EFFECTS OF CRYSTAL SIZE AND ORIENTATION OF SUBSTRATES ON CELL ADHESION: IMPLICATION FOR MEDICAL IMPLANTS
Bibliographic record
Abstract
The aim of this study is to investigate the effect of atomic structure of polycrystalline materials on cell-substrate interactions. Samples are prepared from rods and sheets of Ti -6 Al -4 V substrates with predominately two distinct crystallographic orientations as well as nano-structured and annealed titanium fabricated through high-pressure torsion and heat treatment processes. The degree of preosteoblast attachment and rate of growth, which are regulated through the activity and interaction of proteins present in the extracellular matrix, are notably increased on the nano-structured titanium and substrate having predominant [Formula: see text] orientation. The improved cell activity is attributed to the nano-structured feature of these substrates consisting of ultra-fine crystals (< 50 nm) and specific atomic order of [Formula: see text] substrate which provide higher degree of surface wettability. These findings demonstrate the advantages of nano-structured titanium over the conventional and coated titanium implants, as both mechanical properties and cellular response are improved. Furthermore, crystal orientation of the substrates can influence cell responses and, therefore, substrate engineering can be used to improve and control cell-substrate interactions.
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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 | 0.001 |
| 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".