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Record W2107652450 · doi:10.1155/2012/872169

Identification of<i>Candida</i>Species Associated with Vulvovaginal Candidiasis by Multiplex PCR

2012· article· en· W2107652450 on OpenAlexaff
Mahnaz Mahmoudi Rad, Ameneh Sh Zafarghandi, Maryam Amel Zabihi, Mahkam Tavallaee, Yasaman Mirdamadi

Bibliographic record

VenueInfectious Diseases in Obstetrics and Gynecology · 2012
Typearticle
Languageen
FieldImmunology and Microbiology
TopicReproductive tract infections research
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsMultiplex polymerase chain reactionCandida glabrataCandida albicansVulvovaginal CandidiasisCorpus albicansBiologyMicrobiologyAgarose gel electrophoresisPolymerase chain reactionGeneGenetics

Abstract

fetched live from OpenAlex

BACKGROUND: Vulvovaginal candidiasis is a common infection. The aim of this study was to identify the species of vaginal Candida isolates by using multiplex PCR technique. METHODS: 191 isolates from patients admitted to Mahdieh hospital were identified. The vaginal swab specimens were cultured on Sabouraud Dextrose Agar. The ITS1 region between the 18S and 5.8S rRNA genes and a specific DNA fragment within the ITS2 region were amplified. The multiplex PCR products were separated by electrophoresis in 2% agarose gel, visualized by staining with ethidium bromide, and photographed. Descriptive statistics, Chi-square test, and Spearman correlation were used to summarize the findings. RESULTS: C. albicans and C. glabrata were the most common species isolated from the specimens. A mix of C. glabrata and C. albicans was the most common mixed infection isolated from the samples. The analysis revealed a significant positive association between older age and infection with C. glabrata isolates (Spearman's rho = 0.89, P = 0.015). CONCLUSION: Multiplex PCR is a fast, yet reliable method to identify Candida species. C. albicans and then C. glabrata are the two most common causes of vulvovaginal candidiasis. The number of mixed fungal infections is higher among Iranian population compared to international reports.

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)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
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 head0.011
GPT teacher head0.254
Teacher spread0.243 · 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.

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

Citations54
Published2012
Admission routes1
Has abstractyes

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