Antibody Characterization Report for PLC-gamma-2 (PLCG2)
Bibliographic record
Abstract
This report presents a guide to selecting high-quality commercial antibodies against PLC-gamma-2 by Western blot, immunoprecipitation and immunofluorescence, using a standardized experimental protocol based on comparing read-outs in knockout cell lines and isogenic parental controls. The research displayed in this study can be considered a subsequent study following the initial PLC-gamma-2 report published to the YCharOS community in February 2023 (DOI:10.5281/zenodo.7671689). Although the eleven tested antibodies remain constant, a THP-1 cell line is used to test the antibodies in all 3 applications rather than a HAP1 cell line. Furthermore, in the Western blot experimental protocol, THP-1 WT and PLCG2 KO lysates were treated with or without PMA prior to antibody incubation to determine it's effect on the antibodies ability to specifically target PLC-gamma-2. Thank you to IUSM-Purdue for collaborating on this work. This study was funded in part by a grant from the National Institute on Aging under award number U54AG065181.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.028 | 0.037 |
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".