Search Results (43)

Diabetic neuropathy (DN) is a multifactorial complication of diabetes mellitus driven by chronic hyperglycemia, insulin resistance, and disturbed metabolic homeostasis, leading to progressive injury of both the peripheral and central nervous systems. This study investigated whether L-serine supplementation could attenuate DN through dose-dependent metabolic and neuroprotective mechanisms in a high-fat diet (HFD) plus streptozotocin (STZ)-induced diabetic rat model. Male Wistar rats (n = 8 per group) were allocated to five groups: normal control (NC), diabetic control (DC), pioglitazone (PIO; 1.5 mg/kg/day), low-dose L-serine (S1; 200 mg/kg/day), and high-dose L-serine (S2; 400 mg/kg/day). After 60 days of oral gavage, behavioural testing, glucose and insulin profiling, HOMA-IR calculation, brain histopathology, nerve growth factor (NGF) immunohistochemistry, and LC–MS/MS-based proteomic analysis of cerebral tissue were performed. Diabetic rats exhibited marked hyperglycaemia (355.33 ± 4.72 mg/dL), hyperinsulinaemia, severe insulin resistance (HOMA-IR 16.8 ± 3.2; a 14-fold increase), impaired thermal nociception, motor dysfunction, and pronounced neuronal degeneration. L-serine supplementation significantly improved metabolic status: S1 reduced HOMA-IR by 77.4% and S2 by 87.5% relative to diabetic controls (p < 0.001). High-dose L-serine produced greater improvements in thermal sensitivity, motor coordination (rotarod latency 26.67 ± 1.52 s vs. 16.1 ± 0.85 s in DC; p < 0.05), and NGF expression (8.6-fold increase vs. DC). Histopathology confirmed attenuation of neuronal injury and gliosis in both treatment groups. Exploratory, group-level proteomic profiling identified dose-specific molecular signatures: S1 was predominantly associated with carbohydrate, lipid, and biosynthetic pathways, whereas S2 was associated with synaptic, neurotransmission-related, and proteostasis pathways. Within the constraints of an exploratory design—group-level pooled proteomics, analysis of cerebral rather than peripheral-nerve tissue, and only two doses—these findings indicate that L-serine attenuates the metabolic and behavioural features of experimental diabetic neuropathy and generates the testable hypothesis of dose-dependent neuro-metabolic remodelling. The proteomic signatures are hypothesis-generating and require orthogonal validation before any mechanistic or translational inference can be drawn. Full article

Despite decades of therapeutic advances, cardiovascular diseases remain the leading cause of global mortality, underscoring the need for strategies that move beyond untargeted systemic pharmacotherapy. Synthetic biology introduces a programmable therapeutic paradigm in which engineered gene circuits can sense, compute, and respond to pathological signals with spatiotemporal precision. This review examines the current progress of synthetic gene circuits for cardiovascular therapy, organized across three domains of clinical relevance. The first domain comprises circuits engineered for direct cardiac applications, from inducible switches to classifier systems. This discussion is further expanded by exploring circuits that indirectly target cardiovascular disease; these circuits address upstream risk factors such as cholesterol dysregulation and chronic inflammation. Looking ahead, the focus shifts to orthogonal architectures pioneered in other therapeutic contexts that hold promise for future cardiac applications. This review further discusses the emerging role of computational tools, including gene regulatory network inference and foundation models, in accelerating target discovery. Finally, a modified Design-Build-Test-Learn framework is proposed to overcome translational bottlenecks, thus paving the way for next-generation cardiac therapeutics. Full article

Torsional resonance is a common phenomenon in engineering vehicle drivelines. To avoid the influence of resonance on the driveline, it is typical to modify the frequency. However, traditional frequency modification methods cannot precisely achieve expected frequencies while keeping others unchanged. They often cause frequency ‘overflow’ and fail to account for the influence of modal damping on drivelines. To address the issues above, a passive modification method is proposed to modify the natural frequencies of engineering vehicle drivelines, considering modal damping. In this paper, the dynamic equations for gears and shafts are derived by a lumped-parameter model that employs the Lagrange method to establish a reasonably equivalent model as a serial-parallel system consisting of (moment of inertia)-(torsional spring)-(torsional damper) with free boundary conditions. Additionally, the passive structural modification for the partial eigenvalue assignment (PEVAPSM) method is employed to modify the specified partial natural torsional frequencies to realizable expected values, while others remain unchanged. The modal damping of the original driveline is modified based on the orthogonal decomposition method. Finally, the practical applicability of the method proposed in this paper is demonstrated through a specific example. Results indicate that the PEVAPSM method has been successfully extended and supplemented from a theoretical translational system, ignoring modal damping, to a practical torsional system considering modal damping to modify natural frequencies of the structure. The improved PEVAPSM method enables to precisely determine the moment of inertia and modal damping of gears in the driveline, preventing resonance with other structures at the same frequency. It offers valuable guidance for studying the torsional vibration characteristics of engineering vehicle drivelines. Full article

Oral probiotic-based therapy has emerged as a promising solution with multifaceted benefits for immunosuppression treatment. However, their widespread and clinical utility is severely limited by the poor viability of probiotics under harsh gastrointestinal conditions in the intestine. To address these challenges, a probiotic-based biohybrid (Lr@DGN) was bio-orthogonally fabricated by covalently anchoring the prebiotic β-glucan (GN) to the probiotic Limosilactobacillus reuteri (Lr). Upon oral administration, Lr@DGN colonized intestines with high survival rates, aided by gastrointestinal stress-shielding of GN, leading to immuno-enhancing effects through combining GN and live Lr. Consequently, in a Cy-induced immunosuppression mouse model, oral administration of Lr@DGN significantly mitigated body weight loss, restored the key immune organ indexes (thymus and spleen), ameliorated Cy-induced damage to the small intestine, enhanced the intestinal immune response, and elevated the serum levels of immunoglobulins IgG and IgA. By integrating the effects of a prebiotic shield and a live probiotic, this biohybrid system offers a promising and translatable approach for managing immunodeficiency and related disorders. Full article

Background/Objectives: Accurate intraoperative tumour localisation remains challenging in minimally invasive colorectal surgery, where conventional tattooing methods suffer from marker migration, tissue diffusion, and potential allergic reactions. Radio frequency identification (RFID) technology offers a promising alternative through implantable passive transponders detectable via electromagnetic coupling, eliminating ionising radiation exposure. Methods: This preclinical feasibility study evaluated three RFID frequency bands for surgical tumour marking: 134 kHz (low frequency, LF), 13.56 MHz (high frequency, HF), and 868 MHz (ultra-high frequency, UHF). Finite element electromagnetic simulations characterised antenna field distributions, while experimental validation employed glass-encapsulated transponders in air and tissue-simulating saline (0.9% NaCl, σ ≈ 1.5 S/m). Detection ranges were measured across 28 angular configurations with expanded measurement uncertainty (k = 2) ranging from ±0.9 to ±3.2 mm. Results: Maximum detection distances in air were 25.0 ± 0.9 mm (LF), 23.0 ± 1.1 mm (HF), and 68.0 ± 2.3 mm (UHF). In saline, ranges decreased to 22.5 ± 1.0 mm, 20.7 ± 1.2 mm, and 18.0 ± 1.4 mm, respectively, demonstrating tissue attenuation of 10% at LF/HF vs. 74% at UHF. Angular characterisation revealed 64–70% range reduction at orthogonal orientation for LF/HF systems. Computational–experimental correlation yielded r² = 0.975 across 154 paired observations. Conclusions: The 13.56 MHz HF band emerges as the optimal candidate for clinical translation, offering adequate tissue penetration (20.7 mm), superior antenna miniaturisation potential (5 mm diameter), established biocompatibility pathways, and mature near-field communication ecosystem support. Future development should address angular sensitivity through multi-axis antenna configurations and validation in anatomically realistic tissue phantoms. This study establishes the electromagnetic evidence base for clinical system development; translation to clinical practice requires sequential preclinical and clinical evaluation. Full article

Background: Magnetic Particle Imaging (MPI) is an emerging biomedical imaging modality that detects superparamagnetic iron oxide nanoparticles (SPIONs), providing high contrast, sensitivity, and quantification capabilities without ionizing radiation, making it particularly suitable for cancer diagnostics. Considerable engineering efforts are underway to translate MPI technology to clinical settings. Most of these MPI scanners feature a cylindrical bore geometry similar to that of other clinical imaging modalities, which limits their potential application primarily to head scanning. Methods: We have developed a single-sided MPI scanner designed to expand the modality’s applicability to other regions of the human body through a unique hardware design developed in our previous work. Imaging experiments were performed on an anatomical breast phantom containing implanted SPION point sources placed at anatomically plausible locations for breast tumors. These point sources served as artificial tumors for evaluating the system’s suitability for breast imaging applications. Results: The scanner successfully detected and clearly resolved the implanted SPION tumors in two orthogonal imaging planes. Tumor positioning was independently validated by ultrasound imaging, confirming MPI’s accurate localization. In addition, sensitivity measurements demonstrated a detection limit of 4.0 $\mathsf{\mu }\mathrm{g}$ of iron, below the estimated 4.8 $\mathsf{\mu }\mathrm{g}$ sensitivity threshold required for breast tumor detection with electronic depth scanning up to 3.5 cm deep. Conclusions: Together, these results demonstrate the capability of a single-sided MPI geometry for breast imaging applications. Imaging an anatomical breast-shaped volume presents significant challenges for MPI due to the size and accessibility constraints of conventional hardware. The results presented highlight the advantages of this approach and support its potential to extend MPI from small-animal imaging to clinically relevant applications. Full article

Human induced pluripotent stem cell (iPSC)-derived brain organoids have emerged as powerful three-dimensional (3D) platforms for modeling human neurodevelopment and neurological disorders. However, the absence of a functional vascular network remains a critical limitation, restricting oxygen and nutrient delivery, impairing metabolic stability, and constraining long-term maturation. Conventional extracellular matrix (ECM) mimetics, such as Matrigel and other static synthetic hydrogels, provide biochemical support but fail to recapitulate the dynamic remodeling that characterizes the developing neurovascular niche. Recent advances in stimuli-responsive hydrogels offer spatiotemporal control over matrix stiffness, degradability, viscoelasticity, and biochemical cue presentation. In this review, we discuss dynamic hydrogel systems within a structure–property–function framework, highlighting how network chemistry and architecture may regulate endothelial sprouting, lumen formation, vascular stabilization, and neurovascular unit maturation in vascularized brain organoid models, based on evidence from both organoid studies and related biomaterial or vascular systems. Photoresponsive, enzyme-cleavable, thermo-responsive, supramolecular, bio-orthogonal click-based, and bioprinted platforms are discussed with emphasis on mechanotransduction, angiocrine signaling, and barrier specialization. Functional outcomes, including trans-endothelial electrical resistance, selective permeability, transporter expression, electrophysiological integration, and sustained perfusion, are discussed alongside translational challenges such as cytocompatibility, oxidative stress, scalability, and regulatory feasibility. Collectively, dynamic hydrogels provide a versatile biomaterial strategy for improving vascularization and aspects of functional maturation in brain organoid models with enhanced physiological relevance. Ultimately, stimuli-responsive hydrogel systems may serve as enabling platforms for engineering vascularized brain organoids and advancing human-relevant neurovascular disease modeling. Full article

In Orthogonal Time–Frequency Space (OTFS) systems, signal detection algorithms based on convolutional neural networks (CNNs) suffer from insufficient feature extraction and are limited by local mixing. Additionally, fixed convolution kernels struggle to match the sparsity and non-stationary characteristics of OTFS signals in the delay-Doppler domain, resulting in slow convergence and high training costs. We do not stop at simply integrating more features outside the existing CNN framework. Instead, we go deeper into the network and replace the fixed convolution kernels with wavelet convolution layers that have time–frequency-adaptive capabilities. This fundamental change allows the network to more intrinsically match the physical characteristics of OTFS signals in the delay-Doppler domain, thereby achieving excellent detection performance while also gaining faster convergence efficiency. Therefore, this paper proposes a signal detection method using an adaptive wavelet convolutional neural network (AWCNN). The approach replaces the first convolutional layer of a standard CNN with an adaptive wavelet layer, which leverages the time–frequency localization properties of Sym4 wavelet kernels along with learnable scaling and translation factors. This enhances the network’s ability to extract sparse features from OTFS signals. Additionally, the model incorporates both the original received signal and preliminary estimates from the message-passing (MP) algorithm as input features, enriching the dataset and further improving detection performance. Experimental results demonstrate that the AWCNN model achieves superior convergence efficiency compared to the CNN model, which attains a bit error rate (BER) comparable to that of the CNN algorithm at a low signal-to-noise ratio of 2 dB, operating without the need for pilot-assisted channel state information acquisition. Full article

Effective drug delivery in oncology is challenged by a hierarchy of biological barriers—from abnormal vasculature and dense stroma to cellular immunosuppression and specialized interfaces like the blood–brain barrier. This review provides a contemporary analysis of smart nanoformulations through the lens of a rational, stage-gated design pipeline. We first deconstruct the solid tumor microenvironment as a multi-tiered obstacle (systemic, stromal, cellular), establishing a barrier-specific foundation for nanocarrier design. The core of the review articulates an architectural toolkit, detailing how intrinsic nanoparticle properties precondition in vivo identity via the protein corona, which in turn informs the selection of advanced ligands for cellular targeting and programmed intracellular trafficking. This integrated framework sets the stage for exploring sophisticated applications, including endogenous and externally triggered responsive systems, bio-orthogonal activation, immuno-nanoformulations, and combination strategies aimed at overcoming multidrug resistance. By synthesizing these components into a cohesive design philosophy, this review moves beyond a catalog of advances to offer a blueprint for engineering next-generation nanotherapeutics. We critically assess the translational landscape and contend that this hierarchical design approach is essential for developing more effective, personalized, and clinically viable cancer treatments. Full article

Temperature-responsive hydrogels are sophisticated stimuli-responsive biomaterials that undergo rapid, reversible sol–gel phase transitions in response to subtle thermal stimuli, most notably around physiological temperature. This inherent thermosensitivity enables non-invasive, precise spatiotemporal control of material properties and bioactive payload release, rendering them highly promising for advanced biomedical applications. This review critically surveys recent advances in the design, synthesis, and translational potential of thermo-responsive hydrogels, emphasizing nanoscale and hybrid architectures optimized for superior tunability and biological performance. Foundational systems remain dominated by poly(N-isopropylacrylamide) (PNIPAAm), which exhibits a sharp lower critical solution temperature near 32 °C, alongside Pluronic/Poloxamer triblock copolymers and thermosensitive cellulose derivatives. Contemporary developments increasingly exploit biohybrid and nanocomposite strategies that incorporate natural polymers such as chitosan, gelatin, or hyaluronic acid with synthetic thermo-responsive segments, yielding materials with markedly enhanced mechanical robustness, biocompatibility, and physiologically relevant transition behavior. Cross-linking methodologies—encompassing covalent chemical approaches, dynamic physical interactions, and radiation-induced polymerization are rigorously assessed for their effects on network topology, swelling/deswelling kinetics, pore structure, and degradation characteristics. Prominent applications include on-demand drug and gene delivery, injectable in situ gelling systems, three-dimensional matrices for cell encapsulation and organoid culture, tissue engineering scaffolds, self-healing wound dressings, and responsive biosensing platforms. The integration of multi-stimuli orthogonality, nanotechnology, and artificial intelligence-guided materials discovery is anticipated to deliver fully programmable, patient-specific hydrogels, establishing them as pivotal enabling technologies in precision and regenerative medicine. Full article

This study aims to evaluate the kinematic performance of two shoulder rehabilitation exoskeleton configurations to address the critical challenge of human–robot compatibility. Utilizing Hunt’s mobility formula and task-specific Jacobian analysis, we developed a closed-chain kinematic model integrating transient glenohumeral joint dynamics, validated through force/torque measurements and ANOVA statistical comparisons. The PPRRRP configuration, featuring orthogonally distributed passive prismatic joints, demonstrated superior performance: 40–60% lower interaction forces (${\overline{\mathrm{F}}}_{\mathrm{t}\mathrm{o}\mathrm{t}\mathrm{a}\mathrm{l}}=2.66 \mathrm{N}$), near-isotropic manipulability (ellipsoid axis ratio < 1.5), and 60% reduced operational torque (${\overline{\mathrm{T}}}_{\mathrm{t}\mathrm{o}\mathrm{t}\mathrm{a}\mathrm{l}}=0.18 \mathrm{N}·\mathrm{m}$) compared to RRRUP’s universal joint design. These results establish passive DOF optimization as a viable alternative to actuator-dense systems, diverging from conventional approaches like ARMin-III that prioritize active control. The originality lies in bridging theoretical configuration synthesis with empirical validation, offering a replicable framework for compatibility assessment. This work advances rehabilitation robotics by demonstrating that mechanical transparency—achieved through strategic passive joint allocation—enhances natural movement synergy without compromising stability, proposing hypotheses on energy efficiency and isotropy–fatigue correlations for future exploration. Clinical translation and adaptive impedance control integration are identified as critical next steps to optimize patient-specific rehabilitation outcomes. Full article

Non-small cell lung cancer (NSCLC) remains a leading cause of cancer mortality, with therapeutic resistance posing the primary barrier to durable outcomes. Beyond genetic and epigenetic alterations, amino acid transporter-driven metabolic reprogramming—mediated by LAT1 (SLC7A5), ASCT2 (SLC1A5), and xCT (SLC7A11)—supports tumor proliferation, redox homeostasis, and immune escape. Their preferential expression in NSCLC highlights their potential as therapeutic targets and predictive biomarkers. In parallel, α-particle therapy has gained attention for its capacity to eradicate resistant clones through densely clustered, irreparable DNA double-strand breaks. Astatine-211 (²¹¹At) combines a clinically relevant half-life, high linear energy transfer, and predictable decay scheme, positioning it as a unique candidate among α-emitters. Preclinical studies of ²¹¹At-labeled transporter ligands, particularly LAT1-targeted conjugates, demonstrate potent tumor suppression and synergy with targeted therapy, chemotherapy, radiotherapy, immunotherapy, and ferroptosis inducers. Advances in radiochemistry, delivery systems (antibodies, peptides, and nanocarriers), and PET tracers such as [¹⁸F]FAMT and [¹⁸F]FSPG collectively support a theranostic framework for patient stratification and adaptive dosing. By linking transporter biology with α-particle delivery, ²¹¹At-based theranostics offer a mechanistically orthogonal strategy to overcome resistance and heterogeneity in NSCLC. Successful translation will depend on precise dosimetry, scaffold stabilization, and biomarker-guided trial design, enabling progression toward first-in-human studies and future integration into multimodal NSCLC therapy. Full article

Cisplatin is a widely used antineoplastic agent whose therapeutic efficacy is often limited by its adverse effects on the central nervous system. In this exploratory study, we characterized the transcriptomic impact of a cumulative cisplatin regimen on the male Wistar rat brain using microarray technology. Differentially expressed genes were identified, and their functional roles were investigated through enrichment analyses (KEGG) and Gene Ontology (GO), and the construction of protein–protein interaction (PPI) networks. Our results revealed significant alterations in pathways related to synaptic signaling, neuroplasticity, and cellular metabolism. To generate translational hypotheses, these findings were subsequently correlated in silico with public human lower-grade glioma (LGG) datasets, which suggested a potential association between key cisplatin-regulated genes and clinical prognosis and immune cell infiltration patterns. This manuscript does not include RT-qPCR (or Western blot) validation; results should be interpreted as hypothesis-generating and require orthogonal confirmation. These findings provide a comprehensive transcriptomic map of cisplatin-induced neurotoxicity, offering novel insights into its underlying molecular mechanisms and identifying a rich set of candidate targets for future neuroprotective strategies. Full article

Future wireless networks are expected to deliver enhanced spectral efficiency while being energy efficient. MIMO and other non-orthogonal transmission schemes, such as non-orthogonal multiple access (NOMA), offer substantial theoretical spectral efficiency gains. However, these gains have yet to translate into practical deployments, largely due to limitations in current signal processing methods. Linear transceiver processing, though widely adopted, fails to fully exploit non-orthogonal transmissions, forcing massive MIMO systems to use a disproportionately large number of RF chains for relatively few streams, increasing power consumption. Non-linear processing can unlock the full potential of non-orthogonal schemes but is hindered by high computational complexity and integration challenges. Moreover, existing message-passing receivers for NOMA depend on specially designed sparse signals, limiting resource allocation flexibility and efficiency. This work presents NL-COMM, an efficient non-linear processing framework that translates the theoretical gains of non-orthogonal transmissions into practical benefits for both the uplink and downlink. NL-COMM delivers over 200% spectral efficiency gains, enables 50% reductions in antennas and RF chains (and thus base station power consumption), and increases concurrently supported users by 450%. In distributed MIMO deployments, the antenna reduction halves fronthaul bandwidth requirements, mitigating a key system bottleneck. Furthermore, NL-COMM offers the flexibility to unlock new NOMA schemes. Finally, we present both hardware and software architectures for NL-COMM that support massively parallel execution, demonstrating how advanced non-linear processing can be realized in practice to meet the demands of next-generation networks. Full article

Click chemistry has become a powerful and flexible approach for designing hydrogels used in tissue engineering thanks to its high specificity, fast reaction rates, and compatibility with biological systems. In this review, we introduce the core principles of click chemistry, including efficiency, orthogonality, and modularity, and highlight the main types of reactions commonly used in hydrogel formation, such as azide-alkyne c-cloadditions, thiol-ene/yne reactions, Diels–Alder cycloadditions, and tetrazine–norbornene couplings. These chemistries allow researchers to create covalently crosslinked hydrogels that are injectable, responsive to environmental stimuli, biodegradable, or multifunctional. We also explore strategies to enhance bioactivity, such as incorporating peptides, growth factors, or extracellular matrix components, and enabling precise spatial and temporal control over biological cues. Click-based hydrogels have shown promise across a wide range of tissue engineering applications, from cartilage and skin repair to neural regeneration, corneal healing, and cardiovascular scaffolds, as well as in 3D bioprinting technologies. Despite the many advantages of click chemistry such as mild reaction conditions and customizable material properties, some challenges remain, including concerns around copper toxicity, the cost of specialized reagents, and scalability. Finally, we discuss the status of clinical translation, regulatory considerations, and future directions, including integration with advanced bio fabrication methods, the design of dual-click systems, and the emerging role of in vivo click chemistry in creating next-generation biomaterials. Full article