Broadband Air Interface for 4G Mobile Radio Systems (DoCoMo Report WP 1.1: "Reference Air Interface" - Phase 2)
Bibliographic record
Abstract
Anti-tumour lipids are synthetic analogues of lysophosphatidylcholine. These drugs are both cytotoxic and cytostatic, and more interestingly, exert these effects preferentially in tumour cells. While the exact mechanism of action isn't fully elucidated, these drugs appear to preferentially partition into rigid lipid domains in cell membranes. Upon insertion, the compounds alter membrane domain organization, disrupt normal signal transduction, and cause cell death. Recently, it has been reported that these drugs induce accumulation of diacylglycerol in yeast cells which in turn sensitizes cells to the drugs. Conversely, phosphatidic acid accumulation appears to protect cells against the drugs. In the current work, the aim was to compare the biophysical effects of the drugs edelfosine, miltefosine and perifosine on monolayers of dimyristoyl phosphatidic acid, dimyristoyl glycerol and an equimolar mixture, to understand how these lipids modulate the mode of action. Surface pressure - area isotherms, compression moduli and Brewster angle microscopy were used to compare drug effects on lipid packing, monolayer compressibility and lateral domain organization of these films. Results suggest that edelfosine and miltefosine have stabilizing effects on all of the monolayers, while perifosine destabilizes dimyristoyl glycerol and the equimolar mixture. Additionally, all three drugs change the morphology of the domains observed. Based on these results the stabilization of diacylgylcerol by edelfosine and miltefosine may contribute to the mode of action as diacylglycerol is a known disruptor of bilayers. Perifosine however does not stabilize diacylglycerol, and therefore cell death may occur through a more direct inhibition of specific signal transduction. These results suggest that perifosine may illicit cytotoxicity through a different mechanism compared to the other antitumor lipid drugs.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".