Differential effects of prolonged post-fixation on immunohistochemical and histochemical staining for postmortem human brains
Bibliographic record
Abstract
Purpose: Immunohistochemical (IHC) and histochemical (HC) staining techniques are widely used on human brains that are post-fixed in formalin and stored in brain banks worldwide for varying durations, from months to decades. Understanding the effects of prolonged post-fixation, postmortem interval (PMI), and age on these staining procedures is important for accurately interpreting their outcomes, thereby improving the diagnosis and research of brain disorders afflicting millions of people worldwide. Methods: In this study, we conducted both IHC and HC staining on the prefrontal cortex of postmortem human brains post-fixed for 1, 5, 10, 15, and 20 years. For IHC staining, we used two antibodies for each marker: the neuron marker neuronal nuclear antigen (NeuN), the astrocyte marker glial fibrillary acidic protein (GFAP), and the microglia marker ionized calcium-binding adaptor molecule 1 (Iba1). For HC staining, we conducted hematoxylin and eosin Y (H&E), cresyl violet (CV), and Luxol fast blue (LFB) stains to examine neuropils, neurons, and myelin, respectively. Results: We observed that the intensity of NeuN, Iba1, CV, or LFB staining was negatively correlated with post-fixation durations. Conversely, we detected a positive correlation between the intensity of GFAP and H&E staining and post-fixation durations. Moreover, there was no correlation between the intensity of NeuN, GFAP, Iba1, H&E, CV, and LFB staining and PMI. Additionally, no correlation was found between these staining intensities and age, except for the intensity of GFAP immunostained by one antiserum, which was negatively correlated with age. Conclusion: Taken together, these findings suggest that prolonged post-fixation has both positive and negative effects, while age and PMI exert limited influence on these IHC and HC parameters. Therefore, it is essential to consider these differential changes when interpreting results derived from tissues with extended post-fixation durations. Furthermore, if feasible, we recommend conducting IHC and HC staining on human brains with the same post-fixation time spans and using the most optimal antibodies to mitigate the impact on subsequent analyses.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".