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Record W3028971414 · doi:10.1111/neup.12660

The autophagic marker p62 highlights Alzheimer type <scp>II</scp> astrocytes in metabolic/hepatic encephalopathy

2020· article· en· W3028971414 on OpenAlexaff
Ellen Gelpí, Jasmin Rahimi, Sigrid Klotz, Susanne Schmid, Gerda Ricken, Sara Forcen‐Vega, Herbert Budka, Gábor G. Kovács

Bibliographic record

VenueNeuropathology · 2020
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsOccupational Cancer Research CentreUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsImmunohistochemistryPathologyHepatic encephalopathyEncephalopathyMedicineEtiologyBiologyInternal medicine

Abstract

fetched live from OpenAlex

Metabolic/hepatic encephalopathy is neuropathologically characterized by the presence of Alzheimer type II astrocytes (AA II) with large and clear nuclear morphology. To date, there is no good immunohistochemical marker to better identify these cells. Here, we assessed cases of hepatic encephalopathy of different etiologies by immunohistochemistry using an anti-p62 antibody. We observed peripheral or diffuse nuclear staining of variable intensity in AA II in all cases but not in normal controls or reactive astrocytes. We conclude that p62 is a useful immunohistochemical marker for the identification of AA II and may be helpful for the neuropathological diagnosis of metabolic/hepatic encephalopathy in difficult or equivocal cases.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

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)0.0020.000

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 head0.030
GPT teacher head0.289
Teacher spread0.259 · 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 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

Citations15
Published2020
Admission routes1
Has abstractyes

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