ZmbZIP60 mRNA is spliced in maize in response to ER stress
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
BACKGROUND: Adverse environmental conditions produce ER stress and elicit the unfolded protein response (UPR) in plants. Plants are reported to have two "arms" of the ER stress signaling pathway-one arm involving membrane-bound transcription factors and the other involving a membrane-associated RNA splicing factor, IRE1. IRE1 in yeast to mammals recognizes a conserved twin loop structure in the target RNA. RESULTS: A segment of the mRNA encoding ZmbZIP60 in maize can be folded into a twin loop structure, and in response to ER stress this mRNA is spliced, excising a 20b intron. Splicing converts the predicted protein from a membrane-associated transcription factor to one that is targeted to the nucleus. Splicing of ZmbZIP60 can be elicited in maize seedlings by ER stress agents such as dithiothreitol (DTT) or tunicamycin (TM) or by heat treatment. Younger, rather than older seedlings display a more robust splicing response as do younger parts of leaf, along a developmental gradient in a leaf. The molecular signature of an ER stress response in plants includes the upregulation of Binding Protein (BIP) genes. Maize has numerous BIP-like genes, and ER stress was found to upregulate one of these, ZmBIPb. CONCLUSIONS: The splicing of ZmbZIP60 mRNA is an indicator of ER stress in maize seedlings resulting from adverse environmental conditions such as heat stress. ZmbZIP60 mRNA splicing in maize leads predictively to the formation of active bZIP transcription factor targeted to the nucleus to upregulate stress response genes. Among the genes upregulated by ER stress in maize is one of 22 BIP-like genes, ZmBIPb.
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 | 0.001 | 0.003 |
| 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