Search results for: pattern recognition receptor

Authors: Dileep Kumar, Janhavi Ramchandra Rao Kumar, Rao

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COVID-19 has ravaged the globe, and it is spreading its Spectre day by day. In the absence of established drugs, this disease has created havoc. Some of the infected persons are symptomatic or asymptomatic. The respiratory system, cardiac system, digestive system, etc. in human beings are affected by this virus. In our present investigation, we have undertaken a study of the Indian Ayurvedic herb, Ocimum sanctum against SARS-CoV-2 using molecular docking and dynamics studies. The docking analysis was performed on the Glide module of Schrödinger suite on two different proteins from SARS-CoV-2 viz. NSP15 Endoribonuclease and spike receptor-binding domain. MM-GBSA based binding free energy calculations also suggest the most favorable binding affinities of carvacrol, β elemene, and β caryophyllene with binding energies of −61.61, 58.23, and −54.19 Kcal/mol respectively with spike receptor-binding domain and NSP15 Endoribonuclease. It rekindles our hope for the design and development of new drug candidates for the treatment of COVID19.

Keywords: molecular docking, COVID-19, ocimum sanctum, binding energy

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Authors: Thuy Bui Anh, Ngan Nguyen Thi Thanh

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Currently, social work in Vietnam is entering the first step in the development process to become a true profession with a strong position in society. However, Spirit of helping and sharing of social work has already existed in the daily life of Vietnamese people for a very long time, becoming a precious heritage passed down from ancestors to the next generations while expanding the territory, building and defending for the country. Following the stream of history, charity work in Vietnam has gradually transformed itself towards a more professional work, especially in the last 2 decades. Accordingly, more than 50 universities and educational institutions in Vietnam have been licensed to train social work, ensuring a stronger foundation on human resources working in this field. Despite the strong growth, social work profession, social work education and the recognition of the role of the social workers still need to be fueled to develop, responded to the increasing demand of Vietnam society.

Keywords: education, history, recognition, social work, Vietnam

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Authors: Muhammad Azam, Micheal Olaolu Arowolo, Fei He, Mihail Popescu, Dong Xu

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The number of biological papers is growing quickly, which means that the number of biological pathway figures in those papers is also increasing quickly. Each pathway figure shows extensive biological information, like the names of genes and how the genes are related. However, manually annotating pathway figures takes a lot of time and work. Even though using advanced image understanding models could speed up the process of curation, these models still need to be made more accurate. To improve gene name recognition from pathway figures, we applied a Siamese network to map image segments to a library of pictures containing known genes in a similar way to person recognition from photos in many photo applications. We used a triple loss function and a triplet spatial pyramid pooling network by combining the triplet convolution neural network and the spatial pyramid pooling (TSPP-Net). We compared VGG19 and VGG16 as the Siamese network model. VGG16 achieved better performance with an accuracy of 93%, which is much higher than OCR results.

Keywords: biological pathway, image understanding, gene name recognition, object detection, Siamese network, VGG

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Authors: Yifang Gong

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Pulse diagnosis is one of the most important diagnosis methods in traditional Chinese medicine. It is also the trickiest method to learn. It is known as that it can only to be sensed not explained. This becomes a serious threat to the survival of this diagnostic method. However, there are a large amount of experiences accumulated during the several thousand years of practice of Chinese doctors. A pulse pattern called 'Slippery pulse' is one of the indications of pregnancy. A simple fluid dynamic model is proposed to simulate the effects of the existence of a placenta. The placenta is modeled as an extra plenum in an extremely simplified fluid network model. It is found that because of the existence of the extra plenum, indeed the pulse pattern shows a secondary peak in one pulse period. As for the author’s knowledge, this work is the first time to show the link between Pulse diagnoses and basic physical principle. Key parameters which might affect the pattern are also investigated.

Keywords: Chinese medicine, flow network, pregnancy, pulse

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Authors: Rui Liu, Pengyu Cui, Nan Jiang

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At present, there is much research on the application of centralized management and cross-integration application of basic geographic information. However, the idea of information integration and sharing between land, sea, and air navigation targets is not deeply applied into the research of navigation information service, especially in the information expression. Targeting at this problem, the paper carries out works about the expression pattern of navigation electronic map for ground vehicles under air and land united navigation mechanism. At first, with the support from multi-source information fusion of GIS vector data, RS data, GPS data, etc., an air and land united information expression pattern is designed aiming at specific navigation task of emergency rescue in the earthquake. And then, the characteristics and specifications of the united expression of air and land navigation information under the constraints of map load are summarized and transferred into expression rules in the rule bank. At last, the related navigation experiment is implemented to evaluate the effect of the expression pattern. The experiment selects evaluation factors of the navigation task accomplishment time and the navigation error rate as the main index, and make comparisons with the traditional single information expression pattern. To sum up, the research improved the theory of navigation electronic map and laid a certain foundation for the design and realization of united navigation system in the aspect of real-time navigation information delivery.

Keywords: navigation electronic map, united navigation, multi-element expression pattern, multi-source information fusion

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Authors: Henni Sid Ahmed, Belbachir Mohamed Faouzi, Jean Caelen

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Behavior recognition has been studied for realizing drivers assisting system and automated navigation and is an important studied field in the intelligent Building. In this paper, a recognition method of behavior recognition separated from a real image was studied. Images were divided into several categories according to the actual weather, distance and angle of view etc. SIFT was firstly used to detect key points and describe them because the SIFT (Scale Invariant Feature Transform) features were invariant to image scale and rotation and were robust to changes in the viewpoint and illumination. My goal is to develop a robust and reliable system which is composed of two fixed cameras in every room of intelligent building which are connected to a computer for acquisition of video sequences, with a program using these video sequences as inputs, we use SIFT represented different images of video sequences, and SVM (support vector machine) Lights as a programming tool for classification of images in order to classify people’s behaviors in the intelligent building in order to give maximum comfort with optimized energy consumption.

Keywords: video analysis, people behavior, intelligent building, classification

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Authors: Liang Ning, Chung Hau Yin

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Angiogenesis is the process of new blood vessel development. It has been recognized as a therapeutic target for blocking cancer growth four decades ago. Vascular sprouting is initiated by pro-angiogenic factors. Vascular endothelial cell growth factor (VEGF) plays a central role in angiogenic initiation, many patients with cancer or ocular neovascularization have been benefited from anti-VEGF therapy. Emerging approaches impacting in the later stages of vessel remodeling and maturation are expected to improve clinical efficacy. TIE receptor as well as the corresponding angiopoietin ligands, were identified as another endothelial cell specific receptor tyrosine kinase signaling system. Much efforts were made to reduce the activity of angiopoietin-TIE receptor axis. Two eudesmane-type sesquiterpenes from laggera alata, namely, 15-dihydrocostic acid and ilicic acid were found with strong anti-angiogenic properties in zebrafish model. Meanwhile, the mRNA expression levels of VEGFR2 and TIE2 pathway related genes were down-regulated in the sesquiterpenes treated zebrafish embryos. Besides, in human umbilical vein endothelial cells (HUVECs), the sesquiterpenes have the ability to inhibit VEGF-induced HUVECs proliferation and migration at non-toxic concentration. Moreover, angiopoietin-2 induced TIE2 phosphorylation was inhibited by the sesquiterpenes, the inhibitory effect was detected in angiopoietin-1 induced HUVECs proliferation as well. Thus, we hypothesized the anti-angiogenic activity of the compounds may via the inhibition of VEGF and TIE2 related pathways. How the compounds come into play as the pathways inhibitors need to be evaluated in the future.

Keywords: Laggera alata, eudesmane-type sesquiterpene, anti-angiogenesis, VEGF, angiopoietin, TIE2

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Authors: Huy Hieu Pham, Houssam Salmane, Louahdi Khoudour, Alain Crouzil, Pablo Zegers, Sergio Velastin

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We present a deep learning-based multitask framework for joint 3D human pose estimation and action recognition from color video sequences. Our approach proceeds along two stages. In the first, we run a real-time 2D pose detector to determine the precise pixel location of important key points of the body. A two-stream neural network is then designed and trained to map detected 2D keypoints into 3D poses. In the second, we deploy the Efficient Neural Architecture Search (ENAS) algorithm to find an optimal network architecture that is used for modeling the Spatio-temporal evolution of the estimated 3D poses via an image-based intermediate representation and performing action recognition. Experiments on Human3.6M, Microsoft Research Redmond (MSR) Action3D, and Stony Brook University (SBU) Kinect Interaction datasets verify the effectiveness of the proposed method on the targeted tasks. Moreover, we show that our method requires a low computational budget for training and inference.

Keywords: human action recognition, pose estimation, D-CNN, deep learning

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Authors: Kittitara Chunlakittiphan, Patompong Satapornpong

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Introduction: The variation of genetics affects how our body responds to pharmaceuticals elucidates the correlation between long-term use of medical cannabis and adverse drug reactions (ADRs). Medical cannabis is regarded as the treatment for chronic pain, cancer pain, acute pain, psychological disorders, multiple sclerosis and migraine management. However, previous studies have shown that delta-9-Tetrahydrocannabinol (THC), an ingredient found in cannabis, was the cause of ADRs in CB1 receptors found in humans. Previous research suggests that distributions of the cannabinoid type 1 (CB1) receptor gene and pharmacogenetic markers, which vary amongst different populations, might affect incidences of ADRs. Although there is an evident need to investigate the level of the CB1 receptor gene (rs806365), studies on the distribution of CB1-pharmacogenetics markers in Thai patients are limited. Objective: Therefore, the aim of this study is to investigate the distribution of the rs806365 polymorphism in Thai patients who have been treated with medical cannabis. Materials and Methods: We enrolled 31 Thai patients with THC-induced ADRs and 34 THC-tolerant controls to take part in this study. All patients with THC-induced ADRs were accessed through a review of medical records by physicians. EDTA blood of 3ml was collected to obtain the CNR1 gene (rs806365) and genotyping of this gene was conducted using the real-time PCR ViiA7 (ABI, Foster City, CA, USA) following the manufacturer’s instruction. Results: The sample consisted of 65 patients (40/61.54%) were females and (25/38.46%) were males, with an age range of 19-87 years, who have been treated with medical cannabis. In this study, the most common THC-induced ADRs were dry mouth and/or dry throat, tachycardia, nausea, and arrhythmia. Across the whole sample, we found that 52.31% of Thai patients carried a heterozygous variant (rs806365, CT allele). Moreover, the number of rs806365 (CC, homozygous variant) carriers totaled seventeen people (26.15%) amongst the subjects of Thai patients treated with medical cannabis. Furthermore, 17 out of 22 patients (77.27%) who experienced severe ADRs: Tachycardia and/or arrhythmia, carried an abnormal rs806365 gene (CT and CC alleles). Conclusions: The results propose that the rs806365 gene is widely distributed amongst the Thai population and there is a link between this gene and vulnerability to developing THC-induced ADRs after being treated with medical cannabis. Therefore, it is necessary to screen for the rs806365 gene before using medical cannabis to treat a patient.

Keywords: rs806365, THC-induced adverse drug reactions, CB1 receptor, Thai population

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Authors: Maha Jazouli

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Suicide is one of the most important causes of death in the prison environment, both in Canada and internationally. Rates of attempts of suicide and self-harm have been on the rise in recent years, with hangings being the most frequent method resorted to. The objective of this article is to propose a method to automatically detect in real time suicidal behaviors. We present a gesture recognition system that consists of three modules: model-based movement tracking, feature extraction, and gesture recognition using machine learning algorithms (MLA). Our proposed system gives us satisfactory results. This smart video surveillance system can help assist staff responsible for the safety and health of inmates by alerting them when suicidal behavior is detected, which helps reduce mortality rates and save lives.

Keywords: suicide detection, Kinect azure, RGB-D camera, SVM, machine learning, gesture recognition

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Authors: Oussama Hafferssas, Hiba Benyahia, Amina Madani, Nassima Zeriri

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Although data nowadays has multiple forms; from text to images, and from audio to videos, yet text is still the most used one at a public level. At an academical and research level, and unlike other forms, text can be considered as the easiest form to process. Therefore, a brunch of Data Mining researches has been always under its shadow, called "Text Mining". Its concept is just like data mining’s, finding valuable patterns in data, from large collections and tremendous volumes of data, in this case: Text. Named entity recognition (NER) is one of Text Mining’s disciplines, it aims to extract and classify references such as proper names, locations, expressions of time and dates, organizations and more in a given text. Our approach "Octopub" does not aim to find new ways to improve named entity recognition process, rather than that it’s about finding a new, and yet smart way, to use NER in a way that we can extract sentiments of millions of people using Social Networks as a limitless information source, and Marketing for product promotion as the main domain of application.

Keywords: textmining, named entity recognition(NER), sentiment analysis, social media networks (SN, SMN), business intelligence(BI), marketing

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Authors: Christian Arcos, Marley Vellasco, Abraham Alcaim

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In this paper, we present a wavelet coefficients masking based on Local Binary Patterns (WLBP) approach to enhance the temporal spectra of the wavelet coefficients for speech enhancement. This technique exploits the wavelet denoising scheme, which splits the degraded speech into pyramidal subband components and extracts frequency information without losing temporal information. Speech enhancement in each high-frequency subband is performed by binary labels through the local binary pattern masking that encodes the ratio between the original value of each coefficient and the values of the neighbour coefficients. This approach enhances the high-frequency spectra of the wavelet transform instead of eliminating them through a threshold. A comparative analysis is carried out with conventional speech enhancement algorithms, demonstrating that the proposed technique achieves significant improvements in terms of PESQ, an international recommendation of objective measure for estimating subjective speech quality. Informal listening tests also show that the proposed method in an acoustic context improves the quality of speech, avoiding the annoying musical noise present in other speech enhancement techniques. Experimental results obtained with a DNN based speech recognizer in noisy environments corroborate the superiority of the proposed scheme in the robust speech recognition scenario.

Keywords: binary labels, local binary patterns, mask, wavelet coefficients, speech enhancement, speech recognition

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Authors: Yili Chen, Xiaokun Liang, Zhicheng Zhang, Yaoqin Xie

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In an effort to restore visual perception in retinal diseases, an electronic retinal prosthesis with thousands of electrodes has been developed. The image processing strategies of retinal prosthesis system converts the original images from the camera to the stimulus pattern which can be interpreted by the brain. Practically, the original images are with more high resolution (256x256) than that of the stimulus pattern (such as 25x25), which causes a technical image processing challenge to do large-capacity image information reduction. In this paper, we focus on developing an efficient image processing stimulus pattern extraction algorithm by using a single cue saliency map for extracting salient objects in the image with an optimal trimming threshold. Experimental results showed that the proposed stimulus pattern extraction algorithm performs quite well for different scenes in terms of the stimulus pattern. In the algorithm performance experiment, our proposed SCSPE algorithm have almost five times of the score compared with Boyle’s algorithm. Through experiment s we suggested that when there are salient objects in the scene (such as the blind meet people or talking with people), the trimming threshold should be set around 0.4max, in other situations, the trimming threshold values can be set between 0.2max-0.4max to give the satisfied stimulus pattern.

Keywords: retinal prosthesis, image processing, region of interest, saliency map, trimming threshold selection

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Authors: Md. Khayrul Bashar, Md. Saiful Islam, Kimiko Yamashita, Yano Midori

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Despite having some progress in human authentication, conventional biometrics (e.g., facial features, fingerprints, retinal scans, gait, voice patterns) are not robust against falsification because they are neither confidential nor secret to an individual. As a non-invasive tool, electrocardiogram (ECG) has recently shown a great potential in human recognition due to its unique rhythms characterizing the variability of human heart structures (chest geometry, sizes, and positions). Moreover, ECG has a real-time vitality characteristic that signifies the live signs, which ensure legitimate individual to be identified. However, the detection accuracy of the current ECG-based methods is not sufficient due to a high variability of the individual’s heartbeats at a different instance of time. These variations may occur due to muscle flexure, the change of mental or emotional states, and the change of sensor positions or long-term baseline shift during the recording of ECG signal. In this study, a new method is proposed for human identification, which is based on the extraction of the local roughness of ECG heartbeat signals. First ECG signal is preprocessed using a second order band-pass Butterworth filter having cut-off frequencies of 0.00025 and 0.04. A number of local binary patterns are then extracted by applying a moving neighborhood window along the ECG signal. At each instant of the ECG signal, the pattern is formed by comparing the ECG intensities at neighboring time points with the central intensity in the moving window. Then, binary weights are multiplied with the pattern to come up with the local roughness description of the signal. Finally, histograms are constructed that describe the heartbeat signals of individual subjects in the database. One advantage of the proposed feature is that it does not depend on the accuracy of detecting QRS complex, unlike the conventional methods. Supervised recognition methods are then designed using minimum distance to mean and Bayesian classifiers to identify authentic human subjects. An experiment with sixty (60) ECG signals from sixty adult subjects from National Metrology Institute of Germany (NMIG) - PTB database, showed that the proposed new method is promising compared to a conventional interval and amplitude feature-based method.

Keywords: human identification, ECG biometrics, local roughness patterns, supervised classification

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Authors: John-Nelson Ekumah, Selorm Yao-Say Solomon Adade, Mingming Zhong, Yufan Sun, Qiufang Liang, Muhammad Safiullah Virk, Xorlali Nunekpeku, Nana Adwoa Nkuma Johnson, Bridget Ama Kwadzokpui, Xiaofeng Ren

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Enhancing starch gel strength and stability is crucial. However, traditional gel property assessment methods are destructive, time-consuming, and resource-intensive. Thus, understanding ethanol treatment effects on kudzu starch gel strength and developing a rapid, nondestructive gel strength assessment method is essential for optimizing the treatment process and ensuring product quality consistency. This study investigated the effects of different ethanol concentrations on the microstructure of kudzu starch gels using a comprehensive microstructural analysis. We also developed a nondestructive method for predicting gel strength and classifying treatment levels using near-infrared (NIR) spectroscopy, and advanced data analytics. Scanning electron microscopy revealed progressive network densification and pore collapse with increasing ethanol concentration, correlating with enhanced mechanical properties. NIR spectroscopy, combined with various variable selection methods (CARS, GA, and UVE) and modeling algorithms (PLS, SVM, and ELM), was employed to develop predictive models for gel strength. The UVE-SVM model demonstrated exceptional performance, with the highest R² values (Rc = 0.9786, Rp = 0.9688) and lowest error rates (RMSEC = 6.1340, RMSEP = 6.0283). Pattern recognition algorithms (PCA, LDA, and KNN) successfully classified gels based on ethanol treatment levels, achieving near-perfect accuracy. This integrated approach provided a multiscale perspective on ethanol-induced starch gel modification, from molecular interactions to macroscopic properties. Our findings demonstrate the potential of NIR spectroscopy, coupled with advanced data analysis, as a powerful tool for rapid, nondestructive quality assessment in starch gel production. This study contributes significantly to the understanding of starch modification processes and opens new avenues for research and industrial applications in food science, pharmaceuticals, and biomaterials.

Keywords: kudzu starch gel, near-infrared spectroscopy, gel strength prediction, support vector machine, pattern recognition algorithms, ethanol treatment

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Authors: Sourav Ray, Christoph Stein, Marcus Weber

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A new class of drug candidates, initially derived from mathematical modeling of ligand-receptor interactions, activate the μ-opioid receptor (MOR) preferentially at acidic extracellular pH-levels, as present in injured tissues. This is of commercial interest because it may preclude the adverse effects of conventional MOR agonists like fentanyl, which include but are not limited to addiction, constipation, sedation, and apnea. Animal studies indicate the importance of taking the pH value of the chemical environment of MOR into account when designing new drugs. Hydrogen bonds (HBs) play a crucial role in stabilizing protein secondary structure and molecular interaction, such as ligand-protein interaction. These bonds may depend on the pH value of the chemical environment. For the MOR, antagonist naloxone and agonist [D-Ala2,N-Me-Phe4,Gly5-ol]-enkephalin (DAMGO) form HBs with ionizable residue HIS 297 at physiological pH to modulate signaling. However, such interactions were markedly reduced at acidic pH. Although fentanyl-induced signaling is also diminished at acidic pH, HBs with HIS 297 residue are not observed at either acidic or physiological pH for this strong agonist of the MOR. Molecular dynamics (MD) simulations can provide greater insight into the interaction between the ligand of interest and the HIS 297 residue. Amino acid protonation states are adjusted to the model difference in system acidity. Unbiased and unrestrained MD simulations were performed, with the ligand in the proximity of the HIS 297 residue. Ligand-receptor complexes were embedded in 1-palmitoyl-2-oleoyl-sn glycero-3-phosphatidylcholine (POPC) bilayer to mimic the membrane environment. The occurrence of HBs between the different ligands and the HIS 297 residue of MOR at acidic and physiological pH values were tracked across the various simulation trajectories. No HB formation was observed between fentanyl and HIS 297 residue at either acidic or physiological pH. Naloxone formed some HBs with HIS 297 at pH 5, but no such HBs were noted at pH 7. Interestingly, DAMGO displayed an opposite yet more pronounced HB formation trend compared to naloxone. Whereas a marginal number of HBs could be observed at even pH 5, HBs with HIS 297 were more stable and widely present at pH 7. The HB formation plays no and marginal role in the interaction of fentanyl and naloxone, respectively, with the HIS 297 residue of MOR. However, HBs play a significant role in the DAMGO and HIS 297 interaction. Post DAMGO administration, these HBs might be crucial for the remediation of opioid tolerance and restoration of opioid sensitivity. Although experimental studies concur with our observations regarding the influence of HB formation on the fentanyl and DAMGO interaction with HIS 297, the same could not be conclusively stated for naloxone. Therefore, some other supplementary interactions might be responsible for the modulation of the MOR activity by naloxone binding at pH 7 but not at pH 5. Further elucidation of the mechanism of naloxone action on the MOR could assist in the formulation of cost-effective naloxone-based treatment of opioid overdose or opioid-induced side effects.

Keywords: effect of system acidity, hydrogen bond formation, opioid action, receptor activation

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Authors: Syed Asif Hassan, Tabrej Khan

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Multiple sclerosis (MS) is a chronic demyelinating autoimmune disorder, of the central nervous system (CNS). In the present scenario, the current therapies either do not halt the progression of the disease or have side effects which limit the usage of current Disease Modifying Therapies (DMTs) for a longer period of time. Therefore, keeping the current treatment failure schema, we are focusing on screening novel analogues of the available DMTs that specifically bind and inhibit the Sphingosine1-phosphate receptor1 (S1PR1) thereby hindering the lymphocyte propagation toward CNS. The novel drug-like analogs molecule will decrease the frequency of relapses (recurrence of the symptoms associated with MS) with higher efficacy and lower toxicity to human system. In this study, an integrated approach involving ligand-based virtual screening protocol (Ultrafast Shape Recognition with CREDO Atom Types (USRCAT)) to identify the non-toxic drug like analogs of the approved DMTs were employed. The potency of the drug-like analog molecules to cross the Blood Brain Barrier (BBB) was estimated. Besides, molecular docking and simulation using Auto Dock Vina 1.1.2 and GOLD 3.01 were performed using the X-ray crystal structure of Mtb LprG protein to calculate the affinity and specificity of the analogs with the given LprG protein. The docking results were further confirmed by DSX (DrugScore eXtented), a robust program to evaluate the binding energy of ligands bound to the ligand binding domain of the Mtb LprG lipoprotein. The ligand, which has a higher hypothetical affinity, also has greater negative value. Further, the non-specific ligands were screened out using the structural filter proposed by Baell and Holloway. Based on the USRCAT, Lipinski’s values, toxicity and BBB analysis, the drug-like analogs of fingolimod and BG-12 showed that RTL and CHEMBL1771640, respectively are non-toxic and permeable to BBB. The successful docking and DSX analysis showed that RTL and CHEMBL1771640 could bind to the binding pocket of S1PR1 receptor protein of human with greater affinity than as compared to their parent compound (Fingolimod). In this study, we also found that all the drug-like analogs of the standard MS drugs passed the Bell and Holloway filter.

Keywords: antagonist, binding affinity, chemotherapeutics, drug-like, multiple sclerosis, S1PR1 receptor protein

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Authors: B. J. Mahen, N. E. Lloyd-Gale, S. Johnson, W. P. Rakowicz, M. J. Harris, A. D. Miller

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Background: Migraine is a leading cause of disability in the world. Calcitonin gene-related peptide (CGRP) receptor antagonists offer an approach to migraine prophylaxis by inhibiting the inflammatory and vasodilatory effects of CGRP. In recent years, NICE licensed the use of three CGRP-receptor antagonists: Fremanezumab, Galcanezumab, and Erenumab. Here, we present the outcomes of CGRP-antagonist treatment in a cohort of patients who suffer from episodic or chronic migraine and have failed at least three oral prophylactic therapies. Methods: We offered CGRP antagonists to 86 patients who met the NICE criteria to start therapy. We recorded the number of headache days per month (HDPM) at 0 weeks, 3 months, and 12 months. Of those, 26 patients were switched to an alternative treatment due to poor response or side effects. Of the 112 total cases, 9 cases did not sufficiently maintain their headache diary, and 5 cases were not followed up at 3 months. We have therefore included 98 sets of data in our analysis. Results: Fremanezumab achieved a reduction in HDPM by 51.7% at 3 months (p<0.0001), with 63.7% of patients meeting NICE criteria to continue therapy. Patients trialed on Galcanezumab attained a reduction in HDPM by 47.0% (p=0.0019), with 51.6% of patients meeting NICE criteria to continue therapy. Erenumab, however, only achieved a reduction in HDPM by 17.0% (p=0.29), and this was not statistically significant. Furthermore, 34.4%, 9.7%, and 4.9% of patients taking Fremanezumab, Galcanezumab, and Erenumab, respectively, continued therapy beyond 12 months. Of those who attempted drug holidays following 12 months of treatment, migraine symptoms relapsed in 100% of cases. Conclusion: We observed a significant improvement in HDPM amongst episodic and chronic migraine patients following treatment with Fremanezumab or Galcanezumab.

Keywords: migraine, CGRP, fremanezumab, galcanezumab, erenumab

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Authors: Rutusha Bhutada, Gaurav Chavan, Sarvesh Kasat, Varsha Mujumdar

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This software system will be an Augmented Reality application designed to maximize the doctor’s productivity by providing tools to assist in automating the patient recognition and updating patient’s records using face and voice recognition features, which would otherwise have to be performed manually. By maximizing the doctor’s work efficiency and production, the application will meet the doctor’s needs while remaining easy to understand and use. More specifically, this application is designed to allow a doctor to manage his productive time in handling the patient without losing eye-contact with him and communicate with a group of other doctors for consultation, for in-place treatments through video streaming, as a video study. The system also contains a relational database containing a list of doctor, patient and display techniques.

Keywords: augmented reality, hand-held devices, head-mounted devices, marker based systems, speech recognition, face detection

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Authors: Sabrina Barsky, Ashley Monks

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In humans, exercise improves symptoms of various pathological states, although exercise adaptations seem to differ in response to sex. Skeletal muscle anabolism is thought to be regulated by androgen receptor (AR) through poorly specified mechanisms. Interactions of AR and exercise on muscle phenotype remain inconclusive in males, and undetermined in females. We hypothesized that sex differences in exercise adaptations are regulated by the androgenic system and the type of exercise performed. Here we examined interactions between a muscle-specific AR overexpression transgene (HSA-AR) and forced aerobic exercise paradigm on muscle and adipose exercise adaptation in male and female rats. We used dual-energy X-ray absorptiometry (DXA) to examine body composition adaptations post 9-week exercise protocol. We replicated the effects of HSA-AR on body composition, with males only having increased % lean mass and reduced % fat mass (P<0.05). Aerobic exercise improved lean body phenotype significantly, with lesser indices of total and % fat mass (P<0.01) in both sexes. Sex-specific effects of exercise included decreased total body mass (P<0.01) in males and increased lean mass % (P<0.001) in females. Surprisingly, neither AR manipulation nor exercise affected bone parameters in either sex. This varied response in total mass and lean mass according to exercise presents a sexually dimorphic response to exercise. Neither sex showed an interaction between HSA-AR and forced aerobic exercise on body composition. Future work is proposed to examine the effects of exercise type (aerobic versus resistance) and the role of gonadal androgens in sexually dimorphic exercise-mediated mitochondrial adaptations. This work implicates the development of sex-specific exercise therapies.

Keywords: androgen receptor, forced exercise, muscle physiology, sexual dimorphism

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Authors: Jesus Alfredo Ortega Granados, Pandiyan Thangarasu

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Antibiotic tetracycline presents as a micro-contaminant in fresh water, wastewater and soils, causing environmental and health problems. In this work, tetracycline (TC) has been employed as chemo-sensor for the recognition of Al³⁺ without interring other ions, and the results show that it enhances the fluorescence intensity for Al³⁺ and there is no interference from other coexisting cation ions (Cd²⁺, Ni²⁺, Co²⁺, Sr²⁺, Mg²⁺, Fe³⁺, K⁺, Sm³⁺, Ag⁺, Na⁺, Ba²⁺, Zn²⁺, and Mn²⁺). For the addition of Cu²⁺ to [TET-Al³⁺], it appears that the intensity of fluorescence has been quenched. Other combinations of metal ions in addition to TC do not change the fluorescence behavior. The stoichiometry determined by Job´s plot for the interaction of TC with Al³⁺ was found to be 1:1. Importantly, the detection of Al³⁺⁺ successfully employed in the real samples like living cells, and it was found that TC efficiently performs as a fluorescent probe for Al³⁺ ion in living systems, especially in Saccharomyces cerevisiae; this is confirmed by confocal laser scanning microscopy.

Keywords: chemo-sensor, recognition of Al³⁺ ion, Saccharomyces cerevisiae, tetracycline,

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Authors: Li Chen, Feng Zhang, Shizhong Zheng

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SaikosaponinD (SSD) is a major component of saikosaponins isolated from Bupleurumfalactum. Our current study was to examine the toxic effect of SSD on liver cells and explore the possible mechanism. The results demonstrated that SSD induced mouse liver injury and led to apoptosis in LO2 cells. HE staining and TUNEL analyses showed that SSD stimulated liver injury and hepatocyte apoptosis in vivo. Subsequent experiments showed that SSD down-regulated Bcl-2 but up-regulated Bax. In vitro, SSD-treated LO2 cells exhibited apparent down-regulated expression of p-p38. Moreover, PDGF-βR agonist PDGF-BB alone significantly upregulated p38 phosphorylation, while combined with SSD, p38 phosphorylation expression was reduced. Furthermore, shRNA-mediated PDGF-βR knockdown augmented the inactivation of p-p38 and Bcl2 but abrogated the activation of Bax, these results were more obvious when shRNA combined with SSD. These data indicated that SSD stimulated liver injury and apoptosis in hepatocytes and PDGF-βR /p38 pathway may be the potential mechanistic.

Keywords: saikosaponin D, hepatotoxicity, liver injury, apoptosis, platelet-derived growth factor-β receptor, p38

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Authors: R. R. Hordijk, O. J. G. Somsen

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Traditionally, radar systems are the eyes and ears of a ship. However, these systems have their drawbacks and nowadays they are extended with systems that work with video and photos. Processing of data from these videos and photos is however very labour-intensive and efforts are being made to automate this process. A major problem when trying to recognize objects in water is that the 'background' is not homogeneous so that traditional image recognition technics do not work well. Main question is, can a method be developed which automate this recognition process. There are a large number of parameters involved to facilitate the identification of objects on such images. One is varying the resolution. In this research, the resolution of some images has been reduced to the extreme value of 1% of the original to reduce clutter before the polynomial fit (pre-processing). It turned out that the searched object was clearly recognizable as its grey value was well above the average. Another approach is to take two images of the same scene shortly after each other and compare the result. Because the water (waves) fluctuates much faster than an object floating in the water one can expect that the object is the only stable item in the two images. Both these methods (pre-processing and comparing two images of the same scene) delivered useful results. Though it is too early to conclude that with these methods all image problems can be solved they are certainly worthwhile for further research.

Keywords: image processing, image recognition, polynomial fit, water

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Authors: M. Jazouli, S. Elhoufi, A. Majda, A. Zarghili, R. Aalouane

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Autism spectrum disorder is a complex developmental disability. It is defined by a certain set of behaviors. Persons with Autism Spectrum Disorders (ASD) frequently engage in stereotyped and repetitive motor movements. The objective of this article is to propose a method to automatically detect this unusual behavior. Our study provides a clinical tool which facilitates for doctors the diagnosis of ASD. We focus on automatic identification of five repetitive gestures among autistic children in real time: body rocking, hand flapping, fingers flapping, hand on the face and hands behind back. In this paper, we present a gesture recognition system for children with autism, which consists of three modules: model-based movement tracking, feature extraction, and gesture recognition using artificial neural network (ANN). The first one uses the Microsoft Kinect sensor, the second one chooses points of interest from the 3D skeleton to characterize the gestures, and the last one proposes a neural connectionist model to perform the supervised classification of data. The experimental results show that our system can achieve above 93.3% recognition rate.

Keywords: ASD, artificial neural network, kinect, stereotypical motor movements

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Authors: Naouel Zoghlami

Abstract:

Spoken-word recognition involves the simultaneous activation of potential word candidates which compete with each other for final correct recognition. In continuous speech, the activation-competition process gets more complicated due to speech reductions existing at word boundaries. Lexical processing is more difficult in L2 than in L1 because L2 listeners often lack phonetic, lexico-semantic, syntactic, and prosodic knowledge in the target language. In this study, we investigate the on-line lexical segmentation hypotheses that French listeners of L2 English form and then revise as subsequent perceptual evidence is revealed. Our purpose is to shed further light on the processes of L2 spoken-word recognition in context and better understand L2 listening difficulties through a comparison of skilled and unskilled reactions at the point where their working hypothesis is rejected. We use a variant of the gating experiment in which subjects transcribe an English sentence presented in increments of progressively greater duration. The spoken sentence was “And this amazing athlete has just broken another world record”, chosen mainly because it included common reductions and phonetic features in English, such as elision and assimilation. Our preliminary results show that there is an important difference in the manner in which proficient and less-proficient L2 listeners handle connected speech. Less-proficient listeners delay recognition of words as they wait for lexical and syntactic evidence to appear in the gates. Further statistical results are currently being undertaken.

Keywords: gating paradigm, spoken word recognition, online lexical segmentation, L2 listening

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Authors: Christine F. Boos, Fernando M. Azevedo

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Electroencephalogram (EEG) is a record of the electrical activity of the brain that has many applications, such as monitoring alertness, coma and brain death; locating damaged areas of the brain after head injury, stroke and tumor; monitoring anesthesia depth; researching physiology and sleep disorders; researching epilepsy and localizing the seizure focus. Epilepsy is a chronic condition, or a group of diseases of high prevalence, still poorly explained by science and whose diagnosis is still predominantly clinical. The EEG recording is considered an important test for epilepsy investigation and its visual analysis is very often applied for clinical confirmation of epilepsy diagnosis. Moreover, this EEG analysis can also be used to help define the types of epileptic syndrome, determine epileptiform zone, assist in the planning of drug treatment and provide additional information about the feasibility of surgical intervention. In the context of diagnosis confirmation the analysis is made using long term EEG recordings with at least 24 hours long and acquired by a minimum of 24 electrodes in which the neurophysiologists perform a thorough visual evaluation of EEG screens in search of specific electrographic patterns called epileptiform discharges. Considering that the EEG screens usually display 10 seconds of the recording, the neurophysiologist has to evaluate 360 screens per hour of EEG or a minimum of 8,640 screens per long term EEG recording. Analyzing thousands of EEG screens in search patterns that have a maximum duration of 200 ms is a very time consuming, complex and exhaustive task. Because of this, over the years several studies have proposed automated methodologies that could facilitate the neurophysiologists’ task of identifying epileptiform discharges and a large number of methodologies used neural networks for the pattern classification. One of the differences between all of these methodologies is the type of input stimuli presented to the networks, i.e., how the EEG signal is introduced in the network. Five types of input stimuli have been commonly found in literature: raw EEG signal, morphological descriptors (i.e. parameters related to the signal’s morphology), Fast Fourier Transform (FFT) spectrum, Short-Time Fourier Transform (STFT) spectrograms and Wavelet Transform features. This study evaluates the application of these five types of input stimuli and compares the classification results of neural networks that were implemented using each of these inputs. The performance of using raw signal varied between 43 and 84% efficiency. The results of FFT spectrum and STFT spectrograms were quite similar with average efficiency being 73 and 77%, respectively. The efficiency of Wavelet Transform features varied between 57 and 81% while the descriptors presented efficiency values between 62 and 93%. After simulations we could observe that the best results were achieved when either morphological descriptors or Wavelet features were used as input stimuli.

Keywords: Artificial neural network, electroencephalogram signal, pattern recognition, signal processing

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Authors: Ihtisham Bukhari

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In the current study, we enrolled a 46, XY phenotypically female patient bearing testes in her inguinal canal. DNA sequencing of the AR gene detected a missense mutation C.1715A > G (p. Y572C) in exon 2 which is already known to cause Complete androgen insensitivity syndrome (CAIS). We further studied the effects of this mutation on the testicular histopathology of the patient. No spermatocytes were seen in the surface spreading of testicular tissues while H&E staining showed that seminiferous tubules predominantly have only Sertoli cells. To confirm this meiotic failure is likely due to the current AR mutation we performed mRNA expression of genes associated with AR pathway, expression and location of the associated proteins in testicular tissues. Western blot and real-time PCR data showed that the patient had high levels of expression of AMH, SOX9, and INNB in testis. Tubules were stained with SOX9 and AMH which revealed Sertoli cell maturation arrest. Therefore, we suggest that AR mutation enhances AMH expression which ultimately leads to failure in the maturation of Sertoli cells and failure in spermatogenesis.

Keywords: androgen receptor, spermatogenesis, infertility, Sertoli cell only syndrome

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Authors: Syarif Hidayat

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As millions of people with different backgrounds perform hajj every year in Saudi Arabia, it brings out several problems. Missing people is among many crucial problems need to be encountered. Some people might have had insufficient knowledge of using tracking system equipment. Other might become a victim of an accident, lose consciousness, or even died, prohibiting them to perform certain activity. For those reasons, people could not send proper SOS message. The major contribution of this paper is the application of the diverse alert method in pilgrims tracking system. It offers a simple yet robust solution to send SOS message by pilgrims during Hajj. Knowledge of context aware computing is assumed herein. This study presents four methods that could be utilized by pilgrims to send SOS. The first method is simple mobile application contains only a button. The second method is based on behavior analysis based off GPS location movement anomaly. The third method is by introducing pressing pattern to smartwatch physical button as a panic button. The fourth method is by identifying certain accelerometer pattern recognition as a sign of emergency situations. Presented method in this paper would be an important part of pilgrims tracking system. The discussion provided here includes easy to use design whilst maintaining tracking accuracy, privacy, and security of its users.

Keywords: context aware computing, emergency alert system, GPS, hajj pilgrim tracking, location-based services

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Authors: Elham Sharif, Nasser Rizk, Sirin Abu Aqel, Ofelia Masoud

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Background: Previous studies have investigated the association of rs1544410, rs7975232 and rs731236 polymorphisms in vitamin D receptor gene and its impact on diseases such as cancer, diabetes and hypertension in different ethnic backgrounds. Aim: The aim of this study is to investigate the association between VDR polymorphisms using three SNP’s (rs1544410, rs7975232 and rs731236) and the severity of the significant lesion in coronary arteries among angiographically diagnosed CAD. Methods: A prospective-retrospective study was conducted on 192 CAD patients enrolled from the cardiology department-Heart Hospital HMC, grouped in 96 subjects with significant stenosis and 96 with non-significant stenosis with a mean age between 30 and 75 years old. Genotyping was performed for the following SNPs rs1544410, rs7975232 and rs731236 using TaqMan assay by the Real Time PCR, ABI 7500 in Health Sciences Labs at Qatar University Biomedical Research Center. Results: The results showed that both groups have matched age and gender distribution but patients with the significant stenosis have significantly higher; BMI (p=0.047); smoking status (p=0.039); FBS (p= 0.031); CK-MB (p=0.025) and Troponin (p=0.002) than the patients with non–significant lesion. Among the traditional risk factors, smoking increases the odds of the severe stenotic lesion in CAD patients by 1.984, with 95% CI between 1.024 – 7.063, with p= 0.042.HWE showed deviations of the rs1544410 and rs731236 among the study subjects. The most frequent genotype in distribution of rs7975232 is the AA among the significant stenosis patients, while the heterozygous AC was the frequent genotype in distribution among the non-significant stenosis group. The carriers of CC genotype in rs7975232 increased the risk of having significant coronary arteries stenotic lesion by 1.83 with 95% CI (1.020 – 3.280), p=0.043. No association was found between the rs7975232 with vitamin D and VDBP. Conclusion: There is a significant association between rs7975232 and the severity of CAD lesion. The carrier of CC genotype in rs7975232 increased the risk of having significant coronary arteries atherosclerotic lesion especially in patients with smoking history independent of vitamin D.

Keywords: vitamin D, vitamin D receptor, polymorphism, coronary harat disease

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Authors: Tomas Trainys, Algimantas Venckauskas

Abstract:

Application of biometric features to the cryptography for human identification and authentication is widely studied and promising area of the development of high-reliability cryptosystems. Biometric cryptosystems typically are designed for patterns recognition, which allows biometric data acquisition from an individual, extracts feature sets, compares the feature set against the set stored in the vault and gives a result of the comparison. Preprocessing and fusion of biometric data are the most important phases in generating a feature vector for key generation or authentication. Fusion of biometric features is critical for achieving a higher level of security and prevents from possible spoofing attacks. The paper focuses on the tasks of initial processing and fusion of multiple representations of finger vein modality patterns. These tasks are solved by applying conventional image preprocessing methods and machine learning techniques, Convolutional Neural Network (SVM) method for image segmentation and feature extraction. An article presents a method for generating sets of biometric features from a finger vein network using several instances of the same modality. Extracted features sets were fused at the feature level. The proposed method was tested and compared with the performance and accuracy results of other authors.

Keywords: bio-cryptography, biometrics, cryptographic key generation, data fusion, information security, SVM, pattern recognition, finger vein method.

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