Search results for: brain tumor classification

Authors: Milton Ayoki, Edward Bbaale

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This paper analyses the relationship between innovation and employment at firm level with the objective of understanding the contribution of the different innovation strategies in fostering employment growth in Uganda. We use National Innovation Survey (micro-data of 705 Ugandan firms) for the period 2011-2014 and follow closely Harrison et al. (2014) structured approach, and relate employment growth to process innovations and to the growth of sales separately due to innovative and unchanged products. We find positive effects of product innovation on employment at firm level, while process innovation has no discernable impact on employment. Although there is evidence to suggest displacement of labour in some cases where firms only introduce new process, this effect is compensated by growth in employment from new products, which for most firms are introduced simultaneously with new process. Results suggest that source of innovation as well as size of innovating firms or end users of innovation matter for job growth. Innovation that develops from within the firm itself (user) and involving larger firms has greater impact on employment than that developed from outside or coming from within smaller firms. In addition, innovative firms are one and half times more likely to survive in the innovation driven economy environment than those that do not innovate. These results have important implications for policymakers and stakeholders in innovation ecosystem. Supporting policies need to be correctly tailored since the impacts depend on the innovation strategy (type) and characteristics and sector of the innovative firms (small, large, industry, etc.). Policies to spur investment, particularly in innovative sectors and firms with high growth potential would have long lasting effects on job creation. JEL Classification: D24, J0, J20, L20, O30.

Keywords: employment, process innovation, product innovation, Sub-Saharan Africa

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Authors: Junbeom Lee, Jaehyuck Cho, Wookyeong Jeong, Jonghan Won, Jungmin Hwang, Youngseok Song, Taikyeong Jeong

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This paper investigates and analyzes meta-learning technologies that use multiple-cameras to monitor and check abnormal behavior in people in real-time in the area of healthcare fields. Advances in artificial intelligence and computer vision technologies have confirmed that cameras can be useful for individual health monitoring and abnormal behavior detection. Through this, it is possible to establish a system that can respond early by automatically detecting abnormal behavior of the elderly, such as patients and the elderly. In this paper, we use a technique called meta-learning to analyze image data collected from cameras and develop a commercial product to determine abnormal behavior. Meta-learning applies machine learning algorithms to help systems learn and adapt quickly to new real data. Through this, the accuracy and reliability of the abnormal behavior discrimination system can be improved. In addition, this study proposes a meta-learning-based abnormal behavior detection system that includes steps such as data collection and preprocessing, feature extraction and selection, and classification model development. Various healthcare scenarios and experiments analyze the performance of the proposed system and demonstrate excellence compared to other existing methods. Through this study, we present the possibility that camera-based meta-learning technology can be useful for monitoring and testing abnormal behavior in the healthcare area.

Keywords: artificial intelligence, abnormal behavior, early detection, health monitoring

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Authors: Jyoti Brahma

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Folk epics of India are found in various Indian languages. The study of folk epics and its importance in folkloristic study in India came into prominence only during the nineteenth century. The British administrators and missionaries collected and documented folk epics from various parts of the country. The paper is an attempt to investigate how colonial outpost appears to penetrate the interiors of Indian land and society and triggered off the Indian Renaissance. It takes into account the compositions of the epics of India and the attention it received during the nineteenth century, which in turn gave, rise to the national consciousness shaping the culture of India. Composed as oral traditions these folk epics are now seen as repositories of historical consciousness whereas in earlier times societies without literacy were said to be without history. So, there is an urgent need to re-examine the British impact on Indian literary traditions. The Bhakti poets through their nuanced responses in their efforts to change the behavior of Indian society gives us the perfect example of deferment in the clear cut distinction between the folk and the classical in the context of India. It evades a pure categorization and classification of the classical and constitutes part of the folk traditions of the cultural heritage of India. Therefore, the ethical question of what is ontologically known as ordinary discourse in the case of the “folk” forms metaphors and folk language gains importance once more. The paper also thus seeks simultaneously to outline the significant factors responsible for shaping the destiny of folklore in South India particularly the four political states of the Indian Union: Andhra Pradesh, Karnataka, Kerala and Tamil Nadu, what could be termed as South Indian “cultural zones”.

Keywords: colonial, folk, folklore, tradition

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Authors: Zahra Kazemi Saleh, Bénédicte Poulin-Charronnat, Annie Vinter

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This study examines the effects of aging on visual statistical learning, using eye-tracking techniques to investigate this cognitive phenomenon. Visual statistical learning is a fundamental brain function that enables the automatic and implicit recognition, processing, and internalization of environmental patterns over time. Some previous research has suggested the robustness of this learning mechanism throughout the aging process, underscoring its importance in the context of education and rehabilitation for the elderly. The study included three distinct groups of participants, including 21 young adults (Mage: 19.73), 20 young-old adults (Mage: 67.22), and 17 old-old adults (Mage: 79.34). Participants were exposed to a series of 12 arbitrary black shapes organized into 6 pairs, each with different spatial configurations and orientations (horizontal, vertical, and oblique). These pairs were not explicitly revealed to the participants, who were instructed to passively observe 144 grids presented sequentially on the screen for a total duration of 7 min. In the subsequent test phase, participants performed a two-alternative forced-choice task in which they had to identify the most familiar pair from 48 trials, each consisting of a base pair and a non-base pair. Behavioral analysis using t-tests revealed notable findings. The mean score for the first group was significantly above chance, indicating the presence of visual statistical learning. Similarly, the second group also performed significantly above chance, confirming the persistence of visual statistical learning in young-old adults. Conversely, the third group, consisting of old-old adults, showed a mean score that was not significantly above chance. This lack of statistical learning in the old-old adult group suggests a decline in this cognitive ability with age. Preliminary eye-tracking results showed a decrease in the number and duration of fixations during the exposure phase for all groups. The main difference was that older participants focused more often on empty cases than younger participants, likely due to a decline in the ability to ignore irrelevant information, resulting in a decrease in statistical learning performance.

Keywords: aging, eye tracking, implicit learning, visual statistical learning

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Authors: Arwa Alzughaibi

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Human Motion detection is a challenging task due to a number of factors including variable appearance, posture and a wide range of illumination conditions and background. So, the first need of such a model is a reliable feature set that can discriminate between a human and a non-human form with a fair amount of confidence even under difficult conditions. By having richer representations, the classification task becomes easier and improved results can be achieved. The Aim of this paper is to investigate the reliable and accurate human motion detection models that are able to detect the human motions accurately under varying illumination levels and backgrounds. Different sets of features are tried and tested including Histogram of Oriented Gradients (HOG), Deformable Parts Model (DPM), Local Decorrelated Channel Feature (LDCF) and Aggregate Channel Feature (ACF). However, we propose an efficient and reliable human motion detection approach by combining Histogram of oriented gradients (HOG) and local phase quantization (LPQ) as the feature set, and implementing search pruning algorithm based on optical flow to reduce the number of false positive. Experimental results show the effectiveness of combining local phase quantization descriptor and the histogram of gradient to perform perfectly well for a large range of illumination conditions and backgrounds than the state-of-the-art human detectors. Areaunder th ROC Curve (AUC) of the proposed method achieved 0.781 for UCF dataset and 0.826 for CDW dataset which indicates that it performs comparably better than HOG, DPM, LDCF and ACF methods.

Keywords: human motion detection, histograms of oriented gradient, local phase quantization, local phase quantization

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Authors: Govindan Sudha, Mathumitha Subramaniam, Alamelu Govindasamy, Sasikala Gunasekaran

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The aim of this study was to investigate the protective effect of Hypsizygus ulmarius polysaccharides (HUP) on reducing oxidative stress, cognitive impairment and neurotoxicity in D-galactose induced aging mice. Mice were subcutaneously injected with D-galactose (150 mg/kg per day) for 6 weeks and were administered HUP simultaneously. Aged mice receiving vitamin E (100 mg/kg) served as positive control. Chronic administration of D-galactose significantly impaired cognitive performance oxidative defence and mitochondrial enzymes activities as compared to control group. The results showed that HUP (200 and 400 mg/kg) treatment significantly improved the learning and memory ability in Morris water maze test. Biochemical examination revealed that HUP significantly increased the decreased activities of superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPx), glutathione reductase (GR), glutathione-S-transferase (GST), mitochondrial enzymes-NADH dehydrogenase, malate dehydrogenase (MDH), isocitrate dehydrogenase (ICDH), Na+K+, Ca2+, Mg2+ATPase activities, elevated the lowered total anti-oxidation capability (TAOC), glutathione (GSH), vitamin C and decreased the raised acetylcholinesterase (AChE) activities, malondialdehyde (MDA), hydroperoxide (HPO), protein carbonyls (PCO), advanced oxidation protein products (AOPP) levels in brain of aging mice induced by D-gal in a dose-dependent manner. In conclusion, present study highlights the potential role of HUP against D-galactose induced cognitive impairment, biochemical and mitochondrial dysfunction in mice. In vitro studies on the effect of HUP on scavenging DPPH, ABTS, DMPD, OH radicals, reducing power, B-carotene bleaching and lipid peroxidation inhibition confirmed the free radical scavenging and antioxidant activity of HUP. The results suggest that HUP possesses anti-aging efficacy and may have potential in treatment of neurodegenerative diseases.

Keywords: aging, antioxidants, mushroom, neurotoxicity

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Authors: Adamu Abdullahi, On Francisca, Saidu Isah Rambo, G. N. Obunadike, D. T. Chinyio

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The paper discusses the potential threat of Denial of Service (DoS) attacks in the Internet of Things (IoT) networks on constrained application protocols (CoAP). As billions of IoT devices are expected to be connected to the internet in the coming years, the security of these devices is vulnerable to attacks, disrupting their functioning. This research aims to tackle this issue by applying mixed methods of qualitative and quantitative for feature selection, extraction, and cluster algorithms to detect DoS attacks in the Constrained Application Protocol (CoAP) using the Machine Learning Algorithm (MLA). The main objective of the research is to enhance the security scheme for CoAP in the IoT environment by analyzing the nature of DoS attacks and identifying a new set of features for detecting them in the IoT network environment. The aim is to demonstrate the effectiveness of the MLA in detecting DoS attacks and compare it with conventional intrusion detection systems for securing the CoAP in the IoT environment. Findings: The research identifies the appropriate node to detect DoS attacks in the IoT network environment and demonstrates how to detect the attacks through the MLA. The accuracy detection in both classification and network simulation environments shows that the k-means algorithm scored the highest percentage in the training and testing of the evaluation. The network simulation platform also achieved the highest percentage of 99.93% in overall accuracy. This work reviews conventional intrusion detection systems for securing the CoAP in the IoT environment. The DoS security issues associated with the CoAP are discussed.

Keywords: algorithm, CoAP, DoS, IoT, machine learning

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Authors: Jacob J. Shila, Xiaoyu O. Wu

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As the applications of unmanned aerial vehicles (UAV) continue to increase across the world, it is critical to understand the factors that contribute to incidents and accidents associated with these systems. Given the variety of daily applications that could utilize the operations of the UAV (e.g., medical, security operations, construction activities, landscape activities), the main discussion has been how to safely incorporate the UAV into the national airspace system. The types of UAV incidents being reported range from near sightings by other pilots to actual collisions with aircraft or UAV. These incidents have the potential to impact the rest of aviation operations in a variety of ways, including human lives, liability costs, and delay costs. One of the largest causes of these incidents cited is the human factor; other causes cited include maintenance, aircraft, and others. This work investigates the key human factors associated with UAV incidents. To that end, the data related to UAV incidents that have occurred in the United States is both reviewed and analyzed to identify key human factors related to UAV incidents. The data utilized in this work is gathered from the Federal Aviation Administration (FAA) drone database. This study adopts the human factor analysis and classification system (HFACS) to identify key human factors that have contributed to some of the UAV failures to date. The uniqueness of this work is the incorporation of UAV incident data from a variety of applications and not just military data. In addition, identifying the specific human factors is crucial towards developing safety operational models and human factor guidelines for the UAV. The findings of these common human factors are also compared to similar studies in other countries to determine whether these factors are common internationally.

Keywords: human factors, incidents and accidents, safety, UAS, UAV

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Authors: Kasidis Chomrat, Nopasit Chakpitak, Anukul Tamprasirt, Annop Thananchana

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Internet of Things devices or IoT and Edge Computing has become one of the biggest things happening in innovations and one of the most discussed of the potential to improve and disrupt traditional business and industry alike. With rises of new hang cliff challenges like COVID-19 pandemic that posed a danger to workforce and business process of the system. Along with drastically changing landscape in business that left ruined aftermath of global COVID-19 pandemic, looming with the threat of global energy crisis, global warming, more heating global politic that posed a threat to become new Cold War. How emerging technology like edge computing and usage of specialized design visual processing units will be great opportunities for business. The literature reviewed on how the internet of things and disruptive wave will affect business, which explains is how all these new events is an effect on the current business and how would the business need to be adapting to change in the market and world, and example test benchmarking for consumer marketed of newer devices like the internet of things devices equipped with new edge computing devices will be increase efficiency and reducing posing a risk from a current and looming crisis. Throughout the whole paper, we will explain the technologies that lead the present technologies and the current situation why these technologies will be innovations that change the traditional practice through brief introductions to the technologies such as cloud computing, edge computing, Internet of Things and how it will be leading into future.

Keywords: internet of things, edge computing, machine learning, pattern recognition, image classification

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Authors: Jeanne Gallee, Sofia Vallila-Rohter

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Technology-based applications are increasingly being utilized in aphasia rehabilitation as a means of increasing intensity of treatment and improving accessibility to treatment. These interactive therapies, often available on tablets, lead individuals to complete language and cognitive rehabilitation tasks that draw upon skills such as the ability to name items, recognize semantic features, count syllables, rhyme, and categorize objects. Tasks involve visual and auditory stimulus cues and provide feedback about the accuracy of a person’s response. Research has begun to examine the efficacy of tablet-based therapies for aphasia, yet much remains unknown about how individuals interact with these therapy applications. Thus, the current study aims to examine the efficacy of a tablet-based therapy program for anomia, further examining how strategy training might influence the way that individuals with aphasia engage with and benefit from therapy. Individuals with aphasia are enrolled in one of two treatment paradigms: traditional therapy or strategy therapy. For ten weeks, all participants receive 2 hours of weekly in-house therapy using Constant Therapy, a tablet-based therapy application. Participants are provided with iPads and are additionally encouraged to work on therapy tasks for one hour a day at home (home logins). For those enrolled in traditional therapy, in-house sessions involve completing therapy tasks while a clinician researcher is present. For those enrolled in the strategy training group, in-house sessions focus on limiting cue use in order to maximize lexical retrieval attempts and naming opportunities. The strategy paradigm is based on the principle that retrieval attempts may foster long-term naming gains. Data have been collected from 7 participants with aphasia (3 in the traditional therapy group, 4 in the strategy training group). We examine cue use, latency of responses and accuracy through the course of therapy, comparing results across group and setting (in-house sessions vs. home logins).

Keywords: aphasia, speech-language pathology, traumatic brain injury, language

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Authors: Balkibekova Venera Serikpaevna

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Background: Autism Spectrum Disorder (ASD) poses significant challenges in both diagnosis and treatment. Existing therapeutic interventions often target specific symptoms, necessitating the exploration of alternative approaches. This study investigates the RITM (Rhythm Integration Tapping Music) developed by Balkibekova, aiming to create imitation, social engagement and a wide range of emotions through brain development. Methods: A randomized controlled trial was conducted with 100 participants diagnosed with ASD, aged 1 to 4 years. Participants were randomly assigned to either the RITM therapy group or a control group receiving standard care. The RITM therapy, rooted in tapping rhythm to music such as: marche on the drums, waltz on bells, lullaby on musical triangle, dancing on tambourine, polka on wooden spoons. Therapy sessions were conducted over a 3 year period, with assessments at baseline, midpoint, and post-intervention. Results: Preliminary analyses reveal promising outcomes in the RITM therapy group. Participants demonstrated significant improvements in social interactions, speech understanding, birth of speech, and adaptive behaviors compared to the control group. Careful examination of subgroup analyses provides insights into the differential effectiveness of the RITM approach across various ASD profiles. Conclusions: The findings suggest that RITM therapy, as developed by Balkibekova, holds promise as intervention for ASD. The integrative nature of the approach, addressing multiple domains simultaneously, may contribute to its efficacy. Further research is warranted to validate these preliminary results and explore the long-term impact of RITM therapy on individuals with ASD. This abstract presents a snapshot of the research, emphasizing the significance, methodology, key findings, and implications of the RITM therapy method for consideration in an autism conference.

Keywords: RITM therapy, tapping rhythm, autism, mirror neurons, bright emotions, social interactions, communications

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Authors: Rostyslav Horbay, Nick Korolis, Vahid Anvari, Rostyslav Stoika

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Introduction: Giant cancer cells (GCC) are common in all types of cancer, especially after poor therapy. Some specific features of such cells include ~10-fold enlargement, drug resistance, and the ability to propagate similar daughter cells. We used murine NK/Ly lymphoma, an aggressive and fast growing lymphoma model that has already shown drastic changes in GCC comparing to parental cells (chromatin condensation, nuclear fragmentation, tighter OXPHOS/cellular respiration coupling, multidrug resistance). Materials and methods: In this study, we compared morpho-functional changes of GCC that predominantly show either a cytostatic or a cytotoxic effect after treatment with drugs. We studied the effect of a combined cytostatic/cytotoxic drug treatment to determine the correlation of drug efficiency and GCC formation. Doses of G1/S-specific drug paclitaxel/PTX (G2/M-specific, 50 mg/mouse), vinblastine/VBL (50 mg/mouse), and DNA-targeting agents doxorubicin/DOX (125 ng/mouse) and cisplatin/CP (225 ng/mouse) on C57 black mice. Several tests were chosen to estimate morphological and physiological state (propidium iodide, Rhodamine-123, DAPI, JC-1, Janus Green, Giemsa staining and other), which included cell integrity, nuclear fragmentation and chromatin condensation, mitochondrial activity, and others. A single and double factor ANOVA analysis were performed to determine correlation between the criteria of applied drugs and cytomorphological changes. Results: In all cases of treatment, several morphological changes were observed (intracellular vacuolization, membrane blebbing, and interconnected mitochondrial network). A lower gain in ascites (49.97% comparing to control group) and longest lifespan (22+9 days) after tumor injection was obtained with single VBL and single DOX injections. Such ascites contained the highest number of GCC (83.7%+9.2%), lowest cell count number (72.7+31.0 mln/ml), and a strong correlation coefficient between increased mitochondrial activity and percentage of giant NK/Ly cells. A high number of viable GCC (82.1+9.2%) was observed compared to the parental forms (15.4+11.9%) indicating that GCC are more drug resistant than the parental cells. All this indicates that the giant cell formation and its ability to obtain drug resistance is an expanding field in cancer research.

Keywords: ANOVA, cisplatin, doxorubicin, drug resistance, giant cancer cells, NK/Ly lymphoma, paclitaxel, vinblastine

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Authors: Vanitha Varadharaj, Vijalakshmi Krishnamurthy

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Annona squamosa Linn, commonly known as Sugar apple, belonging to the family Annonaceae, is said to show varied medicinal effects, including insecticide, antiovulatory and abortifacient. The alkaloid and flavonoids present in Annona squamosa leaf has proved to have antioxidant activity. The present work has been planned to investigate the effect of ethanolic leaf extract of Annona squamosa leaf on Den Induced wistar albino rats. The study was carried out to analyze the biochemical Parmeters like Total Proteins, Bilirubin, Enzymatic and Non –Enzymatic enzymes, Marker enzymes and Tumor markers in serum and also the histopathological studies in liver is carried out in control and DEN induced rats. Supplementation of ELAS (Ethanolic Leaf Extract Of Annona squamosa) reduced the liver weight and also reduced the tumour incidence. Chemoprevention group showed near normal values of bilirubin when compared with the control rats. Total protein was decreased in the cancer bearing group and on treatment with the extract the levels of protein were restored. Both in pre and post treatment group, the activities of enzymatic antioxidants such as superoxide dismutase, catalase, and Glutathione peroxidase were increased but in pre treated animals it was more effective than post treated animals. The non- enzymatic antioxidants such as vitamin C and vitamin E were brought back to normal level significantly in post and pre treated animals. Activities of marker enzymes such as SGOT, SGPT, ALP, γ GT were significantly elevated in the serum of cancer animals and the values returned to normal after treatment with the extract suggesting the hepato protective effect of the extract. Lipid peroxide was found to be elevated in the cancer induced group. This condition was brought back to the normal in the pre and post treated animals with ELAS. Histological examination also confirmed the anti- carcinogenic potential of ELAS, Cancer induced groups had a triple fold increase in their AFP values when compared to other groups. DEN treatment increased the level of AFP expression while ELAS partially counteracted the effect of it. So the scientific validation obtained from this study may pave way to many budding scientists to find new drugs from Annona squamosa for various ailments.

Keywords: annona squamosa, biochemical parmeters, cancer, leaf extract

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Authors: Katie Emerson, Sara Perez-Ojalvo, Jim Komorowski, Danielle Greenberg

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The purpose of this study was to evaluate arginase activity levels in response to combinations of an inositol-stabilized arginine silicate (ASI; Nitrosigine®), L-arginine, and Inositol. Arginine acts as a vasodilator that promotes increased blood flow resulting in enhanced delivery of oxygen and nutrients to the brain and other tissues. ASI alone has been shown to improve performance on cognitive tasks. Arginase, found in human serum, catalyzes the conversion of arginine to ornithine and urea, completing the last step in the urea cycle. Decreasing arginase levels maintains arginine and results in increased nitric oxide production. This study aimed to determine the most effective combination of ASI, L-arginine and inositol for minimizing arginase levels and therefore maximize ASI’s effect on cognition. Serum was taken from untreated healthy donors by separation from clotted factors. Arginase activity of serum in the presence or absence of test products was determined (QuantiChrom™, DARG-100, Bioassay Systems, Hayward CA). The remaining ultra-filtrated serum units were harvested and used as the source for the arginase enzyme. ASI alone or combined with varied levels of Inositol were tested as follows: ASI + inositol at 0.25 g, 0.5 g, 0.75 g, or 1.00 g. L-arginine was also tested as a positive control. All tests elicited changes in arginase activity demonstrating the efficacy of the method used. Adding L-arginine to serum from untreated subjects, with or without inositol only had a mild effect. Adding inositol at all levels reduced arginase activity. Adding 0.5 g to the standardized amount of ASI led to the lowest amount of arginase activity as compared to the 0.25g 0.75g or 1.00g doses of inositol or to L-arginine alone. The outcome of this study demonstrates an interaction of the pairing of inositol with ASI on the activity of the enzyme arginase. We found that neither the maximum nor minimum amount of inositol tested in this study led to maximal arginase inhibition. Since the inhibition of arginase activity is desirable for product formulations looking to maintain arginine levels, the most effective amount of inositol was deemed preferred. Subsequent studies suggest this moderate level of inositol in combination with ASI leads to cognitive improvements including reaction time, executive function, and concentration.

Keywords: arginine, inositol, arginase, cognitive benefits

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Authors: Nigatu Tadesse, Li Juan, Liuhong Ming

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Gastric cancer (GC) is the fifth most common and fourth deadly cancer in the world with limited treatment options at late advanced stage in which surgical therapy is not recommended with chemotherapy remain as the mainstay of treatment. However, the occurrence of chemoresistance as well as intera-tumoral and inter-tumoral heterogeneity of response to targeted and immunotherapy underlined a clear unmet treatment need in gastroenterology. Several molecular and cellular alterations ascribed for chemo resistance in GC including cancer stem cells (CSC) and tumor microenvironment (TME) remodeling. Cancer cells including CSC bears higher metabolic demand and major changes in TME involves alterations of gut microbiota interacting with nutrients metabolism. Metabolic upregulation in lipids, carbohydrates, amino acids, fatty acids biosynthesis pathways identified as a common hall mark in GC. Metabolic addiction to methionine metabolism occurs in many cancer cells to promote the biosynthesis of S-Adenosylmethionine (SAM), a universal methyl donor molecule for high rate of transmethylation in GC and promote cell proliferation. Targeting methionine metabolism found to promotes chemo-sensitivity with treatment non-heterogeneity. Methionine restriction (MR) promoted the arrest of cell cycle at S/G2 phase and enhanced downregulation of GC cells resistance to apoptosis (including ferroptosis), which suggests the potential of synergy with chemotherapies acting at S-phase of the cell cycle as well as inducing cell apoptosis. Accumulated evidences showed both the biogenesis as well as intracellular metabolism of exogenous methionine could be safe and effective target for therapy either alone or in combination with chemotherapies. This review article provides an over view of the upregulation in methionine biosynthesis pathway and the molecular signaling through the PI3K/Akt/mTOR-c-MYC axis to promote metabolic reprograming through activating the expression of L-type aminoacid-1 (LAT1) transporter and overexpression of Methionine adenosyltransferase 2A(MAT2A) for intercellular metabolic conversion of exogenous methionine to SAM in GC, and the potential of targeting with novel therapeutic agents such as methioninase (METase), Methionine adenosyltransferase 2A (MAT2A), c-MYC, methyl like transferase 16 (METTL16) inhibitors that are currently under clinical trial development stages and future perspectives.

Keywords: gastric cancer, methionine metabolism, pi3k/akt/mtorc1-c-myc axis, gut microbiota, MAT2A, c-MYC, METTL16, methioninase

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Authors: D. Jayalakshmi, S. S. Bhosale

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This paper, in its first part, presents the state-of-the-art literature of design approaches for geosynthetic reinforced unpaved roads. The literature starting since 1970 and the critical appraisal of flexible pavement design by Giroud and Han (2004) and Jonathan Fannin (2006) is presented. The design example is illustrated for Indian conditions. The example emphasizes the results computed by Giroud and Han's (2004) design method with the Indian road congress guidelines by IRC SP 72 -2015. The input data considered are related to the subgrade soil condition of Maharashtra State in India. The unified soil classification of the subgrade soil is inorganic clay with high plasticity (CH), which is expansive with a California bearing ratio (CBR) of 2% to 3%. The example exhibits the unreinforced case and geotextile as reinforcement by varying the rut depth from 25 mm to 100 mm. The present result reveals the base thickness for the unreinforced case from the IRC design catalogs is in good agreement with Giroud and Han (2004) approach for a range of 75 mm to 100 mm rut depth. Since Giroud and Han (2004) method is applicable for both reinforced and unreinforced cases, for the same data with appropriate Nc factor, for the same rut depth, the base thickness for the reinforced case has arrived for the Indian condition. From this trial, for the CBR of 2%, the base thickness reduction due to geotextile inclusion is 35%. For the CBR range of 2% to 5% with different stiffness in geosynthetics, the reduction in base course thickness will be evaluated, and the validation will be executed by the full-scale accelerated pavement testing set up at the College of Engineering Pune (COE), India.

Keywords: base thickness, design approach, equation, full scale accelerated pavement set up, Indian condition

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Authors: M. Zareh, H. Mohammadi, B. Naser

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Atherosclerotic plaque rupture is the main trigger of heart attack and brain stroke which are the leading cause of death in developed countries. Better understanding of rupture-prone plaque can help clinicians detect vulnerable plaques- rupture prone or instable plaques- and apply immediate medical treatment to prevent these life-threatening cardiovascular events. Therefore, there are plenty of studies addressing disclosure of vulnerable plaques properties. Necrotic core and fibrous tissue are two major tissues constituting atherosclerotic plaque; using histopathological and numerical approaches, many studies have demonstrated that plaque rupture is strongly associated with a large necrotic core and a thin fibrous cap, two morphological characteristic which can be acquired by two-dimensional imaging of atherosclerotic plaque present in coronary and carotid arteries. Plaque rupture is widely considered as a mechanical failure inside plaque tissue; this failure occurs when the stress within plaque excesses the strength of tissue material; hence, finite element method, a strong numerical approach, has been extensively applied to estimate stress distribution within plaques with different compositions which is then used for assessment of various vulnerability characteristics including plaque morphology, material properties and blood pressure. This study aims to evaluate significance of three-dimensional morphology on vulnerability degree of atherosclerotic plaque. To reach this end, different two-dimensional geometrical models of atherosclerotic plaques are considered based on available data and named Main 2D Models (M2M). Then, for each of these M2Ms, two three-dimensional idealistic models are created. These two 3D models represent two possible three-dimensional morphologies which might exist for a plaque with similar 2D morphology to one of M2Ms. Finite element method is employed to estimate stress, von-Mises stress, within each 3D models. Results indicate that for each M2Ms stress can significantly varies due to possible 3D morphological changes in that plaque. Also, our results show that an atherosclerotic plaque with thick cap may experience rupture if it has a critical 3D morphology. This study highlights the effect of 3D geometry of plaque on its instability degree and suggests that 3D morphology of plaque might be necessary to more effectively and accurately assess atherosclerotic plaque vulnerability.

Keywords: atherosclerotic plaque, plaque rupture, finite element method, 3D model

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Authors: Misty Attwood, Helgi Schioth

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Transmembrane proteins are important components in many essential cell processes such as signal transduction, cell-cell signalling, transport of solutes, structural adhesion activities, and protein trafficking. Due to their involvement in diverse critical activities, transmembrane proteins are implicated in different disease pathways and hence are the focus of intense interest in understanding functional activities, their pathogenesis in disease, and their potential as pharmaceutical targets. Further, as the structure and function of proteins are correlated, investigating a group of proteins with the same tertiary structure, i.e., the same number of transmembrane regions, may give understanding about their functional roles and potential as therapeutic targets. In this in silico bioinformatics analysis, we identify and comprehensively characterize the previously unstudied group of proteins with five transmembrane-spanning regions (5TM). We classify nearly 60 5TM proteins in which 31 are members of ten families that contain two or more family members and all members are predicted to contain the 5TM architecture. Furthermore, nine singlet proteins that contain the 5TM architecture without paralogues detected in humans were also identifying, indicating the evolution of single unique proteins with the 5TM structure. Interestingly, more than half of these proteins function in localization activities through movement or tethering of cell components and more than one-third are involved in transport activities, particularly in the mitochondria. Surprisingly, no receptor activity was identified within this family in sharp contrast with other TM families. Three major 5TM families were identified and include the Tweety family, which are pore-forming subunits of the swelling-dependent volume regulated anion channel in astrocytes; the sidoreflexin family that acts as mitochondrial amino acid transporters; and the Yip1 domain family engaged in vesicle budding and intra-Golgi transport. About 30% of the proteins have enhanced expression in the brain, liver, or testis. Importantly, 60% of these proteins are identified as cancer prognostic markers, where they are associated with clinical outcomes of various tumour types, indicating further investigation into the function and expression of these proteins is important. This study provides the first comprehensive analysis of proteins with 5TM regions and provides details of the unique characteristics and application in pharmaceutical development.

Keywords: 5TM, cancer prognostic marker, drug targets, transmembrane protein

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Authors: Hailemeleak Regassa

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Traditional medicines use medicinal plants as a source of ingredients, and many modern medications are indirectly derived from plants. Consumers in affluent nations are growing disenchanted with contemporary healthcare and looking for alternatives. Oxidative stress is the primary cause of multiple diseases, and exogenous antioxidant supplementation or strengthening the body's endogenous antioxidant defenses are potential ways to counteract the negative effects of oxidative damage. Plants can biosynthesize non-enzymatic antioxidants that can reduce ROS-induced oxidative damage. Aging often aids the propagation and development of carcinogenesis, and older animals and older people exhibit increased vulnerability to tumor promoters. Cancer is a major public health issue, with several anti-cancer medications in clinical use. Potential drugs such as flavopiridol, roscovitine, combretastatin A-4, betulinic acid, and silvestrol are in the clinical or preclinical stages of research. Methodology: Microbial Growth media, Dimethyl sulfoxide (DMSO), methanol, ethyl acetate, and n-hexane were obtained from Himedia Labs, Mumbai, India. plant were collected from the Herbal Garden of Shoolini University campus, Solan, India (Latitude - 30.8644° N and longitude - 77.1184° E). The identity was confirmed by Dr. Y.S. Parmar University of Horticulture and Forestry, Nauni, Solan (H.P.), India, and documented in Voucher specimens - UHF- Herbarium no. 13784; vide book no. 3818 Receipt No. 086. The plant materials were washed with tap water, and 0.1% mercury chloride for 2 minutes, rinsed with distilled water, air dried, and kept in a hot air oven at 40ºc on blotting paper until all the water evaporated and became well dried for grinding. After drying, the plant materials were grounded using a mixer grinder into fine powder transferred into airtight containers with proper labeling, and stored at 4ºc for future use (Horablaga et al., 2023). The extraction process was done according to Altemimi et al., 2017. The 5g powder was mixed with 15 ml of the respective solvents (n-hexane, ethyl acetate, and methanol), and kept for 4-5 days on the platform shaker. The solvents used are based on their increasing polarity index. Then the extract was centrifuged at 10,000rpm for 5 minutes and filtered using No.1 Whatman filter paper.

Keywords: cancer, phytomedicine, medicinal plants, oncology

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Authors: Qasim Munye, Juned Islam, Haseeb Qureshi, Syed Jung

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Lung nodules are commonly identified in computed tomography (CT) scans by experienced radiologists at a relatively late stage. Early diagnosis can greatly increase survival. We propose using a pix2pix conditional generative adversarial network to generate realistic images simulating early-stage lung nodule growth. We have applied deep images prior to 2341 slices from 895 computed tomography (CT) scans from the Lung Image Database Consortium (LIDC) dataset to generate pseudo-healthy medical images. From these images, 819 were chosen to train a pix2pix network. We observed that for most of the images, the pix2pix network was able to generate images where the nodule increased in size and intensity across epochs. To evaluate the images, 400 generated images were chosen at random and shown to a medical student beside their corresponding original image. Of these 400 generated images, 384 were defined as satisfactory - meaning they resembled a nodule and were visually similar to the corresponding image. We believe that this generated dataset could be used as training data for neural networks to detect lung nodules at an early stage or to improve the accuracy of such networks. This is particularly significant as datasets containing the growth of early-stage nodules are scarce. This project shows that the combination of deep image prior and generative models could potentially open the door to creating larger datasets than currently possible and has the potential to increase the accuracy of medical classification tasks.

Keywords: medical technology, artificial intelligence, radiology, lung cancer

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Authors: Saba Gachpaz, Hamid Reza Heidari

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The sharp increase in population growth leads to more pressure on agricultural areas to satisfy the food supply. To achieve this, more resources should be consumed and, besides other environmental concerns, highlight sustainable agricultural development. Land-use management is a crucial factor in obtaining optimum productivity. Machine learning is a widely used technique in the agricultural sector, from yield prediction to customer behavior. This method focuses on learning and provides patterns and correlations from our data set. In this study, nine physical control factors, namely, soil classification, electrical conductivity, normalized difference water index (NDWI), groundwater level, elevation, annual precipitation, pH of water, annual mean temperature, and slope in the alluvial plain in Khuzestan (an agricultural hotspot in Iran) are used to decide the best agricultural land use for both rainfed and irrigated agriculture for ten different crops. For this purpose, each variable was imported into Arc GIS, and a raster layer was obtained. In the next level, by using training samples, all layers were imported into the python environment. A random forest model was applied, and the weight of each variable was specified. In the final step, results were visualized using a digital elevation model, and the importance of all factors for each one of the crops was obtained. Our results show that despite 62% of the study area being allocated to agricultural purposes, only 42.9% of these areas can be defined as a suitable class for cultivation purposes.

Keywords: land suitability, machine learning, random forest, sustainable agriculture

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Authors: Iva Zdrilić, Petra Došenović Bonča, Darija Aleksić

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Since the boundaryless career, with its emphasis on cross-employer movements, was introduced as a new paradigm of career development, inter-organizational employee mobility has been increasing. Although this phenomenon may have positive implications for individual careers and destination organizations, the consequences for the source organizations losing workers are less clear. The aim of this paper is thus to develop a comprehensive typology of possible inter-organizational employee mobility determinants. Since the most common classification differentiates between mobility determinants at different levels (i.e., economic, organizational, and individual), this paper focuses on building a comprehensive multi-level typology of inter-organizational mobility determinants across diverse sectors and industries. By using a structured literature review approach and bibliometric analysis, the paper reveals both intricate relationships between different mobility determinants and the complexity of inter-organizational networks and social ties. The latter appears as both a mobility determinant (at the organizational and individual level) and a mobility effect. Indeed, inter-organizational employee mobility leads to the formation of networks between source and destination organizations. These networks are practically based on the social ties between mobile employees and their colleagues and, in this way, they close the "inter-organizational employee mobility - inter-organizational network/ties" circle. The paper contributes to the career development literature by uncovering hitherto underexplored diverse determinants of intra- and inter-sectoral mobility as well as the conflicting results of the existing studies on some factors (e.g., inter-organizational networks and/or social ties) that appear both as a mobility determinant and a mobility effect.

Keywords: inter-organizational mobility, social ties, inter-organizational network, knowledge transfer

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Authors: A. A. M. A. S. S. Perera, L. A. Ranasinghe, T. K. H. Nimeshika, D. M. Dhanushka Dissanayake, Namalie Walgampaya

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Nowadays, skin fungal diseases are mostly found in people of tropical countries like Sri Lanka. A skin fungal disease is a particular kind of illness caused by fungus. These diseases have various dangerous effects on the skin and keep on spreading over time. It becomes important to identify these diseases at their initial stage to control it from spreading. This paper presents an automated skin fungal disease identification system implemented to speed up the diagnosis process by identifying skin fungal infections in digital images. An image of the diseased skin lesion is acquired and a comprehensive computer vision and image processing scheme is used to process the image for the disease identification. This includes colour analysis using RGB and HSV colour models, texture classification using Grey Level Run Length Matrix, Grey Level Co-Occurrence Matrix and Local Binary Pattern, Object detection, Shape Identification and many more. This paper presents the approach and its outcome for identification of four most common skin fungal infections, namely, Tinea Corporis, Sporotrichosis, Malassezia and Onychomycosis. The main intention of this research is to provide an automated skin fungal disease identification system that increase the diagnostic quality, shorten the time-to-diagnosis and improve the efficiency of detection and successful treatment for skin fungal diseases.

Keywords: Circularity Index, Grey Level Run Length Matrix, Grey Level Co-Occurrence Matrix, Local Binary Pattern, Object detection, Ring Detection, Shape Identification

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Authors: Puneet Goyal, Aarti Agarwal

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Background and Objective: Nutritional support is an integral part of palliative care of advanced non-resectable abdominal malignancy patients, though is frequently neglected aspect. Non-Healing high output Entero-cutaneous fistulas sometimes require long term parenteral nutrition, to take care of catabolism and replacement of nutrients. We present a case of inoperable pancreatic malignancy with high output entero-cutaneous fistula, which was provided parenteral nutritional support with the use of Totally Implantable Venous Access Device (TIVAD). Method and Results: 55 year old man diagnosed with carcinoma pancreas had developed high entero-cutaneous fistula. His tumor was found to be inoperable and was on total parenteral nutrition through routine central line. This line was difficult to maintain as he required it for a long term TPN. He was planned to undergo Totally Implantable Venous Access Device (TIVAD) implantation. 8Fr single lumen catheter with Groshong non-return Valve (Bard Access Systems, Inc. USA) was inserted through right internal jugular vein, under fluoroscopic guidance. The catheter was tunneled subcutaneously and brought towards infraclavicular pocket, cut at appropriate length and connected to port and locked. Port was sutured in floor of pocket. Free flow of blood aspirated, flushed with heparinized saline. There was no kink observed in entire length of catheter under fluoroscopy. Skin over infraclavicular pocket was sutured. Long term catheter care and associated risks were explained to patient and relatives. Patient continued to receive total parenteral nutrition as well as other supportive therapy though TIVAD for next 6 weeks, till his demise. Conclusion: TIVADs are standard of care for long term venous access solutions in cancer patients requiring chemotherapy. In this case, we extended its use for providing parenteral nutrition and other supportive therapy. TIVADs can be implanted in advanced cancer patients for providing venous access solution required for various palliative treatments and medications. This will help in improving quality of life and satisfaction amongst terminally ill cancer patients.

Keywords: parenteral nutrition, totally implantable venous access device, long term venous access, interventions in anesthesiology

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Authors: Xizhen Zhou, Yanjie Ji

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In advancing the management of integrated electric vehicle (EV) parking-charging behaviors, this study uses Changshu City in Suzhou as a case study to establish a data association mechanism for parking-charging platforms and to develop a database for EV parking-charging behaviors. Key indicators, such as charging start time, initial state of charge, final state of charge, and parking-charging time difference, are considered. Utilizing the K-S test method, the paper examines the heterogeneity of parking-charging behavior preferences among pure EV and non-pure EV users. The K-means clustering method is employed to analyze the characteristics of parking-charging behaviors for both user groups, thereby enhancing the overall understanding of these behaviors. The findings of this study reveal that using a classification model, the parking-charging behaviors of pure EVs can be classified into five distinct groups, while those of non-pure EVs can be separated into four groups. Among them, both types of EV users exhibit groups with low range anxiety for complete charging with special journeys, complete charging at destination, and partial charging. Additionally, both types have a group with high range anxiety, characterized by pure EV users displaying a preference for complete charging with specific journeys, while non-pure EV users exhibit a preference for complete charging. Notably, pure EV users also display a significant group engaging in nocturnal complete charging. The findings of this study can provide technical support for the scientific and rational layout and management of integrated parking and charging facilities for EVs.

Keywords: traffic engineering, potential preferences, cluster analysis, EV, parking-charging behavior

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Authors: Argyris B. Karapetsas, Rozi M. Laskaraki, Aikaterini A. Karapetsa, Maria Bampou, Valentini N. Vamvaka

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The main aim of the current protocol is the contribution of neuropsychology in both assessment and rehabilitation settings for children with dyslexia. Objectives: The purpose of this study was to evaluate the significant role of neuropsychological assessment including both Psychometric and electrophysiological tests as well as to investigate the effectiveness of an Auditory Training program, designed via Music designed for children with Developmental Dyslexia (DD). Materials: In our study, participated 45 third-, and fourth-grade students with DD and a matched control group (n=45). Method: At the first phase of the protocol, children underwent a clinical assessment, including both electrophysiological, i.e. Event Related Potentials (ERPs) esp. P300 waveform, and psychometric tests, being conducted in Laboratory of Neuropsychology, at University of Thessaly, in Volos, Greece. Assessment’s results confirmed statistically significant lower performance for children with DD for all tests, compared to the typical readers of the control group. After evaluation, a subgroup of children with DD participated in a Rehabilitation Program including digitized musical auditory training activities. Results: The electrophysiological recordings after the intervention revealed shorter, almost similar, P300 latency values for children with DD to those of the control group, indicating the beneficial effects of the Intervention, thus enabling children develop reading skills and become successful readers. Discussion: Similar research data confirm the crucial role of neuropsychology in both diagnosis and treatment of common disorders, observed in children. Indeed, as for DD, there is growing evidence that brain activity dysfunction does occur, as it is confirmed by neuropsychological assessment and also musical auditory training may have remedial effects. Conclusions: The outcomes of the current study suggest that due to the neurobiological origin of DD, neuropsychology may give the means in both neuropsychological assessment and rehabilitation, enabling professionals to cope with cerebral dysfunction and recovery more efficiently.

Keywords: diagnosis, dyslexia, ERPs, Music, neuropsychology, rehabilitation

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Authors: Sunil Kumar, Uday C. Ghoshal

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Background and aims: Serotonin (5-hydroxtryptamine, 5-HT) is an important factor in gut function, playing key roles in intestinal peristalsis and secretion, and in sensory signaling in the brain-gut axis. Removal from its sites of action is mediated by a specific protein called the serotonin reuptake transporter (SERT). Polymorphisms in the promoter region of the SERT gene have effects on transcriptional activity, resulting in altered 5-HT reuptake efficiency. Functional polymorphisms may underlie disturbance in gut function in individuals suffering with disorders such as irritable bowel syndrome (IBS). The aim of this study was to assess the potential association between SERT polymorphisms and the diarrhea predominant IBS (D-IBS) phenotype Subjects: A total of 36 northern Indian female patients and 55 female northern Indian healthy controls (HC) were subjected to genotyping. Methods: Leucocyte DNA of all subjects was analyzed by polymerase chain reaction based technologies for SERT polymorphisms, specifically the insertion/deletion polymorphism in the promoter (SERT-P). Statistical analysis was performed to assess association of SERT polymorphism allele with the D-IBS phenotype. Results: The frequency of distribution of SERT-P gene was comparable between female patients with IBS and HC (p = 0.086). However, frequency of SERT-P deletion/deletion genotype was significantly higher in female patients with D-IBS compared to C-IBS and A-IBS [17/19 (89.5%) vs. 4/12 (33.3%) vs. 1/5 (20%), p=0.001, respectively]. The mucosal level of serotonin was higher in D-IBS compared to C-IBS and A-IBS [Median, range (159.26, 98.78–212.1) vs. 110.4, 67.87–143.53 vs. 92.34, 78.8–166.3 pmol/mL, p=0.001, respectively]. The mucosal level of serotonin was higher in female patients with IBS with SERT-P deletion/deletion genotype compared deletion/insertion and insertion/insertion [157.65, 67.87–212.1 vs. 110.4, 78.1–143.32 vs. 100.5, 69.1–132.03 pmol/mL, p=0.001, respectively]. Patients with D-IBS with deletion/deletion genotype more often reported symptoms of abdominal pain, discomfort (p=0.025) and bloating (p=0.039). Symptoms development following lactose ingestion was strongly associated with D-IBS and SERT-P deletion/deletion genotype (p=0.004). Conclusions: Significant association was observed between D-IBS and the SERT-P deletion/deletion genotype, suggesting that the serotonin transporter is a potential candidate gene for D-IBS in women.

Keywords: serotonin, SERT, inflammatory bowel disease, genetic polymorphism

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Authors: Sandra Mitrovic, Gaurav Singh

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In many industries, including telecommunications, churn prediction has been a topic of active research. A lot of attention has been drawn on devising the most informative features, and this area of research has gained even more focus with spread of (social) network analytics. The call detail records (CDRs) have been used to construct customer networks and extract potentially useful features. However, to the best of our knowledge, no studies including network features have yet proposed a generic way of representing network information. Instead, ad-hoc and dataset dependent solutions have been suggested. In this work, we build upon a recently presented method (node2vec) to obtain representations for nodes in observed network. The proposed approach is generic and applicable to any network and domain. Unlike node2vec, which assumes a static network, we consider a dynamic and time-evolving network. To account for this, we propose an approach that constructs the feature representation of each node by generating its node2vec representations at different timestamps, concatenating them and finally compressing using an auto-encoder-like method in order to retain reasonably long and informative feature vectors. We test the proposed method on churn prediction task in telco domain. To predict churners at timestamp ts+1, we construct training and testing datasets consisting of feature vectors from time intervals [t1, ts-1] and [t2, ts] respectively, and use traditional supervised classification models like SVM and Logistic Regression. Observed results show the effectiveness of proposed approach as compared to ad-hoc feature selection based approaches and static node2vec.

Keywords: churn prediction, dynamic networks, node2vec, auto-encoders

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Authors: Ecem Deniz Kırkpantur, Ozge Ecmel Onur, Tuba Cimilli Ozturk, Ebru Unal Akoglu

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Moyamoya disease is a unique chronic progressive cerebrovascular disease characterized by bilateral stenosis or occlusion of the arteries around the circle of Willis with prominent arterial collateral circulation. The occurrence of Moyamoya disease is related to immune, genetic and other factors. There is no curative treatment for Moyamoya disease. Secondary prevention for patients with symptomatic Moyamoya disease is largely centered on surgical revascularization techniques. We present here a 62-year old male presented with headache and vision loss for 2 days. He was previously diagnosed with hypertension and glaucoma. On physical examination, left eye movements were restricted medially, both eyes were hyperemic and their movements were painful. Other neurological and physical examination were normal. His vital signs and laboratory results were within normal limits. Computed tomography (CT) showed dilated vascular structures around both lateral ventricles and atherosclerotic changes inside the walls of internal carotid artery (ICA). Magnetic resonance imaging (MRI) and angiography (MRA) revealed dilated venous vascular structures around lateral ventricles and hyper-intense gliosis in periventricular white matter. Ischemic gliosis around the lateral ventricles were present in the Digital Subtracted Angiography (DSA). After the neurology, ophthalmology and neurosurgery consultation, the patient was diagnosed with Moyamoya disease, pulse steroid therapy was started for vision loss, and super-selective DSA was planned for further investigation. Moyamoya disease is a rare condition, but it can be an important cause of stroke in both children and adults. It generally affects anterior circulation, but posterior cerebral circulation may also be affected, as well. In the differential diagnosis of acute vision loss, occipital stroke related to Moyamoya disease should be considered. Direct and indirect surgical revascularization surgeries may be used to effectively revascularize affected brain areas, and have been shown to reduce risk of stroke.

Keywords: headache, Moyamoya disease, stroke, visual loss

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Authors: Ghada Mahmoud El Kassas, Maged Atta El Wakeel

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Background: Environmental enteric dysfunction (EED) is impending trouble that flared up in the last decades to be pervasive in infants and children. EED is asymptomatic villous atrophy of the small bowel that is prevalent in the developing world and is associated with altered intestinal function and integrity. Evidence has suggested that supplementary zinc might ameliorate this damage by reducing gastrointestinal inflammation and may also benefit cognitive development. Objective: We tested whether zinc supplementation improves intestinal integrity, growth, and cognitive function in stunted children predicted to have EED. Methodology: This case–control prospective interventional study was conducted on 120 Egyptian Stunted children aged 1-10 years who recruited from the Nutrition clinic, the National research center, and 100 age and gender-matched healthy children as controls. At the primary phase of the study, Full history taking, clinical examination, and anthropometric measurements were done. Standard deviation score (SDS) for all measurements were calculated. Serum markers as Zonulin, Endotoxin core antibody (EndoCab), highly sensitive C-reactive protein (hsCRP), alpha1-acid glycoprotein (AGP), Tumor necrosis factor (TNF), and fecal markers such as myeloperoxidase (MPO), neopterin (NEO), and alpha-1-anti-trypsin (AAT) (as predictors of EED) were measured. Cognitive development was assessed (Bayley or Wechsler scores). Oral zinc at a dosage of 20 mg/d was supplemented to all cases and followed up for 6 months, after which the 2ry phase of the study included the previous clinical, laboratory, and cognitive assessment. Results: Serum and fecal inflammatory markers were significantly higher in cases compared to controls. Zonulin (P < 0.01), (EndoCab) (P < 0.001) and (AGP) (P < 0.03) markedly decreased in cases at the end of 2ry phase. Also (MPO), (NEO), and (AAT) showed a significant decline in cases at the end of the study (P < 0.001 for all). A significant increase in mid-upper arm circumference (MUAC) (P < 0.01), weight for age z-score, and skinfold thicknesses (P< 0.05 for both) was detected at end of the study, while height was not significantly affected. Cases also showed significant improvement of cognitive function at phase 2 of the study. Conclusion: Intestinal inflammatory state related to EED showed marked recovery after zinc supplementation. As a result, anthropometric and cognitive parameters showed obvious improvement with zinc supplementation.

Keywords: stunting, cognitive function, environmental enteric dysfunction, zinc

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