Abcam Monoclonal Egr-1 ab133695 is an effective primary antibody replacement for Santa Cruz sc-189 polyclonal Egr-1 in songbirds
Bibliographic record
Abstract
BACKGROUND: The immediate early gene ZENK (acronym zif268, Egr-1, NGFI-A, krox24) has been used extensively in songbird research (Mello et al., 1992; Jarvis and Nottebohm, 1997), as well as other research areas. ZENK has been used in assessing learning and memory, measuring neural activation, and identifying the cellular and molecular substrates involved in the first stages of memory formation (Watson and Clements, 1980). Previous songbird research has found that neurons located within the areas involved in auditory perception, namely the caudomedial nidopallium and caudomedial mesopallium, exhibit high levels of ZENK protein expression in response to conspecific songs and calls (Mello and Ribeiro, 1998; Avey et al., 2011). NEW METHOD: In large part due to its neuronal-specific labeling of ZENK protein, Santa Cruz Egr-1 sc-189 has been widely accepted as the standard primary antibody in songbird research. However, Santa Cruz Biotechnology Egr-1 no longer specifically labels and has also discontinued production of Egr-1 sc-189. Thus, the current study is focused on analyzing the effectiveness of alternative primary antibodies: Abcam polyclonal c-Fos, Abcam monoclonal ab133695 Egr-1, and Proteintech polyclonal Egr-1. RESULTS: Abcam monoclonal Egr-1 was successful in specifically labeling ZENK positive cells in the songbird auditory nuclei. Abcam polyclonal c-Fos and Proteintech polyclonal Egr-1 were found to have non-specific labeling. COMPARISON WITH EXISTING METHODS: Abcam monoclonal Egr-1 ab133695 was found to produce differential and specific labeling in the targeted auditory nuclei similar to previous studies successfully using Santa Cruz polyclonal Egr-1 (i.e. Mello and Ribeiro, 1998). CONCLUSIONS: Abcam monoclonal Egr-1 effectively labels ZENK in the songbird auditory nuclei, making it a suitable primary antibody replacement for Santa Cruz polyclonal Egr-1.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".