bluuebunny/crossref_metadata_2025_split huggingface dataset:
Is it a risk factor, a predictor, or even both? The multiple faces of multivariable regression analysis
Authors: Groenwold Rolf H H , Dekkers Olaf M 
Published: January 2023

Abstract
The medical research literature is abundant with regression analyses that include multiple covariates, so-called multivariable regression models. Despite their common application, the interpretation of their results is not always clear or claimed interpretations are not justified. To outline the distinctions between different interpretations, we describe several possible research objectives for which a multivariable regression analysis might be an appropriate way of analyzing the data. In addition, we describe caveats in the interpretation of results of multivariable regression analysis.
Quantifying diets for small pelagic fish: effects of weight versus occurrence methods and sampling effort
Authors: Mousing Erik Askov , Planque Benjamin , Arneberg Per , Bjørdal Vilde Regine , Keulder-Stenevik Felicia , Liebig Penny Lee , Mørk Herdis Langøy , Skern-Mauritzen Mette 
Published: January 2023

AbstractIn the Norwegian Sea, assessment of diet composition relies on annual cruise activity combined with visual identification and weight determination of prey from fish stomachs. This weight-based method is labour intensive, and suggestions to reduce cost include moving from the weight-based to the occurrence-based method and/or reducing sampling effort. Studies have suggested that the occurrence-based method may be more robust while providing similar results as the weight-based method. Here we re-analyse data from &gt;14.000 stomachs for herring, mackerel, and blue whiting. We compare diet composition estimates and quantify the uncertainty using both methods. We also quantify the impact of reducing sampling effort (number of trawl stations and fish per station) on the diet uncertainties. Our results confirm that occurrence-based estimates are more precise than those based on weight. In addition, they are better at capturing year-to-year fluctuations. The occurrence-based method provides similar results to the weight-based method. Differences between methods arise primarily from disparities in the mean weight of prey in stomachs. Decreasing the number of stations sampled leads to increased uncertainty, while reducing the sampling effort from 10 to 5 fish per station has little impact on uncertainty estimates. These results provide quantified insights to guide future diet monitoring programmes.
Enterococcus faeciumfrom chicken feces improves chicken immune response and alleviatesSalmonellainfections: a pilot study
Authors: Khalifa Ashraf , Ibrahim Hairul Islam Mohamed 
Published: January 2023

AbstractProbiotics reduce the emergence of antibiotic resistance in the livestock industry. Chicken feces are reservoirs of beneficial microbiomes. The aim of this study was to isolate putative probiotics from the intestinal contents of broiler chickens. Five fecal samples were collected from two poultry farms in Al-Ahsa, Saudi Arabia. Of the 11 morphologically distinct isolates from chicken feces (CF) samples, five isolates displayed positive reactions to Gram staining, catalase, and oxidase tests, and reacted negatively to a hemolytic assay. The isolates CF1, CF2, CF3, CF8, and CF11 were selected for further analysis of probiotic characterization, gastric survival capacity, antibiotic susceptibility, and antimicrobial activity against poultry infected with Salmonella enterica. CF2 and CF11 showed the highest hydrophobic values (&gt; 51% hydrophobic nature). CF1, CF2, and CF11 showed potent antimicrobial activities. The active isolate CF2 was identified as Enterococcus faecium by 16s rRNA sequencing and showed a genetic similarity of 99.1%. An in vivo study was conducted using a chicken model. Enterococcus faecium-fed chickens showed an improved body weight and a lower mortality rate (17–34%). Salmonella enterica colony-forming unit (CFU) invasion in the spleen and thymus was significantly reduced in the E. faecium-fed chickens. The fecal S. enterica load was reduced from CFU 6.8 to 3.9/g in oral-administered E. faecium-fed chickens. Enterococcus faecium-fed chickens showed increased levels (P &lt; 0.01) of butyric acid and reduced levels (P &lt; 0.01) of intestinal interleukin 1 beta, C-reactive protein, and interferon gamma levels compared to those in the S. enterica-infected chicken group. In addition, E. faecium showed significant binding to Caco-2 epithelial cells in vitro and inhibited S. enterica colonization, indicating co-aggregation of E. faecium in epithelial cells. These results revealed that an E. faecium formulation could prevent bacterial infection and improve the quality of broiler chickens.
Numerical investigation on seismoelectric wave fields in porous media: porosity and permeability
Authors: Peng Rong , Huang Xingxing , Liu Zichun , Li Huafei , Di Bangrang , Wei Jianxin 
Published: January 2023

Abstract
Compared with the seismic wave fields, the influence of porosity and permeability to seismoelectric coupling may be more significant. The seismoelectric effect mainly forms the coseismic signals (CS) and interface response (IR). The influences of the porosity and permeability on the two types of seismoelectric field are still not clear. In this paper, we numerically analyze the response characteristics of the CS and IR with the dependency of porosity and permeability, respectively. The differences in the sensitivity of the CS and the IR fields to porosity and permeability are also determined. The results show that the change of permeability is mainly sensed by the IR field, while the CS has almost no obvious response to it: both the CS and IR fields are sensitive to the change of porosity, but the sensitivity of the IR field is higher and with the increase of porosity, the discrepancy between the sensitivity of the CS and IR fields to porosity changes increases. The signal amplitude anomaly will be caused in both P-wave fields and seismoelectric fields (IR and CS) at the geological body where the porosity changes, but the change of permeability has little impact on the P-wave and only induces an obvious IR amplitude anomaly in seismoelectric fields. This indicates that the seismoelectric effect can better reveal the connectivity characteristics of the geological body than the seismic wave. This investigation can help to distinguish the sensitivity of seismoelectric response to porosity and permeability more clearly.
Modeling seismic waves in ocean with the presence of irregular seabed and rough sea surface
Authors: Liu Xiaobo 
Published: January 2023

Abstract
For the simulation of seismic wavefields in the ocean, it is very important to consider the influences of the irregular seabed and the rough sea surface. To numerically model seismic waves in the ocean, the fluid seawater and the solid seabed must be treated separately, and the air–fluid and fluid–solid boundary conditions must be considered simultaneously. A fluid–solid configuration is created with the influences of a rough sea surface and an irregular seabed to carry out wavefield simulation. Based on the boundary conformal grids, the 2D acoustic wave equations (in the fluid media), the 2D elastic wave equations (in the solid media) and two boundary conditions (at the interface between air and fluid and the interface between fluid and solid) are converted from the Cartesian coordinate system into a curvilinear coordinate system. In curvilinear coordinates, the seismic wave equations and boundary conditions are discretized with finite-difference operators. At the left, right and bottom boundaries of the model, the convolutional perfectly matched layer boundary condition is used to absorb artificial reflections. The numerical simulation results show that the snapshots and shot gathers of the rough sea surface model are more complex and contain stronger reflections than those of the flat model. The rough sea surface and the pattern of the irregular seabed have a great influence on the propagation of seismic waves in the ocean.
Gas hydrate reservoir identification based on rock physics modelling and sensitive elastic parameters
Authors: Wu Cunzhi , Han Lei , Zhang Feng , Liu Junzhou , Chen Haifeng , Di Bangrang 
Published: January 2023

Abstract
Seismic bottom simulating reflections (BSR) analysis and seismic inversion are commonly used for gas hydrate reservoir interpretation. The relationship between gas hydrate saturation and elastic parameters can be influenced by gas hydrate occurrence state (e.g. pore-filling type gas hydrate or load-bearing type gas hydrate), and this may cause inaccurate interpretation. We first used the simplified three-phase Biot equation (STPBE) to model a formation containing two types of gas hydrate at the same time. Then the effects of occurrence state and authigenic minerals on the relationship between saturation and varied elastic parameters are analysed. Results show that bulk modulus (K), shear modulus ($\mu $), P-wave velocity (${V}_p$), S-wave velocity (${V}_s$), velocity ratio (${V}_p/{V}_s$), Poisson's ratio (v) and $\mu \rho $ increase at different rates with gas hydrate saturation, ${V}_p/{V}_s$ and v show relative higher sensitivity to occurrence state. Ratios of elastic parameter increments are further used to highlight the anomalies caused by gas hydrate. Four attributes ($\Delta K/\Delta \mu $, $\Delta {V}_p/\Delta {V}_s$, $\Delta ({V}_p/{V}_s)/\Delta \nu $ and $\Delta \lambda \rho /\Delta \mu \rho $) show good sensitivity to both gas hydrate saturation and occurrence state. $\Delta ({V}_p/{V}_s)/\Delta \nu $ and $\Delta \lambda \rho /\Delta \mu \rho $ can be used to distinguish gas hydrate with varied occurrence states from authigenic minerals (limestone, opal, pyrite and others). Two selected sensitive attributes $\Delta ({V}_p/{V}_s)/\Delta \nu $ and $\Delta \lambda \rho /\Delta \mu \rho $ are applied to well logs, four gas hydrate-bearing intervals in well 2L-38 from Mallik permafrost area in Canada and one gas hydrate-bearing interval in well A from Shenhu area in South China Sea are identified. These results are consistent with the interpreted result from the resistivity log using Archie's formula. This investigation may provide effective tools for the seismic interpretation of gas hydrate reservoirs.
Tumor-activated neutrophils promote metastasis in breast cancer via the G-CSF-RLN2-MMP-9 axis
Authors: Sheng Youjing , Peng Weidong , Huang Yan , Cheng Lanqing , Meng Ye , Kwantwi Louis Boafo , Yang Jiezhen , Xu Jiegou , Xiao Han , Kzhyshkowska Julia , Wu Qiang 
Published: January 2023

AbstractThe immune component of the tumor microenvironment is essential for the regulation of cancer progression. In breast cancer (BC), a patient's tumor mass is frequently infiltrated by neutrophils (tumor-associated neutrophils, TANs). Our study addressed the role of TANs and their mechanism of action in BC. Using quantitative IHC, ROC, and Cox analysis, we demonstrated that a high density of TANs infiltrating the tumor parenchyma was predictive of poor prognosis and of decreased progression-free survival of patients with BC, who underwent surgical tumor removal without previous neoadjuvant chemotherapy, in 3 different cohorts: training, validation, and independent cohorts. Conditioned medium from human BC cell lines prolonged the lifespan of healthy donor neutrophils ex vivo. Neutrophils activated by the supernatants of BC lines demonstrated an increased ability to stimulate proliferation, migration, and invasive activity of BC cells. Cytokines involved in this process were identified using antibody arrays. The relationship between these cytokines and the density of TANs was validated by ELISA and IHC in fresh BC surgical samples. It was determined that tumor-derived G-CSF significantly extended the lifespan and increased the metastasis-promoting activities of neutrophils via the PI3K-AKT and NF-κB pathways. Simultaneously, TAN-derived RLN2 promoted the migratory abilities of MCF7 cells via PI3K-AKT-MMP-9. Analysis of tumor tissues from 20 patients with BC identified a positive correlation between the density of TANs and the activation of the G-CSF-RLN2-MMP-9 axis. Finally, our data demonstrated that TANs in human BC have detrimental effects, supporting malignant cell invasion and migration.
Fast and realistic large-scale structure from machine-learning-augmented random field simulations
Authors: Piras Davide , Joachimi Benjamin , Villaescusa-Navarro Francisco 
Published: January 2023

ABSTRACT
Producing thousands of simulations of the dark matter distribution in the Universe with increasing precision is a challenging but critical task to facilitate the exploitation of current and forthcoming cosmological surveys. Many inexpensive substitutes to full N-body simulations have been proposed, even though they often fail to reproduce the statistics of the smaller non-linear scales. Among these alternatives, a common approximation is represented by the lognormal distribution, which comes with its own limitations as well, while being extremely fast to compute even for high-resolution density fields. In this work, we train a generative deep learning model, mainly made of convolutional layers, to transform projected lognormal dark matter density fields to more realistic dark matter maps, as obtained from full N-body simulations. We detail the procedure that we follow to generate highly correlated pairs of lognormal and simulated maps, which we use as our training data, exploiting the information of the Fourier phases. We demonstrate the performance of our model comparing various statistical tests with different field resolutions, redshifts, and cosmological parameters, proving its robustness and explaining its current limitations. When evaluated on 100 test maps, the augmented lognormal random fields reproduce the power spectrum up to wavenumbers of $1 \, h \, \rm {Mpc}^{-1}$, and the bispectrum within 10 per cent, and always within the error bars, of the fiducial target simulations. Finally, we describe how we plan to integrate our proposed model with existing tools to yield more accurate spherical random fields for weak lensing analysis.
Oscillations in gas-grain astrochemical kinetics
Authors: Dufour Gwenaëlle , Charnley Steven B , Lindberg Johan E 
Published: January 2023

ABSTRACT
We have studied gas-grain chemical models of interstellar clouds to search for non-linear dynamical evolution. A prescription is given for producing oscillatory solutions when a bistable solution exists in the gas-phase chemistry and we demonstrate the existence of limit cycle and relaxation oscillation solutions. As the autocatalytic chemical processes underlying these solutions are common to all models of interstellar chemistry, the occurrence of these solutions should be widespread. We briefly discuss the implications for interpreting molecular cloud composition with time-dependent models and some future directions for this approach.
Improving Orthologous Signal and Model Fit in Datasets Addressing the Root of the Animal Phylogeny
Authors: McCarthy Charley G P , Mulhair Peter O , Siu-Ting Karen , Creevey Christopher J , O’Connell Mary J 
Published: January 2023

Abstract
There is conflicting evidence as to whether Porifera (sponges) or Ctenophora (comb jellies) comprise the root of the animal phylogeny. Support for either a Porifera-sister or Ctenophore-sister tree has been extensively examined in the context of model selection, taxon sampling, and outgroup selection. The influence of dataset construction is comparatively understudied. We re-examine five animal phylogeny datasets that have supported either root hypothesis using an approach designed to enrich orthologous signal in phylogenomic datasets. We find that many component orthogroups in animal datasets fail to recover major lineages as monophyletic with the exception of Ctenophora, regardless of the supported root. Enriching these datasets to retain orthogroups recovering ≥3 major lineages reduces dataset size by up to 50% while retaining underlying phylogenetic information and taxon sampling. Site-heterogeneous phylogenomic analysis of these enriched datasets recovers both Porifera-sister and Ctenophora-sister positions, even with additional constraints on outgroup sampling. Two datasets which previously supported Ctenophora-sister support Porifera-sister upon enrichment. All enriched datasets display improved model fitness under posterior predictive analysis. While not conclusively rooting animals at either Porifera or Ctenophora, we do see an increase in signal for Porifera-sister and a decrease in signal for Ctenophore-sister when data are filtered for orthologous signal. Our results indicate that dataset size and construction as well as model fit influence animal root inference.
Estimating Temporally Variable Selection Intensity from Ancient DNA Data
Authors: He Zhangyi , Dai Xiaoyang , Lyu Wenyang , Beaumont Mark , Yu Feng 
Published: January 2023

AbstractNovel technologies for recovering DNA information from archaeological and historical specimens have made available an ever-increasing amount of temporally spaced genetic samples from natural populations. These genetic time series permit the direct assessment of patterns of temporal changes in allele frequencies and hold the promise of improving power for the inference of selection. Increased time resolution can further facilitate testing hypotheses regarding the drivers of past selection events such as the incidence of plant and animal domestication. However, studying past selection processes through ancient DNA (aDNA) still involves considerable obstacles such as postmortem damage, high fragmentation, low coverage, and small samples. To circumvent these challenges, we introduce a novel Bayesian framework for the inference of temporally variable selection based on genotype likelihoods instead of allele frequencies, thereby enabling us to model sample uncertainties resulting from the damage and fragmentation of aDNA molecules. Also, our approach permits the reconstruction of the underlying allele frequency trajectories of the population through time, which allows for a better understanding of the drivers of selection. We evaluate its performance through extensive simulations and demonstrate its utility with an application to the ancient horse samples genotyped at the loci for coat coloration. Our results reveal that incorporating sample uncertainties can further improve the inference of selection.
Antifungal Drug Concentration Impacts the Spectrum of Adaptive Mutations in Candida albicans
Authors: Todd Robert T , Soisangwan Natthapon , Peters Sam , Kemp Bailey , Crooks Taylor , Gerstein Aleeza , Selmecki Anna 
Published: January 2023

Abstract
Invasive fungal infections are a leading global cause of human mortality. Only three major classes of antifungal drugs are widely used, and resistance to all three classes can arise rapidly. The most widely prescribed antifungal drug, fluconazole, disseminates rapidly and reaches a wide range of concentrations throughout the body. The impact of drug concentration on the spectrum and effect of mutations acquired during adaptation is not known for any fungal pathogen, and how the specific level of a given stress influences the distribution of beneficial mutations has been poorly explored in general. We evolved 144 lineages from three genetically distinct clinical isolates of Candida albicans to four concentrations of fluconazole (0, 1, 8, and 64 μg/ml) and performed comprehensive phenotypic and genomic comparisons of ancestral and evolved populations. Adaptation to different fluconazole concentrations resulted in distinct adaptive trajectories. In general, lineages evolved to drug concentrations close to their MIC50 (the level of drug that reduces growth by 50% in the ancestor) tended to rapidly evolve an increased MIC50 and acquired distinct segmental aneuploidies and copy number variations. By contrast, lineages evolved to drug concentrations above their ancestral MIC50 tended to acquire a different suite of mutational changes and increased in drug tolerance (the ability of a subpopulation of cells to grow slowly above their MIC50). This is the first evidence that different concentrations of drug can select for different genotypic and phenotypic outcomes in vitro and may explain observed in vivo drug response variation.
Structures of human TR4LBD–JAZF1 and TR4DBD–DNA complexes reveal the molecular basis of transcriptional regulation
Authors: Liu Yunlong , Ma Lulu , Li Min , Tian Zizi , Yang Meiting , Wu Xi , Wang Xue , Shang Guohui , Xie Mengjia , Chen Yiyun , Liu Xin , Jiang Lun , Wu Wei , Xu Chaoqun , Xia Liqun , Li Gonghui , Dai Shaodong , Chen Zhongzhou 
Published: January 2023

AbstractTesticular nuclear receptor 4 (TR4) modulates the transcriptional activation of genes and plays important roles in many diseases. The regulation of TR4 on target genes involves direct interactions with DNA molecules via the DNA-binding domain (DBD) and recruitment of coregulators by the ligand-binding domain (LBD). However, their regulatory mechanisms are unclear. Here, we report high-resolution crystal structures of TR4DBD, TR4DBD–DNA complexes and the TR4LBD–JAZF1 complex. For DNA recognition, multiple factors come into play, and a specific mutual selectivity between TR4 and target genes is found. The coactivators SRC-1 and CREBBP can bind at the interface of TR4 originally occupied by the TR4 activation function region 2 (AF-2); however, JAZF1 suppresses the binding through a novel mechanism. JAZF1 binds to an unidentified surface of TR4 and stabilizes an α13 helix never reported in the nuclear receptor family. Moreover, the cancer-associated mutations affect the interactions and the transcriptional activation of TR4 in vitro and in vivo, respectively. Overall, our results highlight the crucial role of DNA recognition and a novel mechanism of how JAZF1 reinforces the autorepressed conformation and influences the transcriptional activation of TR4, laying out important structural bases for drug design for a variety of diseases, including diabetes and cancers.