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Record W4283838258 · doi:10.1093/jxb/erac293

LEAfing through literature: late embryogenesis abundant proteins coming of age—achievements and perspectives

2022· review· en· W4283838258 on OpenAlexaff
Itzell Eurídice Hernández-Sánchez, Israel Maruri-López, Coral Martínez-Martínez, Brett R. Janis, Juan Francisco Jiménez-Bremont, Alejandra A. Covarrubias, Michael A. Menze, Steffen P. Graether, Anja Thalhammer

Bibliographic record

VenueJournal of Experimental Botany · 2022
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsUniversity of Guelph
FundersConsejo Nacional de Ciencia y Tecnología
KeywordsEmbryogenesisBiologyEmbryoCell biology

Abstract

fetched live from OpenAlex

To deal with increasingly severe periods of dehydration related to global climate change, it becomes increasingly important to understand the complex strategies many organisms have developed to cope with dehydration and desiccation. While it is undisputed that late embryogenesis abundant (LEA) proteins play a key role in the tolerance of plants and many anhydrobiotic organisms to water limitation, the molecular mechanisms are not well understood. In this review, we summarize current knowledge of the physiological roles of LEA proteins and discuss their potential molecular functions. As these are ultimately linked to conformational changes in the presence of binding partners, post-translational modifications, or water deprivation, we provide a detailed summary of current knowledge on the structure-function relationship of LEA proteins, including their disordered state in solution, coil to helix transitions, self-assembly, and their recently discovered ability to undergo liquid-liquid phase separation. We point out the promising potential of LEA proteins in biotechnological and agronomic applications, and summarize recent advances. We identify the most relevant open questions and discuss major challenges in establishing a solid understanding of how these intriguing molecules accomplish their tasks as cellular sentinels at the limits of surviving water scarcity.

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)0.001
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 score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0000.001
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.003

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 head0.051
GPT teacher head0.351
Teacher spread0.300 · 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 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

Citations79
Published2022
Admission routes1
Has abstractyes

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