MétaCan
Menu
Back to cohort
Record W2981013951 · doi:10.1080/22221751.2019.1677177

Molecular surveillance of antimicrobial resistance and transmission pattern of <i>Mycobacterium leprae</i> in Chinese leprosy patients

2019· article· en· W2981013951 on OpenAlexaff
Santosh Chokkakula, Zhiming Chen, Haiqin Jiang, Yanqing Chen, Ying Shi, Wenyue Zhang, Wei Gao, Jun Yang, Jinlan Li, Li Xiong, Tiejun Shui, Jun He, Limei Shen, Jie Liu, De Wang, Hao Wang, Huan Chen, Yanfei Kuang, Ziyi Chen, Meiwen Yu, Liangbin Yan, Naveenchandra Suryadevara, Varalakshmi Vissa, Weida Liu, Hongsheng Wang

Bibliographic record

VenueEmerging Microbes & Infections · 2019
Typearticle
Languageen
FieldMedicine
TopicLeprosy Research and Treatment
Canadian institutionsCentre for Global Health Research
Fundersnot available
KeywordsMycobacterium lepraeLeprosyAntibiotic resistanceTransmission (telecommunications)MicrobiologyVirologyBiologyAntimicrobialMedicineAntibioticsImmunologyComputer science

Abstract

fetched live from OpenAlex

Reports on antimicrobial resistance (AMR) of Mycobacterium leprae, relationship with bacteriological index (BI), and transmission in China are limited. We investigated the emergence of AMR mutations, the relationship between BI and AMR in complete, moderate and lack of BI decline cases, and molecular epidemiological features of AMR cases by enrolling 290 leprosy cases from four endemic provinces. Seven (2.41%), one (0.34%), five (1.72%), one (0.34%), and one (0.34%) strains had single mutations in folP1, rpoC, gyrA, gyrB, and 23S rRNA, respectively. Double mutations in folP1 and gyrA, rpoB and gyrA, and gyrA and 23S rRNA were observed in one (0.34%) strain each. Mutated strains occurred in three out of 81 (95% CI−0.005-0.079, p = 0.083) cases with complete BI decline, in seven out of 103 (95% CI 0.018-0.117, p = 0.008) cases with moderate BI decline, and in four out of 34 (95% CI 0.003-0.231, p = 0.044) cases with lack of BI decline. Most of these mutated strains were geographically separated and diverged genotypically. AMR mutations may not be the main cause of the lack of BI decline. The low transmission of AMR strains at the county level indicates an ongoing transmission at close contact levels.

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 score0.016
Threshold uncertainty score0.031

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)0.0020.000

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 head0.003
GPT teacher head0.241
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 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

Citations22
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueEmerging Microbes & InfectionsSame topicLeprosy Research and TreatmentFrench-language works237,207