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Record W2168285814 · doi:10.1099/mic.0.030684-0

Molecular typing of Mycobacterium intracellulare using multilocus variable-number of tandem-repeat analysis: identification of loci and analysis of clinical isolates

2009· article· en· W2168285814 on OpenAlexfundno aff
Kazuya Ichikawa, Tetsuya Yagi, Takayuki Inagaki, Makoto Moriyama, Taku Nakagawa, Kei‐ichi Uchiya, Toshiaki Nikai, Kenji Ogawa

Bibliographic record

VenueMicrobiology · 2009
Typearticle
Languageen
FieldMedicine
TopicMycobacterium research and diagnosis
Canadian institutionsnot available
FundersMcGill University
KeywordsVariable number tandem repeatBiologyTandem repeatTypingMinisatelliteGenotypeMycobacterium avium-intracellulare infectionGeneticsMycobacteriumGenomeVirologyMicrosatelliteAlleleGeneBacteria

Abstract

fetched live from OpenAlex

In addition to its known status as a disseminated disease in HIV-positive patients, Mycobacterium avium complex (MAC) is increasingly recognized as a causative pathogen of respiratory disease in HIV-negative patients. MAC is divided into Mycobacterium avium, and the less-epidemiologically studied Mycobacterium intracellulare. Genetic typing for M. intracellulare using variable number of tandem repeats (VNTR) has not yet been developed. The aim of this study was to identify VNTR loci in the genome of M. intracellulare and apply them as an epidemiological tool to clinical isolates. Here, we identified 25 VNTR loci on the M. intracellulare genome, of which 16 showed variations among clinical isolates in the number of tandem repeat motifs. Among the 74 M. intracellulare isolates, 50 genotypes were distinguished using the 16 VNTR loci, resulting in a Hunter Gaston's discriminatory index of 0.988. Moreover, all 16 VNTR loci were stable in different sets of isolates recovered within time intervals ranging from 2 to 1551 days from 14 separate patients. These results indicate that for use as epidemiological markers of M. intracellulare, the loci in this VNTR assay are highly discriminating and stable over time.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.100
Threshold uncertainty score0.471

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.025
GPT teacher head0.354
Teacher spread0.329 · 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 designBench or experimental
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

Citations30
Published2009
Admission routes1
Has abstractyes

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