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Record W3103049958 · doi:10.1093/jxb/eraa482

Recent insights into the metabolic adaptations of phosphorus-deprived plants

2020· review· en· W3103049958 on OpenAlexaff
D. M. S. B. Dissanayaka, Mina Ghahremani, Meike Siebers, Jun Wasaki, William C. Plaxton

Bibliographic record

VenueJournal of Experimental Botany · 2020
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicPlant nutrient uptake and metabolism
Canadian institutionsQueen's UniversityUniversity of Ottawa
Fundersnot available
KeywordsBiologyMetabolomeBioenergeticsMetabolic pathwayBiochemistryProteomeTranscriptomeMetabolismGene expressionMetaboliteGene

Abstract

fetched live from OpenAlex

Inorganic phosphate (Pi) is an essential macronutrient required for many fundamental processes in plants, including photosynthesis and respiration, as well as nucleic acid, protein, and membrane phospholipid synthesis. The huge use of Pi-containing fertilizers in agriculture demonstrates that the soluble Pi levels of most soils are suboptimal for crop growth. This review explores recent advances concerning the understanding of adaptive metabolic processes that plants have evolved to alleviate the negative impact of nutritional Pi deficiency. Plant Pi starvation responses arise from complex signaling pathways that integrate altered gene expression with post-transcriptional and post-translational mechanisms. The resultant remodeling of the transcriptome, proteome, and metabolome enhances the efficiency of root Pi acquisition from the soil, as well as the use of assimilated Pi throughout the plant. We emphasize how the up-regulation of high-affinity Pi transporters and intra- and extracellular Pi scavenging and recycling enzymes, organic acid anion efflux, membrane remodeling, and the remarkable flexibility of plant metabolism and bioenergetics contribute to the survival of Pi-deficient plants. This research field is enabling the development of a broad range of innovative and promising strategies for engineering phosphorus-efficient crops. Such cultivars are urgently needed to reduce inputs of unsustainable and non-renewable Pi fertilizers for maximum agronomic benefit and long-term global food security and ecosystem preservation.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
gptno category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Other designhigh
models splitAgreement compares identical category sets and study designs across arms.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.054
GPT teacher head0.289
Teacher spread0.235 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designNot applicable · Other design
Domainnot available
GenreReview

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

Citations194
Published2020
Admission routes1
Has abstractyes

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