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Abstract The goal of this article is to examine traffic education and its examination system, using a new approach based on the House of Quality method. While every country has its own legal rules and requirements regarding how traffic education and examinations are conducted, there is a direct relationship between traffic education, its examination system and road safety. Therefore the quality of such a complicated process is of great interest for both stakeholders: the authorities and the citizens. These stakeholders both have their own objectives regarding the system, consequently increasing its complexity. This article investigates, as its case study, the system in Hungary. The House of Quality method has been expanded to provide a unique approach to examine the goals and objectives of both stakeholders, revealing similarities and differences and their interrelationships. Secondary data on the effectiveness of the traffic education and examination system are also analysed. Based on the HOQ model representations of the goals and objectives of the stakeholders regarding the traffic education and exam system, it can be established that the stakeholder points of view are closer to each other in the case of the test system than that of the education system. However, there are unsolved contradictions between the stakeholders that have to be handled, as opinions regarding the quality of the service and the criteria of the stakeholders’ satisfaction are very diverse.

It has been known for a long time that epileptic seizures provoke brain neuroinflammation involving the activation of microglial cells. However, the role of these cells in this disease context and the consequences of their inflammatory activation on subsequent neuron network activity remain poorly understood so far. To fill this gap of knowledge and gain a better understanding of the role of microglia in the pathophysiology of epilepsy, we used an established zebrafish Dravet syndrome epilepsy model based on Scn1Lab sodium channel loss-of-function, combined with live microglia and neuronal Ca2+ imaging, local field potential (LFP) recording, and genetic microglia ablation. Data showed that microglial cells in scn1Lab-deficient larvae experiencing epileptiform seizures displayed morphological and biochemical changes characteristic of M1-like pro-inflammatory activation; i.e., reduced branching, amoeboid-like morphology, and marked increase in the number of microglia expressing pro-inflammatory cytokine Il1β. More importantly, LFP recording, Ca2+ imaging, and swimming behavior analysis showed that microglia-depleted scn1Lab-KD larvae displayed an increase in epileptiform seizure-like neuron activation when compared to that seen in scn1Lab-KD individuals with microglia. These findings strongly suggest that despite microglia activation and the synthesis of pro-inflammatory cytokines, these cells provide neuroprotective activities to epileptic neuronal networks, making these cells a promising therapeutic target in epilepsy.

Energy consumption is a significant concern in daily life, often neglected in terms of cost and environmental impact. Since IT networks play an essential role in our daily routines, energy-saving in this area is crucial. However, the implementation of energy efficiency solutions in this field have to ensure that the network performance is minimally affected. Traditional networks encounter difficulties in achieving this goal. Software-Defined Networks (SDN), which have gained popularity in the past decade, offer easy-to-use opportunities to increase energy efficiency. Features like central controllability and quick programmability can help to reduce energy consumption. In this article, a new algorithm named the Modified Heuristic Algorithm for Energy Saving (MHAES) is presented, which was compared to eight commonly used methods in different topologies for energy efficiency. The results indicate that by maintaining an appropriate load balance, one can save more energy than in case of using some other well-known procedures by applying a threshold value based on forecast, keeping only a minimal number of nodes in an active state, and ensuring that nodes not participating in packet transmission remain in sleep mode.

Feature selection is a crucial step in machine learning, aiming to identify the most relevant features in high-dimensional data in order to reduce the computational complexity of model development and improve generalization performance. Ensemble feature-ranking methods combine the results of several feature-selection techniques to identify a subset of the most relevant features for a given task. In many cases, they produce a more comprehensive ranking of features than the individual methods used alone. This paper presents a novel approach to ensemble feature ranking, which uses a weighted average of the individual ranking scores calculated using these individual methods. The optimal weights are determined using a Taguchi-type design of experiments. The proposed methodology significantly improves classification performance on the CSE-CIC-IDS2018 dataset, particularly for attack types where traditional average-based feature-ranking score combinations result in low classification metrics.

Abstract A leading cause of preterm birth is the exposure to systemic inflammation (maternal/fetal infection), which leads to neuroinflammation and white matter injury (WMI). A wide range of cytokines and chemokines are expressed and upregulated in oligodendrocytes (OLs) in response to inflammation and numerous reports show that OLs express several receptors for immune related molecules, which enable them to sense inflammation and to react. However, the role of OL immune response in WMI is unclear. Here, we focus our study on toll-like receptor-3 (TLR3) that is activated by double-strand RNA (dsRNA) and promotes neuroinflammation. Despite its importance, its expression and role in OLs remain unclear. We used an in vivo mouse model, which mimics inflammation-mediated WMI of preterm born infants consisting of intraperitoneal injection of IL-1β from P1 to P5. In the IL-1β-treated animals, we observed the upregulation of Tlr3, IL-1β, IFN-β, Ccl2, and Cxcl10 in both PDGFRα+ and O4+ sorted cells. This upregulation was higher in O4+ immature OLs (immOLs) as compared to PDGFRα+ OL precursor cells (OPCs), suggesting a different sensitivity to neuroinflammation. These observations were confirmed in OL primary cultures: cells treated with TLR3 agonist Poly(I:C) during differentiation showed a stronger upregulation of Ccl2 and Cxcl10 compared to cells treated during proliferation and led to decreased expression of myelin genes. Finally, OLs were able to modulate microglia phenotype and function depending on their maturation state as assessed by qPCR using validated markers for immunomodulatory, proinflammatory, and anti-inflammatory phenotypes and by phagocytosis and morphological analysis. These results show that during inflammation the response of OLs can play an autonomous role in blocking their own differentiation: in addition, the immune activation of OLs may play an important role in shaping the response of microglia during inflammation.

Preterm birth (PTB) represents 15 million births every year worldwide and is frequently associated with maternal/fetal infections and inflammation, inducing neuroinflammation. This neuroinflammation is mediated by microglial cells, which are brain-resident macrophages that release cytotoxic molecules that block oligodendrocyte differentiation, leading to hypomyelination. Some preterm survivors can face lifetime motor and/or cognitive disabilities linked to periventricular white matter injuries (PWMIs). There is currently no recommendation concerning the mode of delivery in the case of PTB and its impact on brain development. Many animal models of induced-PTB based on LPS injections exist, but with a low survival rate. There is a lack of information regarding clinically used pharmacological substances to induce PTB and their consequences on brain development. Mifepristone (RU-486) is a drug used clinically to induce preterm labor. This study aims to elaborate and characterize a new model of induced-PTB and PWMIs by the gestational injection of RU-486 and the perinatal injection of pups with IL-1beta. A RU-486 single subcutaneous (s.c.) injection at embryonic day (E)18.5 induced PTB at E19.5 in pregnant OF1 mice. All pups were born alive and were adopted directly after birth. IL-1beta was injected intraperitoneally from postnatal day (P)1 to P5. Animals exposed to both RU-486 and IL-1beta demonstrated microglial reactivity and subsequent PWMIs. In conclusion, the s.c. administration of RU-486 induced labor within 24 h with a high survival rate for pups. In the context of perinatal inflammation, RU-486 labor induction significantly decreases microglial reactivity in vivo but did not prevent subsequent PWMIs.

Inflammation mediated by microglia plays a key role in brain injury associated with preterm birth, but little is known about the microglial response in preterm infants. Here, the authors integrate molecular and imaging data from animal models and preterm infants, and find that microglial expression of DLG4 plays a role.

Particle swarm optimization (PSO) based optimization algorithms are simple and easily implementable techniques with low computational complexity, which makes them good tools for solving large-scale nonlinear optimization problems. This paper presents a modified version of the original method by combining PSO with a local search technique at the end of each iteration cycle. The new algorithm is applied for the task of parameter optimization of a fuzzy classification subsystem in a series hybrid electric vehicle (SHEV) aiming at the reduction of the harmful pollutant emission. The new method ensured a better fitness value than either the original PSO algorithm or the clonal selection based artificial immune system algorithm (CLONALG) by using similar parameters.

Our aim was to examine the dynamics of the muscarinic m2 receptor (m2R), a G-protein coupled receptor (GPCR), after agonist activation in living hippocampal neurons, and especially clathrin dependency endocytosis. We have previously shown that the m2R undergoes agonist-induced internalization in vivo. However, the nature of the endocytotic pathway used by m2R after activation is still unknown in living neurons. Using live cell imaging and quantitative analyses, we have monitored the effect of stimulation on the fate of the membrane-bound m2R and on its redistribution in intraneuronal compartments. Shortly (6 min) after activation, m2R is internalized into clathrin immunopositive structures. Furthermore, after clathrin-dependent endocytosis, m2R associates with early and late endosomes and with subcellular organelles involved in degradation. Together, these results provide, for the first time, a description of m2R trafficking in living neurons and prove that m2R undergoes clathrin-dependent endocytosis before being degraded.

Characterization of the genetic defects causing gonadotropic deficiency has made a major contribution to elucidation of the fundamental role of Kisspeptins and Neurokinin B in puberty onset and reproduction. The absence of puberty may also reveal neurodevelopmental disorders caused by molecular defects in various cellular pathways. Investigations of these neurodevelopmental disorders may provide information about the neuronal processes controlling puberty onset and reproductive capacity. We describe here a new syndrome observed in three brothers, which involves gonadotropic axis deficiency, central hypothyroidism, peripheral demyelinating sensorimotor polyneuropathy, mental retardation, and profound hypoglycemia, progressing to nonautoimmune insulin-dependent diabetes mellitus. High-throughput sequencing revealed a homozygous in-frame deletion of 15 nucleotides in DMXL2 in all three affected patients. This homozygous deletion was associated with lower DMXL2 mRNA levels in the blood lymphocytes of the patients. DMXL2 encodes the synaptic protein rabconnectin-3α, which has been identified as a putative scaffold protein for Rab3-GAP and Rab3-GEP, two regulators of the GTPase Rab3a. We found that rabconnectin-3α was expressed in exocytosis vesicles in gonadotropin-releasing hormone (GnRH) axonal extremities in the median eminence of the hypothalamus. It was also specifically expressed in cells expressing luteinizing hormone (LH) and follicle-stimulating hormone (FSH) within the pituitary. The conditional heterozygous deletion of Dmxl2 from mouse neurons delayed puberty and resulted in very low fertility. This reproductive phenotype was associated with a lower number of GnRH neurons in the hypothalamus of adult mice. Finally, Dmxl2 knockdown in an insulin-secreting cell line showed that rabconnectin-3α controlled the constitutive and glucose-induced secretion of insulin. In conclusion, this study shows that low levels of DMXL2 expression cause a complex neurological phenotype, with abnormal glucose metabolism and gonadotropic axis deficiency due to a loss of GnRH neurons. Our findings identify rabconectin-3α as a key controller of neuronal and endocrine homeostatic processes.

Cyanide-resistant non-phosphorylating respiration is known in mitochondria from plants, fungi, and microorganisms but is absent in mammals. It results from the activity of an alternative oxidase (AOX) that conveys electrons directly from the respiratory chain (RC) ubiquinol pool to oxygen. AOX thus provides a bypath that releases constraints on the cytochrome pathway and prevents the over-reduction of the ubiquinone pool, a major source of superoxide. RC dysfunctions and deleterious superoxide overproduction are recurrent themes in human pathologies, ranging from neurodegenerative diseases to cancer, and may be instrumental in ageing. Thus, preventing RC blockade and excess superoxide production by means of AOX should be of considerable interest. However, because of its energy-dissipating properties, AOX might produce deleterious effects of its own in mammals. Here we show that AOX can be safely expressed in the mouse (MitAOX), with major physiological parameters being unaffected. It neither disrupted the activity of other RC components nor decreased oxidative phosphorylation in isolated mitochondria. It conferred cyanide-resistance to mitochondrial substrate oxidation and decreased reactive oxygen species (ROS) production upon RC blockade. Accordingly, AOX expression was able to support cyanide-resistant respiration by intact organs and to afford prolonged protection against a lethal concentration of gaseous cyanide in whole animals. Taken together, these results indicate that AOX expression in the mouse is innocuous and permits to overcome a RC blockade, while reducing associated oxidative insult. Therefore, the MitAOX mice represent a valuable tool in order to investigate the ability of AOX to counteract the panoply of mitochondrial-inherited diseases originating from oxidative phosphorylation defects.

The neuropeptide somatostatin has been suggested to play an important role during neuronal development in addition to its established modulatory impact on neuroendocrine, motor and cognitive functions in adults. Although six somatostatin G protein-coupled receptors have been discovered, little is known about their distribution and function in the developing mammalian brain. In this study, we have first characterized the developmental expression of the somatostatin receptor sst2A, the subtype found most prominently in the adult rat and human nervous system. In the rat, the sst2A receptor expression appears as early as E12 and is restricted to post-mitotic neuronal populations leaving the ventricular zone. From E12 on, migrating neuronal populations immunopositive for the receptor were observed in numerous developing regions including the cerebral cortex, hippocampus and ganglionic eminences. Intense but transient immunoreactive signals were detected in the deep part of the external granular layer of the cerebellum, the rostral migratory stream and in tyrosine hydroxylase- and serotonin- positive neurons and axons. Activation of the sst2A receptor in vitro in rat cerebellar microexplants and primary hippocampal neurons revealed stimulatory effects on neuronal migration and axonal growth, respectively. In the human cortex, receptor immunoreactivity was located in the preplate at early development stages (8 gestational weeks) and was enriched to the outer part of the germinal zone at later stages. In the cerebellum, the deep part of the external granular layer was strongly immunoreactive at 19 gestational weeks, similar to the finding in rodents. In addition, migrating granule cells in the internal granular layer were also receptor-positive. Together, theses results strongly suggest that the somatostatin sst2A receptor participates in the development and maturation of specific neuronal populations during rat and human brain ontogenesis.

Energy consumption is a significant concern in daily life, often neglected in terms of cost and environmental impact. Since IT networks play an essential role in our daily routines, energy-saving in this area is crucial. However, the implementation of energy efficiency solutions in this field have to ensure that the network performance is minimally affected. Traditional networks encounter difficulties in achieving this goal. Software-Defined Networks (SDN), which have gained popularity in the past decade, offer easy-to-use opportunities to increase energy efficiency. Features like central controllability and quick programmability can help to reduce energy consumption. In this article, a new algorithm named the Modified Heuristic Algorithm for Energy Saving (MHAES) is presented, which was compared to eight commonly used methods in different topologies for energy efficiency. The results indicate that by maintaining an appropriate load balance, one can save more energy than in case of using some other well-known procedures by applying a threshold value based on forecast, keeping only a minimal number of nodes in an active state, and ensuring that nodes not participating in packet transmission remain in sleep mode. [ABSTRACT FROM AUTHOR]

Intrusion Detection Systems (IDS) play a critical role in safeguarding corporate IT systems by providing automated protection against various attacks and intrusions. They efficiently identify suspicious attack scenarios and promptly alert or intervene to prevent an attack. This paper focuses on the research conducted to develop a classification module for Behavior-based IDSs (BIDS). Typically, these modules are built using a sample dataset that comprises a significant amount of data describing both benign and malicious network traffic. In our case, the CSE-CIC-IDS2018 dataset on AWS served as the foundation for this purpose. The investigation aimed to develop an effective classifier module for a BIDS system using the CatBoost algorithm. To evaluate the performance of the trained classifier, we compared it to three other well-known classifiers trained on the same data, employing the same selected features. Additionally, we utilized four different performance measures, namely accuracy, precision, recall, and F1 score. The results demonstrated that, overall, the CatBoost classifier delivered performance on par with or better than the baseline methods. This finding supports the initial assumption that a CatBoost-based solution could be a viable choice when developing a BIDS. [ABSTRACT FROM AUTHOR]