Inter-organelle membrane contact sites: implications for lipid metabolism
Bibliographic record
Abstract
This article supplements a recent Perspective by Scorrano et al. in Nature Communications [10 [ (1)]:1287] in which the properties and functions of inter-organelle membrane contact sites were summarized. It is now clear that inter-organelle membrane contact sites are widespread in eukaryotic cells and that diverse pairs of organelles can be linked via unique protein tethers. An appropriate definition of what constitutes an inter-organelle membrane contact site was proposed in the Perspective. In addition, the various experimental approaches that are frequently used to study these organelle associations, as well as the advantages and disadvantages of each of these methods, were considered. The nature of the tethers that link the pairs of organelles at the contact sites was discussed in detail and some biological functions that have been ascribed to specific membrane contact sites were highlighted. Nevertheless, the functions of most types of organelle contact sites remain unclear. In the current article I have considered some of the points raised in the Perspective but have omitted detailed information on the roles of membrane contact sites in biological functions such as apoptosis, autophagy, calcium homeostasis and mitochondrial fusion. Instead, I have provided some background on the initial discovery of mitochondria-endoplasmic reticulum membrane contact sites, and have focussed on the known roles of membrane contact sites in inter-organelle lipid transport. In addition, potential roles for membrane contact sites in human diseases are briefly discussed.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.027 | 0.020 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".