Search Results (143)

Background Plasma membrane proteins (PMPs) play key roles in cell signalling, adhesion, and trafficking, and are attractive therapeutic targets in cancer due to their surface accessibility. However, their typically low abundance limits detection by conventional proteomic approaches. Methods: To improve PMP detection, we employed a surface proteomics workflow combining cell surface biotinylation and affinity purification prior to LC-MS/MS analysis in cervical (SiHa) and bladder (UMUC3) cancer cell lines cultured under normoxic (21% O₂) or hypoxic (0.1% O₂) conditions. Results: In SiHa cells, 43 hypoxia-upregulated proteins were identified exclusively in the biotin-enriched fraction, including ITGB2, ITGA7, AXL, MET, JAG2, and CAV1/CAV2. In UMUC3 cells, 32 unique upregulated PMPs were detected, including CD55, ADGRB1, SLC9A1, NECTIN3, and ACTG1. These proteins were not observed in corresponding whole-cell lysates and are associated with extracellular matrix remodelling, immune modulation, and ion transport. Biotinylation enhanced the detection of membrane-associated pathways such as ECM organisation, integrin signalling, and PI3K–Akt activation. Protein–protein interaction analysis revealed links between membrane receptors and intracellular stress regulators, including mitochondrial proteins. Conclusions: These findings demonstrate that surface biotinylation improves the sensitivity and selectivity of plasma membrane proteomics under hypoxia, revealing hypoxia-responsive proteins and pathways not captured by standard whole-cell analysis. Full article

The growing popularity of Personal Light Electric Vehicles (PLEVs), such as e-scooters, has revolutionized urban mobility by offering compact, cost-effective, and environmentally friendly transportation solutions. However, safety concerns, including inadequate infrastructure, poor protective measures, and high accident rates, remain critical challenges. This paper presents the design and development of an innovative self-balancing microvehicle under the H2020 LEONARDO project, which aims to address these challenges through advanced engineering and user-centric design. The vehicle combines features of monowheels and e-scooters, integrating cutting-edge technologies to enhance safety, stability, and usability. The design adheres to European regulations, including Germany’s eKFV standards, and incorporates user preferences identified through representative online surveys of 1500 PLEV users. These preferences include improved handling on uneven surfaces, enhanced signaling capabilities, and reduced instability during maneuvers. The prototype features a lightweight composite structure reinforced with carbon fibers, a high-torque motorized front wheel, and multiple speed modes tailored to different conditions, such as travel in pedestrian areas, use by novice riders, and advanced users. Braking tests demonstrate deceleration values of up to 3.5 m/s², comparable to PLEV market standards and exceeding regulatory minimums, while smooth acceleration ramps ensure rider stability and safety. Additional features, such as identification plates and weight-dependent motor control, enhance compliance with local traffic rules and prevent misuse. The vehicle’s design also addresses common safety concerns, such as curb navigation and signaling, by incorporating large-diameter wheels, increased ground clearance, and electrically operated direction indicators. Future upgrades include the addition of a second rear wheel for enhanced stability, skateboard-like rear axle modifications for improved maneuverability, and hybrid supercapacitors to minimize fire risks and extend battery life. With its focus on safety, regulatory compliance, and rider-friendly innovations, this microvehicle represents a significant advancement in promoting safe and sustainable urban mobility. Full article

Railway axles are among the most safety-critical components in rolling stock, as their failure can lead to catastrophic consequences. One of the most subtle damage mechanisms affecting these components is fretting fatigue, which is a particularly challenging damage mechanism in these components, as it can initiate cracks under real service conditions and is difficult to detect in its early stages, which is vital to ensure operational safety and to optimize maintenance strategies. This paper focuses on the development of fretting fatigue damage in solid railway axles under realistic service-like conditions. Full-scale axle specimens with artificially induced notches were subjected to loading conditions that promote fretting fatigue crack initiation and growth. Acoustic emission techniques were used to monitor the damage progression, and post-processing of the emitted signals, by using wavelet-based tools, was conducted to identify early indicators of crack formation. The experimental findings demonstrate that the proposed approach allows for reliable identification of fretting-induced crack initiation, contributing valuable insights into the in-service behavior of railway axles under this damage mechanism. Full article

Energy harvesting systems (EHSs) are widely used to power wireless sensors. Piezoelectric harvesters have the advantage of producing an electric signal directly related to the exciting force and can thus be used to power condition monitoring sensors in dynamically loaded structures such as bridges. The need for such monitoring is exemplified by the fact that the condition of close to 25% of public roadway bridges in, e.g., Germany is not satisfactory. Stack-based piezoelectric energy harvesting systems (pEHSs) installed near bridge bearings could provide information about the traffic and dynamic loads on the one hand and condition-dependent changes in the bridge characteristics on the other. This paper presents an approach to co-optimizing the design of the mechanical and electrical components using a nonlinear solver. Such an approach has not been described in the open literature to the best of the authors’ knowledge. The mechanical excitation is estimated through a finite element simulation, and the electric circuitry is modeled in Simulink to account for the nonlinear characteristics of rectifying diodes. We use real traffic data to create statistical randomized scenarios for the optimization and statistical variation. A main result of this work is that it reveals the strong dependence of the energy output on the interaction between bridge, harvester, and traffic details. A second result is that the methodology yields design criteria for the harvester such that the energy output is maximized. Through the case study of an actual middle-sized bridge in Germany, we demonstrate the feasibility of harvesting a time-averaged power of several milliwatts throughout the day. Comparing the total amount of harvested energy for 1000 randomized traffic scenarios, we demonstrate the suitability of pEHS to power wireless sensor nodes. In addition, we show the potential sensory usability for traffic observation (vehicle frequency, vehicle weight, axle load, etc.). Full article

Efficient maintenance is paramount for rail transport systems to avoid catastrophic accidents. Therefore, a method that enables the early detection of defects in critical components is crucial for increasing the availability of rolling stock and reducing maintenance costs. This work’s main contribution is the proposal of a methodology for analyzing vibration signals. The vibration signals, obtained from a bogie axle on a test bench, are decomposed into intrinsic functions, to which classical signal processing techniques are then applied. Finally, decision trees are employed to characterize the axle’s state, yielding excellent results. Full article

Background/Objectives: Subcutaneous tumor models are widely used in colorectal cancer (CRC) research due to their experimental accessibility; however, the spatial organization and regulatory mechanisms of their tumor microenvironment remain poorly understood. Methods: Here, we applied spatial transcriptomics to systematically characterize spatial heterogeneity within MC38 subcutaneous tumors in a syngeneic mouse model. Results: We identified two spatially distinct tumor zones, partitioned by cancer-associated fibroblasts (CAFs), that differ markedly in cellular composition, oncogenic signaling, immune infiltration, and metabolic states. One zone exhibited features of TGF-β-driven extracellular matrix remodeling, immune exclusion, and hyperproliferative metabolism, while the other was enriched for immunosuppressive macrophages, metabolic reprogramming via PPAR and AMPK pathways, and high-risk cell populations. Spatially resolved cell–cell communication networks further revealed zone-specific ligand–receptor interactions—such as ANGPTL4–SDC2 and PROS1–AXL—that underpin stromal remodeling and immune evasion and are associated with patient prognosis. Conclusions: Collectively, our study uncovers how region-specific cellular ecosystems and intercellular crosstalk establish prognostically divergent niches within subcutaneous CRC tumors, offering insights into spatially guided therapeutic strategies. Full article

Inflammation is a self-defense mechanism that controls the homeostasis of an organism, and its alteration by persistent noxious stimuli could lead to an imbalance in the regulation of inflammatory responses mediated by innate and adaptive immunity. During chronic inflammation, sustained exposure of myeloid cells to the various inflammatory signals derived from inflamed tissue could lead to the generation of myeloid cells with an immunosuppressive state, called myeloid-derived suppressor cells (MDSCs), which can exert protective or deleterious functions depending on the nature of signals and the specific inflammatory conditions created by different pathophysiological contexts. Initially identified in various tumor models and cancer patient samples, these cells have long been recognized as negative regulators of anti-tumor immunity. Consequently, researchers have focused on elucidating the molecular mechanisms underlying their potent immunosuppressive activity. As a key component of the signal transducing processes, protein kinases play a central role in regulating the signal transduction mechanisms of many cellular activities, including differentiation and immunosuppression. Over the past decade, at least a dozen kinases, including mechanistic target of rapamycin (mTOR), phosphoinositide 3-kinases (PI3Ks), TAM (Tyro3, Axl, Mer) family of receptor tyrosine kinases (TAM RTKs), mitogen-activated protein kinases (MAPKs), and others, have emerged as key contributors to the generation and differentiation of MDSCs. Here, we discuss the recent findings on these kinases that directly contribute to the immunosuppressive functions of MDSCs. Full article

Glioblastoma multiforme (GBM) is an aggressive and molecularly heterogeneous brain cancer with a poor prognosis. Despite advancements in standard-of-care therapies, including surgery, radiotherapy, and temozolomide (TMZ), the median survival remains approximately 15 months, with a 5-year survival rate of less than 10%. We and others have demonstrated that FOXM1 is a critical oncogenic driver of GBM cell proliferation. However, the role of FOXM1 and its interaction with other oncogenic signaling pathways in GBM remains incompletely understood. In this study, we identified FOXM1, AXL, and eEF2K as highly upregulated oncogenes in GBM patient tumors. We demonstrated, for the first time, that FOXM1 directly interacts with AXL and eEF2K, regulating their expression and promoting GBM cell proliferation, migration, and invasion. Knockdown of these genes disrupted cell proliferation, spheroid formation, migration, and invasion, and induced apoptosis and ferroptosis. Additionally, inhibiting the FOXM1–AXL/eEF2K signaling axis sensitized GBM cells to TMZ, further enhancing apoptotic and ferroptotic responses. These findings highlight the critical role of the FOXM1–AXL/eEF2K signaling pathway in GBM progression and suggest that targeting this axis may offer a novel multitargeted therapeutic strategy in GBM. Full article

The structural integrity of cement concrete pavements, paramount for ensuring traffic safety and operational efficiency, faces mounting challenges from the escalating burden of heavy-duty vehicular traffic. Precise characterisation of pavement dynamic responses under such conditions proves indispensable for implementing effective structural health monitoring and early warning system deployment. This investigation examines the triaxial dynamic response characteristics of cement concrete pavement subjected to low-speed, heavy-duty vehicular excitations, employing data acquired through in situ field measurements. A monitoring system incorporating embedded triaxial MEMS accelerometers was developed to capture vibration signals directly within the pavement structure. Raw data underwent preprocessing utilising a smoothing wavelet transform technique to attenuate noise, followed by empirical mode decomposition (EMD) and short-time energy (STE) analysis to scrutinise the time–frequency and energetic properties of triaxial vibration signals. The findings demonstrate that heavy, slow-moving vehicles generate substantial triaxial vibrations, with the vertical (Z-axis) response exhibiting the greatest amplitude and encompassing higher dominant frequency components compared to the horizontal (X and Y) axes. EMD successfully decomposed the complex signals into discrete intrinsic mode functions (IMFs), identifying high-frequency components (IMF1–IMF3) associated with transient vehicular impacts, mid-frequency components (IMF4–IMF6) presumably linked to structural and vehicle dynamics, and low-frequency components (IMF7–IMF9) representing system trends or ambient noise. The STE analysis of the selected IMFs elucidated the transient nature of axle loading, revealing pronounced, localised energy peaks. These findings furnish a comprehensive understanding of the dynamic behaviour of cement concrete pavements under heavy vehicle loads and establish a robust methodological framework for pavement performance assessment and refined axle load identification. Full article

The article presents a new method of passive dynamic weighing of vehicles based on the registration of seismic signals that occur when wheels pass through strips specially applied to the road surface. Signal processing is carried out using spectral methods, including fast Fourier transform, consistent filtering, and regularization methods for solving inverse problems. Special attention is paid to the use of linear-frequency-modulated signals, which make it possible to distinguish the responses of individual axes even when superimposed. Field tests were carried out on a real section of the road, during which signals from vehicles of various classes were recorded using eight geophones. The average error in determining the speed of 1.2 km/h and the weight of 8.7% was experimentally achieved, while the correct determination of the number of axles was 96.5%. The results confirm the high accuracy and sustainability of the proposed approach with minimal implementation costs. It is shown that this system can be scaled up for use in intelligent transport systems and applied in real traffic conditions without the need to intervene in the design of the roadway. Full article

The safe management of traffic on rail networks requires that trains can be reliably located at all times. In many countries, this is achieved by electrically identifying their presence using ‘track circuits’ at regular intervals along each track: these devices detect when the wheels and axles of a train short-circuit the two rails (they are said to ‘shunt’ them) and the information is passed on to the signaling system. The quality of the electrical contacts between the rails and the wheels obviously plays a decisive role in the correct operation of this detection principle. The occurrence of high wheel–rail contact resistances can lead to malfunctions, known as ‘deshunting’, in which the system is unable for a certain period of time to conclude whether a train is present or absent on a section of track. This type of potentially risky event must obviously be avoided at all costs. In this article, we present the second part of a study devoted to the degradation of the wheel–rail contact resulting from steel oxidation, using a scaled-down home-made test bench that reproduces the real contact in the laboratory under controlled conditions. Following on from the first part, which dealt with the static characterization of the contact studied in the direct current, we are now tackling its dynamic characterization (rolling contact) under AC electrical conditions close to those of a track circuit. These new investigations again involve different degrees of rail oxidation, and analyze the influence of parameters such as contact force, speed, and current intensity. Full article

Maintenance measures are widespread in the industrial environment, and various approaches to maintenance using artificial intelligence are increasingly gaining ground. Predictive assessments of system conditions ensure greater reliability and cost reductions through longer service life. The implementation of a machine learning and a deep learning algorithm for predictive maintenance through early damage detection on an electric rear axle test bench is presented in this paper. The algorithms were selected based on extensive literature research. This paper deals with the question of whether the approach of condition-based or statistical predictive maintenance provides more benefit for a development test bench with highly varying tests. The chosen method of deep learning and machine learning can predict damage for a specific device under test with an accuracy of up to 99% using only one torque signal. In fact, the machine learning approach was found to be sensitive to abnormal behavior on the test bench as well, leaving no abnormality undetected. Although the deep learning model was more resistant to other damage, a pretrained model can be applied to any similar device under test and deliver almost identical results. The methods presented can be adapted to various industrial applications with some adjustments, even without access to big data. This enables predictive maintenance from the very first applications. Full article

The Ras/PI3K/ERK signaling network is frequently mutated and overactivated in various human cancers. Focal adhesion kinase (FAK) is commonly overexpressed in several cancer types and has been implicated in treatment resistance mechanisms. A positive feedback loop between Ras, PI3K, the cytoskeleton, and FAK was previously shown to drive Ras signaling excitability. In this study, we investigated the effectiveness of targeting Ras signaling excitability by concurrently inhibiting FAK and PI3K in cervical and pancreatic cancer cells, which depend on activation Ras/PI3K signaling. We found that the combination of FAK and PI3K inhibitors synergistically suppressed the growth of cervical and pancreatic cancer cell lines through increased apoptosis and decreased mitosis. PI3K inhibitors alone caused only a transient suppression of downstream AKT activity and paradoxically increased FAK signaling in cancer cells. The addition of an FAK inhibitor effectively counteracted this PI3K-inhibitor-induced FAK activation. Furthermore, PI3K inhibitors were found to activate multiple receptor tyrosine kinases (RTKs), including insulin receptor, IGF-1R, EGFR, HER2, HER3, AXL, and EphA2. Taken together, our results suggest that FAK inhibition is necessary to counteract the compensatory RTK activation induced by PI3K inhibitors, thereby achieving more effective suppression of cancer cell growth. These findings highlight the therapeutic potential of combined FAK and PI3K inhibition in cancer treatment. Full article

Neovascularization is an important process in brain tumor development, invasion and metastasis. Several research studies have indicated that the VEGF signaling target has potential for reducing angiogenesis in brain tumors. However, targeting VEGF signaling has not met the expected efficacy, despite initial enthusiasm. This is partly because tumors cleverly use alternative growth factor pathways, other than VEGF signaling, to restore angiogenesis. Multi-target inhibitors have been developed to inhibit several receptor kinases that play a role in the development of angiogenesis. By simultaneously affecting various receptor kinases, these treatments can potentially obstruct various angiogenic pathways that are involved in brain cancer advancement, often offering a more holistic strategy than treatments focusing on just one kinase. Since 2009, the FDA has approved a number of multi-kinase inhibitors that target angiogenic growth factor receptors (e.g., VEGFR, PDGFR, FGFR, RET, c-KIT, MET, AXL and others) for treatment of malignant diseases, including brain cancer. Here, we present some recent results from the literature regarding the preclinical and clinical effects of these inhibitors on brain tumors. Full article

Preeclampsia (PE) is a complex pregnancy-specific disorder characterized by hypertension, proteinuria, and systemic inflammation, posing significant risks to maternal and fetal health. This study investigates the role of growth arrest-specific protein 6 (Gas6) in PE pathogenesis using a rat model. Gas6 administration induces hallmark PE features, including hypertension, proteinuria, and significant alterations in placental gene expression. Transcriptomic analysis revealed changes in pathways related to extracellular matrix remodeling, interleukin signaling, and oxidative stress, highlighting their contribution to PE pathology. Key findings include the upregulation of Fam111a, linked to oxidative stress and DNA replication, and the downregulation of Clca4, associated with ion transport and cellular homeostasis. Protein-level validation through immunofluorescence confirmed these alterations, reinforcing their mechanistic roles in placental dysfunction. Enrichment analysis further identified significant disruptions in extracellular matrix organization and intercellular signaling. These results underscore the pivotal role of Gas6 in exacerbating placental oxidative stress and systemic inflammation. Importantly, therapeutic inhibition of the Gas6/AXL axis using small-molecule inhibitors mitigated PE-like symptoms, highlighting its potential as a therapeutic target. This study provides novel insights into the molecular underpinnings of Gas6-mediated placental dysfunction and supports the development of targeted therapies to improve PE outcomes. Full article