Plant Products as Biocides for Conservation of Cultural Asset Sustainable for Human and Environmental Health
Bibliographic record
Abstract
In the last decades plants products are increasingly used also in defining innovative procedures for sustainable conservation of cultural heritage. Particularly, essential oils or hydro-alcoholic extracts have been fruitful applied to contrast microbial colonization on organic and inorganic artworks or insect infestation (Anobidae) having regard to the repellent action. In this paper, extracts from Asteraceae and Lamiaceae plant families are utilized to counteract widespread microbial colonization (bacteria, cyanobacteria, fungi) due to their antimicrobial activity. In order to define the adequate concentration correlating it to microbial species detected, the antimicrobial activity of natural products is preliminary in vitro assayed by Agar Disc and Well Plate Diffusion methods. Moreover, an integrated approach based on morphological analysis (optical, scanning and confocal electron microscopy), in vitro cultures (Nutrient or Sabouraud agar) and molecular investigation (genomic microbial DNA extraction, sequencing and sequence analysis) are routinely performed for the identification of largest number of microbial taxa. Besides, to enhance the antimicrobial activity different protocols have been performed, such as for Thymus vulgaris products directly applied on wooden sculpture surface as hydro-alcoholic extract, followed by exposure, in a dedicated chamber, to the volatile compound of the corresponding Essential Oil. In other case studies, the exposure to volatile compounds of Crithmum maritmum, Inula critmoides, Thymus vulgaris and Origanum vulgare essential oils was performed under controlled vacuum conditions, comparing the effects to environmental condition exposure. These studies confirm the possible use of plant extracts in replacing synthetic chemical biocides, in full respect of human health and environment sustainability.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".