Atlantic salmon (Salmo salar) and brown trout (Salmo trutta) differ in their suitability as hosts for the endangered freshwater pearl mussel (Margaritifera margaritifera) in northern Fennoscandian rivers

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Increased Production of Xylanase by Expression of a Truncated Version of the xyn11A Gene from Nonomuraea flexuosa in Trichoderma reesei

We have previously shown that the Nonomuraea flexuosa Xyn11A polypeptides devoid of the carbohydrate binding module (CBM) have better thermostability than the full-length xylanase and are effective in bleaching of pulp. To produce an enzyme preparation useful for industrial applications requiring high temperature, the region encoding the CBM was deleted from the N. flexuosa xyn11A gene and the truncated gene was expressed in Trichoderma reesei. The xylanase sequence was fused to the T. reesei mannanase I (Man5A) signal sequence or 3′ to a T. reesei carrier polypeptide, either the Man5A core/hinge or the cellulose binding domain (CBD) of cellobiohydrolase II (Cel6A, CBHII). The gene and fusion genes were expressed using the cellobiohydrolase 1 (cel7A, cbh1) promoter. Single-copy isogenic transformants in which the expression cassette replaced the cel7A gene were cultivated and analyzed. The transformants expressing the truncated N. flexuosa xyn11A produced clearly increased amounts of both the xylanase/fusion mRNA and xylanase activity compared to the corresponding strains expressing the full-length N. flexuosa xyn11A. The transformant expressing the cel6A CBD-truncated N. flexuosa xyn11A produced about 1.9 g liter⁻¹ of the xylanase in laboratory-scale fermentations. The xylanase constituted about 25% of the secreted proteins. The production of the truncated xylanase did not induce the unfolded protein response (UPR) pathway. However, the UPR was induced when the full-length N. flexuosa xyn11A with an exact fusion to the cel7A terminator was expressed. We suggest that the T. reesei folding/secretion machinery is not able to cope properly with the bacterial CBM when the mRNA of the full-length N. flexuosa xyn11A is efficiently translated.     

Inhibitory Activity of the Isoflavone Biochanin A on Intracellular Bacteria of Genus Chlamydia and Initial Development of a Buccal Formulation

Given the established role of Chlamydia spp. as causative agents of both acute and chronic diseases, search for new antimicrobial agents against these intracellular bacteria is required to promote human health. Isoflavones are naturally occurring phytoestrogens, antioxidants and efflux pump inhibitors, but their therapeutic use is limited by poor water-solubility and intense first-pass metabolism. Here, we report on effects of isoflavones against C. pneumoniae and C. trachomatis and describe buccal permeability and initial formulation development for biochanin A. Biochanin A was the most potent Chlamydia growth inhibitor among the studied isoflavones, with an IC₅₀ = 12 µM on C. pneumoniae inclusion counts and 6.5 µM on infectious progeny production, both determined by immunofluorescent staining of infected epithelial cell cultures. Encouraged by the permeation of biochanin A across porcine buccal mucosa without detectable metabolism, oromucosal film formulations were designed and prepared by a solvent casting method. The film formulations showed improved dissolution rate of biochanin A compared to powder or a physical mixture, presumably due to the solubilizing effect of hydrophilic additives and presence of biochanin A in amorphous state. In summary, biochanin A is a potent inhibitor of Chlamydia spp., and the in vitro dissolution results support the use of a buccal formulation to potentially improve its bioavailability in antichlamydial or other pharmaceutical applications.     

Improving Prediction of Surgical Site Infection Risk with Multilevel Modeling

Background

Surgical site infection (SSI) surveillance is a key factor in the elaboration of strategies to reduce SSI occurrence and in providing surgeons with appropriate data feedback (risk indicators, clinical prediction rule).

Aim

To improve the predictive performance of an individual-based SSI risk model by considering a multilevel hierarchical structure.

Patients and Methods

Data were collected anonymously by the French SSI active surveillance system in 2011. An SSI diagnosis was made by the surgical teams and infection control practitioners following standardized criteria. A random 20% sample comprising 151 hospitals, 502 wards and 62280 patients was used. Three-level (patient, ward, hospital) hierarchical logistic regression models were initially performed. Parameters were estimated using the simulation-based Markov Chain Monte Carlo procedure.

Results

A total of 623 SSI were diagnosed (1%). The hospital level was discarded from the analysis as it did not contribute to variability of SSI occurrence (p  = 0.32). Established individual risk factors (patient history, surgical procedure and hospitalization characteristics) were identified. A significant heterogeneity in SSI occurrence between wards was found (median odds ratio [MOR] 3.59, 95% credibility interval [CI] 3.03 to 4.33) after adjusting for patient-level variables. The effects of the follow-up duration varied between wards (p<10⁻⁹), with an increased heterogeneity when follow-up was <15 days (MOR 6.92, 95% CI 5.31 to 9.07]). The final two-level model significantly improved the discriminative accuracy compared to the single level reference model (p<10⁻⁹), with an area under the ROC curve of 0.84.

Conclusion

This study sheds new light on the respective contribution of patient-, ward- and hospital-levels to SSI occurrence and demonstrates the significant impact of the ward level over and above risk factors present at patient level (i.e., independently from patient case-mix).     

Fourier transform infrared spectroscopic imaging and multivariate regression for prediction of proteoglycan content of articular cartilage

Fourier Transform Infrared (FT-IR) spectroscopic imaging has been earlier applied for the spatial estimation of the collagen and the proteoglycan (PG) contents of articular cartilage (AC). However, earlier studies have been limited to the use of univariate analysis techniques. Current analysis methods lack the needed specificity for collagen and PGs. The aim of the present study was to evaluate the suitability of partial least squares regression (PLSR) and principal component regression (PCR) methods for the analysis of the PG content of AC. Multivariate regression models were compared with earlier used univariate methods and tested with a sample material consisting of healthy and enzymatically degraded steer AC. Chondroitinase ABC enzyme was used to increase the variation in PG content levels as compared to intact AC. Digital densitometric measurements of Safranin O-stained sections provided the reference for PG content. The results showed that multivariate regression models predict PG content of AC significantly better than earlier used absorbance spectrum (i.e. the area of carbohydrate region with or without amide I normalization) or second derivative spectrum univariate parameters. Increased molecular specificity favours the use of multivariate regression models, but they require more knowledge of chemometric analysis and extended laboratory resources for gathering reference data for establishing the models. When true molecular specificity is required, the multivariate models should be used.     

Long-term demographic surveys reveal a consistent relationship between average occupancy and abundance within local populations of a butterfly metapopulation

Species distribution models are the tool of choice for large-scale population monitoring, environmental association studies and predictions of range shifts under future environmental conditions. Available data and familiarity of the tools rather than the underlying population dynamics often dictate the choice of specific method – especially for the case of presence–absence data. Yet, for predictive purposes, the relationship between occupancy and abundance embodied in the models should reflect the actual population dynamics of the modelled species. To understand the relationship of occupancy and abundance in a heterogeneous landscape at the scale of local populations, we built a spatio-temporal regression model of populations of the Glanville fritillary butterfly Melitaea cinxia in a Baltic Sea archipelago. Our data comprised nineteen years of habitat surveys and snapshot data of land use in the region. We used variance partitioning to quantify relative contributions of land use, habitat quality and metapopulation covariates. The model revealed a consistent and positive, but noisy relationship between average occupancy and mean abundance in local populations. Patterns of abundance were highly variable across years, with large uncorrelated random variation and strong local population stochasticity. In contrast, the spatio-temporal random effect, habitat quality, population connectivity and patch size explained variation in occupancy, vindicating metapopulation theory as the basis for modelling occupancy patterns in fragmented landscapes. Previous abundance was an important predictor in the occupancy model, which points to a spillover of abundance into occupancy dynamics. While occupancy models can successfully model large-scale population structure and average occupancy, extinction probability estimates for local populations derived from occupancy-only models are overconfident, as extinction risk is dependent on actual, not average, abundance.     

Nanoimprint Lithography–Based Fabrication of Plasmonic Array of Elliptical Nanoholes for Dual-Wavelength,Dual-Polarisation Refractive Index Sensing

Plasmonics - We report on the novel fabrication and characterisation of plasmonic arrays of elliptical nanohole, and their use for refractive index based sensing. The substrates were fabricated...