Bromide supplementation exacerbated the renal dysfunction, injury and fibrosis in a mouse model of Alport syndrome
Bibliographic record
Abstract
A seminal study recently demonstrated that bromide (Br-) has a critical function in the assembly of type IV collagen in basement membrane (BM), and suggested that Br- supplementation has therapeutic potential for BM diseases. Because salts of bromide (KBr and NaBr) have been used as antiepileptic drugs for several decades, repositioning of Br- for BM diseases is probable. However, the effects of Br- on glomerular basement membrane (GBM) disease such as Alport syndrome (AS) and its impact on the kidney are still unknown. In this study, we administered daily for 16 weeks 75 mg/kg or 250 mg/kg (within clinical dosage) NaBr or NaCl (control) via drinking water to 6-week-old AS mice (mouse model of X-linked AS). Treatment with 75 mg/kg NaBr had no effect on AS progression. Surprisingly, compared with 250 mg/kg NaCl, 250 mg/kg NaBr exacerbated the progressive proteinuria and increased the serum creatinine and blood urea nitrogen in AS mice. Histological analysis revealed that glomerular injury, renal inflammation and fibrosis were exacerbated in mice treated with 250 mg/kg NaBr compared with NaCl. The expressions of renal injury markers (Lcn2, Lysozyme), matrix metalloproteinase (Mmp-12), pro-inflammatory cytokines (Il-6, Il-8, Tnf-α, Il-1β) and pro-fibrotic genes (Tgf-β, Col1a1, α-Sma) were also exacerbated by 250 mg/kg NaBr treatment. Notably, the exacerbating effects of Br- were not observed in wild-type mice. These findings suggest that Br- supplementation needs to be carefully evaluated for real positive health benefits and for the absence of adverse side effects especially in GBM diseases such as AS.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.002 |
| 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".