bluuebunny/crossref_metadata_2025 huggingface dataset:
Adverse Effects of 5th Generation Mobile Technology on Flora and Fauna: Review Study
Authors: Kumar Rajesh , Geleta Rabira , Pandey Amit , Sinwar Deepak
Published: March 2021

Technology plays a very vital roles in the growth of the economy of any nation. Hence, information communication channel needs to be very strong for timely delivery of information and growth of any country. Mobile technology is the backbone of communication channel in any country who has incorporated it. Since 1980 mobile communication is very popular mode of communication and researches are going on in this area since that time. Starting from the first generation mobile network to fifth generation mobile network, every nation wants to enhance their information communication technology infrastructures in aspect of communication. The 5G mobile technology is subject of debate now a day. Still, most of the countries are in the race for adopting this technology and are ignoring its adverse effects on human health and environments. 5G mobile technology uses millimetre waves and higher frequency band 6 GHz to 100 GHz for communication. Initially, there was appeal made in United Nation Council and later in European Union against the launch of 5G, which was signed by more than three hundred scientists and doctors, stating that the 5G mobile technology is not good for environment. Various research has been conducted regarding the adverse effects of RF-EMF waves, which are generated by cell towers, on human health and environment. 5G uses very dense infrastructure and there is evidence that the RF-EMF radiation level is very strong in fifth generation mobile technology as compare to previous mobile technologies. Hence, the current study is focused on reviewing the impact of 5G mobile technology on flora and fauna Kingdome.
A Comparative Analysis of Association Rule Mining Algorithms
Authors: Saxena Akash , Rajpoot Vikram
Published: March 2021

The field of data mining (DM) has grown rapidly in recent years. One of the most important data mining techniques is association rule mining (ARM). It is a strategy used to identify trends in the database that are normal. There has been a lot of work in the area of ARM. The paper provides a short description of the principles and algorithms of interaction, several of the implementations. To several researchers, ARM has long been and still is of concern. Data mining is one of the essential activities. This helps to identify associations between various elements in the database. The goal of this paper is to provide an outline of the fundamental concepts of the ARM methodology and the recent relevant research in this area. The paper further explains the different algorithms, methods, strategies, and benefits of the ARM areas, drawbacks. The paper also provides a minor distinction focused on the results of various algorithms related to association rules mining. The paper provides a short description of the principles and algorithms of interaction, several of the implementations. Algorithms are present and evaluate base parameters such as precision, algorithm pace, and help for data. To solve the question of apriori algorithms AprioriTid and the AprioriHybrid have been suggested. From the contrast, we infer that, since it has decreased overall pace and increased precision, AprioriHybrid is superior to Apriori and AprioriTid. We may infer that the LogElcat algorithm performs more than every other algorithm based on these parameters.
Automatic Detection of COVID 19 Infection Using Deep Learning Models from X-Ray Images
Authors: Yadav Anju , Verma Vivek Kumar , Pal Vipin , Singh Saumya
Published: March 2021

In worldwide millions of people are infected due to COVID-19 virus and even that is increasing exponentially. The medical researchers are using RT-PCR test to distinguish between COVID (+) and COVID (-). The growth of virus is exponential that’s lead to an outbreak, and to break this we have to conduct test as many as possible. RT PCR test is costly and not available in remote areas this is big challenge that developing countries is facing. The second big challenge whole world facing is the availability of doctors and radiologists. So, we need an automated system based on AI and Machine learning (ML) for detection of COVID (+) cases. In literature AI, ML and Deep Learning (DL) played an important role in designing automated system in medical field by achieving good accuracy. In this paper, we have applied DL models ResNet 34 and ResNet 50 on X-ray images, achieved accuracy 96.4% with ResNet 34. And compared their result on the basis of various quantitative analysis parameter MCC, F1 Score, Precision, Recall and others to solve both challenges.
Study of Baseline Cyber Security for Various Application Domains
Authors: Chaturvedi Mudit , Sharma Shilpa , Ahmed Gulrej
Published: March 2021

In today’s technical life, the means of production and creation, process, storage and exchange of information and data, rather than in paper-based methods, as an alternative to electronic data and electronic means of communication. That means all information / data is done on the paper as not a written document, but in the form of digital and electronic data. A special type of computer-based system is used in preparing, receiving, processing, transmitting or storing this electronic data / information and the main feature of this computer-based system is that there is a rapid data processing by logical, arithmetic, membrane resources by the systems of electronic, magnetic or optical waves by instruction or communication, work of input, product, investment, processing or storage is done. It is very important for the common man to know about the basic security of information / data in every domain of life. This paper analyses the technical changes and cyber risks arising in various fields, as well as a detailed study of technological security efforts and measures to mitigate cyber risks in various technical areas.
Analysis of Design for One-Way Reinforced Concrete Slabs using Machine Learning Models
Authors: Sancheti G , Patil H , Sharma S , Goswami S
Published: March 2021

Preliminary design parameters of one-way Reinforced Concrete (RC) slabs are one of the significant factors and needs to be precisely determined. Though, these parameters can be suitably determined by using the guidelines laid down by various Indian Standards, a high level of expertise is required to perform this operation. At the same time analysing and fixing design parameters considering different configurations of slab make the prediction somewhat more time consuming. In such a condition, one of the supports for a design engineer is the Machine learning (ML) techniques. This paper investigates the performance of various ML techniques in predicting and analysing the design inputs and outputs for a one war RC slabs. The comparison results show the appropriate machine learning model learning to predict the compressive strength of one-way slab.
Analyzing Evolution of the Olympics by Exploratory Data Analysis using R
Authors: Pradhan Rahul , Agrawal Kartik , Nag Anubhav
Published: March 2021

Olympic Games are one of the main international event and also a matter of prestige for countries and therefore each country tries to give their best performance during the event. Despite a lot of hard work, many countries/player are unable to perform well during the events and grab medals whereas there are many countries which performs very well in the event and secures many medals. An Analysis need to be done by each country to evaluate the previous statistics which will detect the mistakes which they have done previously and will also help them in future development. An analysis can also be done by the host country to find out the mistakes in the arrangements of the Event which will help them in overcoming these mistakes and host the event accurately. The primary objective of this Research paper is to analyze the large Olympic dataset using Exploratory Data Analysis to evaluate the evolution of Olympic Games over the years. This analysis will provide detailed and accurate information regarding various factors which leads to the evolution of Olympic Games and improvement of Countries/Players over the time in visual format. Visualization of the data over various factors will provide us with the statistical view of the various factors which leads to the evolution of the Olympic Games and Improvement in performance of various Countries/Players over the time.
Efficient Predictive Modelling for Classification of Coronary Artery Diseases Using Machine Learning Approach
Authors: Savita  , Sharma Ganga , Rani Geeta , Dhaka Vijaypal Singh
Published: March 2021

Cardiovascular is one of the most critical diseases that affect persons very abominably. Coronary artery diseases (CAD) are one of the categories of cardiovascular diseases that cause a high death rate. So it is imperative to control these death rates by developing an advanced model of machine learning through which diseases can be detected at the premature stage. Due to the lack of enough facilities for tools like angiography it has become a substantial challenge for the health care organization to detect such diseases. If tools exist, then these are known for being expensive and also have numerous side effects. The main goal of this research is to enhance the accuracy of existing models using optimization techniques with machine learning techniques. Alizadeh-Sani CAD dataset has been used which consists of a total of 303 records with 56 attributes. The proposed model reported following values of precision (0.92), recall (0.92), and accuracy (0.93). This proves the efficacy of employing the optimization techniques with machine learning algorithms.
Using Internet of Things in Hypervisor Monitoring -Challenges and Opportunities
Authors: Mathur Sandeep , Kaushik Anurag , Rana Ajay
Published: March 2021

Security worries in IoT are solved by embedded virtualization, as the applications are kept running in various detached situations. In the present research work the proposed framework makes utilization of an ease virtual condition that empowers resource sharing among numerous applications in the system. Adding a hypervisor to an embedded framework includes adaptability and larger amount capabilities, transforming the inserted gadget into another classification of the framework. In the proposed virtualization structure both home computerization and condition checking framework are facilitated in the virtual machine and tested. Further information gathered from home will be utilized by the government for condition observing, in this manner decreasing the excess WSN organization. At long last, engineering of various virtual conditions is considered, and points of interest are talked about with the consequences of specific Phoronix tests on various situations. Therefore, this system gives financially effective arrangements; promotes variety, ensures security and adaptability.
Model of Using New Media Technology in Higher Education Learning
Authors: Bhavana S , Vijayalakshmi V
Published: March 2021

Media is an incredible correspondence and information sharing medium. It permits us to refresh innovation and make it around the world connected. New Media covers computerized media, online media, programming, all web-based assets. New Media has often been defined as the medium by which information is transferred between societies and students. Academies used digital media to promote cooperative learning and social interaction. The research examines the effect on higher education of 116 respondents participating in this study of new media innovation in teaching and learning. Modeling of the Structural Equation (SEM) has been used to evaluate the obtained data. The study reports the effect of these variables on cooperative teaching and learning using new media that could result in educators and learners having an impact on higher education.
Improved wavefront estimation accuracy in a programmable grating array based wavefront sensor
Authors: Pathak Biswajit
Published: March 2021

Shack–Hartmann wavefront sensor (SHWS) is one of the popular zonal wavefront sensor that typically consists of a two-dimensional (2D) array of lenslets and a camera. Another variant of a zonal wavefront sensor is the programmable grating array based wavefront sensor (PGAWS) that replaces the lenslets array of the SHWS with a 2D array of programmable diffraction gratings and a single focusing lens to result in a 2D array of +1 order spots. The ability of a PGAWS to correctly measure the incident wavefront depends on the accuracy with which each +1 order spot centroid position in the camera plane is calculated. However, in practical applications the intensities of the +1 order spots are usually non-uniform and there is presence of higher order spots that lead to erroneous calculation of the centroid position. In the present work, an improved PGAWS is proposed and by exploiting its programmable facility the transmittance function of the grating array is defined to generate an array of uniform intensity +1 order spots with negligible contribution from unwanted higher order spots by breaking them into noise. We present proof-of-concept simulation results that illustrate the generation of uniform intensity +1 order spots and also quantify its uniformity numerically by defining a quality metric. Furthermore, the working of the proposed PGAWS is substantiated through simulation results which demonstrate its accurate wavefront estimation capability in comparison to the conventional PGAWS, in the presence of non-uniform intensity +1 order spots.
Fully-structured counter-propagating optical trap sculpted by spherical aberration
Authors: Otte Eileen , Denz Cornelia
Published: March 2021

Aberrations of light are commonly known as undesired effects in different applications, including optical trapping. However, here we demonstrate how to take advantage of controlled spherical aberration in order to shape extended optical trapping landscapes, fully-structured in three-dimensional (3D) space and embedding transverse as well as longitudinal electric field contributions. We numerically analyze the light field customization by the simple means of including glass plates in a counter-propagating trapping configuration, presenting sculpted intensity as well as 3D polarization ellipse structures. Experimentally, we prove the realized counter-propagating optical structure by particle velocimetry as well as the analysis of scattered light of optically guided micro-particles. Finally, we demonstrate the potential of our approach by creating extended 3D particle assemblies.
Complete mapping of magnetic anisotropy for prototype Ising van der Waals FePS3
Authors: Nauman Muhammad , Kiem Do Hoon , Lee Sungmin , Son Suhan , Park Je-Geun , Kang Woun , Han Myung Joon , Jo Younjung
Published: March 2021

Several Ising-type magnetic van der Waals (vdW) materials exhibit stable magnetic ground states. Despite these clear experimental demonstrations, a complete theoretical and microscopic understanding of their magnetic anisotropy is still lacking. In particular, the validity limit of identifying their one-dimensional Ising nature has remained uninvestigated in a quantitative way. Here we performed the complete mapping of magnetic anisotropy for a prototypical Ising vdW magnet FePS3 for the first time. Combining torque magnetometry measurements with their magnetostatic model analysis and the relativistic density functional total energy calculations, we successfully constructed the three-dimensional mappings of the magnetic anisotropy in terms of magnetic torque and energy. The results not only quantitatively confirm that the easy axis is perpendicular to the ab plane, but also reveal the anisotropies within the ab, ac, and bc planes. Our approach can be applied to the detailed quantitative study of magnetism in vdW materials.
Effect of explosive compaction on microstructure of ODS FeCrAl alloy fabricated by oxidation method
Authors: Yan Fuzhao , Li Jing , Xiong Liangyin , Liu Shi
Published: March 2021

A fabrication process of 14Cr ODS FeCrAl alloy including direct oxidation treatment, explosive compaction and vacuum post-sintering was proposed herein. A thin oxide layer formed on the powder surface during a low-temperature oxidation treatment was crushed in the explosive compaction, resulting in the redistribution of oxides at prior powder boundary (PPB) and the subsequent formation of an exclusive iron oxide layer between the grains of compacted materials. A large number of defects (dislocations and grain boundaries) were also produced in the compacted particles. Through characterizing the evolution of oxide dispersoids during the course of fabrication, the contribution of explosive compaction to dislocations, nanoscale precipitates and mechanical properties was clarified. The results show that the iron oxide layer became the container for transporting oxygen and was dissolved during the post-sintering, which affected the composition of nanoscale precipitates. The high-density dislocations not only became the rapid diffusion paths of oxygen, aluminum and yttrium atom, but also became the preferential sites of Y-Al-O precipitation. With the manufacturing method, the more uniform distribution of oxide nanoparticles and the higher microhardness of ODS alloy were obtained.
Warp deformation model of polyetheretherketone composites reinforced with carbon fibers in additive manufacturing
Authors: Sun Qili , Shan Zhongde , Zhan Li , Wang Shaozong , Liu Xiaohang , Li Zheng , Wu Siyuan
Published: March 2021

Fused deposition modeling (FDM) provides a promising technique for the small-batch fabrication of highly customized objects. The required performance of FDM far exceeds the performances of conventional manufacturing methods. However, the temperature difference that occurs during FDM generates internal stress, which causes warp deformation and affects formed sample quality. Hence, identifying the influencing factors of warp deformation is the key to improving the forming quality of FDM samples. In this work, PEEK/short carbon fiber (CF) composites were prepared by using the FDM method, the warp deformation formula was derived, and the warp deformation mechanism was obtained. Results showed that the material linear expansion coefficient, forming chamber temperature, and forming size had considerable effects on warp deformation. Moreover, CF could improve the warp deformation of the PEEK/CF composites because of their low Poisson’s ratio and high thermal conductivity. The addition of CF could reduce the residual stress of the composites and improve warp deformation. In addition, annealing could improve the tensile and bending mechanical properties of the PEEK/CF composites. Specifically, after 3 h of heat treatment at 190 °C, the tensile and bending mechanical properties of the composites reached 10.7% and 11.6%, respectively. Crystallinity analysis revealed that the mechanical properties of the PEEK/CF composites strongly depended on their crystallinity. High cooling temperature rates were associated with low crystallinity, tensile strengths, and elastic moduli. DMA analysis showed that the addition of CF could improve the high-temperature resistance of the PEEK/CF composites as reflected by the higher glass transition temperature of the composites than that of the pure PEEK resin. Porosity analysis showed that the CF content could tailor the pore size and distribution. The study reported here provides a reference for improving the forming quality and mechanical properties of PEEK/CF composites fabricated through FDM.
Analysis and verification of a biomimetic design model based on fish skin
Authors: Zheng Yu , Guo Ce , Li Xin
Published: March 2021

Many biological architectures are Bouligand structures, which comprise uniaxial fiber layers stacked in a periodic helical arrangement and are characterized by high damage resistance. As an effective flexible protective structure, fish skin is a Bouligand structure that protects the body while ensure flexibility during swimming and predation. In this paper, an analytical model inspired by fish skin is established based on previous studies, and the parameters for describing crack growth are determined. Then, mathematical expressions for the local stress intensity factors and plastic zone are used to predict how the helical stacking angle α influences the crack propagation. The results show that crack deflection and twisting improve the fracture toughness of the composite structure greatly, with the optimal fracture toughness being that for α = 60° – 70°. Moreover, biomimetic flexible composite structures inspired by fish skin are produced using silicone and Kevlar fibers. Scanning electron microscopy is used to observe the cross-sectional morphology of the composite structures, showing that the interfaces between the silicone and Kevlar fibers are highly compact. Results from experimental impact tests agree well with the predicted results.
Adsorption and photocatalytic activity of biosynthesised ZnO nanoparticles using Aloe Vera leaf extract
Authors: Jose Lolly Maria , Raj R S Arun , Sajan D , Aravind Arun
Published: March 2021

In this article, we demonstrates the growth of phase pure ZnO nanostructures fromAloe-Veraleaf extract and degradation of an organic dye-Malachite Green (MG)- from aqueous medium using the same as catalyst. Adsorption mechanisms were evaluated using Lagergren’s pseudo-first-order, pseudo-second-order and intraparticle diffusion kinetic models. X-Ray diffraction data showed that the synthesised ZnO is crystalline with hexagonal wurtzite phase. Average crystallite size and lattice strain was estimated from Scherrer equation and Williamson-Hall analysis with the help of Rietveld refinement data. Crystallite size obtained from Scherrer method is 12.62 nm while that from Williamson-Hall analysis is 19.27 nm. Uniform growth of ZnO nano-sheets were confirmed by FE-SEM analysis. Optical characterisation was carried by UV-Visible spectroscopy and the band gap ZnO nanoparticles was found to be 3.19 eV. Zn-O stretching vibrations were recorded at 550 cm−1using FTIR spectrophotometer. Results showed that biosynthesised ZnO nanosheets are particularly effective for the degradation of MG dye.
How to bring peer review ghostwriters out of the dark
Authors: McDowell Gary S. , Niziolek Caroline A. , Lijek Rebeccah S.
Published: March 2021

Early career researchers are frequent and valuable contributors to peer review. Systemic changes that acknowledge this fact would result in ethical co-reviewing, peer reviews of greater quality, and a reduction in peer reviewer burden.
Food Fortification With Folic Acid for Prevention of Spina Bifida and Anencephaly: The Need for a Paradigm Shift in Evidence Evaluation for Policy-Making
Authors: Martinez Homero , Pachón Helena , Kancherla Vijaya , Oakley Godfrey P
Published: March 2021

Context-specific evidence evaluation is advocated in modern epidemiology to support public health policy decisions, avoiding excessive reliance on experimental study designs. Here we present the rationale for a paradigm shift in evaluation of the evidence derived from independent studies, as well as systematic reviews and meta-analyses of observational studies, applying Hill’s criteria (including coherence, plausibility, temporality, consistency, magnitude of effect, and dose-response) to evaluate food fortification as an effective public health intervention against folic acid–preventable (FAP) spina bifida and anencephaly (SBA). A critical appraisal of evidence published between 1983 and 2020 supports the conclusion that food fortification with folic acid prevents FAP SBA. Policy-makers should be confident that with mandatory legislation, effective implementation, and periodic evaluation, food fortification assures that women of reproductive age will safely receive daily folic acid to significantly reduce the risk of FAP SBA. Current evidence should suffice to generate the political will to implement programs that will save thousands of lives each year in over 100 countries.
Exploring the Seasonal Drivers of Varicella Zoster Virus Transmission and Reactivation
Authors: Bakker Kevin M , Eisenberg Marisa C , Woods Robert , Martinez Micaela E
Published: March 2021

Varicella zoster virus (VZV) is a herpesvirus that causes chickenpox and shingles. The biological mechanisms underpinning the multidecadal latency of VZV in the body and subsequent viral reactivation—which occurs in approximately 30% of individuals—are largely unknown. Because chickenpox and shingles are endemic worldwide, understanding the relationship between VZV transmission and reactivation is important for informing disease treatment and control. While chickenpox is a vaccine-preventable childhood disease with a rich legacy of research, shingles is not a notifiable disease in most countries. To date, population-level studies of shingles have had to rely on small-scale hospital or community-level data sets. Here, we examined chickenpox and shingles notifications from Thailand and found strong seasonal incidence in both diseases, with a 3-month lag between peak chickenpox transmission season and peak shingles reactivation. We tested and fitted 14 mathematical models examining the biological drivers of chickenpox and shingles over an 8-year period to estimate rates of VZV transmission, reactivation, and immunity-boosting, wherein reexposure to VZV boosts VZV-specific immunity to reinforce protection against shingles. The models suggested that the seasonal cycles of chickenpox and shingles have different underlying mechanisms, with ambient levels of ultraviolet radiation being correlated with shingles reactivation.
Formation of taste-active pyroglutamyl peptide ethyl esters in sake by rice koji peptidases
Authors: Ito Toshihiko , Taguchi Yuki , Oue Haruka , Amano Naomi , Nagae Yusuke , Noge Koji , Hashizume Katsumi
Published: March 2021

Formation of taste-active pyroglutamyl (pGlu) peptide ethyl esters in sake was investigated: 2 enzymes (A and B) responsible for the esterification were purified from a rice koji extract. MADLI-TOF/TOF analysis after deglycosylation identified enzyme (A) as peptidase S28 (GenBank accession number OOO13707.1) and enzyme (B) as serine-type carboxypeptidase (accession number AO090010000534). Both enzymes hydrolyzed pGlu peptides and formed ethyl esters under sake mash conditions: acidic pH (3-4) and in ethanol (5%-20% v/v) aqueous solutions. Enzyme (A) formed pGlu penta-peptide ethyl esters from pGlu undeca-peptides by a prolyl endo-type reaction. Enzyme (B) formed (pGlu) deca-peptide and its ethyl esters from pGlu undeca-peptides in an exo-type reaction. We are the first to report the enzymatic ethyl esterification reaction in the formation of pGlu peptides by rice koji peptidases.
Concise enantioselective synthesis of wine lactone via intramolecular Diels–Alder reaction
Authors: Ohkubo Yasutaka , Masuda Yui , Ogura Yusuke , Takikawa Hirosato , Watanabe Hidenori
Published: March 2021

An enantioselective synthesis of (3S,3aS,7aR)-wine lactone, a major aroma component of white wine and citrus juices, was achieved starting from (S)-2-methyl-3-butenoic acid. An intramolecular Diels–Alder reaction was employed as a key step.
Atypical neural topographies underpin dysfunctional pattern separation in temporal lobe epilepsy
Authors: Li Qiongling , Tavakol Shahin , Royer Jessica , Larivière Sara , Vos De Wael Reinder , Park Bo-yong , Paquola Casey , Zeng Debin , Caldairou Benoitu , Bassett Danielle S , Bernasconi Andrea , Bernasconi Neda , Frauscher Birgit , Smallwood Jonathan , Caciagli Lorenzo , Li Shuyu , Bernhardt Boris C
Published: March 2021

Episodic memory is the ability to remember events from our past accurately. The process of pattern separation is hypothesized to underpin this ability and is defined as the capacity to orthogonalize memory traces, to maximize the features that make them unique. Contemporary cognitive neuroscience suggests that pattern separation entails complex interactions between the hippocampus and neocortex, where specific hippocampal subregions shape neural reinstatement in the neocortex. To test this hypothesis, the current work studied both healthy controls and patients with temporal lobe epilepsy who presented with hippocampal structural anomalies. We measured neural activity in all participants using functional MRI while they retrieved memorized items or lure items, which shared features with the target. Behaviourally, patients with temporal lobe epilepsy were less able to exclude lures than controls and showed a reduction in pattern separation. To assess the hypothesized relationship between neural patterns in the hippocampus and neocortex, we identified the topographic gradients of intrinsic connectivity along neocortical and hippocampal subfield surfaces and determined the topographic profile of the neural activity accompanying pattern separation. In healthy controls, pattern separation followed a graded topography of neural activity, both along the hippocampal long axis (and peaked in anterior segments that are more heavily engaged in transmodal processing) and along the neocortical hierarchy running from unimodal to transmodal regions (peaking in transmodal default mode regions). In patients with temporal lobe epilepsy, however, this concordance between task-based functional activations and topographic gradients was markedly reduced. Furthermore, person-specific measures of concordance between task-related activity and connectivity gradients in patients and controls were related to inter-individual differences in behavioural measures of pattern separation and episodic memory, highlighting the functional relevance of the observed topographic motifs. Our work is consistent with an emerging understanding that successful discrimination between memories with similar features entails a shift in the locus of neural activity away from sensory systems, a pattern that is mirrored along the hippocampal long axis and with respect to neocortical hierarchies. More broadly, our study establishes topographic profiling using intrinsic connectivity gradients, capturing the functional underpinnings of episodic memory processes in a manner that is sensitive to their reorganization in pathology.
The Brain Circuits and Dynamics of Curiosity-Driven Behavior in Naturally Curious Marmosets
Authors: Tian Xiaoguang , Silva Afonso C , Liu Cirong
Published: March 2021

Curiosity is a fundamental nature of animals for adapting to changing environments, but its underlying brain circuits and mechanisms remain poorly understood. One main barrier is that existing studies use rewards to train animals and motivate their engagement in behavioral tasks. As such, the rewards become significant confounders in interpreting curiosity. Here, we overcame this problem by studying research-naïve and naturally curious marmosets that can proactively and persistently participate in a visual choice task without external rewards. When performing the task, the marmosets manifested a strong innate preference towards acquiring new information, associated with faster behavioral responses. Longitudinally functional magnetic resonance imaging revealed behavior-relevant brain states that reflected choice preferences and engaged several brain regions, including the cerebellum, the hippocampus, and cortical areas 19DI, 25, and 46D, with the cerebellum being the most prominent. These results unveil the essential brain circuits and dynamics underlying curiosity-driven activity.
Insular Cortex Mediates Attentional Capture by Behaviorally Relevant Stimuli after Damage to the Right Temporoparietal Junction
Authors: Ptak Radek , Pedrazzini Elena
Published: March 2021

The right temporoparietal junction (rTPJ) and insula both play a key role for the processing of relevant stimuli. However, while both have been conceived as neural “switches” that detect salient events and redirect the focus of attention, it remains unclear how these brain regions interact to achieve this behavioral goal. Here, we tested human participants with focal left-hemispheric or right-hemispheric lesions in a spatial cuing task that requires participants to react to lateralized stimuli preceded by a distracter that shares or does not share a relevant feature with the target. Using machine learning to identify significant lesion–behavior relationships, we found that rTPJ damage produces distinctive, pathologically increased attentional capture, but only by relevant distracters. Functional connectivity analyses revealed that the degree of capture is positively associated with a functional connection between insula and rTPJ, together with functional isolation of the rTPJ from right dorsal prefrontal cortex (dPFC). These findings suggest a mechanistic model where the insula–rTPJ connection constitutes a crucial functional unit that breaks attentional focus upon detection of behaviorally relevant events, while the dPFC appears to attune this activity.
A Distinct Population of L6 Neurons in Mouse V1 Mediate Cross-Callosal Communication
Authors: Liang Yajie , Fan Jiang Lan , Sun Wenzhi , Lu Rongwen , Chen Ming , Ji Na
Published: March 2021

Through the corpus callosum, interhemispheric communication is mediated by callosal projection (CP) neurons. Using retrograde labeling, we identified a population of layer 6 (L6) excitatory neurons as the main conveyer of transcallosal information in the monocular zone of the mouse primary visual cortex (V1). Distinct from L6 corticothalamic (CT) population, V1 L6 CP neurons contribute to an extensive reciprocal network across multiple sensory cortices over two hemispheres. Receiving both local and long-range cortical inputs, they encode orientation, direction, and receptive field information, while are also highly spontaneous active. The spontaneous activity of L6 CP neurons exhibits complex relationships with brain states and stimulus presentation, distinct from the spontaneous activity patterns of the CT population. The anatomical and functional properties of these L6 CP neurons enable them to broadcast visual and nonvisual information across two hemispheres, and thus may play a role in regulating and coordinating brain-wide activity events.
Novelty Detection in Memory for Common and Uncommon Odors over Short Delays
Authors: Wenzel Elizabeth S , Cameron E Leslie , Møller Per , Köster Egon P
Published: March 2021

Odor memory is commonly believed to be very strong and long-lasting. The present study examined factors that impact odor recognition memory over short delay intervals (immediately or 30 s after target presentation) with emphasis on memory task (forced-choice vs “monadic”/single stimulus yes/no), odor category, and target/foil relationship. We explored trial-by-trial confidence as well as the effect of target familiarity, pleasantness, and intensity ratings, and odor nameability on memory for odors. Overall odor recognition memory in terms of proportion correct and sensitivity measures did not decline significantly during the 30-s delay interval in either task. However, hit rates were lower at 30 s and correct rejection rates for common odors remained consistently high. Recognition memory was better on trials in which the odor pairs were highly dissimilar, as well as on trials in which the target was an uncommon odor, particularly if it could be named. Familiarity, pleasantness, and intensity had no systematic effect on recognition memory. Whereas the results provide evidence of a fading memory trace, indicated by the decreased hit rates after a 30-s delay, the constant rates of correct rejections and high confidence ratings on those trials, even after delay, suggests that novelty detection (i.e., recognition that an odor is not one that has been encountered previously in that context) may play an important role in the memory for odors over short delays. Whether there is a separate short-term odor memory store is also addressed.
A case report of takotsubo syndrome complicated by ischaemic stroke: the clinical dilemma of anticoagulation
Authors: Iuliano Giuseppe , Napoletano Rosa , Vecchione Carmine , Citro Rodolfo
Published: March 2021

Background

Takotsubo syndrome (TTS) is an acute and transient heart failure syndrome due to reversible myocardial dysfunction characterized by a wide spectrum of possible clinical scenarios. About one-fifth of TTS patients experience adverse in-hospital events. Thromboembolic complications, especially stroke, have been reported, albeit in a minority of patients.

Case summary

A 69-year-old woman presented to our emergency department for dyspnoea after a family quarrel. Electrocardiogram revealed ST-segment elevation in anterolateral leads and laboratory exams showed a slight elevation of high-sensitivity cardiac troponin. The patient was treated according to current guidelines on ST-elevation myocardial infarction and referred to the cath lab. Urgent coronary angiography revealed normal coronary arteries. Based on the patient profile and instrumental findings, a diagnosis of TTS was hypothesized. After 6 days, the patient developed dysarthria and right hemiparesis under therapy with aspirin, whilst low molecular weight heparin had been previously withdrawn. Transthoracic echocardiography (TTE) revealed persisting apical akinesia and a subtle intraventricular thrombus. Head computed tomography and magnetic resonance imaging detected focal areas of ischaemic necrosis resembling diffuse cardioembolic lesions. Anticoagulation therapy was started and regular TTE showed complete recovery of myocardial systolic function and absence of ventricular thrombi at 1-month follow-up. The patient fully recovered speech after 5 months.

Discussion

This challenging case reinforces current recommendations to administer antithrombotic therapy in TTS patients with extensive apical dysfunction up to complete or near-complete recovery of myocardial contractility, regardless of the presence of atrial fibrillation, and highlights the importance of close TTE monitoring during the acute phase.
Efficacy and safety of direct oral anticoagulant in morbidly obese patients with atrial fibrillation: systematic review and meta-analysis
Authors: Thangjui Sittinun , Kewcharoen Jakrin , Yodsuwan Ratdanai , Trongtorsak Angkawipa , Thyagaturu Harshith , Shrestha Bishesh , Winans Amanda R M , Bischof Edward
Published: March 2021

Aims

We conducted a systematic review and meta-analysis on three outcomes. We assessed the efficacy and safety of direct oral anticoagulants (DOAC) compared to vitamin K antagonists (VKA) in morbidly obese patients with atrial fibrillation (AF). We compared the efficacy and safety of DOAC in obese patients and non-obese patients with AF. Finally, we updated the current knowledge of outcomes of AF patients with obesity compared with normal-weight patients regardless of anticoagulation type.

Methods and results

Using PubMed and Embase, we searched for literature published from inception to August 2020 for studies conducted in morbidly obese patients with AF who used DOACs and/or VKA for stroke or systemic embolism (stroke/SE) prevention that report efficacy and/or safety data. GRADE assessment was performed to determine the quality of the meta-analysis results. Direct oral anticoagulant was not statistically different from VKA in reducing stroke/SE with relative risk (RR) of 0.85 [95% confidence interval (CI): 0.56–1.29; very low certainty evidence]. Major bleeding risk was lower in the DOAC groups with RR of 0.62 (95% CI: 0.48–0.80; low certainty evidence). Obese patients with AF who used DOACs had lower risk of stroke/SE and similar major bleeding risk compared to non-obese patients with RR of 0.77 (95% CI: 0.70–0.84; low certainty evidence) and 1.02 (95% CI: 0.94–1.09; low certainty evidence), respectively. Obese patients with AF who used any type of anticoagulant had lower risk of stroke/SE compared to normal-weight patients with RR of 0.62 (95% CI: 0.57–0.69; low certainty evidence).

Conclusion

The use of DOACs in morbidly obese patients may be reasonable if needed, and more dedicated studies are needed to make a more robust recommendation.
Gut microbiome composition predicts summer core range size in two divergent ungulates
Authors: Wolf Jesse F , Kriss Krystal D , MacAulay Kara M , Munro Keith , Patterson Brent R , Shafer Aaron B A
Published: March 2021

The gut microbiome of animals vary by age, diet, and habitat, and directly influences an individual's health. Similarly, variation in home ranges is linked to feeding strategies and fitness. Ungulates (hooved mammals) exhibit species-specific microbiomes and habitat use patterns. We combined gut microbiome and movement data to assess relationships between space use and the gut microbiome in a specialist and a generalist ungulate. We GPS radiocollared 24 mountain goats (Oreamnos americanus) and 34 white-tailed deer (Odocoileus virginianus), collected fecal samples, and conducted high-throughput sequencing of the 16S rRNA gene. We generated gut diversity metrics and key bacterial ratios. Our research question centred around the idea that larger Firmicutes to Bacteroidetes ratios confer body size or fat advantages that allow for larger home ranges, and relationships of disproportionate habitat use are stronger in the habitat specialist mountain goat. Firmicutes to Bacteroidetes ratios were positively correlated with core range area in both species. Mountain goats exhibited a negative relationship between gut diversity and proportional use of treed areas and escape terrain, and no relationships were detected in the habitat generalist white-tailed deer. This is the first study to relate range size to the gut microbiome in wild ungulates and is an important proof of concept that advances the information that can be gleaned from non-invasive sampling.
The 96-week clinical outcomes after cessation of nucleos(t)ide analog treatment in chronic hepatitis B patients
Authors: Xu Wen-Xiong , Li Yang-Mei , Li Jian-Guo , Mei Yong-Yu , Chen You-Ming , Li Xue-Jun , Lin Chao-Shuang , Deng Hong , Zhao Zhi-Xin , Xie Dong-Ying , Gao Zhi-Liang , Peng Liang
Published: March 2021

Background

Chronic hepatitis B (CHB) patients have a high virological relapse rate after cessation of nucleos(t)ide analog (NA) treatment, but the clinical outcome remains unclear. This study aimed to investigate the 96-week clinical outcomes and the risk factors for relapse in CHB after cessation of NAs.

Methods

This study was a prospective trial; 74 eligible patients were enrolled. The patients underwent NA cessation and follow-up according to the 2012 Asian Pacific Association for the Study of the Liver Guideline. Symptoms, biochemical (aspartate aminotransferase [AST], alanine aminotransferase [ALT], total bilirubin, urea nitrogen, creatinine), virological data (hepatitis B surface antigen [HBsAg], hepatitis B e antigen [HBeAg], hepatitis B e antibody [HBeAb], hepatitis B virus [HBV] DNA levels), and color Doppler ultrasound examination results were recorded and analysed.

Results

After NA cessation, 19 cases were HBsAg-negative without relapse during the 96-week follow-up. Of the 55 cases of HBsAg-positive after cessation, four types of clinical outcomes were observed. Twelve patients had no relapse during the 96-week follow-up (type A, 21.8%), 7 patients underwent virological relapses but spontaneously had a non-virological relapse (type B, 12.7%), 10 patients maintained virological relapse (type C, 18.2%), and 26 patients turned to clinical relapse, received NA retreatment, and achieved ALT normalization and negative conversion of HBV DNA within 12 months (type D, 47.3%). The 2-year overall cumulative rates of virological and clinical relapses were 58.1% and 24.3%, respectively. Independent factors associated with virological relapse were duration of negative HBV DNA, EOT (end of treatment) HBsAg, and original status of HBeAg. The EOT HBsAg was also an independent factor for clinical relapse.

Conclusions

There are four types of clinical outcomes in patients with CHB after cessation of NA treatment. Further research is needed to explore the mechanism of different clinical outcomes. The EOT HBsAg level is an independent factor associated with both virological and clinical relapse.
Adaptive Metabolic and Inflammatory Responses Identified Using Accelerated Aging Metrics Are Linked to Adverse Outcomes in Severe SARS-CoV-2 Infection
Authors: Márquez-Salinas Alejandro , Fermín-Martínez Carlos A , Antonio-Villa Neftalí Eduardo , Vargas-Vázquez Arsenio , Guerra Enrique C , Campos-Muñoz Alejandro , Zavala-Romero Lilian , Mehta Roopa , Bahena-López Jessica Paola , Ortiz-Brizuela Edgar , González-Lara María Fernanda , Roman-Montes Carla M , Martinez-Guerra Bernardo A , Ponce de Leon Alfredo , Sifuentes-Osornio José , Gutiérrez-Robledo Luis Miguel , Aguilar-Salinas Carlos A , Bello-Chavolla Omar Yaxmehen
Published: March 2021

Background

Chronological age (CA) is a predictor of adverse coronavirus disease 2019 (COVID-19) outcomes; however, CA alone does not capture individual responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Here, we evaluated the influence of aging metrics PhenoAge and PhenoAgeAccel to predict adverse COVID-19 outcomes. Furthermore, we sought to model adaptive metabolic and inflammatory responses to severe SARS-CoV-2 infection using individual PhenoAge components.

Method

In this retrospective cohort study, we assessed cases admitted to a COVID-19 reference center in Mexico City. PhenoAge and PhenoAgeAccel were estimated using laboratory values at admission. Cox proportional hazards models were fitted to estimate risk for COVID-19 lethality and adverse outcomes (intensive care unit admission, intubation, or death). To explore reproducible patterns which model adaptive responses to SARS-CoV-2 infection, we used k-means clustering using PhenoAge components.

Results

We included 1068 subjects of whom 222 presented critical illness and 218 died. PhenoAge was a better predictor of adverse outcomes and lethality compared to CA and SpO2 and its predictive capacity was sustained for all age groups. Patients with responses associated to PhenoAgeAccel >0 had higher risk of death and critical illness compared to those with lower values (log-rank p < .001). Using unsupervised clustering, we identified 4 adaptive responses to SARS-CoV-2 infection: (i) inflammaging associated with CA, (ii) metabolic dysfunction associated with cardiometabolic comorbidities, (iii) unfavorable hematological response, and (iv) response associated with favorable outcomes.

Conclusions

Adaptive responses related to accelerated aging metrics are linked to adverse COVID-19 outcomes and have unique and distinguishable features. PhenoAge is a better predictor of adverse outcomes compared to CA.