Microencapsulation of Lefty-secreting engineered cells for pulmonary fibrosis therapy in mice
Bibliographic record
Abstract
Idiopathic pulmonary fibrosis (IPF) is a progressive disease that causes unremitting deposition of extracellular matrix proteins, thus resulting in distortion of the pulmonary architecture and impaired gas exchange. Associated with high morbidity and mortality, IPF is generally refractory to current pharmacological therapies. Lefty A, a potent inhibitor of transforming growth factor-β signaling, has been shown to have promising antifibrotic ability in vitro for the treatment of renal fibrosis and other potential organ fibroses. Here, we determined whether Lefty A can attenuate bleomycin (BLM)-induced pulmonary fibrosis in vivo based on a novel therapeutic strategy where human embryonic kidney 293 (HEK293) cells are genetically engineered with the Lefty A-associated GFP gene. The engineered HEK293 cells were encapsulated in alginate microcapsules and then subcutaneously implanted in ICR mice that had 1 wk earlier been intratracheally administered BLM to induce pulmonary fibrosis. The severity of fibrosis in lung tissue was assessed using pathological morphology and collagen expression to examine the effect of Lefty A released from the microencapsulated cells. The engineered HEK293 cells with Lefty A significantly reduced the expression of connective tissue growth factor and collagen type I mRNA, lessened the morphological fibrotic effects induced by BLM, and increased the expression of matrix metalloproteinase-9. This illustrates that engineered HEK293 cells with Lefty A can attenuate pulmonary fibrosis in vivo, thus providing a novel method to treat human pulmonary fibrotic disease and other organ fibroses.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".