Bibliographic record
Abstract
Tumor Lysis Syndrome (TLS) is a potentially life-threatening complication of cytotoxic chemotherapy, arising from tumor cell rupture and the subsequent release of intracellular metabolites into circulation. The resulting metabolic derangements can lead to renal failure, arrhythmias, seizures, and in some cases death, yet targeted treatments for TLS remain unavailable. Recent studies have identified NINJ1 as a critical regulator of plasma membrane rupture (PMR), suggesting it acts as a final control switch for lytic cell death. The loss of NINJ1, whether through genetic knockout or pharmacological inhibition via glycine, has been shown to protect cells from PMR without altering overall cell death rates. Our study demonstrates that NINJ1 inhibition reduces PMR by up to 50% following cytotoxic chemotherapy, while maintaining their antitumor efficacy as confirmed by TUNEL and MTT assays, as well as caspase-3 activation in hematological malignancies. These findings highlight NINJ1’s potential as a targeted TLS intervention, warranting further in vivo studies to explore its clinical applications.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".