Porcine proximal tubular cells (LLC‐PK<sub>1</sub>) are able to tolerate high levels of lithium chloride<i>in vitro</i>: assessment of the influence of 1–20 mM LiCl on cell death and alterations in cell biology and biochemistry
Bibliographic record
Abstract
Lithium, a prophylactic drug for the treatment of bipolar disorder, is prescribed with caution due to its side effects, including renal damage. In this study porcine LLC-PK1 renal tubular cells were used to establish the direct toxicity of lithium on proximal cells and gain insights into the molecular mechanisms involved. In the presence of LiCl, cell proliferation exhibited insignificant decreases in a concentration-dependent manner, but once confluent, constant cell numbers were observed. Cell cycle studies indicated a small dose-dependent accumulation of cells in the G2/M stage after 24 h, as well as an increase in cells in the G0/G1 phase after treatment with 1-10 mM LiCl, but not at 20 mM LiCl. No evidence of apoptosis was observed based on cell morphology or DNA fragmentation studies, or evidence of protein expression changes for Bax, Bcl-2, and p53 proteins using immunocytochemistry. In addition caspases 3, 8 and 9 activity remained unaltered between control and lithium-treated cultures. To conclude, exposure to high concentrations of lithium did not result in overt toxic effects to LLC-PK1 renal cells, although LiCl did alter some aspects of cell behaviour, which could potentially influence function over time.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".