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Record W2120482187 · doi:10.3748/wjg.15.3161

Characterization of clarithromycin resistance in Malaysian isolates of Helicobacter pylori

2009· article· en· W2120482187 on OpenAlexaff
Norazah Ahmad, Wan Rasinah Zakaria, Sheikh Anwar Abdullah, Ramelah Mohamed

Bibliographic record

VenueWorld Journal of Gastroenterology · 2009
Typearticle
Languageen
FieldMedicine
TopicHelicobacter pylori-related gastroenterology studies
Canadian institutionsInstitute for Biological Sciences
Fundersnot available
KeywordsClarithromycin23S ribosomal RNAHelicobacter pyloriBiologyMicrobiologyPoint mutationRestriction enzymePolymerase chain reactionRestriction fragment length polymorphismGeneMutationGeneticsRNA

Abstract

fetched live from OpenAlex

AIM: To characterize the types of mutations present in the 23S rRNA genes of Malaysian isolates of clarithromycin-resistant Helicobacter pylori (H pylori). METHODS: Clarithromycin susceptibility of H pylori isolates was determined by E test. Analyses for point mutations in the domain V of 23S rRNA genes in clarithromycin-resistant and -sensitive strains were performed by sequence analysis of amplified polymerase chain reaction products. Restriction fragment length polymorphism was performed using BsaI and MboII enzymes to detect restriction sites that correspond to the mutations in the clarithromycin-resistant strains. RESULTS: Of 187 isolates from 120 patients, four were resistant to clarithromycin, while 183 were sensitive. The MIC of the resistant strains ranged from 1.5 to 24 microg/mL. Two isolates had an A2142G mutation and another two had A2143G mutations. A T2182C mutation was detected in two out of four clarithromycin-resistant isolates and in 13 of 14 clarithromycin-sensitive isolates. Restriction enzyme analyses with BsaI and MboII were able to detect the mutations. CONCLUSION: Clarithromycin resistance is an uncommon occurrence among Malaysian isolates of H pylori strains and the mutations A2142G and A2143G detected were associated with low-level resistance.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.293
Threshold uncertainty score0.913

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.011
GPT teacher head0.249
Teacher spread0.238 · 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

Citations39
Published2009
Admission routes1
Has abstractyes

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