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Record W3117113326 · doi:10.1111/imb.12690

Molecular characterization of N‐methyl‐d‐aspartate receptor from <i>Bemisia tabaci</i>

2020· article· en· W3117113326 on OpenAlexaff
Sameer Dixit, Nidhi Thakur, Akanchha Shukla, Santosh Kumar Upadhyay, Praveen C. Verma

Bibliographic record

VenueInsect Molecular Biology · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect-Plant Interactions and Control
Canadian institutionsWestern University
FundersScience and Engineering Research Board
KeywordsBiologyIonotropic effectNMDA receptorGlutamatergicProtein subunitPEST analysisHemipteraReceptorCell biologyBotanyBiochemistryGeneGlutamate receptor

Abstract

fetched live from OpenAlex

The N-methyl-d-aspartate receptors (NMDARs) are ionotropic ligand gated channels that are highly permeable to calcium ions. In insects, NMDARs are associated with glutamatergic neurotransmission governing diverse physiological and biological processes like vitellogenesis and ovarian development. Therefore, NMDAR may act as attractive target for insect pest control. In present study, we performed structural and functional characterization of NMDARs in Bemisia tabaci, a highly invasive crop pest and potent virus vector. We identified that NMDAR consists of three subunits each encoded by single gene in whiteflies which are highly conserved among different insect orders. Expression analysis suggests that subunit 1 (BtNR1) and subunit 2 (BtNR2) are the main functional units. External supplementation of NMDAR ligand or BtNRs silencing was lethal to insects, which suggested that NMDAR function is highly balanced in whiteflies.

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 score0.001
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)0.0010.001

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 head0.012
GPT teacher head0.211
Teacher spread0.199 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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