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Record W7074221496

Nicotine metabolism in the cabbage looper Trichoplusia ni (Hübner) - a toxicogenomic approach

2021· article· en· W7074221496 on OpenAlexafffund

Bibliographic record

VenuecIRcle (University of British Columbia) · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicHigh-pressure geophysics and materials
Canadian institutionsUniversity of British Columbia
FundersUniversity of British Columbia
KeywordsCabbage looperTrichoplusiaDetoxification (alternative medicine)XenobioticCytochrome P450NicotineGlutathioneEnzymeInsect
DOInot available

Abstract

fetched live from OpenAlex

The cabbage looper, Trichoplusia ni (T. ni) is a generalist insect (Lepidoptera: Noctuidae) that is an agricultural pest of crucifers and other crops of economic importance. In fact, over 70% of all agricultural pest insects are Lepidopterans. Although insecticides are effective at controlling insect populations by targeting the nervous system, they can have negative off-target effects. Cytochrome P450s (CYPs), glutathione S-transferases (GSTs), UDP-glucuronosyltransferases (UGTs), and carboxylesterases (CEs) are metabolic enzymes frequently implicated in insecticide resistance. These enzymes work in concert with transport genes such as ATP-binding cassette transporters (ABCs), organic cation transporters (OCTs) and multidrug resistance proteins (MRPs). Upregulation of detoxification enzymes and inhibited binding of insecticides due to target-site mutations are the main mechanisms causing insecticide resistance. Enriched metabolic detoxification of xenobiotics along with the subsequent development of insecticide resistance have been linked to the overexpression of CYPs in insects. Previous studies have suggested that generalist insect herbivores’ (e.g. T. ni) growth and development are inhibited by exposure to the plant alkaloid nicotine, whereas specialist insect herbivores (e.g. tobacco hornworm) are not affected. However, it has been shown that the Malpighian (renal) tubules of T. ni actively excrete nicotine. Recent research has shown that T. ni do in fact detoxify nicotine into the three major metabolites; cotinine, cotinine-N- oxide, and nicotine-N-oxide. The objective of this thesis was to utilize next-generation sequencing methods to establish a greater understanding of how nicotine, a model plant alkaloid, is detoxified by a generalist insect such as T. ni. This thesis showed that dietary nicotine exposure in T. ni resulted in the increased expression of a number of metabolic detoxification and transport-related gene candidates. CYPs in particular showed increased expression in response to nicotine in both midgut and renal tissues. A number of these showed high sequence similarity to previously published CYPs in other insect pests. Taken together these data provide further insights on how nicotine is metabolized and excreted by T. ni. This research will increase opportunities for the development of new biochemical and physiological targets for the control of insect agricultural pests and disease vectors which are economically, environmentally, and medically significant.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.008
GPT teacher head0.155
Teacher spread0.147 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes2
Has abstractyes

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