Characterization of The Electrical and Optical Properties of Ultrabithorax Fusion Fibers for Biosensing
Bibliographic record
Abstract
Abstract Protein materials have vital functions in living organisms and in the production of biomedical devices. Silk and collagen are established components of tissue regeneration scaffolds with electrical or bioactive functional properties, while fluorescent proteins are markers of cell activity and toxicity. Ultrabithorax (Ubx) is a protein material with excellent biocompatibility, elasticity, and functionalization pathways with fluorescent reporters, growth factors, and DNA aptamers. In this work, the optical and electrical properties of Ubx protein fusions are measured using techniques relevant for biosensing. Fluorescence spectra and lifetimes of Ubx fusions are measured. Förster resonance energy transfer (FRET) between Ubx and fluorescent fusion partners is reported for the first time. The stability of fluorescence of Ubx protein fusions with fluorescent proteins EGFP and mCherry is confirmed in a range of illumination powers. Impedance spectroscopy measurements show that increased relative humidity causes a rise in the electrical conductivity of Ubx fusion fibers by two orders of magnitude. Nyquist and broadband dielectric analyses indicate that charge transfer is dominated by ions, and the increase in conductivity is driven by increased ion mobility. This paper informs the choice of Ubx functionalization strategies for applications in biosensing using fluorescence lifetime imaging microscopy, FRET, and impedimetric spectroscopy.
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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 | 0.000 |
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 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".