Systemic Inflammation and the Breakdown of Intestinal Homeostasis Are Key Events in Chronic Spinal Cord Injury Patients

Our aim was to investigate the subset distribution and function of circulating monocytes, proinflammatory cytokine levels, gut barrier damage, and bacterial translocation in chronic spinal cord injury (SCI) patients. Thus, 56 SCI patients and 28 healthy donors were studied. The levels of circulating CD14^+highCD16⁻, CD14^+highCD16⁺, and CD14^+lowCD16⁺ monocytes, membrane TLR2, TLR4, and TLR9, phagocytic activity, ROS generation, and intracytoplasmic TNF-α, IL-1, IL-6, and IL-10 after lipopolysaccharide (LPS) stimulation were analyzed by polychromatic flow cytometry. Serum TNF-α, IL-1, IL-6 and IL-10 levels were measured by Luminex and LPS-binding protein (LBP), intestinal fatty acid-binding protein (I-FABP) and zonulin by ELISA. SCI patients had normal monocyte counts and subset distribution. CD14^+highCD16⁻ and CD14^+highCD16⁺ monocytes exhibited decreased TLR4, normal TLR2 and increased TLR9 expression. CD14^+highCD16⁻ monocytes had increased LPS-induced TNF-α but normal IL-1, IL-6, and IL-10 production. Monocytes exhibited defective phagocytosis but normal ROS production. Patients had enhanced serum TNF-α and IL-6 levels, normal IL-1 and IL-10 levels, and increased circulating LBP, I-FABP, and zonulin levels. Chronic SCI patients displayed impaired circulating monocyte function. These patients exhibited a systemic proinflammatory state characterized by enhanced serum TNF-α and IL-6 levels. These patients also had increased bacterial translocation and gut barrier damage.     

Energy Recovery in Pressurized Hydraulic Networks

Water Resources Management - This paper aims to evaluate the possibility of using non-utilized hydraulic energy in urban water distribution systems. For this purpose, the viability and possible...     

The generalized discrete ‐centroid problem

The ‐centroid problem or leader–follower problem is generalized considering different customer choice rules where a customer may use facilities belonging to different firms, if the difference in travel distance (or time) is small enough. Assuming essential goods, some particular customer choice rules are analyzed. Linear programming formulations for the generalized ‐medianoid and ‐centroid problems are presented and an exact solution approach is applied. Some computational examples are included.     

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.     

Demonstration of a tool for automatic learning and re-use of knowledge in the activated sludge process.

Wastewater treatment plant operators encounter complex operational problems related to the activated sludge process and usually respond to these by applying their own intuition and by taking advantage of what they have learnt from past experiences of similar problems. However, previous process experiences are not easy to integrate in numerical control, and new tools must be developed to enable re-use of plant operating experience. The aim of this paper is to investigate the usefulness of a case-based reasoning (CBR) approach to apply learning and re-use of knowledge gained during past incidents to confront actual complex problems through the IWA/COST Benchmark protocol. A case study shows that the proposed CBR system achieves a significant improvement of the benchmark plant performance when facing a high-flow event disturbance.     

Mining statistically significant associations for exploratory analysis of human sleep data.

We introduce a specialized association rule mining technique that can extract patterns from complex sleep data comprising polysomnographic recordings, clinical summaries, and sleep questionnaire responses. The rules mined can describe associations among temporally annotated events and questionnaire or summary data; e.g., the likelihood that an occurrence of a rapid eye movement (REM) sleep stage during the second 100 sleep epochs of the night is associated with moderate caffeine intake. We use chi2 analysis to ensure statistical significance of the mined rules at the level P < 0.05. Our results, obtained by mining sleep-related data from 242 human subjects, reveal clinically interesting associations among the polysomnographic and summary variables. Our experience suggests that association mining may also be useful for selection of variables prior to using logistic regression.