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Record W2288645144 · doi:10.1093/jexbot/52.357.739

Metabolic inhibition of root water flow in red‐osier dogwood (Cornus stolonifera) seedlings

2001· article· en· W2288645144 on OpenAlexafffund
Mohammed Kamaluddin, Janusz J. Zwiazek

Bibliographic record

VenueJournal of Experimental Botany · 2001
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant responses to water stress
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRespirationShootApoplastChemistryWater flowXylemBotanyHorticultureTranspirationBiologyPhotosynthesisCell wall

Abstract

fetched live from OpenAlex

The short-term effects of sodium azide (NaN(3)) on water flow in red-osier dogwood (Cornus stolonifera Michx.) seedlings were examined in excised roots at a constant pressure of 0.3 MPa. NaN(3) significantly decreased root water flow rates (Q(v)). It also induced a significant reduction in root respiration and reduced stomatal conductance to a greater extent in intact seedlings than in excised shoots. Apoplastic flow of water increased with the NaN(3)-induced decreases in Q(v). Mercuric chloride (HgCl(2)) was also used to characterize the water flow responses and respiration of dogwood roots. Similarly to NaN(3), 0.1 and 0.3 mM HgCl(2) decreased root respiration rates and Q(v). The lower, 0.05 mM HgCl(2) treatment, reduced Q(v), but had no significant effect on root oxygen uptake. The reduction of Q(v) in HgCl(2)-treated plants was only partly reversed by 50 mM mercaptoethanol. The mercurial inhibition of Q(v) suggested the presence of Hg-sensitive water channels in dogwood roots. The results indicate that root-absorbed NaN(3) metabolically inhibited water channel activities in roots and in shoots and resulted in stomatal closure. It is suggested that the inhibition of respiration that occurs in plants stressed with environmental factors such as flooding, cold soils, and drought may be responsible for the closure of water channels in root cells and inhibition of root water flow.

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 score0.083
Threshold uncertainty score0.396

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 head0.016
GPT teacher head0.230
Teacher spread0.214 · 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

Citations57
Published2001
Admission routes2
Has abstractyes

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