Cinnamaldehyde in Focus: Antimicrobial Properties, Biosynthetic Pathway, and Industrial Applications
Bibliographic record
Abstract
spp.), has garnered significant attention for its diverse therapeutic properties. Its broad-spectrum antimicrobial activity, targeting both Gram-positive and Gram-negative bacteria as well as various fungi, positions TCA as a potent natural antimicrobial agent. Beyond its antimicrobial effects, TCA demonstrates promising antidiabetic and anti-inflammatory activities, making it a valuable compound in medicinal and cosmetic applications. Recent studies have highlighted its role in disrupting microbial membranes, inhibiting biofilm formation, and modulating key metabolic pathways in pathogens. Furthermore, TCA has gained popularity in cosmetics due to its antimicrobial activity, antioxidant properties, and skin-friendly profile. This review provides a comprehensive overview of TCA's antimicrobial potential, focusing on its mechanisms of action and its market and industrial applications. We also discuss the biosynthetic pathway of TCA, exploring both its natural production in cinnamon and advances in biotechnological production methods. As the demand for sustainable and natural antimicrobial agents grows, TCA emerges as a promising candidate for diverse applications. Finally, this review explores future directions for optimizing TCA production through metabolic engineering and synthetic biology approaches to meet industrial-scale demands.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".