Hierarchical clustering based upon contextual alignment of proteins: a different way to approach phylogeny

Exposures to Volatile Organic Compounds among Healthcare Workers: Modeling the Effects of Cleaning Tasks and Product Use

Objectives

Use of cleaning and disinfecting products is associated with work-related asthma among healthcare workers, but the specific levels and factors that affect exposures remain unclear. The objective of this study was to evaluate the determinants of selected volatile organic compound (VOC) exposures in healthcare settings.

Methods

Personal and mobile-area air measurements (n = 143) from 100 healthcare workers at four hospitals were used to model the determinants of ethanol, acetone, 2-propanol, d-limonene, α-pinene, and chloroform exposures. Hierarchical cluster analysis was conducted to partition workers into groups with similar cleaning task/product-use profiles. Linear mixed-effect regression models using log-transformed VOC measurements were applied to evaluate the association of individual VOCs with clusters of task/product use, industrial hygienists' grouping (IH) of tasks, grouping of product application, chemical ingredients of the cleaning products used, amount of product use, and ventilation.

Results

Cluster analysis identified eight task/product-use clusters that were distributed across multiple occupations and hospital units, with the exception of clusters consisting of housekeepers and floor strippers/waxers. Results of the mixed-effect models showed significant associations between selected VOC exposures and several clusters, combinations of IH-generated task groups and chemical ingredients, and product application groups. The patient/personal cleaning task using products containing chlorine was associated with elevated levels of personal chloroform and α-pinene exposures. Tasks associated with instrument sterilizing and disinfecting were significantly associated with personal d-limonene and 2-propanol exposures. Surface and floor cleaning and stripping tasks were predominated by housekeepers and floor strippers/waxers, and use of chlorine-, alcohol-, ethanolamine-, and quaternary ammonium compounds-based products was associated with exposures to chloroform, α-pinene, acetone, 2-propanol, or d-limonene.

Conclusions

Healthcare workers are exposed to a variety of chemicals that vary with tasks and ingredients of products used during cleaning and disinfecting. The combination of product ingredients with cleaning and disinfecting tasks were associated with specific VOCs. Exposure modules for questionnaires used in epidemiologic studies might benefit from seeking information on products used within a task context.

Methods of combinatorial optimization to reveal factors affecting gene length

In this paper we present a novel method for genome ranking according to gene lengths. The main outcomes described in this paper are the following: the formulation of the genome ranking problem, presentation of relevant approaches to solve it, and the demonstration of preliminary results from prokaryotic genomes ordering. Using a subset of prokaryotic genomes, we attempted to uncover factors affecting gene length. We have demonstrated that hyperthermophilic species have shorter genes as compared with mesophilic organisms, which probably means that environmental factors affect gene length. Moreover, these preliminary results show that environmental factors group together in ranking evolutionary distant species.

Entropy bounds for hierarchical molecular networks

In this paper we derive entropy bounds for hierarchical networks. More precisely, starting from a recently introduced measure to determine the topological entropy of non-hierarchical networks, we provide bounds for estimating the entropy of hierarchical graphs. Apart from bounds to estimate the entropy of a single hierarchical graph, we see that the derived bounds can also be used for characterizing graph classes. Our contribution is an important extension to previous results about the entropy of non-hierarchical networks because for practical applications hierarchical networks are playing an important role in chemistry and biology. In addition to the derivation of the entropy bounds, we provide a numerical analysis for two special graph classes, rooted trees and generalized trees, and demonstrate hereby not only the computational feasibility of our method but also learn about its characteristics and interpretability with respect to data analysis.

Contextual multiple sequence alignment

In a recently proposed contextual alignment model, efficient algorithms exist for global and local pairwise alignment of protein sequences. Preliminary results obtained for biological data are very promising. Our main motivation was to adopt the idea of context dependency to the multiple alignment setting. To this aim the relaxation of the model was developed (we call this new model averaged contextual alignment) and a new family of amino acids substitution matrices are constructed. In this paper we present a contextual multiple alignment algorithm and report the outcomes of experiments performed for the BAliBASE test set. The contextual approach turned out to give much better results for the set of sequences containing orphan genes.