Characteristics of spinal microglia in aged and obese mice: potential contributions to impaired sensory behavior
Bibliographic record
Abstract
BACKGROUND: Both aging and obesity have been recognized widely as health conditions that profoundly affect individuals, families and the society. Aged and obese people often report altered pain responses while underlying mechanisms have not been fully elucidated. We aim to understand whether spinal microglia could potentially contribute to altered sensory behavior in aged and obese population. RESULTS: In this study, we monitored pain behavior in adult (6 months) and aged (17 months) mice fed with diet containing 10 % or 60 % Kcal fat. The group of young adult (3 months) mice was included as theoretical baseline control. Compared with lean adult animals, diet-induced-obese (DIO) adult, lean and DIO-aged mice showed enhanced painful response to heat and cold stimuli, while exhibiting hyposensitivity to mechanical stimulation. The impact of aging and obesity on microglia properties was evidenced by an increased microglial cell density in the spinal cords, stereotypic morphological changes and polarization towards pro-inflammatory phenotype. Obesity strikingly exacerbated the effect of aging on spinal microglia. CONCLUSION: Aging/obesity altered microglia properties in the spinal cords, which can dysregulate neuron-microglia crosstalk and impair physiological pain signal transmission. The inflammatory functions of microglia have special relevance for understanding of abnormal pain behavior in aged/obese populations.
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) | 0.001 | 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".