Bibliographic record
Abstract
Activated hepatic stellate cells (aHSCs) are now established as a central driver of fibrosis in human liver injury. In the presence of chronic or repeated injury, fibrosis, cirrhosis, and hepatocellular carcinoma (HCC) can occur, so there is interest in down-regulating aHSCs activity in order to treat these diseases. Here, we report that Vγ9Vδ2 T cells are reduced in patients with liver cirrhosis, stimulating us to investigate possible interactions between Vγ9Vδ2 T cells and aHSCs. We find that Vγ9Vδ2 T cells kill aHSCs and killing is enhanced when aHSCs are pretreated with BPH-1236, a lipophilic analog of the bone resorption drug zoledronate. Cytotoxicity is mediated by direct cell-to-cell contact as shown by Transwell experiments and atomic force microscopy, with BPH-1236 increasing the adhesion between aHSCs and Vγ9Vδ2 T cells. Mechanistically, BPH-1236 functions by inhibiting farnesyl diphosphate synthase, leading to accumulation of the phosphoantigen isopentenyl diphosphate and recognition by Vγ9Vδ2 T cells. The cytolytic process is largely dependent on the perforin/granzyme B pathway. In a Rag2<sup>-/-</sup>γc<sup>-/-</sup> immune-deficient mouse model, we find that Vγ9Vδ2 T cells home-in to the liver, and when accompanied by BPH-1236, kill not only orthotopic aHSCs but also orthotopic HCC tumors. Collectively, our results provide the first proof-of-concept of a novel immunotherapeutic strategy for the treatment of fibrosis-cirrhosis-HCC diseases using adoptively transferred Vγ9Vδ2 T cells, combined with a lipophilic bisphosphonate.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".