14-3-3ζ mediates an alternative, non-thermogenic mechanism to reduce heat loss and improve cold tolerance
Bibliographic record
Abstract
Summary Following prolonged cold exposure, adaptive thermogenic pathways are activated to maintain homeothermy, and elevations in body temperature are generally associated with UCP1-dependent and -independent increases in energy expenditure. One of the earliest, identified functions of the molecular scaffold, 14-3-3ζ, was its role in the synthesis of norepinephrine, a key endogenous factor that stimulates thermogenesis. This suggests that 14-3-3ζ may have critical roles in cold-induced thermogenesis. Herein, we report that transgenic over-expression of TAP-14-3-3ζ in mice significantly improved tolerance to prolonged cold. When compared to wildtype controls, TAP mice displayed significantly elevated body temperatures and paradoxical decreases in energy expenditure. No changes in β-adrenergic sensitivity or oxidative metabolism were observed; instead, 14-3-3ζ over-expression significantly decreased thermal conductance via increased peripheral vasoconstriction. These findings suggest 14-3-3ζ mediates alternative, non-thermogenic mechanisms to mitigate heat loss for homeothermy. Our results point to an unexpected role of 14-3-3ζ in the regulation of body temperature. Graphical abstract
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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".