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Record W2117010695 · doi:10.1139/w09-110

Proteomic analysis of<i>Trichoderma atroviride</i>mycelia stressed by organophosphate pesticide dichlorvos

2010· article· en· W2117010695 on OpenAlexvenueno aff
Jun Tang, Lixing Liu, Xiuli Huang, Yingying Li, Yunpeng Chen, Jie Chen

Bibliographic record

VenueCanadian Journal of Microbiology · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicChromium effects and bioremediation
Canadian institutionsnot available
FundersNational Science and Technology Program during the Twelfth Five-year Plan Period
KeywordsDichlorvosOrganophosphatePesticideGel electrophoresisPeroxidaseBiochemistryChemistryProteomeMyceliumBiologyFood scienceBotanyEnzymeEcology

Abstract

fetched live from OpenAlex

The proteomic approach is a powerful tool to study microbial response to environmental stress. To evaluate the responses of Trichoderma spp. to the organophosphate pesticide dichlorvos, mycelia of Trichoderma atroviride T23 were exposed to dichlorvos at concentrations of 0, 100, 300, 500, and 1000 microg/mL, respectively. Changes in protein expression were investigated using two-dimensional sodium dodecyl sulfate - polyacrylamide gel electrophoresis. Sixteen protein spots were differentially expressed. They were identified by MALDI-TOF/TOF MS and were found to be linked to energy metabolism, transport, signal transduction, and stress tolerance. Among stress-related proteins, glutathione peroxidase-like protein (GPX), 1,4-benzoquinone reductase, and HEX1 were upregulated by and cyclophilin A induced by 1000 microg/mL dichlorvos when compared with the control. These proteins were considered to be associated with fungal adaptation to adverse conditions. The results will help us to understand molecular mechanisms through which Trichoderma responds to organophosphate pesticides.

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 score0.003

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)0.0000.000

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 head0.003
GPT teacher head0.182
Teacher spread0.180 · 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

Citations33
Published2010
Admission routes1
Has abstractyes

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