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Record W4392635367 · doi:10.53555/sfs.v10i6.2258

Serological And Immunological Study Of Cytomegalovirus In Patients With Rheumatiod Arthriris And Cardiovascular Disease

2023· article· en· W4392635367 on OpenAlexvenueno aff
Mohammed rahil alanazi, Ahoud faisal Almutairi, Shrouq faisal al-hazmi, Mosleh reda soud alanazi, Amal faisal Almutairi, Atyaf Yahya Moafa

Bibliographic record

VenueJournal of Survey in Fisheries Sciences · 2023
Typearticle
Languageen
FieldMedicine
TopicCytomegalovirus and herpesvirus research
Canadian institutionsnot available
Fundersnot available
KeywordsSerologyCytomegalovirus infectionDiseaseCytomegalovirusMedicineVirologyImmunologyAntibodyInternal medicineHuman cytomegalovirusVirusViral diseaseHerpesviridae

Abstract

fetched live from OpenAlex

Cytomegalovirus (CMV) infection has been implicated in various chronic diseases, including rheumatoid arthritis (RA) and cardiovascular disease (CVD). In this study, we aimed to investigate the serological and immunological aspects of CMV infection in patients with RA and CVD. Serum samples from patients with RA, CVD, and healthy controls were tested for CMV-specific antibodies using serological assays. Additionally, the levels of pro-inflammatory cytokines were measured in the serum to assess the immune response to CMV infection. Our results showed a higher prevalence of CMV IgG antibodies in patients with RA and CVD compared to the healthy controls. Furthermore, patients with RA and CVD had elevated levels of pro-inflammatory cytokines, suggesting an inflammatory response to CMV infection. These findings highlight the potential role of CMV in the pathogenesis of RA and CVD and emphasize the importance of investigating the immunological aspects of CMV in these conditions.

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)0.002
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.144
GPT teacher head0.300
Teacher spread0.156 · 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
Published2023
Admission routes1
Has abstractyes

Explore more

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