k-TYPE SLANT HELICES FOR SYMPLECTIC CURVE IN 4-DIMENSIONAL SYMPLECTIC SPACE

In this study, we have expressed the notion of $k$-type slant helix in $4$-symplectic space. Also, we have generated some differential equations for $k$-type slant helix of symplectic regular curves.

The Role of Environmental Factors in Etiology of Attention- Deficit Hyperactivity Disorder

Environmental factors in etiology of ADHD Attention deficit and hyperactivity disorder (ADHD) is one of the most common developmental disorders of childhood. It was reported that it is a disease that affects 5.29% of children and adolescents in the entire world. Although ADHD is a disorder with high inheritability, genetic factors are not the only explanation to ADHD etiology. ADHD is a disorder etiology which has genetic and environmental components and gene-environment interaction. In spite of the fact that many environmental factors are linked to ADHD, the number of environmental factors that are proven to be in significant cause-effect relation is too small. In other words, in presence of proper genetic basis, disease appears in presence of many environmental factors each of which have a slight effect, its severity or prognosis is variable. Environmental factors that are most commonly linked to ADHD pathophysiology are; complications during pregnancy, natal and postnatal period, several toxins and food substances. It has been considered that exposure to risk factors that may affect development of the brain in any of these periods will have long-term effects on behavior. Along with mother’s cigarette or alcohol use during pregnancy, emotional difficulties, medical diseases and complications of pregnancy; natal complications, low birth weight, premature birth, post mature birth, physical traumas that may affect brain development in early childhood, psychosocial difficulties are also found to be related to ADHD. Studies of gene-environment interaction also note the importance of environmental factors. For example, a study showed that in cases which carry 7 repeated alleles of DRD4, exposure to prenatal cigarettes causes more severe symptoms of ADHD. The purpose of this paper is to evaluate the role of environmental factors in etiology of ADHD, review these factors in the light of related literature and, lastly, to mention gene-environment interaction

Automated drowsiness detection for improved driving safety

Several approaches were proposed for the detection and prediction of drowsiness. The approaches can be categorized as estimating the fitness of duty, modeling the sleep-wake rhythms, measuring the vehicle based performance and online operator monitoring. Computer vision based online operator monitoring approach has become prominent due to its predictive ability of detecting drowsiness. Previous studies with this approach detect driver drowsiness primarily by making preassumptions about the relevant behavior, focusing on blink rate, eye closure, and yawning. Here we employ machine learning to datamine actual human behavior during drowsiness episodes. Automatic classifiers for 30 facial actions from the Facial Action Coding system were developed using machine learning on a separate database of spontaneous expressions. These facial actions include blinking and yawn motions, as well as a number of other facial movements. In addition, head motion was collected through automatic eye tracking and an accelerometer. These measures were passed to learning-based classifiers such as Adaboost and multinomial ridge regression. The system was able to predict sleep and crash episodes during a driving computer game with 96% accuracy within subjects and above 90% accuracy across subjects. This is the highest prediction rate reported to date for detecting real drowsiness. Moreover, the analysis revealed new information about human behavior during drowsy drivin

Discrimination of moderate and acute drowsiness based on spontaneous facial expressions

It is important for drowsiness detection systems to identify different levels of drowsiness and respond appropriately at each level. This study explores how to discriminate moderate from acute drowsiness by applying computer vision techniques to the human face. In our previous study, spontaneous facial expressions measured through computer vision techniques were used as an indicator to discriminate alert from acutely drowsy episodes. In this study we are exploring which facial muscle movements are predictive of moderate and acute drowsiness. The effect of temporal dynamics of action units on prediction performances is explored by capturing temporal dynamics using an overcomplete representation of temporal Gabor Filters. In the final system we perform feature selection to build a classifier that can discriminate moderate drowsy from acute drowsy episodes. The system achieves a classification rate of .96 A’ in discriminating moderately drowsy versus acutely drowsy episodes. Moreover the study reveals new information in facial behavior occurring during different stages of drowsiness

Seven years of postseismic deformation following the 2003 Mw = 6.8 Zemmouri earthquake (Algeria) from InSAR time series

International audience[1] We study the postseismic surface deformation of the Mw 6.8, 2003 Zemmouri earthquake (northern Algeria) using the Multi-Temporal Small Baseline InSAR technique. InSAR time series obtained from 31 Envisat ASAR images from 2003 to 2010 reveal sub-cm coastline ground movements between Cap Matifou and Dellys. Two regions display subsidence at a maximum rate of 2 mm/yr in Cap Djenet and 3.5 mm/yr in Boumerdes. These regions correlate well with areas of maximum coseismic uplifts, and their association with two rupture segments. Inverse modeling suggest that subsidence in the areas of high coseismic uplift can be explained by afterslip on shallow sections (<5 km) of the fault above the areas of coseismic slip, in agreement with previous GPS observations. The earthquake impact on soft sediments and the ground water table southwest of the earthquake area, characterizes ground deformation of non-tectonic origin. The cumulative postseismic moment due to 7 years afterslip is equivalent to an Mw 6.3 earthquake. Therefore, the postseismic deformation and stress buildup has significant implications on the earthquake cycle models and recurrence intervals of large earthquakes in the Algiers area

Role of serum metalloproteinases 2 and 9 to assess the severity of COVID-19 in pregnant women: a prospective cross-sectional study

Objectives: To investigate the relationship between blood matrix metalloproteinases -2 and -9 levels and disease severity in pregnant women with COVID-19 infection. Material and methods: A prospective cohort study was conducted at the Kanuni Sultan Suleyman Education and Research Hospital in Istanbul, Turkey. We measured serum MMPs-2 and-9 levels of the healthy pregnant controls and pregnant women with COVID-19 and sought to assess the status of these MMPs in pregnant women with COVID-19, especially in women with a severe form of COVID-19 as diagnosed by abnormal computed tomography (CT) findings in addition to severe clinical and laboratory findings. Results: Of the healthy pregnant controls and pregnant women with COVID-19, the serum MMP-2 levels were comparable, but the MMP-9 level was lower in the pregnant women with COVID-19. Although the serum MMP2 level was somewhat lower in the women with COVID-19 with abnormal CT findings. The serum MMP-9 level of pregnant women with COVID-19 with abnormal CT was meaningfully lower. Conclusions: In the pregnant women, COVID-19 decreases the serum MMP-9 but does not change the serum MMP-2. COVID-19 with abnormal CT findings causes minimal decrease in the serum MMP-2 but decreases the serum MMP-9 with abnormal CT findings. Considering the study variables of current study, the probability of LMWH-related MMP alterations needs to be a study topic to clarify the possible contribution of LMWH to the status of serum MMPs in pregnant women with COVİD-19 especially in the women with COVID-19 with abnormal CT findings

CROssBAR: comprehensive resource of biomedical relations with knowledge graph representations

Systemic analysis of available large-scale biological/biomedical data is critical for studying biological mechanisms, and developing novel and effective treatment approaches against diseases. However, different layers of the available data are produced using different technologies and scattered across individual computational resources without any explicit connections to each other, which hinders extensive and integrative multi-omics-based analysis. We aimed to address this issue by developing a new data integration/representation methodology and its application by constructing a biological data resource. CROssBAR is a comprehensive system that integrates large-scale biological/biomedical data from various resources and stores them in a NoSQL database. CROssBAR is enriched with the deep-learning-based prediction of relationships between numerous data entries, which is followed by the rigorous analysis of the enriched data to obtain biologically meaningful modules. These complex sets of entities and relationships are displayed to users via easy-tointerpret, interactive knowledge graphs within an open-access service. CROssBAR knowledge graphs incorporate relevant genes-proteins, molecular interactions, pathways, phenotypes, diseases, as well as known/predicted drugs and bioactive compounds, and they are constructed on-the-fly based on simple non-programmatic user queries. These intensely processed heterogeneous networks are expected to aid systems-level research, especially to infer biological mechanisms in relation to genes, proteins, their ligands, and diseases

Therapeutic targeting of chronic kidney disease-associated DAMPs differentially contributing to vascular pathology

Chronic Kidney Disease (CKD) is associated with markedly increased cardiovascular (CV) morbidity and mortality. Chronic inflammation, a hallmark of both CKD and CV diseases (CVD), is believed to drive this association. Pro-inflammatory endogenous TLR agonists, Damage-Associated Molecular Patterns (DAMPs), have been found elevated in CKD patients’ plasma and suggested to promote CVD, however, confirmation of their involvement, the underlying mechanism(s), the extent to which individual DAMPs contribute to vascular pathology in CKD and the evaluation of potential therapeutic strategies, have remained largely undescribed. A multi-TLR inhibitor, soluble TLR2, abrogated chronic vascular inflammatory responses and the increased aortic atherosclerosis-associated gene expression observed in nephropathic mice, without compromising infection clearance. Mechanistically, we confirmed elevation of 4 TLR DAMPs in CKD patients’ plasma, namely Hsp70, Hyaluronic acid, HMGB-1 and Calprotectin, which displayed different abilities to promote key cellular responses associated with vascular inflammation and progression of atherosclerosis in a TLR-dependent manner. These included loss of trans-endothelial resistance, enhanced monocyte migration, increased cytokine production, and foam cell formation by macrophages, the latter via cholesterol efflux inhibition. Calprotectin and Hsp70 most consistently affected these functions. Calprotectin was further elevated in CVD-diagnosed CKD patients and strongly correlated with the predictor of CV events CRP. In nephropathic mice, Calprotectin blockade robustly reduced vascular chronic inflammatory responses and pro-atherosclerotic gene expression in the blood and aorta. Taken together, these findings demonstrated the critical extent to which the DAMP-TLR pathway contributes to vascular inflammatory and atherogenic responses in CKD, revealed the mechanistic contribution of specific DAMPs and described two alternatives therapeutic approaches to reduce chronic vascular inflammation and lower CV pathology in CKD

Calprotectin blockade inhibits long-term vascular pathology following peritoneal dialysis-associated bacterial infection

Bacterial infections and the concurrent inflammation have been associated with increased long-term cardiovascular (CV) risk. In patients receiving peritoneal dialysis (PD), bacterial peritonitis is a common occurrence, and each episode further increases late CV mortality risk. However, the underlying mechanism(s) remains to be elucidated before safe and efficient anti-inflammatory interventions can be developed. Damage-Associated Molecular Patterns (DAMPs) have been shown to contribute to the acute inflammatory response to infections, but a potential role for DAMPs in mediating long-term vascular inflammation and CV risk following infection resolution in PD, has not been investigated. We found that bacterial peritonitis in mice that resolved within 24h led to CV disease-promoting systemic and vascular immune-mediated inflammatory responses that were maintained up to 28 days. These included higher blood proportions of inflammatory leukocytes displaying increased adhesion molecule expression, higher plasma cytokines levels, and increased aortic inflammatory and atherosclerosis-associated gene expression. These effects were also observed in infected nephropathic mice and amplified in mice routinely exposed to PD fluids. A peritonitis episode resulted in elevated plasma levels of the DAMP Calprotectin, both in PD patients and mice, here the increase was maintained up to 28 days. In vitro, the ability of culture supernatants from infected cells to promote key inflammatory and atherosclerosis-associated cellular responses, such as monocyte chemotaxis, and foam cell formation, was Calprotectin-dependent. In vivo, Calprotectin blockade robustly inhibited the short and long-term peripheral and vascular consequences of peritonitis, thereby demonstrating that targeting of the DAMP Calprotectin is a promising therapeutic strategy to reduce the long-lasting vascular inflammatory aftermath of an infection, notably PD-associated peritonitis, ultimately lowering CV risk