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Record W2469926853 · doi:10.1093/jxb/erw259

Regulation of programmed cell death by phytoglobins

2016· review· en· W2469926853 on OpenAlexaff
Mohamed M. Mira, Robert D. Hill, Claudio Stasolla

Bibliographic record

VenueJournal of Experimental Botany · 2016
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicPlant responses to water stress
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsJasmonic acidCell biologyProgrammed cell deathBiologyAuxinReactive oxygen speciesSignal transductionCytokininAbiotic stressNitric oxideHypersensitive responseAbiotic componentBiochemistryApoptosisGeneEcology

Abstract

fetched live from OpenAlex

Programmed cell death (PCD) is a fundamental plant process in growth and development and in response to both biotic and abiotic stresses. Nitric oxide (NO) is a central component in determining whether a cell undergoes PCD, either as a direct elicitor of the response or as a factor in signal transduction from various hormones. Both NO and hormones that use NO as a signal transducer are mobile in the plant. Why do one set of cells die while adjacent cells remain alive, if this is the case? There is evidence to suggest that phytoglobins (Pgbs; previously termed non-symbiotic hemoglobins) may act as binary switches to determine plant cellular responses to perturbations. There are anywhere from one to five Pgb genes in plants that are expressed in response to growth and development and to stress. One of their main functions is to scavenge NO. This review will discuss how Pgb modulates cellular responses to auxin, cytokinin, and jasmonic acid during growth and development and in response to stress. The moderation in the production of reactive oxygen species (ROS) by Pgbs and the effects on PCD will also be discussed. An overall mechanism for Pgb involvement will be presented.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.920
Threshold uncertainty score0.326

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.034
GPT teacher head0.288
Teacher spread0.254 · 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 designNot applicable
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

Citations32
Published2016
Admission routes1
Has abstractyes

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