Interaction of primary human trabecular meshwork cells with metal alloy candidates for microinvasive glaucoma surgery
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Microinvasive glaucoma surgery (MIGS) is a relatively new addition to the glaucoma treatment paradigm. Small metallic stents are inserted into the trabecular meshwork in order to increase aqueous humour drainage. MIGS procedures are rapidly being adopted owing to a more favourable side effect profile when compared with traditional surgery. Remarkably, this rapid rate of utilization has occurred without any published studies on the effect of metal alloys used in these stents on human trabecular meshwork cells (HTMCs). Therefore, this study aimed to determine the effect of candidate metal alloys for MIGS on HTMC morphology, viability and function. METHODS: Human trabecular meshwork cells were cultured on the surfaces of titanium (polished and sandblasted), a titanium-nickel (nitinol) alloy and glass (as control substratum). Fluorescence imaging was used to assess cell morphology and spreading. A lactate dehydrogenase cytotoxicity assay, cell death detection ELISA, MTT cell viability assay, BrdU cell proliferation assay and fibronectin ELISA were also conducted. RESULTS: Cells cultured on sandblasted titanium exhibited significantly greater spreading than cells cultured on other substrata. In comparison, HTMCs cultured on nitinol displayed poor spreading. Significantly more cell death, by both necrosis and apoptosis, occurred on nitinol than on titanium and glass. Also, cell viability and proliferation were suppressed on nitinol compared with titanium or glass. Finally, HTMCs on both titanium and nitinol produced greater amounts of fibronectin than cells grown on glass. CONCLUSIONS: Substratum topography and metal alloy composition were found to impact morphology, viability and function of primary HTMC cultures.
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.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it