Les sphingolipides : vecteurs d’agents pathogènes et cause de maladies génétiques
Bibliographic record
Abstract
Sphingolipids are present in all eukaryotic cells and share a sphingoid base : sphingosine. They were first discovered in 1884 and for a long time they were thought to participate to membrane structure only. Recently it has been established that they are mainly located in particular areas of the membrane called rafts which are signalling platforms. It has also been demonstrated that sphingolipids are receptors and second messengers. They play a crucial role in cellular functioning and are necessary to maintenance and developing of living organisms. However due to their receptor properties, they are also gateway for penetration of pathogenic agents such as virus (Ebola, HIV) or toxins (botulinium, tetanus). These agents first bind to glycosphingolipids or proteins mainly located in rafts. The complex so formed is required for the crossing of the membrane by the pathogenic agent. Sphingolipids metabolism is regulated by numerous enzymes. A failure in the activity of one of them induces an accumulation of sphingolipids known as sphingolipidoses. These are genetic diseases having severe consequences for the survival of the organism. The precise mechanisms of the sphingolipidoses are still mainly unknown which explains why few therapeutic strategies are available. These particular properties of lipids rafts and sphingolipids explain why a growing number of studies in the medical and scientific fields are devoted to them.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.005 |
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".