bluuebunny/crossref_metadata_2025_split huggingface dataset:
Precursory Signals to Injection Induced Fault Reactivation in the Laboratory Using Active Ultrasonic Monitoring Methods
Authors: Veltmeijer A. , Naderloo M. , Pluymakers A. , Barnhoorn A. 
Published: February 2024

AbstractInduced earthquakes are still highly unpredictable, and often caused by variations in pore fluid pressure. Monitoring and understanding the mechanisms of fluid‐induced fault slip is essential for seismic risk mitigation and seismicity forecasting. Fluid‐induced slip experiments were performed on critically stressed faulted sandstone samples, and the evolution of the actively sent ultrasonic waves throughout the experiment was measured. Two different fault types were used: smooth saw‐cut fault samples at a 35° angle, and a rough fault created by in situ faulting of the samples. Variations in the seismic slip velocity and friction along the fault plane were identified by the coda of the ultrasonic waves. Additionally, ultrasonic amplitudes show precursory signals to laboratory fault reactivation. Our results show that small and local variations in stress before fault failure can be inferred using coda wave interferometry for time‐lapse monitoring, as coda waves are more sensitive to small perturbations in a medium than direct waves. Hence, these signals can be used as precursors to laboratory fault slip and to give insight into reactivation mechanisms. Our results show that time‐lapse monitoring of coda waves can be used to monitor local stress changes associated with fault reactivation in this laboratory setting of fluid‐induced fault reactivation. This is a critical first step toward a method for continuous monitoring of natural fault zones, contributing to seismic risk mitigation of induced and natural earthquakes.
CD97 inhibits osteoclast differentiation via Rap1a/ERK pathway under compression
Authors: Wang Wen , Wang Qian , Sun Shiying , Zhang Pengfei , Li Yuyu , Lin Weimin , Li Qiwen , Zhang Xiao , Ma Zhe , Lu Haiyan 
Published: February 2024

AbstractAcceleration of tooth movement during orthodontic treatment is challenging, with osteoclast-mediated bone resorption on the compressive side being the rate-limiting step. Recent studies have demonstrated that mechanoreceptors on the surface of monocytes/macrophages, especially adhesion G protein-coupled receptors (aGPCRs), play important roles in force sensing. However, its role in the regulation of osteoclast differentiation remains unclear. Herein, through single-cell analysis, we revealed that CD97, a novel mechanosensitive aGPCR, was expressed in macrophages. Compression upregulated CD97 expression and inhibited osteoclast differentiation; while knockdown of CD97 partially rescued osteoclast differentiation. It suggests that CD97 may be an important mechanosensitive receptor during osteoclast differentiation. RNA sequencing analysis showed that the Rap1a/ERK signalling pathway mediates the effects of CD97 on osteoclast differentiation under compression. Consistently, we clarified that administration of the Rap1a inhibitor GGTI298 increased osteoclast activity, thereby accelerating tooth movement. In conclusion, our results indicate that CD97 suppresses osteoclast differentiation through the Rap1a/ERK signalling pathway under orthodontic compressive force.
All-optical image denoising using a diffractive visual processor
Authors: Işıl Çağatay , Gan Tianyi , Ardic Fazil Onuralp , Mentesoglu Koray , Digani Jagrit , Karaca Huseyin , Chen Hanlong , Li Jingxi , Mengu Deniz , Jarrahi Mona , Akşit Kaan , Ozcan Aydogan 
Published: February 2024

AbstractImage denoising, one of the essential inverse problems, targets to remove noise/artifacts from input images. In general, digital image denoising algorithms, executed on computers, present latency due to several iterations implemented in, e.g., graphics processing units (GPUs). While deep learning-enabled methods can operate non-iteratively, they also introduce latency and impose a significant computational burden, leading to increased power consumption. Here, we introduce an analog diffractive image denoiser to all-optically and non-iteratively clean various forms of noise and artifacts from input images – implemented at the speed of light propagation within a thin diffractive visual processor that axially spans <250 × λ, where λ is the wavelength of light. This all-optical image denoiser comprises passive transmissive layers optimized using deep learning to physically scatter the optical modes that represent various noise features, causing them to miss the output image Field-of-View (FoV) while retaining the object features of interest. Our results show that these diffractive denoisers can efficiently remove salt and pepper noise and image rendering-related spatial artifacts from input phase or intensity images while achieving an output power efficiency of ~30–40%. We experimentally demonstrated the effectiveness of this analog denoiser architecture using a 3D-printed diffractive visual processor operating at the terahertz spectrum. Owing to their speed, power-efficiency, and minimal computational overhead, all-optical diffractive denoisers can be transformative for various image display and projection systems, including, e.g., holographic displays.
High-yield and rapid isolation of extracellular vesicles by flocculation via orbital acoustic trapping: FLOAT
Authors: Rufo Joseph , Zhang Peiran , Wang Zeyu , Gu Yuyang , Yang Kaichun , Rich Joseph , Chen Chuyi , Zhong Ruoyu , Jin Ke , He Ye , Xia Jianping , Li Ke , Wu Jiarong , Ouyang Yingshi , Sadovsky Yoel , Lee Luke P. , Huang Tony Jun 
Published: February 2024

AbstractExtracellular vesicles (EVs) have been identified as promising biomarkers for the noninvasive diagnosis of various diseases. However, challenges in separating EVs from soluble proteins have resulted in variable EV recovery rates and low purities. Here, we report a high-yield ( > 90%) and rapid ( < 10 min) EV isolation method called FLocculation via Orbital Acoustic Trapping (FLOAT). The FLOAT approach utilizes an acoustofluidic droplet centrifuge to rotate and controllably heat liquid droplets. By adding a thermoresponsive polymer flocculant, nanoparticles as small as 20 nm can be rapidly and selectively concentrated at the center of the droplet. We demonstrate the ability of FLOAT to separate urinary EVs from the highly abundant Tamm-Horsfall protein, addressing a significant obstacle in the development of EV-based liquid biopsies. Due to its high-yield nature, FLOAT reduces biofluid starting volume requirements by a factor of 100 (from 20 mL to 200 µL), demonstrating its promising potential in point-of-care diagnostics.
Spatial analysis of the osteoarthritis microenvironment: techniques, insights, and applications
Authors: Fan Xiwei , Sun Antonia Rujia , Young Reuben S. E. , Afara Isaac O. , Hamilton Brett R. , Ong Louis Jun Ye , Crawford Ross , Prasadam Indira 
Published: February 2024

AbstractOsteoarthritis (OA) is a debilitating degenerative disease affecting multiple joint tissues, including cartilage, bone, synovium, and adipose tissues. OA presents diverse clinical phenotypes and distinct molecular endotypes, including inflammatory, metabolic, mechanical, genetic, and synovial variants. Consequently, innovative technologies are needed to support the development of effective diagnostic and precision therapeutic approaches. Traditional analysis of bulk OA tissue extracts has limitations due to technical constraints, causing challenges in the differentiation between various physiological and pathological phenotypes in joint tissues. This issue has led to standardization difficulties and hindered the success of clinical trials. Gaining insights into the spatial variations of the cellular and molecular structures in OA tissues, encompassing DNA, RNA, metabolites, and proteins, as well as their chemical properties, elemental composition, and mechanical attributes, can contribute to a more comprehensive understanding of the disease subtypes. Spatially resolved biology enables biologists to investigate cells within the context of their tissue microenvironment, providing a more holistic view of cellular function. Recent advances in innovative spatial biology techniques now allow intact tissue sections to be examined using various -omics lenses, such as genomics, transcriptomics, proteomics, and metabolomics, with spatial data. This fusion of approaches provides researchers with critical insights into the molecular composition and functions of the cells and tissues at precise spatial coordinates. Furthermore, advanced imaging techniques, including high-resolution microscopy, hyperspectral imaging, and mass spectrometry imaging, enable the visualization and analysis of the spatial distribution of biomolecules, cells, and tissues. Linking these molecular imaging outputs to conventional tissue histology can facilitate a more comprehensive characterization of disease phenotypes. This review summarizes the recent advancements in the molecular imaging modalities and methodologies for in-depth spatial analysis. It explores their applications, challenges, and potential opportunities in the field of OA. Additionally, this review provides a perspective on the potential research directions for these contemporary approaches that can meet the requirements of clinical diagnoses and the establishment of therapeutic targets for OA.
Combining OPM and lesion mapping data for epilepsy surgery planning: a simulation study
Authors: Mellor Stephanie , Timms Ryan C. , O’Neill George C. , Tierney Tim M. , Spedden Meaghan E. ,   The MELD Project Consortium, Spitzer Hannah , Ripart Mathilde , Whitaker Kirstie , Napolitano Antonio , De Palma Luca , De Benedictis Alessandro , Foldes Stephen , Zhang Kai , Hu Wenhan , Mo Jiajie , Likeman Marcus , Davies Shirin , Güttler Christopher , Lenge Matteo , Cohen Nathan T. , Tang Yingying , Wang Shan , Chari Aswin , Tisdall Martin , Bargallo Nuria , Conde-Blanco Estefanía , Pariente Jose Carlos , Pascual-Diaz Saül , Delgado-Martínez Ignacio , Pérez-Enríquez Carmen , Lagorio Ilaria , Abela Eugenio , Mullatti Nandini , O’Muircheartaigh Jonathan , Vecchiato Katy , Liu Yawu , Caligiuri Maria Eugenia , Sinclair Ben , Vivash Lucy , Willard Anna , Kandasamy Jothy , McLellan Ailsa , Sokol Drahoslav , Semmelroch Mira , Kloster Ane G. , Ribeiro Letícia , Yasuda Clarissa , Rossi-Espagnet Camilla , Hamandi Khalid , Tietze Anna , Barba Carmen , Guerrini Renzo , Gaillard William Davis , You Xiaozhen , Wang Irene , González-Ortiz Sofía , Severino Mariasavina , Striano Pasquale , Tortora Domenico , Kälviäinen Reetta , Gambardella Antonio , Labate Angelo , Desmond Patricia , Lui Elaine , O’Brien Terence , Shetty Jay , Jackson Graeme , Duncan John S. , Winston Gavin P. , Pinborg Lars H. , Cendes Fernando , Cross J. Helen , Baldeweg Torsten , Adler Sophie , Brookes Matthew J. , Wagstyl Konrad , Barnes Gareth R. 
Published: February 2024

AbstractWhen planning for epilepsy surgery, multiple potential sites for resection may be identified through anatomical imaging. Magnetoencephalography (MEG) using optically pumped sensors (OP-MEG) is a non-invasive functional neuroimaging technique which could be used to help identify the epileptogenic zone from these candidate regions. Here we test the utility of a-priori information from anatomical imaging for differentiating potential lesion sites with OP-MEG. We investigate a number of scenarios: whether to use rigid or flexible sensor arrays, with or without a-priori source information and with or without source modelling errors. We simulated OP-MEG recordings for 1309 potential lesion sites identified from anatomical images in the Multi-centre Epilepsy Lesion Detection (MELD) project. To localise the simulated data, we used three source inversion schemes: unconstrained, prior source locations at centre of the candidate sites, and prior source locations within a volume around the lesion location. We found that prior knowledge of the candidate lesion zones made the inversion robust to errors in sensor gain, orientation and even location. When the reconstruction was too highly restricted and the source assumptions were inaccurate, the utility of this a-priori information was undermined. Overall, we found that constraining the reconstruction to the region including and around the participant’s potential lesion sites provided the best compromise of robustness against modelling or measurement error.
DNA barcoding of Notopterygii Rhizoma et Radix (Qiang-huo) and identification of adulteration in its medicinal services
Authors: Liu Zhen-Wen , Zhou Jing 
Published: February 2024

AbstractSafety concerns, stemming from the presence of complex and unpredictable adulterants, permeate the entire industrial chain of traditional Chinese medicines (TCMs). The Notopterygii Rhizoma et Radix (NReR) from the Apiaceae family, commonly known as “Qiang-huo”, is a widely used herbal medicine. The recent surge in its demand has given rise to a proliferation of counterfeit and substituted products in the market. Traditional identification presents inherent limitations, while DNA mini-barcoding, reliant on sequencing a short-standardized region, has received considerable attention as a new potential means to identify processed medicinal materials. In this study, we constructed a comprehensive Internal Transcribed Spacer 2 (ITS2) matrix encompassing genuine NReR and their commonly found adulterants for the first time. Leveraging this matrix, we conducted a thorough assessment of the genetic profiles and sources of NReR available in the Chinese herbal medicine market. Following established DNA barcoding protocols, the intra-specific genetic divergences within NReR species were found to be lower than the inter-specific genetic divergences from other species. Among the 120 samples that were successfully amplified, ITS2 exhibits an outstanding species-level identification efficiency of 100% when evaluated using both the BLASTN and neighbor-joining (NJ) tree methods. We concluded that ITS2 is a mini-barcode that has shown its potential and may become a universal mini-barcode for the quality control of “Qiang-huo”, thereby ensuring the safety of clinical medication.
A comprehensive study of Al-Cu-Mg system reinforced with nano-ZrO2 particles synthesized by powder metallurgy technique
Authors: Moustafa Essam B. , Aljabri Abdulrahman , Abushanab Waheed S. , Ghandourah E. , Taha Mohammed A. , Khoshaim Ahmed B. , Youness Rasha A. , Mohamed S. S. 
Published: February 2024

AbstractMore focus has recently been placed on enhancing the strength, elastic modulus, coefficient of thermal expansion (CTE), wear and corrosion resistance, and other qualities of aluminum (Al) alloys by varying the quantity of ceramics added for a range of industrial uses. In this regard, Al-4.2-Cu-1.6Mg matrix nanocomposites reinforced with nano-ZrO2 particles have been created using the powder metallurgy approach. The microstructure and particle size distributions of the produced powders were analyzed using a diffraction particle size analyzer, XRD, TEM, and SEM. To achieve good sinterability, the powders were compacted and sintered in argon. The sintered nanocomposites' mechanical, elastic, and physicochemical characteristics were measured. Additionally, the behavior of corrosion, wear, and thermal expansion were examined. The results showed a decrease in the particle sizes of the Al-Cu-Mg alloy by adding ZrO2 nanoparticles up to 45.8 nm for the composite containing 16 wt.% ZrO2. By increasing the sintering temperature to 570 °C, the densification of nanocomposites was enhanced. Also, the coefficient of thermal expansion and wear rate remarkably decreased by about 28 and 37.5% by adding 16 wt.% ZrO2. Moreover, microhardness yield, strength, and Young’s modulus were enhanced to 161, 145, and 64%, respectively, after adding 16 wt.% ZrO2. In addition, increasing the exposure time was responsible for decreasing the corrosion rate for the same sample.
Ultra-low volume intradermal administration of radiation-attenuated sporozoites with the glycolipid adjuvant 7DW8-5 completely protects mice against malaria
Authors: Watson Felicia N. , Shears Melanie J. , Kalata Anya C. , Duncombe Caroline J. , Seilie A. Mariko , Chavtur Chris , Conrad Ethan , Cruz Talavera Irene , Raappana Andrew , Sather D. Noah , Chakravarty Sumana , Sim B. Kim Lee , Hoffman Stephen L. , Tsuji Moriya , Murphy Sean C. 
Published: February 2024

AbstractRadiation-attenuated sporozoite (RAS) vaccines can completely prevent blood stage Plasmodium infection by inducing liver-resident memory CD8+ T cells to target parasites in the liver. Such T cells can be induced by ‘Prime-and-trap’ vaccination, which here combines DNA priming against the P. yoelii circumsporozoite protein (CSP) with a subsequent intravenous (IV) dose of liver-homing RAS to “trap” the activated and expanding T cells in the liver. Prime-and-trap confers durable protection in mice, and efforts are underway to translate this vaccine strategy to the clinic. However, it is unclear whether the RAS trapping dose must be strictly administered by the IV route. Here we show that intradermal (ID) RAS administration can be as effective as IV administration if RAS are co-administrated with the glycolipid adjuvant 7DW8-5 in an ultra-low inoculation volume. In mice, the co-administration of RAS and 7DW8-5 in ultra-low ID volumes (2.5 µL) was completely protective and dose sparing compared to standard volumes (10–50 µL) and induced protective levels of CSP-specific CD8+ T cells in the liver. Our finding that adjuvants and ultra-low volumes are required for ID RAS efficacy may explain why prior reports about higher volumes of unadjuvanted ID RAS proved less effective than IV RAS. The ID route may offer significant translational advantages over the IV route and could improve sporozoite vaccine development.
A new HaCV-EBHSV recombinant lagovirus circulating in European brown hares (Lepus europaeus) from Catalonia, Spain
Authors: Almeida Tereza , Lopes Ana M. , Estruch Josep , Rouco Carlos , Cavadini Patrizia , Neimanis Aleksija , Gavier-Widén Dolores , Le Gall-Reculé Ghislaine , Velarde Roser , Abrantes Joana 
Published: February 2024

AbstractIn 2020/2021, several European brown hare syndrome virus (EBHSV) outbreaks were recorded in European hares (Lepus europaeus) from Catalonia, Spain. Recombination analysis combined with phylogenetic reconstruction and estimation of genetic distances of the complete coding sequences revealed that 5 strains were recombinants. The recombination breakpoint is located within the non-structural protein 2C-like RNA helicase (nucleotide position ~ 1889). For the genomic fragment upstream of the breakpoint, a non-pathogenic EBHSV-related strain (hare calicivirus, HaCV; GII.2) was the most closely related sequence; for the rest of the genome, the most similar strains were the European brown hare syndrome virus (EBHSV) strains recovered from the same 2020/2021 outbreaks, suggesting a recent origin. While the functional impact of the atypical recombination breakpoint remains undetermined, the novel recombinant strain was detected in different European brown hare populations from Catalonia, located 20–100 km apart, and seems to have caused a fatal disease both in juvenile and adult animals, confirming its viability and ability to spread and establish infection. This is the first report of a recombination event involving HaCV and EBHSV and, despite the recombination with a non-pathogenic strain, it appears to be associated with mortality in European brown hares, which warrants close monitoring.
Construction and validation of a colon cancer prognostic model based on tumor mutation burden-related genes
Authors: Zou Daoyang , Xu Tianwen 
Published: February 2024

AbstractCurrently, immunotherapy has entered the clinical diagnosis and treatment guidelines for colon cancer, but existing immunotherapy markers cannot predict the effectiveness of immunotherapy well. This study utilized the TCGA-COAD queue to perform differential gene analysis on high and low-mutation burden samples, and screen differentially expressed genes (DEGs). To explore new molecular markers or predictive models of immunotherapy by using DEGs for NMF classification and prognostic model construction. Through systematic bioinformatics analysis, the TCGA-COAD cohort was successfully divided into high mutation burden subtypes and low mutation burden subtypes by NMF typing using DEGs. The proportion of MSI-H between high mutation burden subtypes was significantly higher than that of low mutation burden subtypes, but there was no significant difference in immunotherapy efficacy between the two subtypes. Drug sensitivity analysis showed significant differences in drug sensitivity between the two subtypes. Subsequently, we constructed a prognostic model using DEGs, which can effectively predict patient survival and immunotherapy outcomes. The prognosis and immunotherapy outcomes of the low-risk group were significantly better than those of the high-risk group. The external dataset validation of the constructed prognostic model using the GSE39582 dataset from the GEO database yielded consistent results. At the same time, we also analyzed the TMB and MSI situation between the high and low-risk groups, and the results showed that there was no significant difference in TMB between the high and low-risk groups, but the proportion of MSI-H in the high-risk group was significantly higher than that in the low-risk group. Finally, we conclude that TMB is not a suitable molecular marker for predicting the efficacy of immunotherapy in colon cancer. The newly constructed prognostic model can effectively differentiate the prognosis of colon cancer patients and predict their immunotherapy efficacy.
Multi-modality trajectory prediction with the dynamic spatial interaction among vehicles under connected vehicle environment
Authors: Jin Lisheng , Liu Xingchen , Wang Yinlin , Han Zhuotong , Guo Baicang , Luo Guofeng , Xu Xinliang 
Published: February 2024

AbstractCompared to non-connected vehicle environments, the connected vehicle environment establishes vehicle interconnection through communication technologies, resulting in more complex interaction, network topologies, and large-scale inputs. This complexity renders traditional trajectory prediction models, which rely primarily on inputting historical information of the target vehicle, inadequate for handling the complex and dynamic interactive lane-changing scenarios in connected vehicle environments. In a connected vehicle environment, it is necessary to propose a more targeted and stable lane-changing behavior prediction method based on vehicle traveling characteristics. Taking into account dynamic spatial interaction among vehicles, this study proposes a multi-modality trajectory prediction model called STA-LSTM to perform analysis on the potential interactive behaviors among vehicles under connected vehicle lane-changing scenarios, and specifically to expand the multi-modality feature input of the vehicle trajectory prediction model. The spatial grid occupancy method is used to model the interactions between vehicles. A space-dimensional attention mechanism is introduced to adaptively match the influencing weights of the surrounding vehicles with the target vehicle and to improve the interactive information extraction method. In addition, the attention module is incorporated into the LSTM decoder from the time dimension so that the established model can identify significant historical hidden features during each trajectory decoding process. To account for the uncertainty of trajectory prediction, the vectors of vehicle interactions are incorporated into contextual information to improve the reliability of prediction results and the robustness of the established model. Compared with conventional baseline models, the proposed model exhibited lower root mean square error (RMSE) and negative log-likelihood (NLL) values, and the RMSE values at different prediction times of 1s, 2s, 3s, 4s, and 5s are 0.46m, 1.15m, 1.89m, 2.84m, and 4.05m, respectively. This indicates that the proposed model can accurately predict the interactions between vehicles and the travel paths of surrounding target vehicles.