High Payload Research Articles

HPDH-MI: A High Payload Data Hiding Technique for Medical Images Based on AMBTC

In the realm of electronic health (eHealth) services powered by the Internet of Things (IoT), vast quantities of medical images and visualized electronic health records collected by IoT devices must be transmitted daily. Given the sensitive nature of medical information, ensuring the security of transmitted health data is paramount. To address this critical concern, this paper introduces a novel data hiding algorithm tailored for Absolute Moment Block Truncation Coding (AMBTC) in medical images, named HPDH-MI (High Payload Data Hiding for Medical Images). The proposed method embeds secret data into the AMBTC compression code inconspicuously to avoid detection by malicious users. It achieves this by first classifying AMBTC compressed blocks into four categories—flat, smooth, complex I, and complex II—using three predetermined thresholds. A 1-bit indicator, based on the proposed grouping strategy, facilitates efficient and effective block classification. A data embedding strategy is applied to each block type, focusing on block texture and taking into account the symmetric features of the pixels within the block. This approach achieves a balance between data hiding capacity, image quality, and embedding efficiency. Experimental evaluations highlight the superior performance of HPDH-MI. When tested on medical images from the Osirix database, the method achieves an average image quality of 31.22 dB, a payload capacity of 225,911 bits, and an embedding efficiency of 41.78%. These results demonstrate that the HPDH-MI method not only significantly increases the payload for concealing secret data in AMBTC compressed medical images but also maintains high image quality and embedding efficiency. This makes it a promising solution for secure data transmission in telemedicine, addressing the challenges of limited bandwidth while enhancing steganographic capabilities in eHealth applications.

Nanoparticles with "K-edge" Metals Bring "Color" in Multiscale Spectral Photon Counting X-ray Imaging.

Preclinical and clinical diagnostics depend greatly on medical imaging, which enables the identification of physiological and pathological processes in living subjects. It is often necessary to use contrast agents to complement anatomical data with functional information or to describe the disease phenotypically. Nanomaterials are used as contrast agents in many advanced bioimaging techniques and applications because of their high payload, physicochemical properties, improved sensitivity, and multimodality. Metals with k-edge energy within the X-ray bandwidth respond to photon counting and spectral X-ray imaging. This Perspective examines the progress made in the emerging area of nanoparticle-based k-edge contrast agents. These nano "k-edge" particles have been explored with spectral photon counting CT (SPCCT) for multiplexed molecular imaging, pushing the boundaries of resolution and capabilities of CT imaging. Design considerations, contrast properties, and biological behavior are discussed in detail. The key applications are highlighted by categorizing these nanomaterials based on their X-ray, k-edge energy, and biological properties, as well as their synthesis, functionalization, and characterization processes. The article delves into the transformative impact of nano "k-edge" particles on early disease detection and other biomedical applications. The review provides further insights into how the "k-edge signatures" of these nanoparticles combined with photon counting technique can be leveraged for quantitative, multicontrast imaging of diseases. We also discuss the status quo of clinically approved nanoparticles for imaging and highlight the challenges such as toxicity and clearance as well as promising clinical perspectives, providing a balanced view of the potential and limitations of these nanomaterials. Furthermore, we discuss the necessary future research efforts required to clinically translate nano "k-edge" particles as SPCCT contrast agents for early disease diagnosis and tracking.

Model-based Evaluation of Advanced Energy Management Control Strategies for Heavy-Duty Fuel Cell Powertrains

<div>In recent years, fuel cell electric vehicles (FCEV) have become a promising alternative to battery electric vehicles in medium- and heavy-duty on-road applications, which specifically require long vehicle range, high payload capacity, and fast refueling times. While FCEVs are more likely to meet these requirements, they come with their own challenges of high upfront system cost, reduced system efficiency at high load, on-board hydrogen storage system packaging, and fuel cell system (FCS) durability. To address these challenges, it is critical to ensure optimal propulsion system component sizing during the concept phase as well as ensure optimal propulsion system energy management during vehicle operation. In a previous publication, authors presented a model-based approach for system sizing and optimization of FCEV propulsion system components for a Class 8 long-haul application. In this study, the authors have evaluated and optimized multiple advanced propulsion system energy management control strategies to maximize the FCEV propulsion system efficiency during vehicle operation.</div> <div>Specifically, several energy management strategies were evaluated with the primary objective of reducing hydrogen consumption through efficient power split between FCS and high-voltage battery, while maintaining vehicle performance and sustaining battery state of charge (SOC). A 1D multi-physics-based plant model of the vehicle propulsion and thermal system was developed in GT-SUITE and validated against vehicle test data. The validated plant model was then used for model-in-loop (MiL) simulations to evaluate multiple control strategies such as rule-based, equivalent consumption minimization strategy (ECMS), and dynamic programming (DP), on real-world drive cycles.</div>

Study on the Beam Section and Joint Configuration of Payload Frame of Special Vehicle

Abstract With the increasing demand for series of special equipment, light-weight and high-payload capacity along with high mobility have become the major trends in the development of the new generation of special vehicles. The key to achieving high-payload capacity in thin-walled special vehicles lies in the successful application of annular frame beams. This paper focuses on the structural forms of typical annular frames of thin-walled special vehicle, with a particular emphasis on the study of beam cross-sections and beam joint configurations. By applying the Optistruct shape optimization method, improvements to configuration parameters were made to achieve the optimal structural form. A simulation comparison with traditional structural forms was conducted, and the results demonstrate that the new beam cross-section and beam joint configurations can significantly reduce the payload stress level and increase the payload strength while reducing thickness, meeting the high payload characteristic requirements of thin-walled special vehicles.

Enhanced reversible data hiding using difference expansion and modulus function with selective bit blocks in images

The rapid growth of Information and communication technology not only has positive impacts but also unveils opportunities for data and information security threats. In recent years, many researchers have worked on developing methods to enhance data security, particularly through data hiding techniques aimed at safeguarding communications by concealing their existence. With the same objective in mind, this study introduces a novel method for Reversible Data Hiding (RDH) based on a combination of difference expansion (DE) and a modulus function. Our method enables the embedding of 3-bit data into 2-bit Least Significant Bit (LSB) difference values of pixel pairs formed in rectangular blocks. Based on the experimental results, the payload capacity of our method can reach 0.3953 bpp with a PSNR of 53.5900 dB on common images and 0.5764 bpp with a PSNR of 52.9234 dB on medical images. Our method consistently achieves high payload capacity with good visual quality, and our method surpasses previous approaches in terms of performance, payload capacity, and visual quality.

The Problematic Issues of Unmanned Aerial Vehicle Application in Agriculture

The current rapid development of unmanned aviation is largely driven by the needs of the defense-industrial complex. In light of these events, the Russian industry has currently focused its attention on the development of unmanned aerial vehicles characterized by high payload capacity, autonomous flight range, and navigation precision. Considering the projected increase in the production rates of UAVs and the expansion of their functionalities, there is a pressing need for their active integration into various sectors of the economy, including agriculture. Despite the fact that the application of aerial agro-drones, like other aircraft, is regulated by the "Federal Rules for the Use of Airspace of the Russian Federation" (Government Resolution No. 138 dated March 11, 2010), there are currently no unified regulated approaches and requirements for the operation of unmanned aerial vehicles in agriculture. Given the growing relevance of issues related to the integration of unmanned aerial vehicles into agriculture, there is an increased need for the development of documents that regulate the use of agrochemicals for the treatment of agricultural land using these devices. The research objective if the development of a protocol for the inclusion of pesticides if the catalog approved for use through unmanned aerial vehicles.

Expansion high payload imperceptible steganography using parameterized multilayer EMD with clock-adjustment model

Steganography is a widely used technique for protecting data privacy. In such research, the desired attributes always include undetectability, a high embedding payload, and excellent image quality for the stego-image. However, achieving both high image quality and substantial embedding payloads often involves a trade-off. The development of an algorithm that can achieve this balance remains a key focus of these studies. Although progress has been made, there is still room for improvement in optimizing this balance between embedding capacity and image quality in current research. To address this challenge, in this study, we propose a novel steganographic method called the parameterized multilayer EMD with clock adjustment model (PMEMD–CAM). In the proposed method, we generalize the embedding and extraction process, offering a more efficient and flexible way to conceal data via the innovative concept of a CAM. In CAM, the sender can predefine the parameters to determine the number of pointers on a clock and the weight of each pointer. The pixel values in a block subsequently result in an initial clock status, and the corresponding secret data yield a target clock status. The main idea of CAM is to adjust the pointers in the clock with a minimum number of cost steps to achieve the target status for hiding the secret data. Subsequently, the authorized receiver can extract the secret data based on the clock model. In addition, a multilayer embedding strategy is applied to improve the embedding payload. Experimental results demonstrate that the proposed method achieves a high capacity of 4.754 bits per pixel (bpp) with a peak signal-to-noise ratio (exceeding 30 decibels (dB), outperforming existing schemes. Furthermore, our method exhibits resilience against various steganalysis attacks.

Stable Porous Organic Cage Nanocapsules for pH-Responsive Anticancer Drug Delivery for Precise Tumor Therapy.

The search for drug nanocarriers with stimuli-responsive properties and high payloads for targeted drug delivery and precision medicine is currently a focal point of biomedical research, but this endeavor still encounters various challenges. Herein, a porous organic cage (POC) is applied to paclitaxel (PTX) drug delivery for cancer therapy for the first time. Specifically, water-soluble, stable, and biocompatible POC-based nanocapsules (PTX@POC@RH40) with PTX encapsulation efficiency over 98% can be synthesized by simply grafting nonionic surfactant (Polyoxyl 40 hydrogenated castor oil, RH40) on the POC surface. These PTX@POC@RH40 nanocapsules demonstrate remarkable stability for more than a week without aggregation and exhibit pH-responsive behavior under acidic conditions (pH 5.5) and display sustained release behavior at both pH 7.4 and pH 5.5. Intravenous administration of PTX@POC@RH40 led to a 3.5-fold increase in PTX bioavailability compared with the free PTX group in rats. Moreover, in vivo mouse model experiments involving 4T1 subcutaneous breast cancer tumors revealed that PTX@POC@RH40 exhibited enhanced anticancer efficacy with minimal toxicity compared with free PTX. These findings underscore the potential of POCs as promising nanocarriers for stimuli-responsive drug delivery in therapeutic applications.

Generating Payloads of Power Monitoring Systems Compliant with Power Network Protocols Using Generative Adversarial Networks

In the network environment of power systems, payload generation is used to construct data packets, which are used to obtain data for the security management of network assets. Payloads generated by existing methods cannot satisfy the specifications of the protocols in power systems, resulting in low efficiency and information errors. In this paper, a payload generation model, LoadGAN, is proposed by using generative adversarial networks (GANs). Firstly, we find segmentation points to cut payloads into different segment sequences using sliding window schema based on Bayesian optimization. Then, we use different payload segments to train several child generators to generate corresponding parts of a whole payload. Segment sequences generated by these generators are assembled to form a whole new payload that is compliant with the specifications of the original network protocol. Experiments on the Mozi botnet dataset show that LoadGAN achieves precise payload segmentation while maintaining a high payload effectiveness of 85.5%, which is a 40% improvement compared to existing methods.

RNA Nanotechnology for Codelivering High-Payload Nucleoside Analogs to Cancer with a Synergetic Effect.

Nucleoside analogs are potent inhibitors for cancer treatment, but the main obstacles to their application in humans are their toxicity, nonspecificity, and lack of targeted delivery tools. Here, we report the use of RNA four-way junctions (4WJs) to deliver two nucleoside analogs, floxuridine (FUDR) and gemcitabine (GEM), with high payloads through routine and simple solid-state RNA synthesis and nanoparticle assembly. The design of RNA nanotechnology for the co-delivery of nucleoside analogs and the chemotherapeutic drug paclitaxel (PTX) resulted in synergistic effects and high efficacy in the treatment of Triple-Negative Breast Cancer (TNBC). The 4WJ-drug complexes were confirmed to have efficient tumor spontaneous targeting and no toxicity because the motility of RNA nanoparticles has been previously shown to enable these RNA-drug complexes to spontaneously accumulate in tumor blood vessels. The negative charge of RNA enables those RNA complexes that are not targeted to tumor vasculature to circulate in the blood and enter the urine through the kidney glomerulus, without accumulating in organs, therefore being nontoxic. Drug incorporation into RNA 4WJ can be precisely controlled with a defined loading amount, location, and ratio. The incorporation of nucleoside analogs into 4WJ only requires one step using nucleoside analogue phosphoramidites during solid-phase RNA synthesis, without the need for additional conjugation and purification processes.

Design and structural analysis of high payload C1 container

Abstract To meet the need of storing the nuclear facility dismantling wastes in Taiwan, National Atomic Research Institute (NARI) plans to develop a new type of low-level radioactive waste container based on the exterior specifications of the existing C1 container but with higher payload. Currently, the design of this container has been finished, and the associated structural analyses specified in the regulations have also been done. In this article, it summarizes what NARI has performed and what NARI plans to do for the development of this container. It includes not only the information of C1 container and its actual applications but also the design specifications and the associated numerical analyses of the container under development. Based on the analysis results, the container under development satisfies the requirements of the low-level radioactive waste storage container and the industrial package type 2. Currently, NARI has entrusted a local vendor to fabricate the prototypes of this container and perform the specified tests in the second half of 2024. The usage permit application of this container will be submitted to the authority agency in the first half of 2025. Hopefully, the usage permit could be granted in 2026.

PVA-Stabilized and Coassembled Nano/Microparticles with High Payload of Dual Phytochemicals for Enhanced Antibacterial and Targeting Effect.

The codelivery of multiple bioactive phytochemicals via nano/microparticles (NPs/MPs) represents a promising strategy for enhancing therapeutic efficacy. This study presents the development of novel poly(vinyl alcohol) (PVA)-stabilized hybrid particles designed for codelivery of palmatine hydrochloride (PAL) and glycyrrhizic acid (GL). Employing a straightforward coassembly method, we synthesized dual-drug particles achieving a high payload capacity of over 70%. The particles were characterized as uniform in size, within the nano/micron range, and exhibited a ζ-potential of -5.0 mV. The incorporation of PVA not only stabilized the particles but also refined the aggregation process, resulting in more uniform and finer particles approximately 1 μm in size. Spectral analysis and molecular dynamics simulations verified the presence of π-π stacking and hydrogen bonding between PAL and GL within the particles. In vitro antibacterial assays indicated that the hybrid particles had a lower minimum inhibitory concentration against Escherichia coli and Multidrug-Resistant Staphylococcus aureus than those of the pure drugs. In vivo biodistribution study in rats revealed that the PVA-stabilized particles revealed enhanced targeting to the liver, lung, and heart, demonstrating improved tissue selectivity compared with the solution group. In summary, the PVA-stabilized hybrid NPs/MPs represent an innovative and efficient platform for codelivery of multidrugs. These findings highlight the promise of coassembled particles for high loading, enhanced bioactivity, and targeted delivery, making them a strong candidate for future clinical applications.

Development of a bionic hexapod robot with adaptive gait and clearance for enhanced agricultural field scouting.

High agility, maneuverability, and payload capacity, combined with small footprints, make legged robots well-suited for precision agriculture applications. In this study, we introduce a novel bionic hexapod robot designed for agricultural applications to address the limitations of traditional wheeled and aerial robots. The robot features a terrain-adaptive gait and adjustable clearance to ensure stability and robustness over various terrains and obstacles. Equipped with a high-precision Inertial Measurement Unit (IMU), the robot is able to monitor its attitude in real time to maintain balance. To enhance obstacle detection and self-navigation capabilities, we have designed an advanced version of the robot equipped with an optional advanced sensing system. This advanced version includes LiDAR, stereo cameras, and distance sensors to enable obstacle detection and self-navigation capabilities. We have tested the standard version of the robot under different ground conditions, including hard concrete floors, rugged grass, slopes, and uneven field with obstacles. The robot maintains good stability with pitch angle fluctuations ranging from -11.5° to 8.6° in all conditions and can walk on slopes with gradients up to 17°. These trials demonstrated the robot's adaptability to complex field environments and validated its ability to maintain stability and efficiency. In addition, the terrain-adaptive algorithm is more energy efficient than traditional obstacle avoidance algorithms, reducing energy consumption by 14.4% for each obstacle crossed. Combined with its flexible and lightweight design, our robot shows significant potential in improving agricultural practices by increasing efficiency, lowering labor costs, and enhancing sustainability. In our future work, we will further develop the robot's energy efficiency, durability in various environmental conditions, and compatibility with different crops and farming methods.

Active Disturbance Rejection Control of Hydraulic Quadruped Robots Rotary Joints for Improved Impact Resistance

Hydraulic actuated quadruped robots have bright application prospects and significant research values in unmanned area investigation, disaster rescue and other scenarios, due to the advantages of high payload and high power to weight ratio. Among these fields, inevitable collision of robots may occur when contact with unknown objects, step on empty objects, or collapse, all of which have an impact on the working hydraulic system. To overcome the unknown external disturbances, this paper proposes an active disturbance rejection control (ADRC) strategy of double vane hydraulic rotary actuators for the hip joints of the quadruped robots. Considering the order of the valve-controlled actuator model, a three-stage tracking differentiator, a four-stage extended state observer, and a state error feedback controller are designed relatively, and the extended state observer is adopted to observe and compensate the uncertainty of external load torque of the system. The effectiveness of the ADRC method is verified in simulation environment and a single joint experimental platform. Moreover, the impact experiments of the limb leg unit are carried out after introducing the proposed ADRC strategy into hip joint, the limb leg unit of quadruped robots presents better impact resistance ability.

An in situ depot for the sustained release of a TLR7/8 agonist in combination with a TGFβ inhibitor promotes anti-tumor immune responses

Cancer curing immune responses against heterogeneous solid cancers require that a coordinated immune activation is initiated in the antigen avid but immunosuppressive tumor microenvironment (TME). The plastic TME, and the poor systemic tolerability of immune activating drugs are, however, fundamental barriers to generating curative anticancer immune responses. Here, we introduce the CarboCell technology to overcome these barriers by forming an intratumoral sustained drug release depot that provides high payloads of immune stimulatory drugs selectively within the TME. The CarboCell thereby induces a hot spot for immune cell training and polarization and further drives and maintains the tumor-draining lymph nodes in an anticancer and immune activated state. Mechanistically, this transforms cancerous tissues, consequently generating systemic anticancer immunoreactivity. CarboCell can be injected through standard thin-needle technologies and has inherent imaging contrast which secure accurate intratumoral positioning. In particular, here we report the therapeutic performance for a dual-drug CarboCell providing sustained release of a Toll-like receptor 7/8 agonist and a transforming growth factor-β inhibitor in preclinical tumor models in female mice.

Hyaluronic acid-covered ferric ion-rich nanobullets with high zoledronic acid payload for breast tumor-targeted chemo/chemodynamic therapy

Due to the heterogeneity of the tumor microenvironment, the clinical efficacy of tumor treatment is not satisfied, highlighting the necessity for new strategies to tackle this issue. To effectively treat breast tumors by tumor-targeted chemo/chemodynamic therapy, herein, the Fe3+-rich MIL-88B nanobullets (MNs) covered with hyaluronic acid (HA) were fabricated as vehicles of zoledronic acid (ZA). The attained ZA@HMNs showed a high ZA payload (ca 29.6 %), outstanding colloidal stability in the serum-containing milieu, and accelerated ZA as well as Fe3+ release under weakly acidic and glutathione (GSH)-rich conditions. Also, the ZA@HMNs consumed GSH by GSH-mediated Fe3+ reduction and converted H2O2 into OH via Fenton or Fenton-like reaction with pH reduction. After being internalized by 4T1 cells upon CD44-mediated endocytosis, the ZA@HMNs depleted intracellular GSH and degraded H2O2 into OH, thus eliciting lipid peroxidation and mitochondria damage to suppress cell proliferation. Also, the ZA@HMNs remarkably killed macrophage-like RAW 264.7 cells. Importantly, the in vivo studies and ki67 and GPX4 staining of tumor sections demonstrated that the ZA@HMNs efficiently accumulated in 4T1 tumors to hinder tumor growth via ZA chemotherapy combined with OH-mediated ferroptosis. This work presents a practicable strategy to fabricate ZA@HMNs for breast tumor-targeted chemo/chemodynamic therapy with potential clinical translation.

Expanding the repertoire of Antibody Drug Conjugate (ADC) targets with improved tumor selectivity and range of potent payloads through in-silico analysis.

Antibody-Drug Conjugates (ADCs) have emerged as a promising class of targeted cancer therapeutics. Further refinements are essential to unlock their full potential, which is currently limited by a lack of validated targets and payloads. Essential aspects of developing effective ADCs involve the identification of surface antigens, ideally distinguishing target tumor cells from healthy types, uniformly expressed, accompanied by a high potency payload capable of selective targeting. In this study, we integrated transcriptomics, proteomics, immunohistochemistry and cell surface membrane datasets from Human Protein Atlas, Xenabrowser and Gene Expression Omnibus utilizing Lantern Pharma's proprietary AI platform Response Algorithm for Drug positioning and Rescue (RADR®). We used this in combination with evidence based filtering to identify ADC targets with improved tumor selectivity. Our analysis identified a set of 82 targets and a total of 290 target indication combinations for effective tumor targeting. We evaluated the impact of tumor mutations on target expression levels by querying 416 genes in the TCGA mutation database against 22 tumor subtypes. Additionally, we assembled a catalog of compounds to identify potential payloads using the NCI-Developmental Therapeutics Program. Our payload mining strategy classified 729 compounds into three subclasses based on GI50 values spanning from pM to 10 nM range, in combination with sensitivity patterns across 9 different cancer indications. Our results identified a diverse range of both targets and payloads, that can serve to facilitate multiple choices for precise ADC targeting. We propose an initial approach to identify suitable target-indication-payload combinations, serving as a valuable starting point for development of future ADC candidates.

Reversible data hiding in encrypted images based on secret sharing and hierarchical embedding

With the increasing emphasis on information security, reversible data hiding technology in encrypted images (RDH-EI) has been widely applied in cloud storage privacy protection in recent years. However, once the data hider is leaked or compromised, the current algorithm of RDH-EI will encounter the challenge of effectiveness and security. In order to tackle this issue, this paper proposes an RDH-EI scheme based on secret sharing and hierarchical embedding. First, an image secret sharing based on (4, 6)-threshold algorithm is proposed. This algorithm aims to combine image encryption and sharing processes to generate six different encrypted images with vertical correlation. Sending them in encrypted form to cloud storage is beneficial for protecting the semantics of cover image. Then, the hierarchical embedding method is suggested to attain a high embedding payload. In this approach, by analyzing the vertical correlation of adjacent pixels, we have designed three mapping rules based on multi-MSB prediction. Among them, case 1 reserves the highest embedding capacity, case 2 follows, and case 3 has no embedding space. Based on this, the paper can adaptively embed secret data. Finally, fully authorized users can extract secret data and restore the original image by decrypting four or more marked encrypted images. Experimental results indicate that our approach surpass some existing RDH-EI approaches in payload, which average payloads in the best case on the BOSSbase and BOWS-2 datasets reach 4.466 bpp and 4.152 bpp, respectively. Additionally, the proposed RDH-EI method transfers and stores image data in a distributed manner, which helps prevent excessive concentration of power by data hiders and misuse of data. Compared to traditional end-to-end RDH-EI schemes, the proposed approach offers higher security.

High‐Load Core@Shell Nanocarriers with Irinotecan and 5‐Fluorouracil for Combination Chemotherapy in Colorectal Cancer

Colorectal cancer (CRC) is the third most common cancer type and second leading cause of cancer‐related deaths worldwide, requiring novel drug‐delivery concepts. ITC@ZrO(TocP)/ZrO(FdUMP) core@shell nanocarriers (designated ITC‐FdUMP‐NC) with the clinically relevant chemotherapeutics irinotecan (ITC) and fluoro‐2′‐deoxyuridine‐5′‐phosphate (FdUMP) (active derivative of 5′‐fluorouracil/5‐FU) are a new type of nanocarrier with high drug payload (22 wt% of lipophilic ITC: particle core; 10 wt% of hydrophilic FdUMP: particle shell). The nanocarriers are tested in different CRC cell lines, a normal cell line, and rectal cancer patient‐derived organoids (PDOs). Fluorescence‐labeled nanocarriers show efficient uptake by all CRC cells and allow to distinctly track the intracellular trafficking toward endolysosomal compartments. Although free chemotherapeutic drugs exhibit a greater potency in 2D cell cultures, ITC‐FdUMP‐NC demonstrate equivalent cytotoxic efficacies as the freely dissolved drugs in the more complex 3D rectal cancer PDOs. The sustained drug‐release profile of the nanocarriers contrasts favorably with conventional free drugs, potentially enhancing the therapeutic outcome in vivo. With a chemotherapeutic cocktail comparable to the clinically applied FOLFIRI (ITC + 5‐FU), the ITC‐FdUMP‐NC represent a novel type of nanocarrier with high anti‐tumor effect and high drug payload, offering a promising strategy to circumvent chemoresistance and to improve therapy efficacy in vivo with less side effects.

Preparation and characterization of oregano essential oil microcapsules by gelatin/polysaccharide composite coagulation method

Complex cohesions were formed through electrostatic interactions between gelatin (GE) and gum arabic, sodium carboxymethyl cellulose, pectin, and sodium alginate (SA). Of them, GE and SA served as an ideal wall material for encapsulating oregano essential oil (OEO). Applying the composite coalescence method, we here generated unique encapsulated OEO microcapsules (EOMs) by using GE–SA as the microcapsule wall material and OEO as the core material. At a concentration of 1 % (w/v), a core-to-wall ratio of 1:2, a recoalescence reaction temperature of 45 °C, and an emulsifier concentration of 5 % (w/w), EOMs exhibited excellent performance. Under the optimal conditions, the prepared EOMs (average particle size: 78.389 μm) had a homogeneous and complete spherical structure. Freeze-dried EOMs had a high encapsulation efficiency (71.20 %) and payload (56.08 %). Fourier transform infrared spectroscopy unveiled the presence of electrostatic interactions between GE and SA. The OEO in the EOMs had higher thermal stability and more stable antioxidant properties than the free OEO. Furthermore, in aqueous, acidic, oily, and alcoholic environments, EOMs exhibited some degree of slow-release ability. Additionally, EOMs exhibited strong antibacterial properties, with effective inhibition of Escherichia coli (E. coil), Staphylococcus aureus (S. aureus), and Curvularia lunata (C. lunata). Among them, the strongest inhibitory effect was on C. lunata. In summary, microcapsules prepared using GE–SA as a wall material had effectively improved OEO degradation-protecting, which enhanced the stability of OEO and controlled its antioxidant properties. Meanwhile, the microcapsules exhibited excellent antibacterial properties. This system exerted considerable potential in protecting the stability of essential oils and realizing slow release.