Lactobacillus casei Is Able To Survive and Initiate Protein Synthesis during Its Transit in the Digestive Tract of Human Flora-Associated Mice

Live Lactobacillus casei is present in fermented dairy products and has beneficial properties for human health. In the human digestive tract, the resident flora generally prevents the establishment of ingested lactic acid bacteria, the presence of which is therefore transient. The aim of this work was to determine if L. casei DN-114 001 survives during transit and how this bacterium behaves in the digestive environment. We used the human flora-associated (HFA) mouse model. L. casei DN-114 001 was genetically modified by the introduction of erm and lux genes, encoding erythromycin resistance and luciferase, respectively. For this modified strain (DN-240 041), light emission related to luciferase expression could easily be detected in the contents of the digestive tract. When inoculated into the digestive tract of HFA mice, L. casei (DN-240 041) survives but is eliminated with the same kinetics as an inert transit marker, indicating that it does not establish itself. In pure culture of L. casei, luciferase activities were high in the exponential and early stationary growth phases but decreased to become undetectable 1 day after inoculation. Viability was only slightly reduced even after more than 5 days. After transit in HFA mice, luciferase activity was detected even when 5-day-old L. casei cultures were given to the mice. In culture, the luciferase activity could be restored after 0.5 to 7 h of incubation in fresh medium or milk containing glucose, unless protein synthesis was inhibited by the addition of chloramphenicol or rifampin. These results suggest that in HFA mice L. casei DN-240 041, and thus probably L. casei DN-114 001, is able to initiate new protein synthesis during its transit with the diet. The beneficial properties of L. casei-fermented milk for human health might be related to this protein synthesis in the digestive tract

Empirical Matching Functions: Searchers, Vacancies, and (Un-)biased Elasticities

This paper shows that conventional empirical estimates of matching functions are systematically biased, because unobservable and endogenous search behaviour, such as on-the-job search by workers or the use of different search channels by firms, is neglected. I propose an approach for recovering unbiased elasticities under different scenarios of competition for workers and jobs without the need for constructing proxies for unobserved stocks of searchers and vacancies. Using German administrative data, I estimate the biases affecting conventional studies and derive bias-corrected estimates of the matching elasticities under different scenarios. Copyright (c) The London School of Economics and Political Science 2007.