Evidence map›Paper›PMID 24242341›Full record

ArticleJournal of chemical ecology1994

Metabolic costs of terpenoid accumulation in higher plants.

J Gershenzon

Abstract read
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In one paragraph

Article in Journal of chemical ecology, 1994. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 111 papers.

0numbers the graph read from it
0cells of the map it votes in
111citing papers in PubMed
2.6field-weighted citation impact, top 9% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

111 citing papers in PubMed, 515 citations in OpenAlex.

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  16. Resistance toPlants (Basel, Switzerland) · 2024
    Article
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51 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author at 1 institution in 2 countries.

J GershenzonInstitute of Biological Chemistry, Washington State University, 99164-6340, Pullman, Washington.
Washington State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The net value of any plant trait can be assessed by measuring the costs and benefits associated with that trait. While the other contributors to this issue examine the possible benefits of terpenoids to plants, this article explores the metabolic costs of terpenoid accumulation in plants in the light of recent advances in terpenoid biochemistry. Terpenoids are more expensive to manufacture per gram than most other primary and secondary metabolites due to their extensive chemical reduction. The enzyme costs of making terpenoids are also high since terpenoid biosynthetic enzymes are apparently not shared with other metabolic pathways. In fact, plant cells may even possess more than one set of enzymes for catalyzing the basic steps of terpenoid formation. Terpenoids are usually sequestered in complex, multicellular secretory structures, and so storage costs for these substances are also likely to be substantial. However, not all of the processes involved in terpenoid accumulation require large investments of resources. For instance, the maintenance of terpenoid pools is probably inexpensive because there is no evidence that substantial quantities of terpenes are lost as a result of metabolic turnover, volatilization, or leaching. Moreover, plants may reduce their net terpenoid costs by employing individual compounds in more than one role or by catabolizing substances that are no longer needed, although it is still unclear if such practices are widespread. These findings (and other facets of terpenoid biochemistry and physiology) are discussed in relation to the assumptions and predictions of several current theories of plant defense, including the carbonnutrient balance hypothesis, the growth-differentiation balance hypothesis, and the resource availability hypothesis.

Identifiers

PMID24242341
OpenAlexW2062138213

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.