Blood–brain barrier and gut barrier dysfunction in chronic kidney disease with a focus on circulating biomarkers and tight junction proteins
Bibliographic record
Abstract
Kidney failure and associated uraemia have implications for the cardiovascular system, brain, and blood-brain barrier (BBB). We aim to examine BBB disruption, by assessing brain-derived neurotropic factor (BDNF), neuron-specific enolase (NSE) levels, and gut-blood barrier (GBB) disruption by trimethylamine N-oxide (TMAO), in chronic kidney disease (CKD) patients. Additionally, endothelial tight-junction protein expressions and modulation via TMAO were assessed. Serum from chronic kidney disease (CKD) female and male haemodialysis (HD) patients, and controls, were used to measure BDNF and NSE by enzyme-linked immunosorbent assays, and TMAO by mass spectrometry. Immunofluorescent staining of subcutaneous fat biopsies from kidney transplant recipients, and controls, were used to measure microvascular expression of tight-junction proteins (claudin-5, occludin, JAM-1), and control microvasculature for TMAO effects. HD patients versus controls, had significantly lower and higher serum levels of BDNF and NSE, respectively. In CKD biopsies versus controls, reduced expression of claudin-5, occludin, and JAM-1 were observed. Incubation with TMAO significantly decreased expression of all tight-junction proteins in the microvasculature. Uraemia affects BBB and GBB resulting in altered levels of circulating NSE, BDNF and TMAO, respectively, and it also reduces expression of tight-junction proteins that confer BBB maintenance. TMAO serves as a potential candidate to alter BBB integrity in CKD.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".