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Record W7006258805

Test Accuracy of the Montreal Cognitive Assessment in Screening for Early Poststroke Neurocognitive Disorder

2020· other· en· W7006258805 on OpenAlexaboutno aff

Bibliographic record

VenueDuo Research Archive (University of Oslo) · 2020
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsEnterocyteImmune systemNeurocognitiveNOD2Human immunodeficiency virus (HIV)Intestinal mucosaInflammationIleum
DOInot available

Abstract

fetched live from OpenAlex

Background. Human immunodeficiency virus (HIV)–infected immunological nonresponders (INRs) fail to reconstitute their CD4+ T-cell pool after initiation of antiretroviral therapy, and their prognosis is inferior to that of immunological responders (IRs). A prevailing hypothesis is that the INR phenotype is caused by a persistently disrupted mucosal barrier, but assessments of gut mucosal immunology in different anatomical compartments are scarce. Methods. We investigated circulating markers of mucosal dysfunction, immune activation, mucosal Th17 and Th22 cells, and mucosa-adherent microbiota signatures in gut mucosal specimens from sigmoid colon and terminal ileum of 19 INRs and 20 IRs in addition to 20 HIV-negative individuals. Results. INRs had higher blood levels of the enterocyte damage marker intestinal fatty acid–binding protein than IRs. In gut mucosal biopsies, INRs had lower fractions of CD4+ T cells, higher fractions of interleukin 22, and a tendency to higher fractions of interleukin 17–producing CD4+ T cells. These findings were all restricted to the colon and correlated to circulating markers of enterocyte damage. There were no observed differences in gut microbial composition between INRs and IRs. Conclusions. Restricted to the colon, enterocyte damage and mucosal immune dysfunction play a role for insufficient immune reconstitution in HIV infection independent of the gut microbiota.

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)0.003
metaresearch head score (Gemma)0.014
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
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 head0.044
GPT teacher head0.318
Teacher spread0.274 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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