Functionalised Anodised Aluminium Oxide as a Biocidal Agent

In this article, we describe the antimicrobial properties of a new composite based on anodic aluminium oxide (AAO) membranes containing propyl-copper-phosphonate units arranged at a predetermined density inside the AAO channels. The samples were prepared with four concentrations of copper ions and tested as antimicrobial drug on four different strains of Escherichia coli (K12, R2, R3 and R4). For comparison, the same strains were tested with three types of antibiotics using the minimal inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) tests. Moreover, DNA was isolated from the analysed bacteria which was additionally digested with formamidopyrimidine-DNA glycosylase (Fpg) protein from the group of repair glycosases. These enzymes are markers of modified oxidised bases in nucleic acids produced during oxidative stress in cells. Preliminary cellular studies, MIC and MBC tests and digestion with Fpg protein after modification of bacterial DNA suggest that these compounds may have greater potential as antibacterial agents than antibiotics such as ciprofloxacin, bleomycin and cloxacillin. The described composites are highly specific for the analysed model Escherichia coli strains and may be used in the future as new substitutes for commonly used antibiotics in clinical and nosocomial infections in the progressing pandemic era. The results show much stronger antibacterial properties of the functionalised membranes on the action of bacterial membranes in comparison to the antibiotics in the Fpg digestion experiment. This is most likely due to the strong induction of oxidative stress in the cell through the breakdown of the analysed bacterial DNA. We have also observed that the intermolecular distances between the functional units play an important role for the antimicrobial properties of the used material. Hence, we utilised the idea of the 2D solvent to tailor them.     

Synthesis and Biological Evaluation of Small Molecules as Potential Anticancer Multitarget Agents

Twenty-six triazole-based derivatives were designed for targeting both PD-L1 (programmed death receptor ligand 1) and VEGFR-2 (vascular endothelial growth factor receptor 2). These compounds were synthetized and biologically evaluated as multitarget inhibitors of VEGFR-2, PD-L1 and c-Myc proteins. The antiproliferative activity of these molecules on several tumor cell lines (HT-29, A-549, and MCF-7) and on the non-tumor cell line HEK-293 was determined. The effects on the abovementioned biological targets were evaluated for some selected compounds. Compound 23, bearing a p-chlorophenyl group, showed better results than sorafenib in regard to the downregulation of VEGFR-2 and a similar effect to BMS-8 on both PD-L1 and c-Myc proteins. The antiangiogenic and antivascular activities of chloro derivatives were also established by endothelial microtube formation assay on Matrigel^®.     

Establishing In-House Cutoffs of CSF Alzheimer’s Disease Biomarkers for the AT(N) Stratification of the Alzheimer Center Barcelona Cohort

Background: Clinical diagnosis of Alzheimer’s disease (AD) increasingly incorporates CSF biomarkers. However, due to the intrinsic variability of the immunodetection techniques used to measure these biomarkers, establishing in-house cutoffs defining the positivity/negativity of CSF biomarkers is recommended. However, the cutoffs currently published are usually reported by using cross-sectional datasets, not providing evidence about its intrinsic prognostic value when applied to real-world memory clinic cases. Methods: We quantified CSF Aβ1-42, Aβ1-40, t-Tau, and p181Tau with standard INNOTEST^® ELISA and Lumipulse G^® chemiluminescence enzyme immunoassay (CLEIA) performed on the automated Lumipulse G600II. Determination of cutoffs included patients clinically diagnosed with probable Alzheimer’s disease (AD, n = 37) and subjective cognitive decline subjects (SCD, n = 45), cognitively stable for 3 years and with no evidence of brain amyloidosis in 18F-Florbetaben-labeled positron emission tomography (FBB-PET). To compare both methods, a subset of samples for Aβ1-42 (n = 519), t-Tau (n = 399), p181Tau (n = 77), and Aβ1-40 (n = 44) was analyzed. Kappa agreement of single biomarkers and Aβ1-42/Aβ1-40 was evaluated in an independent group of mild cognitive impairment (MCI) and dementia patients (n = 68). Next, established cutoffs were applied to a large real-world cohort of MCI subjects with follow-up data available (n = 647). Results: Cutoff values of Aβ1-42 and t-Tau were higher for CLEIA than for ELISA and similar for p181Tau. Spearman coefficients ranged between 0.81 for Aβ1-40 and 0.96 for p181TAU. Passing–Bablok analysis showed a systematic and proportional difference for all biomarkers but only systematic for Aβ1-40. Bland–Altman analysis showed an average difference between methods in favor of CLEIA. Kappa agreement for single biomarkers was good but lower for the Aβ1-42/Aβ1-40 ratio. Using the calculated cutoffs, we were able to stratify MCI subjects into four AT(N) categories. Kaplan–Meier analyses of AT(N) categories demonstrated gradual and differential dementia conversion rates (p = 9.815⁻²⁷). Multivariate Cox proportional hazard models corroborated these findings, demonstrating that the proposed AT(N) classifier has prognostic value. AT(N) categories are only modestly influenced by other known factors associated with disease progression. Conclusions: We established CLEIA and ELISA internal cutoffs to discriminate AD patients from amyloid-negative SCD individuals. The results obtained by both methods are not interchangeable but show good agreement. CLEIA is a good and faster alternative to manual ELISA for providing AT(N) classification of our patients. AT(N) categories have an impact on disease progression. AT(N) classifiers increase the certainty of the MCI prognosis, which can be instrumental in managing real-world MCI subjects.     

Spanish Melon Landraces: Revealing Useful Diversity by Genomic,Morphological, and Metabolomic Analysis

Spain is a secondary centre of the diversification of the melon (Cucumis melo L.), with high diversity represented in highly appreciated landraces belonging to the Flexuosus and Ibericus groups. A collection of 47 accessions of Flexuosus, Chate, Piel de Sapo, Tendral, Amarillo, Blanco, and Rochet was analysed using a genotyping-by-sequencing (GBS) approach. A total of 66,971 quality SNPs were identified. Genetic analysis differentiated Ibericus accessions and exotic materials (Ameri, Momordica, Kachri, and Agrestis), while Flexuous accessions shared ancestry between them. Within the Ibericus group, no clear genomic distinction could be identified for the different landraces evaluated, with accessions of different landraces showing high genetic similarity. The morphological characterization confirmed that the external colour and fruit shape had been used as recognition patterns for Spanish melon landraces, but variability within a landrace exists. Differences were found in the sugars and acid and volatile profiles of the materials. Flexuosus and Chate melons at the immature commercial stage accumulated malic acid and low levels of hexoses, while Ibericus melons accumulated high contents of sucrose and citric acid. Specific trends could be identified in the Ibericus landraces. Tendral accumulated low levels of sugars and citric acid and high of malic acid, maintaining higher firmness, Rochet reached higher levels of sugars, and Amarillo tended to lower malic acid contents. Interestingly, high variability was found within landraces for the acidic profile, offering possibilities to alter taste tinges. The main volatile organic compounds (VOCs) in Flexuosus and Chate were aldehydes and alcohols, with clear differences between both groups. In the Ibericus landraces, general trends for VOC accumulation could be identified, but, again, a high level of variation exists. This situation highlights the necessity to develop depuration programs to promote on-farm in situ conservation and, at the same time, offers opportunities to establish new breeding program targets and to take advantage of these sources of variation.     

Pituitary Tumor-Transforming Gene 1/Delta like Non-Canonical Notch Ligand 1 Signaling in Chronic Liver Diseases

The management of chronic liver diseases (CLDs) remains a challenge, and identifying effective treatments is a major unmet medical need. In the current review we focus on the pituitary tumor transforming gene (PTTG1)/delta like non-canonical notch ligand 1 (DLK1) axis as a potential therapeutic target to attenuate the progression of these pathological conditions. PTTG1 is a proto-oncogene involved in proliferation and metabolism. PTTG1 expression has been related to inflammation, angiogenesis, and fibrogenesis in cancer and experimental fibrosis. On the other hand, DLK1 has been identified as one of the most abundantly expressed PTTG1 targets in adipose tissue and has shown to contribute to hepatic fibrosis by promoting the activation of hepatic stellate cells. Here, we extensively analyze the increasing amount of information pointing to the PTTG1/DLK1 signaling pathway as an important player in the regulation of these disturbances. These data prompted us to hypothesize that activation of the PTTG1/DLK1 axis is a key factor upregulating the tissue remodeling mechanisms characteristic of CLDs. Therefore, disruption of this signaling pathway could be useful in the therapeutic management of CLDs.     

A Systematic Study of Restorative Crown-Materials Combinations for Dental Implants: Characterization of Mechanical Properties under Dynamic Loads

This study aimed to find the optimum mechanical characteristics of the restorative materials for the manufacture of implant crowns subjected to impact loading when different combinations of materials are used for the inner and outer crown. Several combinations of external–internal crown restorative materials were analyzed. The dynamic stresses at eight different zones of a dental implant subjected to an impact load and the influence of several mechanical properties, such as the Young’s modulus, Poisson’s ratio, density, and initial velocity, were analyzed and compared. A detailed 3D model was created, including the crown, the retention screw, the implant, and a mandible section. The model was then built by importing the 3D geometries from CAD software. The whole 3D model was carefully created in order to guarantee a finite element mesh that produced results adjusted to physical reality. Then, we conducted a numerical simulation using the finite element method (FEM). The results of the FEM analysis allowed for evaluating the effect that different combinations of restorative materials and mechanical properties had on the stress distribution in various regions of the implant. The choice of restorative material is a factor to be considered in order to preserve the integrity of osseointegration. Restorative materials transfer more or less stress to the dental implant and surrounding bone, depending on their stiffness. Therefore, an inadequate Young’s modulus of the rehabilitation material can affect the survival of the implant over time. Eight interactive graphics were provided on a web-based surface platform to help clinical dentists, researchers, and manufacturers to select the best restorative materials combination for the crown.     

Removal of an Azo Dye from Wastewater through the Use of Two Technologies: Magnetic Cyclodextrin Polymers and Pulsed Light

Water pollution by dyes is a huge environmental problem; there is a necessity to produce new decolorization methods that are effective, cost-attractive, and acceptable in industrial use. Magnetic cyclodextrin polymers offer the advantage of easy separation from the dye solution. In this work, the β-CD-EPI-magnetic (β-cyclodextrin-epichlorohydrin) polymer was synthesized, characterized, and tested for removal of the azo dye Direct Red 83:1 from water, and the fraction of non-adsorbed dye was degraded by an advanced oxidation process. The polymer was characterized in terms of the particle size distribution and surface morphology (FE-SEM), elemental analysis (EA), differential scanning calorimetry (DSC), thermal gravimetric analysis (TGA), infrared spectrophotometry (IR), and X-ray powder diffraction (XRD). The reported results hint that 0.5 g and pH 5.0 were the best conditions to carry out both kinetic and isotherm models. A 30 min contact time was needed to reach equilibrium with a qmax of 32.0 mg/g. The results indicated that the pseudo-second-order and intraparticle diffusion models were involved in the assembly of Direct Red 83:1 onto the magnetic adsorbent. Regarding the isotherms discussed, the Freundlich model correctly reproduced the experimental data so that adsorption was confirmed to take place onto heterogeneous surfaces. The calculation of the thermodynamic parameters further demonstrates the spontaneous character of the adsorption phenomena (ΔG° = −27,556.9 J/mol) and endothermic phenomena (ΔH° = 8757.1 J/mol) at 25 °C. Furthermore, a good reusability of the polymer was evidenced after six cycles of regeneration, with a negligible decline in the adsorption extent (10%) regarding its initial capacity. Finally, the residual dye in solution after treatment with magnetic adsorbents was degraded by using an advanced oxidation process (AOP) with pulsed light and hydrogen peroxide (343 mg/L); >90% of the dye was degraded after receiving a fluence of 118 J/cm²; the discoloration followed a pseudo first-order kinetics where the degradation rate was 0.0196 cm²/J. The newly synthesized β-CD-EPI-magnetic polymer exhibited good adsorption properties and separability from water which, when complemented with a pulsed light-AOP, may offer a good alternative to remove dyes such as Direct Red 83:1 from water. It allows for the reuse of both the polymer and the dye in the dyeing process.     

Light Spectral Composition Modifies Polyamine Metabolism in Young Wheat Plants

Although light-emitting diode (LED) technology has extended the research on targeted photomorphogenic, physiological, and biochemical responses in plants, there is not enough direct information about how light affects polyamine metabolism. In this study, the effect of three spectral compositions (referred to by their most typical characteristic: blue, red, and the combination of blue and red [pink] lights) on polyamine metabolism was compared to those obtained under white light conditions at the same light intensity. Although light quality induced pronounced differences in plant morphology, pigment contents, and the expression of polyamine metabolism-related genes, endogenous polyamine levels did not differ substantially. When exogenous polyamines were applied, their roborative effect were detected under all light conditions, but these beneficial changes were correlated with an increase in polyamine content and polyamine metabolism-related gene expression only under blue light. The effect of the polyamines on leaf gene expression under red light was the opposite, with a decreasing tendency. Results suggest that light quality may optimize plant growth through the adjustment of polyamine metabolism at the gene expression level. Polyamine treatments induced different strategies in fine-tuning of polyamine metabolism, which were induced for optimal plant growth and development under different spectral compositions.     

Learning Structure from Data and Its Application to Ozone Prediction

In this paper we propose an algorithm for structure learning in predictive expert systems based on a probabilistic network representation. The idea is to have the simplest structure (minimum number of links) with acceptable predictive capability. The algorithm starts by building a tree structure based on measuring mutual information between pairs of variables, and then it adds links as necessary to obtain certain predictive performance. We have applied this method for ozone prediction in México City, where the ozone level is used as a global indicator for the air quality in different parts of the city. It is important to predict the ozone level a day, or at least several hours in advance, to reduce the health hazards and industrial losses that occur when the ozone reaches emergency levels. We obtained as a first approximation a tree-structured dependency model for predicting ozone in one part of the city. We observe that even with only three parameters, its estimations are acceptable.A causal network representation and the structure learning techniques produced some very interesting results for the ozone prediction problem. Firstly, we got some insight into the dependence structure of the phenomena. Secondly, we got an indication of which are the important and not so important variables for ozone forecasting. Taking this into account, the measurement and computational costs for ozone prediction could be reduced. And thirdly, we have obtained satisfactory short term ozone predictions based on a small set of the most important parameters.     

VPM: A visual,precise and multilevel metamodeling framework for describing mathematical domains and UML (The Mathematics of Metamodeling is Metamodeling Mathematics)

As UML 2.0 is evolving into a family of languages with individually specified semantics, there is an increasing need for automated and provenly correct model transformations that (i) assure the integration of local views (different diagrams) of the system into a consistent global view, and, (ii) provide a well-founded mapping from UML models to different semantic domains (Petri nets, Kripke automaton, process algebras, etc.) for formal analysis purposes as foreseen, for instance, in submissions for the OMG RFP for Schedulability, Performance and Time. However, such transformations into different semantic domains typically require the deep understanding of the underlying mathematics, which hinders the use of formal specification techniques in industrial applications. In the paper, we propose a multilevel metamodeling technique with precise static and dynamic semantics (based on a refinement calculus and graph transformation) where the structure and operational semantics of mathematical models can be defined in a UML notation without cumbersome mathematical formulae.