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Record W4226020346 · doi:10.1080/02648725.2022.2060594

Features, modulation and analysis of glycosylation patterns of therapeutic recombinant immunoglobulin A

2022· review· en· W4226020346 on OpenAlexfundno aff
В. В. Аргентова, Т. К. Алиев, Д. А. Долгих, Zuzana Pakanová, Jaroslav Katrlı́k, М. П. Кирпичников

Bibliographic record

VenueBiotechnology and Genetic Engineering Reviews · 2022
Typereview
Languageen
FieldMedicine
TopicMonoclonal and Polyclonal Antibodies Research
Canadian institutionsnot available
FundersMinistry of Health, British ColumbiaMinisterstvo Zdravotnictví Ceské Republiky
KeywordsGlycosylationGlycoproteinAntibodyGlycanRecombinant DNAMonoclonal antibodyComputational biologyBiologyChemistryImmunologyBiochemistryGene

Abstract

fetched live from OpenAlex

Increasing the production of recombinant antibodies while ensuring high and stable protein quality remains a challenge in mammalian cell culture. This review is devoted to advances in the field of obtaining stable and optimal glycosylation of therapeutic antibodies based on IgA, as well as the subsequent issues of glycosylation control of glycoproteins during their production. Current studies also demonstrate a general need for a more fundamental understanding of the use of CHO cell-based producer cell lines, through which the glycoprofile of therapeutic IgA antibodies is produced and the dependence of glycosylation on culture conditions could be controlled. Optimization of glycosylation improves the therapeutic efficacy and can expand the possibilities for the creation of highly effective glycoprotein therapeutic drugs. Current status and trends in glycan analysis of therapeutic IgA, dominantly based on mass spectrometry and lectin microarrays are herein summarised as well.

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.982
Threshold uncertainty score0.684

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
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 head0.042
GPT teacher head0.326
Teacher spread0.284 · 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 designOther design
Domainnot available
GenreReview

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

Citations7
Published2022
Admission routes1
Has abstractyes

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