Identification of Rothia Bacteria as Gluten-Degrading Natural Colonizers of the Upper Gastro-Intestinal Tract

Gluten proteins, prominent constituents of barley, wheat and rye, cause celiac disease in genetically predisposed subjects. Gluten is notoriously difficult to digest by mammalian proteolytic enzymes and the protease-resistant domains contain multiple immunogenic epitopes. The aim of this study was to identify novel sources of gluten-digesting microbial enzymes from the upper gastro-intestinal tract with the potential to neutralize gluten epitopes.Oral microorganisms with gluten-degrading capacity were obtained by a selective plating strategy using gluten agar. Microbial speciations were carried out by 16S rDNA gene sequencing. Enzyme activities were assessed using gliadin-derived enzymatic substrates, gliadins in solution, gliadin zymography, and 33-mer α-gliadin and 26-mer γ-gliadin immunogenic peptides. Fragments of the gliadin peptides were separated by RP-HPLC and structurally characterized by mass spectrometry. Strains with high activity towards gluten were typed as Rothia mucilaginosa and Rothia aeria. Gliadins (250 µg/ml) added to Rothia cell suspensions (OD(620) 1.2) were degraded by 50% after ∼30 min of incubation. Importantly, the 33-mer and 26-mer immunogenic peptides were also cleaved, primarily C-terminal to Xaa-Pro-Gln (XPQ) and Xaa-Pro-Tyr (XPY). The major gliadin-degrading enzymes produced by the Rothia strains were ∼70-75 kDa in size, and the enzyme expressed by Rothia aeria was active over a wide pH range (pH 3-10).While the human digestive enzyme system lacks the capacity to cleave immunogenic gluten, such activities are naturally present in the oral microbial enzyme repertoire. The identified bacteria may be exploited for physiologic degradation of harmful gluten peptides

Harnessing Sustainable Motivation: A Grounded Theory Exploration of Public Service Motivation in Local Governments of the State of Oregon, United States

Employee motivation has always been a matter of concern for both public and private sector organizations. Since the industrial revolution in the late 18th century, organizations have struggled to foster workforce motivation and morale to enhance productivity. While a plethora of literature focuses on private sector motivation research, public sector organizations receive only modest scholarly attention. However, a new concept has emerged in public management literature during the late 1980s and 1990s, later known as public service motivation (PSM). The debate about PSM is premised on the notion that the motivation of public sector employees is quite different from their private sector counterparts because of their orientation to public service. Perry and Wise (1990) expressed this concept in the theory of PSM. Subsequently, a growing stream of scholarship has emerged which explores the many aspects of antecedents and outcomes related to PSM. However, questions remain about how to best keep the motivation of public sector employees sustainably high, and about what factors embolden or enervate the motivation and morale of public sector employees. This study focuses on the sustainable work motivation of local government employees. Its arguments and discussions draw from PSM theory, total quality management (TQM) principles, and inspiration from Sustainable Development Goals (SDGs). This study examines and attempts to uncover the career trajectories of local government employees in the State of Oregon, United States, through a rigorous grounded theory method (GTM) of inquiry. The study reveals a number of factors that facilitate and/or inhibit employees’ PSM. We expect the findings to be useful for both practitioners and government human resource policymakers in understanding the subtlety and vicissitudes of public sector employee careers and motivations

Semi-supervised classification based on subspace sparse representation

Graph plays an important role in graph-based semi-supervised classification. However, due to noisy and redundant features in high-dimensional data, it is not a trivial job to construct a well-structured graph on high-dimensional samples. In this paper, we take advantage of sparse representation in random subspaces for graph construction and propose a method called Semi-Supervised Classification based on Subspace Sparse Representation, SSC-SSR in short. SSC-SSR first generates several random subspaces from the original space and then seeks sparse representation coefficients in these subspaces. Next, it trains semi-supervised linear classifiers on graphs that are constructed by these coefficients. Finally, it combines these classifiers into an ensemble classifier by minimizing a linear regression problem. Unlike traditional graph-based semi-supervised classification methods, the graphs of SSC-SSR are data-driven instead of man-made in advance. Empirical study on face images classification tasks demonstrates that SSC-SSR not only has superior recognition performance with respect to competitive methods, but also has wide ranges of effective input parameters

An investigation of the effect of ti, pd and zr on the dehydriding kinetics of mgh2

The effect of additives Ti, Pd and Zr on the rate of hydrogen desorption from MgH2 is investigated using high-pressure differential scanning calorimetry. Van't Hoff analysis as well as X-ray powder diffraction measurements confirm that no new intermetallic phases are formed in these systems but enhanced dehydriding kinetics are obtained in the presence of Pd and Zr. For the Mg-Zr composite, Zr precipitates are formed throughout the material on heating to 500 °C but these do not grow with further thermal cycling. The desorption rate for all the composites was found to increase with temperature as well as pressure difference between experimental and equilibrium pressures. A value of 114 ± 4 kJ mol−1 was obtained for the activation energy for dehydriding of the Mg-Ti-Pd composite. The effect of additives Ti, Pd and Zr on the rate of hydrogen desorption from MgH2 is investigated using high-pressure differential scanning calorimetry. Van't Hoff analysis as well as X-ray powder diffraction measurements confirm that no new intermetallic phases are formed in these systems but enhanced dehydriding kinetics are obtained in the presence of Pd and Zr. For the Mg-Zr composite, Zr precipitates are formed throughout the material on heating to 500 °C but these do not grow with further thermal cycling. The desorption rate for all the composites was found to increase with temperature as well as pressure difference between experimental and equilibrium pressures. A value of 114 ± 4 kJ mol−1 was obtained for the activation energy for dehydriding of the Mg-Ti-Pd composite