Hemodialysis‐induced changes in the blood composition affect function of the endothelium
Bibliographic record
Abstract
Hemodialysis induces oxidative stress causing intravascular inflammation, which may cause endothelial dysfunction. We evaluated how hemodialysis-induced changes in blood affect the function of endothelial cells in in vitro culture. Serum samples were collected from 42 uremic patients treated with hemodialysis, one before the start of dialysis and the other one at the end of session. All patients were dialysed with polysulfone dialyzer. Concentrations of the inflammatory molecules carbonyl protein and metabolites of NO synthesis were measured in blood. Additionally, the effect of the serum obtained before and after dialysis on the function of endothelial cells in in vitro culture was studied. Hemodialysis caused increase of monocyte chemoattractant protein (MCP)-1 (+17%), hepatocyte growth factor (+91%), and pentraxin-3 (+30%) concentration in serum. Concentration of carbonyl protein was decreased by 30%. Decrease of blood level of asymmetric dimethylarginine (-25%) and nitrate/nitrites (-62%) was observed. Serum obtained after hemodialysis stimulated proliferation of endothelial cells (+10%) and synthesis of MCP-1(+11%) in these cells. Hemodialysis-induced intravascular inflammation changes the function of endothelial cells, which may lead to acceleration of atherosclerosis.
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) | 0.000 | 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".