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Record W2029438439 · doi:10.1021/jp052445l

Nonlinear Enhancement of Oxygen Evolution in Thylakoid Membranes:  Modeling the Effect of Light Intensity and β-Cyclodextrin Concentration

2005· article· en· W2029438439 on OpenAlexaff
M. Fragata, Subhan Dudekula

Bibliographic record

VenueThe Journal of Physical Chemistry B · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPhotosynthetic Processes and Mechanisms
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsThylakoidLight intensityOxygenMembraneOxygen evolutionIntensity (physics)Nonlinear systemBiophysicsCyclodextrinChemistryChloroplastPhysicsOpticsChromatographyBiologyBiochemistryPhysical chemistryElectrochemistry

Abstract

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Electron transport through photosystem II, measured as oxygen evolution (OE), was investigated in isolated thylakoid membranes treated with beta-cyclodextrin (beta-CD, a cyclic oligosaccharide constituted of seven alpha-d-glucose residues linked by alpha-1,4 glycosidic bonds) and irradiated with white light of variable intensity. First, we found that the light-response curves of oxygen evolution are well fitted with a hyperbolic function, the shape of which is not affected by the beta-CD concentration. Second, we showed that under conditions of irradiation with white light of saturating intensity ( approximately 5000 mumol of photons/m(2).s) beta-CD enhances the oxygen evolution in the thylakoid membranes according to a sigmoid function displaying a sharp inflection point, or transition. Unexpectedely, this beta-CD effect is not observed at irradiances of less than approximately 300 mumol of photons/m(2).s. We attempted a theoretical analysis of the combined effect of irradiance and beta-CD concentration on oxygen evolution (OE(th)). For this purpose, the effect of irradiance (I) was modeled with a hyperbola (i) and the beta-CD concentration (C) contribution with a Hill equation, that is, a sigmoid function (ii). The mathematical simulations generated the following general expressions: (i) OE(th) = [OE(max)(0) G(1)(C)]I/[L(1/2)(0) G(2)(C) + I] and (ii) G(i)()(C) = 1 + p[C(n)()/(K(1/2)(n)() + C(n)())], where OE(max)(0) is the OE maximum (OE(max)) in the absence of beta-CD, L(1/2)(0) is the photon flux density giving OE(max)/2 in the absence of beta-CD, G(1)(C) or G(2)(C) is obtained from G(i)()(C) where i is 1 or 2, n is the Hill coefficient, p is a parameter to account for the beta-CD-mediated maximum OE increase, and K(1/2) is the beta-CD concentration giving half-maximal OE activity. The results of the calculations yielded the expression (iii) OE(th) = 151[1 + 3.3C(4.8)/(13.1(4.8) + C(4.8))]I/{97.5[1 + 5.2C(7.8)/(14.8(7.8) + C(7.8))] + I} which agrees well with the experimental data for a broad range of I and C. Note that, for C = 0, eq iii reverts to the light-response curve of oxygen evolution in the absence of beta-CD. We conclude that eq iii is a good approximation of the combined effect of irradiance and beta-CD concentration, meaning that the model has a significant value for predicting the outcome of associated photochemical and biochemical reactions.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.226
Teacher spread0.222 · 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 designSimulation or modeling
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

Citations6
Published2005
Admission routes1
Has abstractyes

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