bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of narrow-wide row planting patterns on canopy photosynthetic characteristics, bending resistance and yield of soybean in maize‒soybean intercropping systems
Authors: Gu Yan , Zheng Haoyuan , Li Shuang , Wang Wantong , Guan Zheyun , Li Jizhu , Mei Nan , Hu Wenhe 
Published: April 2024

AbstractWith the improvements in mechanization levels, it is difficult for the traditional intercropping planting patterns to meet the needs of mechanization. In the traditional maize‒soybean intercropping, maize has a shading effect on soybean, which leads to a decrease in soybean photosynthetic capacity and stem bend resistance, resulting in severe lodging, which greatly affects soybean yield. In this study, we investigated the effects of three intercropping ratios (four rows of maize and four rows of soybean; four rows of maize and six rows of soybean; six rows of maize and six rows of soybean) and two planting patterns (narrow-wide row planting pattern of 80–50 cm and uniform-ridges planting pattern of 65 cm) on soybean canopy photosynthesis, stem bending resistance, cellulose, hemicellulose, lignin and related enzyme activities. Compared with the uniform-ridge planting pattern, the narrow-wide row planting pattern significantly increased the LAI, PAR, light transmittance and compound yield by 6.06%, 2.49%, 5.68% and 5.95%, respectively. The stem bending resistance and cellulose, hemicellulose, lignin and PAL, TAL and CAD activities were also significantly increased. Compared with those under the uniform-ridge planting pattern, these values increased by 7.74%, 3.04%, 8.42%, 9.76%, 7.39%, 10.54% and 8.73% respectively. Under the three intercropping ratios, the stem bending resistance, cellulose, hemicellulose, lignin content and PAL, TAL, and CAD activities in the M4S6 treatment were significantly greater than those in the M4S4 and M6S6 treatments. Compared with the M4S4 treatment, these variables increased by 12.05%, 11.09%, 21.56%, 11.91%, 18.46%, 16.1%, and 16.84%, respectively, and compared with the M6S6 treatment, they increased by 2.06%, 2.53%, 2.78%, 2.98%, 8.81%, 4.59%, and 4.36%, respectively. The D-M4S6 treatment significantly improved the lodging resistance of soybean and weakened the negative impact of intercropping on soybean yield. Therefore, based on the planting pattern of narrow-wide row maize‒soybean intercropping planting pattern, four rows of maize and six rows of soybean were more effective at improving the lodging resistance of soybean in the semiarid region of western China.
A dense matching method for remote sensing images fused with CPS denoising
Authors: Zhu Bo , Tan Xiao , Li Houpu 
Published: April 2024

AbstractDense matching of remote sensing images is crucial for 3D reconstruction. This study proposes an enhanced dense matching method employing the CPS image denoising algorithm, aiming to boost the SGM algorithm's accuracy and efficiency in remote sensing image matching. The stereo image pair's quality is evaluated using the PSNR index, and a decision-making criterion based on the CPS algorithm is incorporated to determine the need for denoising. Preprocessing steps, including image cropping and pixel coordinate transformation, significantly reduce computational requirements. An epipolar line model, minimizing the disparity between two pixels, is used for calculations. This model is employed to construct an epipolar image, enhancing the accuracy and efficiency of the process. The study conducted experimental validation and analysis of the mismatch rate, running time, and denoising effect of the algorithm using the Middlebury 2021 stereo datasets. Additionally, the matching results of the World-View3 satellite stereo image pairs were visualized and analyzed. The experimental results indicate that the proposed algorithm reduces the average mismatch rate by 13.1% and increases the running speed by about 3 to 4 times compared to the SGBM algorithm. Specifically, the denoising effect reduces the mismatch rate of the reconstructed image by an average of 8.97%. The results indicate that the CPS method effectively addresses dense matching challenges in the presence of image blur and noise, thereby improving the operational efficiency and accuracy of the dense matching algorithm.
Uncovering uncharacterized binding of transcription factors from ATAC-seq footprinting data
Authors: Schultheis Hendrik , Bentsen Mette , Heger Vanessa , Looso Mario 
Published: April 2024

AbstractTranscription factors (TFs) are crucial epigenetic regulators, which enable cells to dynamically adjust gene expression in response to environmental signals. Computational procedures like digital genomic footprinting on chromatin accessibility assays such as ATACseq can be used to identify bound TFs in a genome-wide scale. This method utilizes short regions of low accessibility signals due to steric hindrance of DNA bound proteins, called footprints (FPs), which are combined with motif databases for TF identification. However, while over 1600 TFs have been described in the human genome, only ~ 700 of these have a known binding motif. Thus, a substantial number of FPs without overlap to a known DNA motif are normally discarded from FP analysis. In addition, the FP method is restricted to organisms with a substantial number of known TF motifs. Here we present DENIS (DE Novo motIf diScovery), a framework to generate and systematically investigate the potential of de novo TF motif discovery from FPs. DENIS includes functionality (1) to isolate FPs without binding motifs, (2) to perform de novo motif generation and (3) to characterize novel motifs. Here, we show that the framework rediscovers artificially removed TF motifs, quantifies de novo motif usage during an early embryonic development example dataset, and is able to analyze and uncover TF activity in organisms lacking canonical motifs. The latter task is exemplified by an investigation of a scATAC-seq dataset in zebrafish which covers different cell types during hematopoiesis.
Integrating tumor and healthy epithelium in a micro-physiology multi-compartment approach to study renal cell carcinoma pathophysiology
Authors: Somova Maryna , Simm Stefan , Padmyastuti Adventina , Ehrhardt Jens , Schoon Janosch , Wolff Ingmar , Burchardt Martin , Roennau Cindy , Pinto Pedro Caetano 
Published: April 2024

AbstractThe advent of micro-physiological systems (MPS) in biomedical research has enabled the introduction of more complex and relevant physiological into in vitro models. The recreation of complex morphological features in three-dimensional environments can recapitulate otherwise absent dynamic interactions in conventional models. In this study we developed an advanced in vitro Renal Cell Carcinoma (RCC) that mimics the interplay between healthy and malignant renal tissue. Based on the TissUse Humimic platform our model combines healthy renal proximal tubule epithelial cells (RPTEC) and RCC. Co-culturing reconstructed RPTEC tubules with RCC spheroids in a closed micro-perfused circuit resulted in significant phenotypical changes to the tubules. Expression of immune factors revealed that interleukin-8 (IL-8) and tumor necrosis factor-alfa (TNF-α) were upregulated in the non-malignant cells while neutrophil gelatinase-associated lipocalin (NGAL) was downregulated in both RCC and RPTEC. Metabolic analysis showed that RCC prompted a shift in the energy production of RPTEC tubules, inducing glycolysis, in a metabolic adaptation that likely supports RCC growth and immunogenicity. In contrast, RCC maintained stable metabolic activity, emphasizing their resilience to external factors. RNA-seq and biological process analysis of primary RTPTEC tubules demonstrated that the 3D tubular architecture and MPS conditions reverted cells to a predominant oxidative phosphorylate state, a departure from the glycolytic metabolism observed in 2D culture. This dynamic RCC co-culture model, approximates the physiology of healthy renal tubules to that of RCC, providing new insights into tumor-host interactions. Our approach can show that an RCC-MPS can expand the complexity and scope of pathophysiology and biomarker studies in kidney cancer research.
Optimization of hepatological clinical guidelines interpretation by large language models: a retrieval augmented generation-based framework
Authors: Kresevic Simone , Giuffrè Mauro , Ajcevic Milos , Accardo Agostino , Crocè Lory S. , Shung Dennis L. 
Published: April 2024

AbstractLarge language models (LLMs) can potentially transform healthcare, particularly in providing the right information to the right provider at the right time in the hospital workflow. This study investigates the integration of LLMs into healthcare, specifically focusing on improving clinical decision support systems (CDSSs) through accurate interpretation of medical guidelines for chronic Hepatitis C Virus infection management. Utilizing OpenAI’s GPT-4 Turbo model, we developed a customized LLM framework that incorporates retrieval augmented generation (RAG) and prompt engineering. Our framework involved guideline conversion into the best-structured format that can be efficiently processed by LLMs to provide the most accurate output. An ablation study was conducted to evaluate the impact of different formatting and learning strategies on the LLM’s answer generation accuracy. The baseline GPT-4 Turbo model’s performance was compared against five experimental setups with increasing levels of complexity: inclusion of in-context guidelines, guideline reformatting, and implementation of few-shot learning. Our primary outcome was the qualitative assessment of accuracy based on expert review, while secondary outcomes included the quantitative measurement of similarity of LLM-generated responses to expert-provided answers using text-similarity scores. The results showed a significant improvement in accuracy from 43 to 99% (p < 0.001), when guidelines were provided as context in a coherent corpus of text and non-text sources were converted into text. In addition, few-shot learning did not seem to improve overall accuracy. The study highlights that structured guideline reformatting and advanced prompt engineering (data quality vs. data quantity) can enhance the efficacy of LLM integrations to CDSSs for guideline delivery.
Detection of ribonucleotides embedded in DNA by Nanopore sequencing
Authors: Grasso Lavinia , Fonzino Adriano , Manzari Caterina , Leonardi Tommaso , Picardi Ernesto , Gissi Carmela , Lazzaro Federico , Pesole Graziano , Muzi-Falconi Marco 
Published: April 2024

AbstractRibonucleotides represent the most common non-canonical nucleotides found in eukaryotic genomes. The sources of chromosome-embedded ribonucleotides and the mechanisms by which unrepaired rNMPs trigger genome instability and human pathologies are not fully understood. The available sequencing technologies only allow to indirectly deduce the genomic location of rNMPs. Oxford Nanopore Technologies (ONT) may overcome such limitation, revealing the sites of rNMPs incorporation in genomic DNA directly from raw sequencing signals. We synthesized two types of DNA molecules containing rNMPs at known or random positions and we developed data analysis pipelines for DNA-embedded ribonucleotides detection by ONT. We report that ONT can identify all four ribonucleotides incorporated in DNA by capturing rNMPs-specific alterations in nucleotide alignment features, current intensity, and dwell time. We propose that ONT may be successfully employed to directly map rNMPs in genomic DNA and we suggest a strategy to build an ad hoc basecaller to analyse native genomes.
Multiscale X-ray phase-contrast CT unveils the evolution of bile infarct in obstructive biliary disease
Authors: Xin Xiaohong , Jian Jianbo , Fan Xu , Qi Beining , Zhao Yuanyuan , Lv Wenjuan , Zhao Yuqing , Zhao Xinyan , Hu Chunhong 
Published: April 2024

AbstractBile infarct is a pivotal characteristic of obstructive biliary disease, but its evolution during the disease progression remains unclear. Our objective, therefore, is to explore morphological alterations of the bile infarct in the disease course by means of multiscale X-ray phase-contrast CT. Bile duct ligation is performed in mice to mimic the obstructive biliary disease. Intact liver lobes of the mice are scanned by phase-contrast CT at various resolution scales. Phase-contrast CT clearly presents three-dimensional (3D) images of the bile infarcts down to the submicron level with good correlation with histological images. The CT data illustrates that the infarct first appears on day 1 post-BDL, while a microchannel between the infarct and hepatic sinusoids is identified, the number of which increases with the disease progression. A 3D model of hepatic acinus is proposed, in which the infarct starts around the portal veins (zone I) and gradually progresses towards the central veins (zone III) during the disease process. Multiscale phase-contrast CT offers the comprehensive analysis of the evolutionary features of the bile infarct in obstructive biliary disease. During the course of the disease, the bile infarcts develop infarct-sinusoidal microchannels and gradually occupy the whole liver, promoting the disease progression.
Spatial partitioning of terrestrial precipitation reveals varying dataset agreement across different environments
Authors: Markonis Yannis , Vargas Godoy Mijael Rodrigo , Pradhan Rajani Kumar , Pratap Shailendra , Thomson Johanna Ruth , Hanel Martin , Paschalis Athanasios , Nikolopoulos Efthymios , Papalexiou Simon Michael 
Published: April 2024

AbstractThe study of the water cycle at planetary scale is crucial for our understanding of large-scale climatic processes. However, very little is known about how terrestrial precipitation is distributed across different environments. In this study, we address this gap by employing a 17-dataset ensemble to provide, for the first time, precipitation estimates over a suite of land cover types, biomes, elevation zones, and precipitation intensity classes. We estimate annual terrestrial precipitation at approximately 114,000 ± 9400 km3, with about 70% falling over tropical, subtropical and temperate regions. Our results highlight substantial inconsistencies, mainly, over the arid and the mountainous areas. To quantify the overall discrepancies, we utilize the concept of dataset agreement and then explore the pairwise relationships among the datasets in terms of “genealogy”, concurrency, and distance. The resulting uncertainty-based partitioning demonstrates how precipitation is distributed over a wide range of environments and improves our understanding on how their conditions influence observational fidelity.
Rapid diagnosis of bloodstream infections using a culture-free phenotypic platform
Authors: Shi Xuyang , Sharma Shivani , Chmielewski Richard A. , Markovic Mario J. , VanEpps J. Scott , Yau Siu-Tung 
Published: April 2024

Abstract
Background
Bloodstream infections (BSIs) are a life-threatening acute medical condition and current diagnostics for BSIs suffer from long turnaround time (TAT). Here we show the validation of a rapid detection-analysis platform (RDAP) for the diagnosis of BSIs performed on clinical blood samples

Methods
The validation was performed on a cohort of 59 clinical blood samples, including positive culture samples, which indicated confirmed bloodstream infections, and negative culture samples. The bacteria in the positive culture samples included Gram-positive and Gram-negative pathogenic species. RDAP is based on an electrochemical sandwich immunoassay with voltage-controlled signal amplification, which provides an ultra-low limit of detection (4 CFU/mL), allowing the platform to detect and identify bacteria without requiring culture and perform phenotypic antibiotic susceptibility testing (AST) with only 1–2 h of antibiotic exposure. The preliminary diagnostic performance of RDAP was compared with that of standard commercial diagnostic technologies.

Results
Using a typical clinical microbiology laboratory diagnostic workflow that involved sample culture, agar plating, bacteria identification using matrix-assisted laser desorption ionization time-of-flight (MALDI TOF) mass spectrometry, and AST using MicroScan as a clinical diagnostic reference, RDAP showed diagnostic accuracy of 93.3% and 95.4% for detection-identification and AST, respectively. However, RDAP provided results at least 15 h faster.

Conclusions
This study shows the preliminary feasibility of using RDAP to rapidly diagnose BSIs, including AST. Limitations and potential mitigation strategies for clinical translation of the present RDAP prototype are discussed. The results of this clinical feasibility study indicate an approach to provide near real-time diagnostic information for clinicians to significantly enhance the treatment outcome of BSIs.
Spectroflat: A generic spectrum and flat-field calibration library for spectro-polarimetric data
Authors: Hölken J. , Doerr H.-P. , Feller A. , Iglesias F. A. 
Published: April 2024

Context. Flat-fielding spectro-polarimetric data with one spatial and one spectral dimension is inherently difficult as the imprint of the spectral lines needs to be separated from other wavelength-dependent instrumental effect (e.g., fringes or prefilter profiles) and wavelength-independent effects (e.g., dust and sensor response). Current approaches for spectrometers are often based on moving the grating or they depend on optical models and/or on lab calibration data. They are also limited to small spectral regions and are instrument-specific. Approaches that would be suitable for polarimeters have not been reported yet.Aims. We present an approach that allows for flat-field calibration data to be to obtained for diffraction-grating-based, long-slit spec-trographs combined with temporally modulated polarimetry from high-resolution solar telescopes. This approach is based on nominal flat-fielding procedures performed during the instrument’s science operations.Methods. We performed a precise and field-dependent correction of the spectrographic distortion effect (resulting in curved spectral lines, typically denoted as a “smile” effect) to ensure the orthogonality of the spectral and spatial dimensions. We identified distortions by tracking the position of multiple spectral lines within the full spectral field of view. From the raw modulated flats, we then removed the solar line imprints and derived separate flat-fields for sensor and slit dust features. Optionally, wavelength calibration and continuum correction can be included in this process.Results. We have created generic Python libraries that can be plugged into existing Python-based data reduction pipelines or used as a standalone calibration tool. We show that for spectrographs covering many spectral lines, a correction of the smile distortion based on optical models alone is not sufficient. Our results demonstrate a suppression of fringes, sensor artifacts, and fixed-pattern imprints in demodulated data by one order of magnitude. For intensity images, the photon noise level can be closely attained after calibration. Our correction works across the full spectral range. The algorithm was tested for different wavelength regimes with emission (EUV range) or absorption (near-UV, VIS, IR range) spectra, on data acquired with ground-based (SST/TRIPPLE-SP, GREGOR/GRIS), balloon-borne (SUNRISE-III/SUSI), and space-based (SolO/SPICE) instruments. The data calibrated with our method offer robust and precise inversion results.Conclusions. We have extended existing spectroscopic flat-field techniques to modern instruments with large imaging sensors covering many spectral lines simultaneously, and with polarimetric capabilities, where methods described so far are not adequate. We believe that our method is applicable as a standard calibration approach for most modern high resolution large-FOV, long-slit spectrographs – both with and without polarimetric capabilities.
The VELOCE modulation zoo
Authors: Netzel H. , Anderson R. I. , Viviani G. 
Published: April 2024

Context. The photometric observations from the recent decade revolutionized our view on classical pulsators. Low-amplitude signals have been detected photometrically in addition to the dominant high-amplitude radial mode pulsations in many RR Lyrae stars and classical Cepheids. First-overtone pulsators with an additional low-amplitude signal at a period ratio of around 0.61 with the main mode, the so-called 0.61 stars, form the most populous group among these stars. The nature of this signal has been attributed to non-radial pulsations. Another mysterious group are stars in which the additional signal forms a period ratio of around 0.68. These are the 0.68 stars. The origin of the signal remains unknown.
Aims. Here, we search for similar phenomena in spectroscopic observations of first-overtone classical Cepheids collected as part of the VELOCE project.
Methods. We performed a frequency analysis of several parameters derived from cross-correlation functions (CCFs), including radial velocity, the full width at half maximum, the bisector inverse span, and the CCF depth (contrast). Using standard pre-whitening, we searched for additional low-amplitude signals. We identified the location of these stars in various sequences of the Petersen diagram.
Results. We detect additional signals in four first-overtone classical Cepheids: BG Cru, QZ Nor, V0391 Nor, and V0411 Lac. We classified BG Cru, QZ Nor, and V0391 Nor as 0.61 stars based on their period ratios. V0411 Lac, however, exhibits a ratio of 0.68 between the two modes, and the additional signal has a longer period. This type of multi-periodicity remains unexplained.
Conclusions. VELOCE CCFs yield the first spectroscopic detections of non-radial pulsation modes in classical Cepheids. This opens an asteroseismic window for pursuing a more detailed understanding of these important stars. While the 0.61 signal of BG Cru, QZ Nor, and V0391 Nor is understood to originate from non-radial modes of moderate degrees, the 0.68 signal of V0411 Lac still lacks a physical explanation.
Gray two-moment neutrino transport: Comprehensive tests and improvements for supernova simulations
Authors: Andresen Haakon , O’Connor Evan P. , Andersen Oliver Eggenberger , Couch Sean M. 
Published: April 2024

Aims. In this work we extended an energy-integrated neutrino transport method to facilitate efficient, yet precise, modeling of compact astrophysical objects. We particularly focus on core-collapse supernovae.
Methods. We implemented a gray neutrino-transport framework from the literature into FLASH and performed a detailed evaluation of its accuracy in core-collapse supernova simulations. Based on comparisons with results from simulations using energy-dependent neutrino transport, we incorporated several improvements to the original scheme.
Results. Our analysis shows that our gray neutrino transport method successfully reproduces key aspects from more complex energy-dependent transport across a variety of progenitors and equations of state. We find both qualitative and reasonable quantitative agreement with multi-group M1 transport simulations. However, the gray scheme tends to slightly favor shock revival. In terms of gravitational wave and neutrino signals, there is a good alignment with the energy-dependent transport, although we find 15–30% discrepancies in the average energy and luminosity of heavy-lepton neutrinos. Simulations using the gray transport are around four times faster than those using energy-dependent transport.