bluuebunny/crossref_metadata_2025_split huggingface dataset:
A multi-modal, asymmetric, weighted, and signed description of anatomical connectivity
Authors: Tanner Jacob , Faskowitz Joshua , Teixeira Andreia Sofia , Seguin Caio , Coletta Ludovico , Gozzi Alessandro , Mišić Bratislav , Betzel Richard F. 
Published: July 2024

AbstractThe macroscale connectome is the network of physical, white-matter tracts between brain areas. The connections are generally weighted and their values interpreted as measures of communication efficacy. In most applications, weights are either assigned based on imaging features–e.g. diffusion parameters–or inferred using statistical models. In reality, the ground-truth weights are unknown, motivating the exploration of alternative edge weighting schemes. Here, we explore a multi-modal, regression-based model that endows reconstructed fiber tracts with directed and signed weights. We find that the model fits observed data well, outperforming a suite of null models. The estimated weights are subject-specific and highly reliable, even when fit using relatively few training samples, and the networks maintain a number of desirable features. In summary, we offer a simple framework for weighting connectome data, demonstrating both its ease of implementation while benchmarking its utility for typical connectome analyses, including graph theoretic modeling and brain-behavior associations.
Optimizing high-temperature energy storage in tungsten bronze-structured ceramics via high-entropy strategy and bandgap engineering
Authors: Gao Yangfei , Song Zizheng , Hu Haichao , Mei Junwen , Kang Ruirui , Zhu Xiaopei , Yang Bian , Shao Jinyou , Chen Zibin , Li Fei , Zhang Shujun , Lou Xiaojie 
Published: July 2024

AbstractAs a vital material utilized in energy storage capacitors, dielectric ceramics have widespread applications in high-power pulse devices. However, the development of dielectric ceramics with both high energy density and efficiency at high temperatures poses a significant challenge. In this study, we employ high-entropy strategy and band gap engineering to enhance the energy storage performance in tetragonal tungsten bronze-structured dielectric ceramics. The high-entropy strategy fosters cation disorder and disrupts long-range ordering, consequently regulating relaxation behavior. Simultaneously, the reduction in grain size, elevation of conductivity activation energy, and increase in band gap collectively bolster the breakdown electric strength. This cascade effect results in outstanding energy storage performance, ultimately achieving a recoverable energy density of 8.9 J cm−3 and an efficiency of 93% in Ba0.4Sr0.3Ca0.3Nb1.7Ta0.3O6 ceramics, which also exhibit superior temperature stability across a broad temperature range up to 180 °C and excellent cycling reliability up to 105. This research presents an effective method for designing tetragonal tungsten bronze dielectric ceramics with ultra-high comprehensive energy storage performance.
Loss of tumor suppressors promotes inflammatory tumor microenvironment and enhances LAG3+T cell mediated immune suppression
Authors: Zahraeifard Sara , Xiao Zhiguang , So Jae Young , Ahad Abdul , Montoya Selina , Park Woo Yong , Sornapudi Trinadharao , Andohkow Tiffany , Read Abigail , Kedei Noemi , Koparde Vishal , Yang Howard , Lee Maxwell , Wong Nathan , Cam Maggie , Wang Kun , Ruppin Eytan , Luo Ji , Hollander Christine , Yang Li 
Published: July 2024

AbstractLow response rate, treatment relapse, and resistance remain key challenges for cancer treatment with immune checkpoint blockade (ICB). Here we report that loss of specific tumor suppressors (TS) induces an inflammatory response and promotes an immune suppressive tumor microenvironment. Importantly, low expression of these TSs is associated with a higher expression of immune checkpoint inhibitory mediators. Here we identify, by using in vivo CRISPR/Cas9 based loss-of-function screening, that NF1, TSC1, and TGF-β RII as TSs regulating immune composition. Loss of each of these three TSs leads to alterations in chromatin accessibility and enhances IL6-JAK3-STAT3/6 inflammatory pathways. This results in an immune suppressive landscape, characterized by increased numbers of LAG3+ CD8 and CD4 T cells. ICB targeting LAG3 and PD-L1 simultaneously inhibits metastatic progression in preclinical triple negative breast cancer (TNBC) mouse models of NF1-, TSC1- or TGF-β RII- deficient tumors. Our study thus reveals a role of TSs in regulating metastasis via non-cell-autonomous modulation of the immune compartment and provides proof-of-principle for ICB targeting LAG3 for patients with NF1-, TSC1- or TGF-β RII-inactivated cancers.
Ubiquitous purine sensor modulates diverse signal transduction pathways in bacteria
Authors: Monteagudo-Cascales Elizabet , Gumerov Vadim M. , Fernández Matilde , Matilla Miguel A. , Gavira José A. , Zhulin Igor B. , Krell Tino 
Published: July 2024

AbstractPurines and their derivatives control intracellular energy homeostasis and nucleotide synthesis, and act as signaling molecules. Here, we combine structural and sequence information to define a purine-binding motif that is present in sensor domains of thousands of bacterial receptors that modulate motility, gene expression, metabolism, and second-messenger turnover. Microcalorimetric titrations of selected sensor domains validate their ability to specifically bind purine derivatives, and evolutionary analyses indicate that purine sensors share a common ancestor with amino-acid receptors. Furthermore, we provide experimental evidence of physiological relevance of purine sensing in a second-messenger signaling system that modulates c-di-GMP levels.
Temperature sensitivity of bat antibodies links metabolic state of bats with antigen-recognition diversity
Authors: Toshkova Nia , Zhelyzkova Violeta , Reyes-Ruiz Alejandra , Haerens Eline , de Castro Deus Marina , Lacombe Robin V. , Lecerf Maxime , Gonzalez Gaelle , Jouvenet Nolwenn , Planchais Cyril , Dimitrov Jordan D. 
Published: July 2024

AbstractThe bat immune system features multiple unique properties such as dampened inflammatory responses and increased tissue protection, explaining their long lifespan and tolerance to viral infections. Here, we demonstrated that body temperature fluctuations corresponding to different physiological states in bats exert a large impact on their antibody repertoires. At elevated temperatures typical for flight, IgG from the bat species Myotis myotis and Nyctalus noctula show elevated antigen binding strength and diversity, recognizing both pathogen-derived antigens and autoantigens. The opposite is observed at temperatures reflecting inactive physiological states. IgG antibodies of human and other mammals, or antibodies of birds do not appear to behave in a similar way. Importantly, diversification of bat antibody specificities results in preferential recognition of damaged endothelial and epithelial cells, indicating an anti-inflammatory function. The temperature-sensitivity of bat antibodies is mediated by the variable regions of immunoglobulin molecules. Additionally, we uncover specific molecular features of bat IgG, such as low thermodynamic stability and implication of hydrophobic interactions in antigen binding as well as high prevalence of polyreactivity. Overall, our results extend the understanding of bat tolerance to disease and inflammation and highlight the link between metabolism and immunity.
Keypoint-MoSeq: parsing behavior by linking point tracking to pose dynamics
Authors: Weinreb Caleb , Pearl Jonah E. , Lin Sherry , Osman Mohammed Abdal Monium , Zhang Libby , Annapragada Sidharth , Conlin Eli , Hoffmann Red , Makowska Sofia , Gillis Winthrop F. , Jay Maya , Ye Shaokai , Mathis Alexander , Mathis Mackenzie W. , Pereira Talmo , Linderman Scott W. , Datta Sandeep Robert 
Published: July 2024

AbstractKeypoint tracking algorithms can flexibly quantify animal movement from videos obtained in a wide variety of settings. However, it remains unclear how to parse continuous keypoint data into discrete actions. This challenge is particularly acute because keypoint data are susceptible to high-frequency jitter that clustering algorithms can mistake for transitions between actions. Here we present keypoint-MoSeq, a machine learning-based platform for identifying behavioral modules (‘syllables’) from keypoint data without human supervision. Keypoint-MoSeq uses a generative model to distinguish keypoint noise from behavior, enabling it to identify syllables whose boundaries correspond to natural sub-second discontinuities in pose dynamics. Keypoint-MoSeq outperforms commonly used alternative clustering methods at identifying these transitions, at capturing correlations between neural activity and behavior and at classifying either solitary or social behaviors in accordance with human annotations. Keypoint-MoSeq also works in multiple species and generalizes beyond the syllable timescale, identifying fast sniff-aligned movements in mice and a spectrum of oscillatory behaviors in fruit flies. Keypoint-MoSeq, therefore, renders accessible the modular structure of behavior through standard video recordings.
Gut microbiota-based machine-learning signature for the diagnosis of alcohol-associated and metabolic dysfunction-associated steatotic liver disease
Authors: Park In-gyu , Yoon Sang Jun , Won Sung-min , Oh Ki-Kwang , Hyun Ji Ye , Suk Ki Tae , Lee Unjoo 
Published: July 2024

AbstractAlcoholic-associated liver disease (ALD) and metabolic dysfunction-associated steatotic liver disease (MASLD) show a high prevalence rate worldwide. As gut microbiota represents current state of ALD and MASLD via gut-liver axis, typical characteristics of gut microbiota can be used as a potential diagnostic marker in ALD and MASLD. Machine learning (ML) algorithms improve diagnostic performance in various diseases. Using gut microbiota-based ML algorithms, we evaluated the diagnostic index for ALD and MASLD. Fecal 16S rRNA sequencing data of 263 ALD (control, elevated liver enzyme [ELE], cirrhosis, and hepatocellular carcinoma [HCC]) and 201 MASLD (control and ELE) subjects were collected. For external validation, 126 ALD and 84 MASLD subjects were recruited. Four supervised ML algorithms (support vector machine, random forest, multilevel perceptron, and convolutional neural network) were used for classification with 20, 40, 60, and 80 features, in which three nonsupervised ML algorithms (independent component analysis, principal component analysis, linear discriminant analysis, and random projection) were used for feature reduction. A total of 52 combinations of ML algorithms for each pair of subgroups were performed with 60 hyperparameter variations and Stratified ShuffleSplit tenfold cross validation. The ML models of the convolutional neural network combined with principal component analysis achieved areas under the receiver operating characteristic curve (AUCs) > 0.90. In ALD, the diagnostic AUC values of the ML strategy (vs. control) were 0.94, 0.97, and 0.96 for ELE, cirrhosis, and liver cancer, respectively. The AUC value (vs. control) for MASLD (ELE) was 0.93. In the external validation, the AUC values of ALD and MASLD (vs control) were > 0.90 and 0.88, respectively. The gut microbiota-based ML strategy can be used for the diagnosis of ALD and MASLD.ClinicalTrials.gov NCT04339725
Preferential and sustained platelet activation in COVID-19 survivors with mental disorders
Authors: Maugeri Norma , De Lorenzo Rebecca , Mazza Mario Gennaro , Palladini Mariagrazia , Ciceri Fabio , Rovere-Querini Patrizia , Manfredi Angelo A. , Benedetti Francesco 
Published: July 2024

AbstractPre-existing mental disorders are considered a risk factor for severe COVID-19 outcomes, possibly because of higher vascular burden. Moreover, an unconventional platelet activation characterizes COVID-19 and contributes to inflammatory and thrombotic manifestations. In the light of the inflammation theory of mental disorders, we hypothesized that patients with mental disorders could be sensitive to the SARS-CoV-2 elicited platelet activation. We investigated platelet activation in 141 COVID-19 survivors at one month after clearance of the virus, comparing subjects with or without an established pre-existing diagnosis of mental disorder according to the DSM-5. We found that platelets from patients with a positive history of psychiatric disorder underwent unconventional activation more frequently than conventional activation or no activation at all. Such preferential activation was not detected when platelets from patients without a previous psychiatric diagnosis were studied. When testing the effects of age, sex, and psychiatric history on the platelet activation, GLZM multivariate analysis confirmed the significant effect of diagnosis only. These findings suggest a preferential platelet activation during acute COVID-19 in patients with a pre-existing psychiatric disorder, mediated by mechanisms associated with thromboinflammation. This event could have contributed to the higher risk of severe outcome in the psychiatric population.
Long-term prediction modeling of shallow rockburst with small dataset based on machine learning
Authors: Rao Guozhu , Rao Yunzhang , Wan Jiazheng , Huang Qiang , Xie Yangjun , Lai Qiande , Yang Zhihua , Xiang Run , Zhang Laiye 
Published: July 2024

AbstractRockburst present substantial hazards in both deep underground construction and shallow depths, underscoring the critical need for accurate prediction methods. This study addressed this need by collecting and analyzing 69 real datasets of rockburst occurring within a 500 m burial depth, which posed challenges due to the dataset's multi-categorized, unbalanced, and small nature. Through a rigorous comparison and screening process involving 11 machine learning algorithms and optimization with KMeansSMOKE oversampling, the Random Forest algorithm emerged as the most optimal choice. Efficient adjustment of hyper parameter was achieved using the Optuna framework. The resulting KMSORF model, which integrates KMeansSMOKE, Optuna, and Random Forest, demonstrated superior performance compared to mainstream models such as Gradient Boosting (GB), Extreme Gradient Boosting (XBG), and Extra Trees (ET). Application of the model in a tungsten mine and tunnel project showcased its ability to accurately forecast rockburst levels, thereby providing valuable insights for risk management in underground construction. Overall, this study contributes to the advancement of safety measures in underground construction by offering an effective predictive model for rockburst occurrences.
A community of practice approach to the management of metal resources, metalworking and hoarding in Bronze Age societies
Authors: Orfanou Vana , Bruyère Caroline , Karydas Andreas G. , Jovanović Dragan , Franković Filip , Spasić Miloš , Koledin Jovan , Jacanović Dragan , Cerović Momir , Davidović Jasmina , Molloy Barry 
Published: July 2024

AbstractThe burial of metals in hoards is a trademark phenomenon of prehistoric Europe that may be counterintuitive to perceptions of value nowadays. For the first time here, we establish detailed biographies of a large corpus of hoarded metal objects, providing new insights into how societies in the second millennium BC engaged with their convertible material wealth. We move beyond previous research on prehistoric hoarding commonly focussing on separate questions such as what was placed in hoards, who selected the objects, what were the origins of materials, and where and when they were buried. Analysing ca. 200 metal tools and weapons, we use data reduction methods to define technological pathways in the long biographies of hoarded objects extending across the sourcing of materials, production, use, decommissioning, and deposition in the Carpathian Basin. We show how the differential treatment of materials and objects was strongly biased by social decisions across artefact types. We identify shared, standardised signature treatments that crossed over social-spatial boundaries. Our findings bring new insights on the interface between communal and elite wealth management at the intersection of technological reasoning and cultural beliefs in prehistoric communities.
Multiplex LAMP assay for detecting the prevalent species of dust mites Dermatophagoides farinae and Dermatophagoides pteronyssinus in the domestic environment
Authors: Shuai Yujun , Xue Qiqi , Tu Huanxin , Guo Junjie , Teng Qiao , Xu Yueye , Xu Jingang , Li Yuanyuan , Zhou Hongming , Zhao Jinhong 
Published: July 2024

AbstractDermatophagoides farina (D. farinae) and Dermatophagoides pteronyssinus (D. pteronyssinus) are the prevalent kinds of house dust mites (HDMs). HDMs are common inhalant allergens that cause a range of allergic diseases, such as rhinitis, atopic dermatitis, and asthma. The epidemiology of these diseases is associated with exposure to mites. Therefore, in the present study, a method named multiplex loop-mediated isothermal amplification (LAMP) was developed to detect environmental dust mites. The multiplex LAMP assay allows amplification within a single tube and has an ITS plasmid detection limit as low as 40 fg/µL for both single dust mites and mixed dust mites (D. pteronyssinus and D. farinae), which is up to ten times more sensitive than classical PCR techniques. Furthermore, the multiplex LAMP method was applied to samples of single dust mites and clinical dust to confirm its validity. The multiplex LAMP assay exhibited higher sensitivity, simpler instrumentation, and visualization of test results, indicating that this method could be used as an alternative to traditional techniques for the detection of HDMs.
A universal AC electrokinetics-based strategy toward surface antifouling of underwater optics
Authors: Jiang Hao , Wang Yan , Du Fei , Stolte Stefan , Specht Uwe , Pesch Georg R. , Baune Michael 
Published: July 2024

AbstractThe practical applications of underwater optical devices, such as cameras or sensors, often suffer from widespread surface biofouling. Current antifouling techniques are primarily hindered by low efficiency, poor compatibility, as well as environmental pollution issues. This paper presents a transparent electrode coating as antifouling system of underwater optics as potential substitute for alternating current electrokinetic (ACEK)-based systems. A strong-coupling model is established to predict the Joule heating induced fluid flows and the negative dielectrophoretic (nDEP) effect for mobilizing organisms or deposited sediments on optic surfaces. The performance of the proposed antifouling system is numerically evaluated through simulations of electrostatic, fluid and temperature fields as well as trajectories of submicron particles, which is then experimentally verified and found to be in good agreement. A parametric study revealed that the degree of electrodes asymmetry is the key factor affecting the flow pattern and therefore the overall performance of the system. This ACEK-based universal strategy is expected to shed light on designing high performance and non-toxic platforms toward energy-efficient surface antifouling applications of underwater optics.
A light-efficient and versatile multiplexing method for snapshot spectral imaging
Authors: Andersson David , Bao Yupan , Kornienko Vassily , Popović Dean , Kristensson Elias 
Published: July 2024

AbstractThe study of rapid and stochastic events that involve multiple species, such as chemical reactions and plasma dynamics, requires means to capture multispectral information in two dimensions at both high temporal- and spatial resolution. Commercially available cameras that provide high temporal resolution are based on either signal intensification or rapid data acquisition. Intensified cameras provide extremely short acquisition times using intensification by means of micro channel plates, but the conversion between electrons and photons makes these cameras inherently monochrome. In contrast, high-speed cameras can achieve color-sensitivity through integrated Bayer filters but suffer from a reduced light collection efficiency and a fixed spectral composition. In this article we present a non-integrated optical arrangement for instantaneous multispectral imaging based on FRAME image multiplexing. By spectrally separating the signal using lossless dichroic mirrors, a 16-fold increase in light-collection efficiency is gained (compared to past solutions), resulting in an equivalent increase in temporal resolution. This improvement provides new avenues for multispectral imaging of rapid events. We demonstrate the system’s versatility and suitability for studies of such processes by applying it for (i) temperature mapping using a high-resolution CCD camera, (ii) high-speed videography up to 10 kHz at four spectral channels and (iii) dual-species visualization in a plasma discharge using an intensified sCMOS camera.
Experimental study on the treatment of deep miscellaneous fill foundation in Xinjiang by vibrating rod compaction method
Authors: Liu Xuejun , Xue Jingchun , Mao Wei , Xie Liangfu , Du Guangyin 
Published: July 2024

AbstractCurrently, the treatment of miscellaneous fill foundations, composed of a mixture of domestic garbage, construction solid waste, and natural soil, presents a significant challenge in urban peripheral engineering construction. This paper discusses the application of vibrating rod compaction technology for foundation treatment in Xinjiang. It evaluates the effectiveness of cross-section vibrating rod compaction equipment in reinforcing fine-grained miscellaneous fill foundations. The study analyzes the impact of construction disturbances caused by the insertion of the vibrating rod, monitoring horizontal stresses at various depths. Both laboratory and field tests show significant improvements: soil dry density increased by 8% to 18%, porosity decreased by 10% to 23%, compression modulus increased by 22% to 246%, and compression coefficient decreased by 8% to 70%. Additionally, cohesion (C) and angle of friction (ɸ) saw increases ranging from 7 to 38% and 3% to 25%, respectively. Below a depth of 3 m, cone tip resistance exceeded 10 MPa, and sidewall friction resistance increased to over 100 kPa, surpassing pre-treatment values. The standard penetration test results doubled stroke length compared to pre-treatment, indicating a substantial improvement in foundation bearing capacity. Surface wave tests before and after treatment showed a 15% increase in wave velocity, reflecting a more compact soil structure. The vibrating rod compaction method is innovative, energy-efficient, environmentally friendly, and economically beneficial, holding great potential for future miscellaneous fill treatments.