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The generation of energy from renewable sources is subjected to very dynamic changes in environmental parameters and asset operating conditions. This is a very relevant issue to be considered when developing reliability studies, modeling asset degradation and projecting renewable energy production. To that end, Artificial Neural Network (ANN) models have proven to be a very interesting tool, and there are many relevant and interesting contributions using ANN models, with different purposes, but somehow related to real-time estimation of asset reliability and energy generation. This document provides a precise review of the literature related to the use of ANN when predicting behaviors in energy production for the referred renewable energy sources. Special attention is paid to describe the scope of the different case studies, the specific approaches that were used over time, and the main variables that were considered. Among all contributions, this paper highlights those incorporating intelligence to anticipate reliability problems and to develop ad-hoc advanced maintenance policies. The purpose is to offer the readers an overall picture per energy source, estimating the significance that this tool has achieved over the last years, and identifying the potential of these techniques for future dependability analysis.

A persistent challenge in digital asset management is the lack of standardized models for integrating health assessment—such as the Asset Health Index (AHI)—into Digital Twins, limiting their extended implementation beyond individual projects. Asset managers in the energy sector face challenges of digitalization such as digital environment selection, employed digital modules (absence of an architecture guide) and their interconnection, sources of data, and how to automate the assessment and provide the results in a friendly decision support system. Thus, for energy systems, the integration of Asset Assessment in virtual replicas by Digital Twins is a complete way of asset management by enabling real-time monitoring, predictive maintenance, and lifecycle optimization. Another challenge in this context is how to compound in a structured assessment of asset condition, where the Asset Health Index (AHI) plays a critical role by consolidating heterogeneous data into a single, actionable indicator easy to interpret as a level of risk. This paper tries to serve as a guide against these digital and structured assessments to integrate AHI methodologies into Digital Twins for energy converters. First, the proposed AHI methodology is introduced, and after a structured data model specifically designed, orientated to a basic and economic cloud implementation architecture. This model has been developed fulfilling standardized practices of asset digitalization as the Reference Architecture Model for Industry 4.0 (RAMI 4.0), organizing asset-related information into interoperable domains including physical hierarchy, operational monitoring, reliability assessment, and risk-based decision-making. A Unified Modeling Language (UML) class diagram formalizes the data model for cloud Digital Twin implementation, which is deployed on Microsoft Azure Architecture using native Internet of Things (IoT) and analytics services to enable automated and real-time AHI calculation. This design and development has been realized from a scalable point of view and for future integration of Machine-Learning improvements. The proposed approach is validated through a case study involving three high-capacity converters in distinct operating environments, showing the model’s effective assistance in anticipating failures, optimizing maintenance strategies, and improving asset resilience. In the case study, AHI-based monitoring reduced unplanned failures by 43% and improved maintenance planning accuracy by over 30%.

In the context of energy storage systems, optimizing the life cycle of power converters is crucial for reducing costs, making informed decisions, and ensuring sustainability. This study presents a comprehensive methodology for calculating the life cycle cost (LCC) of power converters, employing a nine-step process that integrates digitalization, Internet of Things (IoT) technologies, and the Asset Health Index (AHI). The methodology adapts the Woodward model to provide a detailed cost analysis, encompassing the acquisition, operation, maintenance, and end-of-life phases. Our findings reveal significant insights into asset management, highlighting the importance of preventive and major maintenance in controlling failure rates and extending asset life. This study concludes that adopting sustainable business models and leveraging advanced technologies can enhance the reliability and maintainability of power converters, ultimately leading to more competitive and environmentally friendly energy storage solutions.

Protein kinase C (PKC) comprises a family of highly related serine/threonine protein kinases involved in multiple signaling pathways, which control cell proliferation, survival, and differentiation. The role of PKCα in cancer has been studied for many years. However, it has been impossible to establish whether PKCα acts as an oncogene or a tumor suppressor. Here, we analyzed the importance of PKCα in cellular processes such as proliferation, migration, or apoptosis by inhibiting its gene expression in a luminal A breast cancer cell line (MCF-7). Differential expression analysis and phospho-kinase arrays of PKCα-KD vs. PKCα-WT MCF-7 cells identified an essential set of proteins and oncogenic kinases of the JAK/STAT and PI3K/AKT pathways that were down-regulated, whereas IGF1R, ERK1/2, and p53 were up-regulated. In addition, unexpected genes related to the interferon pathway appeared down-regulated, while PLC, ERBB4, or PDGFA displayed up-regulated. The integration of this information clearly showed us the usefulness of inhibiting a multifunctional kinase-like PKCα in the first step to control the tumor phenotype. Then allowing us to design a possible selection of specific inhibitors for the unexpected up-regulated pathways to further provide a second step of treatment to inhibit the proliferation and migration of MCF-7 cells. The results of this study suggest that PKCα plays an oncogenic role in this type of breast cancer model. In addition, it reveals the signaling mode of PKCα at both gene expression and kinase activation. In this way, a wide range of proteins can implement a new strategy to fine-tune the control of crucial functions in these cells and pave the way for designing targeted cancer therapies.

Proteins containing C2 domains are the sensors for Ca(2+) and PI(4,5)P2 in a myriad of secretory pathways. Here, the use of a free-mounting system has enabled us to capture an intermediate state of Ca(2+) binding to the C2A domain of rabphilin 3A that suggests a different mechanism of ion interaction. We have also determined the structure of this domain in complex with PI(4,5)P2 and IP3 at resolutions of 1.75 and 1.9 Å, respectively, unveiling that the polybasic cluster formed by strands β3-β4 is involved in the interaction with the phosphoinositides. A comparative study demonstrates that the C2A domain is highly specific for PI(4,5)P2/PI(3,4,5)P3, whereas the C2B domain cannot discriminate among any of the diphosphorylated forms. Structural comparisons between C2A domains of rabphilin 3A and synaptotagmin 1 indicated the presence of a key glutamic residue in the polybasic cluster of synaptotagmin 1 that abolishes the interaction with PI(4,5)P2. Together, these results provide a structural explanation for the ability of different C2 domains to pull plasma and vesicle membranes close together in a Ca(2+)-dependent manner and reveal how this family of proteins can use subtle structural changes to modulate their sensitivity and specificity to various cellular signals.

In the early 1970s, the existence of a “lipid annulus” stably surrounding the individual intrinsic protein molecules was proposed by several authors. They referred to a number of lipid molecules in slow exchange with the bulk lipid in the bilayer, i.e., more or less protein-bound, and more ordered than the bulk lipid. The annular lipids would control enzyme activity. This idea was uncritically accepted by most scientists working with intrinsic membrane proteins at the time, so that the idea operated like a myth in the field. However, in the following decade, hard spectroscopic and biochemical evidence showed that the proposed annular lipids were not immobilized for a sufficiently long time to influence enzyme or transporter activity, nor were they ordered by the protein. Surprisingly, forty years later, the myth survives, and the term ‘annular lipid’ is still in use, in a different, but even more illogical sense.

Clotrimazole (1-[(2-chlorophenyl)-diphenylmethyl]-imidazole) is an azole antifungal drug belonging to the imidazole subclass that is widely used in pharmacology and that can be incorporated in membranes. We studied its interaction with 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC) phospholipid vesicles by using differential scanning calorimetry and found that the transition temperature decreases progressively as the concentration of clotrimazole increases. However, the temperature of completion of the transition remained constant despite the increase of clotrimazole concentration, suggesting the formation of fluid immiscibility. 1H-NMR and 1H NOESY MAS-NMR were employed to investigate the location of clotrimazole in 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) phospholipid membranes. In the presence of clotrimazole, all the resonances originating from POPC were shifted upfield, but mainly those corresponding to C2 and C3 of the fatty acyl, chains suggesting that clotrimazole aromatic rings preferentially locate near these carbons. In the same way, 2D-NOESY measurements showed that the highest cross-relaxation rates between protons of clotrimazole and POPC were with those bound to the C2 and C3 carbons of the fatty acyl chains. Molecular dynamics simulations indicated that clotrimazole is located near the top of the hydrocarbon-chain phase, with the nitrogen atoms of the imidazole ring of clotrimazole being closest to the polar group of the carbonyl moiety. These results are in close agreement with the NMR and the conclusion is that clotrimazole is located near the water–lipid interface and in the upper part of the hydrophobic bilayer.

Morphine is thoroughly used for pain control; however, it has a high addictive potential. Opioid liposome formulations produce controlled drug release and have been thoroughly tested for pain treatment although their role in addiction is still unknown. This study investigated the effects of free morphine and morphine encapsulated in unilamellar and multilamellar liposomes on antinociception and on the expression and extinction of the positive and negative memories associated with environmental cues. The hot plate test was used to measure central pain. The rewarding effects of morphine were analyzed by the conditioned-place preference (CPP) test, and the aversive aspects of naloxone-precipitated morphine withdrawal were evaluated by the conditioned-place aversion (CPA) paradigm. Our results show that encapsulated morphine yields prolonged antinociceptive effects compared with the free form, and that CPP and CPA expression were similar in the free- or encapsulated-morphine groups. However, we demonstrate, for the first time, that morphine encapsulation reduces the duration of reward and aversive memories, suggesting that this technological process could transform morphine into a potentially less addictive drug. Morphine encapsulation in liposomes could represent a pharmacological approach for enhancing extinction, which might lead to effective clinical treatments in drug addiction with fewer side effects.

The C2 domain of PKCα (C2α) induces fluorescence self-quenching of NBD-PS in the presence of Ca2+, which is interpreted as the demixing of phosphatidylserine from a mixture of this phospholipid with phosphatidylcholine. Self-quenching of NBD-PS was considerably increased when phosphatidylinositol-4,5-bisphosphate (PIP2) was present in the membrane. When PIP2 was the labeled phospholipid, in the form of TopFluor-PIP2, fluorescence self-quenching induced by the C2 domain was also observed, but this was dependent on the presence of phosphatidylserine. An independent indication of the phospholipid demixing effect given by the C2α domain was obtained by using 2H-NMR, since a shift of the transition temperature of deuterated phosphatidylcholine was observed as a consequence of the addition of the C2α domain, but only in the presence of PIP2. The demixing induced by the C2α domain may have a physiological significance since it means that the binding of PKCα to membranes is accompanied by the formation of domains enriched in activating lipids, like phosphatidylserine and PIP2. The formation of these domains may enhance the activation of the enzyme when it binds to membranes containing phosphatidylserine and PIP2.

The C2 domain of PKCα possesses two different binding sites, one for Ca(2+) and phosphatidylserine and a second one that binds PIP2 with very high affinity. The enzymatic activity of PKCα was studied by activating it with large unilamellar lipid vesicles, varying the concentration of Ca(2+) and the contents of dioleylglycerol (DOG), phosphatidylinositol 4,5-bisphosphate (PIP2) and phosphadidylserine (POPS) in these model membranes. The results showed that PIP2 increased the Vmax of PKCα and, when the PIP2 concentration was 5 mol% of the total lipid in the membrane, the addition of 2 mol% of DOG did not increase the activity. In addition PIP2 decreases K0.5 of Ca(2+) more than 3-fold, that of DOG almost 5-fold and that of POPS by a half. The K0.5 values of PIP2 amounted to only 0.11 µM in the presence of DOG and 0.39 in its absence, which is within the expected physiological range for the inner monolayer of a mammalian plasma membrane. As a consequence, PKCα may be expected to operate near its maximum capacity even in the absence of a cell signal producing diacylglycerol. Nevertheless, we have shown that the presence of DOG may also help, since the K0.5 for PIP2 notably decreases in its presence. Taken together, these results underline the great importance of PIP2 in the activation of PKCα and demonstrate that in its presence, the most important cell signal for triggering the activity of this enzyme is the increase in the concentration of cytoplasmic Ca(2+).