Search Results (1,163)

Fabricating breast tumor models that mimic the natural breast tissue-like microenvironment (normal or cancerous) both physically and bio-metabolically, despite extended research, is still a challenge. A native-mimicking breast tumor model is the demand since complex biophysiological mechanisms in the native breast tissue hinder deciphering the root causes of cancer initiation and progression. Hydrogels, which mimic the natural extracellular matrix (ECM), are increasingly demanded for various biomedical applications, including tissue engineering and tumor modeling. Their biomimetic 3D network structures have demonstrated significant potential to enhance the breast tumor model, treatment, and recovery. Additionally, 3D tumor organoids cultivated within hydrogels maintain the physical and genetic traits of native tumors, offering valuable platforms for personalized medicine and therapy response evaluation. Hydrogels are broadly classified into static and dynamic hydrogels. Static hydrogels, however, are inert to external stimuli and do not actively participate in biological processes or provide scaffolding systems. Dynamic hydrogels, on the other hand, adapt and respond to the surrounding microenvironment or even create new microenvironments according to physiological cues. Dynamic hydrogels typically involve reversible molecular interactions—through covalent or non-covalent bonds—enabling the fabrication of hydrogels tailored to meet the mechanical and physiological properties of target tissues. Although both static and dynamic hydrogels can be advanced by incorporating active nanomaterials, their combinations with dynamic hydrogels provide enhanced functionalities compared to static hydrogels. Further, engineered hydrogels with adipogenic and angiogenic properties support tissue integration and regeneration. Hydrogels also serve as efficient delivery systems for chemotherapeutic and immunotherapeutic agents, enabling localized, sustained release at tumor sites. This approach enhances therapeutic efficacy while minimizing systemic side effects, supporting ongoing research into hydrogel-based breast cancer therapies and reconstructive solutions. This review summarizes the roles of dynamic hydrogels in breast tumor models. Furthermore, this paper discusses the advantages of integrating nanoparticles with dynamic hydrogels for drug delivery, cancer treatment, and other biomedical applications, alongside the challenges and future perspectives. Full article

This study investigates the dynamic relationship between key macroeconomic indicators, specifically inflation (CPI), the Federal Funds Rate, GDP growth, unemployment, and money supply, and U.S. stock market returns, represented by the S&P 500 index, over the period January 2015 to June 2025. The objective is to understand how inflation and monetary policy affect market performance in both the short and long run. Using an Autoregressive Distributed Lag (ARDL) modeling framework and Error Correction Model (ECM), the study examines monthly S&P 500 returns alongside macroeconomic variables, accounting for lagged effects and potential cointegration. The model captures both immediate and delayed impacts, employing the Bounds Testing approach to confirm long-run equilibrium relationships. Results show significant mean-reversion in stock returns, a delayed negative impact of inflation and interest rate increases, and a positive contemporaneous response to GDP growth. Unemployment exhibits a counterintuitive positive effect on returns, suggesting forward-looking investor expectations. The money supply also positively influences equity prices, supporting liquidity-based asset pricing theories. This paper provides updated empirical evidence on macro-finance linkages and highlights the complex interplay of monetary policy, inflation, and market expectations in shaping U.S. equity returns. Full article

The primary objective of this research is to simplify and make the industrial manufacturing process of coated maraging steels more economical by combining the advantages of additive manufacturing with simultaneous bulk (aging) and surface (nitriding) treatment in an effective manner. With this aim, preliminary experiments were performed that demonstrated the hardness (and related microstructure) of an as-built MS1 maraging steel, produced by selective laser melting (SLM), is comparable to that of the bulk maraging steel products treated by conventional solution annealing. The direct aging of the solution-annealed and as-built 3D printed maraging steel resulted in similar hardness, indicating that the kinetics of the precipitation hardening process are identical for the steel in both conditions. This assumption was strengthened by a thermodynamic analysis of the kinetics and determination of the activation energy for precipitation hardening using Differential Scanning Calorimetry (DSC) measurements. Industrial target experiments were performed on duplex-coated SLM-printed MS1 steel specimens, which were simultaneously aged and salt-bath nitrided, followed by PVD coating with three different ceramic layers: DLC, CrN, and TiN. For reference, similar duplex-coated samples were used, featuring a bulk Böhler W720 maraging steel substrate that was solution annealed, precipitation hardened, and salt-bath nitrided in separate steps, following conventional procedures. The technological parameters (temperature and time) of the simultaneous nitriding and aging process were optimized by modeling the phase transformations of the entire heat treatment procedure using DSC measurements. A comparison was made based on the in-depth hardness profile estimated by the so-called expanding cavity model (ECM), demonstrating that the hardness of the surface layer of the coated composite material systems is determined solely by the type of the coatings and does not influenced by the type of the applied substrate materials (bulk or 3D printed) or its heat treatment (whether it is a conventional, multi-step treatment or a simultaneous nitriding + aging process). Based on the research work, a proposal is suggested for modernizing and improving the cost-effectiveness of producing aged, duplex-treated, wear-resistant ceramic-coated maraging steel. Full article

Osteoarthritis (OA) is a prevalent degenerative joint disease characterized by cartilage degradation, synovial inflammation, and subchondral bone remodeling, leading to chronic pain and reduced mobility. In early-stage OA, sustained oxidative stress and inflammation drive chondrocyte dysfunction and extracellular matrix (ECM) loss. Hyaluronic acid (HA), a key component of synovial fluid responsible for lubrication and viscoelasticity, is prone to enzymatic and oxidative degradation under inflammatory conditions, limiting its therapeutic effect. To address this, we developed an HA-based system incorporating the natural antioxidant and anti-inflammatory molecule carvacrol. The potential of this formulation was assessed in interleukin-1b-stimulated chondrocytes, which mimic the inflammatory environment of OA. The carvacrol-added HA combination upregulated antioxidant enzyme expression, attenuated pro-inflammatory signaling, and promoted ECM preservation by up regulating cartilage-specific markers and glycosaminoglycan production. In vivo efficacy was further evaluated in a rat model of monosodium iodoacetate-induced OA. HA-Carvacrol treatment alleviated pain-related behaviors and preserved cartilage structure, as confirmed by behavioral assessments and histological analyses. This dual-function formulation integrates the lubricating benefits of HA with the bioactivity of carvacrol, providing preclinical proof-of-concept evidence for its potential in early-stage OA. Full article

Fascia, once considered a passive connective covering, is now recognized as a mechanosensitive tissue and stem cell niche with roles in regeneration, ECM remodeling, and immune–vascular regulation. The aim of this review was to synthetize evidence of fascia-derived progenitors and their mechanobiological functions across in vitro, preclinical and clinical domains. A systematic search of PubMed, Scopus and Web of Science (up to August 2025) was performed in accordance with PRIMS guidelines. Eligible studies addressed fascia in relation to stem/progenitor cells and regenerative outcomes. Risk of bias was assessed with OHAT criteria for in vitro studies, SYRCLE for animal studies and ROBINS-I for clinical studies. Of 648 records identified, 34 studies were included, encompassing 17 in vitro, 17 animal and 4 clinical investigations, with overlap across domains, and 3 reviews. In vitro, fascia-derived stem cells (FDSCs), FAPs and ASCs were shown to remodel ECM, promote angiogenesis and respond to mechanical cues. Animal models revealed collective fibroblast migration as ECM patches, regulated by N-cadherin, Connexin43 and p120-catenin, while CD201+ progenitors directed scar formation. Clinical studies, though few, reported improved outcomes with subfascial PRP injections and adipofascial flaps. Fascia appears as an active mechanobiological hub and stem cell reservoir that may influence tissue repair and fibrosis, although current evidence, particularly from clinical studies, remains preliminary. Despite promising insights, evidence is limited by methodological heterogeneity, emphasizing the need for mechanistic human studies and well-powered clinical trials. Full article

Adaptive Equivalent Consumption Minimization Strategies (A-ECMSs) are one of the best methodologies to optimize fuel consumption of plug-in hybrid vehicles (PHEVs) coupled with low computational requirements. In this paper, a review of A-ECMSs is proposed. Starting from an economic-environmental contextualization, hybrid vehicles are presented and classified, together with their modeling methodologies and the physical-mathematical representation of their components. Next, the control theory for hybrid vehicles is introduced and classified, deriving the A-ECMS approach. Several works accounting for different A-ECMS implementations, based on technology integration, time horizon, adaptivity mechanism, and technique, are addressed. The literature analysis shows a broad coverage of possibilities: the simple proportional-integral (PI) rule for equivalence factor adaptivity is often used, imposing a given battery state-of-charge (SoC); it is possible to optimally plan the battery SoC trajectory through offline optimization with optimal algorithms or by predicting ahead conditions with model predictive control (MPC) or neural networks (NNs); the integration with emerging technologies such as Vehicle-To-Everything (V2X) can be helpful, accounting also for car-following data and GPS information. Moreover, speed prediction is another common technique to optimally plan the battery SoC trajectory. Depending on available on-board computational power and data, it is possible to choose the best A-ECMS according to its application. Full article

Due to the highly nonlinear, dynamic, and slowly time-varying nature of lithium-ion batteries (LIBs) during operation, achieving accurate and real-time parameters online identification in first-order RC equivalent circuit models (ECMs) remains a significant challenge, including low accuracy and poor real-time performance. This paper establishes a fractional-order chaotic system for first-order RC-ECM based on a charge-controlled memristor. The system exhibits chaotic behavior when parameters are tuned. Then, based on the principle of the state observer, an identification observer is designed for each unknown parameter of the first-order RC-ECM, achieving online identification of these unknown parameters of the first-order RC-ECM of LIB. The proposed method addresses key limitations of traditional parameter identification techniques, which often rely on large sample datasets and are sensitive to variations in ambient temperature, road conditions, load states, and battery chemistry. Experimental validation was conducted under the HPPC, DST, and UDDS conditions. Using the actual terminal voltage of a single cell as a reference, the identified first-order RC-ECM parameters enabled accurate prediction of the online terminal voltage. Comparative results demonstrate that the proposed state observer achieves significantly higher accuracy than the forgetting factor recursive least squares (FFRLS) algorithm and Kalman filter (KF) algorithm, while offering superior real-time performance, robustness, and faster convergence. Full article

Preeclampsia (PE) and intrauterine growth restriction (IUGR) are major pregnancy complications that are linked to placental dysfunction and environmental stimulation such as the use of electronic cigarettes (eCig). This study investigates the molecular impacts of timed eCig exposure in a C57BL/6 mouse model of PE and IUGR using bulk RNA-sequencing of placental tissues. Pregnant mice were exposed to eCig vapor via nose-only system starting at embryonic day 12.5 (eCig-6d, before spiral artery (SA) invasion) or 14.5 (eCig-4d, after SA invasion) until E18.5 (necropsy), with healthy controls exposed to room air (n = 6/group). The eCig-4d group developed PE, whereas the eCig-6d group developed both PE and IUGR. RNA-seq analysis revealed 429 differentially expressed genes (DEGs) in eCig-4d (IUGR-like) group and 64 DEGs in eCig-6d (PE + IUGR-like) group compared to controls. Pathway and gene network analyses indicated that eCig-4d exposure activated NF-κB–driven inflammation, suppressed ECM organization and collagen biosynthesis, and downregulated vasoactive genes/mitochondrial-associated genes (NOS1/2), accompanied by impaired complement initiation and reduced both macrophage and monocyte signals. Similarly, eCig-6d exposure led to downregulation of complement-associated genes and granule-related components, possibly implicating weakened neutrophil responsiveness and compromised inflammatory resolution at the maternal–fetal interface. Our findings align with prior studies on physiological dysfunctions in PE and IUGR, while also providing novel insights into the temporally specific cellular responses induced by eCig exposure. Full article

Abdominal aortic aneurysms (AAAs) are progressive, life-threatening vascular disorders characterized by focal dilation of the abdominal aorta due to chronic weakening of the arterial wall. The condition often remains asymptomatic until rupture, which carries mortality rates exceeding 70–85%. Among the various etiological theories of AAA development, degradation of the extracellular matrix (ECM) has emerged as the most widely accepted paradigm, with the breakdown of elastin representing a central and irreversible hallmark event. Elastin, a highly cross-linked and durable structural protein, provides elasticity and recoil to the aortic wall. In human AAA specimens, reduced elastin content, impaired cross-linking, and extensive fiber fragmentation are consistently observed, while experimental studies across multiple animal models confirm that elastin degradation directly correlates with aneurysm initiation, expansion, and rupture risk. Elastin loss is driven by a complex interplay of proteolytic enzymes coupled with inflammatory cell infiltration and oxidative stress. Furthermore, elastin-derived peptides perpetuate immune cell recruitment and matrix degradation, creating a vicious cycle of wall injury. Genetic and epigenetic factors, including variants in ECM regulators and dysregulation of non-coding RNAs, further modulate elastin homeostasis in AAA pathobiology. Clinically, biomarkers of elastin turnover and elastin-targeted molecular imaging techniques are emerging as tools for risk stratification. Therapeutically, novel strategies aimed at stabilizing elastin fibers, enhancing cross-linking, or delivering drugs directly to sites of elastin damage have shown promise in preclinical models and early translational studies. In parallel, regenerative approaches employing stem cells, exosomes, and bioengineered elastin scaffolds are under development to restore structural integrity. Collectively, these advances underscore the pivotal roles of elastin not only as a structural determinant of aneurysm development but also as a diagnostic and therapeutic target. This review summarizes and integrates recent discoveries on elastin biology in AAA, with a particular emphasis on molecular mechanisms of elastin degradation and the translational potential of elastin-centered interventions for the prevention and treatment of AAA. Full article

Impaired bone regeneration and wound healing represent a major clinical and socioeconomic challenge for our aging and multimorbid population. Fracture and wound healing share many common features, with transforming growth factor beta (TGF-β) being a key regulator of inflammation, angiogenesis, fibroblast activation, and matrix remodeling. The dysregulation of TGF-β signaling is a hallmark of chronic wounds, excessive scar formation, and fracture non-union. Extracellular matrix protein 1 (ECM1) plays a crucial role in the activation of latent TGF-β. As a protein of the extracellular matrix, ECM1 offers ideal conditions for the biofunctionalization of bone implants or wound patches. Its mode of action has been studied mainly in fibrosis models of the liver or heart, where TGF-β acts as a driver of the disease. The controlled knock-out or overexpression of ECM1 either promoted or improved fibrosis development. In this review, we discuss how these findings can be applied to the biofunctionalization of implants to support bone and wound healing, considering the impact of TGF-β on the different healing phases. Full article

The tumor microenvironment (TME) plays a crucial role in regulating cancer cell proliferation, invasion, and drug resistance. Traditional two-dimensional (2D) in vitro models and animal models often fail to replicate the biochemical and biophysical complexity of human tumors, leading to low predictive power in preclinical drug screening. In recent years, scaffold-based three-dimensional (3D) in vitro models have emerged as promising alternatives, offering a more physiologically relevant context for studying tumor behavior. Among these, biomimetic scaffolds capable of replicating the composition, stiffness, porosity, and signaling features of the tumor extracellular matrix (ECM) are of particular interest. This review provides a comprehensive overview of scaffold-based approaches for mimicking the TME in vitro. After outlining the key characteristics of the tumor ECM, we discuss various scaffold typologies, including those based on natural, synthetic, and hybrid biomaterials, as well as decellularized ECM. Recent advancements in fabrication technologies, such as electrospinning and 3D bioprinting, are also highlighted for their role in replicating the geometric and mechanical features of tumor tissues. Special attention is given to the integration of vascular components and stromal cells to recapitulate the complexity of the TME. Finally, we explore current limitations and future directions, emphasizing the need for standardized and reproducible models, particularly in the context of personalized cancer therapy. Full article

We present the design of an optically transparent, flexible, and tunable microwave absorber covering the X and Ku frequency bands. The absorber is based on a metasurface composed of a periodic array of graphene spiral resonators (GSRs) attached to an ultrathin PET film placed over an ITO-backed dielectric spacer. An equivalent circuit model (ECM), described by closed-form equations, is proposed to optimize the structure for maximum absorption within the target frequency range. The optimized absorber achieves a peak absorbance of 99.7% for normally incident waves while maintaining over 90% absorption at various incident angles in the frequency range from 8.5 GHz to 17.4 GHz. In addition, a double-layer graphene spiral resonator (DGSR) metasurface is proposed to extend the absorber’s operational bandwidth, demonstrating a bandwidth enhancement of approximately 3 GHz and a relative bandwidth of 90% without compromising miniaturization or incident angle stability. Given their remarkable attributes, both GSR and DGSR configurations show great potential for applications in radar stealth technology and transparent electromagnetic compatibility. Full article

Cancer-associated fibroblasts (CAFs) are key components of the tumor microenvironment (TME) that influence cancer progression via extracellular matrix (ECM) remodeling and secretion of growth factors and cytokines. Endothelial-to-mesenchymal transition (EndMT) is emerging as an important axis among the heterogeneous origins of CAFs. This review introduces the diverse methods used to induce EndMT in cancer—mouse tumor models, conditioned-medium treatment, co-culture, targeted gene perturbation, ligand stimulation, exosome exposure, irradiation, viral infection, and three-dimensional (3D) culture systems—and summarizes EndMT cell-type evidence uncovered using transcriptomic and proteomic technologies. Hallmark EndMT features include spindle-like morphology, increased motility, impaired angiogenesis and barrier function, decreased endothelial markers (CD31, VE-cadherin), and increased mesenchymal markers (α-SMA, FN1). Reported mechanisms include signaling via TGF-β, cytoskeletal/mechanical stress, reactive oxygen species, osteopontin, PAI-1, IL-1β, GSK-3β, HSP90α, Tie1, TNF-α, HSBP1, and NOTCH. Cancer-induced EndMT affects tumors and surrounding TME—promoting tumor growth and metastasis, expanding cancer stem cell-like cells, driving macrophage differentiation, and redistributing pericytes—and is closely associated with poor survival and therapy resistance. Finally, we indicate each study’s stance: some frame cancer-induced EndMT as a source of CAFs, whereas others, from an endothelial perspective, emphasize barrier weakening and promotion of metastasis. Full article

As life expectancy continues to increase, age-related disorders are becoming more prevalent. Among these, vascular complications resulting from chronic inflammation are particularly concerning, as they impair angiogenesis and hinder tissue repair, both processes that heavily rely on a well-structured extracellular matrix (ECM). In this context, MicroMatrix^® UBM Particulate, a skin substitute composed of collagen, laminin, and proteoglycans, appears to offer properties conducive to tissue regeneration. The aim of this study was to evaluate the regenerative potential of MicroMatrix^® combined with the Secretome of human Dental Pulp Stem Cells (hDPSC-S), using the medicinal leech Hirudo verbana, a well-established model for studying wound healing, angiogenesis, and tissue regeneration. Adult leeches were injected with MicroMatrix^® either suspended in FBS-free medium (CTRL) or supplemented with hDPSC-S. 1-week post-treatment, the animals were sacrificed and subjected to morphological and immunohistochemical analyses. Our findings revealed that MicroMatrix^® successfully integrated into the leech body wall. Notably, when supplemented with hDPSC-S, there was a marked increase in cell infiltration, including telocytes and Hematopoietic Precursor Stem Cells, along with a significantly higher vessel density compared to CTRL. These results support the effectiveness of the cell-free device composed of MicroMatrix^® and hDPSC-S, highlighting its potential as a promising strategy for regenerative therapies aimed at treating complex wounds with poor vascularization. Full article

Energy management in hybrid fuel cell ship systems faces the dual challenges of optimizing hydrogen consumption and ensuring power quality. This study proposes an Improved Weighted Antlion Optimization (IW-ALO) algorithm for multi-objective problems. The method incorporates a dynamic weight adjustment mechanism and an elite-guided strategy, which significantly enhance global search capability and convergence performance. By integrating IW-ALO with the Equivalent Consumption Minimization Strategy (ECMS), an improved weighted ECMS (IW-ECMS) is developed, enabling real-time optimization of the equivalence factor and ensuring efficient energy sharing between the fuel cell and the lithium-ion battery. To validate the proposed strategy, a system simulation model is established in Matlab/Simulink 2017b. Compared with the rule-based state machine control and optimization-based ECMS methods over a representative 300 s ferry operating cycle, the IW-ECMS achieves a hydrogen consumption reduction of 43.4% and 42.6%, respectively, corresponding to a minimum total usage of 166.6 g under the specified load profile, while maintaining real-time system responsiveness. These reductions reflect the scenario tested, characterized by frequent load variations. Nonetheless, the results highlight the potential of IW-ECMS to enhance the economic performance of ship power systems and offer a novel approach for multi-objective cooperative optimization in complex energy systems. Full article