Temperature-induced Artifacts in Tau Phosphorylation: Implications for Reliable Alzheimer’s Disease Research
Bibliographic record
Abstract
In preclinical research on Alzheimer's disease and related tauopathies, tau phosphorylation analysis is routinely employed in both cellular and animal models. However, recognizing the sensitivity of tau phosphorylation to various extrinsic factors, notably temperature, is vital for experimental accuracy. Hypothermia can trigger tau hyperphosphorylation, while hyperthermia leads to its dephosphorylation. Nevertheless, the rapidity of tau phosphorylation in response to unintentional temperature variations remains unknown. In cell cultures, the most significant temperature change occurs when the cells are removed from the incubator before harvesting, and in animal models, during anesthesia prior to euthanasia. In this study, we investigate the kinetics of tau phosphorylation in N2a and SH-SY5Y neuronal cell lines, as well as in mice exposed to anesthesia. We observed changes in tau phosphorylation within the few seconds upon transferring cell cultures from their 37°C incubator to room temperature conditions. However, cells placed directly on ice post-incubation exhibited negligible phosphorylation changes. In vivo, isoflurane anesthesia rapidly resulted in tau hyperphosphorylation within the few seconds needed to lose the pedal withdrawal reflex in mice. These findings emphasize the critical importance of preventing temperature variation in researches focused on tau. To ensure accurate results, we recommend avoiding anesthesia before euthanasia and promptly placing cells on ice after removal from the incubator. By controlling temperature fluctuations, the reliability and validity of tau phosphorylation studies can be significantly enhanced.
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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 | 0.018 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".