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Pathogenic enterotoxigenic Escherichia coli (ETEC) are the major bacterial cause of diarrhea in young children in developing countries and in travelers, causing significant mortality in children. Adhesive fimbriae are a prime virulence factor for ETEC, initiating colonization of the small intestinal epithelium. Similar to other Gram-negative bacteria, ETEC express one or more diverse fimbriae, some assembled by the chaperone-usher pathway and others by the alternate chaperone pathway. Here, we elucidate structural and biophysical aspects and adaptations of each fimbrial type to its respective host niche. CS20 fimbriae are compared with colonization factor antigen I (CFA/I) fimbriae, which are two ETEC fimbriae assembled via different pathways, and with P-fimbriae from uropathogenic E.coli. Many fimbriae unwind from their native helical filament to an extended linear conformation under force, thereby sustaining adhesion by reducing load at the point of contact between the bacterium and the target cell. CFA/I fimbriae require the least force to unwind, followed by CS20 fimbriae and then P-fimbriae, which require the highest unwinding force. We conclude from our electron microscopy reconstructions, modeling and force spectroscopy data that the target niche plays a central role in the biophysical properties of fimbriae that are critical for bacterial pathophysiology.

Objectives: In a working environment it is important to measure dust exposure to evaluate possible health issues. Passive sampling could be an alternative to active sampling with pumps when measuring occupational dust exposure. One passive sampler is the University of North Carolina passive aerosol sampler (UNC sampler). Promising results for the applicability of this type of passive sampler have been shown for particles above 2.5 μm, but indicate large underestimations for PM_2.5. The overall purpose was to develop more knowledge about the UNC sampler and the possibility of using it for personal sampling of occupational dust exposure. Specific aims were to: evaluate and possibly improve the UNC sampler for stationary sampling in a working environment and compare the UNC sampler with commonly used aerosol sampling methods; characterise the impairment in performance of the UNC sampler concentrations when decreasing the number of images in order to achieve lowered costs and decreased analysis time, and; establish if the UNC sampler could be used for personal sampling in the working environment.

Methods: All sample collection in this thesis was performed in an open pit mine. For stationary sampling UNC samplers, impactors (PM₁₀ and PM_2.5), respirable cyclones, and an aerodynamic particle sizer were used. For personal sampling UNC samplers and respirable cyclones were used. The analysis of the UNC sampler consisted of two parts, the microscopic imaging of the deposited particles and the analysis model for calculations of mass concentration.

Results: In the first pilot study the UNC sampler with its original analysis model was used. Compared to PM₁₀ impactor concentrations the UNC sampler showed 58% of the impactor results and 35% of PM_2.5 impactor results. The second study showed that a new analysis model and use of higher microscopy resolution led to no underestimation compared to PM_2.5 impactors, while PM₁₀ improved but not to the same extent. A higher precision was also achieved compared to the respirable cyclone (intraclass correlation: 0.51 versus 0.24). When UNC sampler particle size distributions were compared to aerodynamic particle sizer data, they showed similar distributions for the new analysis model, but deviating distributions for the original analysis model. In the third study the number of images needed from the microscopic imaging process was reduced. Reducing the number of images analysed from 60 to 10 increased the coefficient of variation from 36% to 37% for respirable fraction. Finally, the UNC sampler was used for personal sampling in a working environment for the first time. Again, the particle size distribution of the new UNC sampler analysis model was reasonable, while the distribution of the original model was not. There were almost exclusively particles of mineral origin on the UNC sampler, but compared to the respirable cyclone, the UNC sampler overestimated the particle concentrations approximately 30 times.

Conclusions: The new analysis model for the UNC sampler enables stationary passive sampling of dust exposure of mineral character. Quicker microscopic image analysis, by reducing the number of images for mass concentration calculations to ten, results in a negligible loss in precision. Personal sampling with the UNC sampler showed deposited particles of reasonable size distribution and obviously originating from the working environment, but with severe overestimation of the mass concentration. Thus, the UNC sampler with the new analysis model can be used for stationary sampling in a mine, but is not yet ready for personal sampling.

Objectives: In an occupational environment, passive sampling could be an alternative to active sampling with pumps for sampling of dust. One passive sampler is the University of North Carolina passive aerosol sampler (UNC sampler). It is often analysed by microscopic imaging. Promising results have been shown for particles above 2.5 µm, but indicate large underestimations for PM_2.5. The aim of this study was to evaluate, and possibly improve, the UNC sampler for stationary sampling in a working environment.

Methods: Sampling was carried out at 8-h intervals during 24 h in four locations in an open pit mine with UNC samplers, respirable cyclones, PM₁₀ and PM_2.5 impactors, and an aerodynamic particle sizer (APS). The wind was minimal. For quantification, two modifications of the UNC sampler analysis model, UNC sampler with hybrid model and UNC sampler with area factor, were compared with the original one, UNC sampler with mesh factor derived from wind tunnel experiments. The effect of increased resolution for the microscopic imaging was examined.

Results: Use of the area factor and a higher resolution eliminated the underestimation for PM₁₀ and PM_2.5. The model with area factor had the overall lowest deviation versus the impactor and the cyclone. The intraclass correlation (ICC) showed that the UNC sampler had a higher precision and better ability to distinguish between different exposure levels compared to the cyclone (ICC: 0.51 versus 0.24), but lower precision compared to the impactor (PM₁₀: 0.79 versus 0.99; PM_2.5: 0.30 versus 0.45). The particle size distributions as calculated from the different UNC sampler analysis models were visually compared with the distributions determined by APS. The distributions were obviously different when the UNC sampler with mesh factor was used but came to a reasonable agreement when the area factor was used.

Conclusions: High resolution combined with a factor based on area only, results in no underestimation of small particles compared to impactors and cyclones and a better agreement with the APS’s particle size distributions. The UNC sampler had lower precision than the impactors, but higher than the respirable cyclone. The UNC sampler with area factor could be used for PM_2.5, PM₁₀ and respirable fraction measurements in this working environment without wind.

The aim of this study was to make a preliminary evaluation of the University of North Carolina passive aerosol sampler (UNC sampler) for personal air sampling of particles. Nine personal air samplings of respirable fraction were conducted in an open-pit mine, with pairwise UNC samplers and a respirable cyclone mounted on the chest of workers. UNC samples were analyzed with scanning electron microscopy (SEM) and to some extent energy dispersive X-ray spectroscopy (EDS). Respirable cyclone filter samples were weighed. Correlations and particle elemental compositions were described. Microscopic imaging of the collection surface showed that the particles were heterogeneously deposited across the surface of the UNC sampler. Collected particles were shaped as gravel particles and the resulting particle size distribution in air showed a peak at ca. 3 µm aerodynamic diameter, similarly to what has previously been reported from the same mine. The elemental composition indicated mineral origin. All correlations between the airborne mass concentrations from UNC samplers and respirable cyclones (Pearson = 0.54 and Spearman = 0.43) and between pairs of parallel UNC samplers (Pearson = 0.55 and Spearman = 0.67) were weak. The UNC sampler mass concentrations were approximately 30 times higher than those measured with the respirable cyclone. In conclusion, the UNC sampler, when used for personal sampling in a mine, provides a reasonable particle size distribution and the deposited particles appeared to be of mineral origin and not from textile or skin but the approximately 30-fold overestimation of mass concentrations when comparing with respirable cyclone sampling indicates that further improvements are necessary. Positioning of the sampler may be critical and moving the UNC sampler from the chest to e.g. the top of a helmet might be an improvement. Grounding of the sampler in order to avoid static electricity might also be useful. The UNC sampler should continue to be researched for personal sampling, as passive sampling might become a useful alternative to more laborious sampling techniques.

The University of North Carolina passive aerosol sampler (UNC sampler) could be an alternative when measuring occupational dust exposure, but the time required for microscopic imaging of the sampler needs to be reduced to make it more attractive. The aims of this study were to 1) characterise the effect on precision when reducing imaging, in order to shorten analysis time and 2) assess if the position of the images makes a difference. Eighty-eight samplers were deployed in different locations of an open pit mine. Sixty images were captured for each UNC sampler, covering 51% of its collection surface, using scanning electron microscopy. Bootstrapped samples were generated with different image combinations, to assess the within-sampler coefficient of variation (CV_ws) for different numbers of images. In addition, the particle concentration relative to the distance from the centre of the sampler was studied. Reducing the number of images collected from the UNC sampler led to up to 8.3% CV_ws for ten images when calculating respirable fraction. As the overall CV has previously been assessed to 36%, the additional contribution becomes minimal, increasing the overall CV to 37%. The mean concentrations of the images were modestly related to distance from the centre of the sampler. The CV_ws changed from 8.26% to 8.13% for ten images when applying rules for the image collection based on distance. Thus, the benefit of these rules on the precision is small and the images can therefore be chosen at random. In conclusion, reducing the number of images analysed from 60 to 10, corresponding to a reduction of the imaged sampling area from 51% to 8.5%, results in a negligible loss in precision for respirable fraction dust measurements in occupational environments.

Objectives: Dust is generally sampled on a filter using air pumps, but passive sampling could be a cost-effective alternative. One promising passive sampler is the University of North Carolina passive aerosol sampler (UNC sampler). The aim of this study is to characterize and compare the UNC sampler’s performance with PM₁₀ and PM_2.5 impactors in a working environment.

Methods: Area sampling was carried out at different mining locations using UNC samplers in parallel with PM_2.5 and PM₁₀ impactors. Two different collection surfaces, polycarbonate (PC) and carbon tabs (CT), were employed for the UNC sampling. Sampling was carried out for 4–25 hours.

Results: The UNC samplers underestimated the concentrations compared to PM₁₀ and PM_2.5 impactor data. At the location with the highest aerosol concentration, the time-averaged mean of PC showed 24% and CT 35% of the impactor result for PM_2.5. For PM₁₀, it was 39% with PC and 58% with CT. Sample blank values differed between PC and CT. For PM_2.5, PC blank values were ~7 times higher than those of CT, but only 1.8 times higher for PM₁₀. The blank variations were larger for PC than for CT.

Conclusions: Particle mass concentrations appear to be underestimated by the UNC sampler compared to impactors, more so for PM_2.5 than for PM₁₀. CT may be preferred as a collection surface because the blank values were lower and less variable than for PC. Future validations in the working environment should include respirable dust sampling.