Bibliographic record
Abstract
The eukaryotic filamentous fungus Neurospora crassa has proven to be a durable and dependable model system for the analysis of the cellular and molecular bases of circadian rhythms. Pioneering genetic analyses identified clock genes, and beginning with the cloning of frequency (frq), work over the past 2 decades has revealed the molecular basis of a core circadian clock feedback loop that has illuminated our understanding of circadian oscillators in microbes, plants, and animals. In this transcription/translation-based feedback loop, a heterodimer of the White Collar-1 (WC-1) and WC-2 proteins acts both as the circadian photoreceptor and, in the dark, as a transcription factor that promotes the expression of the frq gene. FRQ dimerizes and feeds back to block the activity of its activators (making a negative feedback loop), as well as feeding forward to promote the synthesis of its activator, WC-1. Phosphorylation of FRQ by several kinases leads to its ubiquitination and turnover, releasing the WC-1/WC-2 dimer to reactivate frq expression and restart the circadian cycle. Light resetting of the clock can be understood through the rapid light induction of frq expression and temperature resetting through the influence of elevated temperatures in driving higher levels of FRQ. Several FRQ- and WC-independent, noncircadian FRQ-less oscillators (FLOs) have been described, each of which appears to regulate aspects of Neurospora growth or development. Overall, the FRQ/white collar complex feedback loop appears to coordinate the circadian system through its activity to regulate downstream-target clock-controlled genes, either directly or via regulation of driven FLOs.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".