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Purpose: The raised competitiveness among technology companies, especially for being able to work with markets physically distant from their final consumer, makes it important to know the employee's perception about the built environment since the physical workspaces influence productivity. This paper aims to analyze the attributes and dimensions of the built environment of a development software company that most impact the employee's satisfaction through their perception. It allows the company to identify the strengths and weaknesses of the built environment, enhancing the employee's satisfaction, productivity and, consequently, the company revenues. Design/methodology/approach: This research applied a survey by the drop off method and analyzed data through confirmatory factor analysis and multiple linear regression. Therefore, these methods explain how the attributes behave in each theoretical dimension and evaluate the relation between the dependent and independent dimensions. Findings: The theoretical result of this research concerns the employee's satisfaction with the built environment of a software development company. Overall, employee satisfaction is related to the dimensions of functionality, appearance and personal relationships, not being significant aspects of configuration. On the other hand, the employee's overall satisfaction with the built environment is related to the functional dimension. Research limitations/implications: This research limitation is related to the size of the sample, which is a pre-determined and fixed population: all the company's employees. Originality/value: Perceived quality applied to a work environment of a software development company. [ABSTRACT FROM AUTHOR]

The physiological and molecular effects of tobacco smoke in adult humans and the development of cancer have been well described. In contrast, how tobacco smoke affects embryonic development remains poorly understood. Morphological studies of the fetuses of smoking pregnant women have shown various physical deformities induced by constant fetal exposure to tobacco components, especially nicotine. In addition, nicotine exposure decreases fetal body weight and bone/cartilage growth in addition to decreasing cranial diameter and tibia length. Unfortunately, the molecular pathways leading to these morphological anomalies are not completely understood. In this study, we applied interactome data mining tools and small compound interaction networks to elucidate possible molecular pathways associated with the effects of tobacco smoke components during embryonic development in pregnant female smokers. Our analysis showed a relationship between nicotine and 50 additional harmful substances involved in a variety of biological process that can cause abnormal proliferation, impaired cell differentiation, and increased oxidative stress. We also describe how nicotine can negatively affect retinoic acid signaling and cell differentiation through inhibition of retinoic acid receptors. In addition, nicotine causes a stress reaction and/or a pro-inflammatory response that inhibits the agonistic action of retinoic acid. Moreover, we show that the effect of cigarette smoke on the developing fetus could represent systemic and aggressive impacts in the short term, causing malformations during certain stages of development. Our work provides the first approach describing how different tobacco constituents affect a broad range of biological process in human embryonic development. [ABSTRACT FROM AUTHOR]

Promoters are DNA sequences located upstream of the transcription start site of genes. In bacteria, the RNA polymerase enzyme requires additional subunits, called sigma factors (σ) to begin specific gene transcription in distinct environmental conditions. Currently, promoter prediction still poses many challenges due to the characteristics of these sequences. In this paper, the nucleotide content of Escherichia coli promoter sequences, related to five alternative σ factors, was analyzed by a machine learning technique in order to provide profiles according to the σ factor which recognizes them. For this, the clustering technique was applied since it is a viable method for finding hidden patterns on a data set. As a result, 20 groups of sequences were formed, and, aided by the Weblogo tool, it was possible to determine sequence profiles. These found patterns should be considered for implementing computational prediction tools. In addition, evidence was found of an overlap between the functions of the genes regulated by different σ factors, suggesting that DNA structural properties are also essential parameters for further studies. HighlightsCurrently, promoter prediction still poses many challenges due to the characteristics of promoter sequences.A clustering technique was applied on promoter sequences related to the alternative sigma factors of Escherichia coli. Creating 20 distinct profiles.The results exhibited evidence of an overlap in gene functions between the sigma factors. These found patterns should be considered for implementing computational prediction tools. [ABSTRACT FROM AUTHOR]