Differential Microvasculature Dysfunction in Living Kidney Donor Transplant Recipients: Nondialyzed versus Dialyzed Chronic Kidney Disease Patients
Bibliographic record
Abstract
We hypothesized that there was differential vasomotor dysfunction in the microcirculation between nondialyzed and dialyzed chronic kidney disease (CKD) patients. During live donor kidney transplantation procedures, skin arterioles (SkA; internal diameter = 120 +/- 5 microm) from donors (n = 27) and recipients (nondialysis = 15; dialysis = 20) were dissected from the abdominal wall at the incision site. In vivo aortic pulse wave velocity (PWV) was also measured. In the in vitro isometric force measurement, nondialyzed SkA exhibited comparable contraction to donor SkA, whereas dialyzed SkA had 60 and 40-50% increase in contraction in response to depolarization and agonist (that is, phenylephrine, serotonin and endothelin-1) stimulation, respectively. The acetylcholine-induced relaxation in the nondialyzed SkA was decreased by 50% compared with dialyzed SkA. However, pre-incubation with superoxide dismutase greatly enhanced the relaxation response in the nondialyzed, but not in the dialyzed SkA and donor SkA. Pre-incubation with N(G)-nitro-L-arginine methyl ester (L-NAME) elevated the resting tension and left-shifted the concentration response curve of phenylephrine-stimulated contraction in the donor-SkA. L-NAME only increased the resting tension in the nondialyzed vessel. In vitro stiffness positively correlated with PWV (R(2) = 0.302, p = 0.001), and dialyzed SkA was 60% stiffer than nondialyzed and donor SkA. The acetylcholine relaxation was negatively correlated with PWV in donors and recipients (R(2) = 0.282, p = 0.01). In conclusion, we have uniquely demonstrated differential microvasculature dysfunction between nondialyzed and dialyzed CKD patients.
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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 | 0.001 |
| 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 | 0.000 |
| 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".