MétaCan
Menu
Back to cohort

Purification and characterization of a small copper carrier found in mammalian blood plasma and in the urine of mice and dogs with copper overload

2016· article· en· W2474449218 on OpenAlexaboutno aff
Miguel Tellez, Travis Alsky, Matthew D. Dalphin, Stephen Flynn, Arturo Muñoz, Denise Ibarra, Helen Truong, Maria C. Linder, Svetlana Lutsenko, Scott Weldy

Bibliographic record

VenueThe FASEB Journal · 2016
Typearticle
Languageen
FieldNursing
TopicTrace Elements in Health
Canadian institutionsnot available
Fundersnot available
KeywordsChemistryFast protein liquid chromatographyCopperUrineSize-exclusion chromatographyUltrafiltration (renal)ChromatographyExcretionBlood proteinsPeptideBiochemistryHigh-performance liquid chromatographyEnzyme

Abstract

fetched live from OpenAlex

We recently discovered a small copper carrier (SCC), which in most mammals is mainly bound to larger proteins and can be released by EDTA. It normally accounts for at least 10% of total plasma copper, and more than half the total in Atp7b−/− mice and some Labrador retrievers with copper overload, where it circulates in the “free” form and appears in the urine. This suggests SCC is an alternative means of excreting copper when biliary excretion is inhibited. To begin to isolate and characterize SCC, blood plasma of human volunteers (permitted by the university IRB), pigs, cows, sheep and Labrador retriever dogs were analyzed for their quantities or free and protein‐bound SCC, using 10 and 3kDa ultrafiltration and size exclusion chromatography (SEC) with Superdex 200 and peptide FPLC. By MALDI‐TOF, the main component identified as potentially SCC consistently had a mass of 1329.5 Da (not including Cu), identical to that reported for urinary SCC from Atp7b−/− mice. It eluted between vitamin B12 and NADH in small pore SEC and not with Cu‐EDTA, which aggregated. Two amino acids were identified; a third was blocked by sulfate or phosphate. However, solution NMR indicated the samples were not pure. Preliminary data suggested phenyl HIC and anion exchange might be useful purification steps. Plasma from the pig had the highest levels of total SCC and more than 10% in the “free form”. So it was chosen to identify the best steps for large scale SCC purification.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.017
GPT teacher head0.248
Teacher spread0.231 · 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 source (direct Gemma or distilled Codex), 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
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueThe FASEB JournalSame topicTrace Elements in HealthFrench-language works237,207