Preparation, characterization and preliminary application of polyclonal antibodies against mouse TRIM59.
Bibliographic record
Abstract
【Objective】 The research prepared the high titer and specific rabbit anti-mouse antibody of TRIM59(Tripartite motif-containing 59).【Method】 The mouse TRIM59 gene was amplified by PCR.The target fragment digested by the enzyme was cloned into pGEX-2T,taking pGEX-2T-TRIM59 into BL21 for expression induced by IPTG.The expression product of TRIM59 was collected and purified.New Zealand's White rabbits were used to produce antiserum against GST-TRIM59 recombinant proteins.The titer and specificity of the anti-mouse TRIM59 polyclonal antibodies were detected by ELISA and Western blot.【Result】 GST-TRIM59 fusion protein had been expressed successfully.5 weeks after first injection,we got antiserum against GST-TRIM59 recombinant proteins from rabbit.The titer of the anti-serum was above 1∶106 by ELISA,this antibody specific detected TRIM59 protein by Western blot.TRIM59 expression was high in prostate cancer cells by immunohistochemistry.【Conclusion】 The rabbit anti-mouse TRIM59 polyclonal antibody is characterized with high titer and specificity,which is the foundation to study the characters and function of TRIM59.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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".