bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sociological and Criminological Research of Victimization Issues: Preliminary Stage and New Sphere of Cybercrime Categorization
Authors: Auwal A. M. , Lazarus S. 
Published: January 2025

Objective: to identify the main issues of victimization as a result of cybercrime growth in the world in general and in Nigerian society in particular from the standpoint of sociological approaches, using a Tripartite Cybercrime Framework (TCF), which comprises geopolitical, psychosocial and socioeconomic categories of cybercrime.Methods: the methodology is based on the sociological research method. The data collection included the distribution of a questionnaire among 896 participants from the academic environment, including students and university staff, and the analysis of the responses. The presented data were analyzed using descriptive statistics, with special attention to the issues of gender inequality, socio-economic factors, the impact of educational level on vulnerability to online fraud and victimization as a result of cybercrime through the prism of the ideal victim concept and the socio-economic gap between North and South.Results: the article presents an analysis of the Tripartite Cybercrime Framework. The survey showed that 65.20% of the participants had been victims of cybercrime. There were more men among the victims (64.69%). The authors found patterns in the distribution of cybercrimes. All cybercrimes against the respondent were socio-economic ones, which underlines the high frequency of cybercrime and the relevance of countering it in Nigerian society. Special attention was paid to the issues of gender inequality, socio-economic factors, and the impact of education on vulnerability to cybercrime. The article considers from the viewpoint of the ideal victim concept. The study results provide an idea of the prevalence and distribution of specific types of cybercrime in the socio-economic category among the studied population.Scientific novelty: For the first time, the study uses the Tripartite Cybercrime Framework (TCF) to study victimization as a result of cybercrime in Nigerian society. The research novelty is also due to the fact that the conceptual foundations of countering cybercrime that have developed in the global North are not fully applicable in Nigeria.Practical significance: the results obtained demonstrate the need to apply carefully calibrated gender-based, inclusive and contextual approaches to the development of a national legal policy to combat cybercrime. The results can be used to justify the law-making decisions which are being developed in the field of preventing and countering manifestations of cybercrime, as well as to form the basis for legal measures to protect cybercrime victims.
Legal Aspects of Personal Data Protection and the Issues of Competition in Digital Marketplaces
Authors: Kolawole A. 
Published: January 2025

Objective: to develop approaches and proposals to improve the legal mechanisms for the personal data protection in the context of the evolving digital markets and the growing digital competition.Methods: the article is prepared based on formal legal and comparative legal research methods.Results: the unique features of digital markets are shown, which must be taken into account to achieve the goals of antimonopoly legislation. It is marked that the fundamental elements of the digital market include the big data concept and big data analytics, which, based on digital platforms, are capable of producing many direct and indirect network effects. The latter require understanding for an effective antitrust response and the application of appropriate legislation. The author proves that the growth of digital platforms as a business model and vital infrastructure of the digital economy should be viewed as a factor in improving legal regulation of relations in the sphere of data protection and confidentiality. The paper identifies the potential of digital platforms for assessing the current market power and the impact of competition on limiting this power. The data are considered as an integral component of the overall competitive market landscape. The current European Union regulation in the field of digital platforms and personal data protection is analyzed. The author identifies difficulties associated with the creation and application of effective regulations governing the activities of digital platforms. The article proves that antimonopoly authorities need to change approaches to analytics in order to take into account the distinctive features of digital platforms. It is noted that such changes may require legislative reforms and revision of procedures to match the rapid development of these markets and ensure that any potentially anticompetitive behavior is thoroughly investigated.Scientific novelty: the research contributes to the development of approaches to determining indicators of ensuring the personal data confidentiality under the digitalization of markets and to evaluating the effectiveness of antimonopoly legislation and its application in a new competitive environment.Practical significance: the results obtained can be used as a basis for improving antimonopoly and personal data protection legislation, as well as legal regulation of digital platforms in general.
The kinase domain of TRPM7 interacts with PAK1 and regulates pancreatic cancer cell epithelial-to-mesenchymal transition
Authors: Gautier Mathieu , Auwercx Julie , NEVE Bernadette , VANLAEYS Alison , Bourrin-Reynard Ingrid , SOUDI Mouloud , Brassart-pasco Sylvie , HAGUE Frédéric , Guénin Stéphanie , DUCHENE Belinda , Gutierrez Laurent , Destaing Olivier , DHENNIN-DUTHILLE Isabelle , SEUNINGEN Isabelle VAN , Jonckheere Nicolas 
Published: January 2025

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is the main and the deadliest form of pancreatic cancer. This is a major problem of public health since it will become the second leading cause of death by cancer in the next few years, mainly due to the lack of efficient therapies. Transient Receptor Potential Cation Channel Subfamily M Member 7 (TRPM7) protein, a cation channel fused with a serine/threonine kinase domain is overexpressed in PDAC and associated with a low survival. In this work, we aim to study the role of kinase domain on pancreatic cell fates by using a model of kinase domain deletion by CRISPR-Cas9. PANC-1 and MIA PaCa-2 PDAC cell lines were used and kinase domain was deleted by CRISPR-Cas9 strategy. Kinase domain deletion (ΔK) was validated by RT-qPCR and western-blots. The effect of kinase domain deletion on channel function was studied by patch-clamp and Mn2+-quenching. The cell phenotype was studied by MTT and cell migration/invasion assays. Finally, the role of kinase domain was studied in vivo in xenografted mice. Here we show that TRPM7 kinase domain is required to maintain a mesenchymal phenotype in PDAC cells. We also demonstrated that TRPM7 and PAK1 interact in the same protein complexes. Moreover, TRPM7 kinase domain is required for carcinogenesis and cancer cell dissemination in vivo. Intriguingly, the role of TRPM7 kinase is cell specific and may depend on the KRAS oncogene mutation status. In conclusion, TRPM7 kinase domain is required to maintain a mesenchymal and aggressive phenotype in PDAC cells, and it could be a promising target against PDAC.
Humans have substantially extended fire seasons in all biomes on Earth
Authors: Ellis Todd , Bowman David , Williamson Grant 
Published: January 2025

Abstract

The conjunction of lightning ignitions and dry vegetation has shaped fire regimes throughout geological time. These natural fire regimes have in turn influenced the adaptation of biotas globally. Anthropogenic fire use, however, radically transformed worldwide fire regimes by extending seasons to the limits bounded by periods of high fuel moisture. Conversely, active fire suppression has typically limited the occurrence and extent of lightning ignited fires – particularly where population density is higher. Disaggregating contemporary human- and lightning-caused seasonal fire patterns globally can shed light on the magnitude of the anthropogenic change to fire regimes among biomes. Using global datasets of flammability moisture thresholds and fuel moisture we define the global distribution of fire seasons. We then use a global record of lightning strike density to disaggregate the fire season into mixed (i.e., lightning present) and anthropogenic ignitions periods, before describing the respective importance of these periods amongst biomes. We assess these the breadth of these ignitions periods against a daily satellite burned area record (2001–2023) and contextualise the occurrence of areas burned within mixed and anthropogenic ignitions periods against vegetation productivity and human population density using the established productivity-fire activity relationship. Collectively, we show that current anthropogenic influences have transformed worldwide fire regimes by substantially lengthening fire seasons, irrespective of local land use and fire suppression practices, population density, lightning occurrence, and biome type.
Linoleic acid promotes TF expression through PPAR-α, which leads to tumor progression in primary pulmonary lymphoepithelioma-like carcinoma
Authors: Bao Hejing , Zhang Jiani , Chen Zhuoyan , Wang Yuhuan , Wang Zhe , Chen Zhiting , Jiang Ting , Zhang Baishen , Zeng Wen , Bao Hehong , Ma Shudong 
Published: January 2025

Abstract

Primary pulmonary lymphoepithelioma-like carcinoma (pLELC) is a relatively uncommon variant of primary non-small cell lung cancer, and its etiology is still largely unexplored. Objective: The aim of this study is to investigate the underlying mechanisms and potential therapeutic targets associated with pLELC. The patients diagnosed with advanced pLELC were retrospectively collected and subjected to proteomics and metabonomics analysis. Finally, a patient-derived xenograft (PDX) model of pLELC xenograft was constructed for validation. The results of the data-independent acquisition(DIA) quantitative analysis revealed that the expression of tissue factor (TF) protein was found to be upregulated in pLELC. Furthermore, it was observed that TF protein played a role in iron death, hypoxia-inducible factor-1 (HIF-1) signalling pathway, and leukocyte transendothelial migration. Untargeted metabonomics analysis revealed the presence of major metabolites, namely linoleic acid (LA), free fatty acid (16:0), and histidine. LA has been found to contribute to the progression of tumors by promoting the infiltration of M2 tumor-associated macrophages and inhibiting the infiltration of natural killer(NK) cells. However, this effect can be reversed by the TF inhibitor Tisotumab. LA enhances the expression of TF through peroxisome proliferator-activated receptor (PPAR)-α, and the malignancy caused by LA can be counteracted by TF inhibitors.The findings of this study suggest that LA has the ability to alter the tumor microenvironment in pLELC by upregulating TF expression through PPAR-α. These results indicate that TF could potentially serve as a therapeutic target for pLELC.
Evaluating a Customised Large Language Model (DELSTAR) and its Ability to Address Medication-Related Questions Associated with Delirium: A Quantitative Exploratory Study
Authors: Spagl Katharina Teresa , Watson Edward William , Jatowt Adam , Weidmann Anita Elaine 
Published: January 2025

Abstract

Background: A customised large language model (LLM) could serve as a next-generation clinical pharmacy research assistant to prevent medication-associated delirium. Comprehensive evaluation strategies are still missing.
Aim: This quantitative exploratory study aims to develop an approach to comprehensively assess the domain-specific customised delirium LLM (DELSTAR) ability, quality and performance to accurately address complex clinical and practice research questions on delirium that typically require extensive literature searches and meta-analyses.
Method: DELSTAR, focused on delirium-associated medications, was implemented as a 'Custom GPT' for quality assessment and as a Python-based software pipeline for performance testing on closed and leading open models. Quality metrics included statement accuracy and data credibility; performance metrics covered F1-Score, sensitivity/specificity, precision, AUC, and AUC-ROC curves.
Results: DELSTAR demonstrated more precise information compared to information retrieved by traditional systematic literature reviews (SLRs) (p<0.05) and accessed Application Programmer Interfaces (API), private databases, and high-quality sources despite mainly relying on less reliable internet sources. GPT-3.5 and GPT-4o emerged as the most reliable foundation models. In Dataset 2, GPT-4o (F1-Score: 0.687) and Llama3-70b (F1-Score: 0.655) performed best, while in Dataset 3, GPT-3.5 (F1-Score: 0.708) and GPT-4o (F1-Score: 0.665) led. None consistently met desired threshold values across all metrics.
Conclusion: DELSTAR demonstrated potential as a clinical pharmacy research assistant, surpassing traditional SLRs in quality. Improvements are needed in high-quality data use, citation, and performance optimisation. GPT-4o, GPT-3.5, and Llama3-70b were the most suitable foundation models, but fine-tuning DELSTAR is essential to enhance sensitivity, especially critical in pharmaceutical contexts.
High Temperature Tolerant Mid-Wavelength Infrared Avalanche Photodiodes with Separated Fully-depleted Absorption, Multiplication Region
Authors: Zhu Liqi , Wang Zihao , Lin Jiamu , Huang Jian , He Linxuan , Wang Xi , Zhou Songmin , Gan Zhikai , Li Xun , Li Qingxin , He Li , Lin Changqing , Lin Chun , Chen Baile 
Published: January 2025

Abstract

Mid-wavelength infrared (MWIR) avalanche photodiodes (APD) are extensively employed in rapid, high-precision detection as well as thermal imaging in complex context due to their superior sensitivity, fast response, and high gain. However, conventional MWIR APD’s detection typically requires lowtemperature operation to relieve signal-to-noise limitations imposed by high dark currents in narrow bandgap materials. To address this challenge, we present the high-temperature-operating MWIR avalanche photodiode with a separated fullydepleted absorption, multiplication region (SFDAM) structure to suppress the diffusion dark current and minimize the excess noise. The proposed APD can cope with infrared light well up to 4.2 µm, and exhibits low dark current density at unit gain that nearly an order of magnitude lower than the theoretical diffusion current limitation at elevated temperatures of 160 K. At 80 K, the device achieves comparable gain-normalized dark current density (GNDCD) still <6×10-10A/cm 2 at gain < 20 and demonstrates low excess noise < 1.67. At a high temperature of 160 K, the GNDCD preserves consistently below 2×10−6 A/cm 2 for gain values less than 189, while the excess noise holds below 1.4 and the noise equivalent power is <7.2×10 −16 W/ Hz of 3.5 µm. The device is also validated for imaging weak targets up to 200 km away. These results enable the SFDAM APDs are promising and desirable for future high-temperature-operating MWIR detection and likely the photon-starved applications.
5G Performance and Enhancement with Dust Storm Conditions
Authors: Sh.Hammed Zainab , Ameen Siddeeq Y. 
Published: January 2025

Abstract

The increasing demand for ultra-fast data, high capacity, and low latency in 5G and beyond networks is driving the adoption of millimeter-Wave (mm-Wave) frequencies (3–300 GHz), which utilize spatial multiplexing and beamforming for improved performance. However, environmental factors like humidity, temperature, dust, and sandstorms, particularly in the Middle East, pose significant challenges. The parameters of the channel model and how it behaves statistically when exposed to dust and sandstorms have been analyzed using NYUSIM simulator and MATLAB. Wireless communication channels face challenges like time variability, frequency-selective fading, and interference from adjacent subcarriers, making traditional estimation methods less effective. This paper introduces a DNN model based on Bidirectional Long Short-Term Memory (BI-LSTM) networks, which excel at processing time-series data with long-range dependencies, outperforming standard RNNs. An end-to-end channel estimation and signal detection process using the Bi-LSTM-based detector is simulated and compared with traditional techniques such as LS, ZF, and MMSE. Results show that DNN provides higher estimation accuracy, especially with fewer pilots, achieving SER 30 to 35 times lower than ZF and MMSE. Additionally, the DNN model offers an SNR gain of approximately 10–15 dB or more compared to conventional methods. The proposed approach shows cases promising advancements for not only 5G but also for the evolving requirements of beyond-5G networks, offering a reliable solution for maintaining efficient Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing MIMO-OFDM communication under diverse weather conditions.
In-silico Insights into Protein Targets: New Avenues for Treating E. faecalis in Endodontic Infections – A Systematic Review
Authors: V Swetha Geervani , Neelakantappa Kiran Kumar , Merwade Seema , M Abhishek , M Manimozhi 
Published: January 2025

Abstract

Enterococcus faecalis is a key pathogen in persistent endodontic infections, known for its resilience and resistance to conventional treatments. This systematic review (PROSPERO CRD42024610795) explores in silico methodologies targeting E. faecalis proteins to identify novel therapeutic approaches. A comprehensive literature search identified 11 relevant studies employing molecular docking tools such as AutoDock Vina, Glide XP, and SwissDock to investigate interactions between ligands and critical protein targets, including Sortase A, MurA, c-di-AMP synthetase, and quorum sensing regulators. Promising inhibitors, such as pinocembrin, 24-propylcholesterol, and embelin, exhibited potential to disrupt biofilm formation, quorum sensing, and bacterial metabolism. These findings highlight the potential of plant-derived compounds and novel antibacterial agents in addressing E. faecalis-associated infections. While most studies validated computational results with in vitro assays, variability in ligand preparation, protein optimization, and docking methodologies indicates the need for standardization. This review underscores the significant promise of computer-aided drug design (CADD) in developing effective treatments for E. faecalis infections. Integrating in silico and in vitro approaches can accelerate drug discovery, but further in vivo studies are essential to confirm therapeutic potential and facilitate clinical application.
WITHDRAWN: SUV39H1 alleviates MAFLD through inhibition of the FABPs/CEPT1 signaling pathway
Authors: sun yi , Wang changyuan , Wang Yang , Hao Ru , Liu Lu , Jin yue , Sun Huijun 
Published: January 2025

Abstract

Background
Epigenetics modification has emerged as a potential mechanism of action for MAFLD. The histone methylase SUV39H1 is a key epigenetic transcription factor that regulates adipogenesis and inflammation, but its potential role in MAFLD progression remains largely unknown.
Methods
In this study, the high fat diet (HFD) induced mice and palmitic acid (PA) induced primary mouse hepatocytes were adopted to investigate the effects and mechanisms of SUV39H1 on MAFLD. Point mutation and knockdown of SET domain of SUV39H1 in PA-stimulated AML12 cells and high-fat diet fed mice were adopted to confirm the function of SET domain in MAFLD. RNA–sequencing was used to screen the downstream genes affected by SUV39H1 overexpression in PA-induced AML12 cells. The functional relationship between SUV39H1 and its downstream FABPs was elucidated by CHIP, DNA Pull Down and dual-luciferase reporter assays.
Results
SUV39H1 could attenuate MAFLD by affecting lipid metabolism, suppressing inflammation and insulin resistance. And the SET domain of SUV39H1 was proved to be the functional domain mediating its effects on MAFLD in vivo and in vitro. Further studies revealed that overexpression of FABPs or CEPT1, the downstream genes of SUV39H1 could accelerate the disorder of lipid metabolism in MAFLD. Meanwhile, FABP could promote CEPT1 expression. Histone methylation modification of FABP promoters by SUV39H1 could inhibit the progression of MAFLD.In addition, FABPs derived from hepatocytes could aggravate the progression of MAFLD by promoting M1 polarization of the macrophages.
Conclusion
SUV39H1 alleviates MAFLD through inhibition of the FABPs/CEPT1 signaling pathway.
Genetically predicted blood metabolites mediate the association between circulating inflammation-related proteins and pancreatic cancer
Authors: Duan Yanheng , Zhang Fen , Zhang Xiaojing , Jin Liang , He Kun , Guan Yufan , Dong Xiaotian , Chen Yong , An Jiaze 
Published: January 2025

Abstract

Background: While extensive research highlighted the involvement of circulating inflammatory proteins and metabolism in pancreatic cancer (PC), causality remains unestablished. In the present study, we aimed to investigate the causal relationship of circulating inflammatory proteins and pancreatic cancer and identify the blood metabolites as potential mediators.
Methods: We employed bidirectional two-sample Mendelian randomization analysis to examine the potential causal association between circulating inflammatory proteins, circulating metabolites, and PC using data from genome-wide association studies (GWAS). And two-step MR to discover potential mediating blood metabolites in this process.
Results: MR analysis identified 4 types of circulating inflammation-related proteins causally associated with pancreatic cancer. Furthermore, there was no strong evidence that genetically predicted pancreatic cancer had an effect on these four types of circulating inflammatory proteins. Further two-step MR analysis found 11 types of blood metabolites were causally associated with pancreatic cancer and the associations between circulating Interleukin-15 receptor subunit alpha and pancreatic cancer were mediated by blood 5-methyluridine with proportions of 7.41%.
Conclusion: The present study provides evidence supporting the causal
relationships between various circulating inflammatory proteins, especially Interleukin-15 receptor subunit alpha, and pancreatic cancer, with a potential effect mediated by blood metabolites. Further research is needed on additional risk factors as potential mediators and establish a comprehensive inflammation-metabolism network in pancreatic cancer.
Deep Data-Driven Neural Network for Malaria Vaccination
Authors: Abaka-Quansah Esi , Moore Stephen E. 
Published: January 2025

Abstract

Malaria still remains a significant global health challenge that requires innovative strategies for its control and eventual eradication. In this article, we present a malaria vaccination model to assess and predict the effects of vaccination interventions. The model parameters are learned via feedforward Neural Network. We employed Residual Neural Network and Recurrent Neural Networks(GRU, LSTM, and BiLSTM) to predict and forecast daily and sequential malaria cases using generated data from the Ghana vaccination population.