Europium-doped mesoporous silica nanosphere as an immune-modulating osteogenesis/angiogenesis agent
Why this work is in the frame
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Bibliographic record
Abstract
Although much research has gone into the design of nanomaterials, inflammatory response still impedes the capacity of nanomaterial-induced tissue regeneration. In-situ incorporation of nutrient elements in silica-based biomaterials has emerged as a new option to endow the nanomaterials modulating biological reactions. In this work, europium-doped mesoporous silica nanospheres (Eu-MSNs) were successfully synthesized via a one-pot method. The nanospheres (size of 280-300 nm) possess uniformly spherical morphology and mesoporous structure, and well distributed Eu elements. The nanospheres show distinct fluorescent property at 615 nm for potential bio-labeling. Noticeably, the Eu-MSNs stimulate pro-inflammatory response of macrophages and induce a modulated immune microenvironment, which further activates the osteogenic differentiation of bone marrow stromal cells (BMSCs) as well as angiogenic activity of human umbilical vein endothelial cells (HUVECs). During the process, osteogenesis-related genes (e.g. ALP, OCN, OPN and COL-I) of BMSCs, and angiogenesis-related genes (e.g. CD31, MMP9, VEGFR1/2, and PDGFRα/β) of HUVECs were significantly upregulated by Eu-MSNs modulating immune environment of macrophages. The in vivo study further demonstrated that the Eu-MSNs could not only stimulate osteogenesis by accelerating the new bone formation at critical-sized cranial defect site, but also support the blood vessel formation as well as collagen deposition and re-epithelialization at chronic skin wound sites, showing an improved angiogenesis activity when comparing with MSNs alone. Given the easy handling characteristics and extensive application potential, the results suggest that Eu-MSNs could be used as immunity-modulated osteogenesis/angiogenesis agent for skin and bone regeneration.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 it