Nerve Bundle Density and Expression of NGF and IL-1β Are Intra-Individually Heterogenous in Subtypes of Endometriosis
Bibliographic record
Abstract
Endometriosis is a gynecological disorder associated with local inflammation and neuroproliferation. Increased nerve bundle density has been attributed to increased expression of nerve growth factor (NGF) and interleukin-1β (IL-1β). Immunohistochemical analysis was carried out on 12 patients presenting with all three anatomic subtypes of endometriosis (deep, superficial peritoneal, endometrioma) at surgery, with at least two surgically excised subtypes available for analysis. Immunolocalization for nerve bundle density around endometriosis using protein gene product 9.5 (PGP9.5), as well as NGF and IL-1β histoscores in endometriosis epithelium/stroma, was performed to evaluate differences in scores between lesions and anatomic subtypes per patient. Intra-individual heterogeneity in scores across lesions was assessed using the coefficient of variation (CV). The degree of score variability between subtypes was evaluated using the percentage difference between mean scores from one subtype to another subtype for each marker. PGP9.5 nerve bundle density was heterogenous across multiple subtypes of endometriosis, ranging from 50.0% to 173.2%, where most patients (8/12) showed CV ≥ 100%. The percentage difference in scores showed that PGP9.5 nerve bundle density and NGF and IL-1β expression were heterogenous between anatomic subtypes within the same patient. Based on these observations of intra-individual heterogeneity, we conclude that markers of neuroproliferation in endometriosis should be stratified by anatomic subtype in future studies of clinical correlation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".