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Identification of candidate microRNA markers of endometriosis with the use of next-generation sequencing and quantitative real-time polymerase chain reaction

2020· article· en· W3029129472 on OpenAlexafffund
Elahe Papari, Mehrdad Noruzinia, Ladan Kashani, Warren G. Foster

Bibliographic record

VenueFertility and Sterility · 2020
Typearticle
Languageen
FieldMedicine
TopicEndometriosis Research and Treatment
Canadian institutionsMcMaster University
FundersCanadian Institutes of Health Research
KeywordsReal-time polymerase chain reactionPolymerase chain reactionIdentification (biology)microRNAComputational biologyEndometriosisDNA sequencingBiologyGeneticsMedicineGeneInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To identify novel candidate diagnostic microRNA (miRNA) markers of endometriosis by means of an unbiased search with confirmation by means of targeted polymerase chain reaction (PCR). DESIGN: Retrospective cohort. SETTING: University teaching hospitals. PATIENT(S): Women with endometriosis and control women, confirmed with the use of laparoscopy. INTERVENTIONS(S): Diagnostic laparoscopy and blood sample. MAIN OUTCOME MEASURE(S): Next-generation sequencing (NGS) and quantitative real-time PCR (qRT-PCR). RESULT(S): Candidate miRNAs differentially expressed in women with endometriosis compared with control women were identified by means of NGS and selected for qRT-PCR. Plasma samples from another cohort of women with surgically confirmed endometriosis (n = 53) and disease-free control women (n = 53) were checked for hemolysis using spectrophotometry and the ratio of miR-23a and miR-451 by means of qRT-PCR. MicroRNA signatures were quantified by means of qRT-PCR in hemolysis-free plasma samples of case subjects (n = 25) and control subjects (n = 28) with the use of miRcury LNA miRNA. Circulating levels of eight miRNAs (miR-199a-3p, miR-143-3p, miR-340-5p, let-7b-5p, miR-21-5p, miR-17-5p, miR-20a-5p, and miR-103a-3p) were significantly lower in case subjects compared to control subjects. The sensitivity and specificity for individual miRNAs ranged from 0.36 to 1.00 and from 0.43 to 1.00, respectively, but when combined produced sensitivity and specificity of 0.92 and 0.86 with positive (PPV) and (NPV) predictive values of 0.85 and 0.92, respectively. However, combination of five miRNAs (miR-17-5p, miR-20a-5p, miR-199a-3p, miR-143-3p, and let-7b-5p) produced sensitivity and specificity of 0.96 and 0.79 with PPV and NPV of 0.80 and 0.96, respectively. CONCLUSION(S): We conclude that a panel of candidate miRNAs was comparable to laparoscopy in distinguishing between women with endometriosis and control women.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.117
GPT teacher head0.305
Teacher spread0.187 · 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 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".

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Citations87
Published2020
Admission routes2
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