bluuebunny/crossref_metadata_2025_split huggingface dataset:
Turing pattern of an SIRI model on large-scale homogeneous and heterogeneous networks
Authors: He Le , Su Haijun 
Published: May 2023

Abstract
Taking into account the spatial flow and relapse behaviors, this paper establishes a network-organized reaction-diffusion system for disease spreading with Laplacian matrices. In this paper, the Turing branch of the system is studied, and the derivation of the necessary conditions for Turing instability is extended from homogeneous networks to heterogeneous diffusion environment. Here, it has been demonstrated that the system cannot exhibit Turing instability under conditions of constant growth, linear growth, and Logistic growth in susceptible individuals. Further, we assume that the susceptible satisfy the Logistic growth model with Allen effects, and investigate the system's Turing pattern by numerical methods. The simulation results for homogeneous networks show that the infection rate can significantly change the population distribution patterns on lattice networks. The results for heterogeneous networks show that the diffusion environments of susceptible population and infected population play a dominant role in the formation of network Turing patterns, and the difference between their average degrees shows a positive correlation with the difficulty of pattern formation.
Alcohol Consumption and Endometrial Cancer: A Mendelian Randomization Study
Authors: Yang Jie , Chang Hui , Jiang Fan , zhang Jinru , Yan Lijuan , Ning Peng 
Published: May 2023

Abstract
Background Endometrial cancer (EC) is a common gynecological tumor in females with an increasing incidence over the past few decades. Alcohol consumption has been linked to the occurrence of various cancers; however, epidemiological studies have shown inconsistent associations between alcohol consumption and EC risk. This study aimed to investigate whether there is a causal relationship between alcohol consumption and EC.Methods Mendelian randomization (MR) analysis was conducted using publicly available summary-level data from genome-wide association studies (GWAS). Fifty-seven single nucleotide polymorphisms (SNPs) were extracted as instrumental variables for alcohol exposure from the Social Science Genetic Association Consortium (SSGAC) GWAS summary data involving 941,287 participants of European ancestry. SNPs for EC were obtained from the Endometrial Cancer Association Consortium, the Endometrial Cancer Epidemiology Consortium, and the UK Biobank, involving 121,885 European participants. The inverse variance weighted (IVW) method was used as the primary method to estimate the causal effect, and the MR-Egger regression and weighted median method were used as supplementary methods. Sensitivity analyses were conducted using the Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO) global test, MR-Egger intercept test, and leave-one-out analysis to evaluate the impact of pleiotropy on causal estimates.Results An increase of 1 standard deviation (SD) of genetically predicted log-transformed alcoholic drinks per day was associated with a 43% reduction in EC risk (odds ratio [OR], 0.57; 95% confidence interval [CI], 0.41–0.79; P༜0.001). Subgroup analysis of EC revealed that alcohol consumption was a protective factor for endometrioid endometrial cancer (EEC) (OR, 0.56; 95% CI, 0.38–0.83; P = 0.004) but not for non-endometrioid endometrial cancer (NEC) (OR, 1.36; 95% CI, 0.40–4.66; P = 0.626). The MR-Egger regression and weighted median method yielded consistent causal effects with the IVW method. The consistent results of sensitivity analyses indicated the reliability of our causal estimates. Additionally, alcohol consumption was associated with decreased human chorionic gonadotropin (HCG) and insulin-like growth factor 1 (IGF1) levels.Conclusion This study suggests that alcohol consumption is a protective factor for EC, particularly for EEC, and this protective effect may be mediated through the reduction of HCG and IGF1.
Identification of biomarkers functioning in the lipid-induced IBS symptoms
Authors: Ran Yamei , Wu Kangqi , Hu Chenglin , Liang Renzheng , Zhang Li , Xiao Juan , Peng Yongmei , Sun Wenjing 
Published: May 2023

Abstract
Background: Fat intake is one of the most important triggers for symptom development in patients with irritable bowel syndrome (IBS). But long-term restriction in fatty foods ingestion may lead to nutritional inadequacies. In this study, we aim to identify the vital genes that function in lipid-induced gastrointestinal symptoms, contributing to precise management of fat control for IBS patients.
Methods: The clinical characteristics of the subjects were collected by questionnaire investigation and analyzed using multivariate logistic regression. Differentially expressed genes (DEG) and signaling pathways were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The infiltrated immune cells in the small intestinal mucosa were analyzed using ImmuInfiltration and CIBERSORT packages. Random forest and SVM-RFE algorithms were used to select hub genes. A receiver operating characteristic curve (ROC) was performed to evaluate the diagnostic significance of each hub gene. Gene Set Enrichment Analysis (GSEA) was conducted to clarify the possible molecular mechanisms of hub genes in the pathogenesis of IBS after lipid infusion.
Results: Fat intake was positively associated with the risk, severity, and quality of life (QOL) of IBS patients. A total of 116 robust DEGs were identified in patients with IBS after lipid infusion using the GSE166869 dataset and were mainly clustered in the immune and inflammatory pathways. The infiltration levels of Neutrophils, CD4+T cells and M1 Macrophages were significantly higher in IBS patients compared to the healthy controls. Furthermore, infiltration levels of Neutrophils and resting memory CD4+ T cells were inversely related to the expression of hub genes (IGKV1D-43, IGKV1-12, APOD, FCGR2A and IGKV2-29). GSEA results of each hub gene suggested the importance of pro-inflammatory pathways in IBS pathogenesis after lipid infusion. After verification, only APOD and FCGR2A were stably down-regulated in both small intestinal mucosa and plasma of IBS patients. The area under the curve of APOD combined with FCGR2A expression was 0.9.
Conclusions: APOD and FCGR2A may act as promising biomarkers for discriminating lipid-sensitive IBS patients and IBS diagnosis. Their potential roles in the immune microenvironment of the small intestinal mucosa may provide a vital clue to IBS precision therapy.
Clinical failure of anti-tau and anti-synuclein antibodies in neurodegeneration: a quantitative systems pharmacology model analysis
Authors: Geerts Hugo , Bergeler Silke , Walker Mike , Graaf Piet van der , Courade Jean-Philippe 
Published: May 2023

AbstractMisfolded proteins in Alzheimer’s disease (AD) and Parkinson’s disease (PD) follow a well-defined connectomics-based spatial progression. Several anti-tau and anti-alpha synuclein (aSyn) antibodies have failed to provide clinical benefit in clinical trials despite substantial target engagement in the experimentally accessible cerebrospinal fluid (CSF). The proposed mechanism of action is reducing neuronal uptake of seed-competent protein from the synaptic cleft. We built a quantitative systems pharmacology (QSP) model to quantitatively simulate intrasynaptic secretion, diffusion and antibody capture in the synaptic cleft, postsynaptic membrane binding and internalization of monomeric and seed-competent tau and aSyn proteins. Integration with a physiologically based pharmacokinetic (PBPK) model allowed us to simulate clinical trials of anti-tau antibodies gosuranemab, tilavonemab, semorinemab, and anti-aSyn antibodies cinpanemab and prasineuzumab. Maximal target engagement for monomeric tau was simulated as 45% (semorinemab) to 99% (gosuranemab) in CSF, 30% to 99% in ISF but only 1% to 3% in the synaptic cleft, leading to a reduction of less than 1% in uptake of seed-competent tau. Simulations for prasineuzumab and cinpanemab suggest target engagement of free monomeric aSyn of only 6-8% in CSF, 4-6% and 1-2% in the ISF and synaptic cleft, while maximal target engagement of aggregated aSyn was predicted to reach 99% and 80% in the synaptic cleft with similar effects on neuronal uptake. The study generates optimal values of selectivity, sensitivity and PK profiles for antibodies. The study identifies a gradient of decreasing target engagement from CSF to the synaptic cleft as a key driver of efficacy, quantitatively identifies various improvements for drug design and emphasizes the need for QSP modelling to support the development of tau and aSyn antibodies. Trial registration : N/A
Impact of COVID-19 Research: A Study on Predicting Influential Scholarly Documents and Utilizing a Domain-Independent Knowledge Graph
Authors: Gollam Rabby , Jennifer D'Souza , Allard Oelen , Lucie Dvorackova , Vojtěch Svátek , Sören Auer 
Published: May 2023

Abstract
Multiple studies have investigated bibliometric features and uncategorized scholarly documents for the influential scholarly document prediction task. In this paper, we describe our work that attempts to go beyond bibliometric metadata to predict influential scholarly documents. Furthermore, this work also examines the influential scholarly document prediction task over categorized scholarly documents. We also introduce a new approach to enhance the document representation method with domain independent knowledge graph to find the influential scholarly document using categorized scholarly content. As the input collection, we use the WHO corpus with scholarly documents on the theme of COVID-19. This study examines different document representation methods for machine learning, including TF-IDF, BOW, and embedding-based language models (BERT). The TF-IDF document representation method works better than others. From various machine learning methods tested, logistic regression outperformed the other for scholarly document category classification, and the random forest algorithm obtained the best results for influential scholarly document prediction, with the help of a domain-independent knowledge graph, specifically DBpedia, to enhance the document representation method for predicting influential scholarly documents with categorical scholarly content. In this case, our study combines state-of-the-art machine learning methods with the BOW document representation method. We also enhance the BOW document representation with the direct type (rdf type) and unqualified relation from DBpedia. From this experiment, we did not find any impact of the enhanced document representation for the scholarly document category classification. We found an effect in the influential scholarly document prediction with categorical data.
Molecular mapping of two novel frost resistance genes in common wheat by 660k SNP array
Authors: Lei Chao , Li Mingzheng , Cheng Zhaopeng , He Wei , Liu Bin , Liu Shuqing , Li Xuejun , Xie Yanzhou 
Published: May 2023

Abstract
Low temperature freezing injury has always been one of the natural factors leading to serious yield reduction of wheat. How to improve the frost resistance of wheat has always been the focus of breeders and geneticists. However, the genetic improvement of wheat frost resistance has been slow, mainly due to the fact that frost resistance is a complex quantitative trait, and field phenotypic identification is relatively difficult. Therefore, the discovery of wheat frost resistance genes and the mapping and cloning of frost resistance genes not only provide a theoretical basis for the genetic improvement of wheat frost resistance, but also help to analyze the molecular mechanism of wheat frost resistance. In this study, the wheat line H261 and its EMS mutants LF2099 and XiNong 239 were used as materials. Frost-resistance / non frost-resistance trait segregation was found in the F2 generation of the mutant LF2099 and XiNong 239, and the separation ratio was 15:1. Genetic analysis showed that the frost resistance of wheat was controlled by two dominant overlapping genes, temporarily named Fr-3 and Fr-4. BSA combined with SNP array was used to locate the frost resistance gene. Fr-3 was located between SSR marker BU100519 and KASP marker AX-94843669. The genetic distance between markers was 1.32 cM, and the corresponding physical interval on Chinese Spring 2B chromosome was 5.41 Mb, including 67 genes with functional annotation. Fr-4 was located between the KASP marker AX-94657955 and the SSR marker LC-23. The genetic distance between the markers was 1.79 cM, and the corresponding physical interval on the Chinese Spring 2D chromosome was 2.35 Mb, containing 66 functional annotation genes. Compared with previous studies, Fr-3 and Fr-4 were two new frost resistance genes, which laid the foundation for the fine mapping and cloning of Fr-3 and Fr-4.
Towards smart scanning probe lithography: A framework accelerating nano-fabrication process with in-situ characterization via machine learning
Authors: Zhang Zhen , Liu Yijie , Li Xuexuan , Pei Ben , Ge Lin , Xiong Zhuo 
Published: May 2023

Abstract
Scanning probe lithography (SPL) is a promising technology to fabricate high-resolution, customized and cost-effective features at the nanoscale. However, the quality of nano-fabrication, particularly the critical dimension, is significantly influenced by various SPL fabrication techniques and their corresponding process parameters. Meanwhile, the identification and measurement of nano-fabrication features are very time-consuming and subjective. To tackle these challenges, we propose a novel framework for process parameter optimization and feature segmentation of SPL via machine learning (ML). Different from traditional SPL techniques that rely on manual labeling-based experimental methods, the proposed framework intelligently extracts reliable and global information for statistical analysis to fine-tune and optimize process parameters. Based on the proposed framework, we realized the processing of smaller critical dimensions through the optimization of process parameters, and performed direct-write nano-lithography on a large scale. Furthermore, data-driven feature extraction and analysis could potentially provide guidance for other characterization methods and fabrication quality optimization.
Increasing grain selenium concentration via genetic and agronomic innovations.
Authors: Daud Mohammed Feizel Bin , Bilsborrow Paul , Rempelos Leonidas , Cakmak Ismail , Leifert Carlo 
Published: May 2023

Abstract

Aims
To evaluate the potential to enhance grain Selenium (Se) concentration in wheat through agronomic innovation practices and exploitation of existing genetic variation.
Methods
Grain samples from field experiments carried out as part of the EU projects Nitrogen Use Efficiency (NUE-CROPS), Healthy Minor Cereals (HMC) and Quality Low Input Food (QLIF) were analysed to identify the effects of wheat species/variety, fertiliser type and crop protection regime on grain yield, grain protein and selenium concentrations.
Results
Fertiliser type significantly affected grain Se concentration. In the NUE-CROPS and QLIF trials the use of farm-yard manure (FYM) resulted in significantly higher grain Se concentration when compared with mineral fertiliser applied at the same N input level. Similarly, in the HMC trial, FYM and cattle slurry resulted in a significantly higher grain Se concentration compared with biogas digestate and mineral fertiliser. In the QLIF trials, organic crop protection resulted in significantly higher grain Se concentration when compared with conventional crop protection. The NUE-CROPS and HMC trials detected significant differences between varieties of both common wheat (Triticum aestivum) and spelt (T. spelta). Correlation analyses across the trials identified a negative correlation between yield and grain Se concentration for spelt and positive correlation between plant height and Se concentration for both species.
Conclusions
Higher Se concentrations in the taller spelt varieties suggest that there is considerable potential to breed/select for high grain Se by exploiting traits/genetic variation present in older, traditional wheat species (e.g. spelt).
BongHope: An Annotated Corpus for Bengali Hope Speech Detection
Authors: Nath Tanusree , Singh Vivek Kumar , Gupta Vedika 
Published: May 2023

Abstract
The rapid growth of social media usage has resulted in huge volume of online content, which includes instances of spread of negativity through the influence of hateful speeches as well as innumerable instances of social media providing supportive and encouraging content, which is often referred to as hope speech. Hope Speech has been recently defined in the context of online content as a textual content that promotes peace and reflects a hopeful attitude. Recently some research has been conducted on automatic detection of hope speech in different languages, including English, Tamil, Malayalam, Spanish and Kannada. However, to the best of our knowledge, there is no work on hope speech research in Bengali language text. Bengali is a language with more than 210 million speakers[2] and a lot of content in various social media platforms. Therefore, it is important to develop appropriate computational methods for automatic detection of text in Bengali as Hope and Non-Hope speech. One possible reason for lack of hope speech research in Bengali language is perhaps the non-availability of suitable dataset/ corpus for the purpose. This work, therefore, attempts to bridge this research gap by presenting a suitably curated and annotated high quality dataset comprising of tweets in Bengali language for the purpose of hope speech research. Several state-of-the-art computational models are applied on the created dataset and the results obtained confirm the suitability of the dataset for hope speech research.
[2] https://www.britannica.com/topic/Bengali-language
Effects of Osmolality of Rice Sports Drinks on Sports Performance
Authors: Peepathum Prasit , Mitranun Witid , Jirarattanarangsri Wachira , Surawang Suthat , Loakuldilok Thunnop , Koonrungsesomboon Nut , Braspaiboon Sukan , Osiriphun Sukhuntha 
Published: May 2023

Abstract
Sports drinks are developed to improve performance and prevent or treat dehydration, heatstroke, and muscle cramps. The osmolality and pH of sports drinks affect fluid retention and restoration of fluids lost due to dehydration. This study aimed to compare the effects of a new rice-based sports drink (hypertonic, D group) on performance and related sports physiology with that of four other drinks (control, group A; isotonic, group B; hypotonic, group C; commercial, group E), and to develop a range of rice-based sports drinks. The pH, total titratable acidity, nutritional value, and osmolality of the five drinks were measured in vitro. The association between the osmolality of sports drinks and performance was determined in 20 football players. Tests were performed using a cycle ergometer, after which the blood samples were obtained. Blood glucose levels were significantly higher in groups B, C, D, and E than in the control group (p < 0.05). Blood lactate levels were significantly lower in group D than in the other groups after exercise (p < 0.05). The osmolality of the hypertonic rice sports drink was 402.34 mOsmol/kg, indicating that this drink is expected to enhance endurance performance. Consumption of hypotonic rice drinks affects endurance performance in a similar manner to isotonic drinks and may be more beneficial to endurance performance relative to water and hypotonic drinks that lack sodium. Rice hypertonic drinks can even improve performance by drawing fluid from the circulation into the gut. Understanding osmolality and sports performance values can be useful in commercial beverage production and sports nutrition.
Identification of Quantitative Trait Loci for Drought Tolerance in Bukoba/ Kijivu Andean Mapping Population of Common Bean
Authors: Hamabwe Swivia M , Otieno Nicholas , Soler-Garzón Alvaro , Miklas Phillip , Parker Travis , Kramer David M , Chattopadhyay Abhijnan , Cheelo Pride , Kuwabo Kuwabo , kamfwa kelvin 
Published: May 2023

Abstract
Drought is a major production constraint of common bean (Phaseolus vulgaris L.) worldwide. The objective of this study was to identify the Quantitative Trait Loci (QTL) for drought tolerance in an Andean population of Recombinant Inbred Lines (RILs). A total of 155 F5:7 RILs derived from a cross between Kijivu (drought tolerant) and Bukoba (drought susceptible) were evaluated for drought tolerance in field and pot experiments. Four field experiments were conducted at three locations, including the University of Zambia Research Farm, Golden Valley Agricultural Research Farm, and Kabwe Zambia Agricultural Research Institute Farm, in 2021 and 2022. All field trials were conducted in the dry season under irrigation. The 155 RILs were genotyped with 11,292 SNPs, and composite interval mapping was conducted to identify QTL for drought tolerance. Seed yield for Kijivu under drought stress was consistently higher than for Bukoba across all four field trials. A total of 71 QTL were identified for morphological, agronomic, and physiological traits under drought stress and non-stress conditions. However, the majority of these QTL were specific to drought stress. QTL “hotspots” for drought tolerance were identified on chromosomes Pv06, Pv07, and Pv10. Extensive co-localizations for agronomic and morpho-physiological traits under drought stress were observed at the three drought-tolerance QTL hotspots. Additionally, these three QTL hotspots overlapped with previously identified QTL for drought tolerance, while several other identified QTL are novel. The three identified QTL hotspots could be used in future marker-assisted selection for drought tolerance in common bean.
Low ACADM expression predicts poor prognosis and suppressive tumor microenvironment in clear cell renal cell carcinoma
Authors: Zhou Libin , Yin Min , Guo Fei , Yu Zefeng , Weng Guobin , Long Huimin 
Published: May 2023

Abstract

Clear cell renal cell carcinoma (ccRCC) represents a highly frequent renal cancer subtype. However, medium-chain acyl-CoA dehydrogenase (ACADM) encodes an important enzyme responsible for fatty acid β-oxidation (FAO) and its association with prognosis and immunity in cancers has rarely been reported. Therefore, the present work focused on exploring ACADM’s expression and role among ccRCC cases. We used multiple public databases and showed the hypo levels of ACADM protein and mRNA within ccRCC, which was attributed to the hypermethylation of the ACADM promoter region. Additionally, we found that ACADM down-regulation showed remarkable relation to advanced stage, high histological grade, as well as dismal prognostic outcome. As suggested by Kaplan-Meier curve analysis, cases showing low ACADM levels displayed shorter overall survival (OS) as well as disease-free survival (DFS). Moreover, according to univariate/multivariate Cox regression, ACADM-mRNA independently predicted prognosis of ccRCC. In addition, this work conducted immunohistochemistry for validating ACADM protein expression and its prognostic role in ccRCC samples. KEGG and GO analyses revealed significantly enriched genes related to ACADM expression during fatty acid metabolism. We also found that the low ACADM expression was closely related to immunosuppressive cells and, ultimately, poor response to immunotherapies. In conclusion, our results confirmed that downregulated ACADM predicted a poor prognosis for ccRCC and a poor response to immunotherapy. Our results provide important data for developing immunotherapy for ccRCC.