MétaCan
Menu
Back to cohort
Record W6938908124 · doi:10.60692/hv3jn-c4366

Role of polymorphic bile salt export pump (BSEP, ABCB11) transporters in anti-tuberculosis drug-induced liver injury in a Chinese cohort

2016· article· en· W6938908124 on OpenAlexaff

Bibliographic record

VenueGreater South Information System · 2016
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicDrug-Induced Hepatotoxicity and Protection
Canadian institutionsMcMaster University
Fundersnot available
KeywordsBile Salt Export PumpOdds ratioGenotypeLiver injuryGenotypingLogistic regressionPolymorphism (computer science)TaqMan

Abstract

fetched live from OpenAlex

Evidence indicates that the polymorphisms in bile salt export pump (BSEP, encoded by ABCB11) may play an important role in the development of anti-tuberculosis drug-induced liver injury (ATDILI) and we aim to investigate the association between genetic variants of ABCB11 and the risk of ATDILI in a Chinese cohort. A total of 89 tuberculosis patients with ATDILI and 356 matched ATDILI -free patients constituted cases and controls. Genetic polymorphisms of ABCB11 were determined by TaqMan single-nucleotide polymorphism (SNP) genotyping assay. Odds ratio (OR) with 95% confidence intervals (CIs) was estimated by conditional logistic regression model. There were no significant differences in genotype frequencies of ABCB11 between cases and controls. In the subgroup analysis, polymorphisms of rs2287616 were found to be associated with cholestatic/mixed pattern of liver injury under dominant and addictive model (OR = 3.84, 95% CI:1.16-12.75, P = 0.028 and OR = 2.51, 95% CI:1.12-5.62, P = 0.025, respectively), however the significance disappeared after Bonferroni correction. This study suggested that genetic variants of ABCB11 gene might contribute to anti-tuberculosis drug-induced cholestatic liver injury in Chinese patients. Studies in larger, varied populations are required to confirm these 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 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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.147
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.000
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 head0.300
Teacher spread0.252 · 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.

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
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueGreater South Information SystemSame topicDrug-Induced Hepatotoxicity and ProtectionFrench-language works237,207