Enhancement of healthful novel sugar contents in genetically engineered sugarcane juice integrated with molecularly characterized ThSyGII (CEMB-SIG2)
Bibliographic record
Abstract
Enhancement of sugar contents and yielding healthful sugar products from sugarcane demand high profile scientific strategies. Previous efforts to foster manipulation in metabolic pathways or triggering sugar production through combating abiotic stresses fail to yield high sugar recovery in Saccharum officinarum L. Novel sucrose isomers trehalulose (TH) and isomaltulose (IM) are naturally manufactured in microbial sources. In pursuance of novel scientific methodology, codon optimized sucrose isomerase gene, Trehalulose synthase gene II(CEMB-SIG2) cloned under dual combined stem specific constitutive promoters in pCAMBIA1301 expression vector integrated with Vacuole targeted signal peptide (VTS) to concentrate gene product into the vacuole. The resultant mRNA expression obtained by Real Time PCR validated extremely increased transgene expression in sugarcane culms than leaf tissues. Overall sugar estimation from transgenic sugarcane lines was executed through refractometer. HPLC based quantifications of Trehalulose (TH) alongside different internodes of transgenic sugarcane confirmed the enhancement of boosted sugar concentrations in mature sugarcane culms. Trehalulose synthase gene II receptive sugarcane lines indicated the unprecedented impressions of duly combined constitutive stem regulated promoters. Transgenic sugarcane lines produce highest sugar recovery percentages, 14.9% as compared to control lines (8.5%). The increased sugar recovery percentage in transgenic sugarcane validated the utmost performance and expression of ThSyGII gene .High Profile Liquid chromatography based sugar contents estimation of Trehalulose (TH) and Isomaltulose (IM) yielded unprecedented improvement in the whole sugar recovery percentage as compared to control lines..
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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 | 0.001 |
| 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".