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Record W2143484771 · doi:10.1139/cjm-2012-0490

Detection of<i>Ophiocordyceps sinensis</i>in soil by quantitative real-time PCR

2013· article· en· W2143484771 on OpenAlexvenueno aff
Qingyun Peng, Xin Zhong, Wei Lei, Guren Zhang, Xin Liu

Bibliographic record

VenueCanadian Journal of Microbiology · 2013
Typearticle
Languageen
FieldMedicine
TopicFungal Biology and Applications
Canadian institutionsnot available
FundersNational Key Research and Development Program of ChinaKey Technologies Research and Development Program
Keywordsgenomic DNABiologyInternal transcribed spacerDNA extractionReal-time polymerase chain reactionDNAPolymerase chain reactionVeterinary medicineBotanyMolecular biologyChromatographyRibosomal RNAGeneticsChemistryGene

Abstract

fetched live from OpenAlex

Ophiocordyceps sinensis, one of the best known entomopathogenic fungi in traditional Chinese medicine, parasitizes larvae of the moth genus Thitarodes, which lives in soil tunnels. However, little is known about the spatial distribution of O. sinensis in the soil. We established a protocol for DNA extraction, purification, and quantification of O. sinensis in soil with quantitative real-time PCR targeting the internal transcribed spacer region. The method was assessed using 34 soil samples from Tibet. No inhibitory effects in purified soil DNA extracts were detected. The standard curve method for absolute DNA quantification generated crossing point values that were strongly and linearly correlated to the log10 of the initial amount of O. sinensis genomic DNA (r(2) = 0.999) over 7 orders of magnitude (4 × 10(1) to 4 × 10(7) fg). The amplification efficiency and y-intercept value of the standard curve were 1.953 and 37.70, respectively. The amount of O. sinensis genomic DNA decreased with increasing soil depth and horizontal distance from a sclerotium (P < 0.05). Our protocol is rapid, specific, sensitive, and provides a powerful tool for quantification of O. sinensis from soil.

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 score0.120
Threshold uncertainty score0.999

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 head0.009
GPT teacher head0.227
Teacher spread0.218 · 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

Citations11
Published2013
Admission routes1
Has abstractyes

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