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Record W3166425341 · doi:10.1016/j.crpvbd.2021.100036

Current debates and advances in tick microbiome research

2021· review· en· W3166425341 on OpenAlexaff
Alejandra Wu‐Chuang, Adnan Hodžić, Lourdes Mateos‐Hernández, Agustín Estrada‐Peña, Dasiel Obregón, Alejandro Cabezas‐Cruz

Bibliographic record

VenueCurrent Research in Parasitology and Vector-Borne Diseases · 2021
Typereview
Languageen
FieldImmunology and Microbiology
TopicVector-borne infectious diseases
Canadian institutionsUniversity of Guelph
FundersAgence Nationale de la Recherche
KeywordsMicrobiomeTickBiologyEvolutionary biologyEcologyZoologyBioinformatics

Abstract

fetched live from OpenAlex

The main importance of ticks resides in their ability to harbor pathogens that can be transmitted to terrestrial vertebrates including humans. Recently, studies have focused on the taxonomic and functional composition of the tick microbiome, its microbial diversity and variation under different factors including tick species, sex, and environment among others. Of special interest are the interactions between the tick, the microbiome and pathogens since tick microbiome can influence pathogen colonization within the tick vector, and potentially, transmission to the vertebrate host. In this review, we tackled a synthesis on the growing field of tick microbiomes. We focus on the current state of tick microbiome research, addressing controversial and hotly debated topics and advances in the precise manipulation of tick microbiome. Furthermore, we discuss the innovative anti-tick microbiota vaccines as a possible tool for microbiome modulation and thus, control of tick-borne diseases. Deciphering tick-microbiome pathogen interactions can spur new strategies to control tick-borne diseases via modulation of tick microbiome.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0000.001
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.002

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 head0.113
GPT teacher head0.489
Teacher spread0.376 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations124
Published2021
Admission routes1
Has abstractyes

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