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Record W4220850197 · doi:10.1186/s13007-022-00873-3

Design and fabrication of an improved dynamic flow cuvette for 13CO2 labeling in Arabidopsis plants

2022· article· en· W4220850197 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePlant Methods · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant biochemistry and biosynthesis
Canadian institutionsSt. Michael's HospitalUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Toronto
KeywordsCuvettePhotosynthetically active radiationBiological systemPhotosynthesisBotanyEnvironmental scienceChemistryPhysicsBiologyOptics

Abstract

fetched live from OpenAlex

Abstract Background Stable isotope labeling is a non-invasive, sensitive means of monitoring metabolic flux in plants. The most physiologically meaningful information is obtained from experiments that take advantage of the natural photosynthetic carbon assimilation pathway to introduce a traceable marker with minimal effects on the physiology of the organism. The fundamental substrate in isotopic labeling experiments is 13 CO 2 , which can reveal the earliest events in carbon assimilation and realistically portray downstream metabolism when administered under conditions suitable for making kinetic inferences. Efforts to improve the accuracy and resolution of whole plant labeling techniques have focused on improvements in environmental control, air flow characteristics, and harvesting methods. Results Here we present a dynamic flow cuvette designed for single Arabidopsis thaliana labeling experiments. We have also verified its suitability for labeling Nicotiana benthamiana and essential oils in Pelargonium graveolens . Complete plans for fabrication of this device are included. The design includes three important innovations. First, uniform, circular air flow over the rosette surface is accomplished by a fan and deflector that creates a mini-cyclone effect within the chamber interior. Second, a network of circulating canals connected to a water bath provides temperature control to within ± 0.1 ºC under variable irradiance, humidity, and air flow conditions. When photosynthetically active radiation (PAR) was varied over a range of 1000 μEinsteins m −2 s −1 with no adjustment to the external temperature control system, the abaxial leaf temperature changed by < 3 ºC/1000 PAR. Third, the device is fully compatible with liquid nitrogen quenching of metabolic activity without perturbation of the light environment. For short labeling experiments (< 10 s), the most critical variable is the half-life (t 1/2 ) of the atmosphere within the chamber, which determines the maximum resolution of the labeling system. Using an infrared gas analyzer, we monitored the atmospheric half-life during the transition from 12 CO 2 to 13 CO 2 air at different flow rates and determined that 3.5 L min −1 is the optimal flow rate to initiate labeling (t 1/2 ~ 5 s). Under these conditions, we observed linear incorporation of 13 C into triose phosphate with labeling times as short as 5 s. Conclusions Advances in our ability to conduct short term labeling experiments are critical to understanding of the rates and control of the earliest steps in plant metabolism. Precise kinetic measurements in whole plants using 13 CO 2 inform metabolic models and reveal control points that can be exploited in agricultural or biotechnological contexts. The dynamic labeling cuvette presented here is suitable for studying early events in carbon assimilation and provides high resolution kinetic data for studies of metabolism in intact plants under physiologically realistic scenarios.

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.

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)0.001
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 score0.305
Threshold uncertainty score0.462

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.023
GPT teacher head0.308
Teacher spread0.284 · 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