Red fluorescent proteins (RFPs) and RFP-based biosensors for neuronal imaging applications
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
The inherent advantages of red-shifted fluorescent proteins and fluorescent protein-based biosensors for the study of signaling processes in neurons and other tissues have motivated the development of a plethora of new tools. Relative to green fluorescent proteins (GFPs) and other blue-shifted alternatives, red fluorescent proteins (RFPs) provide the inherent advantages of lower phototoxicity, lower autofluorescence, and deeper tissue penetration associated with longer wavelength excitation light. All other factors being the same, the multiple benefits of using RFPs make these tools seemingly ideal candidates for use in neurons and, ultimately, the brain. However, for many applications, the practical utility of RFPs still falls short of the preferred GFPs. We present an overview of RFPs and RFP-based biosensors, with an emphasis on their reported applications in neuroscience.
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