A comparative study of cytoplasmic granules imaged by the real‐time microscope, Nile Red and Filipin in fibroblasts from patients with lipid storage diseases
Bibliographic record
Abstract
Cytoplasmic granules in fibroblasts, visualized without stains, or labelled with Nile red, Filipin, or anti-LAMP-1 (lysosome-associated membrane protein 1), were imaged using the real-time microscope (RTM). New advances in light microscope technology were applied to detect cytoplasmic granules (RTM-visible granules) and characterize them by imaging contrast, size, shape, cellular distribution, composition, motion dynamics and quantity. Appearing as solid spheroids or ring structures, the majority of the RTM-visible granules contained Nile-red labelled neutral lipids. A smaller subpopulation, appearing dimmer, with less imaging contrast, contained Filipin-labelled free cholesterol. Most lipid storage granules have a diameter ranging from 0.3 mum to 0.6 mum, with a small population measuring up to 1 mum. They typically clustered in the perinuclear region and displayed relatively small oscillatory motion. Immunofluorescence based on LAMP-1 labelling highlighted granular structures that were distinct and separate from RTM-visible granules and other structures in the light modality of the microscope. RTM-visible granules were associated with disease phenotypes that have increased cellular neutral lipid stores corresponding to the Nile red-labelled droplets (e.g. triacylglycerides, cholesterol esters). As predicted, the fibroblast strains with a defect resulting in Wolman disease, when compared to control samples, consistently had RTM-visible granules, higher in imaging contrast and with larger diameters, that were labelled with Nile red, and also an increased frequency of Filipin-cholesterol complexes. By comparison, in fibroblasts where the lipid storage is less evident (Gaucher and Farber diseases) or from GM(1) gangliosidosis, where the primary storage substances are oligosaccharides, fewer and smaller RTM-visible granules were observed. In some cases, changes in contrast and morphology in the unstained cytoplasmic compartments were more evident than in the labelled structures. In summary, applying the RTM imaging system to fibroblasts enables differences between the various disease types to be seen and, in specific examples, a unique phenotype can be readily discerned.
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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) | 0.001 | 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".