Roles of the Unsaturated Fatty Acid Docosahexaenoic Acid in the Central Nervous System: Molecular and Cellular Insights

Fatty acids (FAs) are essential components of the central nervous system (CNS), where they exert multiple roles in health and disease. Among the FAs, docosahexaenoic acid (DHA) has been widely recognized as a key molecule for neuronal function and cell signaling. Despite its relevance, the molecular pathways underlying the beneficial effects of DHA on the cells of the CNS are still unclear. Here, we summarize and discuss the molecular mechanisms underlying the actions of DHA in neural cells with a special focus on processes of survival, morphological development, and synaptic maturation. In addition, we examine the evidence supporting a potential therapeutic role of DHA against CNS tumor diseases and tumorigenesis. The current results suggest that DHA exerts its actions on neural cells mainly through the modulation of signaling cascades involving the activation of diverse types of receptors. In addition, we found evidence connecting brain DHA and ω-3 PUFA levels with CNS diseases, such as depression, autism spectrum disorders, obesity, and neurodegenerative diseases. In the context of cancer, the existing data have shown that DHA exerts positive actions as a coadjuvant in antitumoral therapy. Although many questions in the field remain only partially resolved, we hope that future research may soon define specific pathways and receptor systems involved in the beneficial effects of DHA in cells of the CNS, opening new avenues for innovative therapeutic strategies for CNS diseases.     

Distinct Tomato Cultivars Are Characterized by a Differential Pattern of Biochemical Responses to Drought Stress

Future climate scenarios suggest that crop plants will experience environmental changes capable of affecting their productivity. Among the most harmful environmental stresses is drought, defined as a total or partial lack of water availability. It is essential to study and understand both the damage caused by drought on crop plants and the mechanisms implemented to tolerate the stress. In this study, we focused on four cultivars of tomato, an economically important crop in the Mediterranean basin. We investigated the biochemical mechanisms of plant defense against drought by focusing on proteins specifically involved in this stress, such as osmotin, dehydrin, and aquaporin, and on proteins involved in the general stress response, such as HSP70 and cyclophilins. Since sugars are also known to act as osmoprotectants in plant cells, proteins involved in sugar metabolism (such as RuBisCO and sucrose synthase) were also analyzed. The results show crucial differences in biochemical behavior among the selected cultivars and highlight that the most tolerant tomato cultivars adopt quite specific biochemical strategies such as different accumulations of aquaporins and osmotins. The data set also suggests that RuBisCO isoforms and aquaporins can be used as markers of tolerance/susceptibility to drought stress and be used to select tomato cultivars within breeding programs.     

A glucose-specific metric to assess predictors and identify models

In diabetes, the mean square error (MSE) metric is extensively used for assessing glucose prediction methods and identifying glucose models. One limitation of this metric is that, by equally treating errors in hypo-, eu-, and hyperglycemia, it is not able to weight the different clinical impact of errors in these three situations. In this paper, we propose a new cost function, which overcomes this limitation and can be used in place of MSE for several scopes, in particular for assessing the quality of glucose predictors and identifying glucose models. The new metric called glucose-specific MSE (gMSE) modifies MSE with a Clark error grid inspired penalty function, which penalizes overestimation in hypoglycemia and underestimation in hyperglycemia, i.e., the most harmful conditions on a clinical perspective. From a mathematical point of view, gMSE retains sensitivity of MSE and inherits some of its important mathematical features, in particular it has no local minima, simplifying the optimization. This makes it suitable for model identification purposes also. First, the goodness of it is demonstrated by means of three experiments, designed ad hoc to evidence its sensitivity to accuracy, precision, and distortion in glucose predictions. Second, a prediction assessment problem is presented, in which two real prediction profiles are compared. Results show that the MSE chooses the worst clinical situation, while gMSE correctly selects the situation with less clinical risk. Finally, we also demonstrate that models identified minimizing gMSE are more accurate in potentially harmful situations (hypo- and hyperglycemia) than those obtained by MSE.     

Winds are from Venus, mountains are from Mars: Science fiction in chemical engineering education

In an elective course recently created at Simón Bolívar University, Chemical Engineering students are encouraged to apply their previously acquired knowledge of thermodynamics, transport phenomena and other core subjects to the analysis and solution of problems drawn from science fiction works. We present a brief outline of the course contents, and describe two case studies that illustrate the general approach. The first example deals with the sublimation of carbon dioxide in Mars, and provides the basis for a discussion of the thermodynamics of phase transitions, the differences between water ice and dry ice, and the phenomenon of surface melting. The second example involves the thermal separation of strong winds in Venus, and is used to develop a simplified model of the Ranque–Hilsch vortex tube that helps understand its working principles, limitations and differences with the equivalent but physically impossible action of Maxwell's demon. In both cases, the science fiction narratives are concluded to be unrealistic, either theoretically unsound or based on inaccurate information.     

A quantitative evalution of the photocatalytic performance of TiO2 slurries

This paper reports the results of a comparison between two TiO₂ photocatalysts that differ for particle size and absorption/scattering optical properties. The catalyst with larger particles and lower surface area performed better in the degradation of phenol than the specimen with smaller particles and larger surface area. Following carefully designed experiments, it is possible to assess the relative role of light absorption/scattering properties and catalyst-related efficiency by means of a basic kinetic model for the rate of photocatalytic reactions. Explicit relationships are derived in the framework of the steady-state approximation for the quantum yield as a function of one a-dimensional number collecting surface kinetic constants for charge carrier reactions at the interface, absorbed light and surface substrate concentrations. The dimensionality change to volume-defined quantities allows derivation of the explicit dependence of the quantum yield on substrate concentration and partition constants, catalyst concentration, and the rate of volumetric light absorption. Following this approach, the rate expression for slurry systems, valid in the absence of back reactions, is directly derived. Some further simplification of the rate equation for the case of low quantum yield regime leads to analytical relationships able to account for the dependence of the rate on catalyst concentration and absorbed light in the case of stirred and unstirred conditions. The reported properly designed experiments allow the estimation of catalyst-specific micro-kinetic constants.     

Synthesis,characterization and evaluation of phosphorylated resins in the removal of Pb<Superscript>2+</Superscript> from aqueous solutions

Phosphinic-derivative poly(styrene-co-divinylbenzene)-based on PS–DVB copolymers with different porosity degrees have been prepared by aromatic electrophilic substitution reaction using PCl₃/AlCl₃ followed by base-promoted hydrolysis. The phosphorylation reaction was analyzed by infra-red spectroscopy (FTIR), scanning electron microscopy (SEM), and thermogravimetry (TG/DTG). In addition, the phosphorous content of the phosphorylated copolymers was determined by spectrophotometry using the method based on sodium molybdate reactant so that the extension of that modification could be assessed. The performance of the phosphorylated resins in the extraction of Pb²⁺ from aqueous solutions in a batch system was also evaluated. The Pb²⁺ content was determined by atomic absorption spectrometry (AAS). These materials presented excellent extraction capacity under the contact time of 30 min and pH 6.     

A framework for analytical cost estimation of mechanical components based on manufacturing knowledge representation

This paper presents a novel framework for manufacturing and cost-related knowledge formalization. This artefact allows industries to capitalize the knowled     

A quantitative study of air-borne particulate matter collected on membrane filters by means of X-ray photoelectron spectroscopy

The capability of X-ray photoelectron spectroscopy, XPS or ESCA, in analysing oxidation states and measuring the concentration of elements present in air pollution particulates collected on membrane filters is evaluated. Semi-quantitative data are compared with those from XRF and wet chemical analysis. Differences of about a factor of 2.0–2.5 are found which are critically discussed in relation to particle size and the distribution of ionic species. The importance of intrinsic properties of matrix materials and instrumental factors is also discussed.     

Quantitative analysis of workflow, temporary structure usage, and productivity using 4D models

This paper presents time–space analyses of construction operations supported by quantitative information extracted from 4D CAD models. The application of 4D models is a promising approach to help introduce construction innovations and to evaluate construction alternatives. Current analyses of 4D models are mainly visual and provide project stakeholders with a clear, but limited, insight of construction planning information. This practice does not take advantage of the quantitative data contained in 4D models. We use two 4D models of an industry test case to illustrate how to analyze, compare, and present 4D content quantitatively (i.e., workspace areas, work locations, and distances between concurrent activities). This paper shows how different types of 4D content can be extracted from 4D models to support 4D-content-based analyses and novel presentation of construction planning information. We suggest further research aimed at formalizing the contents in 4D models to enable comparative quantitative analyses of construction planning alternatives. Formalized 4D content can enable the development of reasoning mechanisms that automate 4D-model-based analyses and provide the data content for presentations of construction planning information.