Characterization of Metaproteomics in Crop Rhizospheric Soil
Bibliographic record
Abstract
Soil rhizospheric metaproteomics is a powerful scientific tool to uncover the interactions between plants and microorganisms in the soil ecosystem. The present study established an extraction method suitable for different soils that could increase the extracted protein content. Close to 1000 separate spots with high reproducibility could be identified in the stained 2-DE gels. Among the spots, 189 spots representing 122 proteins on a 2-DE gel of rice soil samples were successfully identified by MALDI-TOF/TOF-MS. These proteins mainly originated from rice and microorganisms. They were involved in protein, energy, nucleotide, and secondary metabolisms, as well as signal transduction and resistance. Three characteristics of the crop rhizospheric metaproteomics seemed apparent: (1) approximately one-third of the protein spots could not be identified by MALDI-TOF/TOF/MS, (2) the conservative proteins from plants formed a feature distribution of crop rhizospheric metaproteome, and (3) there were very complex interactions between plants and microorganisms existing in a crop rhizospheric soil. Further functional analysis on the identified proteins unveiled various metabolic pathways and signal transductions involved in the soil biotic community. This study provides a paradigm for metaproteomic research on soil biology.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".