Search Results (432)

The therapeutic landscape for hematological malignancies has been fundamentally revolutionized over the last decade by the introduction of targeted antibodies. Notably, antibody–drug conjugates (ADCs) have emerged as a critical breakthrough, significantly improving the efficacy of immune-based treatment. ADCs function as highly sophisticated delivery systems: a selective monoclonal antibody recognizes a specific cell-surface target, guiding a potent toxic payload, attached via a chemical linker, directly into the cancer cell upon internalization. Intensive research has been dedicated to optimizing these components—improving antibody selectivity, enhancing linker stability, and utilizing highly effective payloads—which has resulted in a plethora of compounds that have reached patients’ bedsides and improved the clinical course of different tumors. This review provides a crucial overview of the current landscape of approved ADCs for hematological malignancies. It critically discusses their existing limitations and details the essential structural and chemical improvements that have yielded more potent and selective next-generation tools, finally presenting future strategies to generate highly effective “bullets” capable of decisively improving long-term disease prognosis. Full article

Background/Objectives: Glioblastoma (GBM) remains the most aggressive primary brain tumor in adults, with limited therapeutic options and poor prognosis despite maximal surgery, radiotherapy, and chemotherapy. The complex and immunosuppressive tumor microenvironment, pronounced intratumoral heterogeneity, and the presence of the blood–brain barrier (BBB) severely restrict the efficacy of conventional and emerging therapies. In this context, cell-based strategies leveraging macrophages, mesenchymal stromal cells (MSCs), and their derivatives have gained attention as “cellular allies” capable of modulating the GBM microenvironment and acting as targeted delivery platforms. Methods: This review systematically analyzes preclinical and early clinical literature on macrophage- and MSC-based therapeutic strategies in GBM, including engineered cells, extracellular vesicles (EVs), membrane-coated nanoparticles, and hybrid biomimetic systems. Studies were selected based on relevance to GBM biology, delivery across or bypass of the BBB, microenvironmental modulation, and translational potential. Evidence from in vitro models, orthotopic and syngeneic in vivo models, and available clinical trials was critically evaluated, with emphasis on efficacy endpoints, biodistribution, safety, and manufacturing considerations. Results: The reviewed evidence demonstrates that macrophages and MSCs can function as active therapeutic agents or delivery vehicles, enabling localized oncolysis, immune reprogramming, stromal and vascular remodeling, and enhanced delivery of viral, genetic, and nanotherapeutic payloads. EVs and membrane-based biomimetic platforms further extend these capabilities while reducing cellular risks. However, therapeutic efficacy is highly context-dependent, influenced by tumor heterogeneity, BBB integrity, delivery route, and microenvironmental dynamics. Clinical translation remains limited, with most approaches at preclinical or early-phase clinical stages. Conclusions: Cell-based and cell-derived platforms represent a promising but still evolving therapeutic paradigm for GBM. Their successful translation will require rigorous biomarker-driven patient selection, improved models that capture invasive GBM biology, scalable GMP-compliant manufacturing, and rational combination strategies to overcome adaptive resistance mechanisms. Full article

Silica spicules provide a natural transdermal conduit but require a linker that binds strongly under physiological conditions and releases payloads selectively in response to biological cues. Existing silane chemistries or polydopamine coatings lack enzyme responsiveness and show limited control over release. We created a 180-member peptide library with the motif L–X1–X2–[Y–F–Y]–A–L–G–P–H–C and screened for silica binding. Biophysical assays (circular dichroism, ζ-potential, quartz crystal microbalance, atomic force microscopy) and molecular dynamics identified high-affinity binders. The lead, P176, was tested for matrix metalloprotease (MMP)-responsive cleavage. Conjugation and release of Vitamin C and Stigmasterol were analyzed by HPLC and Franz diffusion cells. P176 showed high silica affinity (~55 µg mg⁻¹), robust biophysical signals (Δf −35 to −38 Hz; rupture force ~154 pN; ζ shift −22 to−11.5 mV), and favorable adsorption energy (−48.5 kcal mol⁻¹, contact 4.5 nm², 8.5 H-bonds). The MMP gate displayed efficient kinetics (Vmax 117.9 RFU·min⁻¹, Km 5.0 µM) with >90% cleavage at 60 min, reduced to 26% by inhibitor. Conjugation yields reached 87% (Vitamin C) and 77% (Stigmasterol). Franz diffusion showed MMP-dependent release (24 h: Vitamin C 90–96%, Stigmasterol 80–85%) with minimal basal leakage. Released Vitamin C enhanced collagen I to ~250% in fibroblasts, while Stigmasterol attenuated LPS-induced macrophage morphology; keratinocytes retained normal marker expression. This study demonstrates that a single amphipathic, sequence-programmed peptide can couple strong silica anchoring with protease-responsive release and broad payload compatibility, establishing a versatile platform for spicule-based transdermal and regenerative delivery. Full article

Polymeric micelles have the potential to improve the efficacy and safety of drug delivery by improving drug solubility, enhancing bioaccumulation and reducing off-target toxicity. Despite excellent safety profiles, a major limitation with polymeric micelles is their inability to rapidly release their payload once they have reached their target, leading to the inadequate delivery of therapeutic doses. To address this limitation, we have developed a novel strategy to impart pH-responsiveness in non-responsive micelles through the co-encapsulation of oligoelectrolytes with drugs. Herein, we investigate the influence of copolymer composition and drug identity in combination with oligoelectrolyte—oligo(2-vinyl pyridine) (OVP)—loading on pH-triggered drug release from micelles and their cytotoxicity. A library of OVP-loaded micelles was prepared using conventional and well-established non-responsive block copolymers. Dynamic light scattering (DLS) was used to monitor the changes in the micelles as a function of pH. Regardless of the copolymer composition, an abrupt decrease in the hydrodynamic diameter (D_h) was observed as the pH was reduced due to OVP expulsion from the core, which was also confirmed by release studies. In general, co-encapsulation of OVP and model drugs (doxorubicin (DOX), gossypol (GP), paclitaxel (PX), and 7-ethyl-10-hydroxycamptothecin (SN38)) in the micelles provided good to excellent encapsulation efficiency percentage (EE%) values. In vitro studies revealed the pH triggered release of drugs from the OVP-loaded micelles regardless of the drug identity, which increased as the OVP loading increased. This general behaviour was observed in all cases, largely independent of the copolymer composition, albeit with subtle differences in the release profile for different drugs. Compared to their blank counterparts, the drug-loaded micelles displayed a slight increase in cytotoxicity against a panel of cancer cell lines, in a dose dependent manner. However, drug- and OVP-loaded micelles displayed a significant increase in cytotoxicity (up to 8-fold increase) that was independent of the copolymer composition. These results demonstrate the versatility of the oligoelectrolyte-mediated approach to furnish non-responsive micelles with a pH-trigger that allows the rapid release of drugs, regardless of the micelle composition or the drug identity. Full article

Peptide-based biomaterials have emerged as versatile tools for pharmaceutical drug delivery due to their biocompatibility and tunable sequences, yet a comprehensive overview of their categories, mechanisms, and optimization strategies remains lacking to guide clinical translation. This review systematically collates advances in peptide-based biomaterials, covering peptide excipients (cell penetrating peptides, tight junction modulating peptides, and peptide surfactants/stabilizers), self-assembling peptides (peptide-based nanospheres, cyclic peptide nanotubes, nanovesicles and micelles, peptide-based hydrogels and depots), and peptide linkers (for antibody drug-conjugates, peptide drug-conjugates, and prodrugs). We also dissect sequence-based optimization strategies, including rational design and biophysical optimization (cyclization, stapling, D-amino acid incorporation), functional motif integration, and combinatorial discovery with AI assistance, with examples spanning marketed drugs and research-stage candidates. The review reveals that cell-penetrating peptides enable efficient intracellular payload delivery via direct penetration or endocytosis; self-assembling peptides form diverse nanostructures for controlled release; and peptide linkers achieve site-specific drug release by responding to tumor-associated enzymes or pH cues, while sequence optimization enhances stability and targeting. Peptide-based biomaterials offer precise, biocompatible and tunable solutions for drug delivery, future advancements relying on AI-driven design and multi-functional modification will accelerate their transition from basic research to clinical application. Full article

Three-dimensional (3D) printing has transformed the development of microneedle arrays (MNAs) by enabling exceptional control over their geometry, distribution, materials, and functionality in a single-step, customizable process. This review represents a design-centric framework that organizes recent advancements in four interconnected levers: (i) individual microneedle (MN) geometry and size; (ii) patch-level MN distribution and multi-array architectures; (iii) computer-aided design (CAD), finite element analysis (FEA), computational fluid dynamics (CFD), and artificial intelligence/machine learning (AI/ML)-driven optimization; and (iv) manufacturing constraints and emerging solutions for scalability and reproducibility. Outcomes show that small changes in the radius of the MN’s tip, the MN’s aspect ratio, the MN’s internal lattice architecture, and the spacing of the array can dramatically influence their insertion force, mechanical reliability, payload capacity, and therapeutic coverage. Now, digital tools can bridge the design and experimental outcomes, while novel morphologies, hybrid materials, and theranostic integrations are expanding the clinical potential of MNs. The remaining challenges, resolution-versus-throughput trade-offs, biocompatibility, batch-to-batch consistency, and lack of testing standardization are examined alongside promising directions in high-throughput 3D printing, stimuli-responsive materials, and closed-loop systems. Finally, rational, model-guided design strategies are positioning 3D-printed MNAs as versatile platforms for painless, patient-specific drug delivery, diagnostics, and personalized medicine. Full article

The increasing demand for rapid and sustainable parcel delivery has motivated the exploration of innovative logistics systems that integrate drones with traditional ground vehicles. Among these, the single-truck, multiple-drone last-mile delivery configuration has attracted significant attention due to its potential to reduce both delivery time and environmental impact. However, optimizing such systems remains computationally challenging because of the nonlinear energy consumption behavior of drones, which depends on factors such as payload weight and travel time, among others. This study investigates the energy-aware optimization of truck–drone collaborative delivery systems, with a particular focus on the mathematical formulation as mixed-integer nonlinear problem (MINLP) formulations and linearization of drone energy consumption constraints. Building upon prior models proposed in the literature in the field, we analyze the MINLP computational complexity and introduce alternative linearization strategies that preserve model accuracy while improving performance solvability. The resulting linearized mixed-integer linear problem (MILP) formulations are solved using the PuLP software, a Python library solver, to evaluate the efficacy of linearization on computation time and solution quality across diverse problem instance sizes from a benchmark of instances in the literature. Thus, extensive computational results drawn from a standard dataset benchmark from the literature by running the solver in a cluster infrastructure demonstrated that the designed linearization methods can reduce optimization time of nonlinear solvers to several orders of magnitude without compromising energy estimation accuracy, enabling the model to handle larger problem instances effectively. This performance improvement opens the door to a real-time or near-real-time solution of the problem, allowing the delivery system to dynamically react to operational changes and uncertainties during delivery. Full article

Cell membrane-coated nanoparticles represent a biomimetic drug delivery approach that integrates biological membrane functions with synthetic nanomaterials. Among the various membrane sources, those derived from blood cells such as red blood cells, platelets, and leukocytes offer distinctive advantages, including immune evasion, prolonged systemic circulation, and selective tissue targeting. These properties collectively enable efficient and biocompatible delivery of therapeutic agents to diseased tissues, minimizing off-target effects and systemic toxicity. This review focuses on blood cell membrane-derived nanocarriers as drug delivery and immune-regenerative platforms, in which membrane-mediated immunomodulation synergizes with therapeutic payloads to address inflammatory or degenerative pathology. We discuss recent advances in blood cell membrane coating technologies, including membrane isolation, nanoparticle core selection, fabrication techniques, and the development of hybrid and engineered membrane systems that enhance therapeutic efficacy through integrated immune regulation and localized drug action. To illustrate these advances, we also compile membrane type-specific nanocarrier systems, summarizing their core nanoparticle designs, coating strategies, therapeutic cargoes, and associated disease models. Challenges related to biological source variability, scalability, safety, and regulatory standardization remain important considerations for clinical translation. In this review we systematically address these issues and discuss emerging solutions and design strategies aimed at advancing blood cell membrane-based nanocarriers toward clinically viable immune-regenerative therapies. Full article

Over the years, cancer has continued to be a leading global health threat, prompting researchers to explore advanced therapies that go beyond traditional treatments like chemotherapy and radiotherapy. Among these advanced therapies, gene therapy and immunotherapy have shown significant promise in treating cancer by either altering genetic makeup or stimulating the immune system. However, their clinical applications face significant obstacles such as poor drug delivery, rapid degradation, and immune system clearance. Hybrid nanocarriers have emerged as a transformative development in modern precision oncology, enabling the co-delivery of gene therapy and immunotherapy agents in a highly targeted manner to address the persistent limitations of traditional cancer treatments. This review focuses on hybrid nanocarrier systems specifically engineered for co-delivery applications and critically evaluates when and how these multifunctional platforms outperform conventional single-modality or non-hybrid formulations. We compare key hybrid architectures in terms of payload compatibility, pharmacokinetics, immune modulation, and translational readiness, and examine the influence of tumor microenvironmental characteristics on their therapeutic performance. Particular emphasis is placed on stimuli-responsive designs, biomimetic surface engineering, and artificial intelligence–assisted optimization as emerging strategies to enhance co-delivery efficacy. By synthesizing current evidence and identifying key scientific and manufacturing gaps, this review aims to provide a practical foundation for advancing hybrid nanocarriers from laboratory development to clinically meaningful, personalized cancer therapies. 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

With the rapid development of the low-altitude economy, UAV logistics delivery systems have garnered widespread attention due to their flexibility and efficiency. The cooperative delivery mode involving a UAV with a suspended payload and a ground vehicle represents a typical networked distribution scenario, whose performance is constrained by the tight coupling of sensing, communication, and control. In practical applications, sensor measurement noise and sudden disturbances propagate through the closed-loop system, severely degrading velocity synchronization and swing angle stability. To address this challenge, this paper focuses on a quadrotor UAV slung-load system and proposes a three-layer nested networked closed-loop control architecture for simultaneous velocity tracking of a moving ground target and swing angle stabilization. First, by establishing the system’s dynamic model, the mapping relationship between cable tension and the payload swing angle (based on sensor feedback) is revealed. Then, by setting the payload velocity as the outermost control objective and constructing a coupled error to drive a virtual swing angle actuator, the direct impact of noise in the raw sensor data is effectively mitigated. Subsequently, the desired acceleration of the UAV is derived through inverse computation, achieving synchronous optimization of velocity tracking and swing angle suppression. Theoretical analysis using Lyapunov methods demonstrates the stability of the closed-loop system in the presence of bounded delays. Simulation results show that the proposed method effectively suppresses payload swing, controls velocity synchronization error, and exhibits strong robustness against sensor noise and sudden disturbance. This study provides a control solution that improves the precision and robustness of sensor-enabled networked control systems in complex dynamic scenarios Full article

Liver diseases, including fibrosis, viral hepatitis, hepatocellular carcinoma, and monogenic genetic disorders, represent a major global health burden with limited therapeutic options and frequent systemic toxicity from conventional treatments. Nanovesicle-based drug and gene delivery systems offer targeted approaches that may improve therapeutic precision and reduce off-target effects. This review aims to evaluate the promise and comparative potential of three key nanovesicle platforms—lipid nanoparticles (LNPs), extracellular vesicles (EVs) and liposomes—for drug and gene delivery in liver disease therapy. A systematic search of peer-reviewed studies published in electronic databases was performed, focusing on preclinical and clinical research investigating the use of LNPs, EVs and liposomes for hepatic drug or gene delivery. Studies were analyzed for vesicle composition, targeting efficiency, payload capacity, therapeutic outcomes, and reported limitations. The analysis indicates that LNPs demonstrate strong efficiency in nucleic acid encapsulation and delivery, supported by growing clinical translation. EVs show promising biocompatibility and innate targeting to hepatic cells but face challenges in large-scale production and standardization. Liposomes remain versatile and well-characterized platforms capable of carrying diverse therapeutic molecules, though rapid clearance can limit their efficacy. Together, these nanovesicle systems hold considerable potential for advancing targeted drug and gene therapies in liver disease. Future work should focus on improving stability, manufacturing scalability, and cell-specific targeting to support clinical translation. Full article

A promising approach to advancing sustainable urban mobility is the increased use of light electric vehicles, such as e-cycles and their cargo-carrying variants: e-cargo cycles. These micromobility vehicles fall between e-cycles and conventional vehicles in terms of transport capacity, range, and cost. A key advantage of e-cargo cycles over their non-electrified counterparts is the electric powertrain, which enables them to carry heavier payloads, travel longer distances, and reduce driver fatigue. Since the primary use of e-cargo cycles is urban parchment deliveries, trip efficiency plays a critical role in their effectiveness within urban logistics. This efficiency is influenced by factors such as travel distance, traffic density, and the weight and volume of the delivery payload. While higher delivery capacity generally enhances efficiency, studies have shown that as the drop size increases, the efficiency of e-cargo cycle delivery trips tends to decline. A practical way to address this limitation is the use of cargo attachments, such as trailers. These micromobility solutions are already widely implemented globally and significantly enhance transport capacity. This paper reports the process of designing and testing the control algorithm of an electrical system for an experimental attachment demonstrator that can be used to convert most cycle vehicles into cargo variants. The system integrates two 250 W BLDC hub motors, two 576 Wh lithium-ion batteries, dual load-cell sensing in the coupling element, and an STM32-based controller to provide independent propulsion and synchronization with the leading cycle. The force-based control strategy enables automatic adaptation to varying payloads typically encountered in urban logistics, which is supported by the variable storage volume capable of transporting payloads of up to 200 kg. Full article

Efficient last-mile delivery remains a critical challenge for rural agricultural logistics, globally, particularly in cold-climate regions with dispersed agricultural operations. Truck–drone hybrids can reduce delivery times but face payload limits, cold-weather battery loss, and beyond-visual-line-of-sight regulations. This review evaluates the potential of GIS-enabled truck–drone hybrid systems to overcome infrastructural, environmental, and operational barriers in such settings. This study uses the state of North Dakota (USA) as a representative case because of its cold climate, low density, and weak connectivity. These conditions require different routing and system assumptions than typical regions. The study conducts a systematic review of 81 high-quality publications. It identifies seven interconnected research domains: GIS analytics, truck–drone coordination, smart agriculture integration, rural implementation, sustainability assessment, strategic design, and data security. The findings stipulate that GIS enhances hybrid logistics through route optimization, launch site planning, and real-time monitoring. Additionally, this study emphasizes the rural, low-density context and identifies specific gaps related to cold-weather performance, restrictions to line-of-sight operations, and economic feasibility in ultra-low-density delivery networks. The study concludes with a roadmap for research and policy development to enable practical deployment in cold-climate agricultural regions. Full article

Low Power Wide Area Networks (LPWAN) have emerged as essential connectivity solutions for the Internet of Things (IoT), addressing requirements for long range, energy efficient communication that traditional wireless technologies cannot meet. With LPWAN connections projected to grow at 26% compound annual growth rate until 2027, understanding real-world performance is crucial for technology selection. This review examines four leading LPWAN technologies—LoRaWAN, Sigfox, Narrowband IoT (NB-IoT), and LTE-M. This review analyzes 20 peer reviewed studies from 2015–2025 reporting real-world deployment metrics across power consumption, range, data rate, scalability, availability, and security. Across these studies, practical performance diverges from vendor specifications. In the cited rural and urban LoRaWAN deployments LoRaWAN achieves 2+ year battery life and 11 km rural range but suffers collision limitations above 1000 devices per gateway. Sigfox demonstrates exceptional range (280 km record) with minimal power consumption but remains constrained by 12 byte payloads and security vulnerabilities. NB-IoT provides robust performance with 96–100% packet delivery ratios at −127 dBm on the tested commercial networks, and supports tens of thousands devices per cell, though mobility increases energy consumption. In the cited trials LTE-M offers highest throughput and sub 200 ms latency but fails beyond −113 dBm where NB-IoT maintains connectivity. NB-IoT emerges optimal for large scale stationary deployments, while LTE-M suits high throughput mobile applications. Full article