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Articles by M. Karlsson
Total Records ( 2 ) for M. Karlsson
  A.C. Mgbeahuruike , K. Aliyoo , M. Karlsson and K.F. Chah

Objective: This study was conducted to investigate the fungal community structure in Nigerian poultry environments. Materials and Methods: In ten (layer and broiler) farms, samples were collected from drinkers, doors, feeders, floors, poles, roofs, walls and window nets. Fungal isolation was done on Sabouraud dextrose agar (SDA) followed by identification using morphological and microscopic features. The fungal identities were confirmed by sequencing the internal transcribed spacer region, followed by phylogenetic analysis. Antifungal susceptibility testing was done using nystatin (100 μg mL1), fluconazole (25 μg mL1) and voriconazole (1 μg mL1). Results: A total of 244 fungi were identified in all the locations. In the layers farm, 112 fungal isolates were identified, while 132 isolates were identified in the broiler farm. In all the poultry farms, Aspergillus and Candida species had the highest occurrence of 32.4 and 24.6%, respectively while other fungi (Dematiaceous, Rhizopus, Penicillium, Mucor and Rhodotorula) had 43% occurrence. For the locations, poles and window nets had the highest isolation frequency of 15.2% each. The roofs, feeders and floors had 14.3 and 13.1%, while other locations had 27% isolation rate. Phylogenetic comparison of the isolates showed that closely related fungi from different countries formed separate clades. Candida species were sensitive to the three antifungal agents with the zone of inhibition diameter ranging from 19.08-25.36 mm. All the Aspergillus species were resistant to fluconazole but were sensitive to nystatin and voriconazole. Conclusion: Different fungi were identified in this study and they were all susceptible to nystatin antifungal agent.

  I Haggstrom , L Johansson , A Larsson , N Ostlund , J Sorensen and M. Karlsson

Positron emission tomography (PET) is increasingly used for delineation of tumour tissue in, for example, radiotherapy treatment planning. The most common method used is to outline volumes with a certain per cent uptake over background in a static image. However, PET data can also be collected dynamically and analysed by kinetic models, which potentially represent the underlying biology better. In the present study, a three-parameter kinetic model was used for voxel-wise evaluation of 11C-acetate data of head/neck tumours. These parameters which represent the tumour blood volume, the uptake rate and the clearance rate of the tissue were derived for each voxel using a linear regression method and used for segmentation of active tumour tissue. This feasibility study shows that it is possible to segment images based on derived model parameters. There is, however, room for improvements concerning the PET data acquisition, noise reduction and the kinetic modelling. In conclusion, this early study indicates a strong potential of the method even though no ‘true’ tumour volume was available for validation.

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