Peptide and protein‐based nanotubes for nanobiotechnology
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 The development of biologically relevant nanosystems such as biomolecular probes and sensors requires systems that effectively interface specific biochemical environments with abiotic architectures. The most widely studied nanomaterial, carbon nanotubes, has proven challenging in their adaptation for biomedical applications despite their numerous advantageous physical and electrochemical properties. On the other hand, development of bionanosystems through adaptation of existing biological systems has several advantages including their adaptability through modern recombinant DNA strategies. Indeed, the use of peptides, proteins and protein assemblies as nanotubes, scaffolds, and nanowires has shown much promise as a bottom‐up approach to the development of novel bionanosystems. We highlight several unique peptide and protein systems that generate protein nanotubes (PNTs) that are being explored for the development of biosensors, probes, bionanowires, and drug delivery systems. WIREs Nanomed Nanobiotechnol 2012, 4:575–585. doi: 10.1002/wnan.1180 This article is categorized under: Nanotechnology Approaches to Biology > Nanoscale Systems in Biology Biology-Inspired Nanomaterials > Peptide-Based Structures
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| 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