Mouse PSP94 expression is prostate tissue‐specific as demonstrated by a comparison of multiple antibodies against recombinant proteins
Bibliographic record
Abstract
Prostate tissue-specific gene expression is crucial for driving potentially therapeutic genes to target specifically to the prostate. Prostate secretory protein of 94 amino acids (PSP94), also known as beta-MSP (microseminoprotein), is one of the three most abundant secretory proteins of the prostate gland, and is generally considered to be prostate tissue-specific. We have previously demonstrated that the expression of the rat PSP94 gene is strictly prostate tissue-specific by an antibody against a recombinant rat PSP94. In order to study prostate targeting utilizing the PSP94 gene in a mouse pre-clinical experimental model, we need to establish antibodies against mouse PSP94 to confirm if it is prostate tissue-specific as well. In this study, firstly we raised a polyclonal antibody against a recombinant glutathione-S-transferase- (GST-) mouse mature form of PSP94. However, it showed very poor immunoreactivity against prostate tissue PSP94 as tested in Western blotting experiments. Neither antibodies against rat PSP94 nor mouse PSP94 showed significant cross-reactivity. Thus a second antibody was established against a recombinant mouse mature PSP94 containing N-terminal polyhistidines, and stronger immunoreactivity against mouse prostate tissue PSP94 was identified in Western blotting experiments. Both of these antibodies showed immunohistochemical reactivity, while the latter showed stronger reactivity in IHC when tested with different fixatives. By studying tissue distribution, we demonstrated that, as with rat PSP94, mouse PSP94 is strictly prostate tissue-specific in experiments of both Western blotting and immunohistochemistry (IHC). This conclusion was also derived from a comparison among antibodies against human, rat, and mouse PSP94, showing very different immunoreactivities in Western blotting and IHC. Finally, a competitive assay between different species was performed. We demonstrated that antibodies against PSP94 from different species (human, primate, rodents) have poor cross-reactivities. These observations also indicate that the PSP94 gene is a rapidly evolving gene in all species. Results from this study have led to the possibility of utilizing PSP94 as a targeting agent specifically to the prostate in a mouse experimental model.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".