Analysis of Soybean Embryonic Axis Proteins by Two-Dimensional Gel Electrophoresis and Mass Spectrometry
Bibliographic record
Abstract
A proteomic approach based on two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) for protein separation and subsequent mass spectrometry (MS) for protein identification was applied to establish a proteomic reference map for the soybean embryonic axis. Proteins were extracted from dissected embryonic axes and separated in the first dimension using a pH range from 4-7. A total of 401 protein spots were isolated, digested with trypsin, and analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). We identified 335 protein spots by searching National Center for Biotechnology Information (NCBI) non redundant databases using the Mascot search engine and found a total of 200 unique proteins. Gene Ontology (GO) analysis was employed to understand the molecular processes in which the identified embryonic axes proteins are involved. The majority of proteins play a functional role in catalytic activity (42.9%) and binding (39.3%), followed by nutrient reservoir activity (5.3%), structural molecular activity (4.0%), antioxidant activity (3.2%), transporter activity (2.4%), enzyme regulator activity (1.2%), molecular transducer activity (0.8%), and transcription regulator activity (0.8%). Our 2D-profiling of soybean axis proteins has established for the first time a baseline proteome on which to investigate and compare factors affecting soybean embryonic development and the interaction of beneficial and pathogenic soilborne organisms during seed germination.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".