bluuebunny/crossref_metadata_2025 huggingface dataset:
Algorithm for extracting the normal cross-section parameters of multiple ball screw shaft ball tracks based on an optical micrometer measurement system
Authors: Wu Jian , Ou Yi , Zhou Changguang , Feng Hutian , Chen Zengtao , Qian Chaoqun , Zhuang Haoran
Published: October 2024

The accurate and efficient measurement of the normal cross-section parameters of multiple ball screw shaft spiral ball tracks are pivotal for ensuring quality control in ball track machining. Given the intricate nature of the ball screw shaft spiral ball track, balancing the accuracy and efficiency of the normal cross-section parameters measurement is a significant challenge. In this study, we present a method to calculate two core parameters, arc radius and contact angle. The method consists of four parts: the automatic axial cross-section separation method, the arc symmetric extraction method, the spiral transformation method, and the parameter algorithm based on the weighted least squares method. The experimental and simulation results validated the effectiveness of our method. Compared with the traditional axial measurement and transformation (AMT) method, our algorithm reduced the errors in arc radius and contact angle by up to 13.9 µm and 4.77°, respectively, and improved the accuracy by up to 78.34% and 85.04%. Compared with the traditional AMT methods and directly normal measurement method, the measurement time of our algorithm was reduced by up to 1565 s and 3475 s, respectively, and the efficiency was improved by up to 71.01% and 84.51%, respectively.
Development of a 4-DOF inchworm piezoelectric platform and its experiments on nano scale variable depth scratching
Authors: Ma Xuefeng , Sun Jianhua , Deng Jie , Zhang Shijing , Liu Junkao , Liu Yingxiang
Published: October 2024

Recent developments in nanotechnologies have highlighted the demand for multi-dimensional, cross-scale and variable-depth nanoscale structures for applications such as nanofluidic chips, nanosensors, nanoelectronics and many more. Therefore, the implementation and system of cross-scale and variable-depth nanomanufacturing is the core of advanced nanotechnologies. Among all of the current methods, nano scratching is the easiest and most flexible approach with the advantages of low cost and simple machining procedures. In this work, a three-dimensional piezoelectric manufacturing system (PMS) based on a self-developed four-degree-of-freedom (4-DOF) inchworm piezoelectric platform is proposed for implementation of cross-scale and variable-depth nano scratching. Based on the PMS, effects of the scratching parameters such as exciting voltage and frequency on scratching depth and quality are discussed. In addition, the scratching experiments were successfully performed and achieved the nanoscale depth variation of the grooves, nesting rectangles, and concentric circles using the multi-DOF and cross-scale output characteristics of the proposed 4-DOF piezoelectric platform. To sum up, the PMS based on the 4-DOF inchworm piezoelectric platform has potential applications in the fields of machining three-dimensional nanostructures within millimeter scale.
A molecular dynamics investigation of nano-twins and nano-precipitates effects in CoCrFeNi-based high-entropy alloys
Authors: Gao W H , Qiao L , Zhao D , Wang J J , Fang H Q , Zhang W Y , Ma S G , Zhang T W , Wang Z H
Published: October 2024

This study systematically investigates the effects of twin boundaries and precipitates on the performance of CoCrFeNi HEAs matrix using molecular dynamics simulation methods. By constructing corresponding HEAs models and conducting simulations of their structural evolution and mechanical behavior at the nanoscale, the influence mechanisms of nanotwins (NTs) and nano-precipitates (NPs) on the mechanical properties of the material were explored through in-depth analysis of simulation results. The findings suggest that twin boundaries effectively impede the movement and slip of dislocations and stacking faults in the material. As a result, this enhances its mechanical properties and inhibits plastic deformation, ultimately improving its ductility. Meanwhile, precipitates also impact the material’s performance, and the shape of precipitates may exert different effects on the material, while the phase interface between precipitates and the matrix can hinder the expansion of defects. The presence of twin boundaries can enhance the strengthening effect of precipitates, further improving the material’s performance. This study provides a new perspective for understanding the relationship between the microstructure and mechanical properties of HEAs materials, offering important references for the design and optimization of HEAs materials.
An augmented lead-free Perovskite solar cell based on FASnI3 using V2O5 as HTL
Authors: Vishnuwaran M , Ramachandran K , Sakthivel P
Published: October 2024

The study involved the design and analysis of FASnI3-based perovskite solar cells to determine their power conversion efficiency (PCE) under varying AB-layer thicknesses and temperatures. Despite recent advancements, organic and inorganic lead-based perovskite solar cells have faced challenges due to health hazards and device instability, hindering commercial manufacturing progress. To address this, we explored alternative charge transport materials, such as FASnI3 cells, through numerical simulation using the 1D-SCAPS software. Our investigation focused on optimizing charge transport layers and adjusting acceptor and donor concentrations to achieve high-efficiency, lead-free PSCs. Furthermore, we evaluated the performance and impact of different parameters on simulated cell devices. Through multiple simulation iterations, we achieved the best performance of the FASnI3 PS-cell, delivering a voltage of 1.04 V, current density of 29.40 mA cm−2, and Fill factor of 85.24%, resulting in an overall PCE of 24.45%.
Advancing remote sensing: a unified deep learning approach with pretrained and custom architectures for high-precision classification
Authors: N Salma , G R Madhuri , Jagadale Basavaraj
Published: October 2024

Advancement of remote sensing is vital for accurate land cover mapping and ecological surveillance. This research proposes a cutting-edge deep learning framework that integrates a meticulously designed customary network architecture with the effectiveness of pre-trained models, namely GoogleNet, VGG16, and InceptionV3. Our approach captures the complex features of RGB satellite images throughout various land cover categories using diverse EuroSAT datasets. Our system achieves an impressive 99.40% test accuracy by implementing feature extraction through effective models with a customized deep learning network in an intuitive manner. High class-wise accuracies are observed, ranging from 96.00% to 100.00%, whereas F1-scores, precision, and recall all converge at 99.40%. The aforementioned results demonstrate our approach’s perspective to significantly improve analysis while also confirming its superiority. These results not only confirm the performance of our algorithm but also show that it could be used to redesign satellite visual analysis behavior. These results open the window to further improve and accurate remote sensing systems, giving a helpful viewpoint for researchers as well as professionals.
Correlated scalar perturbations and gravitational waves from axion inflation
Authors: Corbà Sofia P. , Sorbo Lorenzo
Published: October 2024

The scalar and tensor fluctuations generated during inflation can be correlated, if arising from the same underlying mechanism. In this paper we investigate such correlation in the model of axion inflation, where the rolling inflaton produces quanta of a U(1) gauge field which, in turn, source scalar and tensor fluctuations. We compute the primordial correlator of the curvature perturbation, ζ, with the gravitational energy density, Ω
GW
, at frequencies probed by gravitational wave detectors. This two-point function receives two contributions: one arising from the correlation of gravitational waves with the scalar perturbations generated by the standard mechanism of amplification of vacuum fluctuations, and the other coming from the correlation of gravitational waves with the scalar perturbations sourced by the gauge field. Our analysis shows that the former effect is generally dominant. For typical values of the parameters, the correlator, normalized by the amplitude of ζ and by the fractional energy in gravitational waves at interferometer frequencies, turns out to be of the order of 10-4 ÷ 10-2.
Separability probability of two-qubit states
Authors: Thanh Huong Ha , The Khoi Vu
Published: October 2024

Many works have been devoted to determining the volume of the set of separable states and the separability probability both analytically and numerically. However, computing the exact separability probability remains a highly nontrivial open problem. In these notes, we examine this problem in the simplest context of two-qubit states. A novel aspect of our method is the use of the Duistermaat-Heckman measure, which is the push-forward of Liouville measure on the coadjoint orbit along the moment map. On each coadjoint orbit, the Hilbert-Schmidt measure differs from the Duistermaat-Heckman measure by a constant. The latter measure can be explicitly computed by using tools from symplectic geometry. We confirm the conjecture that the separability probability of two-qubit states with Hilbert-Schmidt measure is

8
33

.
Exploring uncertainty of small-scale blue swimming crab fishery (Portunus pelagicus) toward local blue economy: The case of Pati Coastal Waters, Central Java, Indonesia
Authors: Nurhijayat A , Adrianto L , Zairion Z , Salim M G , Zulfikar A
Published: October 2024

Blue swimming crab (BSC) fisheries are characterized as small-scale, with limited biological and socio-economic data. Information limitations, such as those related to administrative inputs, have become a pressing issue in understanding the sustainability of BSC fisheries in coastal Pati Regency. This study aimed to analyze fishery uncertainty. The research was conducted from December 2020 to March 2021 in Alasdowo Village, Dukuhseti District, Pati Regency. Biological data was collected from the daily logbooks of BSC middlemen, encompassing the catch of 368 fishermen from January 2019 to March 2021. Socio-economic data was obtained through structured interviews and focus group discussions. The production value of BSC in zone 2 was approximately 724.6 ± 889.7 kg/day, with a coefficient of variability of 1.23. The number of fishing trips was 188 ± 137, with a coefficient of variability of 0.73. The productivity value was approximately 3.2 ± 3.7 kg/trip, with a coefficient of variability of 1.16. The BSC fishery using trap-net gear in zone 2 exhibits high uncertainty, as evidenced by the high coefficients of variability. Exploring fishery uncertainty can be a valuable component of fisheries management through a social-ecological systems approach.
Metal-free ultrathin terahertz absorber with independently tunable dual narrow bands
Authors: Verma Vikrant , Varshney Gaurav
Published: October 2024

A technique is introduced to precisely control the resonance behaviour of a metal-free graphene-based terahertz absorber by independently tuning the dual resonant peaks. The proposed ultrathin absorber features a multilayer configuration, with two isolated resonator layers of patterned graphene on dielectric (SiO2) substrates and a thin graphite sheet at the bottom serving as a reflector. The stacked arrangement enables independent tunability of the high-absorptivity resonant peaks at 7.33 and 9.34 THz. The structure, with a thickness of just λ/15 of the free-space wavelength, offers a compact design suitable for space-constrained applications. Its symmetrical geometry ensures polarization insensitivity and stable performance for incident angles up to 60°. Simulated results, analyzed via CST Studio and validated with an equivalent circuit model, demonstrate excellent thermal stability. Furthermore, the narrowband response of the proposed absorber improves its sensitivity to refractive index (RI) variations induced by biomolecular interactions, validating its suitability in biosensing applications. The absorber demonstrates peak absorption across both the resonant frequencies with an analyte optimized at 1.5 μm thickness. Sensitivity levels of 1.1 and 1.05 THz/RIU along with figure-of-merit values of 2.11 and 2.23 are recorded for the lower and upper bands, respectively. The absorber offers enhanced selectivity due to low values of full width at half maximum. High Q-factors of 12.85 and 19.3 confirm its strong potential for RI sensing.
Computed tomography employing sensing of high energy particle current
Authors: Zygmanski Piotr , Brivio Davide , Hoegele Wolfgang
Published: October 2024

Objective. We demonstrate High Energy Current Computed Tomography (HEC-CT) employing megavoltage linac x-rays. Approach. Using deterministic radiation transport we simulate two-parameter HEC-CT projections and using inverse Fourier transform we reconstruct two distinct material parameters for water phantoms with ICRP tissue inserts and materials of different atomic number Z. The HEC-CT projections are obtained by beam scanning and rotating the object. Main Results. The first HEC-CT material parameter is alike the standard attenuation coefficient with dependence on atomic number and material density similar to the Hounsfield Units. The second material parameter has opposite trends and does not find any analogy in the standard CT framework. Significance. New CT method has been invented for medical imaging or non-destructive testing. The key feature of the technique is a two-value CT reconstruction based on particle current instead of transmitted dose.
Development of a distributed hydrological model combined with sediment transport calculations and its application to a medium-scale basin in northeast China
Authors: Huang Jinbai , Wang Qingming , Feng Shaoyuan , Wang Bin , Wen Jiawei , Zhang Gengxi
Published: October 2024

An accurate assessment of sediment transport can assist land and resource managers in any region. The primary objective of this study was to develop a distributed hydrological model for calculating rainfall-runoff coupled with sediment transport to provide a practical method for estimating sediment transport in western Heilongjiang Province, China. The Alun River Basin, which has typical meteorological and hydrological characteristics of western Heilongjiang Province, was chosen as the study area. A sediment transport calculation module was developed based on physically based formulas for the suspended load and bedload, which was coupled with a numerical model of the physical distributed rainfall-runoff process. The model’s ability was validated by comparing the sediment sampling survey results of the particle size group distribution (PSGD) in the flow and the corresponding value of the model calculation results for a control case. The root mean square error (RMSE) and the mean absolute error (MAE) were mostly <10%. The model was used to calculate the rainfall-runoff combined with sediment transport in 2016, and the results indicate that the primary form of sediment transport was as suspended load. The suspended load accounted for over 90% of the total sediment transport caused by the maximum flood peak, and the suspended load accounted for over 80% during the period of normal water level across the selected sections. The sediment transport process was dominated by the runoff process. The contribution of the monthly sediment transport in winter to the annual total value was mostly <1%; while in the rainy season, the contribution of the monthly sediment transport to the annual total value was >15%. The results provide a basis for the assessment of sediment transport and the development of a numerical platform for modeling hydrological processes coupled with land surface processes in western Heilongjiang Province, China.
Cyclic loading effects on the heat-generation performance of carbon nanotube-embedded cement composites
Authors: Bang Jinho , Jang Daeik , Yang Beomjoo
Published: October 2024

This study investigates the heat-generation stability of carbon nanotube (CNT)/cement composites after exposing to cyclic loading conditions. The specimens were fabricated with varying CNT contents and levels of fly ash replacement. Results showed that increasing CNT content reduced electrical resistivity, while the impact on the electrical characteristics was found to be insubstantial, even though a considerable portion of fly ash was replaced. In addition, the electrical resistivity of the specimens after exposed to cyclic loading increased. Electrical heating tests revealed both negative and positive temperature coefficient effects depending on the applied voltages. Higher CNT contents improved the heat-generation capability, but the heating capability decreased after exposed to the cyclic loadings which is deduced from the damage of CNT networks during cyclic loadings. In this regard, the authors concluded that the heat-generation stability can be significantly affected by the applied loadings. Thus, the future research will be conducted to improve the heat-generation stability of the cement-based electrical heating systems as exposed to artificial deteriorations.
Unpaired image translation to mitigate domain shift in liquid argon time projection chamber detector responses
Authors: Huang Yi , Torbunov Dmitrii , Viren Brett , Yu Haiwang , Huang Jin , Lin Meifeng , Ren Yihui
Published: October 2024

Deep learning algorithms often are developed and trained on a training dataset and deployed on test datasets. Any systematic difference between the training and a test dataset may severely degrade the final algorithm performance on the test dataset—what is known as the domain shift problem. This issue is prevalent in many scientific domains where algorithms are trained on simulated data but applied to real-world datasets. Typically, the domain shift problem is solved through various domain adaptation (DA) methods. However, these methods are often tailored for a specific downstream task, such as classification or semantic segmentation, and may not easily generalize to different tasks. This work explores the feasibility of using an alternative way to solve the domain shift problem that is not specific to any downstream algorithm. The proposed approach relies on modern Unpaired Image-to-Image (UI2I) translation techniques, designed to find translations between different image domains in a fully unsupervised fashion. In this study, the approach is applied to a domain shift problem commonly encountered in Liquid Argon Time Projection Chamber (LArTPC) detector research when seeking a way to translate samples between two differently distributed LArTPC detector datasets deterministically. This translation allows for mapping real-world data into the simulated data domain where the downstream algorithms can be run with much less domain-shift-related performance degradation. Conversely, using the translation from the simulated data to a real-world domain can increase the realism of the simulated dataset and reduce the magnitude of any systematic uncertainties. To evaluate the quality of the translations, we use both pixel-wise metrics and a downstream task to measure the effectiveness of UI2I methods for mitigating the domain shift problem. We adapted several popular UI2I translation algorithms to work on scientific data and demonstrated the viability of these techniques for solving the domain shift problem with LArTPC detector data. To facilitate further development of DA techniques for scientific datasets, the ‘Simple Liquid-Argon Track Samples’ dataset used in this study is also published.
Efficient mapping of phase diagrams with conditional Boltzmann Generators
Authors: Schebek Maximilian , Invernizzi Michele , Noé Frank , Rogal Jutta
Published: October 2024

The accurate prediction of phase diagrams is of central importance for both the fundamental understanding of materials as well as for technological applications in material sciences. However, the computational prediction of the relative stability between phases based on their free energy is a daunting task, as traditional free energy estimators require a large amount of simulation data to obtain uncorrelated equilibrium samples over a grid of thermodynamic states. In this work, we develop deep generative machine learning models based on the Boltzmann Generator approach for entire phase diagrams, employing normalizing flows conditioned on the thermodynamic states, e.g. temperature and pressure, that they map to. By training a single normalizing flow to transform the equilibrium distribution sampled at only one reference thermodynamic state to a wide range of target temperatures and pressures, we can efficiently generate equilibrium samples across the entire phase diagram. Using a permutation-equivariant architecture allows us, thereby, to treat solid and liquid phases on the same footing. We demonstrate our approach by predicting the solid–liquid coexistence line for a Lennard-Jones system in excellent agreement with state-of-the-art free energy methods while significantly reducing the number of energy evaluations needed.
A facile approach for growing Ag nano-dendrites employing towards E. coli cells monitoring using SERS: a proof-of-concept study
Authors: Murugan Dhatchayani , Diwan Aarti , Chithravel Akila , Shekhawat Abhishek S , Singh Neetika , Lakkakula Satish , Gowrishankar Shanmugaraj , Srivastava Tulika , Saxena Shailendra K , Shrivastav Anand M
Published: October 2024

Here, a highly efficient and inexpensive technique to fabricate silver dendritic nanostructures with unique numerous lateral branches has been demonstrated. The study utilized the metal-assisted growth (MAG) technique, which is a simple, one-step technique that allows exact control over the size and morphology of the generated dendrites. The prepared dendrites are characterized using various techniques and the fabrication mechanism is well explored. The final synthesized Ag dendrites are then utilized to detect in-house cultured E. coli. cells using surface-enhanced Raman scattering (SERS) activity. The proposed reason for their superior SERS performance is due to the contribution from the large amount of plasmon-active ‘hotspots’ present in dendritic structures at the sharp edges enhancing the nearby local electromagnetic fields. The proposed work suggests Ag dendritic nanostructures as a potential candidate for SERS-based applications.
Effect of Cd-doping on optoelectronic properties of ZnO thin films and their application for MAPbI3 photodetector
Authors: Rana Ankur , Rana Megha , Malik Riya , Khanna Suraj P , Srivastava R , Suman C K
Published: October 2024

The Sol–gel method was used to synthesize Cd-doped ZnO nanoparticles at different doping concentrations. The nanomaterials crystal structure and microstructure were explained by XRD and SEM analysis of the materials. The absorption and transmission spectra were analyzed to explore the optical properties of Cd-doped ZnO thin films. The band gap of nanomaterials decreases from 3.26 to 3.12 eV with the increase of Cd doping concentration in ZnO. The Cd-doped ZnO shows an increasing trend of electrical conductivity and mobility with the increase of Cd concentration in ZnO. The Cd-doped ZnO-based MAPbI3 photodetectors show substantial responsivity in the wavelength range of 365 to 635 nm. The highest responsivity for devices FTO/ Zn1-xCdxO/MAPbI3/Al, having x = 0.05, 0.10 and 0.15, upon 465 nm wavelength (4 mW cm−2) illumination are ∼0.192, 0.272, and 2.1 μA W−1, respectively. The LDR of the x = 0.15 Cd-doped ZnO photodetector is two times higher than the x = 0.05 concentration of Cd doped ZnO photodetectors. Our studies confirm that the Cd-doped ZnO creates band narrowing and may be used for suitable perovskite photodetector.
Multi-omics integration analysis reveals the role of N6-methyladenosine in lncRNA translation during glioma stem cell differentiation
Authors: Zhang Meng , Cai Runqiu , Liu Jingjing , Wang Yulan , He Shan , Wang Quan , Song Xiaofeng , Wu Jing , Zhao Jian
Published: October 2024

Glioblastoma is one of the most lethal brain diseases in humans. Although recent studies have shown reciprocal interactions between N6-methyladenosine (m6A) modifications and long noncoding RNAs (lncRNAs) in gliomagenesis and malignant progression, the mechanism of m6A-mediated lncRNA translational regulation in glioblastoma remains unclear. Herein, we profiled the transcriptomes, translatomes, and epitranscriptomics of glioma stem cells and differentiated glioma cells to investigate the role of m6A in lncRNA translation comprehensively. We found that lncRNAs with numerous m6A peaks exhibit reduced translation efficiency. Transcript-level expression analysis demonstrates an enrichment of m6A around short open reading frames (sORFs) of translatable lncRNA transcripts. Further comparison analysis of m6A modifications in different RNA regions indicates that m6A peaks downstream of sORFs inhibit lncRNA translation more than those upstream. Observations in glioma-associated lncRNAs H19, LINC00467, and GAS5 further confirm the negative effect of m6A methylation on lncRNA translation. Overall, these findings elucidate the dynamic profiles of the m6A methylome and enhance the understanding of the complexity of lncRNA translational regulation.
mosGraphGen: a novel tool to generate multi-omics signaling graphs to facilitate integrative and interpretable graph AI model development
Authors: Zhang Heming , Cao Dekang , Chen Zirui , Zhang Xiuyuan , Chen Yixin , Sessions Cole , Cruchaga Carlos , Payne Philip , Li Guangfu , Province Michael , Li Fuhai
Published: October 2024

Motivation

Multi-omics data, i.e. genomics, epigenomics, transcriptomics, proteomics, characterize cellular complex signaling systems from multi-level and multi-view and provide a holistic view of complex cellular signaling pathways. However, it remains challenging to integrate and interpret multi-omics data for mining critical biomarkers. Graph AI models have been widely used to analyze graph-structure datasets, and are ideal for integrative multi-omics data analysis because they can naturally integrate and represent multi-omics data as a biologically meaningful multi-level signaling graph and interpret multi-omics data via graph node and edge ranking analysis. Nevertheless, it is nontrivial for graph-AI model developers to pre-analyze multi-omics data and convert the data into biologically meaningful graphs, which can be directly fed into graph-AI models.

Results

To resolve this challenge, we developed mosGraphGen (multi-omics signaling graph generator), generating Multi-omics Signaling graphs (mos-graph) of individual samples by mapping multi-omics data onto a biologically meaningful multi-level background signaling network with data normalization by aggregating measurements and aligning to the reference genome. With mosGraphGen, AI model developers can directly apply and evaluate their models using these mos-graphs. In the results, mosGraphGen was used and illustrated using two widely used multi-omics datasets of The Cancer Genome Atlas (TCGA) and Alzheimer’s disease (AD) samples.

Availability and implementation

The code of mosGraphGen is open-source and publicly available via GitHub: https://github.com/FuhaiLiAiLab/mosGraphGen.
An adaptive null proportion estimator for false discovery rate control
Authors: Gao Zijun
Published: October 2024

The false discovery rate is a commonly used criterion in multiple testing, and the Benjamini–Hochberg procedure is a standard approach to false discovery rate control. To increase its power, adaptive Benjamini–Hochberg procedures, that use estimates of the null proportion, have been proposed. A particularly popular approach being that based on Storey’s estimator. The performance of Storey’s estimator hinges on a critical hyperparameter, such that a pre-fixed configuration may lack power and existing data-driven hyperparameters may compromise false discovery rate control. In this work, we propose a novel class of adaptive hyperparameters and establish the false discovery rate control of the associated adaptive Benjamini–Hochberg procedure using a martingale argument. Within this class of data-driven hyperparameters, we further present a specific configuration designed to maximize the number of rejections and characterize its convergence to the optimal hyperparameter under a mixture model. The proposed method exhibits significant power gains, particularly in cases with a conservative null distribution, which are common in composite null testing, or with a moderate proportion of weak nonnulls, as is typically observed in biological experiments with enrichment processes.
Bayesian network-guided sparse regression with flexible varying effects
Authors: Ren Yangfan , Peterson Christine B , Vannucci Marina
Published: October 2024

In this paper, we propose Varying Effects Regression with Graph Estimation (VERGE), a novel Bayesian method for feature selection in regression. Our model has key aspects that allow it to leverage the complex structure of data sets arising from genomics or imaging studies. We distinguish between the predictors, which are the features utilized in the outcome prediction model, and the subject-level covariates, which modulate the effects of the predictors on the outcome. We construct a varying coefficients modeling framework where we infer a network among the predictor variables and utilize this network information to encourage the selection of related predictors. We employ variable selection spike-and-slab priors that enable the selection of both network-linked predictor variables and covariates that modify the predictor effects. We demonstrate through simulation studies that our method outperforms existing alternative methods in terms of both feature selection and predictive accuracy. We illustrate VERGE with an application to characterizing the influence of gut microbiome features on obesity, where we identify a set of microbial taxa and their ecological dependence relations. We allow subject-level covariates, including sex and dietary intake variables to modify the coefficients of the microbiome predictors, providing additional insight into the interplay between these factors.
Repetitive subconcussion results in disrupted neural activity independent of concussion history
Authors: Solar Kevin Grant , Ventresca Matthew , Zamyadi Rouzbeh , Zhang Jing , Jetly Rakesh , Vartanian Oshin , Rhind Shawn G , Dunkley Benjamin T
Published: October 2024

Concussion is a public health crisis that results in a complex cascade of neurochemical changes that can have life-changing consequences. Subconcussions are generally considered less serious, but we now realize repetitive subconcussions can lead to serious neurological deficits. Subconcussions are common in contact sports and the military where certain personnel are exposed to repetitive occupational blast overpressure. Post-mortem studies show subconcussion is a better predictor than concussion for chronic traumatic encephalopathy—a progressive and fatal neurodegenerative tauopathy, only diagnosable post-mortem—thus, an in vivo biomarker would be transformative. Magnetoencephalography captures the dynamics of neuronal electrochemical action, and functional MRI shows that functional connectivity is associated with tauopathy patterns. Therefore, both imaging modalities could provide surrogate markers of tauopathy. In this cross-sectional study, we examined the effects of repetitive subconcussion on neuronal activity and functional connectivity using magnetoencephalography and functional MRI, and on neurological symptoms and mental health in a military sample. For magnetoencephalography and outcome analyses, 81 participants were split into ‘high’ and ‘low’ blast exposure groups using the generalized blast exposure value: n = 41 high blast (26.4–65.7 years; 4 females) and n = 40 low blast (28.0–63.3 years; 8 females). For functional MRI, two high blast male participants without data were excluded: n = 39 (29.6–65.7 years). Magnetoencephalography revealed disrupted neuronal activity in participants with a greater history of repetitive subconcussions, including neural slowing (higher delta activity) in right fronto-temporal lobes and subcortical regions (hippocampus, amygdala, caudate, pallidum and thalamus), and functional dysconnectivity in the posterior default mode network (lower connectivity at low and high gamma). These abnormalities were independent of concussion or traumatic stress history, and magnetoencephalography showed functional dysconnectivity not detected in functional MRI. Besides magnetoencephalography changes, those with higher blast exposure had poorer somatic and cognitive outcomes, with no blast-related differences in mental health or associations between neurological symptoms and neuronal activity. This study suggests that repetitive subconcussions have deleterious effects on brain function and that magnetoencephalography provides an avenue for both treatment targets by identifying affected brain regions and in prevention by identifying those at risk of cumulative subconcussive neurotrauma.
Cu nanorod arrays on Cu foam as an effective and low-priced electrode for hydrazine oxidation
Authors: Liu Ran , Luan Yuting , Sheng Shuang , Lin Binbin , Yin Jinling
Published: October 2024

The synthesis of Cu catalysts for hydrazine oxidation has been an important focus for study. Herein, Cu nanorod arrays on Cu foam (Cu NRAs/CF) were synthesized. Profiting from its structural characteristics, hydrazine oxidation began at −1.03 V and the current density attained 178.8 mA cm−2 at −0.6 V. Compared with CF and Cu NPs/CF, Cu NRAs/CF presented a lower charge transfer resistance (Rct) and apparent activation energy (Ea), indicating that hydrazine oxidation on Cu NRAs/CF was associated with comparatively fast kinetics.
Toxoplasma qPCR kinetics to guide pre-emptive treatment of toxoplasmosis after allogeneic hematopoietic stem cell transplantation
Authors: Aerts Robina , Xhaard Alienor , Robin Christine , Groll Andreas H , Cordonnier Catherine , Lagrou Katrien , Bretagne Stéphane
Published: October 2024

Background

Recent ECIL-guidelines recommend a quantitative PCR (qPCR) guided pre-emptive treatment approach to toxoplasmosis in seropositive recipients of allogeneic hematopoietic cell transplantation (allo-HCT). While qPCR might serve as a sensitive tool for early Toxoplasma detection, its role in treatment follow-up remains unknown.

Methods

We analyzed the qPCR kinetics of allo-HCT recipients experiencing either Toxoplasma infection (TI, n=71) or disease (TD, n=14) in relation to different parameters. We included 85 patients with available qPCR values expressed as quantitative cycle (Cq) from four large hematological centers from 2009 to 2023, and kinetic analysis was performed in a selection of 74 patients screened at least weekly with blood qPCR. Day 0 (D0) was the day of anti-Toxoplasma treatment start or (when untreated) day of diagnosis.

Results

Time to qPCR negativity was inversely proportional to the Cq value at D0 (p=0.0063). Not reaching negativity at D10 was associated with a significantly higher mortality at D30 (p=0.023). Patients with a high D0-parasitic load and patients with TD showed slower clearance (p<0.001, p=0.032). Time to negativity was not significantly different for patients started on prophylactic vs curative doses as first-line treatment regimen (p=0.16).

Conclusions

This study underscores the predictive value of qPCR kinetics monitoring in allo-HCT patients with toxoplasmosis. With the aforementioned risk factors, clinicians can identify patients at high-risk for worse outcome. Our results support to consider a therapeutic change or reinforcement if the parasitic load does not decrease after 10 days, supplementing existing clinical guidelines.
Anti-phospholipid antibodies nephropathy is associated with an increased risk of kidney failure: a systematic literature review and meta-analysis
Authors: Hoxha Ariela , Lovisotto Marco , Perin Nicola , Nalesso Federico , Del Prete Dorella , Simioni Paolo
Published: October 2024

Background

Anti-phospholipid antibodies nephropathy (aPL-N) is a complex feature of anti-phospholipid syndrome due to microvascular lesions. Renal prognosis and predictors of outcome are not yet known.

Methods

We performed a systematic review of the literature (February 2006–January 2024) using the PubMed, Scopus, Cochrane Library and EMBASE databases. Two reviewers independently conducted literature screening and data extraction in a blinded, standardized manner. A random effects model was used to pool odds ratios (ORs) [with 95% confidence interval (CI)] for the primary analysis, the risk of kidney failure. Subgroup analyses were performed for clinical and laboratory features that predicted renal outcomes. Heterogeneity was assessed by I2.

Results

Six records involving 709 patients were included in the meta-analysis. Biopsy-proven aPL-N was found in 238/832 (28.6%) patients. Acute kidney injury (AKI) was present at diagnosis in 20/65 (30.8%), while 73/233 (31.3%) patients with aPL-N developed chronic kidney disease (CKD)/end-stage kidney disease (ESKD) at follow-up. aPL-N was associated with an increased risk of CKD/ESKD [OR 6.89 (95% CI 2.42–19.58)] and AKI [OR 2.97 (95% CI 1–4-6.29)]. Arterial hypertension and positivity for lupus anticoagulant, anti-cardiolipin antibodies and anti-β2 glycoprotein I antibodies were associated with an increased risk of developing aPL-N [OR 3.7 (95% CI 1.9–7.23), OR 4.01 (95% CI 1.88–8.53), OR 2.35 (95% CI 1.31–4.21) and OR 19.2 (95% CI 2.91–125.75), respectively].

Conclusion

aPL-N is associated with poor renal outcomes. High blood pressure and aPL positivity have been identified as predictors of adverse renal outcomes. This up-to-date knowledge on renal outcomes and predictors of renal outcomes in aPL-N enables a personalized follow-up and therapeutic approach.
The heat is on: sensitivity of goldsinny wrasse to global climate change
Authors: Perry Diana , Tamarit Elena , Morgenroth Daniel , Gräns Albin , Sturve Joachim , Gullström Martin , Thor Peter , Wennhage Håkan
Published: October 2024

Unsustainable harvesting practices have drastically reduced fish populations globally and developments in aquaculture have increased. Unexpectedly, Atlantic salmon farming caused the opening of a new fishery in northern European countries, where previously unharvested mesopredatory species, like the goldsinny wrasse (Ctenolabrus rupestris), are captured for use as cleaner fish in pens along the coast and fjords. The goldsinny wrasse is widespread in coastal areas where it plays an ecologically important role as a predator of small invertebrates. Since climate change effects are particularly pronounced in coastal waters, it becomes urgent to understand how fish like the goldsinny will respond to global climate change, including the increasing frequency and intensity of marine heatwaves (MHWs), ocean freshening (OF) and ocean acidification (OA). To address this, we conducted a multi-stressor experiment exposing adult goldsinny to each stressor individually, as well as to all three combined. The results indicated that the goldsinny is highly affected by MHWs and extremely sensitive to a multi-stressor environment, with 34% and 53% mortality, respectively. Additionally, exposure to a MHW event, OF and multi-stressor conditions affected fish metabolism, with the highest standard metabolic- and maximum metabolic-oxygen consumption rates observed for the MHW treatment. Increases in oxidized glutathione (GSSG) and percent oxidized glutathione (% GSSG) in the livers, indicative of oxidative stress, were also seen in the MHW, OF and multi-stressor treatments. As a single stressor, OA showed no significant impacts on the measured parameters. This information is important for conservation of coastal marine environments, given the species’ important role in shallow-water habitats and for management of goldsinny or other mesopredatory fish harvested in coastal ecosystems. The sensitivity of the goldsinny wrasse to future stressors is of concern, and any potential reductions in abundance as a result of climate change may lead to cascade effects with ecosystem-wide consequences.
Echocardiographic red flags of ATTR cardiomyopathy a single centre validation
Authors: Henein Michael Y , Pilebro Björn , Lindqvist Per
Published: October 2024

Aims

Echocardiography plays an important role in suspecting the presence of transthyretin cardiomyopathy (ATTR-CM) in patients with heart failure, based on parameters proposed as ‘red flags’ for the diagnosis of ATTR-CM. We aimed to validate those measurements in a group of patients with ATTR-CM including ATTRv and ATTRwt.

Methods and results

We tested a number of echocardiographic red flags in 118 patients with confirmed diagnosis of ATTR-CM. These variables were validated against healthy controls and patients with heart failure with left ventricular hypertrophy (LVH) but not ATTR-CM. The red flag measures outside the proposed cut-off values were also revalidated. In ATTR-CM, all conventional echocardiographic parameters were significantly abnormal compared with controls. Comparing ATTR-CM and LVH, LV wall thickness, LV diameter, E velocity, and relative apical sparing (RELAPS) were all different. Eighty-three per cent of ATTR-CM patients had RELAPS > 1.0, 73% had relative wall thickness (RWT) > 0.6, 72% had LVEF > 50%, 24% had global longitudinal strain (GLS) > −13%, 33% had LVEF/GLS > 4, and 54% had increased left atrial volume index (>34 mL/m2). Forty per cent of ATTR-CM patients had stroke volume index < 30 mL/m2 and 52% had cardiac index < 2.5 L/min/m2. RELAPS, LVEF, and RWT, in order of accuracy, were the three best measures for the presence ATTR-CM in the patient cohort, who all had thick myocardium. The concomitant presence of the three disturbances was found in only 50% but the combination of RELAPS > 1.0 and RWT > 0.6 was found in 72% of the patient cohort.

Conclusion

Increased relative apical sparing proved the most accurate independent marker of the presence of ATTR-CM followed by normal LV ejection fraction and then increased relative wall thickness. The other proposed red flags for diagnosing ATTR-CM did not feature as reliable disease predictors.
How marine are Marine Stramenopiles (MAST)? A cross-system evaluation
Authors: Obiol Aleix , del Campo Javier , de Vargas Colomban , Mahé Frédéric , Massana Ramon
Published: October 2024

Marine Stramenopiles (MAST) were first described two decades ago through ribosomal RNA gene (rRNA gene) sequences from marine surveys of microbial eukaryotes. MAST comprise several independent lineages at the base of the Stramenopiles. Despite their prevalence in the ocean, the majority of MAST diversity remains uncultured. Previous studies, mainly in marine environments, have explored MAST’s cell morphology, distribution, trophic strategies, and genomics using culturing-independent methods. In comparison, less is known about their presence outside marine habitats. Here, we analyse the extensive EukBank dataset to assess the extent to which MAST can be considered marine protists. Additionally, by incorporating newly available rRNA gene sequences, we update Stramenopiles phylogeny, identifying three novel MAST lineages. Our results indicate that MAST are primarily marine with notable exceptions within MAST-2 and MAST-12, where certain subclades are prevalent in freshwater and soil habitats. In the marine water column, only a few MAST species, particularly within clades -1, -3, -4, and -7, dominate and exhibit clear latitudinal distribution patterns. Overall, the massive sequencing dataset analysed in our study confirms and partially expands the previously described diversity of MASTs groups and underscores the predominantly marine nature of most of these uncultured lineages.
Exploring fermentative metabolic response to varying exogenous supplies of redox cofactor precursors in selected wine yeast species
Authors: Tyibilika Viwe , Setati Mathabatha E , Bloem Audrey , Divol Benoit , Camarasa Carole
Published: October 2024

The use of non-Saccharomyces yeasts in winemaking is gaining traction due to their specific phenotypes of technological interest, including their unique profile of central carbon metabolites and volatile compounds. However, the lack of knowledge about their physiology hinders their industrial exploitation. The intracellular redox status, involving NAD/NADH and NADP/NADPH cofactors, is a key driver of yeast activity during fermentation, notably directing the formation of metabolites that contribute to the wine bouquet. The biosynthesis of these cofactors can be modulated by the availability of their precursors, nicotinic acid and tryptophan, and their ratio by that of thiamine. In this study, a multifactorial experiment was designed to assess the effects of these three nutrients and their interactions on the metabolic response of various wine yeast species. The data indicated that limiting concentrations of nicotinic acid led to a species-dependent decrease in intracellular NAD(H) concentrations, resulting in variations of fermentation performance and production of metabolic sinks. Thiamine limitation did not directly affect redox cofactor concentrations or balance, but influenced redox management and subsequently the production of metabolites. Overall, this study identified nicotinic acid and thiamine as key factors to consider for species-specific modulation of the metabolic footprint of wine yeasts.
The Evolution of Gene Expression Plasticity During Adaptation to Salt in Chlamydomonas reinhardtii
Authors: Harry-Paul Yeshoda Y , Lachapelle Josianne , Ness Rob W
Published: October 2024

When environmental change is rapid or unpredictable, phenotypic plasticity can facilitate adaptation to new or stressful environments to promote population persistence long enough for adaptive evolution to occur. However, the underlying genetic mechanisms that contribute to plasticity and its role in adaptive evolution are generally unknown. Two main opposing hypotheses dominate—genetic compensation and genetic assimilation. Here, we predominantly find evidence for genetic compensation over assimilation in adapting the freshwater algae Chlamydomonas reinhardtii to 36 g/L salt environments over 500 generations. More canalized genes in the high-salt (HS) lines displayed a pattern of genetic compensation (63%) fixing near or at the ancestral native expression level, rather than genetic assimilation of the salt-induced level, suggesting that compensation was more common during adaptation to salt. Network analysis revealed an enrichment of genes involved in energy production and salt-resistance processes in HS lines, while an increase in DNA repair mechanisms was seen in ancestral strains. In addition, whole-transcriptome similarity among ancestral and HS lines displayed the evolution of a similar plastic response to salt conditions in independently reared HS lines. We also found more cis-acting regions in the HS lines; however, the expression patterns of most genes did not mimic that of their inherited sequence. Thus, the expression changes induced via plasticity offer temporary relief, but downstream changes are required for a sustainable solution during the evolutionary process.