bluuebunny/crossref_metadata_2025_split huggingface dataset:
Potential of pre-diagnostic metabolomics for colorectal cancer risk assessment or early detection
Authors: Seum Teresa , Frick Clara , Cardoso Rafael , Bhardwaj Megha , Hoffmeister Michael , Brenner Hermann 
Published: October 2024

AbstractThis systematic review investigates the efficacy of metabolite biomarkers for risk assessment or early detection of colorectal cancer (CRC) and its precursors, focusing on pre-diagnostic biospecimens. Searches in PubMed, Web of Science, and SCOPUS through December 2023 identified relevant prospective studies. Relevant data were extracted, and the risk of bias was assessed with the QUADAS-2 tool. Among the 26 studies included, significant heterogeneity existed for case numbers, metabolite identification, and validation approaches. Thirteen studies evaluated individual metabolites, mainly lipids, while eleven studies derived metabolite panels, and two studies did both. Nine panels were internally validated, resulting in an area under the curve (AUC) ranging from 0.69 to 0.95 for CRC precursors and 0.72 to 1.0 for CRC. External validation was limited to one panel (AUC = 0.72). Metabolite panels and lipid-based biomarkers show promise for CRC risk assessment and early detection but require standardization and extensive validation for clinical use.
Phosphorylation of P-stalk proteins defines the ribosomal state for interaction with auxiliary protein factors
Authors: Filipek Kamil , Blanchet Sandra , Molestak Eliza , Zaciura Monika , Wu Colin Chih-Chien , Horbowicz-Drożdżal Patrycja , Grela Przemysław , Zalewski Mateusz , Kmiecik Sebastian , González-Ibarra Alan , Krokowski Dawid , Latoch Przemysław , Starosta Agata L , Mołoń Mateusz , Shao Yutian , Borkiewicz Lidia , Michalec-Wawiórka Barbara , Wawiórka Leszek , Kubiński Konrad , Socała Katarzyna , Wlaź Piotr , Cunningham Kyle W , Green Rachel , Rodnina Marina V , Tchórzewski Marek 
Published: October 2024

AbstractRibosomal action is facilitated by the orchestrated work of trans-acting factors and ribosomal elements, which are subject to regulatory events, often involving phosphorylation. One such element is the ribosomal P-stalk, which plays a dual function: it activates translational GTPases, which support basic ribosomal functions, and interacts with the Gcn2 kinase, linking the ribosomes to the ISR pathway. We show that P-stalk proteins, which form a pentamer, exist in the cell exclusively in a phosphorylated state at five C-terminal domains (CTDs), ensuring optimal translation (speed and accuracy) and may play a role in the timely regulation of the Gcn2-dependent stress response. Phosphorylation of the CTD induces a structural transition from a collapsed to a coil-like structure, and the CTD gains conformational freedom, allowing specific but transient binding to various protein partners, optimizing the ribosome action. The report reveals a unique feature of the P-stalk proteins, indicating that, unlike most ribosomal proteins, which are regulated by phosphorylation in an on/off manner, the P-stalk proteins exist in a constantly phosphorylated state, which optimizes their interaction with auxiliary factors.
Diagnosing and engineering gut microbiomes
Authors: Cappio Barazzone Elisa , Diard Médéric , Hug Isabelle , Larsson Louise , Slack Emma 
Published: October 2024

AbstractThe microbes, nutrients and toxins that we are exposed to can have a profound effect on the composition and function of the gut microbiome. Thousands of peer-reviewed publications link microbiome composition and function to health from the moment of birth, right through to centenarians, generating a tantalizing glimpse of what might be possible if we could intervene rationally. Nevertheless, there remain relatively few real-world examples where successful microbiome engineering leads to beneficial health effects. Here we aim to provide a framework for the progress needed to turn gut microbiome engineering from a trial-and-error approach to a rational medical intervention. The workflow starts with truly understanding and accurately diagnosing the problems that we are trying to fix, before moving on to developing technologies that can achieve the desired changes.
Understanding metabolic plasticity at single cell resolution
Authors: Abbate Christina C. , Hu Jason , Albeck John G. 
Published: October 2024

Abstract
It is increasingly clear that cellular metabolic function varies not just between cells of different tissues, but also within tissues and cell types. In this essay, we envision how differences in central carbon metabolism arise from multiple sources, including the cell cycle, circadian rhythms, intrinsic metabolic cycles, and others. We also discuss and compare methods that enable such variation to be detected, including single-cell metabolomics and RNA-sequencing. We pay particular attention to biosensors for AMPK and central carbon metabolites, which when used in combination with metabolic perturbations, provide clear evidence of cellular variance in metabolic function.
Symbol detection aided channel prediction in fast‐varying massive MIMO systems: Framework and performance analysis
Authors: Gao Wei , Xiao Junqiang , Liu Chuan , Peng Wei 
Published: October 2024

AbstractThe channel in massive multiple‐input multiple‐output systems is fast‐varying that the pilot signal needs to be sent frequently. To obtain timely channel state information with less pilot overheads, a symbol detection aided channel prediction scheme is proposed in this paper. Then, the prediction error lower bound of the proposed scheme within one interval of effective prediction is analysed. Besides, the approximate close‐form post‐processing signal to noise ratio is derived for zero‐forcing detector with imperfect channel predictions. Numerical simulations are implemented to verify the validity of theoretical analysis. The results show that the theoretical expressions have a close match with the real simulated performance under various simulation parameter settings. In addition, the frequency of transmitting the pilot signals can be significantly reduced when adopting this proposed method. Moreover, the application of the proposed scheme can be further expanded when combining it with channel coding, thereby greatly improving the spectrum efficiency of the system.
A hybrid variational level set model based on double Gaussian distribution fitting energy for image segmentation and bias correction
Authors: Tang Liming , Zhang Honglu , Xu Yaya , Ren Yanjun , Li Chunyan 
Published: October 2024

AbstractThe variational level set model has been widely used in image segmentation. However, its performance is significantly hindered by bias fields and noise within the images. To address these limitations, we introduce a novel hybrid variational level set model based on dual Gaussian distribution fitting (DGDF) energy in this paper. The DGDF energy integrates both local and global Gaussian distributions. The local energy is derived from the original image, while the global energy employs the corrected image, enabling effective segmentation of images with intensity inhomogeneity. Furthermore, the model demonstrates low sensitivity to weighting parameters and robust performance for noisy images. We develop an alternating iteration algorithm that combines variational methods with gradient descent to efficiently solve the proposed model. Experimental results validate the effectiveness of the model and the algorithm. In addition, the proposed model shows competitiveness on test images and three datasets compared to several state‐of‐the‐art models, including other variational level set models and deep learning‐based techniques.
DMA‐Net: A dual branch encoder and multi‐scale cross attention fusion network for skin lesion segmentation
Authors: Zhai Guangyao , Wang Guanglei , Shang Qinghua , Li Yan , Wang Hongrui 
Published: October 2024

AbstractAutomatic segmentation of skin lesion is an important step in computer‐aided diagnosis. However, due to the significant variations in the size and shape of the lesion areas, as well as the low contrast with normal skin tissue, the boundaries are not clearly distinguishable, leading to a high possibility of incorrect segmentation. Therefore, this task is highly challenging. To overcome these difficulties, this paper proposes a medical image segmentation architecture named dual branch encoder and multi‐scale cross attention fusion network, which includes a dual‐branch encoder based on convolutional neural network and an improved channel‐enhanced Mamba to comprehensively extract local and global information from dermoscopy images. Additionally, to enhance the feature interaction and fusion of local and global information, a multi‐scale cross attention fusion module is adopted to cross‐merge features in different directions and at different scales, maximizing the advantages of the dual‐branch encoder and achieving precise segmentation of skin lesions. Extensive experiments are conducted on three public skin lesion datasets: ISIC‐2018, ISIC‐2017, and ISIC‐2016, to verify the effectiveness and superiority of the proposed method. The dice similarity coefficient scores on the three datasets reached 81.77%, 81.68% and 85.60%, respectively, surpassing most state‐of‐the‐art methods.
Identification of transmission line voltage sag sources based on multi‐location information convolutional transformer
Authors: Li Qionglin , Zheng Chen , Liu Shuming , Dai Shuangyin , Zhang Bo , Tang Yuzheng , Wang Yi 
Published: October 2024

AbstractConventional methods for identifying voltage sag sources are difficult to categorize accurately due to the complexity of transmission lines and the influence of noise. In order to solve the problem of difficulty in recognizing voltage sag sources of transmission lines under different locations, this paper proposes a new method for transmission line fault diagnosis based on modified wavelet denoising and multi‐location information convolution transformer. The improved wavelet denoising method proposed in this paper solves the problems of discontinuity and bias of the traditional wavelet denoising method, and is able to better reconstruct the original voltage signal in a strong noise environment. In addition, multi‐location information convolution transformer adopts a new model combining multi‐location information convolution and multi‐scale convolution transformer, which realizes the combination of global information and local context information capturing ability under multi‐location faults. This paper validates the method through simulation experiments and practical situations, and the results show that the method can well classify and identify the type and location of voltage sag sources in transmission lines.
Origin of the spectral features observed in the cosmic-ray spectrum
Authors: Recchia S. , Gabici S. 
Published: October 2024

Context. Recent measurements reveal the presence of several features in the cosmic-ray (CR) spectrum. In particular, the proton and helium spectra exhibit a spectral hardening at ≈300 GV and a spectral steepening at ≈15 TV, followed by the well-known knee-like feature at ≈3 PV. The spectra of heavier nuclei also harden at ≈300 GV, while no claim can be currently made about the presence of the ≈15 TV softening, due to low statistics. In addition, the B/C ratio also exhibits a hardening at ≈100 GeV/n and seems to be rather shallow at ≈1 TeV/n
Aims. We propose a possible explanation of the observed spectral features in the framework of a composite diffusion scenario and considering different classes of sources.
Methods. The proposed scenario is based on two assumptions. First, in the Galactic disk, where magnetic field lines are mainly oriented along the Galactic plane, particle scattering is assumed to be very inefficient. Therefore, the transport of CRs from the disk to the halo is set by the magnetic field line random walk induced by large-scale turbulence. Second, we propose that the spectral steepening at ≈15 TV is related to the typical maximum rigidity reached in the acceleration of CRs by the majority of supernova remnants, while we assume that only a fraction of sources, contributing to ≈10 − 20% of the CR population, can accelerate particles up to ∼PV rigidities.
Results. Within this framework we show that it is possible to reproduce the proton and helium spectra from GV to multi-PV; the p/He ratio; the spectra of CRs from lithium to iron; the p̄ flux and the p̄/p ratio; and the abundance ratios B/C, B/O, C/O, Be/C, Be/O, and Be/B. We also discuss the 10Be/9Be ratio in view of the recent AMS02 preliminary measurements.
Observational studies of S-bearing molecules in massive star-forming regions
Authors: Luo R. , Wang J. Z. , Zhang X. , Quan D. H. , Jiang X. J. , Li J. , Gou Q. , Li Y. Q. , Xu Y. N. , Zheng S. Q. , Ou C. , Liu Y. J. 
Published: October 2024

Context. S-bearing molecules are powerful tools for determining the physical conditions inside a massive star-forming region. The abundances of S-bearing molecules, including H2S, H2CS, and HCS+, are highly dependent on physical and chemical changes, which means that they are good tracers of the evolutionary stage of massive star formation.
Aims. We present observational results of H2S 110-101, H234S 110-101, H2CS 514-414, HCS+ 4-3, SiO 4-3, HC3N 19-18, and C18O 1-0 toward a sample of 51 late-stage massive star-forming regions, and study the relationships between H2S, H2 CS, HCS+, and SiO in hot cores. We discuss the chemical connections of these S-bearing molecules based on the relations between the relative abundances in our sources.
Methods. H234S 110-101, as the isotopic line of H2S 110-101, was used to correct the optical depths ofH2S 110-101. Beam-averaged column densities of all molecules were calculated, as were the abundances of H2S, H2CS, and HCS+ relative to H2, which were derived from C18 O. Results from a chemical model that included gas, dust grain surface, and icy mantle phases, were compared with the observed abundances of H2S, H2CS, and HCS+ molecules.
Results. H2S 110-101, H234S 110-101, H2CS 514-414, HCS+ 4-3, andHC3N 19-18 were detected in 50 of the 51 sources, SiO 4-3 was detected in 46 sources, and C18O 1-0 was detected in all sources. The Pearson correlation coefficients between H2CS and HCS+ normalized by H2 and H2S are 0.94 and 0.87, respectively, and a tight linear relationship with a slope of 1.00 and 1.09 is found; this relationship is 0.77 and 0.98 between H2S and H2CS and 0.76 and 0.97 between H2S and HCS+. The full widths at half maxima of H234S 110-101, H2CS 514-414, HCS+ 4-3, and HC3N 19-18 in each source are similar to each other, which indicates that they may trace similar regions. By comparing the observed abundance with model results, we see that there is one possible time (2−3 × 105 yr) a which each source in the model matches the measured abundances of H2S, H2CS, and HCS+. The abundances of HCS+, H2CS, and H2S increase with the SiO abundance in these sources, which implies that shock chemistry may be playing a large role.
Conclusions. The close abundance relation of H2S, H2CS, and HCS+ and the similar line widths in observational results indicate that these three molecules could be chemically linked, with HCS+ and H2CS the most correlated. The comparison of the observational results with chemical models shows that the abundances can be reproduced for almost all the sources at a specific time. The observational results, including the abundances in these sources need to be considered in further modeling of H2S, H2CS, and HCS+ in hot cores with shock chemistry.
Assessing methods for telluric removal on atmospheric retrievals of high-resolution optical exoplanetary transmission spectra
Authors: Maguire Cathal , Sedaghati Elyar , Gibson Neale P. , Smette Alain , Pino Lorenzo 
Published: October 2024

Context. Recent advancements in ultra-stable ground-based high-resolution spectrographs have propelled ground-based astronomy to the forefront of exoplanet detection and characterisation. However, the resultant transmission and emission spectra of exoplanetary atmospheres are inevitably contaminated by telluric absorption and emission lines due to the light’s transmission through the Earth’s atmosphere above the observatory. Retrieving accurate atmospheric parameters depends on accurate modelling and removal of this telluric contamination while preserving the faint underlying exoplanet signal.
Aims. There exist many methods to model telluric contamination, whether directly modelling the Earth’s transmission spectrum via radiative transfer modelling, or using a principal component analysis (PCA)-like reconstruction to fit the time-invariant features of a spectrum, and removing these models from the observations. We aimed to assess the efficacy of these various telluric removal methods in preserving the underlying exoplanetary spectra.
Methods. We compared two of the most common telluric modelling and removal methods, MOLECFIT and the PCA-like algorithm SYSREM, using planetary transmission spectra injected into three high-resolution optical observations taken with ESPRESSO. These planetary signals were injected at orbital periods of P =2 days and P = 12 days, resulting in differing changes in radial velocity during transit. We then retrieved various injected atmospheric model parameters in order to determine the efficacy of the telluric removal methods, as well as their effect on the transmission spectra of exoplanets with varying orbital architectures.
Results. For the close-in, high velocity injected signal, we found that SYSREM performed better for species that are also present in the Earth’s atmosphere-with accurate and precise retrieval of atmospheric abundances and T-P profiles, across each of the datasets. As we moved to slower moving signals at larger orbital separations, for one of the three datasets, SYSREM dampened the planetary H2O signal, leaving the retrieved abundance value unconstrained. In contrast, the H2O signal was preserved for the telluric modelling method, MOLECFIT. However, this behaviour was not ubiquitous across all three of the injected datasets, with another dataset showing a more precise H2O/Fe ratio when preprocessed with SYSREM. These conflicts highlight the importance of testing individual high-resolution dataset reduction routines independently to ensure real exoplanetary signals are preserved.
Fast magnetohydrodynamic oscillations of a coronal loop embedded in a potential coronal arcade
Authors: Lopin I. P. 
Published: October 2024

Context. Observations indicate variable widths exhibited by fan coronal loops and flare loops that tend to widen towards the apex. Short-period, quasi-periodic pulsations in solar flares are often interpreted in terms of the fast-sausage oscillations of flare loops and the collective vertical vibrations of arcade loops are attributed with the vertical kink mode. Both phenomena are used as a seismological tool to estimate the physical parameters in the corona.
Aims. We performed an analytical study of fast sausage and kink oscillations in coronal loops, given the effects of loop curvature, expansion, and Alfvén speed variation.
Methods. We modelled a coronal loop as a dense expanding curved magnetic slab embedded within a potential coronal arcade, using a zero-β plasma limit. We obtained the dispersion relation that governs fast waves in the model and studied it both numerically and analytically.
Results. The effects of loop expansion and variable Alfvén speed reduce the cut-off frequency and increase the cut-off wavenumbers for fast sausage and kink waves. Moreover, the principal vertical kink mode has a cut-off and strongly attenuates in the leaky regime. The frequency increase is found to be minor for the global sausage mode both in the trapped and leaky regimes, with a frequency shift within a few percent. We found that in our model, where the Alfvén speed increases from the footpoints to the loop top, the spatial profile of the longitudinal fundamental is broadened and the antinodes of the first overtone are shifted towards the footpoints.
Conclusions. Using the classical expression for the cut-off wavenumber of the global sausage mode in a straight waveguide results in an underestimation of the density contrast constraint in flare loops. Instead, the suggested formula accounting for variations in loop widths provides more accurate results. The frequency of the global sausage mode can be correctly determined with the straight slab model.
Experimental narratives: A comparison of human crowdsourced storytelling and AI storytelling
Authors: Beguš Nina 
Published: October 2024

AbstractThe paper proposes a framework that combines behavioral and computational experiments employing fictional prompts as a novel tool for investigating cultural artifacts and social biases in storytelling both by humans and generative AI. The study analyzes 250 stories authored by crowdworkers in June 2019 and 80 stories generated by GPT-3.5 and GPT-4 in March 2023 by merging methods from narratology and inferential statistics. Both crowdworkers and large language models responded to identical prompts about creating and falling in love with an artificial human. The proposed experimental paradigm allows a direct and controlled comparison between human and LLM-generated storytelling. Responses to the Pygmalionesque prompts confirm the pervasive presence of the Pygmalion myth in the collective imaginary of both humans and large language models. All solicited narratives present a scientific or technological pursuit. The analysis reveals that narratives from GPT-3.5 and particularly GPT-4 are more progressive in terms of gender roles and sexuality than those written by humans. While AI narratives with default settings and no additional prompting can occasionally provide innovative plot twists, they offer less imaginative scenarios and rhetoric than human-authored texts. The proposed framework argues that fiction can be used as a window into human and AI-based collective imaginary and social dimensions.
On the role of fiducial structures in minisuperspace reduction and quantum fluctuations in LQC
Authors: Mele Fabio M , Münch Johannes 
Published: October 2024

Abstract
In spatially non-compact homogeneous minisuperpace models, spatial integrals in the Hamiltonian and symplectic form must be regularised by confining them to a finite volume Vo
, known as the fiducial cell. As this restriction is unnecessary in the complete field theory before homogeneous reduction, the physical significance of the fiducial cell has been largely debated, especially in the context of (loop) quantum cosmology. Understanding the role of Vo
is in turn essential for assessing the minisuperspace description’s validity and its connection to the full theory. In this work we present a systematic procedure for the field theory reduction to spatially homogeneous and isotropic minisuperspaces within the canonical framework and apply it to both a massive scalar field theory and gravity. Our strategy consists in implementing spatial homogeneity via second-class constraints for the discrete field modes over a partitioning of the spatial slice into countably many disjoint cells. The reduced theory’s canonical structure is then given by the corresponding Dirac bracket. Importantly, the latter can only be defined on a finite number of cells homogeneously patched together. This identifies a finite region, the fiducial cell, whose physical size acquires then a precise meaning already at the classical level as the scale over which homogeneity is imposed. Additionally, the procedure allows us to track the information lost during homogeneous reduction and how the error depends on Vo
. We then move to the quantisation of the classically reduced theories, focusing in particular on the relation between the theories for different Vo
, and study the implications for statistical moments, quantum fluctuations, and semiclassical states. In the case of a quantum scalar field, a subsector of the full quantum field theory where the results from the ‘first reduced, then quantised’ approach can be reproduced is identified and the conditions for this to be a good approximation are also determined.