bluuebunny/crossref_metadata_2025 huggingface dataset:
Neuroprotective Efficacy of a Nanomicellar Complex of Carnosine and Lipoic Acid in a Rat Model of Rotenone-Induced Parkinson’s Disease
Authors: Kulikova Olga , Troshev Dmitry , Berezhnoy Daniil , Stvolinsky Sergey , Timoshina Yulia , Abaimov Denis , Muzychuk Olga , Latanov Alexander , Fedorova Tatiana
Published: June 2023

Oxidative stress, accompanied by mitochondrial dysfunction, is a key mechanism involved in the pathogenesis of Parkinson’s disease (PD). Both carnosine and lipoic acid are potent antioxidants, the applicability of which in therapy is hindered by their limited bioavailability. This study aimed to evaluate the neuroprotective properties of a nanomicellar complex of carnosine and lipoic acid (CLA) in a rotenone-induced rat model of PD. Parkinsonism was induced via the administration of 2 mg/kg rotenone over the course of 18 days. Two doses of intraperitoneal CLA (25 mg/kg and 50 mg/kg) were administered alongside rotenone to assess its neuroprotective effect. At 25 mg/kg CLA decreased muscle rigidity and partially restored locomotor activity in animals that received rotenone. Furthermore, it caused an overall increase in brain tissue antioxidant activity, accompanied by a 19% increase in neuron density in the substantia nigra and increased dopamine levels in the striatum relative to animals that only received rotenone. Based on the acquired results, it may be concluded that CLA have neuroprotective properties and could potentially be beneficial in PD treatment when used in conjunction with the base therapy.
Electromagnetic Imaging for Buried Conductors Using Deep Convolutional Neural Networks
Authors: Chiu Chien-Ching , Chien Wei , Yu Kai-Xu , Chen Po-Hsiang , Lim Eng Hock
Published: June 2023

In the past, many conventional algorithms, such as self-adaptive dynamic differential evolution and asynchronous particle swarm optimization, were used to reconstruct buried objects in the frequency domain; these were unfortunately time-consuming during the iterative, repeated computing process of the scattered field. Consequently, we propose an innovative deep convolutional neural network approach to solve the electromagnetic inverse scattering problem for buried conductors in this paper. Different shapes of conductors are buried in one half-space and the electromagnetic wave from the other half-space is incident. The shape of the conductor can be reconstructed promptly by inputting the received scattered fields measured from the upper half-space into the deep convolutional neural network module, which avoids the computational complexity of Green’s function for training. Numerical results show that the root mean square error for differently shaped—circular, elliptical, arrow, peanut, four-petal, and three-petal—reconstructed images are, respectively, 2.95%, 3.11%, 17.81%, 15.10%, 14.14%, and 15.24%. Briefly speaking, not only can circular and elliptical buried conductors be reconstructed; some irregular shapes can be reconstructed well. On the contrary, the reconstruction result by U-Net for buried objects is worse since it is not able to obtain a good preliminary image by processing only the upper scattered field—that is, rather than the full space. In other words, our proposed deep convolutional neural network can efficiently solve the electromagnetic inverse scattering problem of buried conductors and provide a novel method for the microwave imaging of the buried conductors. This is the first successful attempt at using deep convolutional neural networks for buried conductors in the frequency domain, which may be useful for practical applications in various fields such as the medical, military, or industrial fields, including magnetic resonance imaging, mine detection and clearance, non-destructive testing, gas or wire pipeline detection, etc.
STA-GCN: Spatial-Temporal Self-Attention Graph Convolutional Networks for Traffic-Flow Prediction
Authors: Chang Zhihong , Liu Chunsheng , Jia Jianmin
Published: June 2023

As an important component of intelligent transportation-management systems, accurate traffic-parameter prediction can help traffic-management departments to conduct effective traffic management. Due to the nonlinearity, complexity, and dynamism of highway-traffic data, traffic-flow prediction is still a challenging issue. Currently, most spatial–temporal traffic-flow-prediction models adopt fixed-structure time convolutional and graph convolutional models, which lack the ability to capture the dynamic characteristics of traffic flow. To address this issue, this paper proposes a spatial–temporal prediction model that can capture the dynamic spatial–temporal characteristics of traffic flow, named the spatial–temporal self-attention graph convolutional network (STA-GCN). In terms of feature engineering, we used the time cosine decomposition and one-hot encoding methods to capture the periodicity and heterogeneity of traffic-flow changes. Additionally, in order to build the model, self-attention mechanisms were incorporated into the spatial–temporal convolution to capture the spatial–temporal dynamic characteristics of traffic flow. The experimental results indicate that the performance of the proposed model on two traffic-volume datasets is superior to those of several baseline models. In particular, in long-term prediction, the prediction error can be reduced by over 5%. Further, the interpretability and robustness of the prediction model are addressed by considering the spatial dynamic changes.
Effectiveness of Tuned Mass Damper in Reducing Damage Caused by Strong Earthquake in a Medium-Rise Building
Authors: Mazzon Lucas , Frappa Giada , Pauletta Margherita
Published: June 2023

A case study where a tuned mass damper (TMD) was installed at the top of a five-story reinforced concrete (RC) building is presented. The aim of the study was to investigate the effectiveness of the TMD in changing the structural behavior of medium-rise existing buildings from dissipative to non-dissipative in order to eliminate reparation or demolition costs resulting from damages caused by strong earthquakes. The TMD mass is made by a RC slab lying on flat surface sliders. Horizontal stiffness and damping of the TMD are both provided by lead rubber isolators in the first proposed solution and by low-damping rubber isolators and viscous linear dampers, respectively, in the second. The improvement in the building’s structural behavior attained with the installation of the TMD was assessed by considering the flexural demand over capacity ratios of structural elements and the energy dissipated by the TMD. These results are compared with those of the same building retrofitted with a base isolation system. In both of the proposed solutions, TMD remarkably changed the modal behavior of the considered building, improved the flexural verifications, and dissipated most of the input seismic energy. It is therefore demonstrated that a TMD is a valid solution for the retrofit of medium-rise existing buildings.
An Improved YOLOv7 Model Based on Visual Attention Fusion: Application to the Recognition of Bouncing Locks in Substation Power Cabinets
Authors: Wang Yang , Zhang Xiaofeng , Li Longmei , Wang Liming , Zhou Ziyang , Zhang Peng
Published: June 2023

With the continuous progress of intelligent power system technology, in order to meet the needs of substation operation and maintenance, a target detection algorithm is applied to identify the status of equipment switches. YOLOv7, as the latest achievement of YOLO (You Only Look Once) series algorithms, has good speed and accuracy in target detection tasks. However, when the generalized network is applied in a specific scenario, its advantages are not obvious due to its high weight and poor portability. In this paper, an improved GF-YOLOv7 network model is proposed to apply in the recognition of the status of bounce locks in a substation. The MobileViT module is used to improve the feature extraction ability of the backbone network. Referring to the CBAM feature attention mechanism, the channel attention module and the spatial attention module are used to design a more lightweight feature fusion network. The experimental results in the test set show that the proposed network can significantly reduce the network weight and improve the detection accuracy on the basis of a small reduction in the detection speed, and the accuracy reaches 97.8%, which can meet the needs of the detection task of substation bounce locks.
Weakly Supervised U-Net with Limited Upsampling for Sound Event Detection
Authors: Lee Sangwon , Kim Hyemi , Jang Gil-Jin
Published: June 2023

Sound event detection (SED) is the task of finding the identities of sound events, as well as their onset and offset timings from audio recordings. When complete timing information is not available in the training data, but only the event identities are known, SED should be solved by weakly supervised learning. The conventional U-Net with global weighted rank pooling (GWRP) has shown a decent performance, but extensive computation is demanded. We propose a novel U-Net with limited upsampling (LUU-Net) and global threshold average pooling (GTAP) to reduce the model size, as well as the computational overhead. The expansion along the frequency axis in the U-Net decoder was minimized, so that the output map sizes were reduced by 40% at the convolutional layers and 12.5% at the fully connected layers without SED performance degradation. The experimental results on a mixed dataset of DCASE 2018 Tasks 1 and 2 showed that our limited upsampling U-Net (LUU-Net) with GTAP was about 23% faster in training and achieved 0.644 in audio tagging and 0.531 in weakly supervised SED tasks in terms of F1 scores, while U-Net with GWRP showed 0.629 and 0.492, respectively. The major contribution of the proposed LUU-Net is the reduction in the computation time with the SED performance being maintained or improved. The other proposed method, GTAP, further improved the training time reduction and provides versatility for various audio mixing conditions by adjusting a single hyperparameter.
A Blockchain-Based Cooperative Authentication Mechanism for Smart Grid
Authors: Li Yunfa , Zhang Di , Wang Zetian , Liu Guanxu
Published: June 2023

With the advancement of smart devices, the operation and communication of smart grids have become increasingly efficient. Many smart devices such as smart meters, smart transformers, and smart grid controllers are already widely used in smart grids. Thus, a series of complex architectures and a series of communication modes have been formed. However, these smart devices will be exposed to various cyber attacks such as distributed denial of service (DDoS) attack and replay attack. This is because they are open and dynamic. Therefore, there are serious security problems in the complex architectures and the communication modes. In this paper, we propose a multi-domain authentication mechanism based on blockchain cooperation to maintain the security of smart devices. In this mechanism, we propose a series of methods and algorithms, which include initialization method based on blockchain cooperative authentication, dynamic change method of intelligent devices and information, cross-domain authentication algorithm, and cross-domain key cooperative algorithm. To demonstrate the security and effectiveness of our proposed mechanism, we analysed its security and conducted a series of simulation experiments. The analysis and simulation experiments show that our proposed approach is secure and effective.
Research on Cutting Temperature of GH4169 Turning with Micro-Textured Tools
Authors: Feng Xinmin , Fan Xiwen , Hu Jingshu , Wei Jiaxuan
Published: June 2023

The GH4169 superalloy has the characteristics of high strength, strong thermal stability, large specific heat capacity, small thermal conductivity, etc., but it is also a typical hard-to-cut material. When cutting this material with ordinary cutting tools, the cutting force is large, and the cutting temperature is high, which leads to severe tool wear and short service life. In order to improve the performance of tools when cutting GH4169, reduce the cutting temperature, and extend the service life of the tool, micro-textured tools were used to cut GH4169 in spray cooling. The effects of micro-texture morphology and dimensional parameters on cutting temperature were analyzed. Firstly, tools with micro-textures of five different morphologies were designed near the nose on the rake face of the cemented carbide tools. The three-dimensional cutting models of the micro-textured tools with different morphologies were established by using ABAQUS, and a simulation analysis was carried out. Compared with the non-textured tools, the micro-texture morphology with the lowest cutting temperature was selected according to the simulation results of the cutting temperature. Secondly, based on the optimized morphology, tools with micro-textures of different size parameters were designed. When cutting GH4169, the cutting temperature of the tools was simulated and analyzed, and the size parameters of the micro-textured tools with the lowest cutting temperature were selected as well. Finally, the designed micro-textured tools were processed and applied in cutting experiments. The simulation model was verified in the experiments, and the influence of size parameters of micro-textures on the cutting temperature was analyzed. This paper provides a theoretical reference and basis for cutting GH4169 and the design and application of micro-textured tools.
Global Warming and Topography Impact the Amplitude of the Synoptic-Scale Surface Temperature Variability across the US
Authors: Secor Michael , Sun Jie , Yang Fucheng , Zou Xiaolei , Wu Zhaohua
Published: June 2023

In recent decades, the United States has experienced changing patterns of extreme temperature. Although much progress has been made, delineating the change in synoptic surface temperature variability (SSTV) and understanding its potential causes remain to be pursued. In this study, we seek to provide a quantitative description of the change in SSTV in the past seven decades across the US and its potential relevant physical factors. To achieve this goal, we develop a spatiotemporally local analysis method based on the ensemble empirical mode decomposition that bypasses the stationary assumption and makes it possible to continuously track the change in SSTV in the spatiotemporal domain. We have found that the change in SSTV across the US is spatially inhomogeneous and temporally non-uniform. The change in the SSTV amplitude ranges from −36% to 39% across the continental United States, Northern Mexico, and surrounding oceans. Higher altitudes and surrounding regions generally see an increase in variability, while elsewhere over land, a reduction is observed, creating a three-band zonal structure across the continental United States. Generally, increases in variability are observed in the subtropics. The shape of the spatiotemporal evolution of SSTV implies that the topography of the United States may play an important role in altering synoptic-scale variability.
Structural Damage Identification Using the First-Order Vibration-Mode-Based Frequency-Shift Flexibility Sensitivity Algorithm
Authors: Cao Shanshan , Yang Qiuwei , Peng Xi
Published: June 2023

The diagnosis of structural damage usually belongs to a mathematical inverse problem. This work presents a novel frequency-shift flexibility sensitivity algorithm for structural damage assessment using only the first-order vibration mode to achieve the goal of successfully identifying structural damage with fewer modal parameters. The core idea of the proposed method is to make the first-order vibration mode contribute the most to a structural flexibility matrix through the frequency-shift operation. A high-precision flexibility matrix can be obtained after the frequency-shift operation, which only needs the first mode of structural free vibration. Through this special advantage, structural damage coefficients can be accurately calculated by the frequency-shift flexibility sensitivity equation. Thus, a reliable identification result can be obtained according to the values of the calculated damage coefficients. In some engineering applications, another advantage of the proposed method is that it does not require a complete finite element modeling process, as long as a few lower-frequency vibration modes of the intact structure are measured. A truss structure and a beam structure are used as two numerical examples to demonstrate the proposed approach. The results show that the proposed method has higher calculation accuracy than the ordinary flexibility sensitivity method by using only the first-order vibration mode. The proposed method can overcome possible misdiagnosis of the ordinary flexibility sensitivity method. It also has been shown that the proposed method may have the potential to identify minor damage in a structure. Using the experimental data of a steel frame structure, the effectiveness and reliability of the proposed method have been further verified. The proposed method provides a simple way for structural damage identification with only a few vibration modal data.
Efficient Method to Solve the Monge–Kantarovich Problem Using Wavelet Analysis
Authors: Acosta-Portilla Juan Rafael , González-Flores Carlos , López-Martínez Raquiel Rufino , Sánchez-Nungaray Armando
Published: June 2023

In this paper, we present and justify a methodology to solve the Monge–Kantorovich mass transfer problem through Haar multiresolution analysis and wavelet transform with the advantage of requiring a reduced number of operations to carry out. The methodology has the following steps. We apply wavelet analysis on a discretization of the cost function level j and obtain four components comprising one corresponding to a low-pass filter plus three from a high-pass filter. We obtain the solution corresponding to the low-pass component in level j−1 denoted by μj−1*, and using the information of the high-pass filter components, we get a solution in level j denoted by μ^j. Finally, we make a local refinement of μ^j and obtain the final solution μjσ.
Strong Edge Coloring of K4(t)-Minor Free Graphs
Authors: Yin Huixin , Han Miaomiao , Xu Murong
Published: June 2023

A strong edge coloring of a graph G is a proper coloring of edges in G such that any two edges of distance at most 2 are colored with distinct colors. The strong chromatic index χs′(G) is the smallest integer l such that G admits a strong edge coloring using l colors. A K4(t)-minor free graph is a graph that does not contain K4(t) as a contraction subgraph, where K4(t) is obtained from a K4 by subdividing edges exactly t−4 times. The paper shows that every K4(t)-minor free graph with maximum degree Δ(G) has χs′(G)≤(t−1)Δ(G) for t∈{5,6,7} which generalizes some known results on K4-minor free graphs by Batenburg, Joannis de Verclos, Kang, Pirot in 2022 and Wang, Wang, and Wang in 2018. These upper bounds are sharp.
Cyclosporines Antagonize the Antiviral Activity of IFITMProteins by Redistributing Them toward the Golgi Apparatus
Authors: Prikryl David , Marin Mariana , Desai Tanay M. , Du Yuhong , Fu Haian , Melikyan Gregory B.
Published: June 2023

Interferon-induced transmembrane proteins (IFITMs) block the fusion of diverse enveloped viruses, likely through increasing the cell membrane’s rigidity. Previous studies have reported that the antiviral activity of the IFITM family member, IFITM3, is antagonized by cell pretreatment with rapamycin derivatives and cyclosporines A and H (CsA and CsH) that promote the degradation of IFITM3. Here, we show that CsA and CsH potently enhance virus fusion with IFITM1- and IFITM3-expressing cells by inducing their rapid relocalization from the plasma membrane and endosomes, respectively, towards the Golgi. This relocalization is not associated with a significant degradation of IFITMs. Although prolonged exposure to CsA induces IFITM3 degradation in cells expressing low endogenous levels of this protein, its levels remain largely unchanged in interferon-treated cells or cells ectopically expressing IFITM3. Importantly, the CsA-mediated redistribution of IFITMs to the Golgi occurs on a much shorter time scale than degradation and thus likely represents the primary mechanism of enhancement of virus entry. We further show that rapamycin also induces IFITM relocalization toward the Golgi, albeit less efficiently than cyclosporines. Our findings highlight the importance of regulation of IFITM trafficking for its antiviral activity and reveal a novel mechanism of the cyclosporine-mediated modulation of cell susceptibility to enveloped virus infection.
Highly Specialized Mechanisms for Mitochondrial Transport in Neurons: From Intracellular Mobility to Intercellular Transfer of Mitochondria
Authors: Zaninello Marta , Bean Camilla
Published: June 2023

The highly specialized structure and function of neurons depend on a sophisticated organization of the cytoskeleton, which supports a similarly sophisticated system to traffic organelles and cargo vesicles. Mitochondria sustain crucial functions by providing energy and buffering calcium where it is needed. Accordingly, the distribution of mitochondria is not even in neurons and is regulated by a dynamic balance between active transport and stable docking events. This system is finely tuned to respond to changes in environmental conditions and neuronal activity. In this review, we summarize the mechanisms by which mitochondria are selectively transported in different compartments, taking into account the structure of the cytoskeleton, the molecular motors and the metabolism of neurons. Remarkably, the motor proteins driving the mitochondrial transport in axons have been shown to also mediate their transfer between cells. This so-named intercellular transport of mitochondria is opening new exciting perspectives in the treatment of multiple diseases.
Development of Antiepileptic Drugs throughout History: From Serendipity to Artificial Intelligence
Authors: Corrales-Hernández María , Villarroel-Hagemann Sebastián , Mendoza-Rodelo Isabella , Palacios-Sánchez Leonardo , Gaviria-Carrillo Mariana , Buitrago-Ricaurte Natalia , Espinosa-Lugo Santiago , Calderon-Ospina Carlos-Alberto , Rodríguez-Quintana Jesús
Published: June 2023

This article provides a comprehensive narrative review of the history of antiepileptic drugs (AEDs) and their development over time. Firstly, it explores the significant role of serendipity in the discovery of essential AEDs that continue to be used today, such as phenobarbital and valproic acid. Subsequently, it delves into the historical progression of crucial preclinical models employed in the development of novel AEDs, including the maximal electroshock stimulation test, pentylenetetrazol-induced test, kindling models, and other animal models. Moving forward, a concise overview of the clinical advancement of major AEDs is provided, highlighting the initial milestones and the subsequent refinement of this process in recent decades, in line with the emergence of evidence-based medicine and the implementation of increasingly rigorous controlled clinical trials. Lastly, the article explores the contributions of artificial intelligence, while also offering recommendations and discussing future perspectives for the development of new AEDs.
Aptameric Fluorescent Biosensors for Liver Cancer Diagnosis
Authors: Park Seonga , Cho Euni , Chueng Sy-Tsong Dean , Yoon June-Sun , Lee Taek , Lee Jin-Ho
Published: June 2023

Liver cancer is a prevalent global health concern with a poor 5-year survival rate upon diagnosis. Current diagnostic techniques using the combination of ultrasound, CT scans, MRI, and biopsy have the limitation of detecting detectable liver cancer when the tumor has already progressed to a certain size, often leading to late-stage diagnoses and grim clinical treatment outcomes. To this end, there has been tremendous interest in developing highly sensitive and selective biosensors to analyze related cancer biomarkers in the early stage diagnosis and prescribe appropriate treatment options. Among the various approaches, aptamers are an ideal recognition element as they can specifically bind to target molecules with high affinity. Furthermore, using aptamers, in conjunction with fluorescent moieties, enables the development of highly sensitive biosensors by taking full advantage of structural and functional flexibility. This review will provide a summary and detailed discussion on recent aptamer-based fluorescence biosensors for liver cancer diagnosis. Specifically, the review focuses on two promising detection strategies: (i) Förster resonance energy transfer (FRET) and (ii) metal-enhanced fluorescence for detecting and characterizing protein and miRNA cancer biomarkers.
A Label-Free Carbohydrate-Based Electrochemical Sensor to Detect Escherichia coli Pathogenic Bacteria Using D-mannose on a Glassy Carbon Electrode
Authors: Hargol Zadeh Sakineh , Kashanian Soheila , Nazari Maryam
Published: June 2023

Controlling water and food contamination by pathogenic organisms requires quick, simple, and low-cost methods. Using the affinity between mannose and type I fimbriae in the cell wall of Escherichia coli (E. coli) bacteria as evaluation elements compared to the conventional plate counting technique enables a reliable sensing platform for the detection of bacteria. In this study, a simple new sensor was developed based on electrochemical impedance spectroscopy (EIS) for rapid and sensitive detection of E. coli. The biorecogniton layer of the sensor was formed by covalent attachment of p-carboxyphenylamino mannose (PCAM) to gold nanoparticles (AuNPs) electrodeposited on the surface of a glassy carbon electrode (GCE). The resultant structure of PCAM was characterized and confirmed using a Fourier Transform Infrared Spectrometer (FTIR). The developed biosensor demonstrated a linear response with a logarithm of bacterial concentration (R2 = 0.998) in the range of 1.3 × 10 1~1.3 × 106 CFU·mL−1 with the limit of detection of 2 CFU·mL−1 within 60 min. The sensor did not generate any significant signals with two non-target strains, demonstrating the high selectivity of the developed biorecognition chemistry. The selectivity of the sensor and its applicability to analysis of the real samples were investigated in tap water and low-fat milk samples. Overall, the developed sensor showed to be promising for the detection of E. coli pathogens in water and low-fat milk due to its high sensitivity, short detection time, low cost, high specificity, and user-friendliness.
Molecularly Imprinted Polymer-Based Electrochemical Sensors for the Diagnosis of Infectious Diseases
Authors: Pilvenyte Greta , Ratautaite Vilma , Boguzaite Raimonda , Ramanavicius Simonas , Chen Chien-Fu , Viter Roman , Ramanavicius Arunas
Published: June 2023

The appearance of biological molecules, so-called biomarkers in body fluids at abnormal concentrations, is considered a good tool for detecting disease. Biomarkers are usually looked for in the most common body fluids, such as blood, nasopharyngeal fluids, urine, tears, sweat, etc. Even with significant advances in diagnostic technology, many patients with suspected infections receive empiric antimicrobial therapy rather than appropriate treatment, which is driven by rapid identification of the infectious agent, leading to increased antimicrobial resistance. To positively impact healthcare, new tests are needed that are pathogen-specific, easy to use, and produce results quickly. Molecularly imprinted polymer (MIP)-based biosensors can achieve these general goals and have enormous potential for disease detection. This article aimed to overview recent articles dedicated to electrochemical sensors modified with MIP to detect protein-based biomarkers of certain infectious diseases in human beings, particularly the biomarkers of infectious diseases, such as HIV-1, COVID-19, Dengue virus, and others. Some biomarkers, such as C-reactive protein (CRP) found in blood tests, are not specific for a particular disease but are used to identify any inflammation process in the body and are also under consideration in this review. Other biomarkers are specific to a particular disease, e.g., SARS-CoV-2-S spike glycoprotein. This article analyzes the development of electrochemical sensors using molecular imprinting technology and the used materials’ influence. The research methods, the application of different electrodes, the influence of the polymers, and the established detection limits are reviewed and compared.
A Novel Exploratory Graph-Based Analytical Tool for Functional Near-Infrared Spectroscopy in Naturalistic Experiments: An Illustrative Application in Typically Developing Children
Authors: Sato João Ricardo , Pereira Tiago Duarte , Martins Clarice Maria de Lucena , Bezerra Thaynã Alves , Queiroz Maria Eduarda , Costa Larissa Pereira , Andrade Suellen Marinho , Biazoli Claudinei Eduardo
Published: June 2023

Naturalistic paradigms are being increasingly applied to investigate human brain function. Compared with resting-state and task-based paradigms in neuroimaging, naturalistic stimuli and situations can be potentially more readily translated to daily-life applications. Among neuroimaging modalities, functional near-infrared spectroscopy (fNIRS) is particularly suitable for naturalistic investigations and applications. However, specific and tailored statistical analysis to interrogate brain function using naturalistic fNIRS is warranted. Here, we describe an exploratory graph-centrality-based approach to investigating participants’ spatiotemporal similarities from the fNIRS signal. We illustrate the usefulness of our approach in a sample of typically developing children (10 males and 9 females; mean age of 5.2 years old; sd = 0.78) while they watch the Inscapes movie designed for neuroimaging acquisition. A node in the left dorsal prefrontal cortex presented similar responses across children, and those fNIRS responses were in line with scene transitions in the movie stimulus. Our results suggest the feasibility of applying centrality graph-based measures to investigate brain function in naturalistic fNIRS during development.
The Temporal Relationship between Depressive Symptoms and Loneliness: The Moderating Role of Self-Compassion
Authors: Wang Shujian , Tang Qihui , Lv Yichao , Tao Yanqiang , Liu Xiangping , Zhang Liang , Liu Gang
Published: June 2023

Loneliness and depression are significant mental health challenges among college students; however, the intricate relationship between these phenomena remains unclear, particularly in the context of self-compassion. In this comprehensive study, we employ a cross-lagged panel network (CLPN) analysis to investigate the symptom-level association between depression and loneliness while exploring the potential moderating influence of self-compassion. Our sample consisted of 2785 college students, who were categorized into high- and low-self-compassion groups based on scores from the Self-Compassion Scale. Depressive symptoms were assessed using the Patient Health Questionnaire-9, while the UCLA Loneliness Scale-8 measured loneliness expressions. Our findings indicate that self-compassion plays a crucial role in the relationship between depression and loneliness. Specifically, we observed distinctive patterns within the high and low-self-compassion groups. In the low-self-compassion group, “energy” emerged as the most influential symptom, whereas “motor function” exhibited the highest influence in the high-self-compassion group. Furthermore, among individuals with high self-compassion, the pathway from depression to loneliness was characterized by “guilt—being alone when desired,” while the reverse path from loneliness to depression encompassed “left out—feeling sad” and “left out—anhedonia.” Conversely, in the low-self-compassion group, depression and loneliness demonstrated a more intricate mutual triggering relationship, suggesting that self-compassion effectively moderates the association between these variables. This study provides valuable insights into the underlying mechanisms driving the interplay between depression and loneliness, shedding light on the pivotal role of self-compassion in this intricate dynamic.
Building Adaptation Measures Using Future Climate Scenarios—A Scoping Review of Uncertainty Treatment and Communication
Authors: Gaarder Jørn Emil , Hygen Hans Olav , Bohne Rolf André , Kvande Tore
Published: June 2023

The global climate is changing. Predicting the impacts this will have on buildings is the first step in the process of finding suitable building adaptation measures. Future climate adaptation of buildings and infrastructure is a growing field of research, relying on both socio-economical and meteorological research for input values to the simulation models. Models producing hourly future weather data rely on global climate models which are based on emission scenarios made from assumptions of future political, social, and economic developments. Accounting for the uncertainties from these underlying models as much as possible, and communicating the uncertainties in the results, is obviously paramount for reliable conclusions from the building simulation models. This paper is a scoping review, investigating how 132 studies treat and communicate the string of uncertainties from underlying models connected to future weather file generation in the scientific literature on building adaptation research. The findings suggest that climate-model-induced uncertainties are often under-communicated, due to either insufficient analysis or neglect. The studies that included the most comprehensive analyses of the uncertainties frequently concluded that treatment of these is important for the reliability of the results, and neglecting this could lead to misleading conclusions.
Evaluating Risk in Prefabricated Building Construction under EPC Contracting Using Structural Equation Modeling: A Case Study of Shaanxi Province, China
Authors: Cao Ping , Lei Xiatong
Published: June 2023

Prefabricated buildings have the advantages of high efficiency and saving resources. However, China’s prefabricated buildings were built relatively late, and there are problems in terms of their low standardization, integration, and industrialization. The purpose of this study was to evaluate the risk of constructing prefabricated buildings under the engineering, procurement, and construction (EPC) general contracting mode from the perspective of general contractors and to propose countermeasures for the key risks. Firstly, a risk evaluation index system was established via a literature analysis, and a questionnaire survey was used to collect the data. SPSS was used to conduct the data factor analysis to finally identify 4 first-level indicators and 14 second-level indicators. Then, a structural equation model (SEM) was developed to further evaluate the impact of each indicator on the risk of constructing prefabricated buildings under the EPC general contracting mode. The results showed that the construction and design risk had the greatest impact. Among them, the technical level of the construction personnel while conducting the hoisting, stacking, and protection of on-site materials and the lack of integrated design experience among the designers were the key points for risk control. On the one hand, this study explored the whole life cycle of a project, which makes up for the lack of risk analyses and the control being limited to a single engineering stage that has been presented in previous studies. On the other hand, in terms of the design, procurement, and construction as a whole research object, we found that the fuzzy evaluation method and analytic hierarchy process (AHP) used in previous risk analyses and evaluation methods have defects. They cannot verify the rationality of the logical relationship between the evaluation indices. In contrast, this study used the SEM method to fill this research gap. This ensures the scientific nature of our research to the greatest extent. Additionally, we also found some problems with this type of research: the selection of the evaluation indicators and data collection vary with the region, project characteristics, project contracting mode, and risk management subject, which influence the results of studies. Overall, the SEM method established in this study provides a reference and can help us conduct similar research and model evaluations in other regions. This method can guide project implementers to make the best risk-management decisions, so it is of great significance for practitioners in this field.
Better Late Than Never: The Impact of Steroidal Treatment on the Outcome of Melanoma Patients Treated with Immunotherapy
Authors: Bar-Hai Neta , Ben-Betzalel Guy , Stoff Ronen , Grynberg Shirly , Schachter Jacob , Shapira-Frommer Ronnie , Asher Nethanel
Published: June 2023

Background: Successful treatment with Immune Checkpoint Inhibitors (ICI) requires the balanced activation of the immune system. Over-activation may result in immune-related adverse events (irAEs), which often require steroidal treatment. This study examined the possible impact of steroids on treatment efficacy in melanoma patients concerning initiation timing and dosage. Methods: A retrospective, single-center analysis of patients with advanced melanoma who underwent first-line ICI therapy during 2014–2020 was conducted. Results: Among the 415 patients, two-hundred patients (48.3%) were exposed to steroids during the first line, most of them due to irAEs (n = 169, 84.5%). Nearly a quarter of them were exposed to steroids within the first four weeks of treatment. Surprisingly, steroidal exposure was associated with better progression-free survival (PFS; HR = 0.74, p = 0.015); however, early exposure (within four weeks of treatment) resulted in a significantly shorter PFS compared to late exposure (adjusted HR 3.2, p < 0.001). Conclusions: Early exposure to corticosteroids during the priming phase of ICI therapy could impede the establishment of an effective immune response. These results suggest that caution should be exercised when considering the use of steroids for the management of early-onset irAEs.
Analyses of Genes Critical to Tumor Survival Reveal Potential ‘Supertargets’: Focus on Transcription
Authors: Chetverina Darya , Vorobyeva Nadezhda E. , Gyorffy Balazs , Shtil Alexander A. , Erokhin Maksim
Published: June 2023

The identification of mechanisms that underlie the biology of individual tumors is aimed at the development of personalized treatment strategies. Herein, we performed a comprehensive search of genes (termed Supertargets) vital for tumors of particular tissue origin. In so doing, we used the DepMap database portal that encompasses a broad panel of cell lines with individual genes knocked out by CRISPR/Cas9 technology. For each of the 27 tumor types, we revealed the top five genes whose deletion was lethal in the particular case, indicating both known and unknown Supertargets. Most importantly, the majority of Supertargets (41%) were represented by DNA-binding transcription factors. RNAseq data analysis demonstrated that a subset of Supertargets was deregulated in clinical tumor samples but not in the respective non-malignant tissues. These results point to transcriptional mechanisms as key regulators of cell survival in specific tumors. Targeted inactivation of these factors emerges as a straightforward approach to optimize therapeutic regimens.
SAM-Competitive EZH2-Inhibitors Induce Platinum Resistance by EZH2-Independent Induction of ABC-Transporters
Authors: Groß Elisabeth , Hilger Ralf-Axel , Schümann Franziska Lea , Bauer Marcus , Bouska Alyssa , Rohde Christian , Willscher Edith , Lützkendorf Jana , Müller Lutz Peter , Edemir Bayram , Mueller Thomas , Herling Marco , Binder Mascha , Wickenhauser Claudia , Iqbal Javeed , Posern Guido , Weber Thomas
Published: June 2023

T-cell lymphomas are heterogeneous and rare lymphatic malignancies with unfavorable prognosis. Consequently, new therapeutic strategies are needed. The enhancer of zeste homologue 2 (EZH2) is the catalytic subunit of the polycomb repressive complex 2 and responsible for lysine 27 trimethylation of histone 3. EZH2 is overexpressed in several tumor entities including T-cell neoplasms leading to epigenetic and consecutive oncogenic dysregulation. Thus, pharmacological EZH2 inhibition is a promising target and its clinical evaluation in T-cell lymphomas shows favorable results. We have investigated EZH2 expression in two cohorts of T-cell lymphomas by mRNA-profiling and immunohistochemistry, both revealing overexpression to have a negative impact on patients’ prognosis. Furthermore, we have evaluated EZH2 inhibition in a panel of leukemia and lymphoma cell lines with a focus on T-cell lymphomas characterized for canonical EZH2 signaling components. The cell lines were treated with the inhibitors GSK126 or EPZ6438 that inhibit EZH2 specifically by competitive binding at the S-adenosylmethionine (SAM) binding site in combination with the common second-line chemotherapeutic oxaliplatin. The change in cytotoxic effects under pharmacological EZH2 inhibition was evaluated revealing a drastic increase in oxaliplatin resistance after 72 h and longer periods of combinational incubation. This outcome was independent of cell type but associated to reduced intracellular platinum. Pharmacological EZH2 inhibition revealed increased expression in SRE binding proteins, SREBP1/2 and ATP binding cassette subfamily G transporters ABCG1/2. The latter are associated with chemotherapy resistance due to increased platinum efflux. Knockdown experiments revealed that this was independent of the EZH2 functional state. The EZH2 inhibition effect on oxaliplatin resistance and efflux was reduced by additional inhibition of the regulated target proteins. In conclusion, pharmacological EZH2 inhibition is not suitable in combination with the common chemotherapeutic oxaliplatin in T-cell lymphomas revealing an EZH2-independent off-target effect.
Long-Chain Acyl Coenzyme A Dehydrogenase, a Key Player in Metabolic Rewiring/Invasiveness in Experimental Tumors and Human Mesothelioma Cell Lines
Authors: Pouliquen Daniel , Ortone Giacomo , Rumiano Letizia , Boissard Alice , Henry Cécile , Blandin Stéphanie , Guette Catherine , Riganti Chiara , Kopecka Joanna
Published: June 2023

Cross-species investigations of cancer invasiveness are a new approach that has already identified new biomarkers which are potentially useful for improving tumor diagnosis and prognosis in clinical medicine and veterinary science. In this study, we combined proteomic analysis of four experimental rat malignant mesothelioma (MM) tumors with analysis of ten patient-derived cell lines to identify common features associated with mitochondrial proteome rewiring. A comparison of significant abundance changes between invasive and non-invasive rat tumors gave a list of 433 proteins, including 26 proteins reported to be exclusively located in mitochondria. Next, we analyzed the differential expression of genes encoding the mitochondrial proteins of interest in five primary epithelioid and five primary sarcomatoid human MM cell lines; the most impressive increase was observed in the expression of the long-chain acyl coenzyme A dehydrogenase (ACADL). To evaluate the role of this enzyme in migration/invasiveness, two epithelioid and two sarcomatoid human MM cell lines derived from patients with the highest and lowest overall survival were studied. Interestingly, sarcomatoid vs. epithelioid cell lines were characterized by higher migration and fatty oxidation rates, in agreement with ACADL findings. These results suggest that evaluating mitochondrial proteins in MM specimens might identify tumors with higher invasiveness. Data are available via ProteomeXchange with the dataset identifier PXD042942.
Follicular Helper and Regulatory T Cells Drive the Development of Spontaneous Epstein–Barr Virus Lymphoproliferative Disorder
Authors: Ahmed Elshafa Hassan , Lustberg Mark , Hale Claire , Sloan Shelby , Mao Charlene , Zhang Xiaoli , Ozer Hatice Gulcin , Schlotter Sarah , Smith Porsha L. , Jeney Frankie , Chan Wing Keung , Harrington Bonnie K. , Weigel Christoph , Brooks Eric , Klimaszewski Haley L. , Oakes Christopher C. , Abebe Tamrat , Ibrahim Muntaser E. , Alinari Lapo , Behbehani Gregory K. , Shindiapina Polina , Caligiuri Michael A. , Baiocchi Robert A.
Published: June 2023

Epstein–Barr virus (EBV) is a ubiquitous herpes virus associated with various cancers. EBV establishes latency with life-long persistence in memory B-cells and can reactivate lytic infection placing immunocompromised individuals at risk for EBV-driven lymphoproliferative disorders (EBV-LPD). Despite the ubiquity of EBV, only a small percentage of immunocompromised patients (~20%) develop EBV-LPD. Engraftment of immunodeficient mice with peripheral blood mononuclear cells (PBMCs) from healthy EBV-seropositive donors leads to spontaneous, malignant, human B-cell EBV-LPD. Only about 20% of EBV+ donors induce EBV-LPD in 100% of engrafted mice (High-Incidence, HI), while another 20% of donors never generate EBV-LPD (No-Incidence, NI). Here, we report HI donors to have significantly higher basal T follicular helper (Tfh) and regulatory T-cells (Treg), and depletion of these subsets prevents/delays EBV-LPD. Transcriptomic analysis of CD4+ T cells from ex vivo HI donor PBMC revealed amplified cytokine and inflammatory gene signatures. HI vs. NI donors showed a marked reduction in IFNγ production to EBV latent and lytic antigen stimulation. In addition, we observed abundant myeloid-derived suppressor cells in HI donor PBMC that decreased CTL proliferation in co-cultures with autologous EBV+ lymphoblasts. Our findings identify potential biomarkers that may identify individuals at risk for EBV-LPD and suggest possible strategies for prevention.
Third-Line Palliative Systemic Therapy for Advanced Biliary Tract Cancer: Multicentre Review of Patterns of Care and Outcomes
Authors: Gray Simon , Letissier Octave , d’Abrigeon Constance , Shah Dinakshi , Wardell Stephen , Faluyi Olusola , Lamarca Angela , Hubner Richard A. , Edeline Julien , Valle Juan W. , McNamara Mairéad G.
Published: June 2023

Phase 3 trials have established standard first-line (1L) and 2L systemic therapy options for patients with advanced biliary cancer (ABC). However, a standard 3L treatment remains undefined. Clinical practice and outcomes for 3L systemic therapy in patients with ABC were therefore evaluated from three academic centres. Included patients were identified using institutional registries; demographics, staging, treatment history, and clinical outcomes were collected. Kaplan–Meier methods were used to assess progression-free survival (PFS) and overall survival (OS). Ninety-seven patients, treated between 2006 and 2022, were included; 61.9% had intrahepatic cholangiocarcinoma. At the time of analysis, there had been 91 deaths. Median PFS from initiating 3L palliative systemic therapy (mPFS3) was 3.1 months (95%CI 2.0–4.1), while mOS3 was 6.4 months (95%CI 5.5–7.3); mOS1 was 26.9 months (95%CI 23.6–30.2). Among patients with a therapy-targeted molecular aberration (10.3%; n = 10; all received in 3L), mOS3 was significantly improved versus all other included patients (12.5 vs. 5.9 months; p = 0.02). No differences in OS1 were demonstrated between anatomical subtypes. Fourth-line systemic therapy was received by 19.6% of patients (n = 19). This international multicentre analysis documents systemic therapy use in this select patient group, and provides a benchmark of outcomes for future trial design.