Cornea‐SELEX for aptamers targeting the surface of eyes and liposomal drug delivery
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
Abstract Cornea is the major barrier to drug delivery to the eye, which results in low bioavailability and poor efficacy of topical eye treatment. In this work, we first select cornea‐binding aptamers using tissue‐SELEX on pig cornea. The top two abundant aptamers, Cornea‐S1 and Cornea‐S2, could bind to pig cornea, and their K d values to human corneal epithelial cells (HCECs) were 361 and 174 nм, respectively. Aptamer‐functionalized liposomes loaded with cyclosporine A (CsA) were developed as a treatment for dry eye diseases. The K d of Cornea‐S1‐ or Cornea‐S2‐functionalized liposomes reduces to 1.2 and 15.1 nм, respectively, due to polyvalent binding. In HCECs, Cornea‐S1 or Cornea‐S2 enhanced liposome uptake within 15 min and extended retention to 24 h. Aptamer CsA liposomes achieved similar anti‐inflammatory and tight junction modulation effects with ten times less CsA than a free drug. In a rabbit dry eye disease model, Cornea‐S1 CsA liposomes demonstrated equivalence in sustaining corneal integrity and tear break‐up time when compared to commercial CsA eye drops while utilizing a lower dosage of CsA. The aptamers obtained from cornea‐SELEX can serve as a general ligand for ocular drug delivery, suggesting a promising avenue for the treatment of various eye diseases and even other diseases.
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) | 0.000 | 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 it