Novel Approach for a Controlled Delivery of Essential Oils during Long-Term Maize Storage: Clove Bud and Pennyroyal Oils Efficacy to Control Sitophilus zeamais, Reducing Grain Damage and Post-Harvest Losses.

Maize grains represent a significant contribution for assuring food safety all over the globe. Sitophilus zeamais (Motschulsky) (Coleoptera: Curculionidae), also known as the maize weevil, is one of the most destructive pests in stored maize, causing qualitative and quantitative losses. To control S. zeamais populations in maize storage sites, synthetical chemical insecticides are applied. However, these are often used wastefully, have environmental implications, and can induce the development of resistant populations. In this work, the insecticidal and grain protecting efficacy of an innovative macro-capsule delivery device, loaded with essential oils from Clove bud and Pennyroyal, as well as their combined solutions, was tested against naturally S. zeamais-infested maize grains. The blend of both compounds incorporated in a controlled release device reduced losses by more than 45% over a long storage period of twenty weeks, diminishing the survivability of maize weevils by over 90%. The usage of the blend at a concentration of 370 µL⋅Lair-1 with an antioxidant showed the best results, however, by halving the concentration (185 µL⋅Lair-1), a significant control of S. zeamais populations was still achieved.

Increased Intraspecies Diversity in Escherichia coli Biofilms Promotes Cellular Growth at the Expense of Matrix Production.

Intraspecies diversity in biofilm communities is associated with enhanced survival and growth of the individual biofilm populations. Studies on the subject are scarce, namely, when more than three strains are present. Hence, in this study, the influence of intraspecies diversity in biofilm populations composed of up to six different Escherichia coli strains isolated from urine was evaluated in conditions mimicking the ones observed in urinary tract infections and catheter-associated urinary tract infections. In general, with the increasing number of strains in a biofilm, an increase in cell cultivability and a decrease in matrix production were observed. For instance, single-strain biofilms produced an average of 73.1 µg·cm-2 of extracellular polymeric substances (EPS), while six strains biofilms produced 19.9 µg·cm-2. Hence, it appears that increased genotypic diversity in a biofilm leads E. coli to direct energy towards the production of its offspring, in detriment of the production of public goods (i.e., matrix components). Apart from ecological implications, these results can be explored as another strategy to reduce the biofilm burden, as a decrease in EPS matrix production may render these intraspecies biofilms more sensitive to antimicrobial agents.

Modelling biochemical networks with intrinsic time delays: a hybrid semi-parametric approach.

BACKGROUND: This paper presents a method for modelling dynamical biochemical networks with intrinsic time delays. Since the fundamental mechanisms leading to such delays are many times unknown, non conventional modelling approaches become necessary. Herein, a hybrid semi-parametric identification methodology is proposed in which discrete time series are incorporated into fundamental material balance models. This integration results in hybrid delay differential equations which can be applied to identify unknown cellular dynamics. RESULTS: The proposed hybrid modelling methodology was evaluated using two case studies. The first of these deals with dynamic modelling of transcriptional factor A in mammalian cells. The protein transport from the cytosol to the nucleus introduced a delay that was accounted for by discrete time series formulation. The second case study focused on a simple network with distributed time delays that demonstrated that the discrete time delay formalism has broad applicability to both discrete and distributed delay problems. CONCLUSIONS: Significantly better prediction qualities of the novel hybrid model were obtained when compared to dynamical structures without time delays, being the more distinctive the more significant the underlying system delay is. The identification of the system delays by studies of different discrete modelling delays was enabled by the proposed structure. Further, it was shown that the hybrid discrete delay methodology is not limited to discrete delay systems. The proposed method is a powerful tool to identify time delays in ill-defined biochemical networks.