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Record W1973473423 · doi:10.1271/bbb.100549

Hypoxia-Inducible Genes Encoding Small EF-Hand Proteins in Rice and Tomato

2010· article· en· W1973473423 on OpenAlexaff
Chie Otsuka, Ikuko Minami, Kenji Oda

Bibliographic record

VenueBioscience Biotechnology and Biochemistry · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant responses to water stress
Canadian institutionsInstitute for Biological Sciences
Fundersnot available
KeywordsGeneCytosolBiologyHypoxia (environmental)Green fluorescent proteinHomology (biology)Cell biologyOsmotic shockGene expressionHomologous chromosomeComplementary DNABiochemistryBotanyOxygenChemistryEnzyme

Abstract

fetched live from OpenAlex

Rice has evolved metabolic and morphological adaptations to low-oxygen stress to grow in submerged paddy fields. To characterize the molecular components that mediate the response to hypoxia in rice, we identified low-oxygen stress early response genes by microarray analysis. Among the highly responsive genes, five genes, OsHREF1 to OsHREF5, shared strong homology. They encoded small proteins harboring two EF-hands, typical Ca(2+)-binding motifs. Homologous genes were found in many land plants, including SlHREF in tomato, which is also strongly induced by hypoxia. SlHREF induction was detected in both roots and shoots of tomato plants under hypoxia. With the exception of OsHREF5, OsHREF expression was unaffected by drought, salinity, cold, or osmotic stress. Fluorescent signals of green fluorescent protein-fused OsHREFs were detected in the cytosol and nucleus. Ruthenium red, an inhibitor of intracellular Ca(2+) release, repressed induction of OsHREF1-4 under hypoxia. The HREFs may be related to the Ca(2+) response to hypoxia.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.013
GPT teacher head0.199
Teacher spread0.186 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2010
Admission routes1
Has abstractyes

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