bluuebunny/crossref_metadata_2025_split huggingface dataset:
Unveiling the A-to-I mRNA editing machinery and its regulation and evolution in fungi
Authors: Feng Chanjing , Xin Kaiyun , Du Yanfei , Zou Jingwen , Xing Xiaoxing , Xiu Qi , Zhang Yijie , Zhang Rui , Huang Weiwei , Wang Qinhu , Jiang Cong , Wang Xiaojie , Kang Zhensheng , Xu Jin-Rong , Liu Huiquan 
Published: May 2024

AbstractA-to-I mRNA editing in animals is mediated by ADARs, but the mechanism underlying sexual stage-specific A-to-I mRNA editing in fungi remains unknown. Here, we show that the eukaryotic tRNA-specific heterodimeric deaminase FgTad2-FgTad3 is responsible for A-to-I mRNA editing in Fusarium graminearum. This editing capacity relies on the interaction between FgTad3 and a sexual stage-specific protein called Ame1. Although Ame1 orthologs are widely distributed in fungi, the interaction originates in Sordariomycetes. We have identified key residues responsible for the FgTad3-Ame1 interaction. The expression and activity of FgTad2-FgTad3 are regulated through alternative promoters, alternative translation initiation, and post-translational modifications. Our study demonstrates that the FgTad2-FgTad3-Ame1 complex can efficiently edit mRNA in yeasts, bacteria, and human cells, with important implications for the development of base editors in therapy and agriculture. Overall, this study uncovers mechanisms, regulation, and evolution of RNA editing in fungi, highlighting the role of protein-protein interactions in modulating deaminase function.
Fused in sarcoma (FUS) inhibits milk production efficiency in mammals
Authors: Shao Haili , Huang Jipeng , Wang Hui , Wang Guolei , Yang Xu , Cheng Mei , Sun Changjie , Zou Li , Yang Qin , Zhang Dandan , Liu Zhen , Jiang Xuelong , Shi Lei , Shi Peng , Han Baowei , Jiao Baowei 
Published: May 2024

AbstractEfficient milk production in mammals confers evolutionary advantages by facilitating the transmission of energy from mother to offspring. However, the regulatory mechanism responsible for the gradual establishment of milk production efficiency in mammals, from marsupials to eutherians, remains elusive. Here, we find that mammary gland of the marsupial sugar glider contained milk components during adolescence, and that mammary gland development is less dynamically cyclic compared to that in placental mammals. Furthermore, fused in sarcoma (FUS) is found to be partially responsible for this establishment of low efficiency. In mouse model, FUS inhibit mammary epithelial cell differentiation through the cyclin-dependent kinase inhibitor p57Kip2, leading to lactation failure and pup starvation. Clinically, FUS levels are negatively correlated with milk production in lactating women. Overall, our results shed light on FUS as a negative regulator of milk production, providing a potential mechanism for the establishment of milk production from marsupial to eutherian mammals.
Overcoming strength-ductility tradeoff with high pressure thermal treatment
Authors: Tang Yao , Wang Haikuo , Ouyang Xiaoping , Wang Chao , Huang Qishan , Zhao Qingkun , Liu Xiaochun , Zhu Qi , Hou Zhiqiang , Wu Jiakun , Zhang Zhicai , Li Hao , Yang Yikan , Yang Wei , Gao Huajian , Zhou Haofei 
Published: May 2024

AbstractConventional material processing approaches often achieve strengthening of materials at the cost of reduced ductility. Here, we show that high-pressure and high-temperature (HPHT) treatment can help overcome the strength-ductility trade-off in structural materials. We report an initially strong-yet-brittle eutectic high entropy alloy simultaneously doubling its strength to 1150 MPa and its tensile ductility to 36% after the HPHT treatment. Such strength-ductility synergy is attributed to the HPHT-induced formation of a hierarchically patterned microstructure with coherent interfaces, which promotes multiple deformation mechanisms, including dislocations, stacking faults, microbands and deformation twins, at multiple length scales. More importantly, the HPHT-induced microstructure helps relieve stress concentration at the interfaces, thereby arresting interfacial cracking commonly observed in traditional eutectic high entropy alloys. These findings suggest a new direction of research in employing HPHT techniques to help develop next generation structural materials.
Pharmaceutical treatment status of patients with COPD in the community based on medical Internet of Things: a real-world study
Authors: Wu Peng , Jiang Yi-qun , Si Feng-li , Wang Huan-ying , Song Xiao-bo , Sheng Chun-feng , Xu Xun , Li Fan , Zhang Jing 
Published: May 2024

AbstractThis study aimed to investigate the real-world standardisation and adherence of medical treatment regimens in patients with chronic obstructive pulmonary disease (COPD) in the community for making future management strategy. The follow-up data and treatment information of patients with COPD, which were collected through the Management Information Center of COPD (MICCOPD) in 21 community health service centres in Songjiang District, a countryside region of Shanghai. Concordance between the pharmaceutical treatment plan and recommendation of 2017 Global Initiative for Chronic Obstructive Lung Disease (GOLD) report during the follow-up management period, as well as the medication adherence by patients,were analysed. Out of the 2044 patients diagnosed with COPD, 814 patients (39.8%) who had an initial record of medication use were found to meet the inclusion criteria. The most common medication regimens were long-acting beta-agonist plus inhaled corticosteroids (35.9%) and oral bronchodilators (41.9%). Among these 814 patients, 45.7%, 38.0%, 31.6% and 14.6% adhered to the treatment after 6, 12, 18 and 24 months of follow-up, respectively. The concordance rate with the regimens recommended by the 2017 GOLD guidelines was 35.5% at baseline, 35.5% at 6 months, 32.7% at 12 months, 35.4% at 18 months and 37% at 24 months. The compliance and guideline consistency rates of patients with COPD in the community under the management of general practitioners need to be improved. Enhancing general practitioner proficiency in the prevention and management of COPD and increasing patient awareness of the condition, are crucial standardising and improving adherence to initial and follow-up COPD treatments.
How accurate are existing land cover maps for agriculture in Sub-Saharan Africa?
Authors: Kerner Hannah , Nakalembe Catherine , Yang Adam , Zvonkov Ivan , McWeeny Ryan , Tseng Gabriel , Becker-Reshef Inbal 
Published: May 2024

AbstractSatellite Earth observations (EO) can provide affordable and timely information for assessing crop conditions and food production. Such monitoring systems are essential in Africa, where food insecurity is high and agricultural statistics are sparse. EO-based monitoring systems require accurate cropland maps to provide information about croplands, but there is a lack of data to determine which of the many available land cover maps most accurately identify cropland in African countries. This study provides a quantitative evaluation and intercomparison of 11 publicly available land cover maps to assess their suitability for cropland classification and EO-based agriculture monitoring in Africa using statistically rigorous reference datasets from 8 countries. We hope the results of this study will help users determine the most suitable map for their needs and encourage future work to focus on resolving inconsistencies between maps and improving accuracy in low-accuracy regions.
ROSPaCe: Intrusion Detection Dataset for a ROS2-Based Cyber-Physical System and IoT Networks
Authors: Puccetti Tommaso , Nardi Simone , Cinquilli Cosimo , Zoppi Tommaso , Ceccarelli Andrea 
Published: May 2024

AbstractMost of the intrusion detection datasets to research machine learning-based intrusion detection systems (IDSs) are devoted to cyber-only systems, and they typically collect data from one architectural layer. Often the attacks are generated in dedicated attack sessions, without reproducing the realistic alternation and overlap of normal and attack actions. We present a dataset for intrusion detection by performing penetration testing on an embedded cyber-physical system built over Robot Operating System 2 (ROS2). Features are monitored from three architectural layers: the Linux operating system, the network, and the ROS2 services. The dataset is structured as a time series and describes the expected behavior of the system and its response to ROS2-specific attacks: it repeatedly alternates periods of attack-free operation with periods when a specific attack is being performed. This allows measuring the time to detect an attacker and the number of malicious activities performed before detection. Also, it allows training an intrusion detector to minimize both, by taking advantage of the numerous alternating periods of normal and attack operations.
Prototyping an Ontological Framework for Cellular Senescence Mechanisms: A Homeostasis Imbalance Perspective
Authors: Yamagata Yuki , Fukuyama Tsubasa , Onami Shuichi , Masuya Hiroshi 
Published: May 2024

AbstractAlthough cellular senescence is a key factor in organismal aging, with both positive and negative effects on individuals, its mechanisms remain largely unknown. Thus, integrating knowledge is essential to explain how cellular senescence manifests in tissue damage and age-related diseases. Here, we propose an ontological model that organizes knowledge of cellular senescence in a computer-readable form. We manually annotated and defined cellular senescence processes, molecules, anatomical structures, phenotypes, and other entities based on the Homeostasis Imbalance Process ontology (HOIP). We described the mechanisms as causal relationships of processes and modelled a homeostatic imbalance between stress and stress response in cellular senescence for a unified framework. HOIP was assessed formally, and the relationships between cellular senescence and diseases were inferred for higher-order knowledge processing. We visualized cellular senescence processes to support knowledge utilization. Our study provides a knowledge base to help elucidate mechanisms linking cellular and organismal aging.
Development of correlations between various engineering rockmass classification systems using railway tunnel data in Garhwal Himalaya, India
Authors: Azad Md. Alquamar , Najeh Taoufik , Raina Autar K. , Singh Neelratan , Ansari Abdullah , Ali Mujahid , Fissha Yewuhalashet , Gamil Yaser , Singh S. K. 
Published: May 2024

AbstractEngineering rockmass classifications are an integral part of design, support and excavation procedures of tunnels, mines, and other underground structures. These classifications are directly linked to ground reaction and support requirements. Various classification systems are in practice and are still evolving. As different classifications serve different purposes, it is imperative to establish inter-correlatability between them. The rating systems and engineering judgements influence the assignment of ratings owing to cognition. To understand the existing correlation between different classification systems, the existing correlations were evaluated with the help of data of 34 locations along a 618-m-long railway tunnel in the Garhwal Himalaya of India and new correlations were developed between different rock classifications. The analysis indicates that certain correlations, such as RMR-Q, RMR-RMi, RMi-Q, and RSR-Q, are comparable to the previously established relationships, while others, such as RSR-RMR, RCR-Qn, and GSI-RMR, show weak correlations. These deviations in published correlations may be due to individual parameters of estimation or measurement errors. Further, incompatible classification systems exhibited low correlations. Thus, the study highlights a need to revisit existing correlations, particularly for rockmass conditions that are extremely complex, and the predictability of existing correlations exhibit high variations. In addition to augmenting the existing database, new correlations for metamorphic rocks in the Himalayan region have been developed and presented that can serve as a guide for future rock engineering projects in such formations and aid in developing appropriate excavation and rock support methodologies.
Ultrastructural and immunohistochemical evaluation of hyperplastic soft tissues surrounding dental implants in fibular jaws
Authors: Mustakim Kezia Rachellea , Eo Mi Young , Seo Mi Hyun , Yang Hyeong-Cheol , Kim Min-Keun , Myoung Hoon , Kim Soung Min 
Published: May 2024

AbstractIn reconstructive surgery, complications post-fibula free flap (FFF) reconstruction, notably peri-implant hyperplasia, are significant yet understudied. This study analyzed peri-implant hyperplastic tissue surrounding FFF, alongside peri-implantitis and foreign body granulation (FBG) tissues from patients treated at the Department of Oral and Maxillofacial Surgery, Seoul National University Dental Hospital. Using light microscopy, pseudoepitheliomatous hyperplasia, anucleate and pyknotic prickle cells, and excessive collagen deposition were observed in FFF hyperplastic tissue. Ultrastructural analyses revealed abnormal structures, including hemidesmosome dilation, bacterial invasion, and endoplasmic reticulum (ER) swelling. In immunohistochemical analysis, unfolded protein-response markers ATF6, PERK, XBP1, inflammatory marker NFκB, necroptosis marker MLKL, apoptosis marker GADD153, autophagy marker LC3, epithelial–mesenchymal transition, and angiogenesis markers were expressed variably in hyperplastic tissue surrounding FFF implants, peri-implantitis, and FBG tissues. NFκB expression was higher in peri-implantitis and FBG tissues compared to hyperplastic tissue surrounding FFF implants. PERK expression exceeded XBP1 significantly in FFF hyperplastic tissue, while expression levels of PERK, XBP1, and ATF6 were not significantly different in peri-implantitis and FBG tissues. These findings provide valuable insights into the interconnected roles of ER stress, necroptosis, apoptosis, and angiogenesis in the pathogenesis of oral pathologies, offering a foundation for innovative strategies in dental implant rehabilitation management and prevention.
A comprehensive analysis of spermatozoal RNA elements in idiopathic infertile males undergoing fertility treatment
Authors: Hamilton Matthew , Russell Stewart , Swanson Grace M. , Krawetz Stephen A. , Menezes Karen , Moskovtsev Sergey I. , Librach Clifford 
Published: May 2024

AbstractCurrent approaches to diagnosing male infertility inadequately assess the complexity of the male gamete. Beyond the paternal haploid genome, spermatozoa also deliver coding and non-coding RNAs to the oocyte. While sperm-borne RNAs have demonstrated potential involvement in embryo development, the underlying mechanisms remain unclear. In this study, 47 sperm samples from normozoospermic males undergoing fertility treatment using donor oocytes were sequenced and analyzed to evaluate associations between sperm RNA elements (exon-sized sequences) and blastocyst progression. A total of 366 RNA elements (REs) were significantly associated with blastocyst rate (padj < 0.05), some of which were linked to genes related to critical developmental processes, including mitotic spindle formation and both ectoderm and mesoderm specification. Of note, 27 RE-associated RNAs are predicted targets of our previously reported list of developmentally significant miRNAs. Inverse RE-miRNA expression patterns were consistent with miRNA-mediated down-regulation. This study provides a comprehensive set of REs which differ by the patient’s ability to produce blastocysts. This knowledge can be leveraged to improve clinical screening of male infertility and ultimately reduce time to pregnancy.
An automated multi-layer perceptron discriminative neural network based on Bayesian optimization achieves high-precision one-source single-snapshot direction-of-arrival estimation
Authors: Zhang Bin , He Jiawen , Liu Peishun , Wang Liang , Tang Ruichun 
Published: May 2024

AbstractThis paper proposes an innovative global solution which is a pioneering work applying automated machine learning algorithms to remarkable precision sparse underwater direction-of-arrival (DOA) estimation that views the subaquatic sparse-sampling DOA estimation problem as a classification prediction task. The proposed solution, termed automated multi-layer perceptron discriminative neural network (AutoMPDNN), is built upon a Bayesian optimization framework. AutoMPDNN transforms sparsely sampled time-domain signals into the complex domain, preserving essential components in a one-source single-snapshot scenario. Leveraging Bayesian optimization principles, the algorithm embeds necessary hyperparameters into the loss function, effectively defining it as a maximum likelihood problem using the upper confidence bound function and incorporating sparse signal features. We also explore the model space architecture and introduce variants of AutoMPDNN, denoted as AutoMPDNNs_ln (n = 2,3,4). Through a series of plane wave simulation experiments, it is demonstrated that AutoMPDNN achieves the highest prediction performance for one-source single-snapshot scenarios compared to classical DOA estimation algorithms that incorporate sparse representation approaches, as well as contemporary deep learning DOA methods under varying conditions.
Genetic variability of hepatitis B virus in acute and in different phases of chronic infection in Brazil
Authors: Lago Barbara Vieira , Portilho Moyra Machado , Mello Vinicius Motta , De Sousa Paulo Sergio Fonseca , Angelice Giovana Paula , Marques Bianca Cristina Leires , da Silva Andrade Larissa Tropiano , Marques Vanessa Alves , Lewis-Ximenez Lia Laura , Mello Francisco Campello do Amaral , Villar Livia Melo 
Published: May 2024

AbstractThe selection pressure imposed by the host immune system impacts on hepatitis B virus (HBV) variability. This study evaluates HBV genetic diversity, nucleos(t)ide analogs resistance and HBsAg escape mutations in HBV patients under distinct selective pressures. One hundred and thirteen individuals in different phases of HBV infection were included: 13 HBeAg-positive chronic infection, 9 HBeAg-positive chronic hepatitis, 47 HBeAg-negative chronic infection (ENI), 29 HBeAg-negative chronic hepatitis (ENH) and 15 acute infected individuals. Samples were PCR amplified, sequenced and genetically analyzed for the overlapping POL/S genes. Most HBV carriers presented genotype A (84/113; 74.3%), subgenotype A1 (67/84; 79.7%), irrespective of group, followed by genotypes D (20/113; 17.7%), F (8/113; 7.1%) and E (1/113; 0.9%). Clinically relevant mutations in polymerase (tL180M/M204V) and in the Major Hydrophilic Region of HBsAg (sY100C, T118A/M, sM133T, sD144A and sG145R) were observed. Our findings, however, indicated that most polymorphic sites were located in the cytosolic loops (CYL1-2) and transmembrane domain 4 (TMD4) of HBsAg. Lower viral loads and higher HBV genetic diversity were observed in ENI and ENH groups (p < 0.001), suggesting that these groups are subjected to a higher selective pressure. Our results provide information on the molecular characteristics of HBV in a diverse clinical setting, and may guide future studies on the balance of HBV quasispecies at different stages of infection.
Baicalin enhances the chemotherapy sensitivity of oxaliplatin-resistant gastric cancer cells by activating p53-mediated ferroptosis
Authors: Shao Lihua , Zhu Li , Su Rong , Yang Chunting , Gao Xiaqing , Xu Yan , Wang Hongwei , Guo Chenglong , Li Hailong 
Published: May 2024

AbstractGastric cancer is one of the most common malignant tumors, and chemotherapy is the main treatment for advanced gastric cancer. However, chemotherapy resistance leads to treatment failure and poor prognosis in patients with gastric cancer. Multidrug resistance (MDR) is a major challenge that needs to be overcome in chemotherapy. According to recent research, ferroptosis activation is crucial for tumor therapeutic strategies. In this work, we explored the solution to chemoresistance in gastric cancer by investigating the effects of the Chinese medicine monomer baicalin on ferroptosis. Baicalin with different concentrations was used to treat the parent HGC27 and drug-resistant HGC27/L cells of gastric cancer. Cell viability was measured by CCK8, and synergistic effects of baicalin combined with oxaliplatin were evaluated using Synergy Finder software. The effects of baicalin on organelles and cell morphology were investigated using projective electron microscopy. Iron concentration, MDA production and GSH inhibition rate were measured by colorimetry. ROS accumulation was detected by flow cytometry. The ferroptosis-related genes (IREB2, TfR, GPX4, FTH1), P53, and SLC7A11 were analysed by Western blot, and the expression differences of the above proteins between pretreatment and pretreatment of different concentrations of baicalin, were assayed in both parental HGC27 cells and Oxaliplatin-resistant HGC27/L cells. Mechanically, Baicalin disrupted iron homeostasis and inhibits antioxidant defense, resulting in iron accumulation, lipid peroxide aggregation, and specifically targeted and activated ferroptosis by upregulating the expression of tumor suppressor gene p53, thereby activating the SLC7A11/GPX4/ROS pathway mediated by it. Baicalin activates ferroptosis through multiple pathways and targets, thereby inhibiting the viability of oxaliplatin-resistant gastric cancer HGC27/L cells and enhancing the sensitivity to oxaliplatin chemotherapy.
PermDroid a framework developed using proposed feature selection approach and machine learning techniques for Android malware detection
Authors: Mahindru Arvind , Arora Himani , Kumar Abhinav , Gupta Sachin Kumar , Mahajan Shubham , Kadry Seifedine , Kim Jungeun 
Published: May 2024

AbstractThe challenge of developing an Android malware detection framework that can identify malware in real-world apps is difficult for academicians and researchers. The vulnerability lies in the permission model of Android. Therefore, it has attracted the attention of various researchers to develop an Android malware detection model using permission or a set of permissions. Academicians and researchers have used all extracted features in previous studies, resulting in overburdening while creating malware detection models. But, the effectiveness of the machine learning model depends on the relevant features, which help in reducing the value of misclassification errors and have excellent discriminative power. A feature selection framework is proposed in this research paper that helps in selecting the relevant features. In the first stage of the proposed framework, t-test, and univariate logistic regression are implemented on our collected feature data set to classify their capacity for detecting malware. Multivariate linear regression stepwise forward selection and correlation analysis are implemented in the second stage to evaluate the correctness of the features selected in the first stage. Furthermore, the resulting features are used as input in the development of malware detection models using three ensemble methods and a neural network with six different machine-learning algorithms. The developed models’ performance is compared using two performance parameters: F-measure and Accuracy. The experiment is performed by using half a million different Android apps. The empirical findings reveal that malware detection model developed using features selected by implementing proposed feature selection framework achieved higher detection rate as compared to the model developed using all extracted features data set. Further, when compared to previously developed frameworks or methodologies, the experimental results indicates that model developed in this study achieved an accuracy of 98.8%.