Blocking TGF-β Expression Attenuates Tumor Growth in Lung Cancers, Potentially Mediated by Skewing Development of Neutrophils
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
In the tumor microenvironment (TME), cells secrete a cytokine known as transforming growth factor-β (TGF-β), which polarizes tumor-associated neutrophils (TANs) towards a protumor phenotype. In this work, C57BL/6 mice with TGF-β1 gene knocked out selectively in myofibroblasts receive orthotopic implantation of Lewis lung carcinoma (LLC). Then, TANs’ differentiation and tumor growth are studied both in vivo and in vitro, to examine the potential effects of TGF-β levels in TME on neutrophil polarization and cancer progression. Possible results are anticipated and discussed from various aspects. Though tumor suppression via inhibition of TGF-β signaling has been widely studied in this field, this study is the first to present a detailed experimental design for evaluating the potential antitumor effects of blocking TGF-β expression. This work provides a creative approach for cancer treatment targeting specific cytokines, and the experimental design presented here may apply to future research on other cytokines, promoting the development of novel cancer-treating strategies.
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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 it