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Record W2074560701 · doi:10.1371/journal.pone.0059861

Photophysiological and Photosynthetic Complex Changes during Iron Starvation in Synechocystis sp. PCC 6803 and Synechococcus elongatus PCC 7942

2013· article· en· W2074560701 on OpenAlexafffund
Jared M. Fraser, Sarah E. Tulk, Jennifer Jeans, Douglas A. Campbell, Thomas S. Bibby, Amanda M. Cockshutt

Bibliographic record

VenuePLoS ONE · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPhotosynthetic Processes and Mechanisms
Canadian institutionsMount Allison University
FundersNatural Sciences and Engineering Research Council of CanadaNatural Environment Research CouncilSight Research UK
KeywordsPhotosynthesisCyanobacteriaSynechococcusBiologyChemistryBotanyGeneticsBacteria

Abstract

fetched live from OpenAlex

Iron is an essential component in many protein complexes involved in photosynthesis, but environmental iron availability is often low as oxidized forms of iron are insoluble in water. To adjust to low environmental iron levels, cyanobacteria undergo numerous changes to balance their iron budget and mitigate the physiological effects of iron depletion. We investigated changes in key protein abundances and photophysiological parameters in the model cyanobacteria Synechococcus PCC 7942 and Synechocystis PCC 6803 over a 120 hour time course of iron deprivation. The iron stress induced protein (IsiA) accumulated to high levels within 48 h of the onset of iron deprivation, reaching a molar ratio of ~42 IsiA : Photosystem I in Synechococcus PCC 7942 and ~12 IsiA : Photosystem I in Synechocystis PCC 6803. Concomitantly the iron-rich complexes Cytochrome b6f and Photosystem I declined in abundance, leading to a decrease in the Photosystem I : Photosystem II ratio. Chlorophyll fluorescence analyses showed a drop in electron transport per Photosystem II in Synechococcus, but not in Synechocystis after iron depletion. We found no evidence that the accumulated IsiA contributes to light capture by Photosystem II complexes.

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 score0.015
Threshold uncertainty score0.883

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 head0.022
GPT teacher head0.204
Teacher spread0.181 · 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

Citations80
Published2013
Admission routes2
Has abstractyes

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