bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dipeptidyl peptidase-4 marks distinct subtypes of human adipose stromal/stem cells with different hepatocyte differentiation and immunoregulatory properties
Authors: Zhang Yu , Hua Mingxi , Ma Xuqing , Li Weihong , Cao Yuqi , Han Xueya , Huang Xiaowu , Zhang Haiyan 
Published: August 2024

Abstract

Background
Human adipose-derived stromal/stem cells (hASCs) play important roles in regenerative medicine and numerous inflammatory diseases. However, their cellular heterogeneity limits the effectiveness of treatment. Understanding the distinct subtypes of hASCs and their phenotypic implications will enable the selection of appropriate subpopulations for targeted approaches in regenerative medicine or inflammatory diseases.
Methods
hASC subtypes expressing dipeptidyl peptidase-4 (DPP4) were identified via fluorescence-activated cell sorting (FACS) analysis. DPP4 expression was knocked down in DPP4+ hASCs via DPP4 siRNA. The capacity for proliferation, hepatocyte differentiation, inflammatory factor secretion and T-cell functionality regulation of hASCs from DPP4−, DPP4+, and control siRNA-treated DPP4+ hASCs and DPP4 siRNA-treated DPP4+ hASCs were assessed.
Results
DPP4+ hASCs and control siRNA-treated DPP4+ hASCs presented a lower proliferative capacity but greater hepatocyte differentiation capacity than DPP4− hASCs and DPP4 siRNA-treated DPP4+ hASCs. Both DPP4+ hASCs and DPP4− hASCs secreted high levels of vascular endothelial growth factor-A (VEGF-A), monocyte chemoattractant protein-1 (MCP-1), and interleukin 6 (IL-6), whereas the levels of other factors, including matrix metalloproteinase (MMP)-1, eotaxin-3, fractalkine (FKN, CX3CL1), growth-related oncogene-alpha (GRO-alpha, CXCL1), monokine induced by interferon-gamma (MIG), macrophage inflammatory protein (MIP)-1beta, and macrophage colony-stimulating factor (M-CSF), were significantly greater in the supernatants of DPP4+ hASCs than in those of DPP4− hASCs. Exposure to hASC subtypes and their conditioned media triggered changes in the secreted cytokine profiles of T cells from healthy donors. The percentage of functional T cells that secreted factors such as MIP-1b and IL-8 increased when these cells were cocultured with DPP4+ hASCs. The percentage of polyfunctional CD8+ T cells that secreted multiple factors, such as IL-17A, tumour necrosis factor alpha (TNF-α) and TNF-β, decreased when these cells were cocultured with supernatants derived from DPP4+ hASCs.
Conclusions
DPP4 may regulate proliferation, hepatocyte differentiation, inflammatory cytokine secretion and T-cell functionality of hASCs. These data provide a key foundation for understanding the important role of hASC subpopulations in the regulation of T cells, which may be helpful for future immune activation studies and allow them to be customized for clinical application.
Construction of Improved Substitution-box With Mobius Transformation on Gf (2 8 ) and Its Application in Image Encryption
Authors: . GULRAIZ , JAMIL MUHAMMAD KAMRAN , ALNEFAIE KHOLOOD , ALI JAVED , ALI RASHAD 
Published: August 2024

Abstract

S-boxes are designed to be computationally efficient, compact and resistant to attacks, making them critical to the overall security of block ciphers. Therefore, a well-designed S-box can significantly increase the strength and robustness of block ciphers against various cryptanalytic attacks. As a result, the researchers continue to explore new and improved S-box designs to enhance the security of block ciphers. In this article the substitution matrix is assembled using the elements of Galois field of order 256 with the help of Mobius transformation. In order to increase its invulnerability an appropriate permutation is used. The proposed S-box is then used to encrypt different images after their security evaluation. At the end the results are compared with the different renowned S-boxes.
AMS subject classification: Primary: 94A60; Secondary: 68P25
Quantum Representation for Deterministic Pushdown Automata
Authors: Puram Varun teja , George K M , Thomas Johnson P 
Published: August 2024

Abstract

There are many papers presenting quantum computing models. The definitions parallel the classical definitions of finite state automata, push down automata, context-free grammars etc. Classical computing model definitions define languages precisely. We can state that a string belongs to a language or does not belong to it with no room for error. Quantum definitions do not possess this certainty. Sacrificing the certainty and adopting a quantum definition of a computing model does not appear to provide any concrete power to the model. Therefore, the path of this paper is to begin from the classical definition and end in a quantum circuit. In this paper we start from a Deterministic Push-Down Automaton (DPDA). We present circuit for state transition and stack operations. The circuits presented can be viewed as independent algorithms. As an example, the approach used to construct the circuit for state transition can be utilized to build the circuit for a function presented as a Boolean matrix.
Induction and genetic verification of homologous haploid plants obtained through the anther culture of Citrus cultivars
Authors: Jin Seong Beom , Park Jee Soo , Lee Dong Hoon , Park Suk Man , Moon Young Eel 
Published: August 2024

Abstract

In this study, an anther culture system was developed for two Citrus varieties known for their genetic value: blood orange (Moro) and mandarin (Lee). Anthers were inoculated on N6 solid medium containing thidiazuron (TDZ, 0.44 mg/L), 6-benzylaminopurine (0.8 mg/L), zeatin (0.43 mg/L), kinetin (0.44 mg/L), 1-naphthaleneacetic acid (0.2 mg/L), 2,4-Dichlorophenoxyacetic acid (0.2 mg/L), and malt extract (500 mg/L). The inoculated anthers were treated with N6 liquid medium containing spermidine (200 µM) and gibberellic acid (GA3, 1 mg/L) and cultured for six weeks. Thereafter, the swollen anthers were transferred to Murashige and Skoog (MS) basal medium enriched with malt extract (500 mg/L), sucrose (50 g/L), TDZ (0.5 mg/L), GA3 (1 mg/L), and gelrite (0.2 %), which induced callus and somatic embryos. These somatic embryos from both varieties were then transferred to a germination medium (MS basal medium containing sorbitol [0.05 M], galactose [0.05 M], malt extract [500 mg/L], GA3 [0.5 mg/L], and gelrite [2 g/L]) to develop into normal plants. However, Lee exhibited significantly slower shoot and root growth compared to Moro. Genetic analysis using barley microsatellite-derived cleaved amplified polymorphic sequence markers indicated that Lee likely originated from haploid plants, whereas Moro retained heterozygosity similar to the parent. Ploidy analysis confirmed Lee as diploid, identical to the control. Internal transcribed spacer region analysis confirmed that Lee was an anther-cultured haploid-derived plant, estimated to be a homozygous diploid carrying recessive genes. These findings highlight potential applications in marker development and cultivar breeding enhancement focused on recessive trait-associated phenotypes and genotypes.
YOLOv9-LSBN: An improved YOLOv9 model for cotton pest and disease identification method
Authors: He Ruohong , Li Ping , Zhu Jikui , Zhang Fengkui , Wang Yulong , Zhang Ting , Yang Daorina , Zhou Bao 
Published: August 2024

Abstract

In order to achieve accurate identification of cotton pests and diseases in a natural complex environment, a cotton pest and disease detection method based on an improved You Only Look Once version 9(YOLOv9) model was proposed.The RepLanLsk module was constructed and replaced with RepNCSPELAN4 of YOLOv9 to enhance the diversity of feature extraction and establish a larger receptive field network; a weighted bidirectional feature pyramid network(BIFPN) was added to achieve bidirectional connections between feature pyramids, ensure optimal feature fusion, and strengthen key pest and disease features in the target area.The results showed that the model had an accuracy of 93\%, a recall rate of 92.4\%, and an average precision of 96.4\% for detecting pest and disease cotton, which were 1.6\%, 0.3\%, and 1\% higher than the original YOLOv9 network model, respectively;Through comparative experiments, it is concluded that the accuracy of this model is higher than that of YOLOv7, YOLOv8x and other models, and YOLOv9-LSBN can better extract subtle features in cotton pest images, and the misjudgment rate is lower than other models. This model can effectively reduce the interference of complex backgrounds, accurately and quickly detect cotton pest targets in images, and can provide a reference for crop pest detection research with complex backgrounds in natural environments.
Local Adaptive Mapping of Karyotype Fitness Landscapes
Authors: Andor Noemi , Beck Richard 
Published: August 2024

Abstract

Aneuploidy is prevalent in most solid tumors and can significantly alter cellular phenotype and fitness. Despite its critical role in tumor evolution, a detailed quantitative understanding of the evolutionary dynamics of aneuploidy remains elusive. To bridge this gap, we developed a novel method to infer the fitness landscape of chromosome-level karyotypes. This method utilizes longitudinal single-cell karyotype data from evolving cell populations to estimate the fitness of thousands of karyotypes proximal to the observed data in karyotype space, enabling the emergence of karyotypes not-yet seen in the input data to be predicted. We validated the predictive capability of our approach using both synthetic data from an agent-based model and empirical data from in vitro and in vivo passaged cell lines. Our analysis of the fitted landscapes suggests several key insights: (1) Whole genome doubling promotes aneuploidy by increasing the spectrum of potentially beneficial copy number alterations; (2) Cisplatin treatment alters the fitness impact of these alterations; (3) The fitness consequences of a copy number alteration (CNA) vary depending on the parental karyotype; (4) The rate of chromosome missegregation can dictate the predominant karyotypes in an evolving population.
Differential Diagnosis of Pulmonary Diseases using Convolutional Neural Network with LSTM Architecture
Authors: Shekar B. H. , Mannan Shazia 
Published: August 2024

Abstract

Pulmonary disorders, including conditions such as Pneumonia, Tuberculosis, and COVID-19, affect millions worldwide, presenting a major global health challenge. Accurate and timely detection of these diseases is crucial for effective treatment and patient care. This research paper introduces a novel CNN-LSTM model for effectively differentiating between and categorizing multiple lung disorders. Leveraging a dataset comprising 4529 chest X-rays (CXRs) collected from Shenzhen, Montgomery, Belarus, and COVID-19 Radiography datasets, the study aims to enhance disease diagnosis accuracy. Contrast-limited Adaptive Histogram Equalization and median filtering techniques have been applied to enhance image quality and reduce noise. Although LSTM networks are typically used for sequential data, this study employed them to capture spatial dependencies within 2D medical images. This approach allowed the model to learn complex representations and retain context from different image regions, enhancing feature extraction and overall performance. LSTM worked by exploiting the neighborhood relationships between pixels in CXRs by treating image patches as sequences. This approach enabled the model to better understand and utilize spatial information, thereby improving accuracy. Furthermore, baseline CNN and CNN-Bi LSTM models were also executed for a comparative study. Among the implemented models, CNN-LSTM emerged as the most effective, achieving an accuracy of 96.26% and precision, recall, F1 score of 96.44%, 96.62%, and 96.49%, respectively. It was followed by CNN-BiLSTM and CNN models with accuracy rates of 95.58% and 94.24%.
Cancer-Associated Fibroblasts induce aggressive stem cell phenotype and chemoresistance in cervical tumoroid-fibroblast co-culture system via upregulating CK17 expression
Authors: Liu Xuemei , Du Xin , Wang Xin , Duan Huimin , Wang Dong , Chen Lu , Yang Zhuang , Yuan Yuncong , Du Hang , Lv Bonan , Deng Rui , Ding Ruyi , Tang Jingyi , Wang Xingran , Ling Shuyu , Chen Shan , Chen Si , Zhou Limin , Shen Chao 
Published: August 2024

Abstract

Cervical cancer is a serious health issue affecting women. Cancer development is the result of co-evolution between tumor cells and tumor stroma microenvironment, and Cancer Associated Fibroblasts (CAFs) is a significant part of tumor stroma and plays a big role in helping cancer cells grow, spread, and become aggressive. To investigate the biological function of CAFs in the progression of cervical cancer, we developed a novel CAFs-integrated cervical tumoroid model that can mimic the tumor microenvironment. Our cultured cervical organoids successfully reproduced key features of cervical tissue epithelium, including cellular composition, histological properties and biomarker distribution. Within the co-culture model, CAFs were found to stimulate cancer cells to acquire an aggressive, stem cell-like phenotype. Additionally, CAFs induced an elevated secretion of collagen I, which altered the extracellular matrix to facilitate tumor metastasis. Of particular interest, we discovered that CAFs modulate the CK17-related signaling pathway, causing upregulation of a suite of genes involved in Epithelial-Mesenchymal Transition (EMT) and Cancer Stem Cell (CSC), thus significantly boosting the invasive capacity of tumor cells. Both CK17-overexpressing tumoroids and those co-cultured with CAFs exhibited similar invasive phenotypes in type I collagen matrices, outperforming control tumoroids in terms of invasiveness and proliferation.Our findings indicate that CAFs likely enhance chemoresistance in tumoroid and contribute to malignant progression partly through CK17 upregulation. This implicates CK17 could be a promising clinical target for cervical cancer prevention and treatment.
Monitoring the shelf life of extra virgin olive oil using Fluorescence spectroscopy
Authors: Hafeez Rimsha , Ahmad Naveed , Ansar Areeba , Saleem Muhammad , Ali Hina 
Published: August 2024

Abstract

To maintain the quality of extra virgin olive oil (EVOO), one important factor is to resist its oxidation during processing and storage. It is challenging task to prevent oxidation in EVOOs since various physical and chemical factors must be under control. In the present study extra virgin olive oil was stored under normal storage conditions for three months and monitored via quality parameters. A non-destructive fluorescence spectroscopy was performed to monitor the oxidation changes in EVOO from different olive growing regions of Pakistan and Al-Jouf region of the Kingdom of Saudi Arabia (KSA). Additionally, the impacts of geographic, climatic, and environmental factors on the oxidation of EVOOs were investigated. Two major changes in the fluorescence emission spectra of EVOO samples were mainly observed: a decrease in fluorescence emission intensities in the range between 500 to 600 nm, 650 to 690 nm, as well as a rise in the fluorescence emission intensities in the 365–500 nm region. These two changes were related to a degradation of beta carotene, chlorophyll content and formation of oxidation products. EVOO samples collected from Al-Jouf region, KSA showed low rate of oxidation which might be due to environmental and geographical effect, proper irrigation system, harvesting, processing and storage conditions. In a fast and non-destructive manner, The fluorescence spectroscopy successfully monitored the oxidation changes and deterioration of antioxidants in a rapid and non-destructive manner in the EVOOs.
Genetic information in the decision-making process for the training of a high-performance Brazilian swimmer: A Case Report
Authors: Bottura Ricardo Muller , Dentillo Daniel Blasioli 
Published: August 2024

Abstract

Introduction: Although several genetic variations have been associated with athletic profiles and athletic performance, there is little scientific literature on the incorporation of this information into the planning of daily training, especially in elite athletes. The aim of this study is to present our one-year training experience with a high-performing open water marathon swimmer, integrating insights from genetic information.
Materials & Methods: This is a case study conducted with a 23-year-old open water marathon swimmer aiming to qualify for the Absolute World Championships in Doha, Qatar (2024). The study involves the use of twenty genetic polymorphisms to structure the athlete's training plan.
Results: Training based on genetic polymorphisms proved to be effective in enhancing the athlete's athletic performance, securing his top position among compatriots, and qualifying him for the Absolute World Championships.
Conclusions: Genetic-based training may be an effective strategy to assist sports professionals in making training planning decisions for high performance athletes.
Glutathione attenuates copper levels and alleviates hepatic injury in TX mice
Authors: Wang Mengzhen , Hu Qiang , Wang Ni , Jiang Yuge , Dong Ting , Cao Shijian , Zhou An 
Published: August 2024

Abstract

Wilson's disease(WD) is an inherited disorder of abnormal copper metabolism, and promotion of copper ion excretion is the focus of its treatment in the clinic. Glutathione (GSH) is a tripeptide compound whose active group is the sulfhydryl group, which is involved in a number of important biochemical reactions. Thus, its antioxidant and integrative detoxification effects have attracted interest. Whether glutathione promotes copper ion excretion and anti-oxidative stress to alleviate Wilson's disease liver injury is the focus of this study. Here, we used toxic milk(TX) mice as model mice to study Wilson's disease and treated them with glutathione. We observed that glutathione was effective in promoting copper excretion in TX mice. In addition, glutathione has been shown to be effective in attenuating liver injury, including improving the structure and morphology of stem tissue and reducing hepatocyte necrosis. The effects of glutathione on hepatic oxidative stress as measured by catalase, malondialdehyde and total superoxide dismutase. The results showed that glutathione could increase hepatic antioxidant enzyme activities, reduce lipid peroxidation levels and attenuate liver injury. In conclusion, glutathione may exert its hepatic benefits by promoting copper ion excretion and anti-oxidative stress.
Modelling the Response of an Ice Disc to Radial WaterFlow in the Context of Sea Ice Thickening
Authors: Pantling Jacob , Worster M. Grae , Fitzgerald Shaun D. 
Published: August 2024

Abstract

The Arctic is melting rapidly and is likely to experience its first ice-free summer in the next few decades unless action is taken locally. One proposed method of reducing or perhaps reversing Arctic melting is pumping seawater onto the surface of Arctic sea ice where it should freeze faster and thicken the ice. This may in turn enable it to last longer or even survive the summer melting period, reflecting more sunlight and becoming stronger multi-year ice with increased resistance to future melting. Despite appearing to be a relatively simple physical problem the technique has not been researched in depth. Here, the response of ice to water being pumped over its surface is investigated theoretically and experimentally for radial axisymmetric water flow. The dominant heat transfer mechanisms during the period shortly after placement of water onto ice are conduction through the ice away from the water-ice interface and advection from the water to the interface. During this initial period of evolution, advection and radiation to the atmosphere are much smaller in magnitude and hence not included. The advective heat transfer from the water flow to the interface is modelled for three flows: an inviscid flow without a thermal boundary layer; an inviscid flow with a thermal boundary layer; and viscous flow with a thermal boundary layer. Predictions from these models are compared with data from laboratory experiments at various initial water temperatures. The predictions from the viscous, thermal boundary layer model for the evolution of the ice profile were found to be closest to the data obtained from laboratory experiments with water supplied at 0.5, 1.0 & 1.5°C.
Enhancing Shielding Efficiency against Galactic Cosmic Radiation: Secondary Neutron Optimization
Authors: Dribi Yamina , Ounoughi Nabil 
Published: August 2024

Abstract

GCR (Galactic Cosmic Rays) are highly energetic ionizing radiations originating from sources beyond our solar system. During long-duration missions to outer space such as the Moon or Mars, the health hazards posed by these cosmic rays become a pressing concern for astronauts. Consequently, prioritizing the protection of both the spacecraft and its crew becomes of the highest importance, and the materials most frequently used for shielding are aluminum (Al) and polyethylene (PE). The objective of this study is to simulate the effectiveness of shielding against GCR, particularly focusing on secondary neutrons, using a combination of aluminum and polyethylene materials. Monte Carlo simulation (PHITS code) was used in the simulation. The effectiveness shielding of Al and PE is compared. The flux spectra of secondary emitted from the back of the slab shielding was computed. It shows that secondary neutron is produced mainly by GCR-protons and when multi-layer of PE materials is employed, secondary neutron flux has been reduced (about 10%). This reduction is of paramount significance since neutrons are a crucial component of the radiation emanating from GCR. In summary, the utilization of multi-layer polyethylene materials was demonstrated as an efficient approach to enhance the shielding effectiveness against GCR radiation.
Dynamic Network Slicing Orchestration in Open 5G Networks using Multi-Criteria Decision Making and Secure Federated Learning Techniques
Authors: Kholidy Hisham A. 
Published: August 2024

Abstract

Network slicing enables new revenue opportunities for service providers by allowing them to offer customized network services tailored to various industry verticals and use cases. 5G network uses slicing technology to enable the creation of tailored network slices to support diverse use cases, such as enhanced mobile broadband (eMBB), massive machine-type communications (mMTC), and ultra-reliable low-latency communications (URLLC). However, the complexity of network slicing also introduces challenges, such as maintaining service-level agreements (SLAs), quality of service (QoS), security across multiple slices, and service provisioning and dynamic allocation of resources.
This paper develops a novel Federated Network Slicing Orchestrator (FNSO) that uses the Multi-Criteria Decision Making (MCDM) method to rank and select the proper telecommunication service provider that runs at certain edge Points of Presence (EPoP) of the 5G-based IOT network for slice deployment. The proposed FNSO integrates the Hexagonal Fuzzy approach with the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to address the shortcoming of the TOPSIS and to rank and select the proper EPoP that can host the network slice using numeric and fuzzy Key Performance Indicators (KPIs) such as the security, cost, and performance criteria. Furthermore, we augment the FNSO with a Secure Federated Learning (SFL) model to protect the local 5G domain service provisioning KPIs and secure the FNSO against potential attacks. The experiment results depict that the average slice acceptance ratio of the FNSO is higher than the current solutions such as GRU-DNN, VIKOR-CNSP, and T-S3RA by 28.2%, 10.13%, and 6.1%. Furthermore, On average, the SFL model is faster than the DeTrust-FL, HybridAlpha-FL, PHE-FL, and HybridOne-FL by 7.11%, 7.21%, 15.73%, and 20.61% respectively, and slower than Classic-FL, on average, by 4.37% due to the secure aggregation that the SFL offers.