Isolation of CD146<sup>+</sup> Resident Lung Mesenchymal Stromal Cells from Rat Lungs
Bibliographic record
Abstract
Mesenchymal stromal cells (MSCs) are increasingly recognized for their therapeutic potential in a wide range of diseases, including lung diseases. Besides the use of bone marrow and umbilical cord MSCs for exogenous cell therapy, there is also increasing interest in the repair and regenerative potential of resident tissue MSCs. Moreover, they likely have a role in normal organ development, and have been attributed roles in disease, particularly those with a fibrotic nature. The main hurdle for the study of these resident tissue MSCs is the lack of a clear marker for the isolation and identification of these cells. The isolation technique described here applies multiple characteristics of lung resident MSCs (L-MSCs). Upon sacrifice of the rats, lungs are removed and rinsed multiple times to remove blood. Following mechanical dissociation by scalpel, the lungs are digested for 2-3 hr using a mix of collagenase type I, neutral protease and DNase type I. The obtained single cell suspension is subsequently washed and layered over density gradient medium (density 1.073 g/ml). After centrifugation, cells from the interphase are washed and plated in culture-treated flasks. Cells are cultured for 4-7 days in physiological 5% O2, 5% CO2 conditions. To deplete fibroblasts (CD146(-)) and to ensure a population of only L-MSCs (CD146(+)), positive selection for CD146(+) cells is performed through magnetic bead selection. In summary, this procedure reliably produces a population of primary L-MSCs for further in vitro study and manipulation. Because of the nature of the protocol, it can easily be translated to other experimental animal models.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.005 |
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".