bluuebunny/crossref_metadata_2025_split huggingface dataset:
Plant species diversity and abundance of functional groups influence net nitrogen mineralization along productivity gradients in montane Calluna‐dominated heathlands
Authors: Fernández‐Guisuraga José Manuel , Calvo Leonor , Marcos Elena 
Published: February 2025

Societal Impact StatementHeathlands are globally important ecosystems that provide key functions and services but are increasingly threatened by land use changes. We investigated how plant diversity and productivity influence nitrogen cycling under different management regimes. Our findings reveal that extensive grazing modulates the relationship between plant diversity and soil nitrogen dynamics, with contrasting effects in grazed versus abandoned sites. Increased plant species diversity and abundance of annual and perennial herbs in grazed sites were associated with enhanced N mineralization rates. These insights highlight the need for adaptive management strategies to address the challenges posed by land use changes and biodiversity loss in heathland ecosystems.Summary
Abiotic controls on soil N‐transformations in heathlands are well understood; however, the effects of plant species diversity–productivity on N cycling remain unclear, particularly concerning grazing management.
We evaluated the feedbacks among plant species diversity, functional group productivity and soil properties, as well as their relationship with net N mineralization rates, in six heathlands dominated by Calluna vulgaris with differing management history (grazed at low intensity and abandoned).
Our findings revealed a pronounced increase in soil organic matter content with plant diversity in abandoned, species‐poor heathlands compared to the stronger feedback with soil total N in grazed, species‐rich sites, suggesting trade‐offs in the carbon‐to‐nitrogen ratio. Mean net ammonification, nitrification, and mineralization rates showed no significant differences between species‐rich and species‐poor heathlands. However, increased plant species diversity and abundance of productive functional groups in grazed sites were associated with enhanced N mineralization rates. In contrast, high species diversity in abandoned heathlands led to increased woody species productivity with traits related to nutrient conservation, which was linked to slower N mineralization rates.
These findings enhance our understanding of the effects of the diversity‐productivity relationship on nitrogen cycling in heathlands, providing insights for anticipating ecosystem responses to changing management regimes.
Aurantio‐Obtusin Regulates Gut Microbiota and Serum Metabolism to Alleviate High‐Fat Diet‐Induced Obesity‐Associated Non‐Alcoholic Fatty Liver Disease in Mice
Authors: Li Zhaoyong , Jin Yao , Zhao Huashan , Gu Yuyan , Zhang Yaxin , Cheng Saibo , Zhang Lifang , He Peikun , Liu Xiaoyu , Jia Yuhua 
Published: February 2025

ABSTRACTNon‐alcoholic fatty liver disease (NAFLD) is a progressive condition with limited effective treatments. This study investigated the therapeutic effects of Aurantio‐obtusin (AO), a bioactive compound from Cassiae Semen, on obesity‐associated NAFLD. An obesity‐related NAFLD model was established in ApoE−/− mice fed a high‐fat diet (HFD) for 24 weeks, with AO administered during the last 16 weeks. Mouse body weight, adipose tissue weights, liver weights, serum lipid levels, hepatic steatosis, inflammatory damage, and colonic tissue barrier integrity were evaluated. Gut microbial communities and serum metabolic profiles were analyzed using 16S rRNA sequencing and untargeted metabolomics. Hepatic lipid metabolism‐related gene expression was assessed using molecular biology techniques. AO treatment significantly ameliorated HFD‐induced adiposity, hyperlipidemia, and NAFLD symptoms. It preserved intestinal barrier integrity, modulated gut microbial composition by enriching beneficial taxa, and improved serum metabolic profiles. AO favorably adjusted hepatic lipid metabolism by upregulating PPARα and CPT1A while downregulating SREBP1, FASN, and SCD1. Correlation analysis revealed significant associations among gut microbial composition, serum metabolites, and disease indicators. AO's therapeutic benefits in NAFLD might be attributed to its ability to modulate gut microbial community composition and serum metabolic profile, enhance intestinal barrier function, and regulate hepatic lipid metabolism gene expression. AO presents a promising therapeutic agent for obesity‐associated NAFLD, warranting further investigation into its potential clinical applications.
Improved Protective Effects and Pharmacokinetics of Huperzine A Derivative H14 in Soman Poisoning: A Comparative Study With Huperzine A in Rats
Authors: Yang Guixiang , Cui Yalan , Zong Xingxing , Jin Qian , Zhang Yi , Li Liqin , Liu Dongxin , Chen Xuejun , Wang Chen , Wei Jingchen 
Published: February 2025

ABSTRACTRationaleN‐[2‐Hydroxy‐3,5‐dimethylbenzilidene]‐Hup A (H14) is a derivative of huperzine A (Hup A) that demonstrates superior protective effects against soman (GD) compared to Hup A. This study aims to evaluate the protective efficacy of H14 pretreatment against GD in rats and to provide an analytical framework for the pharmacokinetic evaluation of H14 in experimental animals.MethodsThe study employed protective ratios (PR) as an evaluation criterion to assess the efficacy of H14 and Hup A in preventing GD in vivo. Liquid–liquid extraction techniques were utilized to extract H14 and its metabolite, Hup A, from plasma. The extracted plasma samples were then analyzed using an ultra‐high‐performance liquid chromatography–tandem mass spectrometry (UHPLC–MS/MS) method for the simultaneous quantification of H14 and Hup A.ResultsThe PR values for the 6‐ and 12‐h Hup A groups were 1.26 and 1.08, respectively. In contrast, the 6, 12, and 24‐h H14 groups demonstrated PR values of 2.81, 1.98, and 1.18, respectively, indicating extended protective capabilities compared to Hup A. All validation parameters for the UHPLC–MS/MS method, including linearity, specificity, precision, accuracy, matrix effect, and stability, met the acceptance criteria established by FDA guidelines. The pharmacokinetic analysis indicates that H14, after conversion to Hup A in vivo, significantly extends the duration of Hup A concentrations in the body, leading to more effective prevention of GD poisoning compared to Hup A alone.ConclusionsH14 demonstrates superior efficacy in preventing GD poisoning compared to Hup A. Furthermore, this analytical approach offers a reliable and efficient method for the pharmacokinetic evaluation of H14 in experimental animals.
Automated identification of hedgerows and hedgerow gaps using deep learning
Authors: Wolstenholme J. M. , Cooper F. , Thomas R. E. , Ahmed J. , Parsons K. J. , Parsons D. R. 
Published: February 2025

AbstractHedgerows are a key component of the UK landscape that form boundaries, borders and limits of land whilst providing vital landscape‐scale ecological connectivity for a range of organisms. They are diverse habitats in the agricultural landscape providing a range of ecosystem services. Poorly managed hedgerows often present with gaps, reducing their ecological connectivity, resulting in fragmented habitats. However, hedgerow gap frequency and spatial distributions are often unquantified at the landscape‐scale. Here we present a novel methodology based on deep learning (DL) that is coupled with high‐resolution aerial imagery. We demonstrate how this provides a route towards a rapid, adaptable, accurate assessment of hedgerow and gap abundance at such scales, with minimal training data. We present the training and development of a DL model using the U‐Net architecture to automatically identify hedgerows across the East Riding of Yorkshire (ERY) in the UK and demonstrate the ability of the model to estimate hedgerow gap types, lengths and their locations. Our method was both time efficient and accurate, processing an area of 2479 km2 in 32 h with an overall accuracy of 92.4%. The substantive results allow us to estimate that in the ERY alone, there were 3982 ± 302 km of hedgerows and 2865 ± 217 km of hedgerow gaps (with 339 km classified as for access). Our approach and study show that hedgerows and gaps can be extracted from true colour aerial imagery without the requirement of elevation data and can produce meaningful results that lead to the identification of prioritisation areas for hedgerow gap infilling, replanting and restoration. Such replanting could significantly contribute towards national tree planting goals and meeting net zero targets in a changing climate.
Creating Better Brewing Yeast With the 1011 Yeast Genomes Data Sets
Authors: Krogerus Kristoffer , Rettberg Nils 
Published: February 2025

ABSTRACTYeast strain development has been essential for improving efficiency, flavour diversity, and quality of beer fermentation. Such efforts often rely on laborious in vitro screening experiments. However, with the increasing availability of large‐scale ‘omics’ data sets, it may be possible to replace or complement such experiments with in silico screening. Compared to more traditional in vitro screening, this has several benefits, including lower costs, more rapid results and possibility to include more strains. Here, we briefly review the genetics associated with various desirable and undesirable traits in brewing yeast, and demonstrate how recent genomics, transcriptomics, and proteomics data sets derived from the 1011 yeast genomes project can be exploited for identifying strains with potentially desirable phenotypes. The discussed phenotypes are related to fermentation performance, formation of desirable flavours, and mitigation of off‐flavours. Finally, we perform wort fermentations with five strains from diverse backgrounds, with diverse predicted phenotypes, to validate the in silico predictions. Most predicted phenotypes correlated well with the measured phenotypes, including formation of desirable compounds like isoamyl acetate and ethyl octanoate, as well as formation of undesirable compounds like 4‐vinyl guaiacol, diacetyl, and ethanethiol. Together, the results indicate that utilising large ‘omics’ data sets can be a very useful tool for both strain selection and development for beer fermentation, and naturally other food and beverage fermentations as well. We hope this can inspire and yield improved and more diverse brewing strains to the industry.
Impossible evolutions: textillic thinking with machine learning models
Authors: Geck Kate 
Published: February 2025

Abstract
This paper discusses the creative project ‘Impossible Evolutions’, which uses generative machine learning models in the design of woven tapestries. This project is used as a conduit to unfold highly relational ways of thinking about the entanglements of human and machine assemblages within generative artificial intelligence. The project leverages interconnected ecological stories and the language of textiles to provide novel perspectives on the emerging relations between human and machine intelligences. The project uses Generative Adversarial Networks (GANs) and diffusion models to imagine new iterations of endangered Australian butterflies and wildflowers. The generated images are composed into three textile weavings of place: tapestries of the interconnected lives that generate each creature’s ecosystem. By reflecting on the interweaving of conditions that has disrupted each ecological niche, space is opened to think about unseen sensory worlds (Richmond Birdwing butterfly), symbiotic exchange (Bulloak Jewel butterfly), and stewardship of the land (Sunshine Diuris orchid). Each story becomes a fabric both literal and metaphorical, with this ‘textillic thinking’ offering speculative vantage points for approaching artistic and social practice with ML models. Textillic thinking interweaves creativity, collaboration, and care: conditions which are foregrounded in textile-making practices and disrupted in each creature’s ecological story. The creative work is diffracted with the neomaterialism of Rosi Braidotti and Karen Barad, and with the notions of care offered by both Maria Puig de la Bellacasa and the Indigenous Protocol for Artificial Intelligence. Through this reading and practice, the project offers material language for discussing the processes and effects of ML, while emphasizing the responsibility of the human in their design.
Constructability-based multi-objective optimization with machine learning-enhanced meta-heuristics for reinforcing bar design in rectangular concrete columns
Authors: Verduzco Luis F. 
Published: February 2025

Abstract
Optimization of reinforcing bar (rebar) design represents a preponderant factor in reducing material usage and wastes for reinforced concrete (RC) structures. The assessment of constructability of such rebar designs is crucial to improve their practicality and reduce construction costs, which makes the problem multi-objective (MO). However, when applying optimization methods for the design of rebar in RC structures, little attention has been paid on columns, in comparison to beams and slabs. Meta-heuristic algorithms (MA) have been the ones mostly deployed for these types of elements, which have proven to be of high computational cost. Additionally, an existing gap in the literature as to how to relate the design and construction stage of rebar in RC structures through constructability analysis is evident. In this regard, research has been focused mainly at the building level but not at the element level. This works presents a novel algorithmic framework using Machine Learning (ML)-enhanced meta-heuristics for the optimal design of rebar on rectangular RC columns. To assess the constructability of the resulting rebar layouts a Buildability Score (BS) model at the element level is proposed. The complexity analysis of rebar design under the constructability restrictions, through combinatorial optimization (CO), is used to assess the global time efficiency of the framework. The Non-Sorting Genetic Algorithm II (NSGA-II) was deployed for showcase and five different ML algorithms were used to enhance it, namely the k-NN classifier, SVM regression, ANN, Gauss Process (GP) regression, and Tree Ensembles (TE), where the latter three showed the best performance.
Topology optimization for pressurized nonlinear structures using substructure and experimental studies
Authors: Lu Yifu , Luo Quantian , Tong Liyong 
Published: February 2025

Abstract
A compliant structure under fluidic pressure can undergo relatively large shape change, but the design of such type of structure is challenging as the pressure distribution depends on detailed structural geometry. In this study, a novel mixed substructure-density (MSD) model is proposed for topology representation and update in the optimal design of nonlinear compliant structures under quasi-static fluidic pressure. An optimization algorithm is developed via implementing the present model by using super-elements in commercial finite element analysis (FEA) software. Numerical examples are presented to validate the present model, algorithm, and designs numerically via full linear and nonlinear FEAs. A planar cellular network with five cells arranged in parallel is then designed for representing a pressurized wing rib structure capable of modulating airfoil thickness variation. The test results of the single-cell and five-cell PCS specimens prototyped using polyurethane material show that the respective cell thickness can be reduced by 11.9 and 6.4% respectively under a cell pressure of 250 kPa.
Holomorphic motions, natural families of entire maps, and multiplier-like objects for wandering domains
Authors: Ferreira Gustavo R. , van Strien Sebastian 
Published: February 2025

Abstract
Structural stability of holomorphic functions has been the subject of much research in the last fifty years. Due to various technicalities, however, most of that work has focused on so-called finite-type functions (functions whose set of singular values has finite cardinality). Recent developments in the field go beyond this setting. In this paper we extend Eremenko and Lyubich’s result on natural families of entire maps to the case where the set of singular values is not the entire complex plane, showing under this assumption that the set

$$M_f$$

M
f

of entire functions quasiconformally equivalent to f admits the structure of a complex manifold (of possibly infinite dimension). Moreover, we will consider functions with wandering domains—another hot topic of research in complex dynamics. Given an entire function f with a simply connected wandering domain U, we construct an analogue of the multiplier of a periodic orbit, called a distortion sequence, and show that, under some hypotheses, the distortion sequence moves analytically as f moves within appropriate parameter families.
Investigation of the inhibitory effects of the telomere-targeted compounds on glutathione S-transferase P1
Authors: Ozcan Mehmet , Burus Ayse , Mender Ilgen , Dikmen Z. Gunnur , Gryaznov Sergei M. , Bastug Turgut , Bayazit Yasemin 
Published: February 2025

Abstract
Glutathione S-transferase P1 (GSTP1) plays a significant role in cancer progression and chemotherapy resistance, with its overexpression diminishing chemotherapeutic efficacy across various tumor types. This study evaluates the inhibitory effects of 6-thio-2′-deoxyguanosine (6-thio-dG) and its dimeric form (6-thio-2′-dG-Dimer) on GSTP1. Enzyme inhibition assays with recombinant human GSTP1, kinetic analysis, molecular docking, and molecular dynamic simulations were employed. Enzymatic assays were performed in 0.1 M phosphate buffer (pH 6.5) at 30 °C, containing 1 mM EDTA, 1 mM GSH, and 1 mM CDNB. The compounds 6-thio-dG and its dimer were dissolved in 2.5% DMSO for the experiments. The IC₅₀ values indicated that the dimer exhibited a higher potency (IC₅₀: 0.339 μM) than the monomer (IC₅₀: 15.14 μM). Kinetic analysis revealed noncompetitive inhibition with glutathione (Ki: 12.26 μM) and mixed inhibition with CDNB (Ki: 11.41 μM) for the monomer, whereas the dimer showed mixed inhibition with glutathione (Ki: 0.972 μM) and competitive inhibition with CDNB (Ki: 0.723 μM). Molecular docking confirmed the higher binding affinity of the dimer (binding energy: − 7.9 kcal/mol, Ki: 1.595 μM) compared to the monomer (binding energy: − 6.2 kcal/mol, Ki: 28.21 μM). The dimer form of 6-thio-dG shows strong potential to enhance chemotherapeutic efficacy by effectively inhibiting GSTP1 and overcoming drug resistance. Its superior inhibitory properties make it a valuable candidate for targeted cancer therapies.

Graphical abstract
Effect of muscarinic blockade on the speed of attention shifting, read-out delays and learning
Authors: Thiele Alexander , Milner Agnes McDonald , Hall Corwyn , Mayhew Lucy , Carter Anthony , Sanjeev Sidharth 
Published: February 2025

Abstract
The study aimed to investigate to what extent blockade of muscarinic receptors affects the speed of endogenous versus exogenous attentional shift times, and how it affects learning of attention shifting, cue detection and signal readout. Subjects viewed an array of 10 moving clocks and reported the time a clock indicated when cued. Target clocks were indicated by peripheral or central cues, including conditions of pre-cuing. For peripheral and central cuing, it yielded a compound measure of how long it took to detect the cue, shift attention to the relevant clock and read the time on the clock. For the pre-cue condition it yielded a measure of how long it took to detect the cue and read the time on the clock when attention could have been pre-allocated to the target clock. In study 1, each subject participated in 2 sessions (scopolamine/placebo), whereby the order of drug intake was counterbalanced across subjects, and subjects were blinded to conditions. Scopolamine/placebo was administered before a psychophysical experiment was conducted. In study 2, the effect of muscarinic blockade on learning induced improvements of cue detection, attention shift times (for exogenous and endogenous conditions), and signal readout was investigated. Here scopolamine/placebo was administered immediately after the first (of two) psychophysical sessions, whereby a given subject either received scopolamine or placebo pills. Confirming previous results, we show that pre-cuing resulted in the shortest read-out delays, followed by exogenous cuing, with endogenous read-out delays being slowest. Scopolamine application increased readout-delays in a dose dependent manner. This was mainly driven by increased readout-delays for pre-cue conditions, and to some extent for exogenous cue conditions. It suggests that muscarinic blockade affected the ability to pre-allocated attention to a cued location, as well as to react to peripheral cues. Additionally, blockade of muscarinic receptors immediately after the first session reduced learning dependent improvement of read-out delays. These results demonstrate that muscarinic receptors play an important in detecting cues, and fast read-out of cued information, and they contribute to the learning thereof.
Quantification of Pesticides and In Vitro Effects of Water-Soluble Fractions of Agricultural Soils in South Africa
Authors: Engelbrecht Ilzé , Horn Suranie R. , Giesy John P. , Pieters Rialet 
Published: February 2025

Abstract
Although agrochemicals protect crops and reduce losses, these chemicals can migrate to non-target environments via run-off and leaching following irrigation or heavy rainfall, where non-target organisms can be exposed to a mixture of water-soluble compounds. This study investigated whether the water-soluble fractions of selected agricultural soils from South Africa contain quantifiable concentrations of four commonly used pesticides, 2,4-dichlorophenoxyacetic acid (2,4-D), atrazine, dicamba and imidacloprid, and whether the aqueous extracts induce effects in vitro. Effects investigated included cytotoxicity using the MTT [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide] cell viability assay; xenobiotic metabolism using the H4IIE-luc rat hepatoma cell line; and (anti-)androgenic and (anti-)oestrogenic effects were screened for with the human breast carcinoma cell lines MDA-kb2 and T47D-KBluc, respectively. Oxidative stress responses were measured in H4IIE-luc and human duodenum adenocarcinoma (HuTu-80) cells. All extracts of soil induced oxidative stress, while several samples caused moderate to severe cytotoxicity and/or anti-androgenic effects. The herbicide atrazine had the greatest frequency of detection (89%), followed by dicamba (84%), 2,4-D (74%) and imidacloprid (32%). Concentrations of atrazine [2.0 × 10–1 to 2.1 × 102 ng/g, dry mass (dm)] and the neonicotinoid insecticide, imidacloprid (2.0 × 101 to 9.7 × 101 ng/g, dm), exceeded international soil quality guidelines. Overall, there was no observable trend between the biological effects and pesticides quantified. Nonetheless, the findings of this study show that agricultural soils in South Africa can elicit effects in vitro and contain quantifiable concentrations of polar pesticides. These agrochemicals might pose risks to the health of humans and the environment, but more assessment is necessary to quantify such potential effects.