Search results for: biomarker discovery

Authors: Nanxi Miao, Junjie Wang

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The discovery of 2D materials with distinct compositions and properties has been a research aim since the report of graphene. One of the latest members of the 2D material family is MXene, which is produced from the topochemical deintercalation of the A layer from a laminate MAX phase. Recently, analogous 2D MBenes (transitional metal borides) have been predicted by theoretical calculations as excellent alternatives in applications such as metal-ion batteries, magnetic devices, and catalysts. However, the practical applications of two-dimensional (2D) transition-metal borides (MBenes) have been severely hindered by the lack of accessible MBenes because of the difficulties in the selective etching of traditional ternary MAB phases with orthorhombic symmetry (ort-MAB). Here, we discover a family of ternary hexagonal MAB (h-MAB) phases and 2D hexagonal MBenes (h-MBenes) by ab initio predictions and experiments. Calculations suggest that the ternary h-MAB phases are more suitable precursors for MBenes than the ort-MAB phases. Based on the prediction, we report the experimental synthesis of h-MBene HfBO by selective removal of in from h-MAB Hf2InB2. The synthesized 2D HfBO delivered a specific capacity of 420 mAh g-1 as an anode material in lithium-ion batteries, demonstrating the potential for energy-storage applications. The discovery of this h-MBene HfBO added a new member to the growing family of 2D materials and provided opportunities for a wide range of novel applications.

Keywords: 2D materials, DFT calculations, high-throughput screening, lithium-ion batteries

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Authors: M. Moslehpour, S. Khorsandi

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Due to shortage in IPv4 addresses, transition to IPv6 has gained significant momentum in recent years. Like Address Resolution Protocol (ARP) in IPv4, Neighbor Discovery Protocol (NDP) provides some functions like address resolution in IPv6. Besides functionality of NDP, it is vulnerable to some attacks. To mitigate these attacks, Internet Protocol Security (IPsec) was introduced, but it was not efficient due to its limitation. Therefore, SEND protocol is proposed to automatic protection of auto-configuration process. It is secure neighbor discovery and address resolution process. To defend against threats on NDP’s integrity and identity, Cryptographically Generated Address (CGA) and asymmetric cryptography are used by SEND. Besides advantages of SEND, its disadvantages like the computation process of CGA algorithm and sequentially of CGA generation algorithm are considerable. In this paper, we parallel this process between network resources in order to improve it. In addition, we compare the CGA generation time in self-computing and distributed-computing process. We focus on the impact of the malicious nodes on the CGA generation time in the network. According to the result, although malicious nodes participate in the generation process, CGA generation time is less than when it is computed in a one-way. By Trust Management System, detecting and insulating malicious nodes is easier.

Keywords: NDP, IPsec, SEND, CGA, modifier, malicious node, self-computing, distributed-computing

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Authors: Lamis Naddaf, Yuval Tabach

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In this research, we identified the missense genetic variants that have the potential to enhance resistance against cancer. Such field has not been widely explored, as researchers tend to investigate mutations that cause diseases, in response to the suffering of patients, rather than those mutations that protect from them. In conjunction with the genomic revolution, and the advances in genetic engineering and synthetic biology, identifying the protective variants will increase the power of genotype-phenotype predictions and can have significant implications on improved risk estimation, diagnostics, prognosis and even for personalized therapy and drug discovery. To approach our goal, we systematically investigated the sites of the coding genomes and picked up the alleles that showed a correlation with the species’ cancer resistance. We predicted 250 protecting variants (PVs) with a 0.01 false discovery rate and more than 20 thousand PVs with a 0.25 false discovery rate. Cancer resistance in Mammals and reptiles was significantly predicted by the number of PVs a species has. Moreover, Genes enriched with the protecting variants are enriched in pathways relevant to tumor suppression like pathways of Hedgehog signaling and silencing, which its improper activation is associated with the most common form of cancer malignancy. We also showed that the PVs are more abundant in healthy people compared to cancer patients within different human races.

Keywords: comparative genomics, machine learning, cancer resistance, cancer-protecting alleles

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Authors: Izabela P. Vatanabe, Rafaela Peron, Patricia Manzine, Marcia R. Cominetti

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Introduction: Considering the increase in life expectancy of world population, there is an emerging concern in health services to allocate better care and care to elderly, through promotion, prevention and treatment of health. It has been observed that frailty syndrome is prevalent in elderly people worldwide and this complex and heterogeneous clinical syndrome consist of the presence of physical frailty associated with cognitive dysfunction, though in absence of dementia. This can be characterized by exhaustion, unintentional weight loss, decreased walking speed, weakness and low level of physical activity, in addition, each of these symptoms may be a predictor of adverse outcomes such as hospitalization, falls, functional decline, institutionalization, and death. Cognitive frailty is a recent concept in literature, which is defined as the presence of physical frailty associated with mild cognitive impairment (MCI) however in absence of dementia. This new concept has been considered as a subtype of frailty, which along with aging process and its interaction with physical frailty, accelerates functional declines and can result in poor quality of life of the elderly. MCI represents a risk factor for Alzheimer's disease (AD) in view of high conversion rate for this disease. Comorbidities and physical frailty are frequently found in AD patients and are closely related to heterogeneity and clinical manifestations of the disease. The decreased platelets ADAM10 levels in AD patients, compared to cognitively healthy subjects, matched by sex, age and education. Objective: Based on these previous results, this study aims to evaluate whether ADAM10 platelet levels of could act as a biomarker of cognitive frailty. Methods: The study was approved by Ethics Committee of Federal University of São Carlos (UFSCar) and conducted in the municipality of São Carlos, headquarters of Federal University of São Carlos (UFSCar). Biological samples of subjects were collected, analyzed and then stored in a biorepository. ADAM10 platelet levels were analyzed by western blotting technique in subjects with MCI and compared to subjects without cognitive impairment, both with and without presence of frailty. Statistical tests of association, regression and diagnostic accuracy were performed. Results: The results have shown that ADAM10/β-actin ratio is decreased in elderly individuals with cognitive frailty compared to non-frail and cognitively healthy controls. Previous studies performed by this research group, already mentioned above, demonstrated that this reduction is still higher in AD patients. Therefore, the ADAM10/β-actin ratio appears to be a potential biomarker for cognitive frailty. The results bring important contributions to an accurate diagnosis of cognitive frailty from the perspective of ADAM10 as a biomarker for this condition, however, more experiments are being conducted, using a high number of subjects, and will help to understand the role of ADAM10 as biomarker of cognitive frailty and contribute to the implementation of tools that work in the diagnosis of cognitive frailty. Such tools can be used in public policies for the diagnosis of cognitive frailty in the elderly, resulting in a more adequate planning for health teams and better quality of life for the elderly.

Keywords: ADAM10, biomarkers, cognitive frailty, elderly

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Authors: Tracy Ho, Huann-Shyang Lin, Mina Lin

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This study investigated the different learning path of students with different learning attitude and learning styles in Arts Creation. Based on direct instruction, guided-discovery learning, and discovery learning theories, a tablet app including the following three learning areas were developed for students: (1) replication and remix practice area, (2) guided creation area, and (3) free creation area. Thirty. students with different learning attitude and learning styles were invited to use this app. Students’ learning behaviors were categorized and defined. The results will provide both educators and researchers with insights that can form a useful foundation for designing different content and strategy with the application of new technologies in school teaching. It also sheds light on how an educational App can be designed to enhance Arts Creation.

Keywords: App, arts creation, learning attitude, learning style, tablet

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Authors: Shaista Suhail

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As cancer populations is increasing sharply, the incidence of oral squamous cell carcinoma (OSCC) has also been expected to increase. Oral carcinogenesis is a highly complex, multistep process which involves accumulation of genetic alterations that lead to the induction of proteins promoting cell growth (encoded by oncogenes), increased enzymatic (telomerase) activity promoting cancer cell proliferation. The global increase in frequency and mortality, as well as the poor prognosis of oral squamous cell carcinoma, has intensified current research efforts in the field of prevention and early detection of this disease. The advances in the understanding of the molecular basis of oral cancer should help in the identification of new markers. The study of the carcinogenic process of the oral cancer, including continued analysis of new genetic alterations, along with their temporal sequencing during initiation, promotion and progression, will allow us to identify new diagnostic and prognostic factors, which will provide a promising basis for the application of more rational and efficient treatments. Telomerase activity has been readily found in most cancer biopsies, in premalignant lesions or germ cells. Activity of telomerase is generally absent in normal tissues. It is known to be induced upon immortalization or malignant transformation of human cells such as in oral cancer cells. Maintenance of telomeres plays an essential role during transformation of precancer to malignant stage. Mammalian telomeres, a specialized nucleoprotein structures are composed of large conctamers of the guanine-rich sequence 5_-TTAGGG-3_. The roles of telomeres in regulating both stability of genome and replicative immortality seem to contribute in essential ways in cancer initiation and progression. It is concluded that activity of telomerase can be used as a biomarker for diagnosis of malignant oral cancer and a target for inactivation in chemotherapy or gene therapy. Its expression will also prove to be an important diagnostic tool as well as a novel target for cancer therapy. The activation of telomerase may be an important step in tumorgenesis which can be controlled by inactivating its activity during chemotherapy. The expression and activity of telomerase are indispensable for cancer development. There are no drugs which can effect extremely to treat oral cancers. There is a general call for new emerging drugs or methods that are highly effective towards cancer treatment, possess low toxicity, and have a minor environment impact. Some novel natural products also offer opportunities for innovation in drug discovery. Natural compounds isolated from medicinal plants, as rich sources of novel anticancer drugs, have been of increasing interest with some enzyme (telomerase) blockage property. The alarming reports of cancer cases increase the awareness amongst the clinicians and researchers pertaining to investigate newer drug with low toxicity.

Keywords: oral carcinoma, telomere, telomerase, blockage

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Authors: Bela Siska Afrida, Wisnu Barlianto, Desy Wulandari, Ery Olivianto

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Background: Allergic asthma, caused by IgE-mediated allergic reactions, remains a global health issue with high morbidity and mortality rates. Immunotherapy is the only etiology-based approach to treating asthma, but no standard biomarkers have been established to evaluate the therapy’s effectiveness. This study aims to determine the correlation between the ratios of serum levels of HDM-specific IgE/total IgE and Asthma Control Test (ACT) score as a biomarker of the response to immunotherapy in pediatric allergic asthma patients. Patient and Methods: This retrospective cohort study involved 26 pediatric allergic asthma patients who underwent HDM-specific subcutaneous immunotherapy for 14 weeks at the Pediatric Allergy Immunology Outpatient Clinic at Saiful Anwar General Hospital, Malang. Serum levels of HDM-Specific IgE and Total IgE were measured before and after immunotherapy using Chemiluminescence Immunoassay and Enzyme-linked Immunosorbent Assay (ELISA) method. Changes in asthma control were assessed using the ACT score. The Wilcoxon Signed Ranked Test and Spearman correlation test were used for data analysis. Results: There were 14 boys and 12 girls with a mean age of 6.48 ± 2.54 years. The study showed a significant decrease in serum HMD-specific levels before immunotherapy [9.88 ± 5.74 kuA/L] compared to those of 14 weeks after immunotherapy [4.51 ± 3.98 kuA/L], p = 0.000. Serum Total IgE levels significant decrease before immunotherapy [207.6 ± 120.8IU/ml] compared to those of 14 weeks after immunotherapy [109.83 ± 189.39 IU/mL], p = 0.000. The ratios of serum HDM-specific IgE/total IgE levels significant decrease before immunotherapy [0.063 ± 0.05] compared to those of 14 weeks after immunotherapy [0.041 ± 0.039], p = 0.012. There was also a significant increase in ACT scores before and after immunotherapy (each 15.5 ± 1.79 and 20.96 ± 2.049, p = 0.000). The correlation test showed a weak negative correlation between the ratios of HDM-specific IgE/total IgE levels and ACT score (p = 0.034 and r = -0.29). Conclusion: In conclusion, this study showed that a decrease in HDM-specific IgE levels, total IgE levels, and HDM-specific IgE/total IgE ratios, and an increase in ACT score, was observed after 14 weeks of HDM-specific subcutaneous immunotherapy. The weak negative correlation between the HDM-specific IgE/total IgE ratio and the ACT score suggests that this ratio can serve as a potential biomarker of the effectiveness of immunotherapy in treating pediatric allergic asthma patients.

Keywords: HDM-specific IgE/total IgE ratio, ACT score, immunotherapy, allergic asthma

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Authors: Lorena GóMez Escorcia, Gustavo Aroca MartíNez, Jose Luiz Villarreal, Elkin Navarro Quiroz

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Lupus nephritis (LN) is a high-cost disease, occurring in about half of patients with Systemic Lupus Erythematosus (SLE). Renal biopsy constitutes the only protocol that, to date, allows a correct diagnosis of the level of renal involvement in these patients. However, this procedure can have various adverse effects such as kidney bleeding, muscle bleeding, infection, pain, among others. Therefore, the development of new diagnostic alternatives is required. The neutrophil gelatinase-associated lipocalin (NGAL) has been emerging as a novel biomarker of acute kidney injury. The aim of this study was to assess urinary NGAL levels as a marker for disease activity in patients with lupus nephritis. For this work included 50 systemic lupus erythematosus (SLE) patients, 50 with active lupus nephritis (LN), and 50 without autoimmune and renal disease as controls. TNGAL in urine samples was measured by enzyme-linked immunosorbent assay (ELISA). The results revealed that patients with kidney damage had an elevated urinary NGAL as compared to patients with lupus without kidney damage and controls (p <0.005), and the mean of uNGAL was (28.72 ± 4.53), (19.51 ± 4.72), (8.91 ± 3.37) respectively. Measurement of urinary NGAL levels showed a very good diagnostic performance for discriminating patients with Lupus nephritis from SLE without renal damage and of control individuals.

Keywords: lupus nephritis, biomarker, NGAL, urine samples

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Authors: Santony Santony, Teguh Rahayu Sartono, Iin Noor Chozin

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Introduction: Pneumonia is acute inflammation on lung parenchyma which is caused by bacteria, virus, fungi, or parasite. In Indonesia, Pneumonia is among the ten inpatient cases. Length of stay is related to the increased morbidity rate, nosocomial infection, and costs. The aim of this study is to assess the effect of pulmonary rehabilitation on the difference in length of stay and the level of Interleukin 6 (IL-6) as an inflammation biomarker for community-acquired pneumonia (CAP) patients in non-intensive rooms. Therefore, pulmonary rehabilitation as adjunctive therapy can be routinely exercised in order to shorten the length of stay, along with the decrease in IL-6 level. Methods: This study was conducted from May to October 2019 at Saiful Anwar General Hospital, Malang. 40 community-acquired pneumonia patients in non-intensive rooms were divided into two groups. 20 patients in the treatment group and 20 patients in the control group, all of them were selected through both inclusion and exclusion criteria. This study used simple consecutive random sampling. In the treatment group, pulmonary rehabilitation performed was composed of breathing exercise, effective coughing technique, clapping (percussion), postural drainage, as well as respiratory muscle training using incentive spirometry device. Pulmonary rehabilitation was conducted twice over five days with a minimum duration of 15 minutes. Blood samples were taken both on the first and the fifth day of the treatment to measure IL-6 level as an inflammation biomarker. Result: For the treatment group, the length of stay was 5.35 days whereas the control group 7.6 days. It can be seen that the treatment group had a shorter length of stay by 2.25 days (P<0,001). The IL-6 level on the first day for the treatment group was 36.27 pg/ml, whereas on the fifth day was 34.36 pg/ml. There was a decrease in IL-6 level on the fifth day of treatment even though it was not statistically significant (P=0.628). IL-6 level on the control group for the first day was 67.76 pg/ml, and after the fifth day, the level decreased to 54.43 pg/ml. There seemed to be a decrease in the IL-6, but it was not statistically significant (P=0.502). On the fifth day, the treatment group showed an average IL-6 level of 34.36 pg/ml. This value was lower than that of the control group which did not receive pulmonary rehabilitation having an IL-6 level of 54.43 pg/ml, even though it was not statistically significant (p=0.221). Conclusion: This study concluded that pulmonary rehabilitation as an adjunctive therapy shortened length of stay by 2.25 days for community-acquired pneumonia patients in a non-intensive room. Both groups experienced a decrease in IL-6 level on the fifth day in comparison with the first day even though it was not statistically significant P>0,05. IL-6 level as an inflammation biomarker decreased on the fifth day of treatment which was in accordance with improvement on pneumonia patients.

Keywords: community-acquired pneumonia, interleukin-6, length of stay, pulmonary rehabilitation

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Authors: Mouhammad Alkasassbeh, Mohammad Almseidin

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Network security engineers work to keep services available all the time by handling intruder attacks. Intrusion Detection System (IDS) is one of the obtainable mechanisms that is used to sense and classify any abnormal actions. Therefore, the IDS must be always up to date with the latest intruder attacks signatures to preserve confidentiality, integrity, and availability of the services. The speed of the IDS is a very important issue as well learning the new attacks. This research work illustrates how the Knowledge Discovery and Data Mining (or Knowledge Discovery in Databases) KDD dataset is very handy for testing and evaluating different Machine Learning Techniques. It mainly focuses on the KDD preprocess part in order to prepare a decent and fair experimental data set. The J48, MLP, and Bayes Network classifiers have been chosen for this study. It has been proven that the J48 classifier has achieved the highest accuracy rate for detecting and classifying all KDD dataset attacks, which are of type DOS, R2L, U2R, and PROBE.

Keywords: IDS, DDoS, MLP, KDD

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Authors: Erika Price, Lisa Johnson

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Cognitive and dispositional empathy is decreasing among students worldwide, particularly those at university. This paper looks at the effects of encouraging empathetic positioning in divisive topics by teaching listening skills and moral discovery to university students. Two groups of university students were given the assignment to interview individuals they disagreed with on social issues (e.g. abortion, gun control, legalization of drugs, involvement in Ukraine, etc.). One group completed the assignment with no other instruction. The second group completed the assignment after receiving instruction in active listening and Jonathan Haidt’s theory of moral foundations in politics. Results show that when students are given both active listening techniques and awareness of moral foundations, they are significantly more likely to have socially positive interactions with those they disagree with on issues as compared to those who listen passively to ideological opponents. As students interacted with those they disagreed with, they evidenced prosocial behaviors of acknowledgement, validation, and even commonalities with their opponents’ viewpoints, signifying a heartening trend of empathetic connection that is waning in students. The research suggests that empathy is a skill that can be nurtured by active listening but that it is more fully cultivated when paired with the concept of moral foundations underpinning political ideologies. These findings shed light on how to create more effective pedagogies for social and emotional learning, as well as inclusion.

Keywords: empathy, listening skills, moral discovery, pedagogy, prosocial behavior

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Authors: Adrian Millea

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In hierarchical reinforcement learning, one of the main issues encountered is the discovery of subgoal states or options (which are policies reaching subgoal states) by partitioning the environment in a meaningful way. This partitioning usually requires an expensive global clustering operation or eigendecomposition of the Laplacian of the states graph. We propose a local solution to this issue, much more efficient than algorithms using global information, which successfully discovers subgoal states by computing a simple function, which we call heterogeneity for each state as a function of its neighbors. Moreover, we construct a value function using the difference in heterogeneity from one step to the next, as reward, such that we are able to explore the state space much more efficiently than say epsilon-greedy. The same principle can then be applied to higher level of the hierarchy, where now states are subgoals discovered at the level below.

Keywords: exploration, hierarchical reinforcement learning, locality, options, value functions

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Authors: Hari Bezwada, Michelle Cheon, Ryan Divan, Hannah Escritor, Michelle Kagramian, Isha Korgaonkar, Maya MacAdams, Udgita Pamidigantam, Richard Pilny, Eleanor Race, Angadh Singh, Nathan Zhang, LeeAnn Nguyen, Fina Liotta

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Malaria is a deadly disease caused by the Plasmodium parasite, which continues to develop resistance to current antimalarial drugs. In this research project, the effectiveness of numerous thiazole derivatives was explored in inhibiting the PfPKG, a crucial part of the Plasmodium life cycle. This study involved the synthesis of six thiazole-derived amides to inhibit the PfPKG pathway. Nuclear Magnetic Resonance (NMR) spectroscopy and Infrared (IR) spectroscopy were used to characterize these compounds. Furthermore, AutoDocking software was used to predict binding affinities of these thiazole-derived amides in silico. In silico, compound 6 exhibited the highest predicted binding affinity to PfPKG, while compound 5 had the lowest affinity. Compounds 1-4 displayed varying degrees of predicted binding affinity. In-vitro, it was found that compound 4 had the best percent inhibition, while compound 5 had the worst percent inhibition. Overall, all six compounds had weak inhibition (approximately 30-39% at 10 μM), but these results provide a foundation for future drug discovery experiments.

Keywords: Medicinal Chemistry, Malaria, drug discovery, PfPKG, Thiazole, Plasmodium

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Authors: Basman Abdul Jabbar

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The researchers aimed to improve the importance of the good posture without any divisions & deformities. The importance of research lied in the discovery posture deformities early so easily treated before its transformation into advanced abnormalities difficult to treat and may need surgical intervention. Research problem was noting that some previous studies were based on the discovery of posture deformities, which was dependent on the (self-evaluation) which this type did not have accuracy to discover deformities. The Samples were (500) schoolchildren aged (9-11 years, males) at Baghdad al Karak. They were students at primary schools. The measure included all posture deformities. The researcher used video camera to analyze the posture deformities according to biomechanical variables by Kinovea software for motion analysis. The researcher recommended the need to use accurate scientific methods for early detection of posture deformities in children which contribute to the prevention and reduction of distortions.

Keywords: biomechanics, children, deformities, posture

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Authors: Jessica Chorostecki, Aashka Shah, Fen Bao, Ginny Bao, Edwin George, Navid Seraji-Bozorgzad, Veronica Gorden, Christina Caon, Elliot Frohman

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Background: Parkinson’s Disease (PD) is a neuro degenerative disorder associated with the loss of dopaminergic cells and the presence α-synuclein (AS) aggregation in of Lewy bodies. Both dopaminergic cells and AS are found in the retina. Optical coherence tomography (OCT) allows high-resolution in-vivo examination of retinal structure injury in neuro degenerative disorders including PD. Methods: We performed a cross-section OCT study in patients with definite PD and healthy controls (HC) using Spectral Domain SD-OCT platform to measure the peripapillary retinal nerve fiber layer (pRNFL) thickness and total macular volume (TMV). We performed intra-retinal segmentation with fully automated segmentation software to measure the volume of the RNFL, ganglion cell layer (GCL), inner plexiform layer (IPL), inner nuclear layer (INL), outer plexiform layer (OPL), and the outer nuclear layer (ONL). Segmentation was performed blinded to the clinical status of the study participants. Results: 101 eyes from 52 PD patients (mean age 65.8 years) and 46 eyes from 24 HC subjects (mean age 64.1 years) were included in the study. The mean pRNFL thickness was not significantly different (96.95 μm vs 94.42 μm, p=0.07) but the TMV was significantly lower in PD compared to HC (8.33 mm3 vs 8.58 mm3 p=0.0002). Intra-retinal segmentation showed no significant difference in the RNFL volume between the PD and HC groups (0.95 mm3 vs 0.92 mm3 p=0.454). However, GCL, IPL, INL, and ONL volumes were significantly reduced in PD compared to HC. In contrast, the volume of OPL was significantly increased in PD compared to HC. Conclusions: Our finding of the enlarged OPL corresponds with mRNA expression studies showing localization of AS in the OPL across vertebrate species and autopsy studies demonstrating AS aggregation in the deeper layers of retina in PD. We propose that the enlargement of the OPL may represent a potential biomarker of AS aggregation in PD. Longitudinal studies in larger cohorts are warranted to confirm our observations that may have significant implications in disease monitoring and therapeutic development.

Keywords: Optical Coherence Tomography, biomarker, Parkinson's disease, alpha-synuclein, retina

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Authors: Muhammet Baldan, Emel Timuçin

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Generally, absorption and bioavailability increase if solubility increases; therefore, it is crucial to predict them in drug discovery applications. Molecular descriptors and Molecular properties are traditionally used for the prediction of water solubility. There are various key descriptors that are used for this purpose, namely Drogan Descriptors, Morgan Descriptors, Maccs keys, etc., and each has different prediction capabilities with differentiating successes between different data sets. Another source for the prediction of solubility is structural features; they are commonly used for the prediction of solubility. However, there are little to no studies that combine three or more properties or descriptors for prediction to produce a more powerful prediction model. Unlike available models, we used a combination of those features in a random forest machine learning model for improved solubility prediction to better predict and, therefore, contribute to drug discovery systems.

Keywords: solubility, molecular descriptors, machine learning, random forest

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Authors: Salina Yahya Saddick

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Ovarian cancer remains the most lethal gynecological malignancy due to the lack of highly sensitive and specific screening tools for detection of early-stage disease. The OSE provides the progenitor cells for 90% of human ovarian cancers. Recent morphologic, immunohistochemical and molecular genetic studies have led to the development of a new paradigm for the pathogenesis and origin of epithelial ovarian cancer (EOC) based on a ualistic model of carcinogenesis that divides EOC into two broad categories designated Types I and II which are characterized by specific mutations, including KRAS, BRAF, ERBB2, CTNNB1, PTEN PIK3CA, ARID1A, and PPPR1A, which target specific cell signaling pathways. Type 1 tumors rarely harbor TP53. type I tumors are relatively genetically stable and typically display a variety of somatic sequence mutations that include KRAS, BRAF, PTEN, PIK3CA CTNNB1 (the gene encoding beta catenin), ARID1A and PPP2R1A but very rarely TP53 . The cancer stem cell (CSC) hypothesis postulates that the tumorigenic potential of CSCs is confined to a very small subset of tumor cells and is defined by their ability to self-renew and differentiate leading to the formation of a tumor mass. Potential protein biomarker miRNA, are promising biomarkers as they are remarkably stable to allow isolation and analysis from tissues and from blood in which they can be found as free circulating nucleic acids and in mononuclear cells. Recently, genomic anaylsis have identified biomarkers and potential therapeutic targets for ovarian cancer namely, FGF18 which plays an active role in controlling migration, invasion, and tumorigenicity of ovarian cancer cells through NF-κB activation, which increased the production of oncogenic cytokines and chemokines. This review summarizes update information on epithelial ovarian cancers and point out to the most recent ongoing research.

Keywords: epithelial ovarian cancers, somatic sequence mutations, cancer stem cell (CSC), potential protein, biomarker, genomic analysis, FGF18 biomarker

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Authors: Shajida M., Sakthiyadharshini N. P., Kamalesh S., Aswitha B.

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Natural Language Processing (NLP) continues to play a strategic part in complaint discovery and medicine discovery during the current epidemic. This abstract provides an overview of performance analysis with a combination of visualization and classification techniques of NLP for a medical chatbot. Sentiment analysis is an important aspect of NLP that is used to determine the emotional tone behind a piece of text. This technique has been applied to various domains, including medical chatbots. In this, we have compared the combination of the decision tree with heatmap and Naïve Bayes with Word Cloud. The performance of the chatbot was evaluated using accuracy, and the results indicate that the combination of visualization and classification techniques significantly improves the chatbot's performance.

Keywords: sentimental analysis, NLP, medical chatbot, decision tree, heatmap, naïve bayes, word cloud

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Authors: Shveta Bathla, Preeti Rawat, Sudarshan Kumar, Rubina Baithalu, Jogender Singh Rana, Tushar Kumar Mohanty, Ashok Kumar Mohanty

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Pregnancy is a complex process which includes series of events such as fertilization, formation of blastocyst, implantation of embryo, placental formation and development of fetus. The success of these events depends on various interactions which are synchronized by endocrine interaction between a receptive dam and competent embryo. These interactions lead to change in expression of hormones and proteins. But till date no protein biomarker is available which can be used to detect successful completion of these events. We employed quantitative proteomics approach to develop putative serological biomarker which has diagnostic applicability for early detection of pregnancy in cows. For this study, sera were collected from control (non-pregnant, n=6) and pregnant animals on successive days of pregnancy (7, 19, 45, n=6). The sera were subjected to depletion for removal of albumin using Norgen depletion kit. The tryptic peptides were labeled with iTRAQ. The peptides were pooled and fractionated using bRPLC over 80 min gradient. Then 12 fractions were injected to nLC for identification and quantitation in DDA mode using ESI. Identification using Mascot search revealed 2056 proteins out of which 352 proteins were differentially expressed. Twenty proteins were upregulated and twelve proteins were down-regulated with fold change > 1.5 and < 0.6 respectively (p < 0.05). The gene ontology studies of DEPs using Panther software revealed that majority of proteins are actively involved in catalytic activities, binding and enzyme regulatory activities. The DEP'S such as NF2, MAPK, GRIPI, UGT1A1, PARP, CD68 were further subjected to pathway analysis using KEGG and Cytoscape plugin Cluego that showed involvement of proteins in successful implantation, maintenance of pluripotency, regulation of luteal function, differentiation of endometrial macrophages, protection from oxidative stress and developmental pathways such as Hippo. Further efforts are continuing for targeted proteomics, western blot to validate potential biomarkers and development of diagnostic kit for early pregnancy diagnosis in cows.

Keywords: bRPLC, Cluego, ESI, iTRAQ, KEGG, Panther

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Authors: Tayyaba Bibi, Jenny Ronan, Robert Hernan, Kathleen O’Rourke, Brendan McHugh, Evin McGovern, Michelle Giltrap, Gordon Chambers, James Wilson

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Sediment contamination is a major source of ecosystem stress and has received significant attention from the scientific community. Both the Water Framework Directive (WFD) and Marine Strategy Framework Directive (MSFD) require a robust set of tools for biological and chemical monitoring. For the MSFD in particular, causal links between contaminant and effects need to be assessed. Appropriate assessment tools are required in order to make an accurate evaluation. In this study, a range of recommended sediment bioassays and chemical measurements are assessed in a number of potentially impacted and lowly impacted locations around Ireland. Previously, assessment indices have been developed on individual compartments, i.e. contaminant levels or biomarker/bioassay responses. A number of assessment indices are applied to chemical and ecotoxicological data from the Seachange project (Project code) and compared including the metal pollution index (MPI), pollution load index (PLI) and Chapman index for chemistry as well as integrated biomarker response (IBR). The benefits and drawbacks of the use of indices and aggregation techniques are discussed. In addition to this, modelling of raw data is investigated to analyse links between contaminant and effects.

Keywords: bioassays, contamination indices, ecotoxicity, marine environment, sediments

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Authors: Angelina A. Tzacheva, Jaishree Ranganathan

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Interest in (STEM) Science Technology Engineering Mathematics education especially Computer Science education has seen a drastic increase across the country. This fuels effort towards recruiting and admitting a diverse population of students. Thus the changing conditions in terms of the student population, diversity and the expected teaching and learning outcomes give the platform for use of Innovative Teaching models and technologies. It is necessary that these methods adapted should also concentrate on raising quality of such innovations and have positive impact on student learning. Light-Weight Team is an Active Learning Pedagogy, which is considered to be low-stake activity and has very little or no direct impact on student grades. Emotion plays a major role in student’s motivation to learning. In this work we use the student feedback data with emotion classification using surveys at a public research institution in the United States. We use Actionable Pattern Discovery method for this purpose. Actionable patterns are patterns that provide suggestions in the form of rules to help the user achieve better outcomes. The proposed method provides meaningful insight in terms of changes that can be incorporated in the Light-Weight team activities, resources utilized in the course. The results suggest how to enhance student emotions to a more positive state, in particular focuses on the emotions ‘Trust’ and ‘Joy’.

Keywords: actionable pattern discovery, education, emotion, data mining

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Authors: Teklay Gebrecherkos, Mahmud Abdulkader, Tobias Rinke De Wit, Britta C. Urban, Feyissa Chala, Yazezew Kebede, Dawit Welday

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Background: C-reactive protein (CRP) levels are a reliable surrogate for interleukin-6 bioactivity that plays a pivotal role in the pathogenesis of cytokine storm associated with severe COVID-19. There is a lack of data on the role of CRP as a determinant of COVID-19 severity status in the African context. Methods: We determined the longitudinal kinetics of CRP levels on 78 RT-PCR-confirmed COVID-19 patients (49 non-severe and 29 severe cases) and 50 PCR-negative controls. Results: COVID-19 patients had overall significantly elevated CRP at baseline when compared to PCR-negative controls [median 11.1 (IQR: 2.0-127.8) mg/L vs. 0.9 (IQR: 0.5-1.9) mg/L; p=0.0004)]. Moreover, severe COVID-19 patients had significantly higher median CRP levels than non-severe cases [166.1 (IQR: 48.6-332.5) mg/L vs. 2.4 (IQR: 1.2-7.6) mg/L; p<0.00001)]. In addition, persistently elevated levels of CRP were exhibited among those with comorbidities and higher age groups. Area under receiver operating characteristic curve (AUC) analysis of CRP levels distinguished PCR-confirmed COVID-19 patients from the ones with PCR-negative non-COVID-19 individuals, with an AUC value of 0.77 (95% CI: 0.68-0.84; p=0.001). Moreover, it clearly distinguished severe from non-severe COVID-19 patients, with an AUC value of 0.83 (95% CI: 0.73-0.91). After adjusting for age and the presence of comorbidities, CRP levels above 30 mg/L were significantly associated with an increased risk of developing severe COVID-19 (adjusted relative risk 3.99 (95%CI: 1.35-11.82; p=0.013). Conclusions: Determining CRP levels in COVID-19 patients in African settings may provide a simple, prompt, and inexpensive assessment of the severity status at baseline and monitoring of treatment outcomes.

Keywords: CRP, COVID-19, SARS-CoV-2, biomarker

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Authors: Rajeshwar Singh

Abstract:

The presence of multicollinearity is common in handling with several explanatory variables simultaneously due to exhibiting a linear relationship among them. A great problem arises in understanding the impact of explanatory variables on the dependent variable. Thus, the method of least squares estimation gives inexact estimates. In this case, it is advised to detect its presence first before proceeding further. Using the ridge regression degree of its occurrence is reduced but principal components regression gives good estimates in this situation. This paper discusses well-known techniques of the ridge and principal components regressions and applies to get the estimates of coefficients by both techniques. In addition to it, this paper also discusses the conflicting claim on the discovery of the method of ridge regression based on available documents.

Keywords: conflicting claim on credit of discovery of ridge regression, multicollinearity, principal components and ridge regressions, variance inflation factor

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Authors: Waseem Shahzad, Ayesha Tahir Khan, Hamid Hussain Awan

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Ant-Miner algorithm that lies under ACO algorithms is used to extract knowledge from data in the form of rules. A variant of Ant-Miner algorithm named as cAnt-MinerPB is used to generate list of rules using pittsburgh approach in order to maintain the rule interaction among the rules that are generated. In this paper, we propose a parallel Ant MinerPB in which Ant colony optimization algorithm runs parallel. In this technique, a data set is divided vertically (i-e attributes) into different subsets. These subsets are created based on the correlation among attributes using Mutual Information (MI). It generates rules in a parallel manner and then merged to form a final list of rules. The results have shown that the proposed technique achieved higher accuracy when compared with original cAnt-MinerPB and also the execution time has also reduced.

Keywords: ant colony optimization, parallel Ant-MinerPB, vertical partitioning, classification rule discovery

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Authors: Anis Belhaj Mohamed, Moncef Saidi, Mohamed Soussi, Ibrahim Bouazizi, Monia Ben Jrad

Abstract:

This paper summarizes the results of Rock-Eval pyrolysis and biomarker data of shale samples collected from the Ordovician age (Llanvirnian-Llandeilian) (Azzel Formation) in the Chotts basin southern part of Tunisia. The results are supported by analysis of cutting samples from wells. The Azzel shales has poor to moderate, occasionally good, potential for sourcing oil and gas with Total Organic Carbon (TOC) content varying from 0.80 to 4.49 % and petroleum potential (PP) values varying between 0.68 to 9.20 Kg of HC/t rock in Baguel and Alaguia wells. However, the Azzel Formation show poor to fair TOC and PP in Elfranig and HajBrahim wells not exceeding 1.10% and 1.05 kg HC/t of rock respectively. The Hydrogen Index (HI) and the Oxygen Index (OI) values of 95–165 mg S2/g TOC and of 33–108 mg CO2/g rock relatively show that the Ordovician shales exhibit type II Kerogen that reached the main oil window stage and that the organic matter was bad preserved, Tmax values of 435 – 448°C indicate the organic matter is mature. The biomarker features of the extract samples are characterized by high proportion of tricyclic terpanes that are dominated by C23 and C21 tricyclic terpanes. The hopanes fraction is dominated by C29 and C30 hopanes. The Ordovician shales show a predominance of C27 over C29 steranes (C27/C29>1) and relatively high proportions of diasteranes supporting the shaly character of the source rock.

Keywords: biomarkers, organic geochemistry, ordovician source rock, diasteranes

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Authors: Ahmadu Maidorawa, Kamalrulnizam Abu Bakar

Abstract:

This paper proposed an Enhanced Connectivity Aware Routing (ECAR) protocol for Vehicular Ad hoc Network (VANET). The protocol uses a control broadcast to reduce the number of overhead packets needed in a route discovery process. It is also equipped with an alternative backup route that is used whenever a primary path to destination failed, which highly reduces the frequent launching and re-launching of the route discovery process that waste useful bandwidth and unnecessarily prolonging the average packet delay. NS2 simulation results show that the performance of ECAR protocol outperformed the original connectivity aware routing (CAR) protocol by reducing the average packet delay by 28%, control overheads by 27% and increased the packet delivery ratio by 22%.

Keywords: alternative path, primary path, protocol, routing, VANET, vehicular ad hoc networks

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Authors: Rasha Ahmadi

Abstract:

Glioblastoma is one of the most frequent brain malignancies, having a high mortality rate and limited survival in individuals with this malignancy. Despite different treatments and surgery, recurrence of glioblastoma cancer stem cells may arise as a subsequent tumor. For this reason, it is crucial to research the markers associated with glioblastoma stem cells and specifically their microenvironment. In this study, using bioinformatics analysis, we analyzed and nominated genes in the microenvironment pathways of glioblastoma stem cells. In this study, an appropriate database was selected for analysis by referring to the GEO database. This dataset comprised gene expression patterns in stem cells derived from glioblastoma patients. Gene clusters were divided as high and low expression. Enrichment databases such as Enrichr, STRING, and GEPIA were utilized to analyze the data appropriately. Finally, we extracted the potential genes 2700 high-expression and 1100 low-expression genes are implicated in the metabolic pathways of glioblastoma cancer progression. Cellular senescence, MAPK, TNF, hypoxia, zimosterol biosynthesis, and phosphatidylinositol metabolism pathways were substantially expressed and the metabolic pathways were downregulated. After assessing the association between protein networks, MSMP, SOX2, FGD4 ,and CNTNAP3 genes with high expression and DMKN and SBSN genes with low were selected. All of these genes were observed in the survival curve, with a survival of fewer than 10 percent over around 15 months. hsa-mir-192-5p, hsa-mir-129-5p, hsa-mir-215-5p, hsa-mir-335-5p, and hsa-mir-340-5p played key function in glioblastoma cancer stem cells microenviroments. We introduced critical genes through integrated and regular bioinformatics studies by assessing the amount of gene expression profile data that can play an important role in targeting genes involved in the energy and microenvironment of glioblastoma cancer stem cells. Have. This study indicated that hsa-mir-192-5p, and hsa-mir-129-5p are appropriate candidates for this.

Keywords: Glioblastoma, Cancer Stem Cells, Biomarker Discovery, Gene Expression Profiles, Bioinformatics Analysis, Tumor Microenvironment

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Authors: Amer A. Hasan, Mehri Igci, Ersin Borazan, Rozhgar A. Khailany, Emine Bayraktar, Ahmet Arslan

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Gastric cancer (GC) has high morbidity and fatality rate in various countries and is still one of the most frequent and deadly diseases. Novel mitogenic and motogenic Gastrokine1 (GKN1) and Gastrokine 2 (GKN2) genes that are highly expressed in the normal stomach epithelium and plays an important role in maintaining the integrity and homeostasis of stomach mucosal epithelial cells. Significant loss of copy number and mRNA transcript of GKN1 and GKN2 gene expression were frequently observed in all types of gastric cancer. In this study, 47 paired samples that were grouped according to the types of gastric cancer and the clinical characteristics of the patients, including gender and average of age were investigated with gene expression analysis and mutation screening by monetering RT-PCR, SSCP and nucleotide sequencing techniques. Both GKN1 and GKN2 genes were observed significantly reduced found by (Wilcoxon signed rank test; p<0.05). As a result of gene screening, no mutation (no different genotype) was detected. It is considered that gene mutations are not the cause of inactivation of gastrokines. In conclusion, the mRNA expression level of GKN1 and GKN2 genes statistically was decreased regardless the gender, age or cancer type of patients. Reduced of gastrokine genes seems to occur at the initial steps of cancer development. In order to understand the investigation between gastric cancer and diagnostic biomarker; further analysis is necessary.

Keywords: gastric cancer, diagnostic biomarker, nucleotide sequencing, semi-quantitative RT-PCR

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Authors: Vahid Bairami Rad

Abstract:

Extracting knowledge from spatial data like GIS data is important to reduce the data and extract information. Therefore, the development of new techniques and tools that support the human in transforming data into useful knowledge has been the focus of the relatively new and interdisciplinary research area ‘knowledge discovery in databases’. Thus, we introduce a set of database primitives or basic operations for spatial data mining which are sufficient to express most of the spatial data mining algorithms from the literature. This approach has several advantages. Similar to the relational standard language SQL, the use of standard primitives will speed-up the development of new data mining algorithms and will also make them more portable. We introduced a database-oriented framework for spatial data mining which is based on the concepts of neighborhood graphs and paths. A small set of basic operations on these graphs and paths were defined as database primitives for spatial data mining. Furthermore, techniques to efficiently support the database primitives by a commercial DBMS were presented.

Keywords: spatial data base, knowledge discovery database, data mining, spatial relationship, predictive data mining

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Authors: S. Mahmoudi, A. Belhaj Mohamed, M. Saidi, F. Rezgui

Abstract:

Depositional environment and source potential of the different organic rich levels of Devonian age (up to 990m thick) from the onshore EC-1 well (Southern Tunisia) were investigated using different geochemical techniques (Rock-Eval pyrolysis, GC-MS) of over than 130 cutting samples. The obtained results including Rock Eval Pyrolysis data and biomarker distribution (terpanes, steranes and aromatics) have been used to describe the depositional environment and to assess the thermal maturity of the Devonian organic matter. These results show that the Emsian deposits exhibit poor to fair TOC contents. The associated organic matter is composed of mixed kerogen (type II/III), as indicated by the predominance of C29 steranes over C27 and C28 homologous, that was deposited in a slightly reduced environment favoring organic matter preservation. Thermal maturity assessed from Tmax, TNR and MPI-1 values shows a mature stage of organic matter. The Middle Devonian (Eifelian) shales are rich in type II organic matter that was deposited in an open marine depositional environment. The TOC values are high and vary between 2 and 7 % indicating good to excellent source rock. The relatively high IH values (reaching 547 mg HC/g TOC) and the low values of t19/t23 ratio (down to 0.2) confirm the marine origin of the organic matter (type II). During the Upper Devonian, the organic matter was deposited under variable redox conditions, oxic to suboxic which is clearly indicated by the low C35/C34 hopanes ratio, immature to marginally mature with the vitrinite reflectance ranging from 0.5 to 0.7 Ro and Tmax value of 426°C-436 °C and the TOC values range between 0.8% to 4%.

Keywords: biomarker, depositional environment, devonian, source rock

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