bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modelling the impact of forest management and CO2-fertilisation on growth and demography in a Sitka spruce plantation
Authors: Argles Arthur P. K. , Robertson Eddy , Harper Anna B. , Morison James I. L. , Xenakis Georgios , Hastings Astley , Mccalmont Jon , Moore Jon R. , Bateman Ian J. , Gannon Kate , Betts Richard A. , Bathgate Stephen , Thomas Justin , Heard Matthew , Cox Peter M. 
Published: August 2023

AbstractAfforestation and reforestation to meet ‘Net Zero’ emissions targets are considered a necessary policy by many countries. Their potential benefits are usually assessed through forest carbon and growth models. The implementation of vegetation demography gives scope to represent forest management and other size-dependent processes within land surface models (LSMs). In this paper, we evaluate the impact of including management within an LSM that represents demography, using both in-situ and reanalysis climate drivers at a mature, upland Sitka spruce plantation in Northumberland, UK. We compare historical simulations with fixed and variable CO2 concentrations, and with and without tree thinning implemented. Simulations are evaluated against the observed vegetation structure and carbon fluxes. Including thinning and the impact of increasing CO2 concentration (‘CO2 fertilisation’) gave more realistic estimates of stand-structure and physical characteristics. Historical CO2 fertilisation had a noticeable effect on the Gross Primary Productivity seasonal–diurnal cycle and contributed to approximately 7% higher stand biomass by 2018. The net effect of both processes resulted in a decrease of tree density and biomass, but an increase in tree height and leaf area index.
Computational modeling allows unsupervised classification of epileptic brain states across species
Authors: Dallmer-Zerbe Isa , Jajcay Nikola , Chvojka Jan , Janca Radek , Jezdik Petr , Krsek Pavel , Marusic Petr , Jiruska Premysl , Hlinka Jaroslav 
Published: August 2023

AbstractCurrent advances in epilepsy treatment aim to personalize and responsively adjust treatment parameters to overcome patient heterogeneity in treatment efficiency. For tailoring treatment to the individual and the current brain state, tools are required that help to identify the patient- and time-point-specific parameters of epilepsy. Computational modeling has long proven its utility in gaining mechanistic insight. Recently, the technique has been introduced as a diagnostic tool to predict individual treatment outcomes. In this article, the Wendling model, an established computational model of epilepsy dynamics, is used to automatically classify epileptic brain states in intracranial EEG from patients (n = 4) and local field potential recordings from in vitro rat data (high-potassium model of epilepsy, n = 3). Five-second signal segments are classified to four types of brain state in epilepsy (interictal, preonset, onset, ictal) by comparing a vector of signal features for each data segment to four prototypical feature vectors obtained by Wendling model simulations. The classification result is validated against expert visual assessment. Model-driven brain state classification achieved a classification performance significantly above chance level (mean sensitivity 0.99 on model data, 0.77 on rat data, 0.56 on human data in a four-way classification task). Model-driven prototypes showed similarity with data-driven prototypes, which we obtained from real data for rats and humans. Our results indicate similar electrophysiological patterns of epileptic states in the human brain and the animal model that are well-reproduced by the computational model, and captured by a key set of signal features, enabling fully automated and unsupervised brain state classification in epilepsy.
Genome-wide analysis and characterization of the LRR-RLK gene family provides insights into anthracnose resistance in common bean
Authors: da Silva Dambroz Caroline Marcela , Aono Alexandre Hild , de Andrade Silva Edson Mario , Pereira Welison Andrade 
Published: August 2023

AbstractAnthracnose, caused by the hemibiotrophic fungus Colletotrichum lindemuthianum, is a damaging disease of common beans that can drastically reduce crop yield. The most effective strategy to manage anthracnose is the use of resistant cultivars. There are many resistance loci that have been identified, mapped and associated with markers in common bean chromosomes. The Leucine-rich repeat kinase receptor protein (LRR-RLK) family is a diverse group of transmembrane receptors, which potentially recognizes pathogen-associated molecular patterns and activates an immune response. In this study, we performed in silico analyses to identify, classify, and characterize common bean LRR-RLKs, also evaluating their expression profile in response to the infection by C. lindemuthianum. By analyzing the entire genome of Phaseolus vulgaris, we could identify and classify 230 LRR-RLKs into 15 different subfamilies. The analyses of gene structures, conserved domains and motifs suggest that LRR-RLKs from the same subfamily are consistent in their exon/intron organization and composition. LRR-RLK genes were found along the 11 chromosomes of the species, including regions of proximity with anthracnose resistance markers. By investigating the duplication events within the LRR-RLK family, we associated the importance of such a family with an expansion resulting from a strong stabilizing selection. Promoter analysis was also performed, highlighting cis-elements associated with the plant response to biotic stress. With regard to the expression pattern of LRR-RLKs in response to the infection by C. lindemuthianum, we could point out several differentially expressed genes in this subfamily, which were associated to specific molecular patterns of LRR-RLKs. Our work provides a broad analysis of the LRR-RLK family in P. vulgaris, allowing an in-depth structural and functional characterization of genes and proteins of this family. From specific expression patterns related to anthracnose response, we could infer a direct participation of RLK-LRR genes in the mechanisms of resistance to anthracnose, highlighting important subfamilies for further investigations.
Genetic associations between alcohol phenotypes and life satisfaction: a genomic structural equation modelling approach
Authors: Bountress Kaitlin E. , Cusack Shannon E. , Hawn Sage E. , Grotzinger Andrew , Bustamante Daniel , Kirkpatrick Robert M. , Edenberg Howard J. , Amstadter Ananda B. 
Published: August 2023

AbstractAlcohol use (i.e., quantity, frequency) and alcohol use disorder (AUD) are common, associated with adverse outcomes, and genetically-influenced. Genome-wide association studies (GWAS) identified genetic loci associated with both. AUD is positively genetically associated with psychopathology, while alcohol use (e.g., drinks per week) is negatively associated or NS related to psychopathology. We wanted to test if these genetic associations extended to life satisfaction, as there is an interest in understanding the associations between psychopathology-related traits and constructs that are not just the absence of psychopathology, but positive outcomes (e.g., well-being variables). Thus, we used Genomic Structural Equation Modeling (gSEM) to analyze summary-level genomic data (i.e., effects of genetic variants on constructs of interest) from large-scale GWAS of European ancestry individuals. Results suggest that the best-fitting model is a Bifactor Model, in which unique alcohol use, unique AUD, and common alcohol factors are extracted. The genetic correlation (rg) between life satisfaction-AUD specific factor was near zero, the rg with the alcohol use specific factor was positive and significant, and the rg with the common alcohol factor was negative and significant. Findings indicate that life satisfaction shares genetic etiology with typical alcohol use and life dissatisfaction shares genetic etiology with heavy alcohol use.
Genetic diversity patterns of lionfish in the Southwestern Atlantic Ocean reveal a rapidly expanding stepping-stone bioinvasion process
Authors: Maggioni Rodrigo , Rocha Rafael S. , Viana Jhonatas T. , Giarrizzo Tommaso , Rabelo Emanuelle F. , Ferreira Carlos E. L. , Sampaio Claudio L. S. , Pereira Pedro H. C. , Rocha Luiz A. , Tavares Tallita C. L. , Soares Marcelo O. 
Published: August 2023

AbstractIn 2020, multiple lionfish (Pterois spp.) records along the equatorial Southwestern (SW) Atlantic revealed a new expansion of these potentially damaging invasive populations, which could impact over 3500 km of Brazilian coastline over the next few years, as well as unique ecosystems and marine protected areas in its path. To assess the taxonomic status, invasion route, and correlation with other centres of distribution, we investigated the genetic diversity patterns of lionfish caught in 2022 at the Amazonia, Northeastern Brazil, and Fernando de Noronha and Rocas Atoll ecoregions, using two molecular markers, the mitochondrial COI and the nuclear S7 RP1. The data indicate that all studied lionfish belong to what is generally accepted as P. volitans, and share the same genetic signature as lionfish present in the Caribbean Sea. The shared haplotypes and alleles indicate that the SW Atlantic invasion derives from an active movement of adult individuals from the Caribbean Sea into the Brazilian coast. The Amazon mesophotic reefs likely served as a stepping-stone to overcome the biogeographical barrier represented by the Amazon-Orinoco River plume. New alleles found for S7 RP1 suggest the onset of local genetic diversification, heightening the environmental risks as this bioinvasion heads towards other South Atlantic ecoregions.
Ethnicity-specific association between TERT rs2736100 (A > C) polymorphism and lung cancer risk: a comprehensive meta-analysis
Authors: Wu Xiaozheng , Huang Gao , Li Wen , Chen Yunzhi 
Published: August 2023

AbstractThe rs2736100 (A > C) polymorphism of the second intron of Telomerase reverse transcriptase (TERT) has been confirmed to be closely associated with the risk of Lung cancer (LC), but there is still no unified conclusion on the results of its association with LC. This study included Genome-wide association studies (GWAS) and case–control studies reported so far on this association between TERT rs2736100 polymorphism and LC to clarify such a correlation with LC and the differences in it between different ethnicities and different types of LC. Relevant literatures published before May 7, 2022 on ‘TERT rs2736100 polymorphism and LC susceptibility’ in PubMed, EMbase, CENTRAL, MEDLINE databases were searched through the Internet, and data were extracted. Statistical analysis of data was performed in Revman5.3 software, including drawing forest diagrams, drawing funnel diagrams and so on. Sensitivity and publication bias analysis were performed in Stata 12.0 software. The C allele of TERT rs2736100 was associated with the risk of LC (Overall population: [OR] = 1.21, 95%CI [1.17, 1.25]; Caucasians: [OR] = 1.11, 95%CI [1.06, 1.17]; Asians: [OR] = 1.26, 95%CI [1.21, 1.30]), and Asians had a higher risk of LC than Caucasians (C vs. A: Caucasians: [OR] = 1.11 /Asians: [OR]) = 1.26). The other gene models also showed similar results. The results of stratified analysis of LC patients showed that the C allele was associated with the risk of Non-small-cell lung carcinoma (NSCLC) and Lung adenocarcinoma (LUAD), and the risk of NSCLC and LUAD in Asians was higher than that in Caucasians. The C allele was associated with the risk of Lung squamous cell carcinoma (LUSC) and Small cell lung carcinoma(SCLC) in Asians but not in Caucasians. NSCLC patients ([OR] = 1.27) had a stronger correlation than SCLC patients ([OR] = 1.03), and LUAD patients ([OR] = 1.32) had a stronger correlation than LUSC patients ([OR] = 1.09).In addition, the C allele of TERT rs2736100 was associated with the risk of LC, NSCLC and LUAD in both smoking groups and non-smoking groups, and the risk of LC in non-smokers of different ethnic groups was higher than that in smokers. In the Asians, non-smoking women were more at risk of developing LUAD. The C allele of TERT rs2736100 is a risk factor for LC, NSCLC, and LUAD in different ethnic groups, and the Asian population is at a more common risk. The C allele is a risk factor for LUSC and SCLC in Asians but not in Caucasians. And smoking is not the most critical factor that causes variation in TERT rs2736100 to increase the risk of most LC (NSCLC, LUAD). Therefore, LC is a multi-etiological disease caused by a combination of genetic, environmental and lifestyle factors.
Attentional factorization machine with review-based user–item interaction for recommendation
Authors: Li Zheng , Jin Di , Yuan Ke 
Published: August 2023

AbstractIn recommender systems, user reviews on items contain rich semantic information, which can express users’ preferences and item features. However, existing review-based recommendation methods either use the static word vector model or cannot effectively extract long sequence features in reviews, resulting in the limited ability of user feature expression. Furthermore, the impact of different or useless feature interactions between users and items on recommendation performance is ignored. Therefore, we propose an attentional factorization machine with review-based user–item interaction for recommendation (AFMRUI), which first leverages RoBERTa to obtain the embedding feature of each user/item review, and combines bidirectional gated recurrent units with attention network to highlight more useful information in both user and item reviews. Then we adopt AFM to learn user–item feature interactions to distinguish the importance of different user–item feature interactions and further to obtain more accurate rating prediction, so as to promote recommendation. Finally, we conducted performance evaluation on five real-world datasets. Experimental results on five datasets demonstrated that the proposed AFMRUI outperformed the state-of-the-art review-based methods regarding two commonly used evaluation metrics.
Ceftazidime-assisted synthesis of ultrasmall chitosan nanoparticles for biofilm penetration and eradication of Pseudomonas aeruginosa
Authors: Zheng Xiaoran , Gao Min , Wu Liangquan , Lu Xin , Lin Qiuqi , Zhong Hai , Lu Yingfei , Zhang Yunlei , Zhang Xiuwei 
Published: August 2023

AbstractPseudomonas aeruginosa (P. aeruginosa) infections present a grave threat to immunocompromised individuals, particularly those with cystic fibrosis due to the development of bacterial biofilms. In this study, we engineered self-assembling chitosan-ceftazidime nanoparticles (CSCE) capable of effectively penetrating biofilms and eradicating P. aeruginosa. The CSCE nanoparticles were synthesized through ionic cross-linking, combining negatively charged ceftazidime with positively charged chitosan, resulting in uniform nanoparticles measuring approximately 40 nm in diameter, exhibiting high dispersity and excellent biocompatibility. Remarkably, these nanoparticles exhibited significant inhibition of P. aeruginosa growth, reduced pyocyanin production, and diminished biofilm formation, achieving a maximum inhibition rate of 22.44%. Furthermore, in vivo investigations demonstrated enhanced survival in mice with abdominal P. aeruginosa infection following treatment with CSCE nanoparticles, accompanied by reduced levels of inflammatory cytokines Interleukin-6 (125.79 ± 18.63 pg/mL), Interleukin-17 (125.67 ± 5.94 pg/mL), and Tumor Necrosis Factor-α (135.4 ± 11.77 pg/mL). Critically, mice treated with CSCE nanoparticles showed no presence of bacteria in the bloodstream following intraperitoneal P. aeruginosa infection. Collectively, our findings highlight the potential of these synthesized nanoparticles as effective agents against P. aeruginosa infections.
Persistence of pathogens and bacterial community dynamics in tropical soil after application of raw sewage
Authors: Marques Marcus Vinícius Araújo , Lopes Bruna Coelho , Silvério Thiago Henrique Ribeiro , von Sperling Marcos , Neves Thiago de Alencar 
Published: August 2023

AbstractThe objective of this work was to evaluate the persistence of faecal indicators and pathogenic organisms (Salmonella spp., Escherichia coli and viable helminth eggs) and the structure/diversity of bacterial communities in soil receiving raw sewage (RS) for an extended period of application (3 uninterrupted years). In the experimental design, three treatments were defined: (1) Control soil, characterized by the analysis of a composite sample collected in an area of similar soil, but not a recipient of RS (TSC); (2) Soil receiving conventional mineral fertilization, and furrow irrigation with supply water (TW); and (3) Fertirrigated soil with RS applied by furrows (TF). The results of persistence of pathogenic organisms and indicators in TF indicated a sanitary quality similar to the control soil (TSC), thus potentially bringing low risks of contamination with pathogens present in the soil. The presence of viable helminth eggs was not identified in any treatment studied, because of its low concentration in the raw sewage of the studied system. The TW, TF and TSC treatments had 34.8% of bacterial diversity in common. The bacterial composition of the soil showed a predominance of the Proteobacteria phylum in all treatments studied; however, TF was the one with the highest relative abundance of this phylum (44.8%).
Biosynthesis of ansamitocin P-3 incurs stress on the producing strain Actinosynnema pretiosum at multiple targets
Authors: Huang Qungang , Zhang Xin , Guo Ziyue , Fu Xinnan , Zhao Yilei , Kang Qianjin , Bai Linquan 
Published: August 2023

AbstractMicrobial bioactive natural products mediate ecologically beneficial functions to the producing strains, and have been widely used in clinic and agriculture with clearly defined targets and underlying mechanisms. However, the physiological effects of their biosynthesis on the producing strains remain largely unknown. The antitumor ansamitocin P-3 (AP-3), produced by Actinosynnema pretiosum ATCC 31280, was found to repress the growth of the producing strain at high concentration and target the FtsZ protein involved in cell division. Previous work suggested the presence of additional cryptic targets of AP-3 in ATCC 31280. Herein we use chemoproteomic approach with an AP-3-derived photoaffinity probe to profile the proteome-wide interactions of AP-3. AP-3 exhibits specific bindings to the seemingly unrelated deoxythymidine diphosphate glucose-4,6-dehydratase, aldehyde dehydrogenase, and flavin-dependent thymidylate synthase, which are involved in cell wall assembly, central carbon metabolism and nucleotide biosynthesis, respectively. AP-3 functions as a non-competitive inhibitor of all three above target proteins, generating physiological stress on the producing strain through interfering diverse metabolic pathways. Overexpression of these target proteins increases strain biomass and markedly boosts AP-3 titers. This finding demonstrates that identification and engineering of cryptic targets of bioactive natural products can lead to in-depth understanding of microbial physiology and improved product titers.
Constrained optimization via quantum Zeno dynamics
Authors: Herman Dylan , Shaydulin Ruslan , Sun Yue , Chakrabarti Shouvanik , Hu Shaohan , Minssen Pierre , Rattew Arthur , Yalovetzky Romina , Pistoia Marco 
Published: August 2023

AbstractConstrained optimization problems are ubiquitous in science and industry. Quantum algorithms have shown promise in solving optimization problems, yet none of the current algorithms can effectively handle arbitrary constraints. We introduce a technique that uses quantum Zeno dynamics to solve optimization problems with multiple arbitrary constraints, including inequalities. We show that the dynamics of quantum optimization can be efficiently restricted to the in-constraint subspace on a fault-tolerant quantum computer via repeated projective measurements, requiring only a small number of auxiliary qubits and no post-selection. Our technique has broad applicability, which we demonstrate by incorporating it into the quantum approximate optimization algorithm (QAOA) and variational quantum circuits for optimization. We evaluate our method numerically on portfolio optimization problems with multiple realistic constraints and observe better solution quality and higher in-constraint probability than state-of-the-art techniques. We implement a proof-of-concept demonstration of our method on the Quantinuum H1-2 quantum processor.
Direct observation of Néel-type skyrmions and domain walls in a ferrimagnetic DyCo3 thin film
Authors: Luo Chen , Chen Kai , Ukleev Victor , Wintz Sebastian , Weigand Markus , Abrudan Radu-Marius , Prokeš Karel , Radu Florin 
Published: August 2023

AbstractIsolated magnetic skyrmions are stable, topologically protected spin textures that are at the forefront of research interests today due to their potential applications in information technology. A distinct class of skyrmion hosts are rare earth - transition metal (RE-TM) ferrimagnetic materials. To date, the nature and the control of basic traits of skyrmions in these materials are not fully understood. We show that for an archetypal ferrimagnetic material DyCo3 that exhibits a strong perpendicular anisotropy, the ferrimagnetic skyrmion size can be tuned by an external magnetic field. Moreover, by taking advantage of the high spatial resolution of scanning transmission X-ray microscopy (STXM) and utilizing a large x-ray magnetic linear dichroism (XMLD) contrast that occurs naturally at the RE resonant edges, we resolve the nature of the magnetic domain walls of ferrimagnetic skyrmions. We demonstrate that through this method one can easily discriminate between Bloch and Néel type domain walls for each individual skyrmion. For all isolated ferrimagnetic skyrmions, we observe that the domain walls are of Néel-type. This key information is corroborated with results of micromagnetic simulations and allows us to conclude on the nature of the Dzyaloshinskii-Moriya interaction (DMI) which concurs to the stabilisation of skyrmions in this ferrimagnetic system. Establishing that an intrinsic DMI occurs in RE-TM materials will also be beneficial towards a deeper understanding of chiral spin texture control in ferrimagnetic materials.