Isolation, Antibacterial, Nematicidal and Anxiolytic Activities of Essential Oil from <i>Cinnamomum longepaniculatum</i> (Gamble) N. Chao ex H. W. Li Leaves
Bibliographic record
Abstract
The utilization of natural product resources is significant for economic growth and health care. Herein, Cinnamomum longepaniculatum essential oil (CLEO) was isolated by microwave-assisted hydrodistillation (MAH). The composition of CLEO was determined by gas chromatography/mass spectrometry (GC/MS), and the antibacterial, nematicidal and anxiolytic activities of CLEO were evaluated. GC/MS results revealed that 33 compounds were identified, accounting for 99.87% of the total identified compounds. The major components of CLEO were monoterpenes, including β-myrcene (22.55%), eucalyptol (11.59%), α-pinene (11.56%), terpinen-4-ol (8.63%). Further research found that CLEO can inhibit the growth of Staphylococcus aureus (MIC 7.13 mg/mL, MBC 14.25 mg/mL), Escherichia coli (MIC 14.25 mg/mL, MBC 57 mg/mL), and Pseudomonas aeruginosa (MIC 14.25 mg/mL, MBC 28.50 mg/mL), the zone of inhibition were 17.49 ± 0.51 mm, 13.35 ± 0.27 mm and 15.15 ± 0.31 mm, respectively. CLEO could increase cell membrane permeability and make β-galactosidase, protein and other substances leak from the cell. Importantly, CLEO was first used to kill pine wood nematodes (PWN, Bursaphelenchus xylophilus). It was found that CLEO was toxic to B. xylophilus (LC50=30.81 mg/mL), and PWN treated with CLEO rapidly died and extended. Furthermore, CLEO was used in anxiolytic for the first time. CLEO inhalation can effectively relieve anxiety-like behaviors in open-field test (OFT) and elevated plus-maze test (EPT), and restore neurotransmitters (5-HT, NE, GABA) in brain tissue to normal levels. This study provides a strategy for the industrial production of CLEO and discovers its potential role in food transportation and preservation, forest pest control, and relief of emotional disorders such as anxiety and stress, which are beneficial to health care and economic development and provides a basis for broader application of CLEO.
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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 | 0.001 | 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".