Tacrolimus-Induced Elevation in Plasma Triglyceride Concentrations After Administration to Renal Transplant Patients Is Partially Due to a Decrease in Lipoprotein Lipase Activity and Plasma Concentrations
Bibliographic record
Abstract
BACKGROUND: Hyperlipidemia is a frequent and persistent complication in solid organ transplant recipients, leading to the high occurrence of cardiovascular disease in this patient population. Lipid abnormalities including increased total cholesterol, triglycerides (TG), and low-density lipoprotein-cholesterol have been reported frequently in transplantation patients and a variety of immunosuppressive therapies seem to be one of the main factors that influence posttransplant lipidemic profiles. For many years, tacrolimus (TAC) has been used as an immunosuppressive drug in transplantation. The aim of our investigation was to determine the effect of TAC administration on the plasma lipid profile and some key regulatory proteins of plasma lipid metabolism including cholesterol ester transfer protein, hepatic lipase and lipoprotein lipase (LPL) within renal transplant patients. METHODS: Twenty-five renal transplant patients were recruited and received TAC therapy, of which nine of these patients were treated with statin therapy for dyslipidemia. The effects of TAC on plasma total cholesterol, TG, HDL-C, low-density lipoprotein-cholesterol, cholesterol ester transfer protein, hepatic lipase and LPL concentration and activity were determined from patients plasma samples collected before the transplant surgery (baseline), and weekly for four consecutive weeks after surgery and TAC administration. RESULTS: We observed that TAC significantly increases plasma TG concentrations and reduces LPL plasma concentration and activity in renal transplant patients, independent of any lipid lowering drug treatment patients received. CONCLUSIONS: Taken together, these findings suggest that the reduction in LPL activity, partly due to the decrease of plasma LPL concentration after TAC administration may be an explanation for hypertriglyceridemia observed in patients administered TAC.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".