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Record W3120275261 · doi:10.1097/mol.0000000000000736

Apolipoprotein genetic variants and hereditary amyloidosis

2020· review· en· W3120275261 on OpenAlexafffund
Natasha Jeraj, Robert A. Hegele, Amanda J. Berberich

Bibliographic record

VenueCurrent Opinion in Lipidology · 2020
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAmyloidosis: Diagnosis, Treatment, Outcomes
Canadian institutionsWestern University
FundersCanadian Institutes of Health Research
KeywordsAmyloidosisApolipoprotein BAmyloid (mycology)MutationApolipoprotein EMedicineAmyloid fibrilGeneticsPathogenesisBiologyDiseaseBioinformaticsPathologyGeneEndocrinologyAmyloid βCholesterol

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Amyloidosis is caused by the deposition of misfolded aggregated proteins called amyloid fibrils that in turn cause organ damage and dysfunction. In this review, we aim to summarize the genetic, clinical, and histological findings in apolipoprotein-associated hereditary amyloidosis and the growing list of mutations and apolipoproteins associated with this disorder. We also endeavor to summarize the features of apolipoproteins that have led them to be overrepresented among amyloidogenic proteins. Additionally, we aim to distinguish mutations leading to amyloidosis from those that lead to inherited dyslipidemias. RECENT FINDINGS: Apolipoproteins are becoming increasingly recognized in hereditary forms of amyloidosis. Although mutations in APOA1 and APOA2 have been well established in hereditary amyloidosis, new mutations are still being detected, providing further insight into the pathogenesis of apolipoprotein-related amyloidosis. Furthermore, amyloidogenic mutations in APOC2 and APOC3 have more recently been described. Although no hereditary mutations in APOE or APOA4 have been described to date, both protein products are amyloidogenic and frequently found within amyloid deposits. SUMMARY: Understanding the underlying apolipoprotein mutations that contribute to hereditary amyloidosis may help improve understanding of this rare but serious disorder and could open the door for targeted therapies and the potential development of new treatment options.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.067
GPT teacher head0.365
Teacher spread0.298 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations8
Published2020
Admission routes2
Has abstractyes

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