Perspectives on low voltage transmission electron microscopy as applied to cell biology
Bibliographic record
Abstract
Low voltage transmission electron microscopy (LVTEM) with accelerating voltages as low as 5 kV was applied to cell biology. To take advantage of the increased contrast given by LVTEM, tissue preparation was modified omitting all heavy metals such as osmium, uranium, and lead from the fixation, on block staining and counterstaining. Nonstained ultra-thin tissue sections (40 nm thick) generated highly contrasted images. While the aspect of the cells remains similar to that obtained by conventional TEM, some new substructures were revealed. The pancreatic acinar cells granules present a heterogeneous matrix with partitions corresponding to segregation of their different secretory proteins. Microvilli display their core of microfilaments anchored to the dense top membrane. Mitochondria revealed the presence of distinct particles along their cristea membranes that may correspond to the ATP synthase complexes or oxysomes. The dense nuclear chromatin displays a honey-comb appearance while distinct beads aligned along thin threads were seen in the dispersed chromatin. These new features revealed by LVTEM correlate with structures described or predicted through other approaches. Masking effects due to thickness of the tissue sections and to the presence of heavy metals must have prevented their observation by conventional TEM. Furthermore, the immunogold was adapted to LVTEM revealing nuclear lamin-A at the edge of the dense chromatin ribbons. Combining cytochemistry with LVTEM brings additional advantages to this new approach in cell biology.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".