Measurement of the GTPase Activity of Signal-Transducing G-Proteins in Neuronal Membranes
Bibliographic record
Abstract
The methods described in this chapter are designed to measure the hydrolysis of guanosine triphosphate (GTP) to inorganic phosphate (P i ) and guanosine diphosphate (GDP), a reaction catalyzed by the GTPase enzymes (EC 3.6.1.-). The theory behind the experimental design involves using [γ- 32 P]GTP as a marker, whereby any GTPase-induced hydrolysis will result in the 32 P label appearing as 32 P, and as unhydrolyzed [γ- 32 P]GTP. It was originally described by Cassel and Selinger ( 1 ). 32 P, must be separated from [γ- 32 P]GTP, and then can be easily quantitated by using a liquid scintillation counter. The amount of 32 P i is directly proportional to the amount of [γ- 32 P]GTP hydrolyzed, and, therefore, proportional to the activity of GTPases in the preparation. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".