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Record W3217330276 · doi:10.3390/v13112321

Cytomegalovirus Immunity, Inflammation and Cognitive Abilities in the Elderly

2021· article· en· W3217330276 on OpenAlexafffund
Jacqueline Hesson, Neva J. Fudge, Michael D. Grant

Bibliographic record

VenueViruses · 2021
Typearticle
Languageen
FieldMedicine
TopicCytomegalovirus and herpesvirus research
Canadian institutionsMemorial University of Newfoundland
FundersNewfoundland and Labrador Centre for Applied Health Research
KeywordsCognitionInflammationImmunologyCytomegalovirusCognitive declineMedicineImmunityCognitive skillImmune systemInternal medicineHerpesviridaeDementiaPsychiatryViral diseaseVirusDisease

Abstract

fetched live from OpenAlex

Reducing the socioeconomic toll from age-related physical and mental morbidities requires better understanding of factors affecting healthy aging. While many environmental, lifestyle, and genetic factors affect healthy aging, this study addressed the influence of cytomegalovirus (CMV) infection and immunity on age-related inflammation and cognitive abilities. Healthy adults 70–90 years old were recruited into a prospective study investigating relationships between anti-CMV immunity, markers of inflammation, baseline measures of cognitive ability, and changes in cognitive ability over 18 months. Humoral and cellular responses against CMV, levels of inflammatory markers, and cognitive abilities were measured at study entry, with measurement of cognitive abilities repeated 18 months later. CMV-seropositive and -seronegative sub-groups were compared, and relationships between anti-CMV immunity, markers of inflammation, and cognitive ability were assessed. Twenty-eight of 39 participants were CMV-seropositive, and two had CMV-specific CD8+ T cell responses indicative of CMV immune memory inflation. No significant differences for markers of inflammation or measures of cognitive ability were observed between groups, and cognitive scores changed little over 18 months. Significant correlations between markers of inflammation and cognitive scores with interconnection between anti-CMV antibody levels, fractalkine, cognitive ability, and depression scores suggest areas of focus for future studies.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.488
Threshold uncertainty score0.391

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.048
GPT teacher head0.339
Teacher spread0.291 · 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

Citations9
Published2021
Admission routes2
Has abstractyes

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