Analysis of Chloroplast Proteome of Shandan Huangshen (Sphallerocarpus gracilis) During the Tuberous Root Formation
Bibliographic record
Abstract
Shandan Huangshen (Sphallerocarpus gracilis) is a drought- and alkali-tolerant perennial herb. However, due to overharvesting and habitat degradation, highlighting the urgent need for conservation and artificial cultivation. To elucidate the mechanisms underlying its high adaptability and value, this study investigated the chloroplast proteome during its tuberous root formation using a mass spectrometry-based proteomic approach integrated with LC-MS/MS and bioinformatic analyses. A total of 1,616 chloroplast proteins were identified. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed that the most significantly enriched pathways included metabolic pathways, biosynthesis of amino acids, carbon metabolism, oxidative phosphorylation, photosynthesis, biosynthesis of secondary metabolites, the citrate cycle (TCA cycle), glyoxylate and dicarboxylate metabolism, ribosome function, and proteasome activity. Furthermore, protein-protein interaction network analysis indicated that the core 25-node subnetwork primarily consists of proteins involved in small molecule metabolic processes, single-organism biosynthesis, organic acid metabolism, and oxoacid metabolism. This study provides a comprehensive dataset of the Sphallerocarpus gracilis chloroplast proteome, along with detailed functional annotations, Gene Ontology (GO) enrichment, and KEGG pathway analysis. These findings offer crucial insights into key biological processes in Sphallerocarpus gracilis, advance proteomic research on its high photosynthetic efficiency, and serve as a valuable resource for future functional studies and utilization based on its proteomic profile.
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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 | 0.000 | 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 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".