The role of parental osmotic stress and vanishing taxa on the exacerbation of autoimmune neuroinflammation 4442
Bibliographic record
Abstract
Abstract Description Industrialized lifestyles are associated with increased risk of chronic inflammatory disorders and reduced microbiota diversity compared to traditional populations. Laxative treatments (LT) reduce microbial diversity, yet the effects of LT on autoimmune disease remain unknown. We hypothesized that LT may exacerbate experimental autoimmune encephalomyelitis (EAE), a mouse model of multiple sclerosis. We found that the microbiota of adult offspring of laxative treated (LTO) parents was significantly altered, including loss of Muribaculaceae intestinale (Mb) and several Clostridia species. Further, the severity and incidence of EAE was reduced in LTO mice compared to offspring from parents with no LT (NTO). At peak disease, CD4+ T cells from the central nervous system (CNS) of NTO mice expressed significantly more IFNγ, IL-17A, and GM-CSF compared to LTO mice and CNS microglia (CD45midCD11b+P2RY12+) from NTO mice had higher expression of the proliferation marker Ki67 and the damage response marker Clec7a. These data indicate that recruitment and activation of CNS immune cells is impaired in LTO mice. Adding Mb isolates to adult LTO mice prior to EAE induction increased EAE disease severity compared to LTO mice. Finally, LT in NTO prior to EAE does not ameliorate disease, suggesting that immune education in the presence of Mb and Clostridia species, and the physical presence of Mb in adult mice, prime inflammatory pathways that enhance susceptibility to autoimmune disease. Funding Sources Research in the Osborne lab is supported by the Canadian Institutes of Health Research, Multiple Sclerosis Canada, the Weston and Praespero Foundations. SP is supported through an endMS Doctoral Award. Topic Categories Neuroimmunology (NEUR)
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".