Polycationic Lipids Translocate Lipopolysaccharide into HeLa Cells
Bibliographic record
Abstract
We have investigated the ability of LIPOFECTAMINE, a polycationic lipid reagent used in DNA transfection, to translocate E. coli lipopolysaccharide (LPS) into HeLa cells. Although HeLa cells did not spontaneously take up fluorescein isothiocyanate-labelled LPS (FITC-LPS) from the culture medium, the cells that were co-incubated with greater than 1 g/mL FITC-LPS and LIPOFECTAMINE showed punctate fluorescence. Virtually all cells were loaded on incubation with 100 micrograms/mL FITC-LPS. Confocal scanning laser microscopy showed extensive FITC-LPS loading in the cytoplasm of HeLa cells, but no label was evident in the nuclear regions of these cells. Loading with LPS for up to six hours had no effect on the viability of HeLa cells, beyond the 30% reduction in live cells that is attributable to the toxic effect of LIPOFECTAMINE itself. In contrast to cells treated with etoposide for six hours, LPS-loaded cells did not display apoptotic bodies. Exposure of cells to 4 beta-phorbol 12-myristate 13-acetate led to the induction of the immediate early gene c-fos and resulted in an enhanced c-Fos signal, detected by Western blot analysis. In contrast, LPS loading did not alter the c-fos expression in HeLa cells. The loading of LPS into HeLa cells by means of polycationic lipids results in relatively low acute toxicity, as judged from cell viability, morphology and c-fos expression. Therefore, our method appears well suited to the study of acute actions of LPS in the intracellular compartment of mammalian cells.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".