A dataset of proteomic changes during human heat stress and heat acclimation
Bibliographic record
Abstract
Hotter climates have important impacts on human health and performance. Yet, the cellular and molecular responses involved in human heat stress and acclimation remain understudied. This dataset includes physiological measurements and the plasma concentration of 2,938 proteins collected from 10 healthy adults, before and during passive heat stress that was performed both prior to and after a 7-day heat acclimation protocol. Physiological measurements included body temperatures, sweat rate, cutaneous vascular conductance, blood pressure, and skin sympathetic nerve activity. The proteomic dataset was generated using the Olink Explore 3072 assay, enabling a high-multiplex antibody-based assessment of protein changes based on proximity extension assay technology. The data need to be interpreted in the context of the moderate level of body hyperthermia attained and the specific demographic of young, healthy adults. We have made this dataset publicly available to facilitate research into the cellular and molecular mechanisms involved in human heat stress and acclimation, crucial for addressing the health and performance challenges posed by rising temperatures.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".