bluuebunny/crossref_metadata_2025 huggingface dataset:
Latent-Variable-Modeling-Based Fault Diagnosis for Unknown Nonlinear Distributed Parameter Systems with Application to Snap Curing Oven
Authors: Luo Zhao-dong , Li Han-Xiong
Published: March 2023

A novel fault detection method based on time/space separation and latent variable model is proposed for unknown nonlinear distributed parameter systems in sensor-constrained environments. By performing time/space separation, the augmented matrix formed by the spatio-temporal distribution data of the DPSs can be split into a spatial basis function (SBFs) and a time series model, and the dimensionality reduction capability of the SBF is further utilized to obtain a low-order temporal model. Then, the temporal model is further extracted by using a dynamic latent variable modeling method to obtain the dominant time components and establish the corresponding monitoring statistics. Utilizing the appropriate kernel density function, confidence bounds are selected for the monitoring statistics when the system is normal. As a data-based fault diagnosis method, it requires only the past data records of the system and no reliance on complex mathematical models. Two sets of experiments performed on a snap curing oven verified the effectiveness of the proposed method.
Modeling and High-performance Trajectory Optimization of the Industrial Robot
Authors: Huang Shihui , Lin Yamei , Jiang Aipeng , Qiu Guangsheng
Published: March 2023

Rapidity, accuracy and energy cost are the key performance indexes for of the work of industrial robot. In this paper, the shortest time and the minimum energy consumption are taken as the goal for the comprehensive optimization. The control vector parameterization method is used to reasonably refine the time grid of the optimization problem. Then, an efficient control strategy for non-uniform adaptive mesh refinement is proposed. According to different changing trends, time nodes are merged or inserted into the time grid. While reducing the number of discrete grids, it also ensures the accuracy of the solution. Taking the Manutec R3 industrial robot as the object, the trajectory optimization simulation calculation is carried out. According to the verification of the simulation computing, the proposed method can significantly improve the time grid refinement. Compared with the traditional CVP method, not only the calculation time is shortened, but also more accurate results can be obtained.
Non-communicating Decentralized Multi-robot Collision Avoidance in Grid Graph Workspace based on Dueling Double Deep Q-Network
Authors: Liu Yuanxin , Tian Delei , Zheng Bin
Published: March 2023

This paper designs a motion rule suitable for grid environment and proposes a multi-robot autonomous obstacle avoidance method based on deep reinforcement learning. The training and validation of the method are done under the Stage simulation platform based on ROS operating system. During the training process, the robot uses Lidar to obtain the surrounding state information and generates actions based on the state information to obtain rewards, and the robot is guided by the rewards to optimize the strategy. Based on the D3QN algorithm, a new reward function is designed, a proximity penalty is introduced to reduce the collision between robots, a distance reward is added to guide the robot to complete the task, a step reward is added to improve the efficiency of the robot to complete the task, and an illegal action penalty is added to avoid the robot to choose an illegal action; the input is 5 frames of Lidar data, and in the network structure, the agent can better learn the correlation between the data by introducing Long Short Term Memory(LSTM) layer, and introducing Convolutional Block Attention Module(CBAM), a hybrid attention mechanism to allow the robot to pay more attention to the information of the surrounding robots. By designing experiments, we demonstrate that the learned strategy can effectively guide the robot through obstacle avoidance and complete the task.
Research on Vehicle Re-identification for Vehicle Road Collaboration
Authors: Sun Chenyang , Wang Yang , Deng Yanfei , Li Huafu , Guo Junqi
Published: March 2023

Vehicles and roads cooperate to perceive traffic targets, which can reduce the perception blind spots of vehicles and improve driving safety. In this paper, we proposes a vehicle re-identification method oriented to vehicle-road coordination. This method first designs a lightweight vehicle re-identification network based on ShufflenetV2 to solve the computational efficiency problem of vehicle-road coordination scenarios, which can efficiently complete vehicle feature extraction; then, due to the real-time requirements of scenario communication, an adaptive feature conversion mechanism is designed in combination with the LSH algorithm, which can make the re-identification module to dynamically perform binary bit feature conversion and adjust the dimension according to the communication channel state; finally, a loss function for the conversion of vehicle re-identification features is designed, which can greatly reduce the accuracy loss rate of converting floating-point features to bit features. Experiments show that our method can efficiently complete the information extraction and comparison of vehicle re-identification features in the vehicle-road coordination scenario, and can improve the perception efficiency of vehicle-road coordination while taking into account performance and bandwidth.
A Cloud-based State of Health Estimation Method for Lithium-ion Batteries Using Sparse Charging Data
Authors: Guo Wenchao , Yang Lin , Deng Zhongwei
Published: March 2023

Under the current background of the national standard requirements for electric vehicle remote management and the companies’ needs for their digital platform services, automobile factories habitually transmit battery data to a cloud in a sparse way for state of health (SOH) estimation. Compared with the dynamic discharge condition of the vehicle, the charging process has been noticed in recent years due to its relatively stable advantages. In this paper, a cloud-based SOH estimation method for lithium-ion batteries using sparse charging data is proposed. A HI feature that can be extracted from the sparse data is derived and only the constant voltage charging process is considered. By using the experimental data deployed on the cloud computing system, the correlation of battery health with the HI is verified and SOH can be efficiently estimated by taking as this feature an input to three data-driven methods. The results show that all methods can achieve a low test error of 2% under 10s sparsity, which is promising to be applied in cloud sparse charging conditions.
Cell State Recognition of Cytopathic Effect with YOLO Detector
Authors: Xu Zixi , Lou Wange , Lu Wenxin , Wei Wenxia
Published: March 2023

Cell state recognition and evaluation of its life cycle are the fundamental and critical procedure to identify the pathological mechanism of viruses and analyze pharmacodynamic effectiveness. Modern life science research is based on large-scale biological experiments so that it is inefficiency to estimate and decide the physicochemical results on petri dishes. With the development of target recognition in computer science, especially YOLO (You Only Look Once) approach, we are able to incorporate unified, real-time object detection into cell state recognition in this paper, which realizes automotive process of detection and classification of CPE (cytopathic effect) states. In our work, we build up photomicrograph datasets of Vero cell in CPE state and train our YOLO model with it. Finally, our model learns characteristic pixel structure of cell rounding, syncytium and inclusion bodies, acting as end-to-end detector in cell infected experiments.
Detection Method of River Floating Objects based on Edge Computing
Authors: Li He , Jia Huimei , Zhang Rui , Yang Shuaipeng , Qi Qinglei , Liu Tianyang
Published: March 2023

For the detection of objects floating in the river, most of the traditional intelligent video monitoring methods are used to monitor through manual viewing. During the traditional video data transmission and processing, the massive amount of data will put pressure on the background such as network and computing power. The new effective method is to crop and optimize YOLOV5s, add a specific image pre-processing module, and deploy it by edge computing, embed a SOC (System on Chip) chip in the web camera for real-time processing of video data. Simulation experiments prove that the above method can improve the accuracy and speed of the target detection network.
MPPT Study of Outdoor Sensing Terminal PV System Based on Improved PSO Algorithm
Authors: Xiao Yu , Zhu Li , Tan Jianjun , Zhun Yunyu , Yang Chen
Published: March 2023

With the popularity of wireless sensor use, the problem of supplying energy to its outdoor nodes is becoming more and more prominent. An outdoor wireless sensing terminal photovoltaic system is proposed to address the problem of outdoor wireless sensing terminal node power supply. The maximum power tracking (MPPT) is achieved by Adaptive weight adjustment Particle swarm optimization (AwaPSO) to achieve fast tracking and stable and reliable output, so that the Buck main circuit output of the PV system can meet the working requirements of the outdoor sensor terminal. The simulation model is built by Matlab/Simulink, and the simulation results show that the improved PSO algorithm can track the maximum power quickly and output stably and reliably, with the stabilization time shortened to 0.041s and the tracking error up to 0.625%, and its speed and stability can meet the outdoor wireless sensing terminal PV power supply requirements.
A Toolpath Optimization Algorithm for Layered 3D Printings based on Solving the TSP
Authors: Hu Kaiyu , Li Hailong , Xi Kou
Published: March 2023

In order to optimize the tool path of 3D printing such that the efficiency is improved, by summerizing the pros and cons of existing methods, we proposed a noval tool path optimization algorithm for layered 3D printings based on solving the Traveling Salesman Problem. Our algorithm first adjusts the major printing direction using Principal Components Analysis, and then applies the greedy strategy and generates multiple printing paths by interleavingly appending the filling segments and contour segments along the major printing direction. Thereafter, by considering the multiple printing paths as “cities”, and elaborately defining the distances between them, we successfully model the problem of minimizing the flying distances as a kind of Traveling Salesman Problem. Af-ter converting the accurate solution of TSP to our problem, we are able to get the global optimized tool path with the given multiple printing paths. Experiments demonstrate that the proposed algorithm not only miminizes the flying distances, but also reduces the switches between printing status and flying status, and boosts the percentage of long segments in the whole tool path as well, thus the printing efficiency is significently imporved without sac-rifying the printing quality.
Design of Sweeping Robot Based on STM32 Single Chip Microcomputer
Authors: Long Tao
Published: March 2023

As a new product in the field of service robots, the sweeping robot has made some achievements, but there are still many key technical problems to be solved or improved. This paper focuses on the precise obstacle avoidance and highly sensitive execution of the sweeping robot, and designs a sweeping robot based on STM32 microcontroller. The infrared ranging and ultrasonic ranging are combined to achieve accurate data acquisition. When the measurement distance is relatively close, infrared ranging is used. Otherwise, the ultrasonic distance measurement is adopted. In addition, PID algorithm is used to speed up the response of the system, and the motion state of the sweeping robot is adjusted through prediction data to ensure the accuracy of STM32 execution. It provides reference for the development of sweeping robot industry.
Partial Discharge Detection Method for Distribution Network Based on Feature Engineering
Authors: Liu Hongxiao , Xiang Mian Xiang , Zhou Bingtao , Zhu Li , Duan Yaqiong , Zhang Xiaoyan
Published: March 2023

Partial discharge phenomenon of overhead lines in distribution network is usually caused by the concentration of local electric field inside or on the surface of electrical equipment. According to partial discharge problem, based on the characteristics of the project the use of a machine learning is proposed for distribution network overhead line partial discharge detection model, first using the characteristics of engineering to extract the signal characteristics of different sides characterization, then respectively using K neighbor algorithm and back propagation algorithm, support vector machine (SVM) classification algorithm test. Experimental results show that when machine learning algorithm is used to classify time domain characteristic signals based on the feature engineering selected in this paper, k-nearest Neighbor algorithm has better classification and recognition effect than back propagation algorithm and support vector machine algorithm, with accuracy rate of 97.20%, recall rate of 96.30% and F value of 96.73%. In the frequency domain feature recognition and classification, the k-nearest Neighbor algorithm has 98.95% accuracy, 99.42% recall rate and 97.61% F value. Compared with the back propagation algorithm and support vector machine algorithm, the K-nearest Neighbor algorithm has the highest detection accuracy in the frequency domain feature detection of partial discharge on overhead lines of distribution network.
Parameter Identification of Permanent Magnet Synchronous Motor Based on Improved MRAS Algorithm
Authors: Liu Yi , Ran Quan , Zhao Shiping
Published: March 2023

During the operation of a permanent magnet synchronous motor, the electrical parameters of the motor will be affected by the temperature and the saturation of the magnetic chain, which will lead to a decrease in the effectiveness of the control algorithm for motor control. In this paper, we address the problem that the traditional MRAS algorithm has under-ranked equations when identifying motor parameters, and the three parameter identification values are coupled with each other and affect each other, which leads to scattered identification results and slow identification speed. In this paper, we propose a segmentation identification algorithm that combines the traditional MRAS algorithm with the recursive least squares method. In this paper, the inductance value is first identified by the recursive least squares method, and then the inductance value is substituted into the MRAS to identify the stator resistance and rotor magnetic chain, which effectively solves the problems of equation under-ranking and slow identification speed in the traditional MRAS, thus improving the stability of the permanent magnet synchronous motor operation.
Probabilistic forecasting of tropical cyclones intensity using machine learning model
Authors: Meng Fan , Yao Yichen , Wang Zhibin , Peng Shiqiu , Xu Danya , Song Tao
Published: March 2023

This study proposes a machine learning approach to probabilistic forecasting of tropical cyclone (TC) intensity. The earth system is complex and nonlinear, leading to inherent uncertainty in TC forecasting at all times, and therefore a representation of this uncertainty should be provided. Previous studies construct this uncertainty through ensemble or statistical methods, neither of which can directly characterize this uncertainty and suffer from problems such as excessive computational effort. And for this reason, we propose to assess the forecast without this uncertainty through the forecast distribution. Meanwhile, none of the previous studies on TC intensity forecasting by artificial intelligence methods characterize the uncertainty, so this study is a new supplement to data-driven TC forecasting. During the 2010–2020 evaluation period, the model’s point forecast can outperform the current state-of-the-art operational statistic-dynamical model results, and can obtain forecast intervals to provide reliable probabilistic forecasts, which are critical for disaster warnings.
Market-oriented solutions for groundwater commons through collective-action
Authors: Allen Jonah J , Smith Steven M
Published: March 2023

Groundwater scarcity poses threats to communities across the globe, and effectively managing those challenges requires designing policy that achieves institutional fit. Collective action is well-suited to match rules with local context, and multiple pathways exist for communities to achieve reductions in groundwater use. To better understand how local conditions influence rule design, we examine two groundwater-reliant communities in the Western US that engaged in collective-action to arrive at distinct groundwater management rules. We consider: what drove stakeholders in Northwestern Kansas (NWKS) and San Luis Valley, Colorado (SLV) to adopt local groundwater policies, and why were different management pathways chosen? Further, why is more heterogeneity observed between local management organizations in SLV as compared to NWKS? To investigate these questions, we employ grounded theory to interpret the rules in reference to local hydro-agro-economic statistics and interviews with stakeholders (n = 19) in each region selected by expert sampling. We find that the additional goals of groundwater rules in SLV, partially driven by key contrasts in the resource system compared to NWKS, and higher resource productivity in SLV, creates both the need for and efficacy of a price-centered policy. Furthermore, variation in the resource systems and associated farm characteristics between subdistricts drives higher heterogeneity in rule design between local management districts in SLV compared to NWKS. More generally, we find the local flexibility afforded through the collective-action process as critical, even if it were to arrive at alternative, non-economic based incentives.
Discretizing advection equations with rough velocity fields on non-Cartesian grids
Authors: Jabin Pierre-Emmanuel , Zhou Datong
Published: March 2023

We investigate the properties of discretizations of advection equations on non-Cartesian grids and graphs in general. Advection equations discretized on non-Cartesian grids have remained a long-standing challenge as the structure of the grid can lead to strong oscillations in the solution, even for otherwise constant velocity fields. We introduce a new method to track oscillations of the solution for rough velocity fields on any graph. The method in particular highlights some inherent structural conditions on the mesh for propagating regularity on solutions.
Developing a Culturally Competent Neuropsychological Assessment Battery for Vietnamese-speaking Patients with Suspected Dementia
Authors: McCauley Stephen R , Nguyen Thomas , Nguyen Christopher , Strutt Adriana M , Stinson Jennifer M , Windham Victoria A , York Michele K
Published: March 2023

Objectives

To assemble a core battery of culturally and linguistically appropriate neuropsychological measures that can be administered to Vietnamese-speaking patients with suspected dementia.

Methods

Test instruments in Vietnamese were identified through systematic searches of PubMed, PsychInfo, and Google Scholar, and in consultation with two Vietnamese-speaking cultural brokers.

Results

A battery assessing the domains of attention, executive function, verbal and visual episodic memory, basic language abilities, visuospatial/visuoconstruction abilities, and mood/anxiety was assembled that included core measures developed either specifically for a Vietnamese-speaking population, or were validated/normed with a Vietnamese-speaking sample either in Vietnam or Vietnamese-speaking persons in the U.S. Supplemental measures were selected that can be administered using translated instructions with U.S. English normative data. The rationale for test selection and caveats for their clinical use are presented.

Conclusions

The number of neuropsychological measures identified in Vietnamese and/or with Vietnamese normative data was sparse. Given the large and growing population of Vietnamese-speaking residents in the U.S. and the aging of these communities, it is imperative to develop additional, appropriately designed and normed instruments to provide culturally competent assessments to better serve these individuals.
Silicone Migration From Breast Implants: A Case of Ocular Siliconoma and Literature Review
Authors: Montemurro Paolo , Pellegatta Tommaso , Burton Harry , Pafitanis Georgios
Published: March 2023

Background

Breast augmentation with implants is one of the most popular cosmetic surgery operations performed worldwide. Complications of breast implants are well recognized, and include capsular contracture, implant rupture, and infrequently distant migration of silicone, resulting in siliconoma. Distant migration of silicone can present many years after implantation with a wide variety of signs and symptoms.

Objectives

The aim of this study was to describe the authors’ experience of orbital silicone migration and to review the literature describing documented cases of distant silicon migration from breast implants, both ocular and nonocular.

Methods

In January 2022, a case of breast implant augmentation presented with silicone migration into the right orbit. This rare case was monitored and diagnosed with ocular muscle palsy and diplopia. Here, the authors present the patient's presenting complaint, symptomatology, working investigations, and outcomes. A comprehensive report of all available cases of distant silicone migration is presented along with their associated complications and more specifically ocular silicone migration.

Results

Systemic migration of silicone from breast implants to the orbital region is extremely rare: a total of 4 previous cases of ocular silicone migration from breast implants have been described previously; the authors describe the fifth case herein.

Conclusions

Silicone implant rupture can present with a wide variety of clinical symptoms that may mimic different clinical pathologies. In every patient with a history of breast augmentation with silicone implants, the possibility of silicone migration should be always taken into consideration during the differential diagnosis process.

Level of Evidence: 5
End-to-end interpretable disease–gene association prediction
Authors: Li Yang , Guo Zihou , Wang Keqi , Gao Xin , Wang Guohua
Published: March 2023

Identifying disease–gene associations is a fundamental and critical biomedical task towards understanding molecular mechanisms, the diagnosis and treatment of diseases. It is time-consuming and expensive to experimentally verify causal links between diseases and genes. Recently, deep learning methods have achieved tremendous success in identifying candidate genes for genetic diseases. The gene prediction problem can be modeled as a link prediction problem based on the features of nodes and edges of the gene–disease graph. However, most existing researches either build homogeneous networks based on one single data source or heterogeneous networks based on multi-source data, and artificially define meta-paths, so as to learn the network representation of diseases and genes. The former cannot make use of abundant multi-source heterogeneous information, while the latter needs domain knowledge and experience when defining meta-paths, and the accuracy of the model largely depends on the definition of meta-paths. To address the aforementioned challenges above bottlenecks, we propose an end-to-end disease–gene association prediction model with parallel graph transformer network (DGP-PGTN), which deeply integrates the heterogeneous information of diseases, genes, ontologies and phenotypes. DGP-PGTN can automatically and comprehensively capture the multiple latent interactions between diseases and genes, discover the causal relationship between them and is fully interpretable at the same time. We conduct comprehensive experiments and show that DGP-PGTN outperforms the state-of-the-art methods significantly on the task of disease–gene association prediction. Furthermore, DGP-PGTN can automatically learn the implicit relationship between diseases and genes without manually defining meta paths.
Rapid and sustained response to spesolimab in five Chinese patients with generalized pustular psoriasis
Authors: Ran Delin , Yang Baoqi , Sun Lulu , Wang Na , Qu Peng , Liu Jing , Pan Futang , Wang Guangjin , Wu Weizhi , Zhang Zhaoxia , Shi Zhongxiang , Yang Qing , Liu Hong , Zhang Furen
Published: March 2023

Generalized pustular psoriasis (GPP) is a rare skin disease characterized by generalized sterile pustules with or without severe systemic symptoms. Here we share our experience with spesolimab in five Chinese patients with GPP flare.
Inflammatory Bowel Disease and Risk of Colorectal Polyps: A Nationwide Population-Based Cohort Study From Sweden
Authors: Axelrad Jordan E , Olén Ola , Söderling Jonas , Roelstraete Bjorn , Khalili Hamed , Song Mingyang , Faye Adam , Eberhardson Michael , Halfvarson Jonas , Ludvigsson Jonas F
Published: March 2023

Background

Inflammatory bowel disease [IBD] has been linked to an increased risk of colorectal neoplasia. However, the types and risks of specific polyp types in IBD are less clear.

Methods

We identified 41 880 individuals with IBD (Crohn’s disease [CD: n = 12 850]; ulcerative colitis [UC]: n = 29 030]) from Sweden matched with 41 880 reference individuals. Using Cox regression, we calculated adjusted hazard ratios [aHRs] for neoplastic colorectal polyps [tubular, serrated/sessile, advanced and villous] defined by histopathology codes.

Results

During follow-up, 1648 [3.9%] IBD patients and 1143 [2.7%] reference individuals had an incident neoplastic colorectal polyp, corresponding to an incidence rate of 46.1 and 34.2 per 10 000 person-years, respectively. This correlated to an aHR of 1.23 (95% confidence interval [CI] 1.12–1.35) with the highest HRs seen for sessile serrated polyps [8.50, 95% CI 1.10–65.90] and traditional serrated adenomas [1.72, 95% CI 1.02–2.91]. aHRs for colorectal polyps were particularly elevated in those diagnosed with IBD at a young age and at 10 years after diagnosis. Both absolute and relative risks of colorectal polyps were higher in UC than in CD [aHRs 1.31 vs 1.06, respectively], with a 20-year cumulative risk difference of 4.4% in UC and 1.5% in CD, corresponding to one extra polyp in 23 patients with UC and one in 67 CD patients during the first 20 years after IBD diagnosis.

Conclusions

In this nationwide population-based study, there was an increased risk of neoplastic colorectal polyps in IBD patients. Colonoscopic surveillance in IBD appears important, especially in UC and after 10 years of disease.
Ecophysiological responses of individually and group reared Cydalima perspectalis (Lepidoptera: Crambidae) to alkaloid-containing host plants
Authors: Kholghahmadi Maryam , Karimi-Malati Azadeh , Jalali Sendi Jalal
Published: March 2023

The box tree moth, Cydalima perspectalis (Walker), is an invasive pest of Hyrcanian forests in Iran. In the current study, the effects of two boxwood species, Buxus hyrcana Pojark and B. microphylla Sieb. and Zucc. (Buxales: Buxaceae), were examined on ecophysiology of the pest. The demographic parameters were evaluated based on the age-stage, two-sex life table theory. The physiological characteristics of C. perspectalis were considered through fresh/dry weights and individually/group rearing methods. The results showed that C. perspectalis larvae were able to develop, survive and reproduce on both boxwood species. The developmental times were 41.62 and 41.46 days on B. hyrcana and B. microphylla, respectively. The total lifespan did not differ on boxwood species. However, the difference of fecundity on B. hyrcana (412.82 eggs/female) and B. microphylla (286.06 eggs/female) was significant. The intrinsic rate of increase (r) and finite rate of increase (λ) were significantly higher on B. hyrcana than B. microphylla. The nutritional indices showed that the consumption index (CI) on B. hyrcana were significantly lower than on B. microphylla based on fresh/dry weights in both rearing methods. Conversely, the efficiency of conversion of digested food (ECD) and the efficiency of conversion of ingested food (ECI) on B. hyrcana were significantly higher than on B. microphylla. Despite nonsignificant differences in leaf nutrient contents (except calcium), total protein, triglyceride, and alkaline phosphatase activity were inversely different in larvae compared to adult stage on boxwood species. These findings could help to comprehensively understand the performance of the pest on boxwood species.
Reversal and removal of oral antithrombotic drugs in patients with active or perceived imminent bleeding
Authors: Cao Davide , Amabile Nicolas , Chiarito Mauro , Lee Victoria T , Angiolillo Dominick J , Capodanno Davide , Bhatt Deepak L , Mack Michael J , Storey Robert F , Schmoeckel Michael , Gibson C Michael , Deliargyris Efthymios N , Mehran Roxana
Published: March 2023

Remarkable progress has been made in the pharmacological management of patients with cardiovascular disease, including the frequent use of antithrombotic agents. Nonetheless, bleeding complications remain frequent and potentially life-threatening. Therapeutic interventions relying on prompt antithrombotic drug reversal or removal have been developed to assist clinicians in treating patients with active bleeding or an imminent threat of major bleeding due to urgent surgery or invasive procedures. Early phase studies on these novel strategies have shown promising results using surrogate pharmacodynamic endpoints. However, the benefit of reversing/removing antiplatelet or anticoagulant drugs should always be weighed against the possible prothrombotic effects associated with withdrawal of antithrombotic protection, bleeding, and surgical trauma. Understanding the ischemic-bleeding risk tradeoff of antithrombotic drug reversal and removal strategies in the context of urgent high-risk settings requires dedicated clinical investigations, but challenges in trial design remain, with relevant practical, financial, and ethical implications.
How to tuna fish: constraint, convergence, and integration in the neurocranium of pelagiarian fishes
Authors: Knapp Andrew , Rangel-de Lázaro Gizéh , Friedman Matt , Johanson Zerina , Evans Kory M , Giles Sam , Beckett Hermione T , Goswami Anjali
Published: March 2023

Morphological evolution of the vertebrate skull has been explored across a wide range of tetrapod clades using geometric morphometrics, but the application of these methods to teleost fishes, accounting for roughly half of all vertebrate species, has been limited. Here we present the results of a study investigating 3D morphological evolution of the neurocranium across 114 species of Pelagiaria, a diverse clade of open-ocean teleost fishes that includes tuna and mackerel. Despite showing high shape disparity overall, taxa from all families fall into three distinct morphological clusters. Convergence in shape within clusters is high, and phylogenetic signal in shape data is significant but low. Neurocranium shape is significantly correlated with body elongation and significantly but weakly correlated with size. Diet and habitat depth are weakly correlated with shape, and nonsignificant after accounting for phylogeny. Evolutionary integration in the neurocranium is high, suggesting that convergence in skull shape and the evolution of extreme morphologies are associated with the correlated evolution of neurocranial elements. These results suggest that shape evolution in the pelagiarian neurocranium reflects the extremes in elongation found in body shape but is constrained along relatively few axes of variation, resulting in repeated evolution toward a restricted range of morphologies.
Sperm-contributed centrioles segregate stochastically into blastomeres of 4-cell stage Caenorhabditis elegans embryos
Authors: Gönczy Pierre , Balestra Fernando R
Published: March 2023

Whereas both sperm and egg contribute nuclear genetic material to the zygote in metazoan organisms, the inheritance of other cellular constituents is unequal between the 2 gametes. Thus, 2 copies of the centriole are contributed solely by the sperm to the zygote in most species. Centrioles can have a stereotyped distribution in some asymmetric divisions, but whether sperm-contributed centrioles are distributed in a stereotyped manner in the resulting embryo is not known. Here, we address this question in Caenorhabditis elegans using marked mating experiments, whereby the presence of the 2 sperm-contributed centrioles is monitored in the embryo using the stable centriolar component SAS-4::GFP, as well as GFP::SAS-7. Our analysis demonstrates that the distribution of sperm-contributed centrioles is stochastic in 4-cell stage embryos. Moreover, using sperm from zyg-1 mutant males that harbor a single centriole, we show that the older sperm-contributed centriole is likewise distributed stochastically in the resulting embryo. Overall, we conclude that, in contrast to the situation during some asymmetric cell divisions, centrioles contributed by the male germ line are distributed stochastically in embryos of C. elegans.
The emergence of Leveller polemic: William Walwyn, collaborative authorship and radical identity, 1645–7
Authors: De Krey Gary S
Published: March 2023

This article investigates Leveller prehistory by analysing three polemical tracts of 1646–7. William Walwyn and Richard Overton arguably collaborated in the Remonstrance of Many Thousand Citizens and in the New Found Stratagem Framed in the Old Forge of Machivilisme, as well as in the Warning to All the Counties of England. Their denunciations of the dominant Presbyterian faction supported the independent alliance; but they employed distinctive language too extreme for many independents, pointing to their increasing political ambiguity. Their collaboration challenges scholarly characterizations of Walwyn’s ‘gentle’ style. The essay concludes by examining the related emergence of London, army and county radicals, some of whom would soon become Levellers.
Characterization of “Off-Target” Immune Modulation Induced by Live Attenuated Yellow Fever Vaccine
Authors: Xiang J , Chang Q , McLinden J H , Bhattarai N , Welch J L , Kaufman T M , Stapleton Jack T
Published: March 2023

Background

Live attenuated vaccines alter immune functions and are associated with beneficial outcomes. We previously demonstrated that live attenuated yellow fever virus (YFV) vaccine (LA-YF-Vax) dampens T-cell receptor (TCR) signaling in vitro via an RNA-based mechanism. We examined study participants before and after LA-YF-Vax to assess TCR-mediated functions in vivo.

Methods

Serum samples and peripheral blood mononuclear cells (PBMCs) were obtained before and after LA-YF-Vax (with or without additional vaccines) or quadrivalent influenza vaccine. TCR-mediated activation was determined by interleukin 2 release or phosphorylation of the lymphocyte-specific Src kinase. TCR-regulating phosphatase (protein tyrosine phosphatase receptor type E [PTPRE]) expression was also measured.

Results

Compared with prevaccination findings, LA-YF-Vax recipient PBMCs demonstrated transient reduction in interleukin 2 release after TCR stimulation and PTPRE levels, unlike in control participants who received quadrivalent influenza vaccine. YFV was detected in 8 of 14 participants after LA-YF-Vax. After incubation of healthy donor PBMCs in serum-derived extracellular vesicles prepared from LA-YF-Vax recipients, TCR signaling and PTPRE levels were reduced after vaccination, even in participants without detectable YFV RNA.

Conclusions

LA-YF-Vax reduces TCR functions and PTPRE levels after vaccination. Extracellular vesicles from serum recapitulated this effect in healthy cells. This likely contributes to the reduced immunogenicity for heterologous vaccines after LA-YF-Vax administration. Identification of specific immune mechanisms related to vaccines should contribute to understanding of the “off-target,” beneficial effects of live vaccines.
Blood transcriptome of Rasa Aragonesa rams with different sexual behavior phenotype reveals CRYL1 and SORCS2 as genes associated with this trait
Authors: Lakhssassi Kenza , Sarto María Pilar , Lahoz Belén , Alabart José Luis , Folch José , Serrano Malena , Calvo Jorge Hugo
Published: March 2023

Reproductive fitness of rams is seasonal, showing the highest libido during short days coinciding with the ovarian cyclicity resumption in the ewe. However, the remarkable variation in sexual behavior between rams impair farm efficiency and profitability. Intending to identify in vivo sexual behavior biomarkers that may aid farmers to select active rams, transcriptome profiling of blood was carried out by analyzing samples from 6 sexually active (A) and 6 nonactive (NA) Rasa Aragonesa rams using RNA-Seq technique. A total of 14,078 genes were expressed in blood but only four genes were differentially expressed (FDR < 0.10) in the A vs. NA rams comparison. The genes, acrosin inhibitor 1 (ENSOARG00020023278) and SORCS2, were upregulated (log2FC > 1) in active rams, whereas the CRYL1 and immunoglobulin lambda-1 light chain isoform X47 (ENSOARG00020025518) genes were downregulated (log2FC < -1) in this same group. Gene set Enrichment Analysis (GSEA) identified 428 signaling pathways, predominantly related to biological processes. The lysosome pathway (GO:0005764) was the most enriched, and may affect fertility and sexual behavior, given the crucial role played by lysosomes in steroidogenesis, being the SORCS2 gene related to this signaling pathway. Furthermore, the enriched positive regulation of ERK1 and ERK2 cascade (GO:0070374) pathway is associated with reproductive phenotypes such as fertility via modulation of hypothalamic regulation and GnRH-mediated production of pituitary gonadotropins. Furthermore, external side of plasma membrane (GO:0009897), fibrillar center (GO:0001650), focal adhesion (GO:0005925), and lamellipodium (GO:0030027) pathways were also enriched, suggesting that some molecules of these pathways might also be involved in rams’ sexual behavior. These results provide new clues for understanding the molecular regulation of sexual behavior in rams. Further investigations will be needed to confirm the functions of SORCS2 and CRYL1 in relation to sexual behavior.
Xylella fastidiosa inoculation behaviors (EPG X wave) are performed differently by blue-green sharpshooters based on infection status of prior probing host
Authors: Roddee Jariya , Backus Elaine A , Cervantes Felix A , Hanboonsong Yupa
Published: March 2023

Does Xylella fastidiosa, a bacterial plant pathogen with noncirculative foregut-borne transmission, manipulate behavior of its sharpshooter vector to facilitate its own inoculation? To answer this question, blue-green sharpshooters, Graphocephala atropunctata (Signoret), were reared on basil to clean their foreguts, then removed from the colony and given one of four pre-electropenetrography (EPG) treatments: i) old colony adults on basil, ii) young colony adults on basil, iii) young colony adults held on healthy grapevine for 4 days, and iv) young colony adults held on Xf-infected (symptomatic) grapevine for 4 days. After treatments, stylet probing behaviors were recorded on healthy grapevine via AC-DC electropenetrography. Waveforms representing putative Xf inoculation (XB1 [salivation and rinsing egestion] and XC1 [discharging egestion]) and other behaviors were statistically compared among treatments. Mean number of events per insect and ‘total’ duration per insect of XB1 and XC1 were highest for insects from healthy grape, lowest for basil (regardless of insect age), and intermediate for Xf-infected grape. The surprising results showed that prior exposure to healthy grapevines had a stronger effect on subsequent performance of inoculation behaviors on healthy grapevine than did prior exposure to Xf-infected grapevine. It is hypothesized that non-Xf microbes were acquired from healthy grapevine, causing greater clogging of the precibarium, leading to more performance of inoculation behaviors. This study shows for the first time that presence of noncirculative, foregut-borne microbes can directly manipulate a vector’s behavior to increase inoculation. Also, EPG can uniquely visualize the dynamic interactions between vectors and the microbes they carry.
Life-Span and Multicultural Perspectives
Authors: Achenbach Thomas M.
Published: March 2023

This chapter employs developmental psychopathology and an empirically based paradigm for understanding psychopathology across the life span around the world. Developmental psychopathology conceptualizes maladaptive functioning in relation to developmental periods, sequences, and processes. The empirically based paradigm derives taxonomic constructs from multivariate analyses of assessment data, which have yielded hierarchical models spanning from specific problem items, to empirically derived syndromes, internalizing and externalizing groupings of syndromes, and a general psychopathology (p) dimension. Data are obtained from multiple informants to take account of variations in functioning and informant perspectives. Assessment of population samples in more than 50 societies has supported syndrome and item structures originally derived from US data. Multicultural norms are available for societies with relatively low, intermediate, or high problem scores. Instruments are available in 113 languages for intake and subsequent reassessments and are used in many genetic, longitudinal, and other studies, as reported in more than 11,000 publications from more than 100 societies.
Attention Deficit Hyperactivity Disorder
Authors: Noordermeer Siri , Oosterlaan Jaap
Published: March 2023

Individuals with attention deficit hyperactivity disorder (ADHD) suffer from persistent and age-inappropriate levels of inattention and/or hyperactivity-impulsivity, occurring in multiple situations, to such a degree that symptoms have a severely detrimental impact on their daily life functioning or development. Throughout the past three decades, scientific interest in ADHD and knowledge about the disorder have grown exponentially. While a large body of research is available on ADHD, the number of unanswered questions remains substantial. ADHD has proved to be a heterogeneous disorder, causing a difficult challenge for research to create a consistent image of the disorder. Partly due to this heterogeneity, the past decades have been characterized by an increase in questions and concerns about the validity of ADHD and stigmatization of patients diagnosed with the disorder. This chapter covers the prevalence, course, comorbidities, and functional impact of ADHD, as well as diagnosis, treatment, and etiology and risk factors of the disorder. The heterogeneity and complexity of ADHD are key issues, and an extensive and critical overview of current knowledge of the disorder is provided.
Role of the 5′ end phosphorylation state for small RNA stability and target RNA regulation in bacteria
Authors: Schilder Alexandra , Görke Boris
Published: March 2023

In enteric bacteria, several small RNAs (sRNAs) including MicC employ endoribonuclease RNase E to stimulate target RNA decay. A current model proposes that interaction of the sRNA 5′ monophosphate (5′P) with the N-terminal sensing pocket of RNase E allosterically activates cleavage of the base-paired target in the active site. In vivo evidence supporting this model is lacking. Here, we engineered a genetic tool allowing us to generate 5′ monophosphorylated sRNAs of choice in a controllable manner in the cell. Four sRNAs were tested and none performed better in target destabilization when 5′ monophosphorylated. MicC retains full activity even when RNase E is defective in 5′P sensing, whereas regulation is lost upon removal of its scaffolding domain. Interestingly, sRNAs MicC and RyhB that originate with a 5′ triphosphate group are dramatically destabilized when 5′ monophosphorylated, but stable when in 5′ triphosphorylated form. In contrast, the processing-derived sRNAs CpxQ and SroC, which carry 5′P groups naturally, are highly stable. Thus, the 5′ phosphorylation state determines stability of naturally triphosphorylated sRNAs, but plays no major role for target RNA destabilization in vivo. In contrast, the RNase E C-terminal half is crucial for MicC-mediated ompD decay, suggesting that interaction with Hfq is mandatory.
Oncogenic long noncoding RNA LINC02283 enhances PDGF receptor A-mediated signaling and drives glioblastoma tumorigenesis
Authors: Goenka Anshika , Song Xiao , Tiek Deanna , Iglesia Rebeca Piatniczka , Lu Minghui , Zeng Chang , Horbinski Craig , Zhang Wei , Hu Bo , Cheng Shi-Yuan
Published: March 2023

Background

Long noncoding RNAs (lncRNAs) regulate the etiology of complex diseases and cancers, including glioblastoma (GBM). However, lncRNA-based therapies are limited because the mechanisms of action of many lncRNAs with their binding partners are not completely understood.

Methods

We used transcriptomic and genomic data to analyze correlations between LINC02283 and PDGFRA (platelet-derived growth factor receptor A). The biological functions of the novel lncRNA were assessed in vivo using patient-derived glioma stem-like cells (GSCs), and orthotopic GBM xenografts. Immunoblotting, qRT-PCR, RNA pull down, crosslinked RNA immunoprecipitation, fluorescence in situ hybridization, and antisense oligo-mediated knockdown were performed to explore the regulation of LINC02283 on PDGFRA signaling. Expression of LINC02283 in clinical samples was assessed using pathologically diagnosed GBM patient samples.

Results

We identified a novel oncogenic lncRNA, LINC02283, that is highly expressed in the PDGFRA mutation-driven cohort of glioma patients and associated with worse prognosis. LINC02283 gene co-amplifies with the PDGFRA locus and shows high correlation with PDGFRA expression. Deprivation of LINC02283 in GSCs with PDGFRA amplification mutation, attenuated tumorigenicity and enhanced survival in orthotopic GBM xenograft models, while overexpression of LINC02283 in GSCs with wild-type PDGFRA, enhances PDGFRA signaling, and decreases survival. Further, LINC02283 interacts with PDGFRA to enhance its signaling and that of its downstream targets AKT and ERK, thus promoting oncogenesis in GBM.

Conclusions

Our results provide strong evidence of LINC02283 as a regulator of PDGFRA oncogenic activity and GBM malignancy and support the potential of lncRNAs as possible therapeutic targets.
Niraparib with Abiraterone Acetate and Prednisone for Metastatic Castration-Resistant Prostate Cancer: Phase II QUEST Study Results
Authors: Chi Kim N , Fleshner Neil , Chiuri Vincenzo Emanuele , Van Bruwaene Siska , Hafron Jason , McNeel Douglas G , De Porre Peter , Maul Raymond Scott , Daksh Mahesh , Zhong Xiaogang , Mason Gary E , Tutrone Ronald F
Published: March 2023

Niraparib (NIRA) is a highly selective inhibitor of poly (adenosine diphosphate-ribose) polymerase, PARP1 and PARP2, which play a role in DNA repair. The phase II QUEST study evaluated NIRA combinations in patients with metastatic castration-resistant prostate cancer who were positive for homologous recombination repair gene alterations and had progressed on 1 prior line of novel androgen receptor-targeted therapy. Results from the combination of NIRA with abiraterone acetate plus prednisone, which disrupts androgen axis signaling through inhibition of CYP17, showed promising efficacy and a manageable safety profile in this patient population.