IMP2RIS, an automated plant root PET radiotracer gas delivery system for in-soil visualization of symbiotic N2 fixation in nodulated roots of soybean plants via PET imaging
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Bibliographic record
Abstract
The real-time and non-invasive visualization and quantification of symbiotic nitrogen fixation (SNF) in nodulated roots of soybean plants using Positron Emission Tomography (PET) imaging, coupled with the application of [ 13 N]N 2 gas as a PET radiotracer, has been explored in only a few studies. In these studies, [ 13 N]N 2 was delivered to nodulated soybean roots suspended in air within gas-tight acrylic boxes, followed by two-dimensional (2D) PET imaging to visualize the assimilated [ 13 N]N 2 in the air-suspended root nodules. In this paper, we introduce the In-Media Plant PET Root Imaging System (IMP 2 RIS), a novel gas delivery system designed and constructed in-house. Unlike the previous methods, IMP 2 RIS allows for non-intrusive delivery and exposure of [ 13 N]N 2 gas to the nodulated roots of soybean plants grown in a clay-rich, soil-like and visually opaque growth medium. This advancement enabled in-soil, three-dimensional (3D) visualization of SNF in soybean root nodules using Sofie, a preclinical PET scanner. Equipped with automated controls, IMP 2 RIS ensures ease of operation and operator safety during the [ 13 N]N 2 delivery process. We describe the components and functionalities of IMP 2 RIS, supported by experimental results showcasing its successful application in efficient delivery and exposure of [ 13 N]N 2 gas to nodulated roots of three soybean plant cultivars that vary in rates of N 2 fixation. The in-soil quantitative PET imaging of SNF, aided by IMP 2 RIS, holds promise for enhancing the integration of SNF as a functional phenotypic trait into breeding programs, aiming to enhance SNF efficiency by identifying breeding materials with high SNF capacities.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it