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Record W4417015519 · doi:10.5376/lgg.2025.16.0024

Molecular Dissection of Cold Response Pathways in Adzuki Bean

2025· article· W4417015519 on OpenAlexvenueno aff
Xi Kathy Zhou

Bibliographic record

VenueLegume Genomics and Genetics · 2025
Typearticle
Language
FieldAgricultural and Biological Sciences
TopicPlant pathogens and resistance mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsVignaGeneSignal transductionGene expressionEpigeneticsDNA methylation

Abstract

fetched live from OpenAlex

Adzuki beans ( Vigna angularis ), as an important edible legume crop, have a wide cultivation base and nutritional value in East Asia. However, during early spring or high-latitude planting, it often suffers from low-temperature stress, which seriously affects seed germination, seedling growth and yield formation. To deeply analyze the response mechanism of adzuki beans to low-temperature stress, this study systematically explored the key regulatory networks of their cold response pathways at the molecular level, and sorted out the low-temperature perception and initial signal transduction mechanisms of adzuki beans, including the dynamic changes of early signal molecules such as calcium signaling (Ca 2+ ), reactive oxygen species (ROS), and nitric oxide (NO). Focusing on the classic ICE-CBF-COR pathway, the expression characteristics of transcription factors such as CBF/DREB, MYB, and bZIP and their regulatory effects on downstream cold resistance genes were analyzed. Further, the epigenetic mechanisms such as DNA methylation and histone modification, as well as the regulatory roles of miRNA and lncRNA in the cold response of adzuki beans were explored. In this study, through the analysis of actual cases, multiple candidate genes with significant differential expression under low-temperature conditions were identified and verified. Combined with qRT-PCR and heterologous overexpression experiments, their potential functions in enhancing cold resistance were revealed. This study provides theoretical support for a deeper understanding of the complex molecular mechanism of adzuki beans' low-temperature response, and also offers key genetic resources and technical foundations for breeding cold-resistant and high-yield varieties.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.221
Threshold uncertainty score0.527

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.009
GPT teacher head0.198
Teacher spread0.189 · 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 teacher head, 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

Citations0
Published2025
Admission routes1
Has abstractyes

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