Immunohistochemical findings in human pituitaries following traumatic brain injury
Bibliographic record
Abstract
Following traumatic brain injury (TBI) approximately 25% of patients develop partial or complete hypopituitarism (HP). In our previous histologic study we found no changes in the pituitaries of patients who died instantly after TBI (Group I). In 43% of patients who survived 1‐7 days acute pituitary infarcts were apparent (Group II). In the present work, 3 group I and 7 group II pituitaries with infarcts were selected for histological and immunohistochemistry (IH) evaluation. IH was performed for adenohypophyseal hormones by the streptavidin‐biotin‐peroxidase method. In group I pituitaries, no histological changes were found and IH showed normal distribution and intensity for GH, PRL, ACTH, TSH, FSH, LH and α‐subunit (α‐SU). In group II pituitaries acute infarct (size range: 10% to 80%) was evident. IH in the non‐necrotic areas revealed no significant change. In the area of early necrosis the dying cells were still immunopositive (IP) for GH, PRL, ACTH, TSH, FSH, LS, and α‐SU. Even in the necrotic cells with loss of cell membrane, nuclear pyknosis, rhexis and lysis IP cytoplasms were still apparent indicating that hormone release is affected by ischemia. Subsequently the intensity of IP cells gradually decreased and IP granules leaked out from the necrotic cells and were seen extracellularly. In conclusion infarction and loss of adenohypophyseal cells may contribute to HP but other factors should also be considered.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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 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".