Adenoviral-Mediated Gene Transfer into Bone Marrow: An Effective Surgical Technique in Rat
Bibliographic record
Abstract
BACKGROUND: The role of transforming growth factor-beta 1 (TGF-β₁) in the onset of bone marrow fibrosis has been confirmed in some animal models. To further understand the genetic expression of some myeloproliferative disorders affecting marrow stem cells, however, it is necessary to develop a specific and reliable procedure to deliver modified adenoviral vectors into the bone marrow cavity. The aim of this paper is to report a surgical technique designed to deliver an adenoviral vector-mediated gene expressing TGF-β₁ into the bone marrow of rat femurs. METHODS: Forty-two Sprague-Dawley rats were used in the study. Rat femurs were exposed and the compact and trabecular bones at the proximal head removed. An intrabone marrow injection of a mutated TGF-β₁ adenoviral vector, a null adenoviral vector, or PBS was delivered into the bone. Three groups were accounted (n = 14 per group): fibrogenic and positive and negative controls. The quality of the surgical entrance was assessed by means of computerized tomography and histological changes were assessed by histochemistry. The concentration of TGF-β₁ in the bone marrow was determined by ELISA. RESULTS: The surgical technique was conducted under ideal timing (approx. 10 min) and no surgical or postsurgical complications were observed. Computerized tomography revealed no changes in the bone tissue and a clean entrance was delimited through the bone to the bone marrow. HE and Masson's trichrome staining indicated highly fibrotic areas in the profibrotic group and bone marrow lavage reported a significantly higher concentration of TGF-β₁ (p < 0.05) in that same group. CONCLUSIONS: The present study confirmed that the proposed surgical technique is an effective method to deliver adenoviral vectors into the femoral bone marrow to investigate the physiopathology of bone marrow fibrosis in rats.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".