bluuebunny/crossref_metadata_2025 huggingface dataset:
Abstract IA07: Identifying metabolic dependencies in pancreatic cancer
Authors: Kimmelman Alec
Published: December 2020

Pancreatic cancers are highly resistant to currently available therapeutics, which results in a 5-year survival rate of approximately 6%. We believe that this resistance points toward altered cell metabolic pathways. In this regard we have previously shown that that oncogenic Kras promotes a rewiring of pancreatic cancer metabolism, allowing carbon sources to be utilized in a variety of biosynthetic pathways. Importantly, several of these metabolic pathways are critical for tumor growth and therefore represent potential therapeutic targets. Ongoing studies from our group are exploring targeting various aspects of metabolism as therapeutic approaches. Additional studies from our group have demonstrated that pancreatic cancers have elevated basal autophagy, which is required for their continued growth. Importantly, inhibition of autophagy pharmacologically or genetically leads to decreased oxidative phosphorylation, a drop in ATP production, and ultimately growth inhibition. These findings have implicated autophagy as a key component of pancreatic cancer metabolism and have motivated the opening of multiple clinical trials assessing the efficacy of hydroxychloroquine as an autophagy inhibitor in pancreatic cancer. Recently, we have identified an autophagy-dependent metabolic crosstalk that exists between pancreatic tumor cells and the surrounding stroma. Ongoing work from our group seeks to understand the metabolic contributions that autophagy makes in pancreatic tumors. These and other aspects of pancreatic cancer metabolism will be discussed.

Citation Format: Alec Kimmelman. Identifying metabolic dependencies in pancreatic cancer [abstract]. In: Proceedings of the AACR Special Conference on Targeting PI3K/mTOR Signaling; 2018 Nov 30-Dec 8; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Res 2020;18(10_Suppl):Abstract nr IA07.
Abstract IA08: Pooled CRISPR screens for novel autophagy-related factors identify TMEM41, an ER-resident protein predicted to be a channel
Authors: Denic Vladimir
Published: December 2020

The power of forward genetics in yeast is the foundation on which the field of autophagy research firmly stands. Complementary work on autophagy in metazoans has revealed both the deep conservation of this process, as well as novel mechanisms by which autophagy is regulated in the context of development, immunity, and neuronal homeostasis. The recent emergence of new CRISPR/Cas9-based technologies has begun facilitating efforts to define novel autophagy factors and pathways by forward genetic screening in mammalian cells. Here, we set out to develop an expanded and improved toolkit of autophagy reporters for CRISPR/Cas9 screening. Genome-wide screening of our reporters in mammalian cells recovered virtually all known ATG factors as well as previously uncharacterized factors including VPS37A, TMEM251, ALS2, ACP1, and TMEM41B. To validate this dataset, we used quantitative microscopy and biochemical analyses to show that one novel hit, TMEM41B, is required for a late step in phagophore maturation. We found that TMEM41B is an integral ER membrane protein distantly related to the established autophagy factor VMP1, and our data show that these two factors play related, albeit not fully overlapping, roles in autophagosome biogenesis. In sum, our work uncovers new ATG factors, reveals a malleable network of autophagy receptor genetic interactions, and provides a valuable resource (http://crispr.deniclab.com) for further mining of novel autophagy mechanisms.

Citation Format: Vladimir Denic. Pooled CRISPR screens for novel autophagy-related factors identify TMEM41, an ER-resident protein predicted to be a channel [abstract]. In: Proceedings of the AACR Special Conference on Targeting PI3K/mTOR Signaling; 2018 Nov 30-Dec 8; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Res 2020;18(10_Suppl):Abstract nr IA08.
Abstract IA10: Structure and dynamics of Rag heterodimers in a complex with mTORC1
Authors: Anandapadamanaban Madhan , Perisic Olga , Berndt Alex , Masson Glenn R , Kaufman Jonathan , McLaughlin Stephen H. , Johnson Chris M. , Sabatini David M. , Williams Roger L.
Published: December 2020

Eukaryotic cells coordinate growth with the availability of nutrients through the protein kinase complex mTORC1, which is part of a pathway that is often upregulated in cancer. The mTORC1 complex is activated by association with two types of GTPases, Rags and RHEB. The heterodimeric Rag GTPases are key components in the activation of the mTORC1 pathway in response to amino acids. The Rag heterodimer interacts with the RAPTOR subunit of mTORC1 in a manner dependent on the nucleotide-bound states of its constituent GTPases. We used hydrogen/deuterium exchange mass spectrometry (HDX-MS) to map the interface of RAPTOR with an active Rag heterodimer, and we determined X-ray crystal structures of human Rag heterodimers in several nucleotide-bound states. Our high-resolution crystal structure of an oncogenic mutant heterodimer enabled us to interpret the cryo-EM structure of a complex of mTORC1 with the mutant RagA/C heterodimer. The cryo-EM structure shows that the G-domains from both Rags contact helical repeats of the RAPTOR subunit of mTORC1, but the GTP-bound RagA G domain forms almost all of the interface. The structure suggests how the nucleotide state of RagA is coordinated with the nucleotide state of RagC. The conformation of mTORC1 in a complex with the Rags is nearly identical to the apo mTORC1 complex, suggesting that the primary role of Rag binding is to recruit the mTORC1 complex to the lysosomal surface in the presence of the Ragulator complex.

Citation Format: Madhan Anandapadamanaban, Olga Perisic, Alex Berndt, Glenn R Masson, Jonathan Kaufman, Stephen H. McLaughlin, Chris M. Johnson, David M. Sabatini, Roger L. Williams. Structure and dynamics of Rag heterodimers in a complex with mTORC1 [abstract]. In: Proceedings of the AACR Special Conference on Targeting PI3K/mTOR Signaling; 2018 Nov 30-Dec 8; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Res 2020;18(10_Suppl):Abstract nr IA10.
Abstract IA26: Reprogramming tumor-associated macrophages by targeting PI3K-gamma with IPI-549
Authors: Kutok Jeffery L.
Published: December 2020

The PI3 kinases (PI3K) belong to a family of signal-transducing enzymes that mediate key cellular functions in cancer and immunity. The PI3K-gamma (γ) isoform is highly expressed in myeloid cells/macrophages and plays an important role in M2 macrophage polarization (Kaneda, Nature 2016). PI3K-γ knockout mice also demonstrated the role for PI3K-γ in tumor growth and immune tolerance (Gunderson, Cancer Discovery 2015; Kaneda, 2016). IPI-549 is an oral, potent, and selective inhibitor of PI3K-γ that shows single-agent antitumor activity in multiple murine tumor models (Kaneda, 2016) and enhanced antitumor activity and improved survival when combined with immune-checkpoint blockade (ICB) (De Henau, Nature 2016). This antitumor activity is dependent on the presence of both immune-suppressive tumor-associated CD11b+ myeloid cells and CD8+ cytotoxic T cells. IPI-549 can reduce the suppression of T-cell activity by both murine and human myeloid-derived suppressor cells in vitro and in vivo. IPI 549 treatment of tumor-bearing mice leads to a shift in tumor-associated myeloid cells from an immunosuppressive M2 phenotype to a proinflammatory M1 phenotype and an increased frequency of circulating tumor-specific T cells and tumor-infiltrating CD8+ T cells. In addition, preclinical tumor model systems show that resistance to ICB is directly mediated by the suppressive activity of infiltrating myeloid cells (De Henau, Nature 2016). Treatment of ICB-resistant 4T1 and B16GMCSF tumor-bearing mice with IPI-549 and anti-PD1 for 14 days led to a significant antitumor activity and an increased CD8+/T-reg cell ratio, confirming that selective pharmacologic targeting PI3K-γ by IPI-549 restores sensitivity to ICB. We are conducting a Ph 1/1b study IPI-549-01 (ClinicalTrials.gov NCT02637531) evaluating the safety, tolerability, pharmacokinetics, pharmacodynamics, and immunomodulatory activity of IPI-549 to determine its recommended phase 2 dose and preliminary clinical activity, as both a monotherapy and in combination with nivolumab, in patients with advanced solid tumors.

Citation Format: Jeffery L. Kutok. Reprogramming tumor-associated macrophages by targeting PI3K-gamma with IPI-549 [abstract]. In: Proceedings of the AACR Special Conference on Targeting PI3K/mTOR Signaling; 2018 Nov 30-Dec 8; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Res 2020;18(10_Suppl):Abstract nr IA26.
Abstract PR05: Regulation of mRNA N6-adenosine methylation by the mTOR signaling
Authors: Lee Gina , Cho Sungyun , Pickering Brian F. , Jang Cholsoon , Rabinowitz Joshua D. , Jaffrey Samie R. , Blenis John
Published: December 2020

N6-adenosine methylation (m6A) is the most abundant chemical modification on eukaryotic mRNA. Emerging evidence shows that alterations in m6A modifications on mRNAs encoding oncogenes and tumor suppressors drive cancer initiation and progression including leukemia, glioma, breast and lung cancers. A methyltransferase complex METTL3/METTL14/WTAP deposits methyl groups on mRNA, and then the m6A-marked mRNAs undergo various fates including changes in stability, localization, and translation efficiency. Through phosphoproteomic and transcriptomic analyses of mTOR signaling, we identified the methyltransferase complex as a novel downstream target of the mTOR pathway. We have also found that mTOR signaling, potentially through m6A methylation, regulates expression of the one-carbon metabolic pathway enzymes, which provide building blocks and methyl donors for growing cells. Together, our results indicate that mTOR signaling controls the activity of the methyltransferase complex to govern the m6A modifications of key mRNAs impacting tumor growth.

This abstract is also being presented as Poster A11.

Citation Format: Gina Lee, Sungyun Cho, Brian F. Pickering, Cholsoon Jang, Joshua D. Rabinowitz, Samie R. Jaffrey, John Blenis. Regulation of mRNA N6-adenosine methylation by the mTOR signaling [abstract]. In: Proceedings of the AACR Special Conference on Targeting PI3K/mTOR Signaling; 2018 Nov 30-Dec 8; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Res 2020;18(10_Suppl):Abstract nr PR05.
Abstract PR08: AKT mutant allele-specific activation dictates pharmacologic sensitivities
Authors: Bhattarai Tripti Shrestha , Shamu Tambudzai , Patel Swati , Gorelick Alexander , Chang Matthew T. , Gavrila Elena I. , Gao JianJong , Donoghue Mark T.A. , Gao Paul S. , Soumerai Tara , Abida Wassim , Smyth Lilian M. , Hyman David M. , Solit David B. , Taylor Barry S.
Published: December 2020

The objective of this study is to explore the biochemical characteristics and therapeutic sensitivity profiles of novel, non-E17K, less frequent AKT1 mutations, and thereby expand the biomarker of sensitivity to AKT inhibition in molecularly defined cancer patients. AKT is a critical signaling node that translates phosphoinositide 3-kinase (PI3K) pathway stimulation into diverse cellular effects. Gain-of-function AKT1 mutations arise in diverse human cancers, of which E17K is the most common. Presence of AKT1 E17K mutation renders these tumors susceptible to AKT inhibition. Nevertheless, the long tail of potentially activating mutations in AKT is largely uncharacterized, thereby limiting our ability to act clinically in prospectively sequenced advanced cancer patients. We performed a population-scale candidate driver mutation discovery analysis in AKT1, AKT2 and AKT3 in a cohort of 41,075 retrospectively and prospectively sequenced primary and metastatic cancers and explored both their functional and biologic impact as well as their therapeutic sensitivity. Our results demonstrated that some, but not all, of the identified AKT missense mutations activated PI3K signaling in a growth factor-independent manner, and sensitized tumor cells to diverse AKT inhibitors. By contrast, we discovered a different class of small in-frame paralogous AKT duplication mutants that induced distinctive structural changes, leading to a far greater degree of membrane affinity, AKT activation, pathway dependence, and hypersensitivity to ATP-competitive AKT inhibitors, while conferring resistance to allosteric AKT inhibitors. Leveraging a co-clinical trial framework, we are now enrolling patients on the basis of these mutations in a basket study involving AKT alterations. One such case was that of a castration-resistant metastatic prostate cancer patient who harbored AKT2 duplication mutant, and subsequently responded to AKT inhibition. Collectively, our data indicate that the degree and mechanism of activation of oncogenic AKT mutants vary, thereby dictating allele-specific pharmacologic sensitivities to AKT inhibition.

This abstract is also being presented as Poster B20.

Citation Format: Tripti Shrestha Bhattarai, Tambudzai Shamu, Swati Patel, Alexander Gorelick, Matthew T. Chang, Elena I. Gavrila, JianJong Gao, Mark T.A. Donoghue, Paul S. Gao, Tara Soumerai, Wassim Abida, Lilian M. Smyth, David M. Hyman, David B. Solit, Barry S. Taylor. AKT mutant allele-specific activation dictates pharmacologic sensitivities [abstract]. In: Proceedings of the AACR Special Conference on Targeting PI3K/mTOR Signaling; 2018 Nov 30-Dec 8; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Res 2020;18(10_Suppl):Abstract nr PR08.
There is a Strong Association between Early Preeclampsia and Congenital Heart Defects: A Large Population-Based, Retrospective Study
Authors: Liu Jie , Zhao Guanglin , Xie Jiansheng , Wu Shuhua , Li Bohong , Yao Jilong
Published: December 2020

Objective: The aim of this study was to determine the prevalence of congenital heart defects and examine their association with preeclampsia (PE). Methods: A clinical-based, retrospective study was conducted in Shenzhen between 2004 and 2017. Data were collected from Shenzhen Maternal and Child Health Hospital Medical Record Database. This study included all infants who were born at the hospital with or without heart defects and their mothers (N = 177,434 newborns). Data processing and analysis were performed by SPSS23.0 (Chicago, IL, USA). Results: 6,852 women (3.9%) were diagnosed as PE and 1,289 newborns (7.30 per 1,000) have congenital heart disease (CHD). Prevalence of CHD in newborns of women with PE is 15.8 per 1,000 significantly higher than the overall prevalence (7.30 per 1,000). CHD in newborns has strong association with PE, especially early-onset PE (adjusted OR 3.29 and 95% CI 2.15–5.03) and severe PE (adjusted OR 2.75 and 95% CI 2.13–3.56). Among those with CHD, infants of preeclamptic women had higher prevalence of tetralogy of Fallot (43.78 vs. 28.14 per 100,000), atrial septal defect (335.67 vs. 53.93 per 100,000), ventricular dysplasia (102.16 vs. 89.69 per 100,000), and ventricular septal defect (525.39 vs. 212.22 per 100,000) than pregnant women with non-PE. Conclusion: PE, especially early-onset PE and severe PE, is strongly associated with offspring CHD. Our results help advance the current understanding of the association between PE and offspring CHD. So preventing PE and reducing PE may have a beneficial effect on the offspring CHD.
The pH-Responsive Property of Antimicrobial Peptide GH12 Enhances Its Anticaries Effects at Acidic pH
Authors: Jiang Wentao , Luo Junyuan , Wang Yufei , Chen Xiangshu , Jiang Xuelian , Feng Zening , Zhang Linglin
Published: December 2020

Dental caries is closely related to the acidification of the biofilms on the tooth surface, in which cariogenic bacteria bring about a dramatic pH decrease and disrupt remineralisation equilibrium upon the fermentation of dietary sugars. Thus, approaches targeting the acidified niches with enhanced anticaries activities at acidic pH are highly desirable. In our previous study, a cationic amphipathic α-helical antimicrobial peptide GH12 (Gly-Leu-Leu-Trp-His-Leu-Leu-His-His-Leu-Leu-His-NH2) was designed with good stability, low cytotoxicity, and excellent antibacterial effects. Considering its potent antibacterial activity against the acidogenic bacteria and its histidine-rich sequence, it was speculated that GH12 might show enhanced antimicrobial effects at an acidic pH. In this study, the pH-responsive property of GH12 was determined to evaluate its potential as a smart acid-activated anticaries agent. GH12 possessed much lower minimal inhibitory concentrations and minimal bactericidal concentrations against various kinds of bacteria at pH 5.5 than at pH 7.2. Employing Streptococcus mutans, the principal caries pathogen, as the model system, it was found that GH12 showed much stronger bactericidal effects on both planktonic S. mutans and S. mutans embedded in the biofilm at pH 5.5. In addition, short-term treatment with GH12 showed much more effective inhibitory effects on water-insoluble exopolysaccharides synthesis and lactic acid production of the preformed S. mutans biofilm at pH 5.5. As for the mechanism exploration, it was found that the net positive charge of GH12 increased and the tryptophan fluorescence intensity heightened with the peak shifting towards the short wavelength at pH 5.5, which demonstrated that GH12 could be more easily attracted to the anionic microbial cell membranes and that GH12 showed stronger interactions with the lipid membranes. In conclusion, acidic pH enhanced the antibacterial and antibiofilm activities of GH12, and GH12 is a potential smart anticaries agent targeting the cariogenic acidic microenvironment.
Hyperinflammation and Immune Response Generation in COVID-19
Authors: Mishra Kamla Prasad , Singh Ajay Kumar , Singh Shashi Bala
Published: December 2020

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) that causes coronavirus disease 2019 (COVID-19) pandemic has affected millions of people worldwide. The pathophysiology of this virus is not very clearly known, thus, enormous efforts are being made by the scientific community to delineate its evading mechanism. In this review, we have summarized the hyperinflammation and humoral and cell-mediated immune response generated in human body after infection with the SARS-CoV-2 virus. The inflammatory response generated after infection by increased proinflammatory cytokines and chemokines, and complement proteins activation may likely contribute to disease severity. We also discussed the other factors that may affect immunity and could be important comorbidities in the disease severity and outcome.
Bleeding Duodenal Ulcer: Strategies in High-Risk Ulcers
Authors: Mille Markus , Engelhardt Thomas , Stier Albrecht
Published: December 2020

Background: Acute peptic ulcer bleeding is still a major reason for hospital admission. Especially the management of bleeding duodenal ulcers needs a structured therapeutic approach due to the higher morbidity and mortality compared to gastric ulcers. Patient with these bleeding ulcers are often in a high-risk situation, which requires multidisciplinary treatment. Summary: This review provides a structured approach to modern management of bleeding duodenal ulcers and elucidates therapeutic practice in high-risk situations. Initial management including pharmacologic therapy, risk stratification, endoscopy, surgery, and transcatheter arterial embolization are reviewed and their role in the management of bleeding duodenal ulcers is critically discussed. Additionally, a future perspective regarding prophylactic therapeutic approaches is outlined. Key Messages: Beside pharmacotherapeutic and endoscopic advances, bleeding management of high-risk duodenal ulcers is still a challenge. When bleeding persists or rebleeding occurs and the gold standard endoscopy fails, surgical and radiological procedures are indicated to manage ulcer bleeding. Surgical procedures are performed to control hemorrhage, but they are still associated with a higher morbidity and a longer hospital stay. In the meantime, transcatheter arterial embolization is recommended as an alternative to surgery and more often replaces surgery in the management of failed endoscopic hemostasis. Future studies are needed to improve risk stratification and therefore enable a better selection of high-risk ulcers and optimal treatment. Additionally, the promising approach of prophylactic embolization in high-risk duodenal ulcers has to be further investigated to reduce rebleeding and improve outcomes in these patients.
prosa latina ao volgare: O nascimento de uma identidade linguística para além da poesia
Authors: Brito Emanuel França
Published: December 2020

Neste artigo, busca-se ressaltar o papel da vulgarização de textos latinos, na Firenze do séc. XIII, na formação do panorama cultural em torno da língua volga- re. “Natural” e presente não apenas na oralidade como na poesia, essa língua passa a se afirmar gradualmente em estilo culto na prosa, aparecendo em vários gêneros: seja para a difusão de obras tratadísticas da retórica e oratória clássicas, como para obras filosóficas, morais, científicas, historiográficas, didáticas e ficcionais. A partir de então, o conhecimento teórico e as belas letras se dirigem a um público não apenas versado no idioma erudito da época, caracterizando um novo olhar sobre a comunicação escrita cuja expressão mais explícita e objetiva se encontra no Convívio de Dante. Entre as figuras de relevo em tal operação, destacamos Brunetto Latini e a sua Rettorica que, com uma finalidade assumidamente didática, traz do latim para o volgare parte do De inventione ciceroniano
sociolinguística no ensino de línguas: a variação diastrática em manuais didáticos de italiano
Authors: Frangiotti Graziele
Published: December 2020

As línguas naturais são formadas por um conjunto de variedades linguísticas resultantes das intensas relações entre língua e sociedade. No ensino de línguas estrangeiras, o livro didático se constitui como uma ferramenta que tem como principal função apresentar a língua aos aprendizes. Diante dessa responsabilidade, ele não deve escamotear elementos da língua com a escusa de simplificar a aprendizagem, mas sim preparar gradativamente o aprendiz para a complexa realidade com a qual se defrontará. Com base nesse pressuposto, o presente artigo tem como finalidade investigar como os livros didáticos Rete! e Linea diretta tratam a dimensão diastrática nos diálogos e explicações oferecidas a discentes e docentes. Para isso, foram definidos 28 critérios ligados a três variedades diastráticas, a saber: o italiano popular, o italiano falado por jovens e a variedade falada por mulheres (COVERI et al., 1998). Os resultados mostram a quase total ausência dessa dimensão nos livros e o tratamento insuficiente e inadequado das três variedades.
The Sanctuary and the Glacis: France, the Federal Republic of Germany, and the Nuclear Factor in the 1980s (Part 2)
Authors: Bozo Frédéric
Published: December 2020

This is the second of two articles exploring efforts at bridging the nuclear weapons gap between France and West Germany during the final decade of the Cold War. This gap existed in various ways: in the two countries’ respective international standing, with the relationship between Paris and Bonn complicated by France's possession of nuclear weapons; in their alliance choices, with their differing approaches to NATO military integration and strategy; and in their tactical nuclear military options (inseparable from conventional options), with the two countries fundamentally at odds over desirable procedures. The first article, published in the previous issue of the JCWS, explores the period from 1981 to 1986. This follow-on article covers the years 1986 to 1990. Although ultimately the dilemmas of nuclear sharing proved impossible to resolve, progress was made in the final years of the Cold War in narrowing differences between the two countries, whose bilateral relationship has been crucial for Europe and the West as a whole in the post–Cold War era.
Global Commons and the Law of the Sea: China’s Lawfare Strategy in the South China Sea
Authors: Hermez Marta
Published: December 2020

The portions of the South China Sea which fall outside the jurisdiction of any coastal state, are some of the world’s most important global maritime commons. Disputes over the maritime features and their surrounding waters of the South China Sea therefore threaten the governance of this global commons, both from a preservation and security perspective. This contribution analyses China’s lawfare strategy in the South China Sea by deconstructing its legal discourse on the matter. It will to that end scrutinize elements of China’s official and academic rhetoric, domestic legislation and operational conduct related to the South China Sea. The contribution will lay some groundwork for an enhanced engagement with China in the battle of the arguments on the South China Sea. In the same vein, it ultimately calls for further deepening our knowledge on China’s interpretation of the law of the sea and an increased interaction thereon in order to be better equipped to face China’s incremental geopolitical and discourse power and their influence on the future development of the legal global governance structure of the oceans.
Studies of Raspy Crickets: Magnumtergalis n. gen. a new gryllacrid genus with elongate male terminalia (Orthoptera: Gryllacrididae) from Colombia
Authors: CADENA-CASTAÑEDA OSCAR J. , GIRALDO CÉSAR QUIROGA , DÍAZ CARLOS JULIO ARANGO , SOTO WOLFANG ANDRÉS RODRÍGUEZ
Published: December 2020

Magnumtergalis n. gen. a new genus from the Inter-Andean Valleys and midlands of the Colombian Andes’ central cordillera is described. Two very peculiar species are placed within this genus, M. aldarioarenasi n. sp. (type species) and M. albonigra n. comb. An unusual terminalia to the family Gryllacrididae characterizes this genus, in which the ninth tergite is noticeably prolonged, covering the other structures of the male terminalia. This is the first genus of leaf-rolling crickets described from the Neotropics in the last 80 years.
Functional Testing on Heart Disease Detection Using Multilayer Perceptron Technique
Authors: Naresh E. , Naik Madhuri D. , Niranjanamurthy M. , Shankar Sahana P.
Published: December 2020

The proposed work shows how important and useful testing for any machine learning application and need to make better models such that bugs and errors are minimized. The proposed work considers patient’s health data which can be used for decision making or prediction using various
calculation, in this work, developing a heart condition prediction system mainly concentrating on artificial neural network, which uses the multilayer perceptron algorithm for the execution. Our dataset consists of vital information about the patient such as age, gender, blood pressure, ECG
measures, and stroke history. This labeled dataset predicts the probability of a patient to have heart diseases or not. To fulfill the proposed work, created a GUI to get the information about a new patient. Once the development of the model finished, complete functionality testing was applied.
The report of the testing helped in identifying the bugs and errors which on rectification by the developer helped in increasing the accuracy of the artificial neural network.
Realtime Learning and Attention Monitoring System for Competitive Exam Preparation
Authors: Spoorthi J. K. , Thejas B. C. , Manoj Kumar M. V.
Published: December 2020

This paper represents the development of an android application for the competitive exam preparation. The proposed application estimates the real-time learning and problem-solving ability of the user. It calculates the time taken by the user for each question and provides feedback and
to improve on the weak areas. The primary result of the project is to provide feedback to the user on the basis of time taken to solve each question and how many questions correctly/wrongly answered. With the help of this application, user can overcome his/her mistakes, and can try to improve
his weak areas.
Analysis of Energy Efficient Load Balancing of Virtual Machine in Cloud Environment
Authors: Jayasimha S. R. , Usha J. , Srivani Iyengar S. G.
Published: December 2020

Cloud computing is the hottest trend in distributed computing. It provides the services based on demand. The services are distributed such as applications, software’s and data bases. The data center handles 53% of load during the peak time. It consumes around 0.67 Zeta bytes of
data and the energy usage is 0.96 billion kilo watts of power during the peak time. The main challenge in the cloud data center is to manage load during the peak time. To reduce the energy consumption, the virtual machine needs to be reconfigured based on the memory, CPU usage and workload
conditions. In this paper, the Virtual Machine allocation is done using proposed method viz Multiplier algorithm and performance during different workload conditions are analyzed and it is found that the energy efficiency increases from 5% to 6% in the cloud data center.
Sentiment Analysis on Gujarati Text: A Survey
Authors: Shah Parita Vishal , Swaminarayan Priya
Published: December 2020

Internet is a source of huge amount of information generated from blog, social websites, and forums and so on by user. In today’s world information available on the internet plays an important role in human’s life. To analyze a huge amount of information it’s require
an automated method to classify this type of information. High usage of web and mobile technologies, user generated content in Guajarati is increasing on the web is motivation behind sentiment analysis. Emotion analysis is the process of identifying user’s opinion in section of text.
This opinion helps to carry out decisions. Now a day’s a new source of opinion for users are web documents. Sentiment analysis is natural language processing task that extract information from various sources such as news, social networking site, blog, forums and classify them into positive,
negative or neutral on the basis of their polarity. Lots of research is done in English language but it’s also important to perform sentiment analysis in Gujarati language as it is 6th official language in India. This paper gives an overview how sentiment analysis can be performed in
Gujarati Language.
Feature Learning Approach for Facial Recognition Using Deep Metric Learning
Authors: Karkal Gaurav , Dhanush Reddy K. , Singh Kaushik , Hosangadi Nikith , Patil Annapurna P.
Published: December 2020

Standard deep learning in the context of facial recognition involves inputting a single image and outputting a label for that image. Deep metric learning distinguishes itself by outputting a real valued feature vector instead of a single label. The usage of deep metric learning has
revolutionised facial recognition, making it very accurate and reliable. This paper exhibits the accuracy and reliability of the facial recognition model using deep metric learning in the application of an automated attendance system. The paper presents a non-intrusive attendance system which
uses the described neural network to recognize faces and record attendance. The system uses the pre-trained neural network to generate embeddings for faces, using a method known as the triple training step, which is described in the paper. These embeddings are generated from a collection of
photos per person. After the embeddings are generated, the system is ready to perform facial recognition on sample photos. CNN is used for facial detection in the sample group photos. Once the faces are detected, a KNN classifier is used for recognizing faces. Finally after the faces are recognized,
the attendance for each recognized student is marked in the database. Thus, the whole process of attendance was automated without the requirement of human interaction.
Smart Farm Monitoring Using Internet of Things and LoRa Technology Based on Wireless Sensor Networks
Authors: Revathi G. P. , Supreetha S.
Published: December 2020

In the recent years there has been rapid evolution in Smart farming and IOT. Farmers are interested in applying new technologies to their farm field to increase their crop yield, but only few farmers are able to apply this to their crop field due to many reasons like excessive cost,
lack of user friendliness. Most wireless communication innovations have high utilization of power and cover small transmission distance and therefore do not satisfy the prerequisites required for applications on IoT’s for establishing networks. Consequently, LoRa technology has been
proposed. LoRa™ is a low power wide area wireless network (LPWAN) protocol mainly used for applications based on Internet of Things (IoTs) technology. LPWAN ia a viable empowering innovation for largescale wireless sensor networks (WSNs). This paper proposes Monitoring of crop field
and Automatic irrigation using LoRa technology.
An Efficient Content Prefetching Method for Cloud Based Mobile Adhoc Network
Authors: Shashidhara D. N. , Chandrappa D. N. , Puttamadappa C.
Published: December 2020

Recently, Mobile Ad-hoc Networks (MANETs) has emerged as a very important research area for provisioning service for remote client through internet, cloud computing, and cellular network. This work focusses on improving image access in MANET. Various method has been present recently
for reducing data access and reduce query latency. Number challenges need to addressed such as caching, content prefetching, shared access environment, dynamic high speed node mobility environment etc. As mobile adhoc network is growing rapidly for the possessions of its capability in forming
provisional network without the requirement of any predefined infrastructure, improving throughput (i.e., access rate), reducing bit error rate (BER) (i.e., query latency) has been a major concern and requirement in mobile adhoc network. This work aimed at building an efficient content prefetching
technique of geographically distributed data for enhancing the access rate and reduce query latency. Along with, our model can minimize processing time and cost for carrying content prefetching operation. Experiment result shows the proposed content prefetching method improves bit error rate
(BER) and throughput performance.
Stress Level Detection Using Electroencephalography Signals
Authors: Suma K. V. , Venkatesh D. , Kumar Arun , Suryabhatla Manjula , Gowda Tejaswini M. , Thejashwini M.
Published: December 2020

Stress is the pressure that is experienced by humans. The impact of stress depends upon the type of stress the individual is experiencing. A positive stress may lead to the individual to feel motivated while a negative stress may impact the individual’s professional life or relationships.
In this work, the approach of detecting the level of individual stress through EEG signal is presented. The EEG signal consists of set of components like Alpha, Beta and Gamma, out of which the dominating component plays a crucial role in determining the stress level. Results shows that 93.33%,
83.33% and 90% of classification accuracy, 87.5%, 80% and 85.71% of sensitivity and 95.45%, 86.66% and 91.30% of specificity for low, medium and high stress respectively is obtained. This work can be used to analyze the region of brain that is contributing more towards the individual’s
stress.
Behavior of Low, Medium and High Rise Reinforced Concrete Frame with Infill Using ATENA 2D
Authors: Santhosh D. , Prabhakara R. , Ragavendra Prasad M. D.
Published: December 2020

The Low, Medium and High rise reinforced concrete (RC) buildings are common in all cities in all countries. Unreinforced masonry wall (URW) is commonly used in low, medium and high rise building as a partition wall both in interior and exterior of building. But structural designers
are not considered URW in analysis and design of buildings. This URM wall as an infill plays a very important role in structure subjected to lateral load. So it is very essential to know the nonlinear behavior of low, medium and high rise frame with and without infill. To conduct experiment
for understanding the nonlinear behaviour of low, medium and high rise RC frame is very expensive and need good sophisticated testing facilities. With the available many finite element softwares, it is easy to create model and to know the performance of structure. So in this study, a finite
element software ATENA 2D (2003) were used to conduct nonlinear analysis for capture nonlinear behaviour of low, medium and high rise RC frame with infill and without infill. Load versus displacement graphs, magnitude of principal compressive stresses, magnitude principal tensile stresses,
stress contours, and cracks pattern are used to know the performance of low, medium and high rise RC frame with infill.
Studies on Seismic Performance of Low, Medium and High Rise Reinforced Concrete Frame with Infill
Authors: Santhosh D. , Prabhakara R. , Jayaramappa N.
Published: December 2020

This paper studies the pushover analysis of Low, Medium and High Rise Reinforced Concrete (RC) frame with infill. Pushover analysis is nonlinear static procedures for the seismic assessment of Low, Medium and High Rise Reinforced concrete (RC) structures, due to its simplicity, efficiency
in modelling and low computational time. Four storey, Eight storey and Twelve storey RC frames with infill models were considered in this analysis. This pushover analysis was carried out for default hinge properties available in program based on FEMA 356. The seismic performance of RC frame
with infill was measured in terms of base force and displacement curve, performance point, number of plastic hinges at different performance levels.
Detection of Tumor Using Gabor Filter for Multimodal Images
Authors: Nandeesh M. D. , Meenakshi M.
Published: December 2020

Imaging segmentation techniques play a significant factor in medical justification for diagnosis and therapy application in healthcare industries. These noninvasive procedures assist the physician to visualize the vital part of the human body planned for treatment. Multimodal fused
images from Computer tomography (CT) and Magnetic resonance imaging (MRI) provides prominent results in detection of the tumor. Maximum information about the image cannot be obtained from individual technique to assess the location and its dimension of tumor. A fusion of multimodal images
like MRI and CT images are used to complimentary information and its segmentation to detect the presence or absence of tumor using objective method. In this paper fusion of CT and MRI is done by a hybrid technique by combining Principal Component Analysis (PCA) and Curvelet Transformation
(CVT). Gabor filter based segmentation of this image is applied as post-processing to obtain the presence of exact location of tumor in the image. Performance of fusion and segmentation is analyzed to obtain better quality image. The simulation consequence has shown better images using a hybrid
fusion algorithm and Gabor filter is used for assisting the physician to find the presence or absence of tumor. Proposed approach based on simulation results has shown a better efficiency as compared to individual techniques.
Computing Opinions for Twitter Review Data
Authors: Tenkale Pallavi S. , Jagannatha S.
Published: December 2020

Customers and users post their opinions or reviews on social networking sites and it has increased the amount of data WWW. With this users from all over world try to share their opinions and sentiments on the blogging sites every day. Internet is being used in form of web pages, social
media, and sometimes blogs which increases online portals sentiments, reviews, opinions, references, scores, and feedbacks are also generated by people. Twitter is the most famous micro-blogging site where users express their opinions in the form of tweets. The user can express their sentiments
about various aspects e.g., books, celebrities, restaurants, various products, research, events, etc. All these opinions plays vital roles and they are quite important for various businesses, for government schemes, and for individual human being as well. Still, there are many curbs in mining
reviews or opinions and process to calculate them. These limitations have turned into highland in investigating the actual gist of opinions and measuring its polarity. Hence, we recommend an inventive way to compute the sentiments for given reviews or opinions. This recommendation is centered
on the social networking sites’ information of various Tweets, a word-emotion-association-network is put up in association to represent opinions and semantics that decides the base for the emotions (sentiment) analysis of opinion or reviews.
Performance Enhancement of Image Stitching Process Under Bound Energy Aided Feature Matching and Varying Noise Environments
Authors: Patil Venkat P. , Ram Singla C.
Published: December 2020

Image mosaicing is a method that combines several images or pictures of the superposing field of view to create a panoramic high-resolution picture. In the field of medical imagery, satellite data, computer vision, military automatic target recognition can be seen the importance of
image mosaicing. The present domains of studies in computer vision, computer graphics and photo graphics are image stitching and video stitching. The registration of images includes five primary phases: feature detection and description; matching feature; rejection of outliers; transformation
function derivation; image replication. Stitching images from specific scenes is a difficult job when images can be picked up under different noise. In this paper, we examine an algorithm for seamless stitching of images in order to resolve all such problems by employing dehazing methods to
the collected images, and before defining image features and bound energy characteristics that match image-based features of the SIFT-Scale Invariant Feature Transform. The proposed method experimentation is compared with the conventional methods of stitching of image using squared distance
to match the feature. The proposed seamless stitching technique is assessed on the basis of the metrics, HSGV and VSGV. The analysis of this stitching algorithm aims to minimize the amount of computation time and discrepancies in the final stitched results obtained.
Real Time Image Fusion Based Technique for Medical Images
Authors: Ramya H. R. , Sujatha B. K.
Published: December 2020

To tackle the cost of storage and storage space with fast-growing technologies, the image fusion is playing an important role in several image-processing areas such as medical-imaging and satelliteimaging. This fused picture is appropriate for machine perception, human visual analysis
or further analysis assignment. Recently the computing method such as fuzzy logic model has been extensively used in the field of image-processing due to the uniqueness of handling uncertain modeling. The fuzzy logic based image-fusion model generally performed better with respect to other
existing image fusion models. In this paper, we considered type-2 fuzzy logic, which has similar function to earlier fuzzy logic technique but consist more functionality that allows optimized management of higher degrees under uncertainty. Interval type-2 fuzzy-logic-system (IT2FLS) are widely
used fuzzy sets due to their ease of use and computational simplicity. A real time image fusion (RTIF) technique that is based on the IT2FLS is used to overcome the excess computation time and nonlinear uncertainties, which is present in the medical images. In the result simulation section,
we have shown that our proposed model has taken less computation time and provided better quality assessment matrices with respect to existing system.
Performance Modeling of Energy Efficiency for Sensors Deployment in Embedded Wireless Sensor Networks
Authors: Kusuma S. M. , Veena K. N. , Vijaya Kumar B. P. , Varun B. V.
Published: December 2020

Present trend of Internet of Things (IoT) and sensors deployment increased in every sectors enormously from last one decade. But the deployment challenges of sensors and their networks with respect to their contextual dynamics and system performance is not much investigated. Hence there
is a need to investigate the deployment challenges of sensors supporting the computing system that exactly imitates the phenomenon by understanding the context and other influencing parameters, i.e., to sense the environmental parameter values accurately and precisely from the respective embedded
sensor system. In this paper, a methodology is proposed to analyze the performance of embedded Wireless Sensor Networks (eWSNs) with respect to energy efficiency based on sensors deployment. The method involves in clustering the sensor nodes based on distance from the phenomenon and its physical
location. Sensors and sensor network lifetime energy consumption for data acquisition is analyzed using Markovian model. Simulation platform for random deployment of sensor nodes along with Self Organizing map neural network for clustering with various cases of sensors deployment, network
dynamics and environment are studied to understand the performance of the embedded WSN system for energy efficiency.
Optimization Study of Blade Profiles of a Low-Pressure Compressor
Authors: Zhivirikhin Mikhail
Published: December 2020

This article discusses the optimization of blade profiles of a low-pressure compressor. The main research method was the combined use of fluid dynamics software (Ansys CFX) and parallel multiobjective optimization software (IOSO PM). To optimize the geometry of a low-pressure compressor,
parametric models of the blades were developed that control the curvature of the centerline, which provided a favorable shape of the profiles for supersonic flow regimes. Based on the conditions of limited resources for computing power and software licenses, an original way of decomposition
of the optimization problem is proposed. Improved blade profiles have significantly reduced kinetic energy losses. Optimization of the blades made it possible to increase efficiency while maintaining the performance parameters and dimensions of a low-pressure compressor, which is demonstrated
in the comparative characteristic.
A rare case of late-onset ticagrelor-induced sinus arrest
Authors: Aranganathan Prabhakaran , Wilson Bivin , Rangan Anandhakumar , Boopathi Arunkumar , Balasundaram Ramprakash
Published: December 2020

Ticagrelor is a potent reversible P2Y12 inhibitor with proven superiority over clopidogrel. Ticagrelor increases the tissue concentration of adenosine, thereby leading to bradyarrhythmia. This complication is reported to occur very early after initiating the drug. A randomized controlled trial reported that ticagrelor-induced pauses have an early onset without much clinical impact. However, our patient developed ticagrelor-induced hemodynamically significant sinus arrest 10 months after coronary artery stenting, which improved after stopping the drug. Ticagrelor should be considered as one of the uncommon reasons for late-onset sinus pause or bradyarrhythmia.
Pregabalin does not decrease acute pain or postoperative nausea and vomiting after hysterectomy: a meta-analysis
Authors: Ni Jie , Jiang Juan , Mao Shiqin , Sun Rui-fang
Published: December 2020

Objective

Hysterectomy is associated with severe postoperative pain. The relative efficacy of pregabalin compared with other treatments for post-hysterectomy pain is unclear.

Methods

We searched the PubMed, Cochrane Library, and Web of Science databases for studies that compared the use of pregabalin and placebo for reducing pain in patients undergoing hysterectomy.

Results

This meta-analysis showed that pregabalin had limited pain-relieving effects at 2, 6, 24, and 48 hours after hysterectomy compared with placebo. Pregabalin significantly reduced postoperative nausea and vomiting. However, there was no significant difference in postoperative sedation or visual disturbances between patients treated with pregabalin and placebo.

Conclusions

Pregabalin is not clinically superior to placebo in terms of reducing pain intensity and morphine consumption in patients undergoing hysterectomy. However, the limitations of this meta-analysis mean that more high-quality randomized controlled trials are necessary to verify our pooled results.