MétaCan
Menu
Back to cohort
Record W2288362700 · doi:10.1371/journal.pone.0150540

Molecular Structure of Human-Liver Glycogen

2016· article· en· W2288362700 on OpenAlexaff
Bin Deng, Mitchell A. Sullivan, Cheng Chen, Jialun Li, Prudence O. Powell, Zhenxia Hu, Robert G. Gilbert

Bibliographic record

VenuePLoS ONE · 2016
Typearticle
Languageen
FieldMedicine
TopicGlycogen Storage Diseases and Myoclonus
Canadian institutionsHospital for Sick Children
FundersUniversity of QueenslandDiabetes Australia
KeywordsGlycogenGlycosidic bondSize-exclusion chromatographyBiochemistryMolecular massHuman liverHydrolysisGlycogen branching enzymeChemistryDiabetes mellitusGlycogen synthaseBiologyIn vitroEnzymeEndocrinology

Abstract

fetched live from OpenAlex

Glycogen is a highly branched glucose polymer which is involved in maintaining blood-sugar homeostasis. Liver glycogen contains large composite α particles made up of linked β particles. Previous studies have shown that the binding which links β particles into α particles is impaired in diabetic mice. The present study reports the first molecular structural characterization of human-liver glycogen from non-diabetic patients, using transmission electron microscopy for morphology and size-exclusion chromatography for the molecular size distribution; the latter is also studied as a function of time during acid hydrolysis in vitro, which is sensitive to certain structural features, particularly glycosidic vs. proteinaceous linkages. The results are compared with those seen in mice and pigs. The molecular structural change during acid hydrolysis is similar in each case, and indicates that the linkage of β into α particles is not glycosidic. This result, and the similar morphology in each case, together imply that human liver glycogen has similar molecular structure to those of mice and pigs. This knowledge will be useful for future diabetes drug targets.

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 score0.002
Threshold uncertainty score1.000

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 head0.028
GPT teacher head0.242
Teacher spread0.215 · 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

Citations49
Published2016
Admission routes1
Has abstractyes

Explore more

Same venuePLoS ONESame topicGlycogen Storage Diseases and MyoclonusFrench-language works237,207