Neural cells secrete a unique repertoire of proteins
Bibliographic record
Abstract
Proteins that are released from cells consist of those in the extracellular matrix, as well as extracellular signaling and adhesion molecules. The majority of these extracellular proteins are, however, unknown. To determine their identity, we have used a proteomics approach to define proteins released from neurons, astrocytes and neural precursor cells. Using two-dimensional gels and liquid chromatography/mass spectrometry technology, it is shown that while astrocytes release a relatively small number of proteins, neurons and neuronal precursor cells release a larger number of proteins with more functional diversity. Although there is overlap between the different cell types, the exact composition of the extracellular protein pool is unique for each cell population. The various subsets of extracellular neural proteins include those involved in cellular Redox regulation and chaperones. In addition, many proteolytic enzymes are found outside of the cell. These data show that the extracellular space within the nervous system has a more diverse protein composition than previously thought.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".