Development of a genetically encoded melanocortin sensor for high sensitivity intravital imaging
Bibliographic record
Abstract
Abstract The central melanocortin system, composed of peptides derived from pro-opiomelanocortin (POMC) such as the melanocyte-stimulating hormones (α-, β-, γ-MSH) and melanocortin 4 receptors (MC4R), along with the agouti-related protein (AgRP), plays a pivotal role in controlling energy balance. To elucidate the dynamic role of α-MSH release in regulating appetite, specific, sensitive, and spatiotemporally resolved genetic sensors are required. The melanocortin 1 receptor (MC1R) scaffold was leveraged for its robust plasma membrane expression, high affinity for melanocortin peptides and low affinity for AgRP to design a α-MSH selective sensor for in vivo use. This was achieved by integrating circularly permuted green fluorescent protein (cpGFP) into the receptor, which we named Fl uorescence A mplified Re ceptor sensor for Melanocortin (FLARE MC ). The FLARE MC sensor shows high potency and selectivity in heterologous and homologous expressing cells for α-MSH and the synthetic melanocortin agonist MTII but not to the inverse agonist AgRP. The sensor exhibited impaired signaling, with reduced G protein activation, no β-arrestin coupling, and failed to internalize upon agonist stimulation. In vitro , FLARE MC displayed high photostability and reversible photoactivation. These properties suggest that the FLARE MC is suitable for long-term activity recording in the brain without desensitizing or interfering with endogenous melanocortin receptor signaling. When expressed in the paraventricular nucleus (PVN) of the mouse hypothalamus, the primary site of anorexigenic α-MSH signaling, FLARE MC demonstrated its effectiveness in detecting changes associated with melanocortin responses in vivo . FLARE MC enables the study of melanocortin system in cultured cells and intravitally. This first of its class highly sensitive melanocortin sensor will serve as a valuable tool to advance our understanding of the complex dynamics governing melanocortin-dependent appetite regulation and related processes in the brain.
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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 | 0.001 | 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".