bluuebunny/crossref_metadata_2025 huggingface dataset:
An HADOOP File Systems Based Data Analysis of Flood Prediction
Authors: Sachin A. Thinesshar , Chandran R. Monish , Dhamodaran S. , Refonaa J. , Jany Shabu S. L.
Published: November 2020

One of the most well-known uses of Artificial Intelligence which has noticed an enormous development within the digital era is actually Machine Learning Techniques in which the method scientific studies and also increases the overall performance of its via progressive learning with
no explicit programming. It is popular within many programs certainly one of them becoming a weather condition prediction. Image distinction, as well as feature extraction, are regarded as to become essentially the most popularly pre-owned techniques finished utilizing machine mastering procedure.
With this proposed method, a hybrid model is developed for predicting rainfall by using feature extraction methods that have been proposed by us. The unit was created in such a manner it fetches a sequence of pictures originating from a data source as well as different info regarding earlier
rainfalls wearing a particular region. The pictures are actually pre-processed as well as additional segmented for option extraction. The segmented pictures are then categorized via the Random Forest algorithm in which the sequence of pictures is actually validated frame by frame. The effectiveness
of the suggested design is actually evaluated and it is kept in a sent out HADOOP File Systems (HDFS) for faster retrieval of information. It’s found that this suggested model provides greater results. The functionality of this unit tends to be more precise because the unit has an iterative
method for characteristic extraction inside classifying pictures. The suggested item is actually incorporated by using an aware process to be able to attain a warning or an alert to the individuals in a space properly prior to a flood really hits.
An Multi Variant Robust Methodology for Detecting the Phishing Websites
Authors: Praveen M. Sai , Gladence L. Mary , Reddy M. Rajasekhar , Refona J. , Nandhini Usha
Published: November 2020

Phishing attacks include the use of techniques to create polymorphic phishing web pages to give the impression of real sites. Other sites rely on the risk of phishing, including money linked, informal organizations, the travel industry, web-based business, and so on. For e.g., phishers
are specifically attached to travel-related administrations by mirroring them as excursion experts, aircraft reservations, accommodation bookings, and so on. Be that as it may, concentrating on reputable pages, given all, leaves the web page looking outwardly like the first one. Right now,
suggest a methodology that relies on the favicon database to discover the existence of the site and use it to determine the validity of the site. Phishing is a program that tricks individuals into giving touchy data such as usernames and passwords, paying card subtleties, delicate bank data,
and so on, by way of e-mail mocking, tweeting, or using counterfeit sites whose look and feel gives the presence of a real site Right now, a technique called parse tree approval is proposed to determine whether a website page is legitimate or phishing. This paper provides an in-depth study
of methods accessible to the detection of phishing sites. A similar research was carried out into the use of enemy phishing instruments and their containment was acknowledged. We have broken down the URL-based highlights used in the past to refine their meanings according to the current situation,
which is our major commitment. In addition, the step-by-step method of structuring the enemy of the phishing model is talked about developing a competent system that adds to our commitment. The views of this analysis are presented alongside recommendations on the existing frameworks.
Serverless Computing Using Amazon Web Services
Authors: Roobini M. S. , Sampathkumar Selvasurya , Basha Shaik Khadar , Ponraj Anitha
Published: November 2020

In the last decade cloud computing transformed the way in which we build applications. The boom in cloud computing helped to develop new software design and architecture. Helping the developers to focus more on the business logic than the infrastructure. FaaS (function as a service)
compute model it gave developers to concentrate only on the application code and rest of the factors will be taken care by the cloud provider. Here we present a serverless architecture of a web application built using AWS services and provide detail analysis of lambda function and micro service
software design implemented using these AWS services.
Active Validation with Sensory Data for Access Control System
Authors: Chittaturi Lalitha , Venkata Chittabatteni Sravani N. , Bharathi B.
Published: November 2020

This paper covers the main motive of using motion sensors and how to protect the information from unauthorized use. It defines the accelerometer motion sensor for obtaining aboutx,y, andz-axis of a device. It maintains fewer vulnerabilities so that there is no chance of intruder attacks. Using wireless sensors makes the application more efficient and high security with low cost as these sensors are already present in the device and that can be used either in Android and Web applications. It discusses algorithms like Advance Standard Encryption and techniques like data preprocessing, f-vector extraction and f-vector matching. The main objective is (i) It is completely based on the user movement (ii) It generates a one-time-password based on the rotation of the device (iii) It picks one of the one-time-password as its password. It shows that the analysts, cell phone sellers and application engineers would site to focus on movement sensors and uphold to structure convey viable guard systems.
Absolute Transformation and Clahe Based High Performance Lucid Proposal for Image Processing
Authors: Archana N. , Mahalakshmi S. , Dhanagopal R. , Menaka R.
Published: November 2020

Image fusion is a one of the enhancement technique which is used to take the decision the images by the various types of sensors. Image fusion is nothing but the combination of two images which is helps to improve the quality of the image. In this paper, visible image and Infrared image
are combined to acquire the informative image. Before and after image fusion, a new transformation technique is introduced to improve the quality of the image. To prove the quality of the image after applying new transformation technique, the fusion is done by four different techniques is
used like Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), Non-Subsampled Contourlet Transform (NSCT) and Dual Tree Complex Wavelet Transform (DT-CWT). The comparison of following parameter values such as Entropy, Standard deviation, Mean gradient, Average pixel intensity
and spatial frequency shows that proposed method is better to improve the image quality.
Design of Frequency Reconfigurable Multiband Compact Antenna
Authors: Sivabalan A. , Vijayadhasan G. Keerthi , Thandapani T. , Balamurali R.
Published: November 2020

This paper describes about the designing of a reconfigurable antenna which operates at different frequencies fulfilling the requirement of 1 to 10 GHz WLAN and 3.5 GHz WIMAX antenna applications. The main objective of this research is to minimize the usage of Antennas used in mobile
phones for various applications covering 1G, 2G, 3G, 4G, Wi-Fi and Bluetooth. This reconfigurable multiband antenna is used for applications such as WiMAX/WLAN and it has 2 PIN diode switches. The proposed antenna has been analyzed using ADS (Agilent advanced design system) software and fabricated
on an FR-4 substrate. The proposed model has a compact structure with an area of about 50 x 45 mm2, and has a slotted ground substrate.
Ergonomic Analysis of an Integrated Human Factor Assessment and Simulation in a Workplace Design
Authors: Kumar R. Deepak Suresh , Dinesh D. , Ravi S. , Vignesh A.
Published: November 2020

Currently, the expanded multifaceted nature of items and assembling forms presents world-class manufacturers with time to market and resource improvement challenges. Assembling Engineering Teams are expected to empower perfect new item dispatches and hold fast to cost, quality and beginning
of creation targets. To address these difficulties, driving makers influence their authoritative knowledge and the accessibility of 3D models of items and assets to practically approve their assembling forms forthright. With new advancing innovation, a large number of approval investigations
can be directed productively and naturally to guarantee forthright creation advancement. A definitive objective of office ergonomics is to make the working station appropriate for the laborer and all the laborers with the adaptability to get most extreme profitability and productivity. This
paper proposes an appraisal of a workplace design and ergonomics analysis based on simulation. Therefore, is possible to solve ergonomic risk in the workplace design.
A Long Short Term Memory with Peephole Connections and Generative Adversarial Network Based Collaborative Methodology to Identify Outliers in ECG Dataset
Authors: Anto Praveena M. D. , Bharathi B.
Published: November 2020

Big Data analytics has become an upward field, and it plays a pivotal role in Healthcare and research practices. Big data analytics in healthcare cover vast numbers of dynamic heterogeneous data integration and analysis. Medical records of patients include several data including medical
conditions, medications and test findings. One of the major challenges of analytics and prediction in healthcare is data preprocessing. In data preprocessing the outlier identification and correction is the important challenge. Outliers are exciting values that deviates from other values of
the attribute; they may simply experimental errors or novelty. Outlier identification is the method of identifying data objects with somewhat different behaviors than expectations. Detecting outliers in time series data is different from normal data. Time series data are the data that are
in a series of certain time periods. This kind of data are identified and cleared to bring the quality dataset. In this proposed work a hybrid outlier detection algorithm extended LSTM-GAN is helped to recognize the outliers in time series data. The outcome of the proposed extended algorithm
attained better enactment in the time series analysis on ECG dataset processing compared with traditional methodologies.
A Comprehensive Analysis of Data Mining Techniques Adopted to Affluence Classification and Retrieval in Health Record Databases
Authors: Irene D. Shiny , Pasupathi Chitra , Sethukarasi T.
Published: November 2020

Salvation of confidentiality in excavating has developed as an entire criterion for switching trustworthy data as that of data enquiry, authentication and dissemination. The theory of immense data at this instant is preserved from diverse perceptions including its consequences in numerous areas curiously comprising of healthcare. Various disputes arise when allocating these massive measures of data, specifically in what means to study this data in a consistent mode. The rudimentary objective of Fitness information studies is to continue in reality medicinal information from all phases of humans to support and develop any kind of treatment and medicinal exercise. Despite of achieving prosperity of healthiness data, incorporating, allocation and availing information are the necessary responsibilities that eventually claim the model of disseminated system. On account of developing this, we have revised numerous documents convoluted in this field in the form of techniques, set of rules and outcomes. However, this evaluation paper has combined the papers assessed parallel to the limitations, archetypal, responsibilities and approaches. Consequences and assessment techniques are talk over for nominated papers and an instantaneous outcome is accessible to complete the paper.
Security Analysis of Storage, Virtualization, Infrastructure and Standardization in Cloud Computing
Authors: Narayana K. E. , Jayashree K.
Published: November 2020

Nowadays the cloud computing grows in high rate with the help of recent technological advancement. It provides the on demand and low cost services to the customer. Cloud computing distributes the services to various location based on the demand. The services can cross various layers
and location which leads the security problem. The existing security system provides reliable solutions which are not enough to secure the resource and services from unauthorized access. Three types of security is available in the cloud namely Infrastructure security, Platform security and
application security. The proposed analysis gives the complete information about these security and its issues. Data security management process has various steps for securing the data around the cloud network with reliable access. Virtualization level security is analyzed with different parameter
based on the number issues present in the cloud. Authentication types are also identified and analyzed over security level. Various types of cloud framework and vulnerabilities are assessed in order to achieve better security.
Twitter Data Sentimental Analysis Using Multiple Classifications
Authors: Adimoolam M. , Sharma Raghav , John A. , Kumar M. Suresh , Kumar K. Ashok
Published: November 2020

In the past few decades human beings have knowledgeable tremendous intensification in the interaction in particular micro blogging websites and various social media as online resources. Many kinds of data have been used and classification data to group and store are challenging in this
real world scenario. Various machine and Natural Language Processing (NLP) were being applied to analysis the sentiment. A major concentration of this work was on using several machine learning algorithms to perform sentimental analysis and comparing various machine learning models for the
sentiment classification. This work analysed various sentimental using multiple classifications. From the evaluation of this experiment, it can be concluded that NLP and machine learning Techniques are efficient for sentimental analysis.
Modeling Snow Ablation over the Mountains of the Western United States: Patterns and Controlling Factors
Authors: Xiao Mu , Mahanama Sarith P. , Xue Yongkang , Chen Fei , Lettenmaier Dennis P.
Published: November 2020

When compared with differences in snow accumulation predicted by widely used hydrological models, there is a much greater divergence among otherwise “good” models in their simulation of the snow ablation process. Here, we explore differences in the performance of the Variable Infiltration Capacity model (VIC), Noah land surface model with multiparameterization options (Noah-MP), the Catchment model, and the third-generation Simplified Simple Biosphere model (SiB3) in their ability to reproduce observed snow water equivalent (SWE) during the ablation season at 10 Snowpack Telemetry (SNOTEL) stations over 1992–2012. During the ablation period, net radiation generally has stronger correlations with observed melt rates than does air temperature. Average ablation rates tend to be higher (in both model predictions and observations) at stations with a large accumulation of SWE. The differences in the dates of last snow between models and observations range from several days to approximately a month (on average 5.1 days earlier than in observations). If the surface cover in the models is changed from observed vegetation to bare soil in all of the models, only the melt rate of the VIC model increases. The differences in responses of models to canopy removal are directly related to snowpack energy inputs, which are further affected by different algorithms for surface albedo and energy allocation across the models. We also find that the melt rates become higher in VIC and lower in Noah-MP if the shrub/grass present at the observation sites is switched to trees.
The Role of Soil Texture in Local Land Surface–Atmosphere Coupling and Regional Climate
Authors: Dennis Eli J. , Berbery Ernesto Hugo
Published: November 2020

Soil hydraulic properties are critical in estimating surface and subsurface processes, including surface fluxes, the distribution of soil moisture, and the extraction of water by root systems. In most numerical weather and climate models, those properties are assigned using maps of soil texture complemented by look-up tables. Comparison of two widely used soil texture databases, the USDA State Soil Geographic database (STATSGO) and Beijing Normal University’s soil texture database (GSDE), reveals that differences are widespread and can be spatially coherent over large areas that can eventually lead to regional climate differences. For instance, over the U.S. Great Plains, GSDE stipulates finer soil grains than STATSGO, while the opposite is true over central Mexico. In this study, we employ the WRF/CLM4 modeling suite to investigate the sensitivity of the simulated regional climate to changes in the prescribed soil maps. Wherever GSDE has finer grains than STATSGO (e.g., over the U.S. Great Plains), the soil retains water more strongly, as evidenced by smaller latent heat flux (−20 W m−2), larger sensible heat flux (+20 W m−2), and correspondingly, a decrease in the 2-m humidity (−1 g kg−1) and an increase in 2-m temperature (+1.5 K). The opposite behavior is found over areas of coarser grains in GSDE (e.g., over central Mexico). Further, the changes in surface fluxes via soil texture lead to differences in the thermodynamic structure of the PBL. Results suggest that neither soil hydraulic properties nor soil moisture solely dictate the strength of surface fluxes, but in combination they alter the land–atmosphere coupling in nontrivial ways.
Education for All: How Schooling Is Creating Social Changes for Lowered-Caste Girls in Rural India
Authors: Dejaeghere Joan , Arur Aditi Ashok
Published: November 2020

Arguments for the expansion of formal schooling have long focused on individual outcomes from schooling, including increasing income, reducing poverty, delaying marriage, and improving health, particularly for girls and women. For nearly three decades now, global education agendas have supported girls’ education in an effort to achieve these outcomes. A large body of research analyzes girls’ individual empowerment from schooling, but less attention is given to how schooling is creating change in families and communities, particularly for lowered-caste girls in India. This article places longitudinal data from a three-year qualitative interview study of schoolgirls in Rajasthan alongside qualitative life-history interviews of girls who completed secondary school in Uttarakhand to understand how schooling affects social changes for lower castes. The analysis, using an intersectional and relational approach, illustrates how girls’ schooling shifts kin and caste relations connected to marriage and work but in ways that do not transform the stickiness of caste and gender norms. We argue that educational policies and programs must attend to the ways in which caste is implicated in achieving outcomes of delayed marriage and formal employment for lowered-caste girls in Indian communities if schooling is to create positive social change.
Cardiopulmonary resuscitation training in secondary education: A prospective cross-sectional survey of 110 Hong Kong secondary schools
Authors: Yim Vivian Wan Cheong , Ip Crystal Ming-Lai , Siu Axel Yuet Chung , Leung Ling Yan , Hung Kevin Kei Ching , Graham Colin Alexander , Song Priscilla P , Walline Joseph Harold
Published: November 2020

Background:

Hong Kong rates of bystander cardiopulmonary resuscitation are very low by international standards. Several Hong Kong secondary schools have begun incorporating cardiopulmonary resuscitation training into their curriculums for teachers and students.

Objective:

This study aimed to explore secondary school cardiopulmonary resuscitation programs and better understand school principals’ attitudes toward cardiopulmonary resuscitation training.

Methods:

A cross-sectional survey was sent to all Hong Kong secondary school principals (public and private, except for special education schools) between December 2017 and March 2018. A self-administered questionnaire of 20 items focusing on school characteristics, details of any in-school cardiopulmonary resuscitation materials or training, attitudes toward teaching cardiopulmonary resuscitation, and any barriers or ways to promote school cardiopulmonary resuscitation training was given to all school principals in the territory. This study was approved by the Survey and Behavioural Research Ethics committee of the Chinese University of Hong Kong on September 13, 2017.

Results:

Out of the 506 schools contacted, 110 completed surveys were returned (21.7%). Cardiopulmonary resuscitation training was offered in 33.6% (37/110), while 92.7% (102/110) had an automatic external defibrillator. A majority (69.1% (76/110)) agreed or strongly agreed that cardiopulmonary resuscitation training should be compulsory for secondary school students. In schools where cardiopulmonary resuscitation was taught, most cardiopulmonary resuscitation students were aged 15–17 years, and most courses ran for < 5 h. Increased funding could encourage more schools to offer cardiopulmonary resuscitation training to students in the future.

Conclusion:

One-third (33.6%) of Hong Kong secondary schools offer cardiopulmonary resuscitation training. Increased funding may support school-based cardiopulmonary resuscitation instruction and improve rates of bystander cardiopulmonary resuscitation in the future.
The levels of bioactive compounds found in raw and cooked Canadian pulses
Authors: Stone AK , Waelchli KN , Çabuk B , McIntosh TC , Wanasundara J , Arntfield SD , Nickerson MT
Published: November 2020

The effect of cooking on the levels of bioactive compounds (oligosaccharides, polyphenols and saponins, and vicine/convicine for faba bean only) were examined in a wide range of Canadian pulses. The total oligosaccharide concentrations were reduced ∼40% for chickpea, 11–81% for lentils, 41–43% for faba beans, 10–51% for beans, and 20–44% for peas. Individual oligosaccharides, raffinose, ciceritol, stachyose and verbascose, increased or decreased in the cooked samples depending on each pulse sample. Cooking reduced the total polyphenol content by 13–25% for chickpeas, 0–83% for lentils, 47–54% for faba beans, 47–54% for beans, and 48–70% for peas. And, the total saponin concentrations were reduced by 11–30% for chickpeas, 0–40% for lentils, 32–46% for beans, 14–30% for peas and increased by 8–26% in faba bean. The vicine and convicine levels in faba bean were reduced by 26–38% with cooking. The reduction in bioactive compounds after cooking depended on the specific compound and specific type of pulse. This large analyses of 20 different pulse samples allows for comparison between and within different types of pulses.
High pretreatment static and dynamic alpha‐fetoprotein values predict reduced overall survival in hepatocellular carcinoma
Authors: Czauderna Carolin , Schmidtmann Irene , Koch Sandra , Pilz Lukas , Heinrich Sophia , Otto Gerd , Mittler Jens , Lang Hauke , Kloeckner Roman , Düber Christoph , Sprinzl Martin F. , Worns Marcus A. , Galle Peter R. , Marquardt Jens U. , Weinmann Arndt
Published: November 2020

Background

Hepatocellular carcinoma is one of the most lethal cancers worldwide. Novel prognostic and/or predictive biomarkers are urgently needed to improve patient management. Alpha‐fetoprotein (AFP) is a well‐established and widely used biomarker for hepatocellular carcinoma. However, diagnostic accuracy of static AFP values is limited and the clinical potential is a matter of ongoing scientific discussion.

Objective

We here evaluated the prognostic impact of pretreatment static and dynamic AFP variables on overall survival of hepatocellular carcinoma patients in a Western cohort.

Methods

Patients with confirmed hepatocellular carcinoma (n = 809) treated at the Johannes Gutenberg University Mainz between 1998 and 2014 and two available pretreatment AFP‐values (AFP‐slope) were retrospectively analysed. Clinicopathological baseline parameters, pretreatment static values and AFP‐slope were assessed. Prognostic impact was determined by Kaplan–Meier analyses and Cox regression models.

Results

High static and dynamic AFP variables prior to therapy were associated with reduced survival rates of hepatocellular carcinoma patients. Several known clinical parameters such as Child–Pugh B (p < 0.01) and C stage (p < 0.001), portal vein thrombosis (p < 0.001) and extrahepatic spread (p < 0.001) were confirmed as independent predictors for overall survival. Addition of static and/or dynamic AFP variable resulted in higher time‐dependent area under the curves. Notably, in patients with more favourable prognosis, AFP‐slope prior to therapy was a slightly stronger predictor for overall survival compared with static AFP values.

Conclusion

Static and dynamic AFP variables prior to therapy are predictive for overall survival of hepatocellular carcinoma patients. Addition of AFP‐slope to established prognostic parameters might improve prognostic classification for a subgroup of hepatocellular carcinoma patients with preserved liver function and without portal vein tumour thrombosis.
Deprescribing medications that may increase the risk of hepatic encephalopathy: A qualitative study of patients with cirrhosis and their doctors
Authors: Williams Sydni , Louissaint Jeremy , Nikirk Sam , Bajaj Jasmohan S. , Tapper Elliot B.
Published: November 2020

Background and Aims

Multiple medications are associated with an increased risk of incident hepatic encephalopathy. Despite this known risk, medications such as opioids, benzodiazepines, gabapentin/pregabalin, and/or proton pump inhibitors are increasingly prescribed to persons with cirrhosis. Deprescribing is a promising intervention to reduce the burden of hepatic encephalopathy. Given that deprescribing has not been trialed in cirrhosis, we evaluated the barriers and facilitators to safe and successful deprescribing in cirrhosis.

Methods

We conducted, transcribed, and analyzed semi‐structured interviews using qualitative methodology with 22 subjects. This included eight patients with cirrhosis and recent use of opiates, benzodiazepines, gabapentin/Lyrica, and/or proton pump inhibitors as well as 14 providers (primary care, transplant surgery, transplant hepatology). Interviews explored opinions, behaviors, and understanding surrounding the risks and benefits of deprescribing.

Results

Major provider‐specific barriers included deferred responsibility of the deprescribing process, knowledge gaps regarding the risk of hepatic encephalopathy associated with medications (e.g., proton pump inhibitors) as well as the safe method of deprescription (i.e., benzodiazepines), and time constraints. Patient‐specific barriers included knowledge gaps regarding the cirrhosis‐specific risks of their medications and anxiety about the recurrence of symptoms after medication discontinuation. Patients uniformly reported trust in their provider's opinions on risks and wished for more comprehensive education during or after visits. Providers uniformly reported support for deprescription resources including pharmacist or nurse outreach.

Conclusion

Given knowledge of medication risks related to hepatic encephalopathy in patients with cirrhosis, deprescribing is universally seen as important. Knowledge gaps, inaction, and uncertainty regarding feasible alternatives prevent meaningful implementation of deprescription. Trials of protocolized pharmacy‐based deprescribing outreach and patient‐facing education on risks are warranted.
Single-cell RNA-seq reveals developmental plasticity with coexisting oncogenic states and immune evasion programs in ETP-ALL
Authors: Anand Praveen , Guillaumet-Adkins Amy , Dimitrova Valeriya , Yun Huiyoung , Drier Yotam , Sotudeh Noori , Rogers Anna , Ouseph Madhu M. , Nair Monica , Potdar Sayalee , Isenhart Randi , Kloeber Jake A. , Vijaykumar Tushara , Niu Leili , Vincent Tiffaney , Guo Guangwu , Frede Julia , Harris Marian H. , Place Andrew E. , Silverman Lewis B. , Teachey David T. , Lane Andrew A. , DeAngelo Daniel J. , Aster Jon C. , Bernstein Bradley E. , Lohr Jens G. , Knoechel Birgit
Published: November 2020

Lineage plasticity and stemness have been invoked as causes of therapy resistance in cancer, because these flexible states allow cancer cells to dedifferentiate and alter their dependencies. We investigated such resistance mechanisms in relapsed/refractory early T-cell progenitor acute lymphoblastic leukemia (ETP-ALL) carrying activating NOTCH1 mutations via full-length single-cell RNA sequencing (scRNA-seq) of malignant and microenvironmental cells. We identified 2 highly distinct stem-like states that critically differed with regard to cell cycle and oncogenic signaling. Fast-cycling stem-like leukemia cells demonstrated Notch activation and were effectively eliminated in patients by Notch inhibition, whereas slow-cycling stem-like cells were Notch independent and rather relied on PI3K signaling, likely explaining the poor efficacy of Notch inhibition in this disease. Remarkably, we found that both stem-like states could differentiate into a more mature leukemia state with prominent immunomodulatory functions, including high expression of the LGALS9 checkpoint molecule. These cells promoted an immunosuppressive leukemia ecosystem with clonal accumulation of dysfunctional CD8+ T cells that expressed HAVCR2, the cognate receptor for LGALS9. Our study identified complex interactions between signaling programs, cellular plasticity, and immune programs that characterize ETP-ALL, illustrating the multidimensionality of tumor heterogeneity. In this scenario, combination therapies targeting diverse oncogenic states and the immune ecosystem seem most promising to successfully eliminate tumor cells that escape treatment through coexisting transcriptional programs.
LncRNA LUADT1 sponges miR-195 to prevent cardiac endothelial cell apoptosis in sepsis
Authors: Zhang Zhimin , Lv Mingzhu , Wang Xiang , Zhao Zheng , Jiang Daolong , Wang Lihua
Published: November 2020

Background

The oncogenic role of the newly identified lncRNA LUADT1 has been revealed in lung adenocarcinoma. It was reported that LUADT1 plays a critical role in multiple human diseases. This study was carried out to investigate the role of LUADT1 in sepsis.

Methods

Sixty patients with sepsis and sixty healthy volunteers were recruited for this study. Plasma samples were collected from all participants. Human primary coronary artery endothelial cells were also used in this study. The expression of Pim-1, miR-195 and LUADT1 were detected by RT-qPCR. The interaction between miR-195 and LUADT1 was determined by overexpression experiments and luciferase activity assay. Cell apoptosis was detected by flow cytometry. The expression of apoptosis-related protein was detected by Western blotting.

Results

Bioinformatics analysis revealed the potential interaction between LUADT1 and miR-195, which was confirmed by dual luciferase reporter assay. LUADT1 was downregulated in patients with sepsis. Moreover, LPS treatment downregulated the expression of LUADT1 in primary cardiac endothelial cells. Overexpression of LUADT1 and miR-195 did not affect the expression of each other in primary cardiac endothelial cells. Interestingly, overexpression of LUADT1 was found to upregulate the expression of Pim-1, a target of miR-195. In addition, it was found that overexpression of LUADT1 and Pim-1 reduced the enhancement effects of miR-195 on LPS-induced cardiac endothelial cell apoptosis.

Conclusion

In summary, LUADT1 may protect cardiac endothelial cells against apoptosis in sepsis by regulating the miR-195/Pim-1 axis.
Illuminating the complexities of conflict with evolution: validation of the scales of evolutionary conflict measure (SECM)
Authors: Sbeglia Gena C. , Nehm Ross H.
Published: November 2020

Background

Although personal, familial, and community conflict with evolution have been documented in the literature, these scales require conceptualization as a construct and operationalization as a measure. The Scales of Conflict with Evolution Measure (SECM) instrument was developed in response to these needs. Using a construct validity framework, the content, internal structure, convergent, and substantive validity of the SECM were evaluated using Rasch analysis, Structural Equation Modeling (SEM), and follow up questioning. The conceptual utility of the instrument was explored by examining whether it added explanatory insights into evolution acceptance above and beyond religiosity, evolution knowledge, and background variables.

Results

A literature review and expert consultation indicated that construct of evolutionary conflict perception should (i) encompass the hierarchical nature of human social structures (personal, family, community) and (ii) probe conflict as it relates to human values, cultures, and beliefs. A three-dimensional construct was operationalized as a nine-item rating scale measure. Using Rasch analyses of SECM responses from a diverse sample of > 1000 students studying evolution, the instrument met criteria of robust measurement, including: fit to model expectations; three-dimensional structure; high reliability; good rating scale function; measurement invariance with time; and convergence with a similar construct. SEM showed that: (i) family and community conflict had unique causal contributions to personal conflict, with family showing a stronger and modest impact, and (ii) personal conflict had a significant and modest causal impact on evolution acceptance above and beyond the contributions of religiosity, evolution knowledge, and background variables.

Conclusion

The SECM is an easy-to-administer instrument to measure conflict with evolution and is supported by several forms of validity evidence. The SECM has potential for facilitating measurement of evolutionary conflict in educational settings, thereby raising instructor awareness of conflict levels in students, promoting rigorous evaluations of educational interventions designed to reduce conflict, and fostering conceptual advances in the field of evolution education. Future work is needed to gather additional forms of validity evidence and to test current validity claims in additional participant samples. SECM measures should also be incorporated into more complex SEM models that treat evolution knowledge and religiosity as part of the structural paths to evolution acceptance. Such models could provide insights into the most worthwhile targets for the development of educational interventions to mitigate conflict at multiple scales.
MADloy: robust detection of mosaic loss of chromosome Y from genotype-array-intensity data
Authors: González Juan R. , López-Sánchez Marcos , Cáceres Alejandro , Puig Pere , Esko Tonu , Pérez-Jurado Luis A.
Published: November 2020

Background

Accurate protocols and methods to robustly detect the mosaic loss of chromosome Y (mLOY) are needed given its reported role in cancer, several age-related disorders and overall male mortality. Intensity SNP-array data have been used to infer mLOY status and to determine its prominent role in male disease. However, discrepancies of reported findings can be due to the uncertainty and variability of the methods used for mLOY detection and to the differences in the tissue-matrix used.

Results

We created a publicly available software tool calledMADloy(Mosaic Alteration Detection for LOY) that incorporates existing methods and includes a new robust approach, allowing efficient calling in large studies and comparisons between methods.MADloyoptimizes mLOY calling by correctly modeling the underlying reference population with no-mLOY status and incorporating B-deviation information. We observed improvements in the calling accuracy to previous methods, using experimentally validated samples, and an increment in the statistical power to detect associations with disease and mortality, using simulation studies and real dataset analyses. To understand discrepancies in mLOY detection across different tissues, we appliedMADloyto detect the increment of mLOY cellularity in blood on 18 individuals after 3 years and to confirm that its detection in saliva was sub-optimal (41%). We additionally applied MADloy to detect the down-regulation genes in the chromosome Y in kidney and bladder tumors with mLOY, and to perform pathway analyses for the detection of mLOY in blood.

Conclusions

MADloyis a new software tool implemented in R for the easy and robust calling of mLOY status across different tissues aimed to facilitate its study in large epidemiological studies.
Mixed logistic regression in genome-wide association studies
Authors: Milet Jacqueline , Courtin David , Garcia André , Perdry Hervé
Published: November 2020

Background

Mixed linear models (MLM) have been widely used to account for population structure in case-control genome-wide association studies, the status being analyzed as a quantitative phenotype. Chen et al. proved in 2016 that this method is inappropriate in some situations and proposed GMMAT, a score test for the mixed logistic regression (MLR). However, this test does not produces an estimation of the variants’ effects. We propose two computationally efficient methods to estimate the variants’ effects. Their properties and those of other methods (MLM, logistic regression) are evaluated using both simulated and real genomic data from a recent GWAS in two geographically close population in West Africa.

Results

We show that, when the disease prevalence differs between population strata, MLM is inappropriate to analyze binary traits. MLR performs the best in all circumstances. The variants’ effects are well evaluated by our methods, with a moderate bias when the effect sizes are large. Additionally, we propose a stratified QQ-plot, enhancing the diagnosis ofpvalues inflation or deflation when population strata are not clearly identified in the sample.

Conclusion

The two proposed methods are implemented in the R packagemilorGWASavailable on the CRAN. Both methods scale up to at least 10,000 individuals. The same computational strategies could be applied to other models (e.g. mixed Cox model for survival analysis).
Intrinsic laws of k-mer spectra of genome sequences and evolution mechanism of genomes
Authors: Yang Zhenhua , Li Hong , Jia Yun , Zheng Yan , Meng Hu , Bao Tonglaga , Li Xiaolong , Luo Liaofu
Published: November 2020

Background

K-mer spectra of DNA sequences contain important information about sequence composition and sequence evolution. We want to reveal the evolution rules of genome sequences by studying the k-mer spectra of genome sequences.

Results

The intrinsic laws of k-mer spectra of 920 genome sequences from primate to prokaryote were analyzed. We found that there are two types of evolution selection modes in genome sequences, named as CG Independent Selection and TA Independent Selection. There is a mutual inhibition relationship between CG and TA independent selections. We found that the intensity of CG and TA independent selections correlates closely with genome evolution and G + C content of genome sequences. The living habits of species are related closely to the independent selection modes adopted by species genomes. Consequently, we proposed an evolution mechanism of genomes in which the genome evolution is determined by the intensities of the CG and TA independent selections and the mutual inhibition relationship. Besides, by the evolution mechanism of genomes, we speculated the evolution modes of prokaryotes in mild and extreme environments in the anaerobic age and the evolving process of prokaryotes from anaerobic to aerobic environment on earth as well as the originations of different eukaryotes.

Conclusion

We found that there are two independent selection modes in genome sequences. The evolution of genome sequence is determined by the two independent selection modes and the mutual inhibition relationship between them.
Genome-wide association studies for methane emission and ruminal volatile fatty acids using Holstein cattle sequence data
Authors: Jalil Sarghale Ali , Moradi Shahrebabak Mohammad , Moradi Shahrebabak Hossein , Nejati Javaremi Ardeshir , Saatchi Mahdi , Khansefid Majid , Miar Younes
Published: November 2020

Background

Methane emission by ruminants has contributed considerably to the global warming and understanding the genomic architecture of methane production may help livestock producers to reduce the methane emission from the livestock production system. The goal of our study was to identify genomic regions affecting the predicted methane emission (PME) from volatile fatty acids (VFAs) indicators and VFA traits using imputed whole-genome sequence data in Iranian Holstein cattle.

Results

Based on the significant-association threshold (p < 5 × 10− 8), 33 single nucleotide polymorphisms (SNPs) were detected for PME per kg milk (n = 2), PME per kg fat (n = 14), and valeric acid (n = 17). Besides, 69 genes were identified for valeric acid (n = 18), PME per kg milk (n = 4) and PME per kg fat (n = 47) that were located within 1 Mb of significant SNPs. Based on the gene ontology (GO) term analysis, six promising candidate genes were significantly clustered in organelle organization (GO:0004984, p = 3.9 × 10− 2) for valeric acid, and 17 candidate genes significantly clustered in olfactory receptors activity (GO:0004984, p = 4 × 10− 10) for PME traits. Annotation results revealed 31 quantitative trait loci (QTLs) for milk yield and its components, body weight, and residual feed intake within 1 Mb of significant SNPs.

Conclusions

Our results identified 33 SNPs associated with PME and valeric acid traits, as well as 17 olfactory receptors activity genes for PME traits related to feed intake and preference. Identified SNPs were close to 31 QTLs for milk yield and its components, body weight, and residual feed intake traits. In addition, these traits had high correlations with PME trait. Overall, our findings suggest that marker-assisted and genomic selection could be used to improve the difficult and expensive-to-measure phenotypes such as PME. Moreover, prediction of methane emission by VFA indicators could be useful for increasing the size of reference population required in genome-wide association studies and genomic selection.
Systemic paralogy and function of retinal determination network homologs in arachnids
Authors: Gainett Guilherme , Ballesteros Jesús A. , Kanzler Charlotte R. , Zehms Jakob T. , Zern John M. , Aharon Shlomi , Gavish-Regev Efrat , Sharma Prashant P.
Published: November 2020

Background

Arachnids are important components of cave ecosystems and display many examples of troglomorphisms, such as blindness, depigmentation, and elongate appendages. Little is known about how the eyes of arachnids are specified genetically, let alone the mechanisms for eye reduction and loss in troglomorphic arachnids. Additionally, duplication of Retinal Determination Gene Network (RDGN) homologs in spiders has convoluted functional inferences extrapolated from single-copy homologs in pancrustacean models.

Results

We investigated a sister species pair of Israeli cave whip spiders,Charinus ioanniticusandC. israelensis(Arachnopulmonata, Amblypygi), of which one species has reduced eyes. We generated embryonic transcriptomes for both Amblypygi species, and discovered that several RDGN homologs exhibit duplications. We show that duplication of RDGN homologs is systemic across arachnopulmonates (arachnid orders that bear book lungs), rather than being a spider-specific phenomenon. A differential gene expression (DGE) analysis comparing the expression of RDGN genes in field-collected embryos of both species identified candidate RDGN genes involved in the formation and reduction of eyes in whip spiders. To ground bioinformatic inference of expression patterns with functional experiments, we interrogated the function of three candidate RDGN genes identified from DGE using RNAi in the spiderParasteatoda tepidariorum. We provide functional evidence that one of these paralogs,sine oculis/Six1 A(soA), is necessary for the development of all arachnid eye types.

Conclusions

Our work establishes a foundation to investigate the genetics of troglomorphic adaptations in cave arachnids, and links differential gene expression to an arthropod eye phenotype for the first time outside of Pancrustacea. Our results support the conservation of at least one RDGN component across Arthropoda and provide a framework for identifying the role of gene duplications in generating arachnid eye diversity.
Chicken cecal DNA methylome alteration in the response to Salmonella enterica serovar Enteritidis inoculation
Authors: Wang Yuanmei , Liu Liying , Li Min , Lin Lili , Su Pengcheng , Tang Hui , Fan Xinzhong , Li Xianyao
Published: November 2020

Background

Salmonella enterica serovar Enteritidis (SE) is one of the pathogenic bacteria, which affects poultry production and poses a severe threat to public health. Chicken meat and eggs are the main sources of human salmonellosis. DNA methylation is involved in regulatory processes including gene expression, chromatin structure and genomic imprinting. To understand the methylation regulation in the response to SE inoculation in chicken, the genome-wide DNA methylation profile following SE inoculation was analyzed through whole-genome bisulfite sequencing in the current study.

Results

There were 185,362,463 clean reads and 126,098,724 unique reads in the control group, and 180,530,750 clean reads and 126,782,896 unique reads in the inoculated group. The methylation density in the gene body was higher than that in the upstream and downstream regions of the gene. There were 8946 differentially methylated genes (3639 hypo-methylated genes, 5307 hyper-methylated genes) obtained between inoculated and control groups. Methylated genes were mainly enriched in immune-related Gene Ontology (GO) terms and metabolic process terms. Cytokine-cytokine receptor interaction, TGF-beta signaling pathway, FoxO signaling pathway, Wnt signaling pathway and several metabolism-related pathways were significantly enriched. The density of differentially methylated cytosines in miRNAs was the highest. HOX genes were widely methylated.

Conclusions

The genome-wide DNA methylation profile in the response to SE inoculation in chicken was analyzed. SE inoculation promoted the DNA methylation in the chicken cecum and caused methylation alteration in immune- and metabolic- related genes. Wnt signal pathway, miRNAs and HOX gene family may play crucial roles in the methylation regulation of SE inoculation in chicken. The findings herein will deepen the understanding of epigenetic regulation in the response to SE inoculation in chicken.