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Record W2405957127 · doi:10.1017/s0317167100051477

TGF-β1 869T/C Polymorphism and Ischemic Stroke: Sex Difference in Chinese

2010· article· en· W2405957127 on OpenAlexvenueno aff
Hongmiao Tao, Guozhong Chen, Xiaodong Lü, Gan-ping Chen, Bei Shao

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicTGF-β signaling in diseases
Canadian institutionsnot available
FundersJinhua Science and Technology Bureau
KeywordsIschemic strokeMedicineInternal medicineStroke (engine)Polymorphism (computer science)CardiologyGeneticsGenotypeBiologyGeneIschemiaPhysics

Abstract

fetched live from OpenAlex

BACKGROUND: Inflammation plays a pivotal role in the pathogenesis of atherosclerosis and of cerebrovascular complications. Transforming growth factor-β (TGF-β) is a pleiotropic cytokine with a central role in inflammation. To investigate whether polymorphisms of the TGF-β1 gene can modify the risk of ischemic stroke (IS) in Chinese population, we conduct this hospital-based, case-control study. METHODS: Transforming growth factor-β1 genotype was determined in 450 Chinese patients (306 male and 144 female) with IS and 450 control subjects (326 male and 124 female). RESULTS: Subjects carrying 869TT were susceptible to IS (odds ratio [OR] =1.58; P=0.003). Further analysis of IS data partitioned by gender revealed the female-specific association with 869T/C (OR=2.64; P=0.001). CONCLUSIONS: Findings suggest that the TT genotype of 869T/C might be a risk factor of IS in Chinese, especially in females.

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 score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.012
GPT teacher head0.247
Teacher spread0.235 · 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

Citations11
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences NeurologiquesSame topicTGF-β signaling in diseasesFrench-language works237,207