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Record W3103249532 · doi:10.1021/acs.inorgchem.0c02100

Exploration of the Potential Role for Aβ in Delivery of Extracellular Copper to Ctr1

2020· article· en· W3103249532 on OpenAlexaff
Ewelina Stefaniak, M. Jake Pushie, Catherine Vaerewyck, David Corcelli, Chloe Griggs, Whitney Lewis, Emma Kelley, Noreen Maloney, Madison Sendzik, Wojciech Bal, Kathryn L. Haas

Bibliographic record

VenueInorganic Chemistry · 2020
Typearticle
Languageen
FieldNursing
TopicTrace Elements in Health
Canadian institutionsUniversity of Saskatchewan
FundersNarodowe Centrum NaukiKosciuszko FoundationResearch Corporation for Science AdvancementGordon and Betty Moore Foundation
KeywordsChemistryPeptideExtracellularCopperTransporterChaperone (clinical)HomeostasisBiophysicsBiochemistryCell biology

Abstract

fetched live from OpenAlex

Abstract Amyloid beta (Aβ) peptides are notorious for their involvement in Alzheimer’s disease (AD), by virtue of their propensity to aggregate to form oligomers, fibrils, and eventually plaques in the brain. Nevertheless, they appear to be essential for correct neurophysiology on the synaptic level and may have additional functions including antimicrobial activity, sealing the blood–brain barrier, promotion of recovery from brain injury, and even tumor suppression. Aβ peptides are also avid copper chelators, and coincidentally copper is significantly dysregulated in the AD brain. Copper (Cu) is released in significant amounts during calcium signaling at the synaptic membrane. Aβ peptides may have a role in maintaining synaptic Cu homeostasis, including as a scavenger for redox-active Cu and as a chaperone for clearing Cu from the synaptic cleft. Here, we employed the Aβ1–16 and Aβ4–16 peptides as well-established non-aggregating models of major Aβ species in healthy and AD brains, and the Ctr1–14 peptide as a model for the extracellular domain of the human cellular copper transporter protein (Ctr1). With these model peptides and a number of spectroscopic techniques, we investigated whether the Cu complexes of Aβ peptides could provide Ctr1 with either Cu­(II) or Cu­(I). We found that Aβ1–16 fully and rapidly delivered Cu­(II) to Ctr1–14 along the affinity gradient. Such delivery was only partial for the Aβ4–16/Ctr1–14 pair, in agreement with the higher complex stability for the former peptide. Moreover, the reaction was very slow and took ca. 40 h to reach equilibrium under the given experimental conditions. In either case of Cu­(II) exchange, no intermediate (ternary) species were present in detectable amounts. In contrast, both Aβ species released Cu­(I) to Ctr1–14 rapidly and in a quantitative fashion, but ternary intermediate species were detected in the analysis of XAS data. The results presented here are the first direct evidence of a Cu­(I) and Cu­(II) transfer between the human Ctr1 and Aβ model peptides. These results are discussed in terms of the fundamental difference between the peptides’ Cu­(II) complexes (pleiotropic ensemble of open structures of Aβ1–16 vs the rigid closed-ring system of amino-terminal Cu/Ni binding Aβ4–16) and the similarity of their Cu­(I) complexes (both anchored at the tandem His13/His14, bis-His motif). These results indicate that Cu­(I) may be more feasible than Cu­(II) as the cargo for copper clearance from the synaptic cleft by Aβ peptides and its delivery to Ctr1. The arguments in favor of Cu­(I) include the fact that cellular Cu export and uptake proteins (ATPase7A/B and Ctr1, respectively) specifically transport Cu­(I), the abundance of extracellular ascorbate reducing agent in the brain, and evidence of a potential associative (hand-off) mechanism of Cu­(I) transfer that may mirror the mechanisms of intracellular Cu chaperone proteins.

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 score0.004

Distilled classifier scores by category (both heads)

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0010.000
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 head0.021
GPT teacher head0.258
Teacher spread0.237 · 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

Citations12
Published2020
Admission routes1
Has abstractyes

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