Search Results (138)

Highly sensitive bioinspired cutaneous receptors are essential for realistic human-robot interaction. This study presents a biomimetic tactile sensor morphologically modeled after the Meissner corpuscle, designed for high dynamic sensitivity achieved using a coiled configuration. Our proposed electrolytic polymerization technique with magnet-responsive hybrid fluid (HF) was employed to fabricate soft, elastic rubber sensors with embedded coiled electrodes. The coiled configuration, optimized by electrolytic polymerization, exhibited high responsiveness to dynamic motions including pressing, pinching, twisting, bending, and shearing. The mechanism of the haptic property was analyzed by electrochemical impedance spectroscopy (EIS), revealing that reactance variations define an equivalent electric circuit (EEC) whose resistance (R_p), capacitance (C_p), and inductance (L_p) change with applied force; these changes correspond to mechanical deformation and the resulting variation in the sensor’s built-in voltage. The roll-type Meissner-inspired sensor demonstrated fast-adapting behavior and broadband vibratory sensitivity, indicating its potential for high-performance tactile and auditory sensing. These findings confirm the feasibility of electrolytically polymerized hybrid fluid rubber as a platform for next-generation bioinspired haptic interfaces. Full article

Urban flood disasters have become one of the most significant natural hazards under the dual pressures of rapid urbanization and intensified climate change. With the increasing interconnection among urban subsystems, these disasters often evolve into urban flood disaster chains, characterized by cascading failures across infrastructure, environment, and society. Current research hotspots mainly focus on three key aspects: the formation mechanisms, identification methods, and risk assessment approaches of urban flood disaster chains. In terms of formation mechanisms, most studies qualitatively describe the triggering and transmission processes of cascading events, revealing how interactions among hazard-inducing factors, disaster-formative environments, and disaster receptor generate chain reactions. Identification methods are categorized into four paradigms: qualitative identification based on experiential reasoning, semantic identification driven by data, structural identification through model inference, and behavioral identification using simulation modeling. Risk assessment approaches include historical disaster analysis, indicator-based evaluation models, uncertainty models, numerical simulation models, and intelligent algorithm models that integrate machine learning with physical simulations. The review finds that, due to the scarcity and heterogeneity of disaster chain event data, existing studies lack a unified quantitative framework to represent the mechanisms of urban flood disaster chains, as well as dynamic identification and assessment methods that can adapt to their evolutionary processes. Future research should focus on developing integrated mathematical paradigms, enhancing multisource data fusion and causal reasoning, and constructing hybrid models to support real-time risk assessment for urban flooding disaster chains. Full article

Standardized, one-size-fits-all COVID-19 booster schedules may be suboptimal due to individual variation in immune backgrounds, particularly prior infection, which induces robust hybrid immunity. This study estimated optimal booster timing by modeling antibody decay in relation to surrogate correlates of protection (CoP). In a prospective cohort of 177 Japanese healthcare workers, we longitudinally monitored anti-spike receptor-binding domain (S-RBD) antibody titers following BNT162b2 vaccination. Participants were stratified into SARS-CoV-2-naïve and previously infected groups. Mixed-effects models were developed to predict when antibody titers would decline below predefined CoP thresholds. The model estimated optimal booster timing after a two-dose primary series to be 3–5 months for naïve individuals and approximately one year for those with prior infection. Following a third dose, the estimated interval extended to 8–12 months for the naïve group and 1.5–2 years for the previously infected group. These substantial differences underscore the limitations of uniform booster schedules. Our findings provide a quantitative framework for personalized vaccination strategies based on individual antibody profiles and immune status, thereby optimizing protection. Full article

Breast cancer is a heterogeneous malignancy with distinct molecular subtypes that complicate the development of effective therapies. Traditional drug discovery methods are often constrained by high cost and long development timelines, underscoring the need for more efficient, subtype-aware approaches. Computer-aided drug design (CADD) has emerged as a valuable strategy to accelerate therapeutic discovery and improve lead optimization. This review synthesizes advances from a subtype-centric perspective and outlines the application of CADD techniques, including molecular docking, virtual screening (VS), pharmacophore modeling, and molecular dynamics (MD) simulations, to identify potential targets and inhibitors in receptor-positive (Luminal), HER2-positive (HER2⁺), and triple-negative breast cancer (TNBC). In addition to traditional pipelines, we highlight artificial intelligence (AI)-enabled methods and a hybrid workflow in which learning-based models rapidly triage chemical space while physics-based simulations provide mechanistic validation. These approaches have facilitated the discovery of subtype-specific compounds and enabled the refinement of candidate drugs to enhance efficacy and reduce toxicity. Despite these advances, critical challenges remain, particularly tumor heterogeneity, drug resistance, and the need to rigorously validate computational predictions through experimental studies. Future progress is expected to be driven by the integration of AI, machine learning (ML), multi-omics data, and digital pathology, which may enable the design of more precise, subtype-informed, and personalized therapeutic strategies for breast cancer. Full article

Background/Objectives: Ovarian cancer is a heterogeneous malignancy with molecular subtypes that strongly influence prognosis and therapy. High-dimensional mRNA data can capture this biological diversity, but its complexity and noise limit robust subtype characterization. Furthermore, current classification approaches often fail to reflect subtype-specific transcriptional programs, underscoring the need for computational strategies that reduce dimensionality and identify discriminative molecular features. Methods: We designed a multi-stage feature selection and network analysis framework tailored for high-dimensional transcriptomic data. Starting with ~65,000 mRNA features, we applied unsupervised variance-based filtering and correlation pruning to eliminate low-information genes and reduce redundancy. The applied supervised Select-K Best filtering further refined the feature space. To enhance robustness, we implemented a hybrid selection strategy combining recursive feature elimination (RFE) with random forests and LASSO regression to identify discriminative mRNA features. Finally, these features were then used to construct a gene co-expression similarity network. Results: This pipeline reduced approximately 65,000 gene features to a subset of 83 discriminative transcripts, which were then used for network construction to reveal subtype-specific biology. The analysis identified four distinct groups. One group exhibited classical high-grade serous features defined by TP53 mutations and homologous recombination deficiency, while another was enriched for PI3K/AKT and ARID1A-associated signaling consistent with clear cell and endometrioid-like biology. A third group displayed drug resistance-associated transcriptional programs with receptor tyrosine kinase activation, and the fourth demonstrated a hybrid profile bridging serous and endometrioid expression modules. Conclusions: This pilot study shows that combining unsupervised and supervised feature selection with network modeling enables robust stratification of ovarian cancer subtypes. Full article

Circulating tumor cells (CTCs) are crucial biomarkers for lung cancer metastasis and recurrence, garnering significant clinical attention. Despite this, efficient and cost-effective detection methods remain scarce. Consequently, there is an urgent demand for the development of highly sensitive CTC detection technologies to enhance lung cancer diagnosis and treatment. This study utilized microspheres and A549 cells to model CTCs, assessing the impact of acoustic field forces on cell viability and proliferation and confirming capture efficiency. Subsequently, CTCs from the peripheral blood of patients with lung cancer were captured and identified using fluorescence in situ hybridization, and the results were compared to the immunomagnetic bead method to evaluate the differences between the techniques. Finally, epidermal growth factor receptor (EGFR) mutation analysis was conducted on CTC-positive samples. The findings showed that acoustic microfluidic technology effectively captures microspheres, A549 cells, and CTCs without compromising cell viability or proliferation. Moreover, EGFR mutation analysis successfully identified mutation types in four samples, establishing a basis for personalized targeted therapy. In conclusion, acoustic microfluidic technology preserves cell viability while efficiently capturing CTCs. When integrated with EGFR mutation analysis, it provides robust support for the precise diagnosis and treatment of lung cancer as well as personalized drug therapy. Full article

Background/Objectives: Cancer progression is characterized by the suppression of apoptosis, activation of metastatic processes, and dysregulation of cell proliferation. The proper functioning of these mechanisms relies on critical signaling pathways, including Phosphoinositide 3-kinase/Protein kinase B/mammalian Target of Rapamycin (PI3K/Akt/mTOR), Mitogen-Activated Protein Kinase (MAPK), and Signal Transducer and Activator of Transcription 3 (STAT3). Although curcumin and resveratrol exhibit anticancer properties and affect these pathways, their pharmacokinetic limitations, including poor bioavailability and low solubility, restrict their clinical application. The aim of our study was to evaluate the synergistic anticancer potential of curcumin and resveratrol through hybrid molecules rationally designed from these compounds to mitigate their pharmacokinetic limitations. Furthermore, we analyzed the multi-target anticancer effects of these hybrids on the AKT serine/threonine kinase 1 (AKT1), MAPK, and STAT3 pathways using in silico molecular modeling approaches. Methods: Three hybrid molecules, including a long-chain (ELRC-LC) and a short-chain (ELRC-SC) hybrid, an ester-linked hybrid, and an ether-linked hybrid (EtLRC), were designed using the Avogadro software (v1.2.0), and their geometry optimization was carried out using Density Functional Theory (DFT). The electronic properties of the structures were characterized through Frontier Molecular Orbital (FMO), Molecular Electrostatic Potential (MEP), and Fourier Transform Infrared (FTIR) analyses. The binding energies of the hybrid molecules, curcumin, resveratrol, their analogs, and the reference inhibitor were calculated against the AKT1, MAPK, and STAT3 receptors using molecular docking. The stabilities of the best-fitting complexes were evaluated through 100 ns molecular dynamics (MD) simulations, and their binding free energies were estimated using the Molecular Mechanics/Poisson–Boltzmann Surface Area (MM/PBSA) method. Results: DFT analyses demonstrated stable electronic characteristics for the hybrids. Molecular docking analyses revealed that the hybrids exhibited stronger binding compared to curcumin and resveratrol. The binding energy of −11.4 kcal/mol obtained for the ELRC-LC hybrid against AKT1 was particularly remarkable. Analysis of 100 ns MD simulations confirmed the conformational stability of the hybrids. Conclusions: Hybrid molecules have been shown to exert multi-target mechanisms of action on the AKT1, MAPK, and STAT3 pathways, and to represent potential anticancer candidates capable of overcoming pharmacokinetic limitations. Our in silico-based study provides data that will guide future in vitro and in vivo studies. These rationally designed hybrid molecules, owing to their receptor affinity, may serve as de novo hybrid inhibitors. Full article

Obesity is a complex, multifactorial disease and a growing global health challenge associated with type 2 diabetes, cardiovascular disorders, cancer, and reduced quality of life. The existing pharmacological therapies are characterized by their limited number and efficacy, and safety concerns further restrict their utilization. This review synthesizes extensive knowledge regarding the role of the endocannabinoid system (ECS) in the pathogenesis of obesity, as well as its potential as a therapeutic target. A thorough evaluation of preclinical and clinical data concerning endocannabinoid ligands, cannabinoid receptors (CB1, CB2), their genetic variants, and pharmacological interventions targeting the ECS was conducted. Literature data suggests that the overactivation of the ECS may play a role in the pathophysiology of excessive food intake, dysregulated energy balance, adiposity, and metabolic disturbances. The pharmacological modulation of ECS components, by means of CB1 receptor antagonists/inverse agonists, CB2 receptor agonists, enzyme inhibitors, and hybrid or allosteric ligands, has demonstrated promising anti-obesity effects in animal models. However, the translation of these findings into clinical practice remains challenging due to safety concerns, particularly neuropsychiatric adverse events. The development of novel strategies, including peripherally restricted compounds, hybrid dual-target agents, dietary modulation of endocannabinoid tone, and non-pharmacological interventions, promises to advance the field of obesity management. Full article

Colorectal cancer (CRC) remains a major contributor to global cancer-related mortality, with rising incidence observed in several regions, including Saudi Arabia. This review compiles and critically analyzes recent preclinical research from Saudi-based institutions that investigates the anti-CRC potential of natural and synthetic compounds. Numerous natural products such as Nigella sativa, Moringa oleifera, Curcuma longa, and marine-derived metabolites have demonstrated cytotoxic effects through pathways involving apoptosis induction, reactive oxygen species (ROS) generation, and inhibition of nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) and cyclooxygenase-2 (COX-2). In parallel, synthetic and semi-synthetic agents, including C4–G4 (semi-synthetic hybrids designed from flavonoids and benzoxazole scaffolds that act as dual epidermal growth factor receptor (EGFR)/COX-2 inhibitors)), oxazole derivatives, and camptothecin-based nanocarriers, exhibit promising anti-tumor activity via molecular targeting of cyclin-dependent kinase 8 (CDK8), phosphatidylinositol 3-kinase/protein kinase B (PI3K/Akt), and β-catenin pathways. Selected in vivo studies primarily utilizing xenograft and chemically induced rodent models have shown reductions in tumor volume and modulation of apoptotic and inflammatory biomarkers. Additionally, green-synthesized metallic nanoparticles (NPs) and polyethylene glycol (PEG)-modified carriers have been investigated to improve bioavailability and tumor targeting of lead compounds. While these findings are encouraging, the majority remain in preclinical phases. Limitations such as poor solubility, lack of pharmacokinetic data, and absence of clinical trials impede translational progress. This review highlights the need for standardized evaluation protocols, mechanistic validation, and region-specific clinical studies to assess efficacy and safety. Given Saudi Arabia’s rich biodiversity and growing research capacity under national strategies like Vision 2030, the country is well-positioned to contribute meaningfully to CRC drug discovery. By integrating bioactive natural products, rationally designed synthetics, and advanced delivery platforms, a pipeline of innovative CRC therapeutics tailored to local and global contexts may be realized. Full article

Lipopolysaccharide (LPS), an essential structural molecule in the outer membrane of Gram-negative bacteria, is recognized as a principal trigger of inflammatory responses and oxidative stress. Thus, the control and clearance of LPS is essential to inhibit LPS-induced excessive inflammation, oxidative stress, and liver injury. In recent years, some native bioactive peptides, such as human β-defensin 126 (DEFB126) and thymopentin (TP5), have been reported to have inhibitory effects against LPS-induced inflammation and oxidative stress. However, the cytotoxicity, weak stability, and poor biological activity have hindered their practical application and clinical development. The development of novel hybrid peptides is a promising approach for overcoming these problems. In this study, we designed a novel hybrid peptide [DTP, DEFB126 (1-39)-TP5] that combines the active center of DEFB126 and full-length thymopentin (TP5). Compared to the parental peptides, DTP has a longer half-life, lower cytotoxicity, and greater anti-inflammatory and antioxidant activity. The anti-inflammatory and antioxidant effects of DTP were demonstrated in a murine LPS-induced sepsis model, which showed that DTP successfully inhibited the indicators associated with LPS-induced liver injury; decreased the contents of TNF-α, IL-6, and IL-1β; increased the level of glutathione (GSH); and improved the activities of catalase (CAT) and superoxide dismutase (SOD). Furthermore, our study revealed that the anti-inflammatory and antioxidant activities of DTP were associated with LPS neutralization, blockade of LPS binding to the Toll-like receptor 4/myeloid differentiation factor 2 (TLR4/MD-2) complex, reduction in reactive oxygen species content, and inhibition of the activation of the nuclear factor kappa-B (NF-кB) signaling pathway. These results elucidate the structural and functional properties of the peptide DTP, reveal its underlying molecular mechanisms, and shed light on its potential as a multifunctional agent for applications in agriculture, food technology, and clinical therapeutics. Full article

This review provides a mechanistic framework to strategically design nanoparticles capable of efficiently crossing the blood–brain barrier (BBB), a critical limitation in neurological treatments. We systematically analyze nanoparticle–BBB transport mechanisms, including receptor-mediated transcytosis, adsorptive-mediated transcytosis, and transient barrier modulation. Essential nanoparticle parameters (size, shape, stiffness, surface charge, and biofunctionalization) are evaluated for their role in enhancing brain targeting. For instance, receptor-targeted nanoparticles can significantly enhance brain uptake, achieving levels of up to 17.2% injected dose per gram (ID/g) in preclinical glioma models. Additionally, validated preclinical models (human-derived in vitro systems, rodents, and non-human primates) and advanced imaging techniques crucial for assessing nanoparticle performance are discussed. Distinct from prior BBB nanocarrier reviews that primarily catalogue mechanisms, this work (i) derives quantitative ‘design windows’ (size 10–100 nm, aspect ratio ~2–5, near-neutral ζ) linked to transcytosis efficiency, (ii) cross-walks human-relevant in vitro/in vivo models (including TEER thresholds and NHP evidence) into a translational decision guide, and (iii) integrates regulatory/toxicology readiness (ISO 10993-4, FDA/EMA, ICH) into practical checklists. We also curate recent (2020–2025) %ID/g brain-uptake data across lipidic, polymeric, protein, inorganic, and hybrid vectors to provide actionable, evidence-based rules for BBB design. Full article

The therapeutic potential of cannabinoids and other ligands of cannabinoid receptors attracts considerable attention due to their diverse pharmacological effects and utility in various medical applications. However, challenges such as low solubility, limited bioavailability, and potential side effects hinder their broad clinical use. Nanoformulation techniques offer a promising approach to address these issues and optimize the therapeutic effectiveness of cannabinoids and other cannabinoid receptor ligands. This comprehensive review explores the advancements in nanoformulation strategies to enhance the therapeutic efficacy and safety of synthetic cannabinoids and related compounds, such as CB13, rimonabant, and HU-211, which have been studied in a range of preclinical models addressing conditions such as neuropathic pain, depression, and cancer. The review discusses various nanocarriers employed in this field, including lipid-based, polymeric, and hybrid nanoparticles, micelles, emulsions, and other nanoengineered carriers. In addition to formulation approaches, this review provides an in-depth analysis of chemical structures and their effect on compound activity, especially in the context of the affinity for the cannabinoid type 1 receptor in the brain, which is chiefly responsible for the psychoactive effects. The provided summary of research concerning either chemical modifications of existing cannabinoids or the creation of new compounds that interact with cannabinoid receptors, followed by the development of nanoformulations for these agents, allows for the identification of new research directions and future perspectives for Cannabis-based medicine. In conclusion, the combination of nanotechnology and cannabinoid pharmacology holds promise for delivering more effective and safer therapeutic solutions for a broad spectrum of medical conditions, making this an exciting area of research with profound implications for the healthcare and pharmaceutical industries. Full article

This work investigates the macroscopic behavior of skeletal muscles from a system-theoretic perspective. Based on data available in the literature, we propose an initial evaluation model for isometric force generation, i.e., force produced at a constant muscle length or in quasi-static conditions, as a function of muscle length and neuronal excitation frequency. This model enables a more physics-inspired representation of isometric force by employing a nonlinear spring framework with controllable properties such as stiffness and rest length. Finally, we introduce a hybrid dynamical filter model to describe components of the sensory system responsible for relaying information about muscle length and its rate of change back to the Central Nervous System. As an application case, we present the modeling of the oculomotor system, highlighting the relevance of the proposed modeling approach in a physiologically meaningful control task. Full article

Background/Objectives: Magnetic iron oxide nanoparticles (IONPs), human serum albumin (HSA) and folic acid (FA) are prospective components for hybrid nanosystems for various biomedical applications. The magnetic nanosystems FA-HSA@IONPs (FAMs) containing IONPs, HSA, and FA residue are engineered in the study. Methods: Composition, stability and integrity of the coating, and peroxidase-like activity of FAMs are characterized using UV/Vis spectrophotometry (colorimetric test using o-phenylenediamine (OPD), Bradford protein assay, etc.), spectrofluorimetry, dynamic light scattering (DLS) and electron magnetic resonance (EMR). The selectivity of the FAMs accumulation in cancer cells is analyzed using flow cytometry and confocal laser scanning microscopy. Results: FAMs (d_N~55 nm by DLS) as a drug delivery platform have been administered to cancer cells (human breast adenocarcinoma MCF-7 and MDA-MB-231 cell lines) in vitro. Methylene blue, as a model photosensitizer, has been non-covalently bound to FAMs. An increase in photoinduced cytotoxicity has been found upon excitation of the photosensitizer bound to the coating of FAMs compared to the single photosensitizer at equivalent concentrations. The suitability of the nanosystems for photodynamic therapy has been confirmed. Conclusions: FAMs are able to effectively enter cells with increased folate receptor expression and thus allow antitumor photosensitizers to be delivered to cells without any loss of their in vitro photodynamic efficiency. Therapeutic and diagnostic applications of FAMs in oncology are discussed. Full article

Chronic neuroinflammation and oxidative stress play an important role in the onset and progression of neurodegenerative disorders, including Alzheimer’s disease, which can ultimately lead to neuronal damage and loss. The mechanisms of sustained neuroinflammation and the coordinated chain of events that initiate, modulate, and then lead to the resolution of inflammation are increasingly being elucidated, offering alternative approaches for treating pathologies with underlying chronic neuroinflammation. Here, we propose a new multitarget approach to address chronic neuroinflammation and oxidative stress in neurodegenerative disorders by activating the formyl peptide receptor 2 (FPR2) combined with the potentiation of hydrogen sulfide (H₂S) release. FPR2 is a key player in the resolution of inflammation because it mediates the effects of several endogenous pro-resolving mediators. At the same time, H₂S is an endogenous gaseous transmitter with anti-inflammatory and pro-resolving properties, and it can protect against oxidative stress. Starting from potent FPR2 agonists identified in our laboratories, we prepared hybrid compounds by embedding an H₂S-donating moiety within the molecular scaffold of these FPR2 agonists. Following this approach, we identified several compounds that combined potent FPR2 agonism with the ability to release H₂S. The release of H₂S was assessed in buffer and intracellularly. Compounds 7b and 8b combined potent FPR2 agonist activity, selectivity over FPR1, and the ability to release H₂S. Compounds 7b and 8b were next studied in murine primary microglial cells stimulated with lipopolysaccharide (LPS), a widely accepted in vitro model of neuroinflammation. Both compounds were able to counterbalance LPS-induced cytotoxicity and the release of pro-inflammatory (IL-18, IL-6) and anti-inflammatory (IL-10) cytokines induced by LPS stimulation. Full article