The Complexity of Sesquiterpene Chemistry Dictates Its Pleiotropic Biologic Effects on Inflammation
Bibliographic record
Abstract
Sesquiterpenes (SQs) are volatile compounds made by plants, insects, and marine organisms. SQ have a large range of biological properties and are potent inhibitors and modulators of inflammation, targeting specific components of the nuclear factor-kappaB (NF-κB) signaling pathway and nitric oxide (NO) generation. Because SQs can be isolated from over 1600 genera and 2500 species grown worldwide, they are an attractive source of phytochemical therapeutics. The chemical structure and biosynthesis of SQs is complex, and the SQ scaffold represents extraordinary structural variety consisting of both acyclic and cyclic (mono, bi, tri, and tetracyclic) compounds. These structures can be decorated with a diverse range of functional groups and substituents, generating many stereospecific configurations. In this review, the effect of SQs on inflammation will be discussed in the context of their complex chemistry. Because inflammation is a multifactorial process, we focus on specific aspects of inflammation: the inhibition of NF-kB signaling, disruption of NO production and modulation of dendritic cells, mast cells, and monocytes. Although the molecular targets of SQs are varied, we discuss how these pathways may mediate the effects of SQs on inflammation.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".