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Record W1973404795 · doi:10.2478/s11536-009-0106-6

Phylogenetic analysis of house dust mites

2009· article· en· W1973404795 on OpenAlexfundno aff
Yubao Cui, Cuixiang Gao, Ying Zhou, Peng Zhou, Ming Peng, Yingzi Lin, Jianglong Peng

Bibliographic record

VenueOpen Medicine · 2009
Typearticle
Languageen
FieldMedicine
TopicAllergic Rhinitis and Sensitization
Canadian institutionsnot available
FundersMcMaster University
KeywordsPhylogenetic treeDust mitesAcariPyroglyphidaeGeneticsMedicineBiologyZoologyGeneHouse dust miteAllergenAllergyImmunologyAntibodyImmunoglobulin E

Abstract

fetched live from OpenAlex

Abstract House dust mites live in house dusts and affect the health of humans. Among the many species, Dermatophagoides farinae, D. pteronyssinus, and Euroglyphus maynei have been found to be commonly associated with Ig-E-mediated allergic diseases. As a result, there is increasing effort to develop methods for the diagnosis and treatment of diseases caused by these species. The purpose of the current study was to explore the evolutionary relationships among house dust mites. After adult D. farinae were separated and isolated for total RNA extract, the cDNA coding for Der f 1 and Der f 2 were cloned and sequenced. Then amino acid sequences for group 1 and 2 allergens of two of the most common house dust mites, D. pteronyssinus, E. maynei, were obtained from databases. Interestingly, homological analysis of amino acid sequences showed that both Der p 1 and Der p 2 from D. pteronyssinus had more similarities to Eur m 1 and Eur m 2, respectively, than they had to Der f 1 and Der f 2 from D. farinae. In the phylogenetic trees, D. pteronyssinus clustered with E. maynei, but not with D. farinae, although D. pteronyssinus and D. farinae belong to the same genus according to morphological taxonomy. It was previously assumed that D. pteronyssinus was more similar to E. maynei than to D. farinae at evolutionary 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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

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 studies0.0010.000
Scholarly communication0.0010.000
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 head0.031
GPT teacher head0.317
Teacher spread0.286 · 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

Citations8
Published2009
Admission routes1
Has abstractyes

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