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Record W2763904592 · doi:10.1016/j.ram.2017.05.003

Biofilm-forming capacity of blood–borne Candida albicans strains and effects of antifungal agents

2017· article· es· W2763904592 on OpenAlexaboutno aff
Hanni Turan, Müge Demirbilek

Bibliographic record

VenueRevista Argentina de Microbiología · 2017
Typearticle
Languagees
FieldMedicine
TopicAntifungal resistance and susceptibility
Canadian institutionsnot available
FundersBaskent Üniversitesi
KeywordsBiofilmAnidulafunginMicafunginMicrobiologyItraconazoleCaspofunginCandida albicansFluconazoleAmphotericin BVoriconazoleEchinocandinsCorpus albicansEchinocandinAntifungalChemistryMedicineBiologyBacteria

Abstract

fetched live from OpenAlex

Infections related to Candida albicans biofilms and subsequent antifungal resistance have become more common with the increased use of indwelling medical devices. Regimens for preventing fungal biofilm formation are needed, particularly in high-risk patients. In this study, we investigated the biofilm formation rate of multiple strains of Candida albicans (n = 162 clinical isolates), their antifungal susceptibility patterns, and the efficacy of certain antifungals for preventing biofilm formation. Biofilm formation was graded using a modified Christensen's 96-well plate method. We further analyzed 30 randomly chosen intense biofilm-forming isolates using the XTT method. Minimum biofilm inhibition concentrations (MBIC) of caspofungin, micafungin, anidulafungin, fluconazole, voriconazole, posaconazole, itraconazole, and amphotericin B were determined using the modified Calgary biofilm method. In addition, the inhibitory effects of antifungal agents on biofilm formation were investigated. Our study showed weak, moderate, and extensive biofilm formation in 29% (n = 47), 38% (n = 61), and 23% (n = 37) of the isolates, respectively. We found that echinocandins had the lowest MBIC values and that itraconazole inhibited biofilm formation in more isolates (26/32; 81.3%) than other tested agents. In conclusion, echinocandins were most effective against formed biofilms, while itraconazole was most effective for preventing biofilm formation. Standardized methods are needed for biofilm antifungal sensitivity tests when determining the treatment and prophylaxis of C. albicans infections. Las infecciones relacionadas con las biopelículas de Candida albicans y la consiguiente resistencia antifúngica se han vuelto fenómenos habituales con el uso creciente de dispositivos médicos permanentes. Son necesarios regímenes para prevenir la formación de biopelículas fúngicas, en especial en los pacientes de alto riesgo. En este estudio se investigó la tasa de formación de biopelículas de numerosas cepas de Candida albicans (162 aislados clínicos), sus patrones de sensibilidad a los antifúngicos y la eficacia de algunos de estos agentes para prevenir la formación de biopelículas. La formación de biopelículas se clasificó utilizando el método de Christensen modificado de 96 pocillos. Posteriormente se analizaron 30 aislados de formación intensa de biopelículas elegidos al azar, utilizando el método XTT. Se calcularon las concentraciones mínimas de inhibición de biopelículas (minimum biofilm inhibition concentrations, MBIC) de la caspofungina, la micafungina, la anidulafungina, el fluconazol, el voriconazol, el posaconazol, el itraconazol y la anfotericina B, utilizando el método modificado de biopelículas de Calgary. Además, se investigaron los efectos inhibitorios de los agentes antifúngicos sobre la formación de biopelículas. Nuestro estudio encontró una formación débil, moderada e intensa de biopelículas en el 29% (n = 47), 38% (n = 61) y 23% (n = 37) de los aislados, respectivamente. Encontramos que las equinocandinas mostraron los menores valores MBIC, y que el itraconazol inhibió la formación de biopelículas en más aislados (26/32; 81,3%) que otros agentes ensayados. En conclusión, las equinocandinas resultaron más eficaces frente a las biopelículas formadas, mientras que el itraconazol resultó más eficaz para prevenir la formación de biopelículas. Se necesita contar con métodos estandarizados para efectuar las pruebas de sensibilidad a los antifúngicos en términos de formación de biopelículas a la hora de determinar el tratamiento y la profilaxis de las infecciones por C. albicans.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.250
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.020
GPT teacher head0.282
Teacher spread0.262 · 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

Citations25
Published2017
Admission routes1
Has abstractyes

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