Design of novel urogenital pharmabiotic formulations containing lactobacilli,salivaricin CRL 1328 and non-microbial compounds with different functionalities

Context: The administration of pharmabiotics is a promising alternative to antimicrobial drugs for the treatment and/or prevention of female urogenital infections.

Objective: To design pharmabiotic formulations including bioactive ingredients of microbial origin combined with non-microbial substances and then to evaluate the stability of the combinations during freeze-drying and storage.

Materials and methods: Different formulations including Lactobacillus gasseri CRL 1263, Lactobacillus salivarius CRL 1328, salivaricin CRL 1328 (a bacteriocin) and non-microbial compounds (lactose, inulin and ascorbic acid) were assayed, and the ingredients were freeze-dried together or separately. The formulations were stored in gelatin capsules at 4?°C for 360?d.

Results: The viability of lactobacilli was affected to different extents depending on the strains and on the formulations assayed. L. salivarius and ascorbic acid were successfully combined only after the freeze-drying process. Salivaricin activity was not detected in formulations containing L. gasseri. However, when combined with ascorbic acid, lactose, inulin or L. salivarius, the bacteriocin maintained its activity for 360?d. The selected microorganisms proved to be compatible for their inclusion in multi-strain formulations together with lactose, inulin and ascorbic acid. Salivaricin could be included only in a L. salivarius CRL 1328 single-strain formulation together with non-microbial substances.

Conclusions: This study provides new insights into the design of urogenital pharmabiotics combining beneficial lactobacilli, salivaricin CRL 1328 and compounds with different functionalities.     

Distribution-free uncertainty quantification for kernel methods by gradient perturbations

Machine Learning - We propose a data-driven approach to quantify the uncertainty of models constructed by kernel methods. Our approach minimizes the needed distributional assumptions, hence,...     

Mixture ratio modeling of dynamic systems

Any knowledge extraction relies (possibly implicitly) on a hypothesis about the modelled-data dependence. The extracted knowledge ultimately serves to a decision-making (DM). DM always faces uncertainty and this makes probabilistic modelling adequate. The inspected black-box modeling deals with “universal” approximators of the relevant probabilistic model. Finite mixtures with components in the exponential family are often exploited. Their attractiveness stems from their flexibility, the cluster interpretability of components and the existence of algorithms for processing high-dimensional data streams. They are even used in dynamic cases with mutually dependent data records while regression and auto-regression mixture components serve to the dependence modeling. These dynamic models, however, mostly assume data-independent component weights, that is, memoryless transitions between dynamic mixture components. Such mixtures are not universal approximators of dynamic probabilistic models. Formally, this follows from the fact that the set of finite probabilistic mixtures is not closed with respect to the conditioning, which is the key estimation and predictive operation. The paper overcomes this drawback by using ratios of finite mixtures as universally approximating dynamic parametric models. The paper motivates them, elaborates their approximate Bayesian recursive estimation and reveals their application potential.     

Biodegradability Study of the Biosurfactant Contained in a Crude Extract from Corn Steep Water

Over the last few years, the global biosurfactant market has raised due to the increasing awareness among consumers, for the use of biological or bio-based products. Because of their composition, it can be speculated that these are more biocompatible and more biodegradable than their chemical homologous. However, at the moment, no studies exist in the literature about the biodegradability of biosurfactants. In this work, a biosurfactant contained in a crude extract, obtained from a corn wet-milling industry stream that ferments spontaneously in the presence of lactic acid bacteria, was subjected to a biodegradation study, without addition of external microbial biomass, under different conditions of temperature (5–45 °C), biodegradation time (15–55 days), and pH (5–7). For that, a Box–Behnken factorial design was applied, which allowed to predict the percentage of biodegradation for the biosurfactant contained in the crude extract, between the range of the independent variables selected in the study, obtaining biodegradation values between 3 and 80%. The percentage of biodegradation for the biosurfactant was calculated based on the increase in the surface tension of samples of the crude extract. Furthermore, it was also possible to predict the variation in t_1/2 for the biosurfactant (time to achieve the 50% of biodegradation) under different conditions.