MétaCan
Menu
Back to cohort

Transformation of hempseed (Cannabis sativa L.) oil cake proteome, structure and functionality after extrusion

2022· article· en· W4213059151 on OpenAlexaff
William Leonard, Pangzhen Zhang, Danyang Ying, Shuai Nie, Evan Tindal, Zhongxiang Fang

Bibliographic record

VenueFood Chemistry · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProteins in Food Systems
Canadian institutionsDepartment of Environment and Conservation
Fundersnot available
KeywordsChemistryFood scienceDifferential scanning calorimetryExtrusionProteomeChromatographyBiochemistryMaterials science

Abstract

fetched live from OpenAlex

The entire protein fractions from hempseed, its oil cake (30-40% protein) and the extruded protein isolate (>90% protein) were investigated. The first semi-quantitative mass spectrometry-based proteomics on hempseed was performed, leading to a sum of 1879 differentially abundant proteins being identified from individual pairwise comparisons of each extruded group compared to unextruded hempseed cake. The 'free-form' amino acid content and total amino acid content of hempseed oil cake were enhanced by up to 315% and 18%, respectively, after extrusion. Changes in the structure and thermal properties of hempseed protein were confirmed through circular dichroism, Fourier transform infrared spectroscopy, scanning electron microscopy and differential scanning calorimetry. The proteomic and structural transformation in the extruded hempseed protein fractions contributed to greater values in majority of tested functionality parameters, such as protein solubility, water and oil binding capacity, emulsification properties, and in vitro digestibility, as compared to their unextruded counterparts.

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 categoriesInsufficient payload (model declined to judge)
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 score0.038
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.011
GPT teacher head0.190
Teacher spread0.179 · 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.

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

Citations14
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueFood ChemistrySame topicProteins in Food SystemsFrench-language works237,207