Investigation of the Azorean Camellia sinensis Processing Conditions to Maximize the Theaflavin 3,3′-di-O-Gallate Content as a Potential Antiviral Compound
Bibliographic record
Abstract
The molecular constituents of Camellia sinensis, in particular epigallocatechin-3-O-gallate (EGCG) and, more remarkably, the galloylated theaflavins, mainly theaflavin-3,3′-di-O-gallate (TF-3,3′-DG), have been reported to inhibit SARS-CoV-2 3-chymotrypsin-like protease (3CLpro), an enzyme required for the cleavage of its polyproteins, to produce vital individual functional proteins for viral cell replication. Our results for total catechin content revealed the values of 174.72, 200.90, and 211.75 mg/g dry weight (DW) in spring, and the values of 183.59, 191.36, and 215.09 mg/g DW in summer, for tea plantation zones 1, 2, and 3, respectively. For the TF-3,3′-DG content, the values of 2.68, 1.13, and 3.72 mg/g DW were observed in spring, and the values of 3.78, 2.06, and 8.91 mg/g DW in summer for zones 1, 2, and 3, respectively. In the same zone, different contents of TF-3,3′-DG were observed across plucking months of April, June, and August, with values of 1.13, 2.77, and 4.18 mg/g DW, respectively, showing higher values in summer. Different values of TF-3,3′-DG contents were also observed in the same tea plantation zone but from different plant parts, revealing higher values in the bud and the first and second leaves (3.62 mg/g DW) and lower values in the third and fourth leaves (1.14 mg/g DW). The TF-3,3′-DG content increased from 3.31 to 4.98 mg/g DW with increased fermentation time from 1 to 3 h, respectively, and increased for lower temperature and longer fermentation time. The aim of this study was to investigate the processing conditions that lead to maximum TF-3,3′-DG content and, given its potential impact as an inhibitor of the 3CLpro enzyme, to create a novel antiviral Azorean black tea.
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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) | 0.001 | 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".