Trichophyton species: use of volatile fingerprints for rapid identification and discrimination

A method for early detection and identification of fungal contamination of building materials using e-nose

The aim of the study was to develop a method for early detection and identification of fungal contamination of building materials using an electronic nose. Therefore, the laboratory experiments based on the analysis of the air in the vicinity of fungal isolates potentially found in the building materials were performed. The results revealed that the employed gas sensors array consisting of MOS-type sensors enables the detection of the differences among the examined samples of fungi and distinguishing between the non-contaminated and contaminated samples, shortly after fungal contamination occurs. Electronic nose readouts were analysed using Principal Component Analysis and the results were verified with standard chromatographic analysis by means of SPME-GC/MS method, which proved that gas sensors array can be applied for early detection of fungal contamination.

Comprehensive volatile metabolic fingerprinting of bacterial and fungal pathogen groups

The identification of pathogen-specific volatile metabolic 'fingerprints' could lead to the rapid identification of disease-causing organisms either directly from ex vivo patient bio-specimens or from in vitro cultures. In the present study, we have evaluated the volatile metabolites produced by 100 clinical isolates belonging to ten distinct pathogen groups that, in aggregate, account for 90% of bloodstream infections, 90% of urinary tract infections, and 80% of infections encountered in the intensive care unit setting. Headspace volatile metabolites produced in vitro were concentrated using headspace solid-phase microextraction and analyzed via two-dimensional gas chromatography time-of-flight mass spectrometry (HS-SPME-GC×GC-TOFMS). A total of 811 volatile metabolites were detected across all samples, of which 203 were: (1) detected in 9 or 10 (of 10) isolates belonging to one or more pathogen groups, and (2) significantly more abundant in cultures relative to sterile media. Network analysis revealed a distinct metabolic fingerprint associated with each pathogen group, and analysis via Random Forest using leave-one-out cross-validation resulted in a 95% accuracy for the differentiation between groups. The present findings support the results of prior studies that have reported on the differential production of volatile metabolites across pathogenic bacteria and fungi, and provide additional insight through the inclusion of pathogen groups that have seldom been studied previously, including Acinetobacter spp., coagulase-negative Staphylococcus, and Proteus mirabilis, as well as the utilization of HS-SPME-GC×GC-TOFMS for improved sensitivity and resolution relative to traditional gas chromatography-based techniques.

3-D and electrically conducting functional skin mapping for biomedical applications

Ex situ and in situ 3-D and electrically conducting mapping of the skin topography via electropolymerization of a conducting polymer on a previously sampled skin stamp or directly on the skin of a live human subject were performed here with the intention to be further used in biomedical applications.

Identification of pathogenic fungi with an optoelectronic nose

Human fungal infections have gained recent notoriety following contamination of pharmaceuticals in the compounding process. Such invasive infections are a more serious global problem, especially for immunocompromised patients. While superficial fungal infections are common and generally curable, invasive fungal infections are often life-threatening and much harder to diagnose and treat. Despite the increasing awareness of the situation's severity, currently available fungal diagnostic methods cannot always meet diagnostic needs, especially for invasive fungal infections. Volatile organic compounds produced by fungi provide an alternative diagnostic approach for identification of fungal strains. We report here an optoelectronic nose based on a disposable colorimetric sensor array capable of rapid differentiation and identification of pathogenic fungi based on their metabolic profiles of emitted volatiles. The sensor arrays were tested with 12 human pathogenic fungal strains grown on standard agar medium. Array responses were monitored with an ordinary flatbed scanner. All fungal strains gave unique composite responses within 3 hours and were correctly clustered using hierarchical cluster analysis. A standard jackknifed linear discriminant analysis gave a classification accuracy of 94% for 155 trials. Tensor discriminant analysis, which takes better advantage of the high dimensionality of the sensor array data, gave a classification accuracy of 98.1%. The sensor array is also able to observe metabolic changes in growth patterns upon the addition of fungicides, and this provides a facile screening tool for determining fungicide efficacy for various fungal strains in real time.

The future of early disease detection? Applications of electronic nose technology in otolaryngology

INTRODUCTION

Recent advances in electronic nose technology, and successful clinical applications, are facilitating the development of new methods for rapid, bedside diagnosis of disease. There is a real clinical need for such new diagnostic tools in otolaryngology.

MATERIALS AND METHODS

We present a critical review of recent advances in electronic nose technology and current applications in otolaryngology.

RESULTS

The literature reports evidence of accurate diagnosis of common otolaryngological conditions such as sinusitis (acute and chronic), chronic suppurative otitis media, otitis externa and nasal vestibulitis. A significant recent development is the successful identification of biofilm-producing versus non-biofilm-producing pseudomonas and staphylococcus species.

CONCLUSION

Electronic nose technology holds significant potential for enabling rapid, non-invasive, bedside diagnosis of otolaryngological disease.

Diagnostic value of morphological, physiological and biochemical tests in distinguishing Trichophyton rubrum from Trichophyton mentagrophytes complex

The two most frequently encountered dermatophyte etiologic agents of glabrous skin and nail dermatophytoses are Trichophyton rubrum and T. mentagrophytes. This study was aimed to discuss the efficacy of morphological, physiological and biochemical diagnostic tests commonly used in the identification of T. rubrum and members of the T. mentagrophytes complex. In this study, we evaluated; hydrolysis of urea in broth and on urea agar slants and Petri plates incubated at 22 degrees C, 28 degrees C and 37 degrees C, in vitro hair perforation (blond child, sheep and goat hair), pigment production on cornmeal dextrose agar (CMDA) and bromcresol purple-milk solids-glucose agar (BCP-MS-G), Tween opacity, sorbitol assimilation, and salt tolerance. Additionally, the production of micro- and macroconidia was investigated by using brain heart infusion agar (BHIA), Christensen's urea agar in Petri plates (UPA), CMDA, Lowenstein-Jensen agar (LJA), malt extract agar, oatmeal agar, Oxoid chromogenic Candida agar, and potato dextrose agar. All cultures were incubated at 28 degrees C, and conidial production was compared on days 5, 10 and 15. It was found that the urea hydrolysis test yielded more rapid and significant results when urea medium was prepared in Petri plates and incubated at 28 degrees C (P<0.01). LJA supported the highest production of microconidia after 15 days (P<0.001). Additionally, it was found that T. rubrum strains produced red pigment on CMDA (P<0.01) and BCP-MS-G, while strains of the T. mentagrophytes species complex did not. A special algorithm containing the various test procedures employed in these studies is presented which was found to be useful in the differentiation of T. rubrum strains from T. mentagrophytes complex. Our results revealed that UPA, CMDA, BCP-MS-G, LJA, and BHIA may be used as common mycological agars in routine practice.