Intranuclear Rodlets in Human Pancreatic Islet Cells
Bibliographic record
Abstract
OBJECTIVES: Intranuclear rodlets (INRs) are rod-shaped intranuclear inclusions that we have described in neurons of the human brain. We recently identified these structures in pancreatic islet cells. The objectives of this study are to describe the light microscopic features and cellular pattern of distribution of INRs in human pancreatic islet cells. METHODS: Double immunofluorescence staining was performed on 5 human pancreatic tissue samples for the detection of class III beta tubulin (C3T) to detect INRs and for promyelocytic leukemia (PML) protein to examine the relationship between PML and INRs. RESULTS: Intranuclear rodlets were detected in 22.99% of pancreatic B cells compared with only 3.11%, 1.80%, and 1.60% of A, D, and PP cells, respectively. Twenty-four percent of C3T-immunoreactive INRs showed partial or complete immunoreactivity for PML. Promyelocytic leukemia staining within the nuclei of B cells was confined to INRs and was not present in the typical PML bodies present in other cell types. Spatially, PML and C3T staining of islet cell INRs appeared to be mutually exclusive within individual INRs. CONCLUSIONS: Intranuclear rodlets are present within the nuclei of pancreatic islet cells, where they reside predominantly but not exclusively in B cells. Immunoreactivity of B-cell INRs for PML suggests that the functional significance of INRs may be related to that of PML and/or PML bodies. Conversely, the exclusive localization of PML staining to INRs in B cells indicates that PML's function in B cells is selectively associated with INRs. The mutually exclusive pattern of PML and C3T staining suggests dynamic interactions between these 2 proteins in B-cell INRs. In light of evidence for the involvement of INRs and of PML bodies in disease, it will be of interest to investigate these structures in animal models of diabetes and in human diabetes.
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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 | 0.001 |
| 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) | 0.002 | 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".