MétaCan
Menu
Back to cohort
Record W4308963718 · doi:10.1038/s41598-022-23828-z

Plant-produced recombinant cytokines IL-37b and IL-38 modulate inflammatory response from stimulated human PBMCs

2022· article· en· W4308963718 on OpenAlexafffund
Igor Kolotilin

Bibliographic record

VenueScientific Reports · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicTransgenic Plants and Applications
Canadian institutionsBiotechnology Research Institute
FundersAgriculture and Agri-Food Canada
KeywordsPeripheral blood mononuclear cellPhytohaemagglutininRecombinant DNALipopolysaccharideEx vivoIn vivoProinflammatory cytokineInflammationInterleukinSecretionCytokineBiologyImmunologyBiotechnologyIn vitroImmune systemBiochemistry

Abstract

fetched live from OpenAlex

Affordable therapeutics are vitally needed for humans worldwide. Plant-based production of recombinant proteins can potentially enhance, back-up, or even substitute for the manufacturing capacity of the conventional, fermenter-based technologies. We plastome-engineered a tobacco cultivar to express high levels of two "plantakines" - recombinant human cytokines, interleukins IL-37b and IL-38, and confirmed their native conformation and folding. Assessment of their biological functionality was performed ex vivo by analyzing the effects exerted by the plantakines on levels of 11 cytokines secreted from human peripheral blood mononuclear cells (PBMCs) challenged with an inflammatory agent. Application of the plant-produced IL-37b and IL-38 in PBMCs stimulated with Lipopolysaccharide or Phytohaemagglutinin resulted in significant, and in particular cases-dose-dependent modulation of pro-inflammatory cytokines secretion, showing attenuation in two-thirds of significant level modulations observed. Plantakine treatments that increased inflammatory responses were associated with the higher dosage. Our results demonstrate feasibility of manufacturing functional recombinant human proteins using scalable, cost-effective and eco-friendly plant-based bioreactors.

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 score0.474
Threshold uncertainty score0.646

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.014
GPT teacher head0.240
Teacher spread0.226 · 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

Citations8
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueScientific ReportsSame topicTransgenic Plants and ApplicationsFrench-language works237,207