From cell-SELEX to tissue-SELEX for targeted drug delivery and aptamer nanomedicine
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
Aptamers are nucleic acid-based ligands that can selectively bind to target molecules. Because of their unique target-binding properties, the use of aptamers for targeting cell surface molecules has attracted broad research interest. The field has evolved from selecting aptamers against purified surface proteins to using whole cells (cell-SELEX) as targets. To further advance the field, the concept of tissue-SELEX was later proposed to ensure that selected aptamers possess optimal binding properties in more native in vivo environments. In this article, we review recent progress made for tissue-SELEX, covering methods including tissue slide-based SELEX, morph-X-SELEX, ex vivo-SELEX, and microfluidic tissue-SELEX. The target tissues include cornea, breast, ovary, lung, cardiac and thyroid tissues. For the diseases targeted, cancer is the most extensively studied followed by cardiomyopathies and vascular conditions. The advantages of each method are discussed and potential limitations are also critically reviewed. Applications of tissue- or in vivo-SELEX-derived aptamers in drug delivery include local administration for ocular diseases and systemic administration for lung cancer. Finally, future directions are discussed, emphasizing the need for systematic comparative studies to evaluate cell-SELEX and tissue-SELEX derived aptamers, using antibodies as benchmarks to guide the development of clinically relevant therapeutic applications.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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