bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multi-omics and single cell characterization of cancer immunosenescence landscape
Authors: Wei Qiuxia , Chen Ruizhi , He Xue , Qu Yanan , Yan Changjian , Liu Xiaoni , Liu Jing , Luo Jiahao , Yu Zining , Hu Wenping , Wang Liqun , Lin Xiaoya , Wu Chaoling , Xiao Jinyuan , Zhou Haibo , Wang Jing , Zhu Mingxia , Yang Ping , Chen Yingtong , Tan Qilong , Yuan Xiaoliang , Jing Hongmei , Zhang Weilong 
Published: July 2024

AbstractCellular senescence (CS) is closely related to tumor progression. However, the studies about CS genes across human cancers have not explored the relationship between cancer senescence signature and telomere length. Additionally, single-cell analyses have not revealed the evolutionary trends of malignant cells and immune cells at the CS level. We defined a CS-associated signature, called “senescence signature”, and found that patients with higher senescence signature had worse prognosis. Higher senescence signature was related to older age, higher genomic instability, longer telomeres, increased lymphocytic infiltration, higher pro-tumor immune infiltrates (Treg cells and MDSCs), and could predict responses to immune checkpoint inhibitor therapy. Single-cell analysis further reveals malignant cells and immune cells share a consistent evolutionary trend at the CS level. MAPK signaling pathway and apoptotic processes may play a key role in CS, and senescence signature may effectively predict sensitivity of MEK1/2 inhibitors, ERK1/2 inhibitors and BCL-2 family inhibitors. We also developed a new CS prediction model of cancer survival and established a portal website to apply this model (https://bio-pub.shinyapps.io/cs_nomo/).
Telomere-to-telomere genome assembly of the goose Anser cygnoides
Authors: Zhao Hongchang , Zhou Hao , Sun Guobo , Dong Biao , Zhu Wenqi , Mu Xiaohui , Li Xiaoming , Wang Jun , Zhao Mengli , Yang Wenhao , Zhang Gansheng , Ji Rongchao , Geng Tuoyu , Gong Daoqing , Meng He , Wang Jian 
Published: July 2024

AbstractOur study presents the assembly of a high-quality Taihu goose genome at the Telomere-to-Telomere (T2T) level. By employing advanced sequencing technologies, including Pacific Biosciences HiFi reads, Oxford Nanopore long reads, Illumina short reads, and chromatin conformation capture (Hi-C), we achieved an exceptional assembly. The T2T assembly encompasses a total length of 1,197,991,206 bp, with contigs N50 reaching 33,928,929 bp and scaffold N50 attaining 81,007,908 bp. It consists of 73 scaffolds, including 38 autosomes and one pair of Z/W sex chromosomes. Importantly, 33 autosomes were assembled without any gap, resulting in a contiguous representation. Furthermore, gene annotation efforts identified 34,898 genes, including 436,162 RNA transcripts, encompassing 806,158 exons, 743,910 introns, 651,148 coding sequences (CDS), and 135,622 untranslated regions (UTR). The T2T-level chromosome-scale goose genome assembly provides a vital foundation for future genetic improvement and understanding the genetic mechanisms underlying important traits in geese.
Dataset of soil hydraulic parameters in the Yellow River Basin based on in situ deep sampling
Authors: Tong Yongping , Wang Yunqiang , Zhou Jingxiong , Guo Xiangyu , Wang Ting , Xu Yuting , Sun Hui , Zhang Pingping , Li Zimin , Lauerwald Ronny 
Published: July 2024

AbstractSoil hydraulic parameters are vital for precisely characterizing soil hydrological processes, which are critical indicators for regulating climate change effects on terrestrial ecosystems and governing feedbacks between water, energy, and carbon–nitrogen cycles. Although many studies have integrated comprehensive soil datasets, data quality and cost challenges result in data completeness deficiencies, especially for deep soil information. These gaps not only impede methodological endeavours but also constrain soil parameter-based ecosystem process studies spanning from local profiles to global earth system models. We established a soil dataset across the entire Yellow River Basin (YRB) (795,000 km2) using high-density in situ field sampling. This observation-based dataset contains records of soil texture (2924), bulk density (2798), saturated hydraulic conductivity (2782), and water retention curve parameters (1035) down to a maximum depth of 5 m. This dataset, which extends the recorded data range for deep soil hydraulic parameters, is valuable as a direct data resource for environmental, agronomical and hydrological studies in the YRB and regions with similar pedological and geological backgrounds around the world.
Hybrid ant colony-based inter-cluster routing protocol for FANET
Authors: Yang Siwei , Wang Shu , Li Tingli , Hu Tao , Xu Ziliang , He Renze , Zhang Bing 
Published: July 2024

AbstractThis study addresses the challenges in large-scale unmanned aerial vehicle (UAV) clusters, specifically the scalability issues and limitations of using reactive routing protocols for inter-cluster routing. These traditional methods place an excessive burden on cluster heads and struggle to adapt to frequently changing topologies, leading to decreased network performance. To solve these problems, we propose an innovative inter-cluster routing protocol (ICRP), which is based on a hybrid ant colony algorithm. During the route establishment phase, ICRP uses this algorithm to identify the optimal relay node. This approach is inspired by the foraging behavior of Physarum polycephalum, combining factors such as the number of hops from the source node, the load condition of the node, and its weight in the pheromone calculation. In the route maintenance phase, ICRP uses a predictive repair and contraction mechanism to dynamically maintain routes, accommodating the high mobility of UAVs. Comparative simulations in OMNeT +  + showed that this protocol surpasses ad-hoc on-demand distance vector (AODV), fuzzy-logic-assisted-AODV, and Enhanced-Ant-AODV routing protocols in packet delivery rate and end-to-end transmission delay. Furthermore, it showed superior adaptation to network environments with high-speed node mobility.
Improving prediction of blood cancer using leukemia microarray gene data and Chi2 features with weighted convolutional neural network
Authors: Alabdulqader Ebtisam Abdullah , Alarfaj Aisha Ahmed , Umer Muhammad , Eshmawi Ala’ Abdulmajid , Alsubai Shtwai , Kim Tai-hoon , Ashraf Imran 
Published: July 2024

AbstractBlood cancer has emerged as a growing concern over the past decade, necessitating early diagnosis for timely and effective treatment. The present diagnostic method, which involves a battery of tests and medical experts, is costly and time-consuming. For this reason, it is crucial to establish an automated diagnostic system for accurate predictions. A particular field of focus in medical research is the use of machine learning and leukemia microarray gene data for blood cancer diagnosis. Even with a great deal of research, more improvements are needed to reach the appropriate levels of accuracy and efficacy. This work presents a supervised machine-learning algorithm for blood cancer prediction. This work makes use of the 22,283-gene leukemia microarray gene data. Chi-squared (Chi2) feature selection methods and the synthetic minority oversampling technique (SMOTE)-Tomek resampling is used to overcome issues with imbalanced and high-dimensional datasets. To balance the dataset for each target class, SMOTE-Tomek creates synthetic data, and Chi2 chooses the most important features to train the learning models from 22,283 genes. A novel weighted convolutional neural network (CNN) model is proposed for classification, utilizing the support of three separate CNN models. To determine the importance of the proposed approach, extensive experiments are carried out on the datasets, including a performance comparison with the most advanced techniques. Weighted CNN demonstrates superior performance over other models when coupled with SMOTE-Tomek and Chi2 techniques, achieving a remarkable 99.9% accuracy. Results from k-fold cross-validation further affirm the supremacy of the proposed model.
Assessment of serum proprotein convertase subtilisin/kexin type 9 in pediatric sepsis syndrome
Authors: Mousa Suzan Omar , Afifi Mohamed Farouk , Hassuna Noha Anwar , Yassa Michael Fekry , Moness Hend Mohamed 
Published: July 2024

AbstractSepsis is a life-threatening condition that arises when the body's response to infection causes injury to its tissues and organs. Proprotein convertase subtilisin/kexin type 9 (PCSK9) is an enzyme released in response to the drop in cholesterol level occurring in sepsis. Our study aimed to evaluate the prognostic role of serum Proprotein convertase subtilisin/kexin type 9 (PCSK9) level in children with sepsis and severe sepsis. Sixty children were included in this study. They were divided into two groups: 30 children in the sepsis group and 30 in the severe sepsis group. Another 30 apparently healthy children were included as a control group. Blood samples were withdrawn from all included children for complete blood count (CBC), renal function tests (RFT), liver function tests (LFT), LDL-cholesterol (LDL-C), blood culture, and serum PCSK9. In this study, PCSK9 and LDL-C were higher in the two sepsis groups than in the control group (p < 0.05). They were also higher in the severe sepsis group than the sepsis group and in the non-survivors than in the survivors (p < 0.05). PCSK9 was positively correlated with length of hospital stay in surviving children (r = 0.67, p = 0.001) and had predicted significant hematological dysfunction (adjusted B =  − 96.95, p = 0.03). In conclusion, the PCSK9 assay can be used as a biomarker for bad prognosis in children suffering from clinical sepsis.
Peak response regularization for localization
Authors: Yu Jiawei , Yao Jinzhen , Zhao Chuangxin , Zhao Xianhong , Hu Qintao 
Published: July 2024

AbstractDeep convolutional neural networks approaches often assume that the feature response has a Gaussian distribution with target-centered peak response, which can be used to guide the target location and classification. Nevertheless, such an assumption is implausible when there is progressive interference from other targets and/or background noise, which produces sub-peaks on the tracking response map and causes model drift. In this paper, we propose a feature response regularization approach for sub-peak response suppression and peak response enforcement and aim to handle progressive interference systematically. Our approach, referred to as Peak Response Regularization (PRR), applies simple-yet-efficient method to aggregate and align discriminative features, which convert local extremal response in discrete feature space to extremal response in continuous space, which enforces the localization and representation capability of convolutional features. Experiments on human pose detection, object detection, object tracking, and image classification demonstrate that PRR improves the performance of image tasks with a negligible computational cost.
Adsorbent based on MOF-5/cellulose aerogel composite for adsorption of organic dyes from wastewater
Authors: Shiri Mohammad , Hosseinzadeh Majid , Shiri Soudeh , Javanshir Shahrzad 
Published: July 2024

AbstractIndustries persistently contribute to environmental pollution by releasing a multitude of harmful substances, including organic dyes, which represent a significant hazard to human health. As a result, the demand for effective adsorbents in wastewater treatment technology is steadily increasing so as to mitigate or eradicate these environmental risks. In response to this challenge, we have developed an advanced composite known as MOF-5/Cellulose aerogel, utilizing the Pampas plant as a natural material in the production of cellulose aerogel. Our investigation focused on analyzing the adsorption and flexibility characteristics of this novel composite for organic dye removal. Additionally, we conducted tests to assess the aerogel’s reusability and determined that its absorption rate remained consistent, with the adsorption capacity of the MOF-5/cellulose aerogel composite only experiencing a marginal 5% reduction. Characterization of the material was conducted through XRD analysis, revealing the cubic structure of MOF aerogel particles under scanning electron microscopy. Our study unequivocally demonstrates the superior adsorption capabilities of the MOF-5/cellulose aerogel composite, particularly evident in its efficient removal of acid blue dye, as evaluated meticulously using UV–Vis spectrophotometric techniques. Notably, our findings revealed an impressive 96% absorption rate for the anionic dye under acidic pH conditions. Furthermore, the synthesized MOF-5/cellulose aerogel composite exhibited Langmuir isotherm behavior and followed pseudo-second-order kinetics during the absorption process. With its remarkable absorption efficiency, MOF-5/cellulose aerogel composites are poised to emerge as leading adsorbents for water purification and various other applications.
Study on the failure mechanism of high-temperature granite under two cooling modes
Authors: Li Chun , Feng Gan , Zhang Xinran , Zhang Chunwang , Hu Yaoqing , Meng Tao 
Published: July 2024

AbstractIn the geothermal development of hot dry rock (HDR), both the drilling of the wellbore and the heat exchange of the heat reservoir involve the effects of different cold and hot conditions on the high-temperature rock mass. The testing machine for rock mechanics was used to conduct a uniaxial compression test and carry out micro testing on the treated samples; furthermore, with the help of scanning electron microscopy the fracture mechanism of granite subjected to different temperatures and cooling methods was studied. The results show: (1) With the gradual increase in temperature, the compressive strength of granite under the two cooling methods gradually decreases. (2) The failure modes of the samples under the two cooling methods are mainly shear failure of the "Y" type. The degree of damage of the sample under water cooling is significantly greater than that under natural cooling. Electron micrographs could confirm these results. (3) It can be obtained by testing the mineral composition and element changes of granite at different temperatures. When the temperature reaches 600℃, its change is more pronounced. The results of this study can provide a theoretical reference for the failure of the wellbore and the degree of fracture of the thermal reservoir rock mass during geothermal development.
Human gastric microbiota analysis of refractory H. pylori infection
Authors: Huang Xianfeng , Zhang Da-ya , Li Da , Lv Yanting , Chen Shiju , Bai Feihu 
Published: July 2024

AbstractH. pylori infection is gaining increasing attention, but detailed investigations into its impact on gastric microbiota remain limited. We collected gastric mucosa samples from 47 individuals divided into three groups: 1. Group HP: patients with initial positive H. pylori infection (25 cases); 2. Group ck: H. pylori-negative patients (14 cases); 3. Group DiffHP: patients with refractory H. pylori infection (8 cases). The samples were analyzed using 16S rDNA sequencing and functional prediction with PICRUSt. Group HP showed differences in flora distribution and function compared to Group ck, while Group DiffHP overlapped with Group HP. The abundances of Aeromonas piscicola, Shewanella algae, Vibrio plantisponsor, Aeromonas caviae, Serratia marcescens, Vibrio parahaemolyticus, Microbacterium lacticum, and Prevotella nigrescens were significantly reduced in both Group DiffHP and Group HP compared to Group ck. Vibrio shilonii was reduced only in Group DiffHP compared to Group ck, while Clostridium perfringens and Paracoccus marinus were increased only in Group DiffHP. LEfSe analysis revealed that Clostridium perfringens and Paracoccus marinus were enriched, whereas Vibrio shilonii was reduced in Group DiffHP compared to Group ck at the species level. In individuals with refractory H. pylori infection, the gastric microbiota exhibited enrichment in various human diseases, organic systems, and metabolic pathways (amino acid metabolism, carbohydrate metabolism, transcription, replication and repair, cell cycle pathways, and apoptosis). Patients with multiple failed H. pylori eradication exhibited significant changes in the gastric microbiota. An increase in Clostridium perfringens and Paracoccus marinus and a decrease in Vibrio shilonii appears to be characteristic of refractory H. pylori infection.
Risks of dairy derived excipients in medications for lactose intolerant and cow milk protein allergic patients
Authors: Figueiredo Alexandra , Auxtero Maria Deolinda , Santo Maria , Casimiro Andreia , Costa Isabel Margarida 
Published: July 2024

AbstractThe use of lactose and cow milk protein (CMP) as potential allergens in pharmaceuticals and their ability to cause allergic reactions remains a significant concern in medicine. Lactose, a common pharmaceutical excipient due to its inert, inexpensive, and stable properties, is found in many prescription-only and over-the-counter medications. However, despite their widespread use, individuals with lactose intolerance (LI) or cow milk protein allergy (CMPA) may experience adverse reactions to these excipients. This study investigated the prevalence of lactose and other dairy-derived ingredients in pharmaceuticals marketed in Portugal. Using the Summary of Product Characteristics (SmPC) from the INFOMED database, various medications, including analgesics, antipyretics, non-steroidal anti-inflammatory drugs (NSAIDs), and antiasthmatics, were analyzed. Results showed a high prevalence of dairy-derived excipients, particularly in antiasthmatic drugs (62.6%) and NSAIDs (39%). Although CMP are not explicitly mentioned in SmPCs, the presence of lactose as an ingredient poses a risk of cross-contamination. The findings emphasize the need for healthcare professionals to be aware of potential allergens in medications and the importance of developing lactose-free alternatives to ensure the safety of patients with LI and CMPA. Further research is required to assess the safety and implications of lactose in medicines for these populations.
The role and mechanism of action of miR-483-3p in mediating the effects of IGF-1 on human renal tubular epithelial cells induced by high glucose
Authors: Abudoureyimu Maidina , Tayier Talaiti , Zhang Ling 
Published: July 2024

AbstractThis study aimed to elucidate the influence of miR-483-3p on human renal tubular epithelial cells (HK-2) under high glucose conditions and to understand its mechanism. Human proximal tubular epithelial cells (HK-2) were exposed to 50 mmol/L glucose for 48 h to establish a renal tubular epithelial cell injury model, denoted as the high glucose group (HG group). Cells were also cultured for 48 h in a medium containing 5.5 mmol/L glucose, serving as the low glucose group. Transfection was performed in various groups: HK-2 + low glucose (control group), high glucose (50 mM) (HG group), high glucose + miR-483-3p mimics (HG + mimics group), high glucose +miR-483-3p inhibitor (HG + inhibitor group), and corresponding negative controls. Real-time quantitative polymerase chain reaction (qPCR) assessed the mRNA expression of miR-483-3p, bax, bcl-2, and caspase-3. Western blot determined the corresponding protein levels. Proliferation was assessed using the CCK-8 assay, and cell apoptosis was analyzed using the fluorescence TUNEL method. Western blot and Masson’s staining were conducted to observe alterations in cell fibrosis post miR-483-3p transfection. Furthermore, a dual-luciferase assay investigated the targeting relationship between miR-483-3p and IGF-1. The CCK8 assay demonstrated that the HG + mimics group inhibited HK-2 cell proliferation, while the fluorescent TUNEL method revealed induced cell apoptosis in this group. Conversely, the HG + inhibitor group promoted cell proliferation and suppressed cell apoptosis. The HG + mimics group upregulated mRNA and protein expression of pro-apoptotic markers (bax and caspase-3), while downregulating anti-apoptotic marker (bcl-2) expression. In contrast, the HG + inhibitor group showed opposite effects. Collagen I and FN protein levels were significantly elevated in the HG + mimics group compared to controls (P < 0.05). Conversely, in the HG + inhibitor group, the protein expression of Collagen I and FN was notably reduced compared to the HG group (P < 0.05). The dual luciferase reporter assay confirmed that miR-483-3p could inhibit the luciferase activity of IGF-1’s 3′-UTR region (P < 0.05). miR-483-3p exerts targeted regulation on IGF-1, promoting apoptosis and fibrosis in renal tubular epithelial cells induced by high glucose conditions.
A rhinopithecus swarm optimization algorithm for complex optimization problem
Authors: Zhou Guoyuan , Wang Dong , Zhou Guoao , Du Jiaxuan , Guo Jia 
Published: July 2024

AbstractThis paper introduces a novel meta-heuristic algorithm named Rhinopithecus Swarm Optimization (RSO) to address optimization problems, particularly those involving high dimensions. The proposed algorithm is inspired by the social behaviors of different groups within the rhinopithecus swarm. RSO categorizes the swarm into mature, adolescent, and infancy individuals. Due to this division of labor, each category of individuals employs unique search methods, including vertical migration, concerted search, and mimicry. To evaluate the effectiveness of RSO, we conducted experiments using the CEC2017 test set and three constrained engineering problems. Each function in the test set was independently executed 36 times. Additionally, we used the Wilcoxon signed-rank test and the Friedman test to analyze the performance of RSO compared to eight well-known optimization algorithms: Dung Beetle Optimizer (DBO), Beluga Whale Optimization (BWO), Salp Swarm Algorithm (SSA), African Vultures Optimization Algorithm (AVOA), Whale Optimization Algorithm (WOA), Atomic Retrospective Learning Bare Bone Particle Swarm Optimization (ARBBPSO), Artificial Gorilla Troops Optimizer (GTO), and Harris Hawks Optimization (HHO). The results indicate that RSO exhibited outstanding performance on the CEC2017 test set for both 30 and 100 dimension. Moreover, RSO ranked first in both dimensions, surpassing the mean rank of the second-ranked algorithms by 7.69% and 42.85%, respectively. Across the three classical engineering design problems, RSO consistently achieves the best results. Overall, it can be concluded that RSO is particularly effective for solving high-dimensional optimization problems.