Multifunctional Nanoengineered Hydrogels Consisting of Black Phosphorus Nanosheets Upregulate Bone Formation
Bibliographic record
Abstract
Tissue-engineered hydrogels have received extensive attention as their mechanical properties, chemical compositions, and biological signals can be dynamically modified for mimicking extracellular matrices (ECM). Herein, the synthesis of novel double network (DN) hydrogels with tunable mechanical properties using combinatorial screening methods is reported. Furthermore, nanoengineered (NE) hydrogels are constructed by addition of ultrathin 2D black phosphorus (BP) nanosheets to the DN hydrogels with multiple functions for mimicking the ECM microenvironment to induce tissue regeneration. Notably, it is found that the BP nanosheets exhibit intrinsic properties for induced CaP crystal particle formation and therefore improve the mineralization ability of NE hydrogels. Finally, in vitro and in vivo data demonstrate that the BP nanosheets, mineralized CaP crystal nanoparticles, and excellent mechanical properties provide a favorable ECM microenvironment to mediate greater osteogenic cell differentiation and bone regeneration. Consequently, the combination of bioactive chemical materials and excellent mechanical stimuli of NE hydrogels inspire novel engineering strategies for bone-tissue regeneration.
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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 | 0.000 |
| 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".