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Record W3001812421 · doi:10.1186/s13071-019-3862-4

Bovine ticks harbour a diverse array of microorganisms in Pakistan

2020· article· en· W3001812421 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueParasites & Vectors · 2020
Typearticle
Languageen
FieldImmunology and Microbiology
TopicVector-borne infectious diseases
Canadian institutionsUniversity of Guelph
FundersUniversity of MelbourneAustralian Centre for International Agricultural ResearchAustralian Society for ParasitologyAustralian Government
KeywordsBiologyAnaplasmaBartonellaBabesiaVeterinary medicineEhrlichiaAnaplasma phagocytophilumTick-borne diseaseTheileriaTickParasitologyMicrobiologyVirologyZoologyParasite hostingGeneticsBorrelia burgdorferi

Abstract

fetched live from OpenAlex

BACKGROUND: Ticks and tick-borne pathogens (TTBP) are a major constraint to livestock production in Pakistan; despite a high prevalence of TTBPs, knowledge on the capacity of Pakistani ticks to carry pathogens and endosymbionts is limited. Furthermore, mixed infections with multiple microorganisms further complicate and limit the detection potential of traditional diagnostic methods. The present study investigated the tick-borne microorganisms in bovine ticks in Pakistan, employing a high-throughput microfluidic real-time PCR based technique. METHODS: Ticks were collected from clinically healthy cattle (n = 116) and water buffaloes (n = 88) from 30 villages across six districts located in five agro-ecological zones (AEZs) of Pakistan from September to November 2017. The microfluidic real-time PCR was used to test the genomic DNA of individual ticks for the presence of 27 bacterial and eight parasitic microorganisms. Phylogenetic methods were used to assess the genetic relationship of DNA sequences determined herein. RESULTS: PCR detected DNA of at least one microorganism in each of 221 ticks tested (94.4%, 221/234). DNA-based detection inferred that single pathogens/endosymbionts were the most common (43.4%, 96/221) followed by double (38.9%, 86/221), triple (14.5%, 32/221), quadruple (2.3%, 5/221) and quintuple (0.9%, 2/221) mixed infections. Piroplasms (Babesia/Theileria spp.) were the most prevalent (31.6%, 74/234), followed by Ehrlichia spp. (20%, 47/234) and Anaplasma marginale (7.7%, 18/234). Anaplasma phagocytophilum, A. ovis, A. centrale, Babesia ovis, Borrelia spp., Rickettsia spp., R. massiliae, Bartonella spp. and Hepatozoon spp. were also detected. Endosymbionts such as Francisella-like (91.5%, 214/234) and Coxiella-like (1.3%, 3/234) organisms were also detected in ticks. The highest diversity of microorganisms was detected in Hyalomma anatolicum ticks (test-positive for 14/14 microorganisms), followed by Rhipicephalus microplus (4/14), Hy. hussaini (3/14) and Rh. annulatus (2/14). Ticks collected from cattle carried significantly more frequently piroplasms (41.2%, 54/131; P < 0.05) than those from buffaloes (19.4%, 20/103). However, the overall prevalence of microorganisms did not vary significantly among ticks from the two host species as well as across different AEZs. CONCLUSIONS: To our knowledge, this is the first study to investigate a wide range of tick-borne microorganisms in bovine ticks using a high-throughput diagnostic method from different AEZs in Pakistan. These findings will aid in establishing the distribution patterns and the control of tick-borne pathogens of bovines in Pakistan.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score1.000

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)0.0020.001

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 head0.013
GPT teacher head0.266
Teacher spread0.253 · 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