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Record W3032923428 · doi:10.1371/journal.pone.0234360

Molecular detection of Coxiella burnetii in livestock farmers and cattle from Magdalena Medio in Antioquia, Colombia

2020· article· en· W3032923428 on OpenAlexaff
Ruth Cabrera, Leonardo Alberto Ríos-Osório, Yoav Keynan, Zulma Vanessa Rueda, Lina A. Gutiérrez

Bibliographic record

VenuePLoS ONE · 2020
Typearticle
Languageen
FieldImmunology and Microbiology
TopicVector-borne infectious diseases
Canadian institutionsUniversity of Manitoba
FundersMinisterio de Ciencia, Tecnología e Innovación
KeywordsCoxiella burnetiiQ feverLivestockVeterinary medicineBiologyPolymerase chain reactionMedicineVirologyEcology

Abstract

fetched live from OpenAlex

Coxiella burnetii causes Q fever in humans and coxiellosis in animals. In humans, it causes acute febrile illnesses like influenza, pneumonia, hepatitis, and chronic illnesses such as endocarditis, vascular infection, and post-infectious fatigue syndrome. It is widely distributed worldwide, and its main reservoirs are sheep, goats, and cattle. This study aimed to determine the frequency of C. burnetii infection using molecular detection and to identify the associated factors in livestock farmers and cattle from the Magdalena Medio region of Antioquia, Colombia. Using real-time polymerase chain reaction (PCR), molecular detection was performed for the IS1111 insertion sequence of C. burnetii using genomic DNA collected from the peripheral blood of 143 livestock farmers and 192 cattle from 24 farms located in Puerto Berrío, Puerto Nare, and Puerto Triunfo. To confirm the results, bidirectional amplicon sequencing of 16S rRNA was performed in four of the positive samples. Additionally, factors associated with C. burnetii were identified using a Poisson regression with cluster effect adjustment. Real-time PCR showed positive results in 25.9% and 19.5% of livestock farmer samples and cattle samples, respectively. For livestock farmers, factors associated with C. burnetii were the area where the farm was located [Puerto Berrío, adjusted prevalence ratio (aPR): 2.13, 95% confidence interval (CI): 1.10-4.11], presence of hens (aPR: 1.47, 95% CI: 1.21-1.79), horses (aPR: 1.61, 95% CI: 1.54-1.67), and ticks (aPR: 2.36, 95% CI: 1.03-5.42) in the residence, and consumption of raw milk (aPR: 1.47, 95% CI: 1.26-1.72). For cattle, the factors associated with Coxiella genus were municipality (Puerto Nare; aPR: 0.39, 95% CI: 0.37-0.41) and time of residence on the farm (≥49 months; aPR: 2.28, 95% CI: 1.03-5.20). By analyzing sequences of the 16S rRNA molecular marker, C. burnetii infection was confirmed in livestock farmers. However, in cattle, only the presence of Coxiella-type bacteria was identified. Further research is necessary to determine the potential role that these types of bacteria have as etiological agents for disease in livestock farmers and cattle from the study area.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.188
Threshold uncertainty score0.511

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.017
GPT teacher head0.202
Teacher spread0.185 · 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

Citations16
Published2020
Admission routes1
Has abstractyes

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