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Record W4309245215 · doi:10.30498/ijb.2022.276921.3012

The <i>HLA rs9267649</i> and <i>CYP24A1 rs2248359</i> Variants are Associated with Multiple Sclerosis: A Study on Iranian Population.

2022· article· en· W4309245215 on OpenAlexaff
Sevil Babashpour, Mitra Ataei, Ferdous Rastgtar Jazii, Shekoofeh Alaie, Mohammad Hossein Sanati

Bibliographic record

VenuePubMed · 2022
Typearticle
Languageen
FieldImmunology and Microbiology
TopicPsoriasis: Treatment and Pathogenesis
Canadian institutionsSGS (Canada)
Fundersnot available
KeywordsMultiple sclerosisAlleleGenotypeMedicineInternal medicineVitamin D and neurologyPopulationExpanded Disability Status ScaleGeneticsBiologyImmunologyGene

Abstract

fetched live from OpenAlex

Background: has shown to play important role in the risk of MS. Objectives: variants with risk of multiple sclerosis (MS) in Iranian population. Materials and Methods: variants were genotyped in 82 Iranian Relapsing-Remitting Multiple Sclerosis (RRMS) patients and 100 matched healthy controls, using the PCR-RFLP method. The genotype and allele frequencies were calculated and statistically analyzed. Results: were found to be more frequent in MS patients than in the healthy controls (p-value: 0.009, OR: 2.264, 95% CI: 1.211-4.231 and p-value: 0.028 OR: 1.594, 95% CI: 1.052-2.415), respectively. Conclusions: gene with MS etiology and an increased risk of MS in Iranian RRMS patients. However, further large-scale investigations in various ethnicities and in the functional genomics level are demanded to confirm our findings.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.033
GPT teacher head0.195
Teacher spread0.162 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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