bluuebunny/crossref_metadata_2025 huggingface dataset:
Mixed-methods evaluation of point-of-care hepatitis C virus RNA testing in a Scottish prison
Authors: Byrne Christopher J , Malaguti Amy , Inglis Sarah Karen , Dillon John F
Published: April 2023

Objectives

Hepatitis C virus (HCV) poses a global public health threat. Prisons are a focus of prevention efforts due to high infection burdens. Expedition of treatment for incarcerated people is critical, as many are short-term sentenced. We evaluated point-of-care (PoC) HCV RNA testing in a maximum-security Scottish prison and assessed its impact on transition to treatment. We also evaluated costs and determinants of implementation.

Design

Mixed-methods evaluation of a single-centre care pathway pilot using National Health Service (NHS) data from 2018 to 2021. Descriptive statistics and survival analysis were undertaken. Cost analysis was assessed from a provider perspective. Healthcare staff participated in semistructured interviews and thematic analysis with a deductive approach was undertaken to identify implementation determinants.

Setting

A large maximum-security Scottish prison health centre administered by the NHS.

Participants

296 incarcerated NHS patients (all men) and six NHS staff members (two men and four women).

Interventions

HCV testing using the Cepheid GeneXpert platform with Xpert HCV VL Fingerstick assay.

Outcome measures

The main outcome was survival (in days) from HCV test to treatment initiation. Secondary outcomes were cost-per-cure obtained and implementation determinants.

Results

During the pilot, 167 Xpert tests were administered, with an 84% completion rate, and treatment transition was superior for those who received it (p=0.014). Where PoC tests were administered, shorter survival to treatment was observed (19 vs 33 days: adjusted HR (aHR) 1.91 (1.03–3.55), p=0.040; 19 vs 50 days; aHR 3.76 (1.67–8.46), p=0.001). PoC was costlier than conventional testing. In qualitative analysis, most facilitators were observed among characteristics of individual domain while most barriers were noted in the inner setting.

Conclusions

Integrating PoC HCV RNA diagnosis into nurse-led HCV care in a maximum-security prison health centre shortens survival to HCV treatment. However, there are cost implications to this approach and multiple determinants that impact on implementation should be addressed.
Three-dimensional stress–strain and strength behavior of silt–clay transition soils
Authors: Anantanasakul Pongpipat , Intharachart Phimmawat , Kaliakin Victor N.
Published: April 2023

The effect of silt content on the mechanical behavior of silt–clay transition soils under 3D stress conditions is presented. Undrained true triaxial tests with constant b values were performed on normally consolidated specimens of silt–clay transition soils created from the same base clay and nonplastic silt, however, with systematically varying gradations. With increasing amount of nonplastic silt, the cohesive soils exhibit less contractive tendencies, stiffer stress–strain response, and larger shear strength. The magnitude of intermediate principal stress, as indicated by the b value, also strongly influences the stress–strain relations, pore pressure behavior, and both total and effective failure surfaces. Although the transition soils exhibit overall clay-like behavior, more pronounced frictional characteristics, as indicated by the shapes of the failure and plastic potential surfaces, were exhibited with increasing silt content.
A new species of Astyanax (Characiformes, Characidae) from the rio Apiacás, rio Teles Pires basin, with a discussion on its phylogenetic position
Authors: Ferreira Katiane M. , Lima Flávio C.T. , Ribeiro Alexandre C. , Junior Nelson Flausino , Machado Francisco A. , Mirande Juan Marcos
Published: April 2023

A new species of Astyanax Baird & Girard, 1854 is described from the rio Apiacás, a tributary of the rio Teles Pires, rio Tapajós basin, Mato Grosso state, Brazil. The new taxon can be distinguished from all congeners, except those belonging to the Astyanax bimaculatus species group and to the Astyanax orthodus species group, by the presence of a horizontally elongated to rounded humeral blotch. The new taxon can be readily distinguished from all species belonging to the A. bimaculatus species group and to the A. orthodus species group by presenting a distinct morphology in premaxillary and dentary teeth with conspicuous diastema (a teeth gap) between them. We also present a hypothesis about the phylogenetic relationships of the new taxon within Astyanax.
Beam dynamics optimization in the LEBT of LLICTF
Authors: Chu Yimeng , Wang Zhijun , Chen Weilong , Sun Kunxiang , Jin Chao , Yi Man , Gong Lingyun , Du Yu , Jia Duanyang
Published: April 2023

A Low Energy Beam Transport (LEBT) has been designed and optimized to inject both a 50[Formula: see text]keV/u, 50[Formula: see text]mA [Formula: see text] beam and a 20[Formula: see text]keV/u, 1[Formula: see text]mA [Formula: see text] beam into the downstream Radio Frequency Quadrupole (RFQ) at the Lanzhou Light Ion Cancer Therapy Facility (LLICTF). The overall aim is to increase the operation efficiency and simplify the complexity of the LLICTF. This dual-beam operation mode creates phase space distortions as a result of the intense space charge, and causes transverse asymmetry due to a mixture of solenoids and a dipole magnet. To mitigate the phase space distortions of the high-intensity proton beam, two beam scrapers have been placed at locations determined through careful analysis of the space charge forces and external focusing force of the beam. Additionally, the Particle Swarm Optimization (PSO) algorithm has been utilized to obtain an approximate solution for the dipole parameters, which helps maintain the symmetry of different symmetrical beams passing through it. Optics designs that implement these solutions are verified with multi-particle simulations.
Energy Consumption Optimization of Connected and Autonomous Vehicles Based on Cooperative Perception in Ramp Overflow Scene
Authors: Su Ziyi , Liu Qingchao , Gong Ling
Published: April 2023

The congestion caused by ramp overflow has an essential impact on the energy consumption of autonomous vehicles. It is urgent to solve the energy waste of ramp overflow on connected and autonomous vehicles and improve the energy utilization rate. Aiming at the traffic congestion caused by ramp overflow, this paper obtains the data of autonomous vehicles and traffic flow based on vehicle road cooperative perception, analyzes the impact mechanism of vehicle energy consumption, and summarizes the energy consumption modes of autonomous vehicles into three categories. Second, an energy consumption evaluation framework is proposed based on the CSANS strategy. This strategy can make up for the deficiency of constructing neighborhoods within European distance, find important influencing variables on connected and autonomous vehicles’ energy consumption, and accurately capture the manifold characteristics of energy consumption data. Finally, flow control is carried out from the macro perspective of traffic engineering to optimize ramp overflow’s impact on autonomous vehicles’ energy consumption. Through multiple groups of experiments, it has been found that it can effectively reduce the energy consumption of autonomous vehicles.
Design of Total Harmonic Distortion Reduction Using Quantum Coyote Optimization Algorithm for Hybrid Power Generation Systems
Authors: Varghese Lijo Jacob , Raj R. Gandhi , Sankar R. S. Ravi , Tan Zhenhai
Published: April 2023

The usage of various inverters in various industries has gained considerable attention in the power electronics industry in recent years. The harmonic distortion that is induced by various renewable energy sources, along with the growing use of nonlinear loads and power electronic devices, has a significant impact on the distribution system. This is because of the rise in penetration of various renewable energy sources and the usage of nonlinear loads and power electronic devices. In addition, distributed generation (DG) units with inverters (such as solar (PV) and wind turbines) that are integrated into distribution networks are viewed as significant harmonic producers that have substantial adverse effects on power quality. The power quality in the system suffers because of these generators. This study proposes a method of harmonic mitigation for addressing power quality problems that are present in distribution systems as a solution to the challenges that have been found. These concerns have been brought to light as a result of previous research. The standard two-level and three-level inverters were the basis for the development of the multilevel inverter (MLI), which was meant to address their shortcomings. One of the effective technologies that can maintain constant performance is the hybrid power generating system. A hybrid energy system has several benefits, including high dependability, cheap cost and minimal emissions. When used in a hybrid power production system, the reduction of total harmonic distortion (THD) becomes absolutely necessary (HPGS). In this context, the research provides a novel approach for high-performance quantum computing called quantum coyote optimization algorithm-based THD reduction (QCOA-THDR). The QCOA-THDR approach that has been presented has been tested with several converters, including SEPIC, buck–boost and Cuk converters. Additionally, the proportional as well as the integral gain variables of the proportional integral (PI) controller are set in order to achieve decreased total harmonic distortion (THD). In addition, the QCOA system is formed by combining the ideas of quantum computing (QC) with the traditional COA. This is how the QCOA system comes to exist. A limited number of simulations were run, and the results are being analyzed from a variety of perspectives in order to investigate the improved effects that the QCOA-THDR approach has on data. The QCOA-THDR method was shown to have superior results than the more modern techniques, as shown by the comparison research.
OPTIMIZATION OF LASER CUTTING PROCESS PARAMETERS ON SS347 USING GRA AND TOPSIS
Authors: SRINIVASAN D. , RAMAKRISHNAN H. , BALASUNDARAM R. , RAVICHANDRAN M.
Published: April 2023

Laser cutting is a one of the efficient manufacturing processes in industry to cut the hard materials by vaporizing. Stainless steel (SS347) is the most popular material for many applications due its unique characteristics such as efficiency to retain good strength with no inter-granular corrosion even at elevated temperatures. However, the cutting or machining of this material is very difficult. On the other side, the machining cost of laser process is high when compared with other processes. In this work, GRA and TOPSIS techniques are used to study the laser cutting process parameters of SS347. The obtained results were compared with the data mining approach. The input parameters are power, speed, pressure and stand-off distance (SOD) and the output responses of surface roughness, machining time and HAZ are considered. The set of experiments were constructed by using the Taguchi’s L9 method. The predicted closeness value of TOPSIS is greater than the GRA technique and the predominant factor observed is SOD followed by pressure, speed and power. In this work, C4.5-decision tree algorithm is applied to find the most influential parameter. It also represents the low-level knowledge of data set into high level knowledge (If-Then rules form). This investigation reveals that both TOPSIS and data mining suggested the SOD as predominant factor. This result of the optimized process parameters supports the laser assisted manufacturing industries by providing optimized output. Better results were obtained using the optimized set of parameters with the machining time, HAZ and surface roughness being 7.83 s, 0.09 mm and 0.86 [Formula: see text]m, respectively. The results of this work would be very useful for automobiles and aircrafts industries where SS347 is highly employed.
STUDY ON PHOTOCATALYTIC PERFORMANCE OF TiO2 FILM PREPARED ON Q235A STEEL AND ITS DEGRADATION OF ORGANIC POLLUTANT IN SIMULATED WASTEWATER
Authors: ZHOU SHENGHUA , YE YOUXIANG
Published: April 2023

TiO2 film is prepared on the surface of Q235A substrate from an acid solution ([Formula: see text]) to research its degradation of methylene blue organic pollutant in wastewater. The titanium oxysulfate is used as the titanium precursor to provide the source of titanium. The preparation of TiO2 film is mainly a polymerization reaction of titanium oxysulfate, which makes Ti2[Formula: see text] and OH− combine to produce [Ti2O5(OH)2]n precipitation deposited on the cathode surface by electrochemical reaction. TiO2 film is formed after high temperature heating. The nitrate ion which derives from potassium nitrate in the electrolyte is reduced to hydroxide ion during the electrochemical reaction process, resulting in the formation of titanium compounds and titanium hydroxide. The TiO2 film prepared from solution containing 0.2 mol/L KNO3 has the best photocatalytic performance which can effectively degrade the methylene blue organic pollutant in wastewater. However, when the KNO3 in the solution is 0.25 mol/L, excessive hydroxide ions inhibit the hydrolysis of titanium salts and accelerate the oxygen evolution resulting in the decrease of degradation efficiency.
EFFECT OF POST-WELD HEAT TREATMENT ON MICROSTRUCTURE, MECHANICAL PROPERTIES, RESIDUAL STRESSES AND ELECTROCHEMICAL BEHAVIOR OF AISI 4140 TIG WELDMENTS
Authors: MANZOOR SHOAIB , TAHIR MUHAMMAD , KARIM RAMZAN ABDUL , XIONG JINPING , KHAN MUHAMMAD IMRAN
Published: April 2023

Welded structures, specifically their fusion and heat-affected zones, are majorly prone to embrittlement and enhanced corrosion due to the induced residual stresses resulting from the complexity of the heating and cooling cycles during welding. In this work, TIG welding of AISI 4140 alloy steel (chromium–molybdenum steel) was done using the filler wire ER80S-B2 (AWS A5.28) followed by post-weld heat treatment. A comparison of base metal, as-welded, and post-weld heat-treated samples is made based on residual stresses, corrosion resistance, and mechanical properties. Due to the presence of stresses and the formation of unstable martensitic structure, the as-welded samples depicted the highest corrosion rate (8.982 mpy) as compared to the post-weld heat-treated sample (5.707 mpy) which is closer to that of base metal (5.627 mpy). Post-weld heat treatment relieves the residual stresses which results in the enhancement of corrosion resistance. The tensile strength for the base metal, as-weld and PWHT samples come out to be 739, 763, and 744 MPa, respectively. Ductility, on the other hand, is restored by post-weld heat treatment which was compromised in the as-welded samples.
Effect Analysis of Probability Estimators on Parameter Estimation of the Three-Parameter Weibull Distribution
Authors: Yang Xiaoyu , Xie Liyang , Song Jiaxin , Chen Jianpeng , Zhao Bingfeng , Yang Yifeng
Published: April 2023

The three-parameter Weibull distribution is one of the most widely used probabilistic models for the characterization of fatigue failure data. The linear regression estimation (LRE), the minimum discrepancy estimation (MDE), errors-in-variables estimation (EIV) as well as the least squares estimation (LSE) are generally applied in the estimation of Weibull parameters for their simplicity, in which probability estimators play an important role. In this paper, compared with five commonly used estimators, an optimal probability estimator with the four methods for different sample sizes is obtained by Monte Carlo simulations. The optimal probability estimator shows more robustness and higher accuracy. In conclusion, an optimal probability estimator of the midpoint rank is recommended for LRE, MDE and EIV especially with small samples in practical applications.
Linearly Implicit Algorithm with Embedded Newton Iteration of Velocity and its Application in Nonlinear Dynamic Analysis of Structures
Authors: Jia Chuanguo , Su Hongchen , Li Yutao , Gou Yingqi
Published: April 2023

With the application of energy dissipation and damping techniques such as viscous dampers and viscoelastic dampers in seismic engineering, dynamic equilibrium equations of overall structures involve nonlinear damping force. Therefore, numerical integration methods with explicit velocity expressions are more favorable. Based on the average acceleration method, a novel linearly implicit algorithm with explicit expression of velocity is proposed in which once Newton iteration is embedded. The stability of the proposed algorithm in solving equations of motion containing nonlinear restoring force and nonlinear damping force is analyzed using the root locus method. The nonlinear stability of the proposed algorithm is also examined using a single-degree-of-freedom shear-type structure. The dynamic response analysis of a three-storey shear structure model equipped with viscous dampers, a three-storey shear structure equipped with metal dampers, and an eight-storey planar frame structure, are carried to investigate the accuracy and stability of the proposed method with respect to the Chang method and the CR method. The results show that the proposed algorithm exhibits higher accuracy and finer stability for nonlinear dynamic problems.
RB-operator and Nijenhuis operator on Hom-associative conformal algebra
Authors: Asif Sania , Wang Yao , Wu Zhixiang
Published: April 2023

Hom-associative conformal algebra [Formula: see text] is an associative conformal algebra with a twist map and satisfies the Hom-associative conformal identity. This study aims to introduce the notion of the Rota–Baxter operator [Formula: see text] on Hom-associative conformal algebra [Formula: see text]. We generalize our study to Hom-dendriform and Hom-tridendriform conformal algebras and give their relation to Hom-preLie conformal algebras. We give the interrelation between dendriform (and tridendriform) algebra with Hom-associative conformal Rota–Baxter algebra. Furthermore, we explore the Nijenhus operator on Hom-associative conformal algebra and describe its relation with Hom-associative Rota–Baxter operator.
The Impact of Attitude and Subjective Norm on Knowledge-Sharing Behaviour Among the Non-Academic Staff: Behavioural Intention as a Mediating Variable
Authors: Eletter Shorouq , Kaba Abdoulaye , Ramaiah Chennupati K. , El Refae Ghaleb A.
Published: April 2023

The main purpose of this study is to understand the attitude of non-academic staff towards knowledge sharing. Additionally, this study investigates the potential factors that might affect knowledge sharing among the non-academic staff. This is a cross-sectional study of 467 non-academic staff from two universities in the United Arab Emirates (UAE) and India. The findings show that male participants are more involved in knowledge-sharing behaviour ([Formula: see text]) than the female participants ([Formula: see text]); participants aged 50 years and above recorded the highest knowledge-sharing behaviour ([Formula: see text]); participants with non-managerial positions appeared to be more involved in knowledge-sharing behaviour ([Formula: see text]) than those with managerial positions; and finally, the participants from Indian university reported more involvement in knowledge-sharing behaviour ([Formula: see text]) than their UAE counterparts ([Formula: see text]). The findings of the study revealed a significant relationship between attitude towards knowledge sharing, subjective norm and knowledge-sharing behaviour ([Formula: see text]). In addition, the study explored the mediating role of behavioural intentions within the previous variables. The findings stressed that management in higher education institutions needs to foster a culture of knowledge sharing to encourage non-academic staff to share knowledge.
EXPLORING THE IMPACT OF DIGITAL ECONOMY ON AMBIDEXTROUS INNOVATION CAPABILITIES OF FIRMS: MEDIATING EFFECT OF KNOWLEDGE ACQUISITION
Authors: YANG LIN , YANG JINGYI , LU LIANGLIANG , WAN GUOGUANG
Published: April 2023

Although recognised as useful, ambidextrous innovation also presents unique managerial challenges particularly when exploration and exploitation are pursued simultaneously. The paper aims to explore the forming mechanisms of firm’s ambidextrous innovation capabilities using the main approaches in strategic management. The authors theoretically examine the direct effects of the digital economy (DE) on ambidextrous innovation capabilities and the mediating effect of knowledge acquisition (KA) and use the stepwise regression method to conduct an empirical analysis of 178 high-tech companies listed in China’s A-share market from 2013 to 2019. The empirical results show that DE has significantly promoted the ambidextrous innovation capabilities of firms, and also has a significant positive impact on the balance effect between exploratory innovation and exploitative innovation; DE has a significant positive impact on both external knowledge acquisition (EKA) and internal knowledge creation; KA has a significantly positive effect on exploratory innovation, exploitative innovation and their balance effect, and the effect of KA on exploratory innovation is greater than that on exploitative innovation. Furthermore, KA plays a significantly mediating role in the relationship between DE and exploratory innovation/exploitative innovation. The findings of our study provide insights for knowledge management research and have important guiding significance for promoting ambidextrous innovation capabilities of firms in DE.
Portfolio risk allocation through Shapley value
Authors: Hagan Patrick S. , Lesniewski Andrew , Skoufis Georgios E. , Woodward Diana E.
Published: April 2023

We argue that using the Shapley value of cooperative game theory as the scheme for risk allocation among non-orthogonal risk factors is a natural way of interpreting the contribution made by each of such factors to overall portfolio risk. We discuss a Shapley value scheme for allocating risk to non-orthogonal greeks in a portfolio of derivatives. Such a situation arises, for example, when using a stochastic volatility model to capture option volatility smile. We also show that Shapley value allows for a natural method of interpreting components of enterprise risk measures such as VaR and ES. For all applications discussed, we derive explicit formulas and/or numerical algorithms to calculate the allocations.
LSDDB: Lysosomal Storage Disorder Database for Lysosomal Proteins and Their Single Amino-Acid Substitutions
Authors: Paul D. Meshach , Chandrasekhar G. , Srinivasan E. , Sekar P. Chandra , Lavinya B. Udhaya , Rajasekaran R.
Published: April 2023

Lysosomal storage diseases (LSDs) consist of about 60 different monogenic disorders. Most of them occur due to protein misfolding. Only a few of those have been treated with molecular chaperones; the remaining either have limited treatment options or only management therapies. About 1860 single amino-acid substitutions (SAS) have been identified under LSDs. Merely, a handful of mutations have been studied experimentally. Availability of computational tools has made researchers turn toward genetic disorders to focus light on unexplored disorders and their mutations. Since all the LSDs are rare genetic disorders, not much research is carried out in this area. However, a mutational effect on protein function could be predicted, through bioinformatics tools. On that note, out of 1860 SAS, 58 predictions were neutral and 778 were predicted to be disease associated by all programs included in this study. The result of the prediction analysis of all mutations in each of the LSDs is curated into a database. This would make researchers know the deleterious nature of a mutation causing LSD. The database is available at http://lsddb.vit.ac.in:3000/ .
Metadial: A Meta-learning Approach for Arabic Dialogue Generation
Authors: Shamas Mohsen , El Hajj Wassim , Hajj Hazem , Shaban Khaled
Published: April 2023

Dialogue generation is the automatic generation of a text response, given a user’s input. Dialogue generation for low-resource languages has been a challenging tasks for researchers. However, the advancements in deep learning models have made developing conversational agents that perform the tasks of dialogue generation not only possible, but also effective and helpful in many applications spanning a variety of domains. Nevertheless, work on conversational bots for low-resource languages such as the Arabic language is still limited due to various challenges, including the language structure, vocabulary, and the scarcity of its data resources. Meta-learning has been introduced before in the natural language processing (NLP) realm and showed significant improvements in many tasks; however, it has rarely been used in natural language generation (NLG) tasks and never in Arabic NLG. In this work, we propose a meta-learning approach for Arabic dialogue generation for fast adaptation on low-resource domains, namely, Arabic. We start by using existing pre-trained models; we then meta-learn the initial parameters on high-resource dataset before finetuning the parameters on the target tasks. We prove that the proposed model that employs meta-learning techniques improves generalization and enables fast adaptation of the transformer model on low-resource NLG tasks. We report gains in the BLEU-4 and improvements in Semantic textual Similarity (STS) metrics when compared to the existing state-of-the-art approach. We also do a further study on the effectiveness of the meta-learning algorithms on the response generation of the models.
CPT-DF: Congestion Prediction on Toll-Gates Using Deep Learning and Fuzzy Evaluation for Freeway Network in China
Authors: Shi Tongtong , Wang Ping , Qi Xudong , Yang Jiacheng , He Rui , Yang Jingwen , Han Yu
Published: April 2023

Toll-gates are crucial points of management and key congestion bottleneck for the freeway. In order to avoid traffic deterioration and alleviate traffic congestion in advance, it is necessary to predict and evaluate the congestion in toll-gates scattering in large-scale region of freeway network. In this paper, traffic volume and operational delay time are selected from various traffic indicators to evaluate congestion considering the particular characteristics of the traffic flow within the toll-gate area. The congestion prediction method is designed including two modules: a deep learning (DL) prediction and a fuzzy evaluation. We propose a modified deep learning method based on graph convolutional network (GCN) structure in the fusion of dilated causal mechanism and optimize the method for spatial feature extraction by constructing a new adjacency matrix. This new AI network could process spatiotemporal information of traffic volume and operational delay time, that extracted from large-scaled toll-gates spontaneously, and predict key indicators in 15/30/60 min future time. The evaluation module is proposed based on these predicted results. Then, fuzzy C-means algorithm (FCM) is further modified by determining coupling weight for these two key indicators to detect congestion state. Original traffic data are obtained from the current 186 toll-gates served on the freeway network in Shaanxi Province, China. Experimental tests are carried out based on historical data of four months after preprogressing. The comparative tests show the proposed CPT-DF (congestion prediction on toll-gates using deep learning and fuzzy evaluation) outperforms the current-used other models by 6-15%. The successful prediction could extend to the real-time prediction and early warning of traffic congestion in the toll system to improve the intelligent level of traffic emergency management and guidance on the key road of disasters to some extent.
3D Point Cloud Data Registration Algorithm Based on Augmented Reality Technology
Authors: Feng Liying , Weng Ng Giap , Ma Liyao
Published: April 2023

Point cloud data registration is one of the key steps in 3D laser scanning data processing. At present, point cloud data registration has the problems of error and is too much time-consuming. In order to solve the above problems, a 3D point cloud data registration algorithm based on augmented reality technology is proposed, and the 3D data registration model is constructed by combining augmented reality technology, build the evaluation index of 3D point cloud data registration, and carry out the initial registration of 3D point cloud based on the evaluation index. The experiment shows that the 3D point cloud data registration algorithm based on augmented reality technology can more effectively improve the accuracy of data registration and avoid the problem of low efficiency of data registration in practice.
Tree‐Based Risk Factor Identification and Stroke Level Prediction in Stroke Cohort Study
Authors: Li Junyao , Luo Yuxiang , Dong Meina , Liang Yating , Zhao Xuejing , Zhang Yafeng , Ge Zhaoming
Published: April 2023

Objective. This study focuses on the identification of risk factors, classification of stroke level, and evaluation of the importance and interactions of various patient characteristics using cohort data from the Second Hospital of Lanzhou University. Methodology. Risk factors are identified by evaluation of the relationships between factors and response, as well as by ranking the importance of characteristics. Then, after discarding negligible factors, some well‐known multicategorical classification algorithms are used to predict the level of stroke. In addition, using the Shapley additive explanation method (SHAP), factors with positive and negative effects are identified, and some important interactions for classifying the level of stroke are proposed. A waterfall plot for a specific patient is presented and used to determine the risk degree of that patient. Results and Conclusion. The results show that (1) the most important risk factors for stroke are hypertension, history of transient ischemia, and history of stroke; age and gender have a negligible impact. (2) The XGBoost model shows the best performance in predicting stroke risk; it also gives a ranking of risk factors based on their impact. (3) A combination of SHAP and XGBoost can be used to identify positive and negative factors and their interactions in stroke prediction, thereby providing helpful guidance for diagnosis.
Off-Grid DOA Estimation Based on Compressed Sensing on Multipath Environment
Authors: Hu Bin , Shen Xueyong , Jiang Min , Zhao Kaiheng
Published: April 2023

Due to the existence of multipath propagation, the array will receive the multipath propagation signals at the same time while receiving the target signal and the performance of directional of arrival (DOA) estimation will be influenced. In this paper, an off-grid DOA estimation technique based on compressed sensing (CS) on multipath environment is proposed. To deal with the off-grid problem and the multipath propagation problem, we present a compressed sensing based method. This method regards the multipath propagation coefficients vector as a superparameter and the grid as an adjustable parameter. Then, the problem of multipath propagation coefficients estimation is converted to the estimation of an error matrix and the grid is refined iteratively. The simulation results show that the method can achieve off-grid DOA estimation in the presence of the multipath propagation signals.
Supplementary Table S3 from Repurposing Ceritinib Induces DNA Damage and Enhances PARP Inhibitor Responses in High-Grade Serous Ovarian Carcinoma
Authors: Kanakkanthara Arun , Hou Xiaonan , Ekstrom Thomas L. , Zanfagnin Valentina , Huehls Amelia M. , Kelly Rebecca L. , Ding Husheng , Larson Melissa C. , Vasmatzis George , Oberg Ann L. , Kaufmann Scott H. , Mansfield Aaron S. , Weroha S. John , Karnitz Larry M.
Published: April 2023

Supplementary Table S3. P-values for indicated PDX tumor growth comparisons
Figure S3 from HER3 Is an Actionable Target in Advanced Prostate Cancer
Authors: Gil Veronica , Miranda Susana , Riisnaes Ruth , Gurel Bora , D’Ambrosio Mariantonietta , Vasciaveo Alessandro , Crespo Mateus , Ferreira Ana , Brina Daniela , Troiani Martina , Sharp Adam , Sheehan Beshara , Christova Rossitza , Seed George , Figueiredo Ines , Lambros Maryou , Dolling David , Rekowski Jan , Alajati Abdullah , Clarke Matthew , Pereira Rita , Flohr Penny , Fowler Gemma , Boysen Gunther , Sumanasuriya Semini , Bianchini Diletta , Rescigno Pasquale , Aversa Caterina , Tunariu Nina , Guo Christina , Paschalis Alec , Bertan Claudia , Buroni Lorenzo , Ning Jian , Carreira Suzanne , Workman Paul , Swain Amanda , Califano Andrea , Shen Michael M. , Alimonti Andrea , Neeb Antje , Welti Jonathan , Yuan Wei , de Bono Johann
Published: April 2023

Supplementary Figure S3
Supplementary Document from Inhibition of FGFR Reactivates IFNγ Signaling in Tumor Cells to Enhance the Combined Antitumor Activity of Lenvatinib with Anti-PD-1 Antibodies
Authors: Adachi Yusuke , Kamiyama Hiroshi , Ichikawa Kenji , Fukushima Sayo , Ozawa Yoichi , Yamaguchi Shogo , Goda Satoshi , Kimura Takayuki , Kodama Kotaro , Matsuki Masahiro , Miyano Saori Watanabe , Yokoi Akira , Kato Yu , Funahashi Yasuhiro
Published: April 2023

Supplementary materials and methods
Supplementary material from Inhibition of ERK5 Elicits Cellular Senescence in Melanoma via the Cyclin-Dependent Kinase Inhibitor p21
Authors: Tubita Alessandro , Lombardi Zoe , Tusa Ignazia , Lazzeretti Azzurra , Sgrignani Giovanna , Papini Dimitri , Menconi Alessio , Gagliardi Sinforosa , Lulli Matteo , Dello Sbarba Persio , Esparís-Ogando Azucena , Pandiella Atanasio , Stecca Barbara , Rovida Elisabetta
Published: April 2023

Supplementary material and supplementary tables
Supplementary Table 3 from Super Enhancer-Mediated Upregulation of HJURP Promotes Growth and Survival of t(4;14)-Positive Multiple Myeloma
Authors: Jia Yunlu , Zhou Jianbiao , Tan Tze King , Chung Tae-Hoon , Chen Yongxia , Chooi Jing-Yuan , Sanda Takaomi , Fullwood Melissa J. , Xiong Sinan , Toh Sabrina H.M. , Balan Kalpnaa , Wong Regina W.J. , Lim Julia S.L. , Zhang Enfan , Cai Zhen , Shen Peng , Chng Wee Joo
Published: April 2023

Supplementary Table 3 Uni- and multivariate Cox survival analysis using HJURP and NSD2 expression in myeloma dataset
Figure S2 from Inhibition of ERK5 Elicits Cellular Senescence in Melanoma via the Cyclin-Dependent Kinase Inhibitor p21
Authors: Tubita Alessandro , Lombardi Zoe , Tusa Ignazia , Lazzeretti Azzurra , Sgrignani Giovanna , Papini Dimitri , Menconi Alessio , Gagliardi Sinforosa , Lulli Matteo , Dello Sbarba Persio , Esparís-Ogando Azucena , Pandiella Atanasio , Stecca Barbara , Rovida Elisabetta
Published: April 2023

Supplementary Figure S2 R1
Supplementary Table 1 from Super Enhancer-Mediated Upregulation of HJURP Promotes Growth and Survival of t(4;14)-Positive Multiple Myeloma
Authors: Jia Yunlu , Zhou Jianbiao , Tan Tze King , Chung Tae-Hoon , Chen Yongxia , Chooi Jing-Yuan , Sanda Takaomi , Fullwood Melissa J. , Xiong Sinan , Toh Sabrina H.M. , Balan Kalpnaa , Wong Regina W.J. , Lim Julia S.L. , Zhang Enfan , Cai Zhen , Shen Peng , Chng Wee Joo
Published: April 2023

Supplementary Table 1 shows the list of 4C primers applied in the Circular Chromosome Conformation Capture assay.
Data from Repurposing Ceritinib Induces DNA Damage and Enhances PARP Inhibitor Responses in High-Grade Serous Ovarian Carcinoma
Authors: Kanakkanthara Arun , Hou Xiaonan , Ekstrom Thomas L. , Zanfagnin Valentina , Huehls Amelia M. , Kelly Rebecca L. , Ding Husheng , Larson Melissa C. , Vasmatzis George , Oberg Ann L. , Kaufmann Scott H. , Mansfield Aaron S. , Weroha S. John , Karnitz Larry M.
Published: April 2023

Abstract
PARP inhibitors (PARPi) have activity in homologous recombination (HR) repair-deficient, high-grade serous ovarian cancers (HGSOC). However, even responsive tumors develop PARPi resistance, highlighting the need to delay or prevent the appearance of PARPi resistance. Here, we showed that the ALK kinase inhibitor ceritinib synergizes with PARPis by inhibiting complex I of the mitochondrial electron transport chain, which increases production of reactive oxygen species (ROS) and subsequent induction of oxidative DNA damage that is repaired in a PARP-dependent manner. In addition, combined treatment with ceritinib and PARPi synergized in HGSOC cell lines irrespective of HR status, and a combination of ceritinib with the PARPi olaparib induced tumor regression more effectively than olaparib alone in HGSOC patient-derived xenograft (PDX) models. Notably, the ceritinib and olaparib combination was most effective in PDX models with preexisting PARPi sensitivity and was well tolerated. These findings unveil suppression of mitochondrial respiration, accumulation of ROS, and subsequent induction of DNA damage as novel effects of ceritinib. They also suggest that the ceritinib and PARPi combination warrants further investigation as a means to enhance PARPi activity in HGSOC, particularly in tumors with preexisting HR defects.
Significance:
The kinase inhibitor ceritinib synergizes with PARPi to induce tumor regression in ovarian cancer models, suggesting that ceritinib combined with PARPi may be an effective strategy for treating ovarian cancer.
Data from T Cells Promote Metastasis by Regulating Extracellular Matrix Remodeling following Chemotherapy
Authors: Haj-Shomaly Jozafina , Vorontsova Avital , Barenholz-Cohen Tamar , Levi-Galibov Oshrat , Devarasetty Mahesh , Timaner Michael , Raviv Ziv , Cooper Tim J. , Soker Shay , Hasson Peleg , Weihs Daphne , Scherz-Shouval Ruth , Shaked Yuval
Published: April 2023

Abstract
Metastasis is the main cause of cancer-related mortality. Despite intense efforts to understand the mechanisms underlying the metastatic process, treatment of metastatic cancer is still challenging. Here we describe a chemotherapy-induced, host-mediated mechanism that promotes remodeling of the extracellular matrix (ECM), ultimately facilitating cancer cell seeding and metastasis. Paclitaxel (PTX) chemotherapy enhanced rapid ECM remodeling and mechanostructural changes in the lungs of tumor-free mice, and the protein expression and activity of the ECM remodeling enzyme lysyl oxidase (LOX) increased in response to PTX. A chimeric mouse model harboring genetic LOX depletion revealed chemotherapy-induced ECM remodeling was mediated by CD8+ T cells expressing LOX. Consistently, adoptive transfer of CD8+ T cells, but not CD4+ T cells or B cells, from PTX-treated mice to naïve immunodeprived mice induced pulmonary ECM remodeling. Lastly, in a clinically relevant metastatic breast carcinoma model, LOX inhibition counteracted the metastasis-promoting, ECM-related effects of PTX. This study highlights the role of immune cells in regulating ECM and metastasis following chemotherapy, suggesting that inhibiting chemotherapy-induced ECM remodeling represents a potential therapeutic strategy for metastatic cancer.
Significance:
Chemotherapy induces prometastatic pulmonary ECM remodeling by upregulating LOX in T cells, which can be targeted with LOX inhibitors to suppress metastasis.

See related commentary by Kolonin and Woodward, p. 197
Data from A Microfluidic Cancer-on-Chip Platform Predicts Drug Response Using Organotypic Tumor Slice Culture
Authors: Chakrabarty Sanjiban , Quiros-Solano William F. , Kuijten Maayke M.P. , Haspels Ben , Mallya Sandeep , Lo Calvin Shun Yu , Othman Amr , Silvestri Cinzia , van de Stolpe Anja , Gaio Nikolas , Odijk Hanny , van de Ven Marieke , de Ridder Corrina M.A. , van Weerden Wytske M. , Jonkers Jos , Dekker Ronald , Taneja Nitika , Kanaar Roland , van Gent Dik C.
Published: April 2023

Abstract
Optimal treatment of cancer requires diagnostic methods to facilitate therapy choice and prevent ineffective treatments. Direct assessment of therapy response in viable tumor specimens could fill this diagnostic gap. Therefore, we designed a microfluidic platform for assessment of patient treatment response using tumor tissue slices under precisely controlled growth conditions. The optimized Cancer-on-Chip (CoC) platform maintained viability and sustained proliferation of breast and prostate tumor slices for 7 days. No major changes in tissue morphology or gene expression patterns were observed within this time frame, suggesting that the CoC system provides a reliable and effective way to probe intrinsic chemotherapeutic sensitivity of tumors. The customized CoC platform accurately predicted cisplatin and apalutamide treatment response in breast and prostate tumor xenograft models, respectively. The culture period for breast cancer could be extended up to 14 days without major changes in tissue morphology and viability. These culture characteristics enable assessment of treatment outcomes and open possibilities for detailed mechanistic studies.
Significance:
The Cancer-on-Chip platform with a 6-well plate design incorporating silicon-based microfluidics can enable optimal patient-specific treatment strategies through parallel culture of multiple tumor slices and diagnostic assays using primary tumor material.
Frequent Overexpression of HER3 in Brain Metastases from Breast and Lung Cancer
Authors: Tomasich Erwin , Steindl Ariane , Paiato Christina , Hatziioannou Teresa , Kleinberger Markus , Berchtold Luzia , Puhr Rainer , Hainfellner Johannes A. , Müllauer Leonhard , Widhalm Georg , Eckert Franziska , Bartsch Rupert , Heller Gerwin , Preusser Matthias , Berghoff Anna Sophie
Published: April 2023

Purpose:

HER3 belongs to a family of receptor tyrosine kinases with oncogenic properties and is targeted by a variety of novel anticancer agents. There is a huge unmet medical need for systemic treatment options in patients with brain metastases (BM). Therefore, we aimed to investigate HER3 expression in BM of breast (BCa) and non–small cell lung cancer (NSCLC) as the basis for future clinical trial design.

Experimental Design:

We analyzed 180 BM samples of breast cancer or NSCLC and 47 corresponding NSCLC extracranial tissue. IHC was performed to evaluate protein expression of HER3, and immune cells based on CD3, CD8, and CD68. To identify dysregulated pathways based on differential DNA methylation patterns, we used Infinium MethylationEPIC microarrays.

Results:

A total of 99/132 (75.0%) of BCa-BM and 35/48 (72.9%) of NSCLC-BM presented with HER3 expression. Among breast cancer, HER2-positive and HER2-low BM showed significantly higher rates of HER3 coexpression than HER2-negative BM (87.1%/85.7% vs. 61.0%, P = 0.004). Among NSCLC, HER3 was more abundantly expressed in BM than in matched extracranial samples (72.9% vs. 41.3%, P = 0.003). No correlation of HER3 expression and intratumoral immune cell density was observed. HER3 expression did not correlate with overall survival from BM diagnosis. Methylation signatures differed according to HER3 status in BCa-BM samples. Pathway analysis revealed subtype-specific differences, such as TrkB and Wnt signaling pathways dysregulated in HER2-positive and triple-negative breast cancer BM, respectively.

Conclusions:

HER3 is highly abundant in BM of breast cancer and NSCLC. Given the promising results of antibody–drug conjugates in extracranial disease, BM-specific trials that target HER3 are warranted.

See related commentary by Kabraji and Lin, p. 2961
Is Tumour Thickness Measurement Required for MOLES Scoring of Melanocytic Choroidal Tumours?
Authors: Ching Jared , AlHarby Lamis , Sagoo Mandeep S. , Damato Bertil
Published: April 2023

Introduction: It can be challenging to distinguish between choroidal naevi and melanomas in the community setting, particularly without access to ultrasonography (US), required to measure the thickness of melanocytic choroidal tumours. We aimed to determine whether thickness measurement is required for MOLES scoring of melanocytic choroidal tumours. Methods: The dataset of a recent MOLES evaluation was reviewed. Patients were selected for the present study if their MOLES tumour size category was determined by tumour thickness measured with US. The largest basal tumour diameter and tumour thickness were then measured from ultra-widefield fundus images and optical coherence tomography (OCT) images, respectively. Results: The tumour size category was determined by tumour diameter in 203/222 (91.4%) with no influence of tumour thickness. The tumour thickness influenced the MOLES score in 19/222 (8.6%) patients. In 11/19 patients with OCT measurements of tumour thickness, the US measurement exceeded the OCT by more than 25% in 5 patients, more than 50% in 2 patients, and more than 75% in 1 patient. As a result, the revised tumour thickness based on OCT determined the size category in 4/216 (1.8%) patients. The ultra-widefield fundus images measurements increased the diameter score by 1 in 5 patients. As a result, the revised tumour thickness determined the size category in 4/216 (1.8%) patients. If both the revised diameter and thickness scores were considered, the MOLES score reduced in 4 patients. If both the diameter and thickness scores were considered, the MOLES score reduced in 5 and increased in 1. Only 0.94% (2/211) of melanocytic choroidal tumours assessed with MOLES when using Optos ultra-widefield fundus images diameter and OCT to measure tumour diameter and thickness, respectively, required a change in management from a reduction in MOLES score from 1 to 0. Discussion/Conclusion: This study suggests that the MOLES category for size is influenced more by the tumour diameter, if it can be measured accurately, than by the thickness. This study suggests ignoring tumour thickness if this cannot be measured accurately with OCT, unless the tumour has a mushroom shape.
Novel Metabolites to Improve Glomerular Filtration Rate Estimation
Authors: Guo Xinghua , Peng Hongquan , Liu Peijia , Tang Leile , Fang Jia , AoIeong ChiWa , Tou Tou , Tsai Tsungyang , Liu Xun
Published: April 2023

Introduction: The glomerular filtration rate (GFR) is crucial for chronic kidney disease (CKD) diagnosis and therapy. Various studies have sought to recognize ideal endogenous markers to improve the estimated GFR for clinical practice. To screen out potential novel metabolites related to GFR (mGFR) measurement in CKD patients from the Chinese population, we identified more biomarkers for improving GFR estimation. Methods: Fifty-three CKD participants were recruited from the Third Affiliated Hospital of Sun Yat-sen University in 2020. For each participant, mGFR was evaluated by utilizing the plasma clearance of iohexol and collecting serum samples for untargeted metabolomics analyses by ultrahigh-performance liquid chromatography-tandem mass spectroscopy. All participants were divided into four groups according to mGFR. The metabolite peak area data were uploaded to MetaboAnalyst 5.0 for one-way analysis of variance, principal component analysis, and partial least squares-discriminant analysis and confirmed the metabolites whose levels increased or decreased with mGFR and variable importance in projection (VIP) values >1. Metabolites were ranked by correlation with the original values of mGFR, and metabolites with a correlation coefficient >0.8 and VIP >2 were identified. Results: We screened out 198 metabolites that increased or decreased with mGFR decline. After ranking by correlation with mGFR, the top 50 metabolites were confirmed. Further studies confirmed the 10 most highly correlated metabolites. Conclusion: We screened out the metabolites that increased or decreased with mGFR decline in CKD patients from the Chinese population, and 10 of them were highly correlated. They are potential novel metabolites to improve GFR estimation.