Interferon γ induced compositional changes in human bone marrow derived mesenchymal stem/stromal cells
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.
Bibliographic record
Abstract
BACKGROUND: Mesenchymal stem/stromal cells (MSC) display a range of immunoregulatory properties which can be enhanced by the exposure to cytokines such interferon γ (IFN-γ). However the compositional changes associated with the 'licensing' of these cells have not been clearly defined. The present study was undertaken to provide a detailed comparative proteomic analysis of the compositional changes that occur in human bone marrow derived MSC following 20 h treatment with IFN-γ. METHODS: 2D LC MSMS analysis of control and IFN-γ treated cells from 5 different healthy donors provided confident identification of more than 8400 proteins. RESULTS: In total 210 proteins were shown to be significantly altered in their expression levels (≥|2SD|) following IFN-γ treatment. The changes for several of these proteins were confirmed by flow cytometry. STRING analysis determined that approximately 30% of the altered proteins physically interacted in described interferon mediated processes. Comparison of the list of proteins that were identified as changed in the proteomic analysis with data for the same proteins in the Interferome DB indicated that ~35% of these proteins have not been reported to be IFN-γ responsive in a range of cell types. CONCLUSIONS: This data provides an in depth analysis of the proteome of basal and IFN-γ treated human mesenchymal stem cells and it identifies a number of novel proteins that may contribute to the immunoregulatory capacity if IFN-γ licensed cells.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it