Allostatic load and comorbidities: A mitochondrial, epigenetic, and evolutionary perspective
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Stress-related pathophysiology drives comorbid trajectories that elude precise prediction. Allostatic load algorithms that quantify biological "wear and tear" represent a comprehensive approach to detect multisystemic disease processes of the mind and body. However, the multiple morbidities directly or indirectly related to stress physiology remain enigmatic. Our aim in this article is to propose that biological comorbidities represent discrete pathophysiological processes captured by measuring allostatic load. This has applications in research and clinical settings to predict physical and psychiatric comorbidities alike. The reader will be introduced to the concepts of allostasis, allostasic states, allostatic load, and allostatic overload as they relate to stress-related diseases and the proposed prediction of biological comorbidities that extend rather to understanding psychopathologies. In our transdisciplinary discussion, we will integrate perspectives related to (a) mitochondrial biology as a key player in the allostatic load time course toward diseases that "get under the skin and skull"; (b) epigenetics related to child maltreatment and biological embedding that shapes stress perception throughout lifespan development; and
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.
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) | 0.001 | 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 it