Gene Expression and Isoflavone Concentrations in Soybean Sprouts Treated with Chitosan
Bibliographic record
Abstract
ABSTRACT This study was undertaken to investigate whether chitosan treatments of sprouts of three soybean [ Glycine max (L.) Merr.] cultivars (OAC Champion, AC Orford, and AC Proteina) can increase not only concentration of isoflavones in sprouts but also the transcript levels of genes and their subfamilies encoding enzymes at key points of the phenylpropanoid pathway (phenylalanine ammonia‐lyase [E.C. 4.3.1.5], chalcone synthase [E.C. 2.3.1.74], chalcone isomerase [E.C. 5.5.1.6], and chalcone reductase [E.C. 2.3.1.170]), and at a key branch‐point enzyme in isoflavone biosynthesis (isoflavone synthase [E.C. 1.14.13.86]). Chitosan effects on transcript levels of 14 genes differed depending on the cultivar as demonstrated by significant interactions ( P < 0.05) between soybean cultivar and chitosan treatment for all genes. For all cultivars, response to chitosan treatments varied significantly depending on the gene. Overall, the greatest response was observed with high molecular weight chitosan. Very‐low‐ and low‐isoflavone cultivars (i.e., AC Orford and OAC Champion) sometimes responded positively to chitosan treatments, while the high‐isoflavone cultivar (i.e., AC Proteina) responded only negatively to chitosan. Chitosan treatments had limited effect on isoflavone concentrations, only reducing glycitein in OAC Champion by 38%. No correlation was found between gene expression and isoflavone concentrations. Differences in isoflavone concentrations were observed between sprouts of the three cultivars; AC Proteina had the highest isoflavone concentration and AC Orford the lowest. Results indicate that although isoflavone concentration and gene expression varied with cultivar, chitosan treatment is not a viable option for increasing isoflavone content in sprouts of cultivars evaluated.
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.
How this classification was reachedexpand
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 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".