Additional file 1 of Direct lineage tracing reveals Activin-a potential for improved pancreatic homing of bone marrow mesenchymal stem cells and efficient ß-cell regeneration in vivo
Bibliographic record
Abstract
Additional file 1: Supplementary Figure 1. (a) Vector map depicting pPBGFP and pCyL43 Pbase plasmids for genomic-integrating and constitutively expressing GFP in transfected BMSC. (b) Islet differentiation stages and immunostaining representative images. Supplementary Figure 2. (a) Pictorial representation of BMSC clone selection strategy using flowcytometry, (b) FACS profiling, gating and sorting parameter images for positive GFP-BMSC clone, (c) Gating strategy and analysis used for population selection with doublet discrimination before BMSC surface immunophenotyping FACS quantification, and (d) representative FACS graphs for confirming cell viability and death using propidium iodide staining and fluorescent image of GFP (green) co-labelled with dapi nuclear staining. Supplementary Figure 3. Comparative immunophenotyping characterization of unmodified and genetically modified BMSCs with key mesenchymal, hematopoietic and pancreatic endocrine cell markers with flow-cytometry. Supplementary Figure 4. Comprehensive flow cytometric quantification of percentage (a) total CD44 population and; (b) GFP population and within the injured pancreas in controls non-recipients and treated BMSC recipients with and without Activin-a treatment. Supplementary Figure 5. Comprehensive flow cytometric quantification of percentage GFP+CD44+ expressing dual population in FACS sorted single islet cell suspension. Supplementary Figure 6. (a) Immunocytochemical images from islet-like structures differentiated from GFP+BMSC. (b) pancreatic immunohistochemical sections from GFP+BMSC and GFP+BMSC + Activin-a treated animals. Supplementary Figure 7. Unedited western blot images for mesenchymal stem cells and pancreatic differentiation transcription factors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.886 | 0.202 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".