Differences in Salmonella Typhimurium infection and excretion among laboratory and field strains of the German cockroach suggest a genomic basis for vector competence.

The German cockroach, Blattella germanica, can be a vector of human enteric bacterial pathogens, including Salmonella enterica serovar Typhimurium (S. Typhimurium). Transmission of such pathogens by cockroaches has largely been considered a passive mechanical process, but recent studies have argued against this dogma by demonstrating bacterial proliferation within the cockroach gut and the necessity of specific bacterial genes for successful transmission in the feces, revealing unappreciated biological complexity in the vector-pathogen relationship between cockroaches and S. Typhimurium. However, the influence of naturally occurring variation among cockroach populations on pathogen infection and dissemination has not been investigated. Thus, this study aimed to examine whether distinct strains of B. germanica exhibit differences in their ability to become infected by and disseminate S. Typhimurium. We performed controlled infections of one long-term laboratory strain and three recently field-collected strains reared under identical conditions, then compared bacterial loads in the body and excreta of individual insects. Separately, we also compared rates of necrophagy, a behavior known to contribute to the horizontal spread of S. Typhimurium among cockroaches. Our data show significant differences in infection susceptibility, pathogen shedding in the excreta, and necrophagy between laboratory and field strains as well as between some field strains. These observations represent the first evidence that genomic variation among cockroach populations may influence their ability to become infected by and disseminate pathogens, providing further support for the hypothesis that German cockroaches are active biological vectors rather than passive mechanical vectors of S. Typhimurium. Additional studies are needed to identify the genomic drivers of vector competence for S. Typhimurium in B. germanica.

Permeation Flux Prediction of Vacuum Membrane Distillation Using Hybrid Machine Learning Techniques.

Vacuum membrane distillation (VMD) has attracted increasing interest for various applications besides seawater desalination. Experimental testing of membrane technologies such as VMD on a pilot or large scale can be laborious and costly. Machine learning techniques can be a valuable tool for predicting membrane performance on such scales. In this work, a novel hybrid model was developed based on incorporating a spotted hyena optimizer (SHO) with support vector machine (SVR) to predict the flux pressure in VMD. The SVR-SHO hybrid model was validated with experimental data and benchmarked against other machine learning tools such as artificial neural networks (ANNs), classical SVR, and multiple linear regression (MLR). The results show that the SVR-SHO predicted flux pressure with high accuracy with a correlation coefficient (R) of 0.94. However, other models showed a lower prediction accuracy than SVR-SHO with R-values ranging from 0.801 to 0.902. Global sensitivity analysis was applied to interpret the obtained result, revealing that feed temperature was the most influential operating parameter on flux, with a relative importance score of 52.71 compared to 17.69, 17.16, and 14.44 for feed flowrate, vacuum pressure intensity, and feed concentration, respectively.

Compaction Curves and Strength of Clayey Soil Modified with Micro and Nano Silica.

Some Clayey soils are generally categorized as weak soils, and structures lying on such soils have been exposed to severe damage. Therefore, the central thesis of this paper is the impact of a waste material known as a silica fume as nano and micro material on soil's behaviour. To evaluate the effects of those additives on Atterberg limits, compaction characteristics and unconfined compressive strength, clayey soil samples have been transformed using micro and nano silica fume (by-product materials). In the current investigation, silica fume is used at four different percentages: 0, 2, 4, and 7%. The results show that the plasticity index of soil decreases with the addition of micro silica and increases with the addition of nano-silica. Increasing nano silica percentage improves the dry density of the compacted soil and reduces the optimum moisture content. An opposite behavior is observed with adding micro silica to compacted soil. Finally, 4% of silica fume is found to be the optimum dosage to improve the unconfined compressive strength of the treated soil with both additives. As a result, treating the weak clay soil with micro and/or nano-silica fume has the potential to be impactful.