Characterization of Two Spontaneously Generated Human Muller Cell Lines from Donors with Type 1 and Type 2 Diabetes
Bibliographic record
Abstract
PURPOSE: Müller cells are the principal glial cells of the retina. They span the entire thickness of the neural retina, and they are in close contact with neurons. Müller cells grow very slowly, and they undergo senescence with increasing passages. Moreover, successful primary cultures of Müller cells can be obtained only with donors no older than 35 years. These limitations of primary cultures motivated the characterization of cell lines. The purpose of this study was thus to compare normal human Müller cells (NHMCs) with two spontaneously generated human Müller cell lines from donors with type 1 and 2 diabetes (HMCLs). METHODS: Both cell lines were investigated for the expression of known markers of Müller cells as well as epithelial and endothelial cells by immunofluorescence and Western blot analyses. RT-PCR was also performed with growth factors that are typical of human Müller cells. RESULTS: In contrast to the typical fibroblast-like morphology of Müller cells, HMCLs showed an epithelial shape. Immunofluorescence analyses and Western blot showed that both NHMCs and HMCLs express the known markers of Müller cells. In addition, HMCLs express cytokeratins K8 and K18 as well as typical growth factors for NHMCs. Finally, HMCLs have reached 30 passages until now without any change in their morphology or expression of markers, whereas NHMCs cannot typically be passed beyond small number of passages. HMCLs are the only human Müller cells lines that have a normal karyotype. CONCLUSIONS: HMCLs can be used as a model to improve the understanding of Müller cells in the context of chronic 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 | 0.001 |
| 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 | 0.001 |
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".