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Record W2436701440

[Preparation of monoclonal antibody against bovine phosphoenolpyruvate carboxykinase].

2015· article· en· W2436701440 on OpenAlexaff
Meilei Sheng, Xiao Zhang, Wei Zhang, Yanfei Zhang, Ying Wāng, Yifan Dai

Bibliographic record

VenuePubMed · 2015
Typearticle
Languageen
FieldMedicine
TopicMonoclonal and Polyclonal Antibodies Research
Canadian institutionsMinistry of Education and Child Care
Fundersnot available
KeywordsMonoclonal antibodyPhosphoenolpyruvate carboxykinaseRecombinant DNAMolecular biologyImmunoprecipitationBlotTransfectionAntibodyBiologyTiterImmunohistochemistryCell cultureChemistryBiochemistryEnzymeImmunologyGene
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To prepare the monoclonal antibody against bovine phosphoenolpyruvate carboxykinase (PEPCK) and characterize its biological functions. METHODS: The recombinant plasmid containing PEPCK gene was constructed and used to transfect Escherichia coli. After expression induction in E.coli, the recombinant protein PEPCK was purified and used to immunize BALB/c mice. After the spleen B cells in the immunized mice were fused with murine myeloma cells, the positive clones were identified and selected by indirect ELISA for titer determination. PEPCK mAb produced by the positive hybridoma cells was enriched and its biological functions were examined by Western blotting, immunohistochemistry and immunoprecipitation. RESULTS: One hybridoma cell line steadily secreting PEPCK mAb was successfully generated, namely 3D36H. Western blotting, immunohistochemistry and immunoprecipitation showed that the PEPCK mAb was able to specifically bind to bovine PEPCK protein. CONCLUSION: The bovine PEPCK mAb was prepared successfully and had a good ability and specificity.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.014
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0140.010

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 head0.053
GPT teacher head0.340
Teacher spread0.287 · 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
Published2015
Admission routes1
Has abstractyes

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