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Record W4324139650 · doi:10.21203/rs.3.rs-2666706/v1

Study of Alfalfa Leaf Proteome Response Under Biological Stress Conditions Caused by Alfalfa Leaf Weevil (Hypera Postica Gell.) Feeding Using Polyacrylamide Gel Electrophoresis, Isoelectric Focusing and Two-dimensional Electrophoresis

2023· preprint· en· W4324139650 on OpenAlexfundno aff
Mehdi Kakaei, Hojjatollah MAZAHERI-LAGHAB, Ali Mostafaie

Bibliographic record

VenueResearch Square · 2023
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicInsect and Pesticide Research
Canadian institutionsnot available
FundersYork University
KeywordsHypera posticaWeevilPEST analysisBiologyProteomeMedicago sativaAgronomyPolyacrylamide gel electrophoresisHorticultureBotanyBiochemistry

Abstract

fetched live from OpenAlex

Abstract Alfalfa is an important forage plant. Alfalfa leaf Weevil (Hypera postica Gell.) is considered a first-class pest of this plant, which causes a lot of damage every year, especially to the first layer of this plant. Knowledge about initial molecular signaling and proteins associated with sensing the damage of pests, especially the weevil pest in the alfalfa plant in among crop plants is limited. In this study, an attempt has been made to investigate the overall protein expression pattern of the leaf of this plant in response to the stress caused by the alfalfa leaf weevil (Hypera postica Gell.) using the proteomics technique, to take a step in investigating the resistance mechanisms of this plant to the aforementioned pest. For this purpose, a sample of stress (under pest feeding) and non-stress stage (Control) was obtained under the same growth conditions. In order to determine the significant difference in protein expression in control and stress conditions caused by alfalfa leaf weevil pest, t-test method was used. The extracted proteins were separated in two dimensions by IPG gels with a gradient pH of 4–7 and with length 18 cm and 12.5% acrylamide gels. The results of the statistical evaluation using Image Master 2D platinum of Melani 6 software showed that out of a total of 241 repeatable protein points, 28 protein points showed changes in expression in stress levels caused by alfalfa leaf weevil. These changes included increased and decreased expression. Mass spectrometry results led to the identification of proteins involved in stress response mechanisms, energy production, metabolism, synthesis and photosynthesis. The evaluation of different protein classes showed that the proteome responding to biological stress in this plant follows two distinct trends in terms of co-expression. The results showed that among the 28 protein spots with significant expression changes in the Yazdi genotype, most of them i.e. 17.85% were expressed for energy production and the same amount was expressed in response to stress in the plant. In general, the results showed that studying the amount of changes in the expression of individual proteins alone will not be the solution, but knowing the set of co-expressed proteins and studying the pattern of their collective changes in response to different levels of biological stress caused by alfalfa leaf weevil. It is very important and gives a better understanding. It is obvious that conducting more studies on other alfalfa genotypes can provide a suitable molecular model for modifying alfalfa leaf weevil resistance in other alfalfa genotypes. These results clarify our understanding of the underlying mechanisms in alfalfa plant tolerance to alfalfa leaf weevil.

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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
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 head0.115
GPT teacher head0.376
Teacher spread0.261 · 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
Published2023
Admission routes1
Has abstractyes

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