Calcium gradient dependence of Neurospora crassa hyphal growth
Bibliographic record
Abstract
A tip-high cytoplasmic calcium gradient has been identified as a requirement for hyphal growth in the fungus Neurospora crassa. The Ca2+ gradient is less steep compared to wall vesicle, wall incorporation and vesicular Ca2+ gradients, but this can be explained by Ca2+ diffusion. Analysis of the relation between the rate of hyphal growth and the spatial distribution of tip-localized calcium indicates that hyphal growth rates depend upon the tip-localized calcium concentration. It is not the steepness of the calcium gradient, but tip-localized calcium and the difference in tip-localized calcium versus subapical calcium concentration which correlate closely with hyphal growth rate. A minimal concentration difference between the apex and subapical region of 30 nM is required for growth to occur. The calcium concentration dependence of growth may relate directly to biochemical functions of calcium in hyphal extension, such as vesicle fusion and enzyme activation during cellular expansion. Initiation of tip growth may rely upon random Ca2+ motions causing localized regions of elevated calcium. Continued hyphal expansion may activate a stretch-activated phospholipase C which would increase tip-localized inositol 1,4,5-trisphosphate (IP3). Hyphal expansion, induced by mild hypoosmotic treatment, does increase diacylglycerol, the other product of phospholipase C activity. This is consistent with evidence that IP3-activated Ca2+ channels generate and maintain the tip-high calcium gradient.
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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 | 0.001 |
| 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".