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Record W3082866510 · doi:10.4103/1735-5362.293516

Expression of recombinant G-CSF receptor domains and their inhibitory role on G-CSF function

2020· article· en· W3082866510 on OpenAlexaff
Hamid Bakherad, Zargham Sepehrizadeh, Neda Setayesh, Seyed Latif Mousavi Gargari, Walead Ebrahimizadeh, Faranak Mavandadnejad, Elnaz Faghfuri, Soheila Ebrahimi, Mohammad Heiat, Mona Shahpari

Bibliographic record

VenueResearch in Pharmaceutical Sciences · 2020
Typearticle
Languageen
FieldMedicine
TopicNeutropenia and Cancer Infections
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsRecombinant DNAReceptorGranulocyte colony-stimulating factor receptorMolecular biologyAntibodyMonoclonal antibodyBiologyCancer researchGranulocyte colony-stimulating factorChemistryImmunologyBiochemistryGeneGenetics

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: Granulocyte colony-stimulating factor (G-CSF) is routinely used in combination with chemotherapy to battle neutropenia. However, studies suggest that this chemokine may increase the risk of metastasis and malignancy in many cancers. To counteract the adverse effects of G-CSF in cancer, antibodies have been used to block its action. However, antibodies are large and complex molecules which makes their production expensive. Thus in this study, we aim to construct different structure variants of the G-CSF receptor containing different domains and select the best variant that prevents the adverse actions of this chemokine. These novel structures are smaller than antibodies and easier to produce. EXPERIMENTAL APPROACH: and purified using standard affinity chromatography techniques. Interaction of recombinant receptor subunits with G-CSF was assessed using enzyme-linked immunosorbent assay and NFS60 cells. FINDINGS / RESULTS: Two recombinant receptor subunits containing D1 + D2 + D3 domains and D2 domain showed the strongest inhibitory activity to G-CSF. CONCLUSION AND IMPLICATIONS: These novel recombinant receptor variants could be candidates for further studies in the development of novel therapeutics.

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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.111
Threshold uncertainty score0.349

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.202
GPT teacher head0.454
Teacher spread0.252 · 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 teacher head, 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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