bluuebunny/crossref_metadata_2025 huggingface dataset:
Survey of case study users during pandemic shift to remote instruction
Authors: Herreid Clyde Freeman , Prud’homme-Généreux Annie , Wright Carolyn , Schiller Nancy , Herreid Ky F.
Published: August 2021

Before COVID-19, the use of case studies to learn science was well established in high school and postsecondary classrooms. Once the pandemic ensued, many faculty continued to use the method as a way to infuse elements of active learning remotely. The results of a survey taken by 600 faculty reveal how they accomplished this feat. Respondents to the survey found that the case method readily transferred to online learning. Most used a mixture of synchronous and asynchronous classrooms. Serious challenges were encountered, primarily due to the difficulty instructors had in keeping track of learner participation. Many obstacles were overcome by creative strategies such as using Google Forms. Some semblance of a normal classroom was achieved by using online conferencing tools and using small groups in synchronous breakout rooms. Cases were commonly broken into chunks and spread over several days. This worked especially well with cases that were already structured this way, including interrupted cases and problem-based learning exercises. Assessment of student performance largely followed the traditional path of exams, projects, and essays, although a third of the faculty attempted to evaluate participation. Classes conducted via an asynchronous approach were largely lecture based, with cases given to learners to complete as homework either individually or as groups. The greatest challenge in this setting was that answers to case questions were often readily available to learners on the internet. This was avoided by faculty modifying questions or creating their own.
The impact of weekly multicourse collective exams on pharmacy student academic behaviors and learning in an integrated biological sciences course
Authors: Dirks-Naylor Amie J.
Published: August 2021

Doctor of Pharmacy (PharmD) degree program curricula are typically comprised of heavy course loads and assessment burden. Typically, students “live” from exam to exam only preparing and studying for the exam directly ahead of them while neglecting concurrent courses. Therefore, the aim of the study was to determine the impact of weekly multicourse collective exams academic behaviors and learning in an integrated biological sciences (BSI) course within a PharmD program. Weekly multicourse exams included questions, four per credit hour, from all first semester courses that traditionally included summative exams. Seven courses contributed questions, which amounted to 15 weekly exams of ∼60 questions. No other graded assessments were given in any of the courses, other than individual course cumulative final exams; the final exams in each course were not collective. After completion of final exams, a Qualtrics survey was emailed to all students and the two professors teaching the course. Course grades, not including the final exam, were compared between two cohorts with or without the collective exams to determine impact on learning. The cumulative final exam was compared between cohorts to determine impact on retention. The majority of students agreed or strongly agreed that the weekly collective exams encouraged them to study BSI more frequently, most days of the week, reduced the likelihood of skipping class, and increased likelihood to pay attention and engage in class. The majority believed that they better learned and retained the BSI material. The majority specified that they liked the collective exams for BSI and preferred it over a traditional exam schedule. Learning also appeared to be improved. However, the impact on retention is less clear and requires further research. In conclusion, the weekly multicourse collective exams improved academic behaviors and learning.
Report on the online course “Basic Concepts in Neurophysiology”: a course promoted during the COVID-19 pandemic quarantine
Authors: Carrazoni Guilherme Salgado , Lima Karine Ramires , Alves Niege , Mello-Carpes Pâmela Billig
Published: August 2021

“Basic Concepts in Neurophysiology” was a 3-wk online course developed during six synchronous meetings combined with asynchronous activities. We proposed an active learning course that used free online platforms to teach physiology during a period in which undergraduates were not in classrooms or taking online classes due to the COVID-19 pandemic. Herein, we report the course organization and the students’ involvement in, acceptance of, and evaluation of the course. To address the students’ perceptions about these points, we sent a questionnaire to 49 participants who finished the course. We found that although most students (52.5%) had never taken a course with similar methods before, almost all of them (95%) liked the flipped class model. Additionally, a majority of the students (92.5%) said that the method increased their study frequency during the social distancing period, which is an important aspect to consider during this challenging time for both students and professors.
Nicotinamide N-methyltransferase upregulation via the mTORC1-ATF4 pathway activation contributes to palmitate-induced lipotoxicity in hepatocytes
Authors: Griffiths Alexandra , Wang Jun , Song Qing , Iyamu Iredia D. , Liu Lifeng , Park Jooman , Jiang Yuwei , Huang Rong , Song Zhenyuan
Published: August 2021

Defined as the dysfunction and/or cell death caused by toxic lipids accumulation in hepatocytes, hepatic lipotoxicity plays a pathological role in nonalcoholic fatty liver disease. The cellular and molecular mechanisms underlying lipotoxicity remain to be elucidated. In this study, using AML12 cells, a nontransformed murine hepatocyte cell line, exposed to palmitate (a 16-C saturated fatty acid) as an experimental model, we investigated the role and mechanisms of nicotinamide N-methyltransferase (NNMT), a methyltransferase catalyzing nicotinamide methylation and degradation, in hepatic lipotoxicity. We initially identified activating transcription factor 4 (ATF4) as a major transcription factor for hepatic NNMT expression. Here, we demonstrated that palmitate upregulates NNMT expression via activating ATF4 in a mechanistic target of rapamycin complex 1 (mTORC1)-dependent mechanism in that mTORC1 inhibition by both Torin1 and rapamycin attenuated ATF4 activation and NNMT upregulation. We further demonstrated that the mTORC1-dependent ATF4 activation is an integral signaling event of unfolded protein response (UPR) as both ATF4 activation and NNMT upregulation by tunicamycin, a well-documented endoplasmic reticulum (ER) stress inducer, are blunted when hepatocytes were pretreated with Torin1. Importantly, our data uncovered that NNMT upregulation contributes to palmitate-induced hepatotoxicity as NNMT inhibition, via either pharmacological (NNMT inhibitors) or genetic approach (siRNA transfection), provided protection against palmitate lipotoxicity. Our further mechanistic exploration identified protein kinase A (PKA) activation to contribute, at least, partially to the protective effect of NNMT inhibition against lipotoxicity. Collectively, our data demonstrated that NNMT upregulation by the mTORC1-ATF4 pathway activation contributes to the development of lipotoxicity in hepatocytes.
Acute effects of sublingual nitroglycerin on cardiovagal and sympathetic baroreflex sensitivity
Authors: Hamaoka Takuto , Blaha Cheryl , Luck Jonathan C. , Leuenberger Urs A. , Sinoway Lawrence I. , Cui Jian
Published: August 2021

The effects of nitroglycerin (glyceryl trinitrate, GTN) on baroreflex sensitivity (BRS) are incompletely understood. Moreover, there are no reports evaluating the acute responses in both the sympathetic BRS (SBRS) and the cardiovagal BRS (CBRS) to the administration of sublingual GTN. We hypothesized that sublingual GTN modulates both CBRS and SBRS. In 10 healthy subjects, beat-to-beat heart rate (HR), blood pressure (BP), and muscle sympathetic nerve activity (MSNA) were recorded before and for 10 min after sublingual administration of GTN 0.4 mg. SBRS was evaluated from the relationship between spontaneous variations in diastolic BP and MSNA. CBRS was assessed with the sequence technique. These variables were assessed during baseline, during 3rd–6th min ( post A), and 7th–10th min ( post B) after GTN administration. Two min after GTN administration, MSNA increased significantly and remained significantly elevated during recording. Compared with baseline, CBRS decreased significantly ( post A: 12.9 ± 1.6 to 7.1 ± 1.0 ms/mmHg, P < 0.05), whereas SBRS increased significantly ( post A: 0.8 ± 0.2 to 1.5 ± 0.2 units·beat−1·mmHg−1, P < 0.05) with an upward shift of the operating point. There were no differences in these variables between posts A and B. A clinical dose of GTN increased MSNA rapidly through effects on both CBRS and SBRS. These effects should be kept in mind when nitrates are used to clinically treat chest pain and acute coronary syndromes and used as vasodilators in experimental settings.
Organization of parietoprefrontal and temporoprefrontal networks in the macaque
Authors: Giarrocco Franco , Averbeck Bruno B.
Published: August 2021

The study of cortical connectivity is crucial for understanding brain function and disease. We show that temporofrontal and parietofrontal networks in the macaque can be described in terms of circuits among clusters of areas that share similar inputs and functional properties. The resulting overall architecture described a dual subdivision of the frontal cortex, consistent with the main cortical fiber bundles and an evolutionary trend that underlies the organization of the cortex in the macaque.
The Comprehensive Contributions of Endpoint Degree and Coreness in Link Prediction
Authors: Tian Yang , Wang Yanan , Tian Hui , Cui Qimei
Published: August 2021

In past studies, researchers find that endpoint degree, H‐index, and coreness can quantify the influence of endpoints in link prediction, especially the synthetical endpoint degree and H‐index improve prediction performances compared with the traditional link prediction models. However, neither endpoint degree nor H‐index can describe the aggregation degree of neighbors, which results in inaccurate expression of the endpoint influence intensity. Through abundant investigations, we find that researchers ignore the importance of coreness for the influence of endpoints. Meanwhile, we also find that the synthetical endpoint degree and coreness can not only describe the maximal connected subgraph of endpoints accurately but also express the endpoint influence intensity. In this paper, we propose the DCHI model by synthesizing endpoint degree and coreness and the HCHI model by synthesizing H‐index and coreness on SRW‐based models, respectively. Extensive simulations on twelve real benchmark datasets show that, in most cases, DCHI shows better prediction performances in link prediction than HCHI and other traditional models.
A Framework to Test Resistency of Detection Algorithms for Stepping‐Stone Intrusion on Time‐Jittering Manipulation
Authors: Wang Lixin , Yang Jianhua , Workman Michael , Wan Peng-Jun
Published: August 2021

Hackers on the Internet usually send attacking packets using compromised hosts, called stepping‐stones, in order to avoid being detected and caught. With stepping‐stone attacks, an intruder remotely logins these stepping‐stones using programs like SSH or telnet, uses a chain of Internet hosts as relay machines, and then sends the attacking packets. A great number of detection approaches have been developed for stepping‐stone intrusion (SSI) in the literature. Many of these existing detection methods worked effectively only when session manipulation by intruders is not present. When the session is manipulated by attackers, there are few known effective detection methods for SSI. It is important to know whether a detection algorithm for SSI is resistant on session manipulation by attackers. For session manipulation with chaff perturbation, software tools such as Scapy can be used to inject meaningless packets into a data stream. However, to the best of our knowledge, there are no existing effective tools or efficient algorithms to produce time‐jittered network traffic that can be used to test whether an SSI detection method is resistant on intruders’ time‐jittering manipulation. In this paper, we propose a framework to test resistency of detection algorithms for SSI on time‐jittering manipulation. Our proposed framework can be used to test whether an existing or new SSI detection method is resistant on session manipulation by intruders with time‐jittering.
Coupled Dynamics of Vehicle‐Bridge Interaction System Using High Efficiency Method
Authors: Sun Lu , Zhao Xingzhuang
Published: August 2021

Vehicle‐bridge interaction is the core for a variety of applications, including vehicle vibration, bridge vibration, bridge structural health monitoring, weight‐in‐motion, bridge condition inspection, and load rating. These applications give rise to a great interest in pursuing a high‐efficiency method that can tackle intensive computation in the context of vehicle‐bridge interaction. This paper studies the accuracy and efficiency of discretizing the beam in space as lumped masses using the flexibility method and as finite elements using the stiffness method. Computational complexity analysis is carried out along with a numerical case study to compare the accuracy and efficiency of both methods against the analytical solutions. It is found that both methods result in a similar level of accuracy, but the flexibility method overperforms the stiffness method in terms of computational efficiency. This high efficiency algorithm and corresponding discretization schema are applied to study the dynamics of vehicle‐bridge interaction. A system of coupled equations is solved directly for a simply supported single‐span bridge and a four‐degree‐of‐freedom vehicle modeling. Pavement roughness significantly influences dynamic load coefficient, suggesting preventative maintenance or timely maintenance of pavement surface on a bridge, to reduce pavement roughness, is of significant importance for bridge’s longevity and life‐cycle cost benefit. For class A and B level pavement roughness, the dynamic load coefficient is simulated within 2.0, compatible with specifications of AASHTO standard, Australian standard, and Switzerland standard. However, the Chinese code underestimates the dynamic load coefficient for a bridge with a fundamental frequency of around 4 Hz. The proposed method is applicable to different types of bridges as well as train‐bridge interaction.
Iterative Algorithms for Deblurring of Images in Case of Electrical Capacitance Tomography
Authors: Jaffri Nasif R. , Almogren Ahmad , Ahmad Aftab , Abrar Usama , Radwan Ayman , Khan Farzan A.
Published: August 2021

Electrical capacitance tomography (ECT) has been used to measure flow by applying gas-solid flow in coal gasification, pharmaceutical, and other industries. ECT is also used for creating images of physically confined objects. The data collected by the acquisition system to produce images undergo blurring because of ambient conditions and the electronic circuitry used. This research includes the principle of ECT techniques for deblurring images that were created during measurement. The data recorded by the said acquisition system ascends a large number of linear equations. This system of equations is sparse and ill-conditioned and hence is ill-posed in nature. A variety of reconstruction algorithms with many pros and cons are available to deal with ill-posed problems. Large-scale systems of linear equations resulting during image deblurring problems are solved using iterative regularization algorithms. The conjugate gradient algorithm for least-squares problems (CGLS), least-squares QR factorization (LSQR), and the modified residual norm steepest descent (MRNSD) algorithm are the famous variations of iterative algorithms. These algorithms exhibit a semiconvergence behavior; that is, the computed solution quality first improves and then reduces as the error norm decreases and later increases with each iteration. In this work, soft thresholding has been used for image deblurring problems to tackle the semiconvergence issues. Numerical test problems were executed to indicate the efficacy of the suggested algorithms with criteria for optimal stopping iterations. Results show marginal improvement compared to the traditional iterative algorithms (CGLS, LSQR, and MRNSD) for resolving semiconvergence behavior and image restoration.
Do City Size and Population Density Influence Regional Innovation Output Evidence from China?
Authors: Shukai Cai , Haochen Wang , Xiaohong Zhou
Published: August 2021

This paper proposed a substantial gap to a large‐scale population density and city size on regional innovation output. To measure the impact of population density and city size on regional innovation output, this study employs the threshold effect model with panel data of 230 prefectures and cities from 2007 to 2016. Based on the econometric analysis, the results exhibit a positive and significant relationship between population density, city size, and innovation output. This correlation suggests that when one factor increases, the other increases in the parallel direction and vice versa. Moreover, when the city size expands the threshold value of 2.934 percent, the innovation promotes and increases the effects of urban‐scale expansion. On the other hand, for medium‐ and low‐density cities, the increase of urban population density has a significant and positive impact on urban innovation output. However, for high‐density cities, the increase of population density has no significant impact on innovation output.
Research on Underground Chemical Gas Monitoring and Target Location Based on an Improved Moth Flame Algorithm
Authors: Tu Chunmei , Chen Guobin
Published: August 2021

The danger of downhole work is mainly due to the chemical toxic gases and flammable gases NO2, CO, SO2, H2S, CH4, CO2, etc. When the concentration reaches a certain value, it will produce very great harm. With the continuous development of sensor technology and communication technology, it is necessary to monitor the relevant geographic features below the ground. Because of the complex environmental parameters of the coal mine roadway and the interference caused by various electrical equipment, the transmission of mine electromagnetic signals will be affected, resulting in low positioning accuracy. However, the underground chemical gas leakage leads to the life of underground workers which cannot be guaranteed, so it is necessary to effectively monitor the concentration of chemical gas components in underground mines. In this paper, a moth flame algorithm based on optimized inertia weights is proposed. By continuously improving the local inertia weights, the global optimum is determined by using the change of inertia weights in the iterative process of the algorithm. By testing the convergence and optimal value of several algorithms under common test functions, IMFO can obtain the global optimal solution. Finally, the concentrations of chemical gases NO2, CO, SO2, H2S, CH4, and CO2 are monitored by setting specific areas to see if they reach the early warning values. Then, 16 coordinates in the region are used to predict the above method, and the IMFO algorithm can achieve the best prediction effect.
Energy‐Efficient Routing Using Fuzzy Neural Network in Wireless Sensor Networks
Authors: Varun Rajesh Kumar , Gangwar Rakesh C. , Kaiwartya Omprakash , Aggarwal Geetika
Published: August 2021

In wireless sensor networks, energy is a precious resource that should be utilized wisely to improve its life. Uneven distribution of load over sensor devices is also the reason for the depletion of energy that can cause interruptions in network operations as well. For the next generation’s ubiquitous sensor networks, a single artificial intelligence methodology is not able to resolve the issue of energy and load. Therefore, this paper proposes an energy‐efficient routing using a fuzzy neural network (ERFN) to minimize the energy consumption while fairly equalizing energy consumption among sensors thus as to prolong the lifetime of the WSN. The algorithm utilizes fuzzy logic and neural network concepts for the intelligent selection of cluster head (CH) that will precisely consume equal energy of the sensors. In this work, fuzzy rules, sets, and membership functions are developed to make decisions regarding next‐hop selection based on the total residual energy, link quality, and forward progress towards the sink. The developed algorithm ERFN proofs its efficiency as compared to the state‐of‐the‐art algorithms concerning the number of alive nodes, percentage of dead nodes, average energy decay, and standard deviation of residual energy.
Aspect‐Level Sentiment Analysis Approach via BERT and Aspect Feature Location Model
Authors: Pang Guangyao , Lu Keda , Zhu Xiaoying , He Jie , Mo Zhiyi , Peng Zizhen , Pu Baoxing
Published: August 2021

With the rapid development of Internet social platforms, buyer shows (such as comment text) have become an important basis for consumers to understand products and purchase decisions. The early sentiment analysis methods were mainly text‐level and sentence‐level, which believed that a text had only one sentiment. This phenomenon will cover up the details, and it is difficult to reflect people’s fine‐grained and comprehensive sentiments fully, leading to people’s wrong decisions. Obviously, aspect‐level sentiment analysis can obtain a more comprehensive sentiment classification by mining the sentiment tendencies of different aspects in the comment text. However, the existing aspect‐level sentiment analysis methods mainly focus on attention mechanism and recurrent neural network. They lack emotional sensitivity to the position of aspect words and tend to ignore long‐term dependencies. In order to solve this problem, on the basis of Bidirectional Encoder Representations from Transformers (BERT), this paper proposes an effective aspect‐level sentiment analysis approach (ALM‐BERT) by constructing an aspect feature location model. Specifically, we use the pretrained BERT model first to mine more aspect‐level auxiliary information from the comment context. Secondly, for the sake of learning the expression features of aspect words and the interactive information of aspect words’ context, we construct an aspect‐based sentiment feature extraction method. Finally, we construct evaluation experiments on three benchmark datasets. The experimental results show that the aspect‐level sentiment analysis performance of the ALM‐BERT approach proposed in this paper is significantly better than other comparison methods.
Multiple Myeloma with Foamy Mott Cells
Authors: Nalbandyan Karen , Benharroch Daniel , Samueli Benzion , Kafka Michael , Gourevitch Anna
Published: August 2021

Intracytoplasmic assorted vacuoles containing immunoglobulin collections are occasionally seen in multiple myeloma. When abundant, they impart a foamy appearance to the tumor cells, which is a potential source for diagnostic pitfalls. Herein, we report the case of a patient who presented with skeletal pain and CT confirmed lytic lesions. A bone marrow biopsy revealed multiple myeloma with unusual foamy Mott cells. The patient was subsequently treated with four cycles of cyclophosphamide, bortezomib, and dexamethasone induction therapy, followed by 3 cycles of lenalidomide with dexamethasone. A biopsy performed following initial biological and immunomodulatory drugs revealed different morphological and clonal characteristics. These features were modified again, five years later, and again, after two years of close monitoring. Hematopathologists should be aware of this morphologic variant of myeloma as well as for the capacity of clonal characteristics, such as light chain monotype, to fluctuate subsequent to treatment.
RS-Lane: A Robust Lane Detection Method Based on ResNeSt and Self-Attention Distillation for Challenging Traffic Situations
Authors: Zhang Ronghui , Wu Yueying , Gou Wanting , Chen Junzhou
Published: August 2021

Lane detection plays an essential part in advanced driver-assistance systems and autonomous driving systems. However, lane detection is affected by many factors such as some challenging traffic situations. Multilane detection is also very important. To solve these problems, we proposed a lane detection method based on instance segmentation, named RS-Lane. This method is based on LaneNet and uses Split Attention proposed by ResNeSt to improve the feature representation on slender and sparse annotations like lane markings. We also use Self-Attention Distillation to enhance the feature representation capabilities of the network without adding inference time. RS-Lane can detect lanes without number limits. The tests on TuSimple and CULane datasets show that RS-Lane has achieved comparable results with SOTA and has improved in challenging traffic situations such as no line, dazzle light, and shadow. This research provides a reference for the application of lane detection in autonomous driving and advanced driver-assistance systems.
Study on Ground Collapse of Covered Karst Soil Caves by Sudden Drop of Groundwater
Authors: Chen Xuejun , Guo Ruijian , Tang Lingming , Zhang Xiaochen
Published: August 2021

In this study, the ellipsoidal soil cave with vertical collapses in the covering karst area is studied. Based on certain assumptions, the mechanical model of karst collapse caused by groundwater drop was established. Then, based on the negative pressure calculation formula of soil cave cavity according to Boyle–Mariotte’s law, the expression of the stability coefficient of the soil cave was proposed. Subsequently, the feasibility of the theoretical formula was verified. The calculation example analyzed the relationship of groundwater parameters and overburden thickness. The results show that when the initial groundwater level is higher than the top of cave, the law between the stability coefficient of soil cave and groundwater drawdown shows the jumping horizontal broken line. Thus, soil cave tends to collapse when the falling groundwater level drops over the vault; when the initial groundwater level ranges from the bottom to the top of the cave body, the stability coefficient and groundwater drawdown show a negative correlation law, the curve is steep at the early stage and then becomes gentle at the latter stage, and the higher the initial groundwater level in the cave is, the greater stability coefficient of soil cave reduces; when the initial groundwater level is lower than the bottom of the cave, the effect of drawdown is limited. In addition, for the small drawdown or low initial groundwater level, the stability coefficient of soil cave first decreases and then increases with the increases in thickness of overburden, and the thinner the overburden is, the greater the drawdown rate is; when the drawdown or the initial groundwater level is higher, the stability coefficient of soil cave positively relates to the thickness of the overburden layer.
Deep Reinforcement Learning for Scheduling in an Edge Computing‐Based Industrial Internet of Things
Authors: Wu Jingjing , Zhang Guoliang , Nie Jiaqi , Peng Yuhuai , Zhang Yunhou
Published: August 2021

The demand for improving productivity in manufacturing systems makes the industrial Internet of things (IIoT) an important research area spawned by the Internet of things (IoT). In IIoT systems, there is an increasing demand for different types of industrial equipment to exchange stream data with different delays. Communications between massive heterogeneous industrial devices and clouds will cause high latency and require high network bandwidth. The introduction of edge computing in the IIoT can address unacceptable processing latency and reduce the heavy link burden. However, the limited resources in edge computing servers are one of the difficulties in formulating communication scheduling and resource allocation strategies. In this article, we use deep reinforcement learning (DRL) to solve the scheduling problem in edge computing to improve the quality of services provided to users in IIoT applications. First, we propose a hierarchical scheduling model considering the central‐edge computing heterogeneous architecture. Then, according to the model characteristics, a deep intelligent scheduling algorithm (DISA) based on a double deep Q network (DDQN) framework is proposed to make scheduling decisions for communication. We compare DISA with other baseline solutions using various performance metrics. Simulation results show that the proposed algorithm is more effective than other baseline algorithms.
Effects of Selenium Supplement on B Lymphocyte Activity in Experimental Autoimmune Thyroiditis Rats
Authors: Li Yang , Zuo Xinhe , Hua Chuan , Zhao Yong , Pei Xun , Tian Man
Published: August 2021

Background and Objective. Thyroid is the organ with the highest selenium content in mammals, and selenium is an essential micronutrient that has close relationship with thyroid autoimmunity. However, the mechanism of how selenium modulates autoimmune thyroiditis remains to be elucidated. Thyroglobulin antibody (TGAb) and thyroid peroxidase antibody (TPOAb), which are produced by B lymphocytes, play a crucial role in autoimmune thyroiditis. The present study was aimed to investigate the effects of selenium supplement on thyroid autoimmunity and B lymphocyte activity in experimental autoimmune thyroiditis (EAT) model rats. Methods. 45 healthy and adult female SD rats were randomly divided into three groups: normal control group, EAT model group, and selenium yeast supplement EAT group. The EAT model rats were induced by subcutaneous injection of porcine thyroglobulin and fed with high iodine water. The concentrations of serum thyroid-stimulating hormone (TSH), TGAb, TPOAb, and B cell activating factor (BAFF) were detected in each group by enzyme-linked immunosorbent assay (ELISA), and the expression of interleukin-10 (IL-10) in thyroid tissue was detected by immunohistochemistry. B cells and regulatory B cells (Bregs) ratios in the spleen of rats were analyzed by flow cytometry. Results. In contrast with the EAT model group, the levels of serum TSH, TGAB, TPOAb, and BAFF were decreased, while IL-10 expression was increased in thyroid tissue, and Bregs ratio was upregulated in the spleen (all

p
<
0.05

) in the selenium yeast supplement EAT group. Conclusion. Selenium yeast supplement could partially attenuate immune imbalance in EAT rats, which may be related to the mechanism of modulating B lymphocyte activity.
Hierarchical Attention Graph Embedding Networks for Binary Code Similarity against Compilation Diversity
Authors: Wang Yan , Jia Peng , Huang Cheng , Liu Jiayong , He Peisong
Published: August 2021

Binary code similarity comparison is the technique that determines if two functions are similar by only considering their compiled form, which has many applications, including clone detection, malware classification, and vulnerability discovery. However, it is challenging to design a robust code similarity comparison engine since different compilation settings that make logically similar assembly functions appear to be very different. Moreover, existing approaches suffer from high-performance overheads, lower robustness, or poor scalability. In this paper, a novel solution HBinSim is proposed by employing the multiview features of the function to address these challenges. It first extracts the syntactic and semantic features of each basic block by static analysis. HBinSim further analyzes the function and constructs a syntactic attribute control flow graph and a semantic attribute control flow graph for each function. Then, a hierarchical attention graph embedding network is designed for graph-structured data processing. The network model has a hierarchical structure that mirrors the hierarchical structure of the function. It has three levels of attention mechanisms applied at the instruction, basic block, and function level, enabling it to attend differentially to more and less critical content when constructing the function representation. We conduct extensive experiments to evaluate its effectiveness and efficiency. The results show that our tool outperforms the state-of-the-art binary code similarity comparison tools by a large margin against compilation diversity clone searching. A real-world vulnerabilities search case further demonstrates the usefulness of our system.
Preclinical Assessment of a MUC12-Targeted BiTE (Bispecific T-cell Engager) Molecule
Authors: Pham Elizabeth , Friedrich Matthias , Aeffner Famke , Lutteropp Michael , Mariano Natalie F. , Deegen Petra , Dahlhoff Christoph , Vogel Franziska , Bluemel Claudia , Harrold John M. , Brandl Christian , Grinberg Natalia , Rattel Benno , Coxon Angela , Bailis Julie M.
Published: August 2021

MUC12 is a transmembrane mucin that is highly expressed in >50% of primary and metastatic colorectal tumors. MUC12 is also expressed by normal epithelial cells of the colon and small intestine. Although MUC12 localization in normal epithelial cells is restricted to the apical membrane, expression in tumors is depolarized and shows broad membrane localization. The differential localization of MUC12 in tumor cells as compared with normal cells makes it a potential therapeutic target. Here, we evaluated targeting of MUC12 with a BiTE (bispecific T-cell engager) molecule. We generated a panel of proof-of-concept half-life extended (HLE) BiTE molecules that bind MUC12 on tumor cells and CD3 on T cells. We prioritized one molecule based on in vitro activity for further characterization in vivo. In vitro, the MUC12 HLE BiTE molecule mediated T-cell–redirected lysis of MUC12-expressing cells with half-maximal lysis of 4.4 ± 0.9 to 117 ± 78 pmol/L. In an exploratory cynomolgus monkey toxicology study, the MUC12 HLE BiTE molecule administered at 200 μg/kg with a step dose to 1,000 μg/kg was tolerated with minimal clinical observations. However, higher doses were not tolerated, and there was evidence of damage in the gastrointestinal tract, suggesting dose levels projected to be required for antitumor activity may be associated with on-target toxicity. Together, these data demonstrate that the apically restricted expression of MUC12 in normal tissues is accessible to BiTE molecule target engagement and highlight the difficult challenge of identifying tumor-selective antigens for solid tumor T-cell engagers.
Application of Blood Group Genotyping by Next-Generation Sequencing in Various Immunohaematology Cases
Authors: Kim Tae Yeul , Yu HongBi , Phan Minh-Trang Thi , Jang Ja-Hyun , Cho Duck
Published: August 2021

Background: Next-generation sequencing (NGS) technology has been recently introduced into blood group genotyping; however, there are few studies using NGS-based blood group genotyping in real-world clinical settings. In this study, we applied NGS-based blood group genotyping into various immunohaematology cases encountered in routine clinical practice. Methods: This study included 4 immunohaematology cases: ABO subgroup, ABO chimerism, antibody to a high-frequency antigen (HFA), and anti-CD47 interference. We designed a hybridization capture-based NGS panel targeting 39 blood group-related genes and applied it to the 4 cases. Results: NGS analysis revealed a novel intronic variant (NM_020469.3:c.29-10T>G) in a patient with an Ael phenotype and detected a small fraction of ABO*A1.02 (approximately 3–6%) coexisting with the major genotype ABO*B.01/O.01.02 in dizygotic twins. In addition, NGS analysis found a homozygous stop-gain variant (NM_004827.3:c.376C>T, p.Gln126*; ABCG2*01N.01) in a patient with an antibody to an HFA; consequently, this patient’s phenotype was predicted as Jr(a−). Lastly, blood group phenotypes predicted by NGS were concordant with those determined by serology in 2 patients treated with anti-CD47 drugs. Conclusion: NGS-based blood group genotyping can be used for identifying ABO subgroup alleles, low levels of blood group chimerism, and antibodies to HFAs. Furthermore, it can be applied to extended blood group antigen matching for patients treated with anti-CD47 drugs.
Facial and Auditory Recognition Abilities of Implanted Primary Schoolers
Authors: Yilar Selma , Tasdemir Ilknur , Koska Betul , Belen Esra , Cetinkaya Buse , Baltaci Isik , Demirkundak Burcu , Cinar Merve , Gultekin Gokce , Atas Ahmet , Emul Murat
Published: August 2021

Objective: Emotions are often conveyed via visual and together with the auditory mode in social interaction. We aimed to investigate the ability to recognize facial and/or auditory emotions in school-aged children with cochlear implantation and healthy controls. Methods: All participants were asked to respond to facial emotions of Ekman and Friesen’s pictures, then auditory emotions, and last, they were asked to respond to video-based dynamic synchronous facial and auditory emotions. Results: The mean accuracy rates in recognizing anger (p = 0.025), surprise (p = 0.029), and neutral (p = 0.029) faces were significantly worse in children with cochlear implants (CIs) than in healthy controls. They were significantly worse than healthy controls in recognizing all auditory emotions except auditory emotion of fear (p = 0.067). The mean accuracy rates in recognizing video-based auditory/facial emotions of surprise (p = 0.031) and neutral (p = 0.029) emotions were significantly worse in children with CIs. Conclusion: The children with hearing loss were poorer in recognizing surprise, anger, and neutral facial emotions than healthy children; they had similar performance in recognizing anger emotions when both stimuli were given synchronously which may have a positive effect on social behaviors. It seems beneficial that emotion recognition training should be included in rehabilitation programs.
Dental Caries Clusters among Adolescents in England, Wales, and Northern Ireland in 2013: Implications for Proportionate Universalism
Authors: Wang Xiaozhe , Bernabe Eduardo , Pitts Nigel , Zheng Shuguo , Gallagher Jennifer E.
Published: August 2021

Management of dental caries in adolescents presents a population health challenge; thus, it is important to use national epidemiological data to inform policy and action to improve oral health and address inequalities. The aims of this research were to examine dental caries clusters among 15-year-olds, taking account of caries thresholds, and explore associated factors to inform public health action. Secondary analysis of the oral health data on 2,160 15-year-olds from the 2013 Children’s Dental Health Survey in England, Wales, and Northern Ireland was performed. Hierarchical cluster analysis of dental caries experience was conducted across all surfaces and at 4 decay diagnostic thresholds (clinical: International Caries Detection and Assessment System [ICDAS] 1–6, cavitated: ICDAS 3–6, obvious: ICDAS 4–6, and extensive obvious: ICDAS 5–6 decay). Ordered logistic regression was used to estimate the association of behavioural and psychosocial factors with the clusters generated in relation to both clinical and obvious decay experience which are of clinical and epidemiological relevance. A 4-cluster decay pattern representing “low” to “extremely high” decay experience was observed under each of the dental caries diagnostic criteria. For clinical decay, which includes visual enamel caries, 28.70% had low, 39.77% medium, 26.71% high, and 4.81% extremely high caries status. In the adjusted model, significant risk factors for clinical decay included non-modifiable (sex, region, school type, and area deprivation) and modifiable (higher sugar intake at 4 or more times per day and suboptimal dental attendance) factors. This study suggests 4 distinct dental caries patterns among adolescent children nationally. Dental caries clusters demonstrate the importance of embracing proportionate universalism in addressing dental caries in the population oral health strategy.
First records of Brazilian three-banded armadillo (Tolypeutes tricinctus, Mammalia, Cingulata, Chlamyphoridae) predation by jaguar (Panthera onca, Mammalia, Carnivora, Felidae)
Authors: Magalhães Rodolfo Assis , Sena Liana Mara Mendes de , Rodrigues Flávio Henrique Guimarães
Published: August 2021

The jaguar Panthera onca and the Brazilian three-banded armadillo Tolypeutes tricinctus are two threatened mammals that coexist in the Caatinga dry forests and the Cerrado savannas of Brazil. Yet, to the best of our knowledge, interactions between these species have not been reported in the literature. Here, we present the first records of P. onca predation on T. tricinctus from two different areas in the Caatinga in northeastern Brazil. We showed that P. onca can pierce the hard carapace of T. tricinctus, which may be possible due to its distinctly strong bite and associated predation behavior. We argue that P. onca may be the most adapted non-human predator to feed on T. tricinctus, and that the smaller body sizes of P. onca individuals in the Caatinga may increase their likelihood to feed on smaller prey, including T. tricinctus. Thus, the originality of our records is probably more related to insufficient research in the areas where these species coexist than to the rarity of this interaction.
Characterization of shelters of the giant otter (Pteronura brasiliensis, Mammalia, Carnivora, Mustelidae) in the pantanal wetlands, state of Mato Grosso, Brazil
Authors: Damasceno Júnio de Souza , Shiraiwa Marília Couto Silva , Dalponte Júlio César
Published: August 2021

The giant otter (Pteronura brasiliensis) is an endangered mammal that occupies aquatic environments, especially in the Amazon Rainforest and Pantanal wetlands in South America. The species uses shelters (dens and campsites), such as burrowed tunnels and tangles of branches and roots along watercourses, where it feeds mainly on fishes. In Espírito Santo Creek (northern portion of the Pantanal wetlands in the state of Mato Grosso, Brazil), 60 shelters (45 dens and 15 campsites) were identified and georeferenced during 12 fieldtrips between 2002 and 2003. The density was 1.8 dens/km. The shelters were significantly found in locations with partial (35%) or complete (55%) plant cover. The dens were dug mainly in soil associated with roots located, on average, 4.4 m in distance and 2.4 m in height in relation to the waterline. The campsites had a significantly smaller distance and height compared to the dens. The greater density of dens in the study area underscores the need for conserved environments with little human interference for the protection of giant otter populations. The vegetal coverage of riparian forests and the occurrence of ravines along Espírito Santo Creek offer greater protection to the shelters, hindering the access of predators to the interior of the shelter. Studies integrating biological and ecological knowledge with social participation in areas of occurrence of the giant otter are fundamental to the conservation of the species and its habitat in the Pantanal wetlands of Mato Grosso, Brazil.
35 years behind the scenes: range extension of the rare Gro’s manticore, Morunasaurus groi (Squamata, Hoplocercidae), in Colombia
Authors: Vásquez-Restrepo Juan Daniel
Published: August 2021

Morunasaurus is a genus of Neotropical iguanid lizards of the family Hoplocercidae, inhabiting Central and northwestern South America. Their phylogenetic relationships are not completely clear but being presumably paraphyletic. Its type species, M. groi, is very rare, known only from two single localities and a handful of specimens. Here I report a new occurrence of this species for Colombia, which constitutes the southeastern record to the date, extending the species range by about 175 km and 510 m altitudinally. Additionally, I discuss about the intraspecific differences in coloration between Panamanian and Colombian specimens.
Redescription of the Neotropical species Trichodischia soror Bigot, 1885 (Diptera: Tachinidae), with a new generic synonymy
Authors: Alvarez-Garcia Deivys M. , Santis Marcelo Domingos de
Published: August 2021

Trichodischia Bigot, 1885 is a Neotropical genus with a confusing taxonomic history. This was initially composed of two species: T. caerulea Bigot, 1885 and T. soror Bigot, 1885. Later, the genus Trichoraea Cortés, 1974 was erected for T. caerulea. When reviewing the taxonomic history of both species, we discovered that both genera have been considered synonymous based on erroneous information and without a formal synonymy being proposed. Herein, we redescribed T. soror, provide images of adults and describe the male terminalia for the first time. In addition, by examining the type material, we propose Trichoraea as a junior synonym of Trichodischia, syn. nov., confirm T. caerulea comb. rest. and T. soror as valid species and provide some comments about the taxonomy and host record of the genus.
Breeding behavior, distribution, and conservation of the Sharp-tailed Tyrant Culicivora caudacuta (Vieillot, 1818) (Aves: Tyrannidae), a South American grassland specialist
Authors: Silva e Silva Robson
Published: August 2021

Culicivora caudacuta occurs in the Cerrado, Pampa and Chaco grasslands of Bolivia, Brazil, Paraguay, Argentina and Uruguay. Its breeding biology is poorly known. Here, I present a summary of the published information and new data gathered between 2003 and 2009 in southeast Brazil at Tapira, Minas Gerais. Breeding occurred during the rainy season (October to March), clutch size being three eggs. Juveniles and immatures show a different plumage from the adults, mostly brownish orange. All nests studied at Tapira showed evidence of cooperative breeding, with one helper engaged in incubation and provisioning the young. This is the first observations of this behavior for the species. The species has a wider range than currently understood and its presence in protected areas is similarly more common.
First record and a new species of Euphrosynoplax (Crustacea: Pseudorhombilidae) from the southwestern Atlantic
Authors: Tavares Marcos Domingos Siqueira , Santana William Ricardo Amâncio
Published: August 2021

A new species of deep-water brachyuran crab, Euphrosynoplax dincao, from southeastern Brazil is described and illustrated. The genus Euphrosynoplax currently consists of two species, E. clausa Guinot, 1969, and E. campechiensis Vázquez-Bader & Gracia, 1991, both only known from the Gulf of Mexico. The new species can be easily separated from its northern counterparts by a suite of carapace and appendage characters. Euphrosynoplax campechiensis is recorded for the first time from the Caribbenan Sea (Guadeloupe and between Saint Kitts and Nevis).
Report of an extra-pair copulation in the Rufous Hornero, Furnarius rufus (Aves: Furnariidae)
Authors: Diniz Pedro , Biagolini-Jr. Carlos
Published: August 2021

In the last decade, studies in bird breeding biology have shown that infidelity is prevalent in socially monogamous species. Here, we describe an extra-pair copulation (EPC) event in the Rufous Hornero (Furnarius rufus), a socially monogamous bird with year-round territoriality and low levels of extra-pair paternity. Before the EPC, a within-pair copulation (WPC) occurred inside the pair’s territory. The WPC occurred on the ground and between a banded male (ca. 6 years-old) and an unbanded female. Ten minutes later this breeding pair invaded a neighboring territory, presumably to forage. The territorial male was chased back to its territory by an unbanded male neighbor after being detected. The male neighbor was paired with an unbanded female that did not participate in the aggressive interaction. When flying back to its territory the male neighbor copulated with the territorial female on the ground (ie. EPC). The territorial male flew, vocalized, and perched above the male neighbor, interrupting the EPC. The aggressive interaction then ceased as each pair resumed foraging in their respective territories. These observations suggest that Rufous Horneros can use EPC to obtain immediate benefits (food access in a neighbor’s territory). Moreover, WPC may be detected by neighbors and physical mate guarding and/or frequent WPC may be necessary to prevent EPC in the Rufous Hornero.