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Record W2773321573 · doi:10.1080/19336896.2017.1405207

Somatostatin in Alzheimer's disease: A new Role for an Old Player

2017· article· en· W2773321573 on OpenAlexafffund
Michael Solarski, Hansen Wang, Holger Wille, Gerold Schmitt‐Ulms

Bibliographic record

VenuePrion · 2017
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsUniversity of AlbertaCanada Research ChairsDiscovery CentreUniversity of Toronto
FundersAlberta Innovates - Health SolutionsAlberta Prion Research InstituteOntario Centres of Excellence
KeywordsSomatostatinDiseaseNeuroscienceAlzheimer's diseaseMedicineBiologyInternal medicineEndocrinology

Abstract

fetched live from OpenAlex

The amyloid beta (Aβ) peptide is central to the pathogenesis of Alzheimer's disease (AD). Insights into Aβ-interacting proteins are critical for understanding the molecular mechanisms underlying Aβ-mediated toxicity. We recently undertook an in-depth in vitro interrogation of the Aβ1-42 interactome using human frontal lobes as the biological source material and taking advantage of advances in mass spectrometry performance characteristics. These analyses uncovered the small cyclic neuropeptide somatostatin (SST) to be the most selectively enriched binder to oligomeric Aβ1-42. Subsequent validation experiments revealed that SST interferes with Aβ fibrillization and promotes the formation of Aβ assemblies characterized by a 50-60 kDa SDS-resistant core. The distributions of SST and Aβ overlap in the brain and SST has been linked to AD by several additional observations. This perspective summarizes this body of literature and draws attention to the fact that SST is one of several neuropeptide hormones that acquire amyloid properties before their synaptic release. The latter places the interaction between SST and Aβ among an increasing number of observations that attest to the ability of amyloidogenic proteins to influence each other. A model is presented which attempts to reconcile existing data on the involvement of SST in the AD etiology.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.207
Threshold uncertainty score0.410

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)0.0000.000

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 head0.061
GPT teacher head0.375
Teacher spread0.314 · 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 designObservational
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

Citations66
Published2017
Admission routes2
Has abstractyes

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