medicineBiologySurgeryCell biology

Abstract

fetched live from OpenAlex

Abstract Hypothesis: Up to 70% of patients after radiotherapy develop radiation fibrosis (RF), an irreversible scarring of normal tissue resulting in functional morbidity and increased risk of surgical complications. Adipose-derived stromal cells (ADSCs) have been used effectively for the treatment of complex wounds in animal models and clinical trials. We hypothesize that ADSCs may reverse RF by repopulating mesenchymal precursor cells and by providing angiogenic, anti-inflammatory, and matrix remodeling factors. Methods: A RF animal model was developed and ADSC isolation was confirmed by immunophenotype and differentiation assay. GFP and luciferase labelled ADSCs were used to assess biodistribution after transplantation. To determine the therapeutic effect of ADSC transplantation for RF, we assessed functional changes to leg contracture, oxygen saturation and perfusion and molecular changes to inflammation, vascularization, and matrix remodeling. To determine the mechanism of ADSC-mediated fibrosis reversal, we assessed transcriptomic and epigenetic changes to RF tissue. Results: A RF model was created by radiating the hind limb of C3H mice. This model showed a dose dependent leg contracture and histological findings of fibrosis. We confirmed the immunophenotype of isolated ADSC and their ability to differentiate into adipogenic, chondrogenic, and osteogenic lineages. ADSC transplantation showed a statistically significant trend towards improved leg contracture (2-way ANOVA, p<0.05). Biodistribution studies confirmed the presence of ADSCs in the subdermis of RF tissue with persistence for at least 18 days post-transplantation. Preliminary RNA-seq analysis using unsupervised hierarchical clustering showed ADSC treated radiation tissue was more similar to normal tissue than control. In depth RNA-seq data analysis is underway. Conclusions: ADSC transplantation may be an effective treatment for the reversal of radiation fibrosis. As cancer survivorship increases, the prevalence of radiation fibrosis will rise and necessitate increased focus on effective treatment strategies for this condition. Citation Format: Xiao Zhao, Ju Hee Lee, Kenneth Yip, Laurie Ailles, Fei-Fei Liu. The role of adipose derived stromal cells for reversal of radiation fibrosis. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1804. doi:10.1158/1538-7445.AM2015-1804

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.113
GPT teacher head0.414
Teacher spread0.301 · 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 designObservational
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

Citations0
Published2015
Admission routes1
Has abstractyes

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