Vibrio proteases for biomedical applications: Modulating the proteolytic secretome of v. alginolyticus and v. parahaemolyticus for improved enzymes production

Proteolytic enzymes are of great interest for biotechnological purposes, and their large-scale production, as well as the discovery of strains producing new molecules, is a relevant issue. Collagenases are employed for biomedical and pharmaceutical purposes. The high specificity of collagenase-based preparations toward the substrate strongly relies on the enzyme purity. However, the overall activity may depend on the cooperation with other proteases, the presence of which may be essential for the overall enzymatic activity, but potentially harmful for cells and tissues. Vibrios produce some of the most promising bacterial proteases (including collagenases), and their exo-proteome includes several enzymes with different substrate specificities, the production and relative abundances of which strongly depend on growth conditions. We evaluated the effects of different media compositions on the proteolytic exo-proteome of Vibrio alginolyticus and its closely relative Vibrio parahaemolyticus, in order to improve the overall proteases production, as well as the yield of the desired enzymes subset. Substantial biological responses were achieved with all media, which allowed defining culture conditions for targeted improvement of selected enzyme classes, besides giving insights in possible regulatory mechanisms. In particular, we focused our efforts on collagenases production, because of the growing biotechnological interest due to their pharmaceutical/biomedical applications

Robust job-sequencing with an uncertain flexible maintenance activity

In this study, the problem of scheduling a set of jobs and one uncertain maintenance activity on a single machine, with the objective of minimizing the makespan is addressed. The maintenance activity has a given duration and must be executed within a given time window. Furthermore, duration and time window of the maintenance are uncertain, and can take different values which can be described by different scenarios. The problem is to determine a job sequence which performs well, in terms of makespan, independently on the possible variation of the data concerning the maintenance. A robust scheduling approach is used for the problem, in which four different measures of robustness are considered, namely, maximum absolute regret, maximum relative regret, worst-case scenario, and ordered weighted averaging. Complexity and approximation results are presented. In particular, we show that, for all the four robustness criteria, the problem is strongly NP-hard. A number of special cases are explored, and an exact pseudopolynomial algorithm based on dynamic programming is devised when the number of scenarios is fixed. Two Mixed Integer Programming (MIP) models are also presented for the general problem. Several computational experiments have been conducted to evaluate the efficiency and effectiveness of the MIP models and of the dynamic programming approach

Pareto optimality in multilayer network growth

We model the formation of multi-layer transportation networks as a multi-objective optimization process, where service providers compete for passengers, and the creation of routes is determined by a multi-objective cost function encoding a trade-off between efficiency and competition. The resulting model reproduces well real-world systems as diverse as airplane, train and bus networks, thus suggesting that such systems are indeed compatible with the proposed local optimization mechanisms. In the specific case of airline transportation systems, we show that the networks of routes operated by each company are placed very close to the theoretical Pareto front in the efficiency-competition plane, and that most of the largest carriers of a continent belong to the corresponding Pareto front. Our results shed light on the fundamental role played by multi-objective optimization principles in shaping the structure of large-scale multilayer transportation systems, and provide novel insights to service providers on the strategies for the smart selection of novel routes

biogas from municipal solid waste landfills a simplified mathematical model

Abstract Municipal solid waste (MSW) landfills now represent one of the most important issues related to the waste management cycle. Knowledge of biogas production is a key aspect for the proper exploitation of this energy source, even in the post-closure period. In the present study, a simple mathematical model was proposed for the simulation of biogas production. The model is based on first-order biodegradation kinetics and also takes into account the temperature variation in time and depth as well as landfill settlement. The model was applied to an operating landfill located in Sicily, in Italy, and the first results obtained are promising. Indeed, the results showed a good fit between measured and simulated data. Based on these promising results, the model can also be considered a useful tool for landfill operators for a reliable estimate of the duration of the post-closure period

Two is better than one? Order aggregation in a meal delivery scheduling problem

We address a single-machine scheduling problem motivated by a last-mile-delivery setting for a food company. Customers place orders, each characterized by a delivery point (customer location) and an ideal delivery time. An order is considered on time if it is delivered to the customer within a time window given by the ideal delivery time , where is the same for all orders. A single courier (machine) is in charge of delivery to all customers. Orders are either delivered individually, or two orders can be aggregated in a single courier trip. All trips start and end at the restaurant, so no routing decisions are needed. The problem is to schedule courier trips so that the number of late orders is minimum. We show that the problem with order aggregation is -hard and propose a combinatorial branch and bound algorithm for its solution. The algorithm performance is assessed through a computational study on instances derived by a real-life application and on randomly generated instances. The behavior of the combinatorial algorithm is compared with that of the best ILP formulation known for the problem. Through another set of computational experiments, we also show that an appropriate choice of design parameters allows to apply the algorithm to a dynamic context, with orders arriving over time

A review on effects of biological soil crusts on hydrological processes

Biological soil crusts (BSCs) are complex consortia of microorganisms able to modify soil physical, chemical, and hydrological characteristics and influence soil erosion resistance. Given their importance, this paper analyses the current knowledge about BSCs reporting the findings of 163 papers about different BSC aspects published from 1990 to 2023. At first, a review of the BSC main detection methods (visual inspection, remote sensing, and morphological characterization) is presented as they represent valuable tools in BSC identification and mapping, revealing some issues related to the adopted classification criteria and the BSC microbial composition. Then, the literature results about their influence on soil characteristics, hydrology, and erosion processes are reported. Although their positive effects on soil characteristics (e.g., stability and fertility) and resistance to soil erosion are widely recognized, conflicting results are reported on their influence on soil hydrology. The analysis of the available literature allowed for providing indications about the choice of which microorganisms are the most suitable to form BSCs, following the required objectives (soil physic-chemical improvements, soil hydrology, erosion processes resistance, cost, and time to produce their effects). In particular, the results showed that i) the BSC effects on the soil physic-chemical characteristics improve along their successional series; ii) bacteria and cyanobacteria can be considered the most valuable BSC in limiting and degraded conditions (sediment concentration in the runoff reduced by 87% in comparison to bare soils, cost of 350 USD ha−1, and a recovery time of 5–10 years); iii) the intrinsic heterogeneity of BSCs does not allow for explaining the divergence of the literature results on soil hydrology; and iv) mosses are the best BSC anti-erosive type as they produce the most similar effects as compared to vegetation. Finally, the main steps required to obtain microbial inoculums, the effects of their application to induce BSC formation, and future prospects of research are reported

Influence of the Height of Municipal Solid Waste Landfill on the Formation of Perched Leachate Zones

Waste settlement as well as consolidation phenomena, which occur inside a landfill for municipal solid waste (MSW), can cause a decrease in waste permeability. This can lead to a reduction in conveyance of the leachate drainage system. It is therefore possible that a so-called perched leachate zone will form. Such a zone is constituted by an area in the body of the landfill where the leachate is temporarily trapped and is unable to infiltrate downward. This phenomenon is influenced by many factors, which include rain infiltration rate, waste moisture and composition, landfill height, and so on. The main aim of the paper is to elucidate the role played by landfill height in the formation of perched leachate zones using a one-dimensional (1D) mathematical model. The model allows for the simulation of the perco- lation fluxes throughout an MSW landfill based on mass-balance equations. The results showed a different response in terms of flow rates throughout the landfill, highlighting the important role of landfill height in the formation of perched leachate zones. Landfill height influences not only the formation of perched leachate zones but also their extension throughout the body of the landfill