Gut Microbiome in BALB/c and C57BL/6J Mice Undergoing Experimental Thyroid Autoimmunity Associate with Differences in Immunological Responses and Thyroid Function
Bibliographic record
Abstract
Abstract Experimental models of hyperthyroid Graves’ disease (GD) and Graves’ orbitopathy (GO) are efficiently developed by genetic immunisation by electroporation with human thyrotropin hormone receptor (hTSHR) A-subunit plasmid in female BALB/c (H-2d) mice. We investigated susceptibility in C57BL/6 J (H-2b) animals to allow studies on disease mechanisms in transgenic and immune response gene knock-out mice. Higher numbers of female C57BL/6 J were positive for pathogenic thyroid stimulating antibodies, but induced hyperthyroidism remained at a low frequency compared to BALB/c animals. Assessment of hTSHR specific T cells showed reduced proliferation in C57BL/6 J animals accompanied with anti-inflammatory IL-10, with less pro-inflammatory IFN-γ compared to BALB/c. Whilst the orbital tissue from immune BALB/c mice showed inflammation and adipogenesis, in contrast C57BL/6 J animals showed normal pathology. We characterised the gut microbiota using 16 S ribosomal RNA gene sequencing to explore its possible pathogenic role in the model. Despite being housed under identical conditions, we observed significantly different organisation of the microbiota (beta-diversity) in the two strains. Taxonomic differences were also noted, with C57BL/6 J showing an enrichment of Operational Taxonomic Units (OTUs) belonging to the Paludibacter and Allobaculum, followed by Limibacter, Anaerophaga and Ureaplasma genera. A higher number of genera significantly correlating with clinical features was observed in C57BL/6 J compared to BALB/c; for example, Limibacter OTUs correlated negatively with thyroid-stimulating antibodies in C57BL/6 J mice. Thus, our data suggest gut microbiota may play a pivotal immunomodulatory role that differentiates the thyroid function and orbital pathology outcome in these two inbred strains undergoing experimental GO.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".