Controlled Copper Ion Release from Phosphate-Based Glasses Improves Human Umbilical Vein Endothelial Cell Survival in a Reduced Nutrient Environment
Bibliographic record
Abstract
The success of tissue engineering is dependent on rapid scaffold vascularization after engraftment. Copper ions are well known to be angiogenic but exhibit cytotoxicity at elevated doses. The high sensitivity to copper concentration underlines the need of a controlled release mechanism. This study investigated the effect of copper ions released from phosphate-based glasses (PGs) on human umbilical vein endothelial cells (HUVECs) under standard growth conditions (SGC), as well as in a reduced nutrient environment (RNE) with decreased bovine serum and growth factor concentrations to approximate conditions in the core of large volume scaffolds where nutrient diffusion is limited. Initially, HUVECs were exposed to a range of CuCl(2) concentrations in order to identify an optimal response in terms of their metabolism, viability, and apoptotic activity. Under SGC, HUVEC metabolic activity and viability were reduced in a dose-dependent manner in the presence of 0.44-12 ppm Cu(2+). In contrast, HUVEC death induced by the RNE was delayed by an optimal dose of 4 ppm Cu(2+), which was associated with a down-regulation of apoptosis as evidenced by caspase-3/7 activity. Copper ion release from soluble PGs of the formulation 50P(2)O(5)-30CaO-(20-x)Na(2)O-xCuO [mol%] (x=0, 1, 5 and 10) demonstrated a controllable increase with CuO content. The presence of 4 ppm copper ions released from the 10% CuO PG composition reproduced the delay in HUVEC death in the RNE, suggesting the potential of these materials to extend survival of transplanted endothelial cells in large volume scaffolds.
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) | 0.000 | 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 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".