bluuebunny/crossref_metadata_2025 huggingface dataset:
Electromagnetic Imaging of Uniaxial Objects by Two-Step Neural Network
Authors: Chien Wei , Chiu Chien-Ching , Chen Po-Hsiang , Wu Hung-Yu , Lim Eng Hock
Published: June 2024

The integration of electromagnetic imaging technology with the Internet of Things plays an important role in fields as diverse as healthcare, geophysics, and industrial diagnostics. This paper presents a novel two-step neural network architecture to solve the electromagnetic imaging for uniaxial objects which can be used in the Internet of Things. We incident TM and TE waves to unknown objects and receive the scattered fields. In order to reduce the training difficulty, we first input the gathered scattered field information into a deep convolutional neural network (DCNN) to obtain the preliminary guess. In the second step, we feed the guessed image into the convolutional neural network (CNN) to reconstruct high-resolution images. Our numerical results demonstrate the real-time imaging capability of our proposed two-step method in reconstructing high-contrast scatterers.
Experimental Investigation of a H2O2 Hybrid Rocket with Different Swirl Injections and Fuels
Authors: Stella Manuel , Zeni Lucia , Nichelini Luca , Bellomo Nicolas , Pavarin Daniele , Migliorino Mario Tindaro , Fabiani Marco , Bianchi Daniele , Nasuti Francesco , Paravan Christian , Galfetti Luciano , Cretella Attilio , Pellegrini Rocco Carmine , Cavallini Enrico , Barato Francesco
Published: June 2024

Hybrid rockets have very interesting characteristics like simplicity, reliability, safety, thrust modulation, environmental friendliness and lower costs, which make them very attractive for several applications like sounding rockets, small launch vehicles, upper stages, hypersonic test-beds and planetary landers. In recent years, advancements have been made to increase hybrid motor performance, and two of the most promising solutions are vortex injection and paraffin-based fuels. Moreover, both technologies can be also used to tailor the fuel regression rate, in the first case varying the swirl intensity, and in the second case with the amount and type of additives. In this way, it is possible not only to design high-performing hybrid motors, but also to adjust their grain and chamber geometries to different mission requirements, particularly regarding thrust and burning time. In this paper, the knowledge about these two technical solutions and their coupling is extended. Three sets of experimental campaigns were performed in the frame of the Italian Space Agency-sponsored PHAEDRA program. The first one investigated a reference paraffin fuel with axial and standard vortex injection. The second campaign tested vortex injection with low values of swirl numbers down to 0.5 with a conventional plastic fuel, namely polyethylene. Finally, the last campaign tested another, lower regressing, paraffin-based fuel with the same low swirl numbers as the second campaign.
Radiological Reporting Systems in Multiple Sclerosis
Authors: Scaravilli Alessandra , Tranfa Mario , Pontillo Giuseppe , Carotenuto Antonio , Lapucci Caterina , Nistri Riccardo , Signoriello Elisabetta , Moccia Marcello , Tortorella Carla , Capra Ruggero , Lus Giacomo , Inglese Matilde , Gasperini Claudio , Lanzillo Roberta , Pozzilli Carlo , Brescia Morra Vincenzo , Brunetti Arturo , Petracca Maria , Cocozza Sirio
Published: June 2024

(1) Background: Although MRI is a well-established tool in Multiple Sclerosis (MS) diagnosis and management, neuroradiological reports often lack standardization and/or quantitative information, with possible consequences in clinical care. The aim of this study was to evaluate the impact of information provided by neuroradiological reports and different reporting systems on the clinical management of MS patients. (2) Methods: An online questionnaire was proposed to neurologists working in Italian tertiary care level MS centers. Questions assessed the impact of different MRI-derived biomarkers on clinical choices, the preferred way of receiving radiological information, and the neurologists’ opinions about different reporting systems and the use of automated software in clinical practice. (3) Results: The online survey was completed by 62 neurologists. New/enlarging (100%) lesions, the global T2w/FLAIR lesion load (96.8%), and contrast-enhancing (95.2%) lesions were considered the most important biomarkers for therapeutic decision, while new/enlarging lesions (98.4%), global T2w/FLAIR lesion load (96.8%), and cerebral atrophy (90.3%) were relevant to prognostic evaluations. Almost all participants (98.4%) considered software for medical imaging quantification helpful in clinical management, mostly in relation to prognostic evaluations. (4) Conclusions: These data highlight the impact of providing accurate and reliable data in neuroradiological reports. The use of software for medical imaging quantification in MS can be helpful to standardize radiological reports and to provide useful clinical information to neurologists.
Improved Adaptive Feedforward Controller Based on Internal Model Principle with Disturbance Observer for Laser-Beam Steering Systems
Authors: Kim Jung-Gon
Published: June 2024

This study presents an effective control algorithm to improve the robustness of fast steering mirror (FSM)-based laser-beam steering systems against dynamic disturbances, such as repetitive disturbances resulting from operating conditions. A stable control system must be able to maintain the required high-precision control, even when dynamic disturbances affect the FSM system. In this study, an improved control method is proposed using an internal model principle (IMP)-based nonlinear controller with a disturbance observer (DOB) for the FSM system. This IMP-based controller with DOB can attenuate the residual control-error signal under dynamic disturbance conditions.
Precise Mission Process Control Based on a Novel Dual-Code Group Network Plan Diagram
Authors: Wu Ao , Xie Xiaowei , Song Qi , Wang Ying , Li Huanyu , Yang Rennong
Published: June 2024

Different from an ordinary project, a large group mission like the unmanned aerial vehicle (UAV) swarm cooperative strike mission is performed by multiple executors and needs to be strictly carried out according to the plan. Because of the complex cooperative relationships between the sub-missions that make up a large mission, a small disturbance may cause a delay in the entire plan. Therefore, the mission process must be precisely controlled in real time to resist disturbances and ensure that the mission proceeds as planned. To address the real-time process control problem of large group missions, we propose a novel dual-code group network plan diagram model that enables plan description and process tracking for complex group missions. Additionally, a mission process closed-loop feedback control system is designed that models the mission process control problem as a mapping from the mission state observation to plan adjustment. Furthermore, an analytic-based mission process control strategy is proposed and rigorously proven to converge and be effective, as well as demonstrate the maximum anti-disturbance capability. Finally, the control strategy is tested on a UAV swarm cooperative strike mission containing 56 sub-missions. The simulation results demonstrate that the proposed control strategy is capable of achieving high, fast, and accurate control for the mission process and enhancing the anti-disturbance capability of the plan by adjusting the mission plan in real time. This will provide a valuable reference for the management of large group missions.
Impact of Biomass Burning, Wildfires, and Wind Events on Aerosol Optical Depth: Implications for Climate Change
Authors: Zielinski Tymon , Willems Amandine , Lartigaud Mathilde
Published: June 2024

In this article, we describe multiannual variations of the atmospheric aerosol optical depth values in the widely understood area of the Baltic Sea. We present the trends in the changes and depict unusual aerosol situations. As a result of analyses, we focus on 2019, since unusually high values of aerosol optical depth were recorded in several stations around the Baltic. We match the high aerosol levels with an unusually high number of wildfires across Europe in spring and summer, which emitted large quantities of aerosols into the atmosphere that were distributed over vast European areas in part by the wind. We then connect this case with the climate change consequences. Since aerosols influence the radiative budget of the planet by directly affecting the atmospheric radiation budget, it is obvious that human well-being is in danger due to wildfires, as well as from the atmospheric perspective. Climate change will lead to more frequent fires; thus, humans need to develop solutions to decrease the risk of fire outbreaks.
Exploring the Spatial Variability of Air Pollution Using Mobile BC Measurements in a Citizen Science Project: A Case Study in Mechelen
Authors: Van Poppel Martine , Peters Jan , Vranckx Stijn , Van Laer Jo , Hofman Jelle , Vandeninden Bram , Vanpoucke Charlotte , Lefebvre Wouter
Published: June 2024

Mobile monitoring is used as an additional tool to collect air quality data at a high spatial resolution and to complement data from fixed air quality stations. Citizens are interested in contributing to air quality monitoring, and while the availability of low-cost air quality sensors can create opportunities to measure the air quality at a high spatial resolution, the data are often of lower quality, and sensors that measure combustion-related aerosols (like black carbon) are not commonly available. Mobile monitoring using a mid-range instrument can fill this gap. We present the results of a mobile BC (black carbon) monitoring campaign performed by citizens in Mechelen as part of a local citizen observatory (CO), Meet Mee Mechelen, initiated as part of the European H2020 project, Ground Truth 2.0. The goal of the study was two-fold: (1) to propose and evaluate a mobile monitoring method (data collection and data processing) to construct pollution maps of BC concentrations and (2) to demonstrate how to organize community-based air quality monitoring to measure both the spatial and temporal variations in air pollution levels. Measurements were taken during peak hours in four campaigns characterized by different meteorological conditions: October–November 2017, February–March 2018, June–July 2018 and September 2018. The results show large spatial and temporal variabilities. Spatial variability is influenced by traffic volume, stop-and-go traffic and also the building environment and the distance of biking paths from road traffic. The four different campaigns show similar spatial patterns, but due to background and meteorological influences, the absolute concentrations differ between seasons. A rescaling method using data from fixed stations in the air quality monitoring network (AQMN) was presented to construct maps representative of longer periods. This paper shows that mobile measurements can be used by CO to assess the spatial variability of air quality in a city. The data can be used to evaluate mobility plans, carry out hot spot detection, evaluate the exposure of cyclists as a function of cycling infrastructure and perform model validation. However, it is important to use high-quality instruments and apply the correct measurement methodology (number of repetitions, season) to obtain meaningful data.
Deep Learning for Flash Drought Detection: A Case Study in Northeastern Brazil
Authors: Barbosa Humberto A. , Buriti Catarina O. , Kumar T. V. Lakshmi
Published: June 2024

Flash droughts (FDs) pose significant challenges for accurate detection due to their short duration. Conventional drought monitoring methods have difficultly capturing this rapidly intensifying phenomenon accurately. Machine learning models are increasingly useful for detecting droughts after training the models with data. Northeastern Brazil (NEB) has been a hot spot for FD events with significant ecological damage in recent years. This research introduces a novel 2D convolutional neural network (CNN) designed to identify spatial FDs in historical simulations based on multiple environmental factors and thresholds as inputs. Our model, trained with hydro-climatic data, provides a probabilistic drought detection map across northeastern Brazil (NEB) in 2012 as its output. Additionally, we examine future changes in FDs using the Coupled Model Intercomparison Project Phase 6 (CMIP6) driven by outputs from Shared Socioeconomic Pathways (SSPs) under the SSP5-8.5 scenario of 2024–2050. Our results demonstrate that the proposed spatial FD-detecting model based on 2D CNN architecture and the methodology for robust learning show promise for regional comprehensive FD monitoring. Finally, considerable spatial variability of FDs across NEB was observed during 2012 and 2024–2050, which was particularly evident in the São Francisco River Basin. This research significantly contributes to advancing our understanding of flash droughts, offering critical insights for informed water resource management and bolstering resilience against the impacts of flash droughts.
Critical Drought Characteristics: A New Concept Based on Dynamic Time Period Scenarios
Authors: Abu Arra Ahmad , Birpınar Mehmet Emin , Gazioğlu Şükrü Ayhan , Şişman Eyüp
Published: June 2024

In research on monitoring drought events, analysis is often carried out using a single period as a reference. On the other hand, changing this default period in drought calculations causes the drought index values obtained from research to differ. As a gap in the literature, this point highlights the necessity of investigating the effect of various time periods on drought characteristics. It underscores the need to propose a new concept and methodology to address this gap effectively. This research aims to analyze critical drought characteristics through dynamic time period scenarios. For the first time in the literature, drought indices and potential and critical characteristics were analyzed for various (dynamic) time periods. Drought analysis was carried out for 13 time period scenarios with 10-year intervals from a meteorological station in Durham (1872–2021) by changing the initial time condition using the Standardized Precipitation Index (SPI). The results showed that in addition to the similarities, there are significant differences between drought characteristics. For example, in some time period scenarios, a drought event was recorded during a specific period, while in other scenarios (S5–S7, S10–S13), no drought was detected during the same period, like in SPI 1. Additionally, for SPI 12, the drought duration varied significantly, lasting between 20 and 29 months, and for SPI 6, the drought duration varied between 3 and 13 months. Regarding the intensity, SPI 1 ranged between −0.89 and −1.33, indicating a 33% difference, and the SPI 3 intensity ranged between −1.08 and −1.91, indicating a 50% increase in intensity. This research significantly contributes to the field by providing a novel approach using dynamic time period scenarios to determine critical drought characteristics, offering valuable insights for water resource management, drought mitigation planning, and design purposes.
Harmonic Series with Multinomial Coefficient 4nn,n,n,n and Central Binomial Coefficient 2nn
Authors: Li Chunli , Chu Wenchang
Published: June 2024

Classical hypergeometric series are reformulated as analytic functions of their parameters (in both the numerator and the denominator). Then, the coefficient extraction method is applied to examine hypergeometric series transformations. Several new closed form evaluations are established for harmonic series containing multinomial coefficient 4nn,n,n,n and central binomial coefficient 2nn. These results exclusively concern the alternating series of convergence rate “−1/4”.
The Existence and Representation of the Solutions to the System of Operator Equations AiXBi + CiYDi + EiZFi = Gi(i = 1, 2)
Authors: Che Gen , Hai Guojun , Mei Jiarui , Cao Xiang
Published: June 2024

In this paper, we give the necessary and sufficient conditions for the existence of general solutions, self-adjoint solutions, and positive solutions to the system of AiXBi+CiYDi+EiZFi=Gi(i=1,2) under additional conditions. In addition, we derive the representation of general solutions to the system of AiXBi+CiYDi+EiZFi=Gi(i=1,2), and provide the matrix representation of the self-adjoint solutions and the positive solutions in the sense of the star order.
ReJOOSp: Reinforcement Learning for Join Order Optimization in SPARQL
Authors: Warnke Benjamin , Martens Kevin , Winker Tobias , Groppe Sven , Groppe Jinghua , Adhiyaman Prasad , Srinivasan Sruthi , Krishnakumar Shridevi
Published: June 2024

The choice of a good join order plays an important role in the query performance of databases. However, determining the best join order is known to be an NP-hard problem with exponential growth with the number of joins. Because of this, nonlearning approaches to join order optimization have a longer optimization and execution time. In comparison, the models of machine learning, once trained, can construct optimized query plans very quickly. Several efforts have applied machine learning to optimize join order for SQL queries outperforming traditional approaches. In this work, we suggest a reinforcement learning technique for join optimization for SPARQL queries, ReJOOSp. SPARQL queries typically contain a much higher number of joins than SQL queries and so are more difficult to optimize. To evaluate ReJOOSp, we further develop a join order optimizer based on ReJOOSp and integrate it into the Semantic Web DBMS Luposdate3000. The evaluation of ReJOOSp shows its capability to significantly enhance query performance by achieving high-quality execution plans for a substantial portion of queries across synthetic and real-world datasets.
Transcriptome-Based Analysis of the Mechanism of Action of Metabolic Disorders Induced by Waterborne Copper Stress in Coilia nasus
Authors: Huang Dongyu , Zhang Lu , Mi Haifeng , Teng Tao , Liang Hualiang , Ren Mingchun
Published: June 2024

To reveal the effects of waterborne copper stress on gene expression changes, molecular pathways, and physiological functions in Coilia nasus, juvenile fish were equally divided into two experimental groups, and the copper levels were 1.61 ± 0.03 mg/L (copper-exposed group) and 0 mg/L (control group), respectively. After 4 h, gill tissue samples were collected for transcript sequencing analysis, and two libraries were constructed from the copper treatment group (Cu) and the control group (C) and sequenced using Illumina sequencing technology. The results showed that approximately 40.2–46.0 M clean reads were obtained from each library, and the percentage of uniquely mapped transcripts ranged from 80.57 to 84.93%. A total of 3915 differentially expressed genes (DEGs) were identified under waterborne copper stress, among which 1300 genes were up-regulated, and 2615 genes were down-regulated. Twelve DEGs were randomly selected for quantitative RT-PCR (qRT-PCR) analysis, and the results confirmed that the transcriptome analysis was reliable. Furthermore, the DEGs were subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, and the results showed that most of the DEGs were involved in metabolic pathways, including steroid biosynthesis, glutathione metabolism, and peroxisome proliferator-activated receptor (PPAR) signaling pathways. Furthermore, due to the waterborne copper levels, gsk-3β was significantly up-regulated, while other metabolism-related genes (tor, pi3k, lpl, aqp7, fabp3) were significantly down-regulated. In addition, the copper-exposed group significantly reduced the expression of some immunity genes (ifn-γ, stat1, cxcl10, and tgf-β), and enhanced the expression of il-1β and tnf-α. In summary, these results indicated that copper causes metabolic disorders and insufficient energy supply in the body, and induces oxidative stress, which results in reduced immune functions.
The Chromosome-Scale Genome of Chitala ornata Illuminates the Evolution of Early Teleosts
Authors: Yuan Zengbao , Song Yue , Zhang Suyu , Chen Yadong , Xu Mengyang , Fan Guangyi , Liu Xin
Published: June 2024

Teleosts are the most prolific vertebrates, occupying the vast majority of aquatic environments, and their pectoral fins have undergone remarkable physiological transformations throughout their evolution. Studying early teleost fishes, such as those belonging to the Osteoglossiformes order, could offer crucial insights into the adaptive evolution of pectoral fins within this group. In this study, we have assembled a chromosomal-level genome for the Clown featherback (Chitala ornata), achieving the highest quality genome assembly for Osteoglossiformes to date, with a contig N50 of 32.78 Mb and a scaffold N50 of 40.73 Mb. By combining phylogenetic analysis, we determined that the Clown featherback diverged approximately 202 to 203 million years ago (Ma), aligning with continental separation events. Our analysis revealed the intriguing discovery that a unique deletion of regulatory elements is adjacent to the Gli3 gene, specifically in teleosts. This deletion might be tied to the specialized adaptation of their pectoral fins. Furthermore, our findings indicate that specific contractions and expansions of transposable elements (TEs) in teleosts, including the Clown featherback, could be connected to their adaptive evolution. In essence, this study not only provides a high-quality genomic resource for Osteoglossiformes but also sheds light on the evolutionary trajectory of early teleosts.
Predicting Climate Change Impact on the Habitat Suitability of the Schistosoma Intermediate Host Oncomelania hupensis in the Yangtze River Economic Belt of China
Authors: Li Yimiao , Guo Mingjia , Jiang Jie , Dai Renlong , Rebi Ansa , Shi Zixuan , Mao Aoping , Zheng Jingming , Zhou Jinxing
Published: June 2024

Oncomelania hupensis is the exclusive intermediary host of Schistosoma japonicum in China. The alteration of O. hupensis habitat and population distribution directly affects the safety of millions of individuals residing in the Yangtze River Economic Belt (YREB) and the ecological stability of Yangtze River Basin. Therefore, it is crucial to analyze the influence of climate change on the distribution of O. hupensis in order to achieve accurate control over its population. This study utilized the MaxEnt model to forecast possible snail habitats by utilizing snail distribution data obtained from historical literature. The following outcomes were achieved: The primary ecological factors influencing the distribution of O. hupensis are elevation, minimum temperature of the coldest month, and precipitation of wettest month. Furthermore, future climate scenarios indicate a decrease in the distribution area and a northward shift of the distribution center for O. hupensis; specifically, those in the upstream will move northeast, while those in the midstream and downstream will move northwest. These changes in suitable habitat area, the average migration distance of distribution centers across different climate scenarios, time periods, and sub-basins within the YREB, result in uncertainty. This study offers theoretical justification for the prevention and control of O. hupensis along the YREB.
Enhanced ε-Poly-L-Lysine Production in Streptomyces albulus through Multi-Omics-Guided Metabolic Engineering
Authors: Wang Liang , Yang Hao , Wu Mengping , Zhang Hongjian , Zhang Jianhua , Chen Xusheng
Published: June 2024

Safe and eco-friendly preservatives are crucial to preventing food spoilage and illnesses, as foodborne diseases caused by pathogens result in approximately 600 million cases of illness and 420,000 deaths annually. ε-Poly-L-lysine (ε-PL) is a novel food preservative widely used in many countries. However, its commercial application has been hindered by high costs and low production. In this study, ε-PL’s biosynthetic capacity was enhanced in Streptomyces albulus WG608 through metabolic engineering guided by multi-omics techniques. Based on transcriptome and metabolome data, differentially expressed genes (fold change >2 or <0.5; p < 0.05) and differentially expressed metabolites (fold change >1.2 or <0.8) were separately subjected to gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The integrative analysis of transcriptome, metabolome, and overexpression revealed the essential roles of isocitrate lyase, succinate dehydrogenase, flavoprotein subunit, diaminopimelate dehydrogenase, polyphosphate kinase, and polyP:AMP phosphotransferase in ε-PL biosynthesis. Subsequently, a strain with enhanced ATP supply, L-lysine supply, and ε-PL synthetase expression was constructed to improve its production. Finally, the resulting strain, S. albulus WME10, achieved an ε-PL production rate of 77.16 g/L in a 5 L bioreactor, which is the highest reported ε-PL production to date. These results suggest that the integrative analysis of the transcriptome and metabolome can facilitate the identification of key pathways and genetic elements affecting ε-PL synthesis, guiding further metabolic engineering and thus significantly enhancing ε-PL production. The method presented in this study could be applicable to other valuable natural antibacterial agents.
FLASH Radiotherapy: Mechanisms of Biological Effects and the Therapeutic Potential in Cancer
Authors: Yan Ouying , Wang Shang , Wang Qiaoli , Wang Xin
Published: June 2024

Radiotherapy is an important treatment for many unresectable advanced malignant tumors, and radiotherapy-associated inflammatory reactions to radiation and other toxic side effects are significant reasons which reduce the quality of life and survival of patients. FLASH-radiotherapy (FLASH-RT), a prominent topic in recent radiation therapy research, is an ultra-high dose rate treatment known for significantly reducing therapy time while effectively targeting tumors. This approach minimizes radiation side effects on at-risk organs and maximally protects surrounding healthy tissues. Despite decades of preclinical exploration and some notable achievements, the mechanisms behind FLASH effects remain debated. Standardization is still required for the type of FLASH-RT rays and dose patterns. This review addresses the current state of FLASH-RT research, summarizing the biological mechanisms behind the FLASH effect. Additionally, it examines the impact of FLASH-RT on immune cells, cytokines, and the tumor immune microenvironment. Lastly, this review will discuss beam characteristics, potential clinical applications, and the relevance and applicability of FLASH-RT in treating advanced cancers.
In Silico Comparative Analysis of Ivermectin and Nirmatrelvir Inhibitors Interacting with the SARS-CoV-2 Main Protease
Authors: de Oliveira Só Yuri Alves , Bezerra Katyanna Sales , Gargano Ricardo , Mendonça Fabio L. L. , Souto Janeusa Trindade , Fulco Umberto L. , Pereira Junior Marcelo Lopes , Junior Luiz Antônio Ribeiro
Published: June 2024

Exploring therapeutic options is crucial in the ongoing COVID-19 pandemic caused by SARS-CoV-2. Nirmatrelvir, which is a potent inhibitor that targets the SARS-CoV-2 Mpro, shows promise as an antiviral treatment. Additionally, Ivermectin, which is a broad-spectrum antiparasitic drug, has demonstrated effectiveness against the virus in laboratory settings. However, its clinical implications are still debated. Using computational methods, such as molecular docking and 100 ns molecular dynamics simulations, we investigated how Nirmatrelvir and Ivermectin interacted with SARS-CoV-2 Mpro(A). Calculations using density functional theory were instrumental in elucidating the behavior of isolated molecules, primarily by analyzing the frontier molecular orbitals. Our analysis revealed distinct binding patterns: Nirmatrelvir formed strong interactions with amino acids, like MET49, MET165, HIS41, HIS163, HIS164, PHE140, CYS145, GLU166, and ASN142, showing stable binding, with a root-mean-square deviation (RMSD) of around 2.0 Å. On the other hand, Ivermectin interacted with THR237, THR239, LEU271, LEU272, and LEU287, displaying an RMSD of 1.87 Å, indicating enduring interactions. Both ligands stabilized Mpro(A), with Ivermectin showing stability and persistent interactions despite forming fewer hydrogen bonds. These findings offer detailed insights into how Nirmatrelvir and Ivermectin bind to the SARS-CoV-2 main protease, providing valuable information for potential therapeutic strategies against COVID-19.
Evaluation of the Effect of β-Wrapin AS69 in a Mouse Model Based on Alpha-Synuclein Overexpression
Authors: Höfs Lennart , Geißler-Lösch David , Wunderlich Kristof M. , Szegö Eva M. , Van den Haute Chris , Baekelandt Veerle , Hoyer Wolfgang , Falkenburger Björn H.
Published: June 2024

Aggregation of the protein α-Synuclein (αSyn) is a hallmark of Parkinson’s disease (PD), dementia with Lewy bodies (DLB) and multiple systems atrophy, and alleviating the extent of αSyn pathology is an attractive strategy against neurodegeneration. The engineered binding protein β-wrapin AS69 binds monomeric αSyn. AS69 reduces primary and secondary nucleation as well as fibril elongation in vitro. It also mitigates aSyn pathology in a mouse model based on intrastriatal injection of aSyn pre-formed fibrils (PFFs). Since the PFF-based model does not represent all aspects of PD, we tested here whether AS69 can reduce neurodegeneration resulting from αSyn overexpression. Human A53T-αSyn was overexpressed in the mouse Substantia nigra (SN) by using recombinant adeno-associated viral vector (rAAV). AS69 was also expressed by rAAV transduction. Behavioral tests and immunofluorescence staining were used as outcomes. Transduction with rAAV-αSyn resulted in αSyn pathology as reported by phospho-αSyn staining and caused degeneration of dopaminergic neurons in the SN. The co-expression of rAAV-AS69 did not reduce αSyn pathology or the degeneration of dopaminergic neurons. We conclude that αSyn monomer binding by rAAV-AS69 was insufficient to protect from aSyn pathology resulting from αSyn overexpression.
Structural Analysis of the Drosophila melanogaster GSTome
Authors: Petiot Nicolas , Schwartz Mathieu , Delarue Patrice , Senet Patrick , Neiers Fabrice , Nicolaï Adrien
Published: June 2024

Glutathione transferase (GST) is a superfamily of ubiquitous enzymes, multigenic in numerous organisms and which generally present homodimeric structures. GSTs are involved in numerous biological functions such as chemical detoxification as well as chemoperception in mammals and insects. GSTs catalyze the conjugation of their cofactor, reduced glutathione (GSH), to xenobiotic electrophilic centers. To achieve this catalytic function, GSTs are comprised of a ligand binding site and a GSH binding site per subunit, which is very specific and highly conserved; the hydrophobic substrate binding site enables the binding of diverse substrates. In this work, we focus our interest in a model organism, the fruit fly Drosophila melanogaster (D. mel), which comprises 42 GST sequences distributed in six classes and composing its GSTome. The goal of this study is to describe the complete structural GSTome of D. mel to determine how changes in the amino acid sequence modify the structural characteristics of GST, particularly in the GSH binding sites and in the dimerization interface. First, we predicted the 3D atomic structures of each GST using the AlphaFold (AF) program and compared them with X-ray crystallography structures, when they exist. We also characterized and compared their global and local folds. Second, we used multiple sequence alignment coupled with AF-predicted structures to characterize the relationship between the conservation of amino acids in the sequence and their structural features. Finally, we applied normal mode analysis to estimate thermal B-factors of all GST structures of D. mel. Particularly, we extracted flexibility profiles of GST and identify key residues and motifs that are systematically involved in the ligand binding/dimerization processes and thus playing a crucial role in the catalytic function. This methodology will be extended to guide the in silico design of synthetic GST with new/optimal catalytic properties for detoxification applications.
Histamine H3 Receptor Isoforms: Insights from Alternative Splicing to Functional Complexity
Authors: Gao Meichun , Ooms Jasper F. , Leurs Rob , Vischer Henry F.
Published: June 2024

Alternative splicing significantly enhances the diversity of the G protein-coupled receptor (GPCR) family, including the histamine H3 receptor (H3R). This post-transcriptional modification generates multiple H3R isoforms with potentially distinct pharmacological and physiological profiles. H3R is primarily involved in the presynaptic inhibition of neurotransmitter release in the central nervous system. Despite the approval of pitolisant for narcolepsy (Wakix®) and daytime sleepiness in adults with obstructive sleep apnea (Ozawade®) and ongoing clinical trials for other H3R antagonists/inverse agonists, the functional significance of the numerous H3R isoforms remains largely enigmatic. Recent publicly available RNA sequencing data have confirmed the expression of multiple H3R isoforms in the brain, with some isoforms exhibiting unique tissue-specific distribution patterns hinting at isoform-specific functions and interactions within neural circuits. In this review, we discuss the complexity of H3R isoforms with a focus on their potential roles in central nervous system (CNS) function. Comparative analysis across species highlights evolutionary conservation and divergence in H3R splicing, suggesting species-specific regulatory mechanisms. Understanding the functionality of H3R isoforms is crucial for the development of targeted therapeutics. This knowledge will inform the design of more precise pharmacological interventions, potentially enhancing therapeutic efficacy and reducing adverse effects in the treatment of neurological and psychiatric disorders.
Agro-Industrial By-Products of Plant Origin: Therapeutic Uses as well as Antimicrobial and Antioxidant Activity
Authors: Enciso-Martínez Yessica , Zuñiga-Martínez B. Shain , Ayala-Zavala Jesús Fernando , Domínguez-Avila J. Abraham , González-Aguilar Gustavo A. , Viuda-Martos Manuel
Published: June 2024

The importance of bioactive compounds in agro-industrial by-products of plant origin lies in their direct impacts on human health. These compounds have been shown to possess antioxidant, anti-inflammatory, and antimicrobial properties, contributing to disease prevention and strengthening the immune system. In particular, the antimicrobial action of these compounds emerges as an important tool in food preservation, providing natural alternatives to synthetic preservatives and contributing to combating antimicrobial resistance. Using agro-industrial by-products of plant origin not only addresses the need to reduce waste and promote sustainability but also inaugurates a new era in the formulation of functional foods. From fruit peels to pulps and seeds, these by-products are emerging as essential ingredients in the creation of products that can promote health. Continued research in this area will unveil new applications and properties of these by-products and open doors to a food paradigm in which health and sustainability converge, paving the way to a healthier and more equitable future. The present review presents an overview of our knowledge of agro-industrial by-products and some of their more relevant health-promoting bioactivities.
Effect of Health Status and Heat-Induced Inactivation on the Proteomic Profile of Plasma Rich in Growth Factors Obtained from Donors with Chronic Inflammatory Skin Conditions
Authors: Anitua Eduardo , Tierno Roberto , Azkargorta Mikel , Elortza Félix , Alkhraisat Mohammad H.
Published: June 2024

Atopic dermatitis, psoriasis and lichen sclerosus are among the most challenging conditions treated by dermatologists worldwide, with potentially significant physical, social and psychological impacts. Emerging evidence suggests that autologous-platelet-rich plasma could be used to manage skin inflammation. However, the presence of soluble autoimmune components could hinder their therapeutic potential. The aim of this study was to analyze the proteomic profile of plasma rich in growth factors (PRGFs) obtained from donors with inflammatory skin conditions to evaluate the impact of skin health status on the composition and bioactivity of PRGF-based treatments. Venous blood from healthy volunteers and patients with psoriasis, lichen sclerosus and atopic dermatitis was processed to produce PRGF supernatant. Half of the samples were subjected to an additional thermal treatment (56 °C) to inactivate inflammatory and immune molecules. Proteomic analysis was performed to assess the protein profile of PRGFs from healthy and non-healthy patients and the effect of Immunosafe treatment. Differential abundance patterns of several proteins related to key biological processes have been identified, including complement activation, blood coagulation, and glycolysis- and gluconeogenesis-related genes. These results also demonstrate that the thermal treatment (Immunosafe) contributes to the inactivation of the complement system and, as a consequence, reduction in the immunogenic potential of PRGF products.
The Evaluation of Drugs as Potential Modulators of the Trafficking and Maturation of ACE2, the SARS-CoV-2 Receptor
Authors: Alkhofash Nesreen F. , Ali Bassam R.
Published: June 2024

ACE2, part of the angiotensin-converting enzyme family and the renin–angiotensin–aldosterone system (RAAS), plays vital roles in cardiovascular and renal functions. It is also the primary receptor for SARS-CoV-2, enabling its entry into cells. This project aimed to study ACE2’s cellular trafficking and maturation to the cell surface and assess the impact of various drugs and compounds on these processes. We used cellular and biochemical analyses to evaluate these compounds as potential leads for COVID-19 therapeutics. Our screening assay focused on ACE2 maturation levels and subcellular localization with and without drug treatments. Results showed that ACE2 maturation is generally fast and robust, with certain drugs having a mild impact. Out of twenty-three tested compounds, eight significantly reduced ACE2 maturation levels, and three caused approximately 20% decreases. Screening trafficking inhibitors revealed significant effects from most molecular modulators of protein trafficking, mild effects from most proposed COVID-19 drugs, and no effects from statins. This study noted that manipulating ACE2 levels could be beneficial or harmful, depending on the context. Thus, using this approach to uncover leads for COVID-19 therapeutics requires a thorough understanding ACE2’s biogenesis and biology.
Biochemical and Functional Profiling of Thioredoxin-Dependent Cytosolic GPX-like Proteins in Euglena gracilis
Authors: Raihan Md Topu , Ishikawa Takahiro
Published: June 2024

Unlike plants and animals, the phytoflagellate Euglena gracilis lacks catalase and contains a non-selenocysteine glutathione peroxidase-like protein (EgGPXL), two peroxiredoxins (EgPrx1 and EgPrx4), and one ascorbate peroxidase in the cytosol to maintain reactive oxygen species (ROS) homeostasis. In the present study, the full-length cDNA of three cytosolic EgGPXLs was obtained and further characterized biochemically and functionally. These EgGPXLs used thioredoxin instead of glutathione as an electron donor to reduce the levels of H2O2 and t-BOOH. The specific peroxidase activities of these enzymes for H2O2 and t-BOOH were 1.3 to 4.9 and 0.79 to 3.5 µmol/min/mg protein, respectively. Cytosolic EgGPXLs and EgPrx1/EgPrx4 were silenced simultaneously to investigate the synergistic effects of these genes on the physiological function of E. gracilis. The suppression of cytosolic EgGPXL genes was unable to induce any critical phenomena in Euglena under normal (100 μmol photons m−2 s−1) and high-light conditions (350 μmol photons m−2 s−1) at both autotrophic and heterotrophic states. Unexpectedly, the suppression of EgGPXL genes was able to rescue the EgPrx1/EgPrx4-silenced cell line from a critical situation. This study explored the potential resilience of Euglena to ROS, even with restriction of the cytosolic antioxidant system, indicating the involvement of some compensatory mechanisms.
DeepIMAGER: Deeply Analyzing Gene Regulatory Networks from scRNA-seq Data
Authors: Zhou Xiguo , Pan Jingyi , Chen Liang , Zhang Shaoqiang , Chen Yong
Published: June 2024

Understanding the dynamics of gene regulatory networks (GRNs) across diverse cell types poses a challenge yet holds immense value in unraveling the molecular mechanisms governing cellular processes. Current computational methods, which rely solely on expression changes from bulk RNA-seq and/or scRNA-seq data, often result in high rates of false positives and low precision. Here, we introduce an advanced computational tool, DeepIMAGER, for inferring cell-specific GRNs through deep learning and data integration. DeepIMAGER employs a supervised approach that transforms the co-expression patterns of gene pairs into image-like representations and leverages transcription factor (TF) binding information for model training. It is trained using comprehensive datasets that encompass scRNA-seq profiles and ChIP-seq data, capturing TF-gene pair information across various cell types. Comprehensive validations on six cell lines show DeepIMAGER exhibits superior performance in ten popular GRN inference tools and has remarkable robustness against dropout-zero events. DeepIMAGER was applied to scRNA-seq datasets of multiple myeloma (MM) and detected potential GRNs for TFs of RORC, MITF, and FOXD2 in MM dendritic cells. This technical innovation, combined with its capability to accurately decode GRNs from scRNA-seq, establishes DeepIMAGER as a valuable tool for unraveling complex regulatory networks in various cell types.
mRCat: A Novel CatBoost Predictor for the Binary Classification of mRNA Subcellular Localization by Fusing Large Language Model Representation and Sequence Features
Authors: Wang Xiao , Yang Lixiang , Wang Rong
Published: June 2024

The subcellular localization of messenger RNAs (mRNAs) is a pivotal aspect of biomolecules, tightly linked to gene regulation and protein synthesis, and offers innovative insights into disease diagnosis and drug development in the field of biomedicine. Several computational methods have been proposed to predict the subcellular localization of mRNAs within cells. However, there remains a deficiency in the accuracy of these predictions. In this study, we propose an mRCat predictor based on the gradient boosting tree algorithm specifically to predict whether mRNAs are localized in the nucleus or in the cytoplasm. This predictor firstly uses large language models to thoroughly explore hidden information within sequences and then integrates traditional sequence features to collectively characterize mRNA gene sequences. Finally, it employs CatBoost as the base classifier for predicting the subcellular localization of mRNAs. The experimental validation on an independent test set demonstrates that mRCat obtained accuracy of 0.761, F1 score of 0.710, MCC of 0.511, and AUROC of 0.751. The results indicate that our method has higher accuracy and robustness compared to other state-of-the-art methods. It is anticipated to offer deep insights for biomolecular research.
Phloridzin Docosahexaenoate, an Omega-3 Fatty Acid Ester of a Flavonoid Precursor, Inhibits Angiogenesis by Suppressing Endothelial Cell Proliferation, Migration, and Differentiation
Authors: Fernando Wasundara , MacLean Emma , Monro Susan , Power Coombs Melanie R. , Marcato Paola , Rupasinghe H. P. Vasantha , Hoskin David W.
Published: June 2024

Angiogenesis is a normal physiological process that also contributes to diabetic retinopathy-related complications and facilitates tumor metastasis by promoting the hematogenic dissemination of malignant cells from solid tumors. Here, we investigated the in vitro, ex vivo, and in vivo anti-angiogenic activity of phloridzin docosahexaenoate (PZ-DHA), a novel ω-3 fatty acid ester of a flavonoid precursor. Human umbilical vein endothelial cells (HUVEC) and human dermal microvascular endothelial cells (HMVEC) treated with a sub-cytotoxic concentration of PZ-DHA to assess in vitro anti-angiogenic activity showed impaired tubule formation on a Matrigel matrix. Ex vivo angiogenesis was measured using rat thoracic aortas, which exhibited reduced vessel sprouting and tubule formation in the presence of PZ-DHA. Female BALB/c mice bearing VEGF165- and basic fibroblast growth factor-containing Matrigel plugs showed a significant reduction in blood vessel development following PZ-DHA treatment. PZ-DHA inhibited HUVEC and HMVEC proliferation, as well as the migration of HUVECs in gap closure and trans-well cell migration assays. PZ-DHA inhibited upstream and downstream components of the Akt pathway and vascular endothelial growth factor (VEGF165)-induced overexpression of small molecular Rho GTPases in HUVECs, suggesting a decrease in actin cytoskeletal-mediated stress fiber formation and migration. Taken together, these findings reveal the potential of combined food biomolecules in PZ-DHA to inhibit angiogenesis.
Adaptive and Compensatory Neural Signatures in Fibromyalgia: An Analysis of Resting-State and Stimulus-Evoked EEG Oscillations
Authors: Camargo Lucas , Pacheco-Barrios Kevin , Marques Lucas M. , Caumo Wolnei , Fregni Felipe
Published: June 2024

This study aimed to investigate clinical and physiological predictors of brain oscillatory activity in patients with fibromyalgia (FM), assessing resting-state power, event-related desynchronization (ERD), and event-related synchronization (ERS) during tasks. We performed a cross-sectional analysis, including clinical and neurophysiological data from 78 subjects with FM. Multivariate regression models were built to explore predictors of electroencephalography bands. Our findings show a negative correlation between beta oscillations and pain intensity; fibromyalgia duration is positively associated with increased oscillatory power at low frequencies and in the beta band; ERS oscillations in the theta and alpha bands seem to be correlated with better symptoms of FM; fatigue has a signature in the alpha band—a positive relationship in resting-state and a negative relationship in ERS oscillations. Specific neural signatures lead to potential clusters of neural adaptation, in which beta oscillatory activity in the resting state represents a more adaptive activity when pain levels are low and stimulus-evoked oscillations at lower frequencies are likely brain compensatory mechanisms. These neurophysiological changes may help to understand the impact of long-term chronic pain in the central nervous system and the descending inhibitory system in fibromyalgia subjects.