Degenerative Cervical Myelopathy induces sex-specific dysbiosis in mice
Bibliographic record
Abstract
Degenerative Cervical Myelopathy (DCM) is the most common cause of spinal cord impairment in elderly populations. It describes a spectrum of disorders that cause progressive spinal cord compression, neurological impairment, loss of bladder and bowel functions, and gastrointestinal dysfunction. The gut microbiota has been recognized as an environmental factor that can modulate both the function of the central nervous system and the immune response through the microbiota-gut-brain axis. Changes in gut microbiota composition or microbiota-producing factors have been linked to the progression and development of several pathologies. However, little is known about the potential role of the gut microbiota in the pathobiology of DCM. Here, DCM was induced in C57BL/6 mice by implanting an aromatic polyether material underneath the C5-6 laminae. The extent of DCM-induced changes in microbiota composition was assessed by 16S rRNA sequencing of the fecal samples. The immune cell composition was assessed using flow cytometry. To date, several bacterial members have been identified using BLAST against the largest collection of metagenome-derived genomes from the mouse gut. In both, female and males DCM caused gut dysbiosis compared to the sham group. However, dysbiosis was more pronounced in males than in females, and several bacterial members of the families Lachnospiraceae and Muribaculaceae were significantly altered in the DCM group. These changes were also associated with altered microbe-derived metabolic changes in propionate-, butyrate-, and lactate-producing bacterial members. Our results demonstrate that DCM causes dynamic changes over time in the gut microbiota, reducing the abundance of butyrate-producing bacteria, and lactate-producing bacteria to a lesser extent. Genome-scale metabolic modeling using gapseq successfully identified pyruvate-to-butanoate and pyruvate-to-propionate reactions involving genes such as Buk and ACH1, respectively. These results provide a better understanding of the sex-specific molecular effects of changes in the gut microbiota on DCM pathobiology.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".