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Record W4396976200 · doi:10.1111/pce.14950

Regulatory networks of senescence‐associated gene‐transcription factors promote degradation in Moso bamboo shoots

2024· article· en· W4396976200 on OpenAlexaff
Wenyu Zhang, Man Shi, Kebin Yang, Junbo Zhang, Zhimin Gao, Yousry A. El‐Kassaby, Quan Li, Tingting Cao, Shixin Deng, Hongsheng Qing, Zhikang Wang, Xinzhang Song

Bibliographic record

VenuePlant Cell & Environment · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Molecular Biology Research
Canadian institutionsUniversity of British Columbia
FundersScientific Research Foundation of Zhejiang A and F UniversityNational Natural Science Foundation of China
KeywordsSenescenceBambooTranscription factorGeneShootBiologyBamboo shootBotanyCell biologyGeneticsEcology

Abstract

fetched live from OpenAlex

Bamboo cultivation, particularly Moso bamboo (Phyllostachys edulis), holds significant economic importance in various regions worldwide. Bamboo shoot degradation (BSD) severely affects productivity and economic viability. However, despite its agricultural consequences, the molecular mechanisms underlying BSD remain unclear. Consequently, we explored the dynamic changes of BSD through anatomy, physiology and the transcriptome. Our findings reveal ruptured protoxylem cells, reduced cell wall thickness and the accumulation of sucrose and reactive oxygen species (ROS) during BSD. Transcriptomic analysis underscored the importance of genes related to plant hormone signal transduction, sugar metabolism and ROS homoeostasis in this process. Furthermore, BSD appears to be driven by the coexpression regulatory network of senescence-associated gene transcription factors (SAG-TFs), specifically PeSAG39, PeWRKY22 and PeWRKY75, primarily located in the protoxylem of vascular bundles. Yeast one-hybrid and dual-luciferase assays demonstrated that PeWRKY22 and PeWRKY75 activate PeSAG39 expression by binding to its promoter. This study advanced our understanding of the molecular regulatory mechanisms governing BSD, offering a valuable reference for enhancing Moso bamboo forest productivity.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.670
Threshold uncertainty score0.254

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.017
GPT teacher head0.190
Teacher spread0.173 · 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

Citations11
Published2024
Admission routes1
Has abstractyes

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