The Diagnostic Potential of Amyloidogenic Proteins

Neurodegenerative disorders are a highly prevalent class of diseases, whose pathological mechanisms start before the appearance of any clear symptoms. This fact has prompted scientists to search for biomarkers that could aid early treatment. These currently incurable pathologies share the presence of aberrant aggregates called amyloids in the nervous system, which are composed of specific proteins. In this review, we discuss how these proteins, their conformations and modifications could be exploited as biomarkers for diagnostic purposes. We focus on proteins that are associated with the most prevalent neurodegenerative disorders, including Alzheimer’s and Parkinson’s diseases, amyotrophic lateral sclerosis, and frontotemporal dementia. We also describe current challenges in detection, the most recent techniques with diagnostic potentials and possible future developments in diagnosis.     

Effect of ball milling on the mechanical properties and crystallization of graphene nanoplatelets reinforced short chain branched-polyethylene

Short-chain-branched-polyethylene (SCB-PE) is extensively used in domestic hot and cold piping systems. SCB-PE nanocomposites using graphene nanoplatelets (GNPs) as a filler, were prepared in this work. The effect of ball-milling as a premixing technique prior to melt-mixing, on the crystallization and the nanomechanical properties of the composites has been studied. Two sets of SCB-PE/GNPs nanocomposites with various filler loadings were prepared; one with and one without the ball-milling step. The dispersion of the filler was evaluated by optical microscopy while the crystallization process was studied using differential scanning calorimetry. The nonisothermal crystallization's experimental data were analyzed using various methods. The materials' nanomechanical behavior was investigated by conducting nanoindentation tests. A finite element analysis process was developed to extract the composites' stress–strain behavior. The composites prepared with ball-milling presented improved dispersion of GNPs in the SCB-PE matrix, which affected the crystallization, while nanoindentation tests showed significantly enhanced mechanical properties.     

Structure of the O-Antigen and the Lipid A from the Lipopolysaccharide of Fusobacterium nucleatum ATCC 51191

Fusobacterium nucleatum is a common member of the oral microbiota. However, this symbiont has been found to play an active role in disease development. As a Gram-negative bacterium, F. nucleatum has a protective outer membrane layer whose external leaflet is mainly composed of lipopolysaccharides (LPSs). LPSs play a crucial role in the interaction between bacteria and the host immune system. Here, we characterised the structure of the O-antigen and lipid A from F. nucleatum ssp. animalis ATCC 51191 by using a combination of GC-MS, MALDI and NMR techniques. The results revealed a novel repeat of the O-antigen structure of the LPS, [→4)-β-d -GlcpNAcA-(1→4)-β-d -GlcpNAc3NAlaA-(1→3)-α-d -FucpNAc4NR-(1→], (R=acetylated 60 %), and a bis-phosphorylated hexa-acylated lipid A moiety. Taken together these data showed that F. nucleatum ATCC 51191 has a distinct LPS which might differentially influence recognition by immune cells.     

Optimized placement of virtualized resources for 5G services exploiting live migration

This paper focuses on a Centralized Radio Access Network solution adopting the concept of resource disaggregation. In this context, it proposes a heuristic suitable to optimally assign Base Band Unit processing functions in softwarized Radio Access Networks to different servers, taking into consideration their processing requirements with the aim to minimize the overall energy consumption. It also proposes the adoption of live migration of virtualized resources, in order to dynamically reallocate these functions to different servers that better match the continuously changing characteristics of 5G services, for increased energy efficiency purposes. The benefits associated with live migration are quantified through a series of experiments. Our results show a reduction of the number of switched-on servers through live migration that leads to a notable improvement in terms of resource and energy efficiency.

     

Isolation of antimicrobial compounds from aniseed and techno-economic feasibility report for industrial-scale application

This work evaluates the antimicrobial activity of the fractionated aqueous extract obtained from the aerial parts of aniseed. Fifteen fractions were collected by column chromatography using ethanol and water as mobile phases. All fractions were tested as potential antimicrobial agents against three common food-spoilage microorganisms: a yeast (Saccharomyces cerevisiae), a mold (Aspergillus awamori) and a bacterium (Lactobacillus delbrueckii subsp. bulgaricus). Fraction 2 exhibited the highest antimicrobial activity in both types of susceptibility test, and therefore, it was further studied for the identification of bioactive compounds. GC-MS analysis of Fraction 2 revealed the presence of threo-Anethole glycol. Based on laboratory-scale experiments, a process flowsheet for potential industrial-scale application is proposed combined with a techno-economic feasibility report. Fraction 2 with the detected compound threo-Anethole glycol showed promising results encouraging the attempts for industrial-scale application of antimicrobial compounds produced from aniseed.     

Development of Deep Learning Models for Predicting the Effects of Exposure to Engineered Nanomaterials on Daphnia magna

This study presents the results of applying deep learning methodologies within the ecotoxicology field, with the objective of training predictive models that can support hazard assessment and eventually the design of safer engineered nanomaterials (ENMs). A workflow applying two different deep learning architectures on microscopic images of Daphnia magna is proposed that can automatically detect possible malformations, such as effects on the length of the tail, and the overall size, and uncommon lipid concentrations and lipid deposit shapes, which are due to direct or parental exposure to ENMs. Next, classification models assign specific objects (heart, abdomen/claw) to classes that depend on lipid densities and compare the results with controls. The models are statistically validated in terms of their prediction accuracy on external D. magna images and illustrate that deep learning technologies can be useful in the nanoinformatics field, because they can automate time‐consuming manual procedures, accelerate the investigation of adverse effects of ENMs, and facilitate the process of designing safer nanostructures. It may even be possible in the future to predict impacts on subsequent generations from images of parental exposure, reducing the time and cost involved in long‐term reproductive toxicity assays over multiple generations.     

Energy analysis of a low‐temperature heat pump heating system in a single‐family house

Energy costs and environmental concerns have made energy optimisation a viable option for buildings. Energy‐efficient heating systems together with an effective use of buildings thermal mass and tightness have a significant impact on the energy requirement and on the possibility for sizeable running cost savings. In this study we use the simulation tool TRNSYS‐EES to model and analyse the performance of a residential house and the low‐temperature heating system that serves its thermal needs. The building is a single‐family house with controlled ventilation and the chosen heating system is a hydronic floor heating system connected to an exhaust air heat pump. The aim of the simulation is to study the performance of the building, the heating system and the controls in an integrated manner. Overall, the results indicate that the energy efficiency issue implicates system design and system thinking concerns as well as techno‐economic difficulties. The controls and the choice of the operation mode are of a great importance. Copyright © 2004 John Wiley & Sons, Ltd.     

Chemical composition and antioxidant activity of the essential oil of Clinopodium vulgare L.

This study was designed to examine the chemical composition and in vitro antioxidant activity of the essential oil of Clinopodium vulgare. GC–MS analysis of the oil resulted in the identification of 40 compounds, representing 99.4% of the oil; thymol (38.9%), γ-terpinene (29.6%) and p-cymene (9.1%) were the main components. The samples were subjected to a screening for their possible antioxidant activity by using 2,2-diphenyl-1-picrylhydrazyl (DPPH) and β-carotene-linoleic acid assays. In the first case, IC₅₀ value of the C. vulgare essential oil was determined as 63.0 ± 2.71 μg/ml. IC₅₀ value of thymol and γ-terpinene, the major compounds of the oil, was determined as 161 ± 1.3 μg/ml and 122 ± 2.5 μg/ml, respectively, whereas p-cymene did not show antioxidant activity. In β-carotene-linoleic acid system, C. vulgare essential oil exhibited 52.3 ± 1.19% inhibition against linoleic acid oxidation. In both systems, antioxidant capacities of BHT, curcumine and ascorbic acid were also determined in parallel experiments.     

The in vitro antioxidative properties of the essential oils and methanol extracts of Satureja spicigera (K. Koch.) Boiss. and Satureja cuneifolia ten

This study was designed to examine the in vitro antioxidant activities of the essential oil and methanol extracts of Satureja spicigera and S. cuneifolia from Turkish flora. GC and GC/MS analysis of the essential oils resulted in the identification of 40 and 29 compounds, representing the 99.4% and 99.5% of the oils, respectively. Major constituents of the oils were carvacrol (42.5% and 67.1%), γ-terpinene (21.5% and 15.2%) and p-cymene (20.9% and 6.7%), respectively. Methanol extracts were also obtained from the aerial parts of the plants. The samples were subjected to a screening for their possible antioxidant activities by using 2,2-diphenyl-1-picrylhydrazyl (DPPH) and β-carotene–linoleic acid assays. In general, samples obtained from S. cuneifolia exerted greater antioxidant activities than did those obtained from S. spicigera. In the DPPH test system, free radical-scavenging activity of S. spicigera oil was determined to be 127 ± 1.63 μg/ml, whereas IC₅₀ value of S. cuneifolia was 89.1 ± 2.29 μg/ml. In the β-carotene–linoleic acid test system, antioxidant activities of the oil were 81.7 ± 1.14% and 93.7 ± 1.83%, respectively. Antioxidant activities of the synthetic antioxidant, BHT, ascorbic acid, curcumin and α-tocopherol were also determined in parallel experiments.     

A Radio Resource Management Framework for Multi-User Multi-Cell OFDMA Networks Based on Game Theory

This work proposes a radio resource management framework employing game theoretic concepts for orthogonal frequency division multiple access, the most prevalent multiple access technique for the next generation wireless networks. The subcarrier allocation problem is encountered as a combinatorial auction, where the base station auctions the subcarriers and the users bid for and buy bundles of subcarriers, aiming at minimising their required transmit power. Subsequently, each allocated subcarrier is loaded with a number of bits, decided by each user independently, and the power control process is set up as a non-cooperative game. Each user responds to the interference sensed in his environment and, through a best responses process, the game converges to the unique, Pareto optimal, Nash equilibrium. In order to guarantee convergence, a limit is imposed to the maximum modulation level for each subcarrier. Simulation results show that the auction algorithm follows closely the performance of the optimal algorithm, whereas it is of lower computational complexity and requires less feedback information. Similarly, the proposed distributed bit loading and power control scheme achieves lower transmit power per offered bit rate unit. However, the distributed nature of the algorithm results in lower total offered bit rate, because of the partial knowledge and exploitation of channel state information.