High surface density immobilization of oligonucleotide on silicon
Bibliographic record
Abstract
Oligonucleotide (11-mer) molecules are immobilized on silicon in high surface population using either a permanent thioether bond or a chemo-selectively reversible disulfide bond to the surface thiol functionality. Substrate hydroxy groups are first silanized with an 11 carbon trichlorosilane containing a terminal, protected thiol moiety. Oligonucleotide modified with a tether possessing a terminal thiol group is further derivatized with a water-soluble, halobenzylic bifunctional reagent, which allows the complete conjugate to be attached to the surface through a permanent thioether bond. Alternatively, the oligonucleotide-tether complex can be combined with a pyridyldisulfide compound, which, in turn, facilitates the formation of a reversible disulfide bond with surface thiol. The amount of immobilized oligonucleotide was determined by radiochemical labeling with 32P. Additional verification of surface amounts was obtained from X-ray photoelectron spectroscopic analysis of substrates. The results of the immobilization protocols are compared with the oligonucleotide surface population achieved through the conventional silanizing agent, mercaptopropyltrimethoxysilane. Finally, a preliminary confirmation of duplex formation of a TTU-attached 25-mer with its complementary strand is outlined.
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.
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 | 0.001 |
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".