Alternative tissue fixation for combined histopathological and molecular analysis in a clinically representative setting

Formalin is the principal tissue fixative used worldwide for clinical and research purposes. Despite optimal preservation of morphology, its preservation of DNA and RNA is poor. As clinical diagnostics increasingly incorporates molecular-based analysis, the requirement for maintaining nucleic acid quality is of increasing importance. Here we assess an alternative non-formalin-based tissue fixation method, PAXgene Tissue system, with the aim of better preserving nucleic acids, while maintaining the quality of the tissue to be used for vital existing diagnostic techniques. In this study, these criteria are assessed in a clinically representative setting. In total, 203 paired PAXgene Tissue and formalin-fixed samples were obtained. Blind-scored haematoxylin and eosin (H&E) sections showed comparable and acceptable staining. Immunohistochemistry (IHC) staining was suboptimal using existing protocols but improved with minor method adjustment and optimisation. Quality of DNA and RNA was significantly improved by PAXgene tissue fixation [RIN 2.8 versus 3.8 (p < 0.01), DIN 5.68 versus 6.77 (p < 0.001)], which translated into improved performance on qPCR assay. These results demonstrate the potential of PAXgene Tissue to be used routinely in place of formalin, maintaining adequate histological staining and significantly improving the preservation of biological molecules in the genomic era

Exploring the quality of social information disclosed in non-financial reports of Croatian companies

By enacting the provisions of Directive 2014/95/EU and the Croatian Accounting Act on disclosing non-financial and diversity information, companies of public interest registering 500 and more employees are required to disclose non-financial information. The purpose of this research is to assess the quality of disclosed social information in non- financial/sustainability reports of Croatian companies. The assessment of the social information was grounded on the framework defined by globally accepted sustainability reporting standards by assessing the quality of social subcategories of human rights, labour practice, community/society and product, measured by attributes of relevance, clarity, verifiability, comparability and clarity. With the overall quality score of 13.16 (out of possible 36), the results prove that Croatian companies do disclose certain social information, but the reliability of this information for benchmarking and competitiveness assessment is questionable, as a consensus on the minimum of information to be disclosed as a fundamental requirement for benchmarking has not yet been reached

Consumers’ perceived corporate social responsibility evaluation and support: the moderating role of consumer information

This study analyzes how consumers’ evaluations of various dimensions of corporate social responsibility (CSR) affect their support of it and how consumers’ searches for CSR information influence such evaluations. The empirical analysis relies on data on CSR from a wide representative sample of 3543 Spanish hotel consumers. We use hierarchical multiple regressions to test the relationships and use factorial analysis to test the validity of the different CSR dimensions. The proposed positive effects of legal, ethical, economic, philanthropic and environmental dimensions of CSR on consumers’ support for corporate reputation, the selection of an establishment, and future purchase intention are corroborated, although they are only partially corroborated in the case of the economic dimension. These relationships are moderated in some cases by consumers’ search for information about hotels’ CSR practices. Managerial and economic implications are derived from the results

A genetic algorithm-Bayesian network approach for the analysis of metabolomics and spectroscopic data: application to the rapid detection of Bacillus spores and identification of Bacillus species

Background The rapid identification of Bacillus spores and bacterial identification are paramount because of their implications in food poisoning, pathogenesis and their use as potential biowarfare agents. Many automated analytical techniques such as Curie-point pyrolysis mass spectrometry (Py-MS) have been used to identify bacterial spores giving use to large amounts of analytical data. This high number of features makes interpretation of the data extremely difficult We analysed Py-MS data from 36 different strains of aerobic endospore-forming bacteria encompassing seven different species. These bacteria were grown axenically on nutrient agar and vegetative biomass and spores were analyzed by Curie-point Py-MS. Results We develop a novel genetic algorithm-Bayesian network algorithm that accurately identifies sand selects a small subset of key relevant mass spectra (biomarkers) to be further analysed. Once identified, this subset of relevant biomarkers was then used to identify Bacillus spores successfully and to identify Bacillus species via a Bayesian network model specifically built for this reduced set of features. Conclusions This final compact Bayesian network classification model is parsimonious, computationally fast to run and its graphical visualization allows easy interpretation of the probabilistic relationships among selected biomarkers. In addition, we compare the features selected by the genetic algorithm-Bayesian network approach with the features selected by partial least squares-discriminant analysis (PLS-DA). The classification accuracy results show that the set of features selected by the GA-BN is far superior to PLS-DA

Bayesian Space-Time Patterns and Climatic Determinants of Bovine Anaplasmosis

Citation: Hanzlicek, G. A., Raghavan, R. K., Ganta, R. R., & Anderson, G. A. (2016). Bayesian Space-Time Patterns and Climatic Determinants of Bovine Anaplasmosis. Plos One, 11(3), 13. doi:10.1371/journal.pone.0151924The space-time pattern and environmental drivers (land cover, climate) of bovine anaplasmosis in the Midwestern state of Kansas was retrospectively evaluated using Bayesian hierarchical spatio-temporal models and publicly available, remotely-sensed environmental covariate information. Cases of bovine anaplasmosis positively diagnosed at Kansas State Veterinary Diagnostic Laboratory (n = 478) between years 2005-2013 were used to construct the models, which included random effects for space, time and space-time interaction effects with defined priors, and fixed-effect covariates selected a priori using an univariate screening procedure. The Bayesian posterior median and 95% credible intervals for the space-time interaction term in the best-fitting covariate model indicated a steady progression of bovine anaplasmosis over time and geographic area in the state. Posterior median estimates and 95% credible intervals derived for covariates in the final covariate model indicated land surface temperature (minimum), relative humidity and diurnal temperature range to be important risk factors for bovine anaplasmosis in the study. The model performance measured using the Area Under the Curve (AUC) value indicated a good performance for the covariate model (>0.7). The relevance of climatological factors for bovine anaplasmosis is discussed

Farmers’ perceptions of climate change : identifying types

Ambitious targets to reduce greenhouse gas (GHG) emissions from agriculture have been set by both national governments and their respective livestock sectors. We hypothesize that farmer self-identity influences their assessment of climate change and their willingness to im- plement measures which address the issue. Perceptions of climate change were determined from 286 beef/sheep farmers and evaluated using principal component analysis (PCA). The analysis elicits two components which evaluate identity (productivism and environmental responsibility), and two components which evaluate behavioral capacity to adopt mitigation and adaptation measures (awareness and risk perception). Subsequent Cluster Analyses reveal four farmer types based on the PCA scores. ‘The Productivist’ and ‘The Countryside Steward’ portray low levels of awareness of climate change, but differ in their motivation to adopt pro-environmental behavior. Conversely, both ‘The Environmentalist’ and ‘The Dejected’ score higher in their awareness of the issue. In addition, ‘The Dejected’ holds a high sense of perceived risk; however, their awareness is not conflated with an explicit understanding of agricultural GHG sources. With the exception of ‘The Environmentalist’, there is an evident disconnect between perceptions of agricultural emission sources and their contribution towards GHG emissions amongst all types. If such linkages are not con- ceptualized, it is unlikely that behavioral capacities will be realized. Effective communication channels which encour- age action should target farmers based on the groupings depicted. Therefore, understanding farmer types through the constructs used in this study can facilitate effective and tai- lored policy development and implementation