The use of mass spectrometry for the characterization of molecules co-purifying with integrins
Bibliographic record
Abstract
Cellular adhesion has been demonstrated to involve supramolecular complexes on plasma membranes of various cell types. These complexes involve not only transmembrane molecules, but rather extend into the cytoplasm to include signal transduction elements, adaptor proteins, and cytoskeletal components. Alterations in activation status or adhesion status of the cell lead to changes in specific associations within the complex. This dynamic process is believed to be mediated through post-translational events which modify the ability of various components to associate with or cross-link other elements. This reversible process of cellular adhesion is necessary for cellular migration through tissue. As adhesion molecules, integrins have a significant contribution to the functioning of these elaborate structures. Mass spectrometry has been used for the characterization of unidentified biomolecules, but this approach has not been utilized for analysis of supramolecular adhesion complexes. To test the validity of applying this technology to supramolecular complexes, proteins co-purifying with the integrin alpha-v/beta-3 were recovered from silver-stained SDS-PAGE gels and analyzed on a MALDI qQ-TOF. Using this approach, the protein(s) contained within each band on the gel could be identified. These findings support the use of mass spectrometry for the characterization of molecules co-purifying with integrins.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".