Review of: Theodore Koditschek, Liberalism, imperialism, and the historical imagination: nineteenth-century visions of a greater Britain
Bibliographic record
Abstract
In recent years, there has been a significant increase in the search for new therapeutic strategies for the treatment of inflammatory diseases. In this sense, natural products emerge as a potential source for the discovery of new drugs, with the research of the pharmacological properties of these products being very important. In addition to its function in plants (insect attraction and repellency), essential oils present pharmacological effects, such as antibacterial, antifungal, antimutagenic, antiviral, antiprotozoal, antioxidant, antidiabetic and anti-inflammatory properties. In this review, we describe the mostly used in vivo acute inflammatory experimental models and the studies showing the in vivo anti-inflammatory activity of essential oils. Essential oil from species from the Apiaceae, Asteraceae, Burseraceae, Boraginaceae, Cupressaceae, Euphorbiaceae, Fabaceae, Lamiaceae, Lauraceae, Myrtaceae, Piperaceae, Poaceae, Rutaceae, Verbenaceae and Zingiberaceae families were described as being anti-inflammatory in vivo. Five models of acute inflammation are commonly used to investigate the anti-inflammatory activity in vivo: ear and paw edema, pleurisy, peritonitis and the subcutaneous air pouch model. In addition to in vivo analysis, ex vivo and in vitro experiments are carried out to study the anti-inflammatory action of essential oils. The most commonly used model was paw edema, especially due to this model being easy to perform. In order to suggest or elucidate the mechanisms involved in the anti-inflammatory effect, many studies measured some inflammatory mediators, such as cytokines, COX-2 expression and the levels of PGE2, and NO, or evaluated the effect of essential oils or their major compounds on inflammation response directly induced by inflammatory mediators.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 teacher head, 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".