Search Results (346)

This paper introduces a theoretical large-scale radio channel model for the downlink in cellular systems, aimed at estimating variations in received signal power at the user terminal as a function of device mobility. This enables applications such as direction-of-arrival (DoA) estimation, estimating power at subsequent points based on received power, and detection of coverage anomalies. The model is validated using real-world measurements from urban and suburban environments, achieving a maximum estimation error of 7.6%. In contrast to conventional models like Okumura–Hata, COST-231, Third Generation Partnership Project (3GPP) stochastic models, or ray-tracing techniques, which estimate average power under static conditions, the proposed model captures power fluctuations induced by terminal movement, a factor often neglected. Although advanced techniques such as wave-domain processing with intelligent metasurfaces can also estimate DoA, this model provides a simpler, geometry-driven approach based on empirical traces. While it does not incorporate infrastructure-specific characteristics or inter-cell interference, it remains a practical solution for scenarios with limited information or computational resources. Full article

Background/Objectives: During the repair of a wounded epithelium, keratinocytes become invasive via the epithelial-to-mesenchymal transition (EMT) process. Usually temporary and controlled, EMT persists in a chronically inflamed epithelium and is exacerbated in epithelial dysplasia and dysregulated in invasive carcinomas. Here we investigated the effects that IL-1 beta, IL-6, and IL-8, inflammatory cytokines expressed in specimens from OPMDs and OSCCs, have on NOKs and OSCC cells. Methods: AKT activation and EMT induction were assessed along with cellular invasiveness. Results: IL-1 beta, IL-6, and IL-8 induced EMT in NOKs, ex novo conferring them invasive capacity. The same cytokines exacerbated the constitutive EMT and invasiveness of OSCC cells. Since these phenomena were accompanied by AKT activation, we tested whether they could be influenced by RTV, a long-used anti-HIV drug that was previously found to block the activation of human AKT and exert antitumor effects. We observed that therapeutic amounts of RTV counteract all the above-mentioned tumorigenic activities of ILs. Finally, consistent with the key role that AKT and EMT play in OSCC radio-resistance, RTV increased OSCC cells’ sensitivity to therapeutic doses of ionizing radiation. Conclusions: These preliminary in vitro findings encourage the use of RTV to prevent the malignant evolution of OPMDs, reduce the risk of OSCC metastasis, and improve the outcomes of anti-OSCC radiotherapy. Full article

The application of non-thermal (cold) plasmas is considered an environmentally friendly method that could affect plant metabolism and cellular development or can be used for the commercial production of natural products that cannot be chemically synthesized. In the present study, the non-embryogenic callus of iris (Iris reichenbachii Heuff.) was treated with a Radio Frequency (RF) plasma needle device using He as a working gas. We investigated short-term (up to seven days) and long-term (up to one year) changes on morphological, physiological and biochemical levels. An increased production of O₂⁻ and H₂O₂ was observed in the callus tissue after plasma treatment. The enzymes SOD and CAT represented the frontline in the antioxidant defense against reactive oxygen species (ROS) produced during the first hour of treatment, while POX was the leading antioxidant enzyme seven days after plasma treatment. Significant long-term morphological changes were observed in the calli due to the increased mitotic activity of the plant cells. In addition, three flavonoids (naringenin, apigenin and acacetin) and two isoflavonoids (irisolidone and irilone) were detected only in the plasma-treated tissue even one year after plasma treatment. The present study emphasizes the application of the plasma technique to promote meristematic activity and stimulate the production of specialized metabolites in iris calli. Full article

In recent research on path planning for cellular-connected Unmanned Aerial Vehicles (UAVs), leveraging navigation models based on complex networks and applying the A* algorithm has emerged as a promising alternative to more computationally intensive methods, such as deep reinforcement learning (DRL). These approaches offer performance that approaches that of DRL, while addressing key challenges like long training times and poor generalization. However, conventional A* algorithms fail to consider critical UAV flight characteristics and lack effective obstacle avoidance mechanisms. To address these limitations, this paper presents a novel solution for path planning of cellular-connected UAVs, utilizing a 3D radio map for enhanced situational awareness. We proposed an innovative path planning algorithm, UAVRM-A*, which builds upon the complex network navigation model and incorporates key improvements over traditional A*. Our experimental results demonstrate that the UAVRM-A* algorithm not only effectively avoids obstacles but also generates flight paths more consistent with UAV dynamics. Additionally, the proposed approach achieves performance comparable to DRL-based methods while significantly reducing radio outage duration and the computational time required for model training. This research contributes to the development of more efficient, reliable, and practical path planning solutions for UAVs, with potential applications in various fields, including autonomous delivery, surveillance, and emergency response operations. Full article

Background: Machine learning methods are increasingly being used in mobile network optimization systems, especially next-generation mobile networks. The need for enhanced radio resource allocation schemes, improved user mobility and increased throughput, driven by a rising demand for data, has necessitated the development of diverse algorithms that optimize output values based on varied input parameters. In this context, we identify the main topics related to cellular networks and machine learning algorithms in order to pinpoint areas where the optimization of parameters is crucial. Furthermore, the wide range of available algorithms often leads to confusion and disorder during classification processes. It is crucial to note that next-generation networks are expected to require reduced latency times, especially for sensitive applications such as Industry 4.0. Research Question: An analysis of the existing literature on mobile network load balancing methods was conducted to identify systems that operate using semi-automatic, automatic and hybrid algorithms. Our research question is as follows: What are the automatic, semi-automatic and hybrid load balancing algorithms that can be applied to next-generation mobile networks? Contribution: This paper aims to present a comprehensive analysis and classification of the algorithms used in this area of study; in order to identify the most suitable for load balancing optimization in next-generation mobile networks, we have organized the classification into three categories, automatic, semi-automatic and hybrid, which will allow for a clear and concise idea of both theoretical and field studies that relate these three types of algorithms with next-generation networks. Figures and tables illustrate the number of algorithms classified by type. In addition, the most important articles related to this topic from five different scientific databases are summarized. Methodology: For this research, we employed the PRISMA method to conduct a systematic literature review of the aforementioned study areas. Findings: The results show that, despite the scarce literature on the subject, the use of load balancing algorithms significantly influences the deployment and performance of next-generation mobile networks. This study highlights the critical role that algorithm selection should play in 5G network optimization, in particular to address latency reduction, dynamic resource allocation and scalability in dense user environments, key challenges for applications such as industrial automation and real-time communications. Our classification framework provides a basis for operators to evaluate algorithmic trade-offs in scenarios such as network fragmentation or edge computing. To fill existing gaps, we propose further research on AI-driven hybrid models that integrate real-time data analytics with predictive algorithms, enabling proactive load management in ultra-reliable 5G/6G architectures. Given this background, it is crucial to conduct further research on the effects of technologies used for load balancing optimization. This line of research is worthy of consideration. Full article

Multiple sclerosis (MS) is a multifaceted inflammatory, demyelinating, and neurodegenerative disease typified by lesions with distinct hallmarks in the central nervous system. Dysregulation of micro-environmental factors, including extracellular matrix (ECM) remodelling and glial cell activation, has a decisive effect on lesion development and disease progression. Understanding the biological and pathological features of lesions would aid in prognosis and personalised treatment decision making. Positron emission tomography (PET) is an imaging technique that uses radio-labelled tracers to detect specific biological phenomena. Recent PET hardware developments enable high-resolution, quantitative imaging, which may allow biological characterisation of relatively small MS lesions. PET may complement MRI by offering objective, quantitative insights into lesion characteristics, including myelin density, inflammation and axonal integrity. Moreover, PET may provide information on lesion traits supporting decision making on upcoming therapeutic strategies for progressive MS, such as the availability of oligodendrocyte progenitor cells and ECM composition that affect remyelination and/or axon regeneration. This review explores the cellular and molecular ECM signatures and neuropathological processes of white matter MS lesions, discusses current and potential novel PET targets that may help characterise MS lesions in vivo, and addresses the potential of PET as a decision tool for selection and evaluation of therapeutic strategies, with a focus on remyelination. Full article

Objectives: Omega-3 fatty acids (n-3 FA) exhibit pro-healing and anti-inflammatory properties. Injectable lipid emulsions containing n-3 FA are being explored for the treatment of acute adverse conditions. Our previous studies demonstrated that a triglyceride (TG)-rich emulsion (TGRP) containing medium-chain TG (MCT) and n-3 TG (8:2 ratio) is rapidly cleared from the blood and efficiently taken up by organs. This study systematically examined the impact of varying MCT:n-3 ratios on cellular uptake and metabolic function in inflammatory processes. Methods and results: We measured the uptake of radio-labeled TGRP, comprising pure MCT, n-3, or mixed at selected ratios (8:2, 6:4, 2:8), both in vitro and in vivo. Murine macrophages with MCT:n-3 (6:4 or 2:8) had a 2-fold higher TG uptake. IV-injected mixed TGRP also enhanced blood clearance and organ uptake. n-3 TGRP reduced LPS-induced pro-inflammatory cytokines (TNF-α, IL-1, IL-6) in a dose-dependent manner. The 8:2 ratio enhanced mitochondrial respiration and glycolytic capacity in macrophages. Pro-inflammatory lipids decreased with MCT:n-3 (2:8) and pure n-3 TGRP. Bolus injections of n-3 TGRP with MCT lowered LPS-induced IL-6 in plasma and tissues. Conclusions: MCT and n-3 FA support metabolic activity and exhibit anti-inflammatory effects, suggesting that optimizing their ratio may enhance the therapeutic effects of emulsions for inflammatory conditions. Full article

The rise of the Internet of Things (IoT) has made it possible to explore different types of communication, such as underwater IoT (UIoT). This new paradigm allows the interconnection of ships, boats, coasts, objects in the sea, cameras, and animals that require constant monitoring. The use of sensors for environmental monitoring, tracking marine fauna and flora, and monitoring the health of aquifers requires the integration of heterogeneous technologies as well as wireless communication technologies. Aquatic mobile sensor nodes face various limitations, such as bandwidth, propagation distance, and data transmission delay issues. Owing to their versatility, wireless sensor networks support remote monitoring and surveillance. In this work, an architecture for a general packet radio service (GPRS) wireless sensor network is presented. The network is used to monitor the geographic position over the coastal area of the Gulf of Mexico. The proposed architecture integrates cellular technology and some ad hoc network configurations in a single device such that coverage is improved without significantly affecting the energy consumption, as shown in the results. The network coverage and energy consumption are evaluated by analyzing the attenuation in a proposed channel model and the autonomy of the electronic system, respectively. Full article

Background/Objectives: Neurotensin receptors (NTSRs), members of the G protein-coupled receptor (GPCR) family, have been found to be overexpressed in several types of human cancers, including breast, colon, lung, liver, prostate, and pancreatic cancer. In particular, NTSR1 is overexpressed in at least 75% of pancreatic ductal adenocarcinomas. The aim of the present study was the development and evaluation of new ^99mTc-labeled nonpeptide NTSR1-antagonists for SPECT imaging of NTSR-positive tumors. Methods: Multistep syntheses of NTSR1 antagonist derivatives were performed following our previously described procedure. Two different chelating strategies were applied for ^99mTc radiolabeling to provide the [^99mTc]Tc-HYNIC complex [^99mTc]1 and the [^99mTc]Tc-tricarbonyl complex [^99mTc]2. Receptor binding assays were performed using hNTSR1-expressing CHO cells. Radiochemical yields (RCYs) were determined by radio-HPLC. For [^99mTc]1 and [^99mTc]2, log D_7.4, plasma protein binding, stability in human plasma and serum, and cellular uptake in HT-29 cells were determined. Biodistribution studies and small animal SPECT studies were performed in HT-29 tumor-bearing nude mice. Results: The radiosynthesis of [^99mTc]1 (log D_7.4 = −0.27) and [^99mTc]2 (log D_7.4 = 1.00) was successfully performed with RCYs of 94–96% (decay-corrected). Both radioligands were stable in human serum and plasma, showed plasma protein binding of 72% ([^99mTc]1) and 82% ([^99mTc]2), and exhibited high and specific uptake in HT-29 cells. Biodistribution studies in HT-29 tumor-bearing mice showed a higher tumor accumulation of [^99mTc]1 compared to [^99mTc]2 (8.8 ± 3.4 %ID/g vs. 2.7 ± 0.2 %ID/g at 2 h p.i.). [^99mTc]2 showed exceptionally high intestinal accumulation (49 ± 22 %ID/g at 1 h p.i.) and was therefore considered unfavorable. In the SPECT/CT imaging of HT-29 tumor xenografts, [^99mTc]1 showed a higher NTSR1-specific tumor uptake than [^99mTc]2 at all time points after tracer injection, with 12 ± 2.8 %ID/g for [^99mTc]1 vs. 3.1 ± 1.1 %ID/g for [^99mTc]2 at 4 h p.i. and adequate tumor-to-background ratios. Conclusions: In particular, the [^99mTc]Tc-HYNIC ligand ([^99mTc]1) showed promising preclinical results, being a potential candidate for SPECT imaging and, therefore, appropriate for translation into the clinic. Full article

With increasing vehicle density and growing demands on transport infrastructure, there is a need for resilient, low-cost communication systems capable of supporting safety-critical applications, especially in situations where primary channels like Wi-Fi or LTE are unavailable. This paper proposes a novel, real-time vehicular network protocol that functions as an emergency fallback communication layer using long-range LoRa modulation and off-the-shelf hardware. The core contribution is a development of Mobile Cell Broadcast Protocol that is implemented using Long-Range modulation and time-division multiple access (TDMA)-based cell broadcast protocol (LoRA TDMA) capable of supporting up to six dynamic clients to connect and exchange lightweight cooperative awareness messages. The system achieves a sub-100 ms node notification latency, meeting key low-latency requirements for safety use cases. Unlike conventional ITS stacks, the focus here is not on full-featured data exchange but on maintaining essential communication under constrained conditions. Protocol has been tested in laboratory to check its ability to ensure real-time data exchange between dynamic network nodes having 14 bytes of payload per data packet and 100 ms network member notification latency. While focused on vehicular safety, the solution is also applicable to autonomous agents (robots, drones) operating in infrastructure-limited environments. Full article

Reliable Position, Navigation, and Timing (PNT) is becoming more and more important, considering the proliferation of highly autonomous safety- and liability-critical systems. Due to their vulnerability to various threats such as deliberate Radio Frequency Interference (RFI), including jamming, spoofing, and others, there is significant research into finding backup/fallback solutions that allow safe mission completion or termination. This work compares two such systems: one based on Angle of Arrival (AoA) measurement and one based on cellular (4G and 5G) signals. The results are generated using simulations, which are substantiated by real-world performance measurements. It is shown that both systems have the potential to serve as backup navigation solutions and that the cellular system outperforms the AoA-based solution, albeit at a much higher price and with higher computational requirements. Full article

This paper presents an optimization model for wireless channel allocation in cellular networks, specifically designed for the transmission of smart meter (SM) data through a mobile virtual network operator (MVNO). The model efficiently allocates transmission channels, minimizing smart grid (SG) costs. The MVNO manages fixed and random channels through a shared access scheme, optimizing meter connectivity. Channel allocation is based on a Markovian approach and optimized through the Hungarian algorithm that minimizes the weight in a bipartite network between meters and channels. In addition, cumulative tokens are introduced that weight transmissions according to channel availability and network congestion. Simulations show that dynamic allocation in virtual networks improves transmission performance, contributing to sustainability and cost reduction in cellular networks. This study highlights the importance of inefficient resource management by cognitive mobile virtual network and cognitive radio virtual network operators (C-MVNOs), laying a solid foundation for future applications in intelligent networks. This work is motivated by the increasing demand for efficient and scalable data transmission in smart metering systems. The novelty lies in integrating cumulative tokens and a Markovian-based bipartite graph matching algorithm, which jointly optimize channel allocation and transmission reliability under heterogeneous wireless conditions. Full article

Modern cellular systems rely on high-capacity and low-latency optical networks to meet ever-increasing data demands. Centralized Radio Access Network (C-RAN) architectures offer a cost-effective approach for deploying mobile infrastructures. In this work, we propose a flexible and cost-efficient fronthaul topology that combines Wavelength Division Multiplexing (WDM) passive optical networks (PONs) with free-space optical (FSO) links. To enhance overall system performance, we introduce Low-Density Parity Check (LDPC) decoding, which provides robust error-correction capabilities against atmospheric turbulence and noise. Our system transmits 20 Gbps, 16-QAM intensity-modulated orthogonal frequency-division multiplexing (OFDM) signals, achieving a substantial reduction in bit error rate (BER). Numerical results show that the proposed WDM-PON-FSO architecture, augmented with LDPC decoding, maintains reliable transmission over 2 km under strong turbulence conditions. Full article

The increasing demand for enhanced communication systems, driven by applications such as real-time video streaming, online gaming, critical operations, and Internet-of-Things (IoT) services, has necessitated the optimization of cellular networks to meet evolving requirements while addressing power consumption challenges. In this context, various initiatives undertaken by industry, academia, and researchers to reduce the power consumption of cellular network systems are comprehensively reviewed. Particular attention is given to emerging technologies, including Software-Defined Networking (SDN), Network Function Virtualization (NFV), and Cloud-Radio Access Network (C-RAN), which are identified as key enablers for reshaping cellular infrastructure. Their collective potential to enhance energy efficiency while addressing convergence challenges is analyzed, and solutions for sustainable network evolution are proposed. A conceptual architecture based on SDN, NFV, and C-RAN is presented as an illustrative example of integrating these technologies to achieve significant power savings. The proposed framework outlines an approach to developing energy-efficient cellular networks, capable of reducing power consumption by approximately 40 to 50% through the optimal placement of virtual network functions. Full article

Background: While gallium-68 has traditionally dominated PET imaging in oncology, copper radionuclides have sparked interest for their potential applications in nuclear medicine and theranostics. Considering the advantageous physical decay properties of copper-61 compared to those of gallium-68, we describe a fully automated GMP-compliant synthesis process for ⁶¹Cu-based radiopharmaceuticals and demonstrate their in vivo application for targeting the overexpressed PSMA by PET/MR imaging. Methods: Copper-61 was obtained through the irradiation of natural zinc liquid targets in a biomedical cyclotron. [⁶¹Cu]Cu-DOTAGA-PSMA-I&T and [⁶¹Cu]Cu-NODAGA-PSMA-I&T were produced without manual intervention in two Synthera^® Extension modules. Radiochemical purity was analyzed by radio-HPLC and iTLC. Cellular uptake was evaluated in LNCaP and DU145 cells. In vivo PET/MRI was performed in control mice to evaluate the biodistribution of both radiopharmaceuticals, and in tumor-bearing mice to assess the targeting ability towards PSMA. Results: The fully automated process developed proved to be effective for the synthesis of ⁶¹Cu-based radiopharmaceuticals, with appropriate molar activities. The final products exhibited high radiochemical purity (>98%) and remained stable for up to 6 h after the EOS. A time-dependent increase in cellular uptake was observed in LNCaP cells, but not in DU145 cells. As opposed to [⁶¹Cu]Cu-NODAGA-PSMA-I&T, [⁶¹Cu]Cu-DOTAGA-PSMA-I&T exhibited poor kinetic stability in vivo. Subsequent PET/MR imaging with [⁶¹Cu]Cu-NODAGA-PSMA-I&T showed tumor uptake lasting up to 4 h post-injection, predominant renal clearance, and no detectable accumulation in non-targeted organs. Conclusions: These results demonstrate the feasibility of the implemented process, which yields adequate amounts of high-quality radiopharmaceuticals and can be adapted to any standard production facility. This streamlined approach enhances reproducibility and scalability, bringing copper-61 closer to widespread clinical use, to the detriment of the conventionally accepted gallium-68. Full article