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Record W4206823501 · doi:10.1016/j.isci.2021.103726

High nitrogen in maize enriches gut microbiota conferring insecticide tolerance in lepidopteran pest Spodoptera litura

2022· article· en· W4206823501 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueiScience · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect symbiosis and bacterial influences
Canadian institutionsLakehead University
FundersNatural Science Foundation of Fujian ProvinceNational Natural Science Foundation of China
KeywordsLarvaPEST analysisGut floraInsectSpodoptera lituraIntegrated pest managementBioassayInoculation

Abstract

fetched live from OpenAlex

Abuse of chemical fertilizers and insecticides has created many environmental and human health hazards. We hypothesized that high nitrogen (N) in crops changes insect gut microbiota leading to enhanced insecticide tolerance. We investigated the effect of high N in maize on gut microbiota and insecticide tolerance of the polyphagous pest Spodoptera litura . Bioassays showed that high N applied in both maize plants and artificial diets significantly enhanced larval growth but reduced larval sensitivity to the insecticide methomyl. High N promoted the gut bacterial abundance in the genus Enterococcus . Inoculation with two strains ( E. mundtii and E. casseliflavus ) isolated from the larval guts increased larval tolerance to methomyl. Incorporation of antibiotics in a high-N diet increased the larval sensitivity to methomyl. These findings suggest that excessive application of N fertilizer to crops can increase insecticide tolerance of insect pests via changing gut microbiota, leading to increased use of insecticides worldwide.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.837
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.017
GPT teacher head0.211
Teacher spread0.194 · 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