Thermoregulatory dynamics reveal sex-specific inflammatory responses to experimental autoimmune encephalomyelitis in mice: Implications for multiple sclerosis-induced fatigue in females
Bibliographic record
Abstract
The course of multiple sclerosis (MS) is characterized by striking sex differences in symptoms such as fatigue and impaired thermal regulation, which are associated with aggravated systemic pro-inflammatory processes. The purpose of this study was to replicate these symptoms in experimental autoimmune encephalomyelitis (EAE) in C57BL/6 mice in the quest to advance the preclinical study of non-motor symptoms of MS. Male and female C57BL/6 mice exposed to a mild form of EAE were evaluated for the progression of clinical, behavioural, thermal, and inflammatory processes. We show higher susceptibility in females to EAE than males based on greater clinical score and cumulative disease index (CDI), fatigue-like and anxiety-like behaviours. Accordingly, infrared (IR) thermography indicated higher cutaneous temperatures in females from post-induction days 12-23. Females also responded to EAE with greater splenic and adrenal gland weights than males as well as sex-specific changes in pro- and anti-inflammatory cytokines. These findings provide the first evidence of a sex-specific thermal response to immune-mediated demyelination, thus proposing a non-invasive assessment approach of the psychophysiological dynamics in EAE mice. The results are discussed in relation to the thermoregulatory correlates of fatigue and how endogenously elevated body temperature without direct heat exposure may be linked to psychomotor inhibition in patients with MS.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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 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".