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Role of aquaporins in root water transport of ectomycorrhizal jack pine (<i>Pinus banksiana</i>) seedlings exposed to NaCl and fluoride

2010· article· en· W4251396518 on OpenAlexafffund
SEONG HEE LEE, Mónica Calvo‐Polanco, Gap Chae Chung, Janusz J. Zwiazek

Bibliographic record

VenuePlant Cell & Environment · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Stress Responses and Tolerance
Canadian institutionsUniversity of Alberta
FundersKorea Science and Engineering FoundationNatural Sciences and Engineering Research Council of CanadaChonnam National University
KeywordsPinus <genus>Water transportBotanyChemistryAquaporinSeedlingSalinityHorticultureBiologyWater flowBiochemistry

Abstract

fetched live from OpenAlex

Effects of ectomycorrhizal (ECM) fungus Suillus tomentosus on water transport properties were studied in jack pine (Pinus banksiana) seedlings. The hydraulic conductivity of root cortical cells (Lpc) and of the whole root system (Lpr) in ECM plants was higher by twofold to fourfold compared with the non-ECM seedlings. HgCl2 had a greater inhibitory effect on Lpc in ECM compared with non-ECM seedlings, suggesting that the mercury-sensitive, aquaporin (AQP)-mediated water transport was largely responsible for the differences in Lpc between the two groups of plants. Lpc was rapidly and drastically reduced by the 50 mm NaCl treatment. However, in ECM plants, the initial decline in Lpc was followed by a quick recovery to the pre-treatment level, while the reduction of Lpc in non-ECM seedlings progressed over time. Treatments with fluoride reduced Lpc by about twofold in non-ECM seedlings and caused smaller reductions of Lpc in ECM plants. When either 2 mm KF or 2 mm NaF were added to the 50 mm NaCl treatment solution, the inhibitory effect of NaCl on Lpc was rapidly reversed in both groups of plants. The results suggest that AQP-mediated water transport may be linked to the enhancement of salt stress resistance reported for ECM plants.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.334
Threshold uncertainty score0.398

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 head0.004
GPT teacher head0.153
Teacher spread0.149 · 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

Citations1
Published2010
Admission routes2
Has abstractyes

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