Generation of Recombinant Rotaviruses Expressing Human Norovirus Capsid Proteins.

Rotavirus, a segmented double-stranded RNA virus of the Reoviridae family, is a primary cause of acute gastroenteritis in young children. In countries where rotavirus vaccines are widely used, norovirus (NoV) has emerged as the major cause of acute gastroenteritis. Towards the goal of creating a combined rotavirus-NoV vaccine, we explored the possibility of generating recombinant rotaviruses (rRVs) expressing all or portions of the NoV GII.4 VP1 capsid protein. This was accomplished by replacing the segment 7 NSP3 open reading frame with a cassette encoding, sequentially, NSP3, a 2A stop-restart translation element, and all or portions (P, P2) of NoV VP1. In addition to successfully recovering rRVs with modified SA11 segment 7 RNAs encoding NoV capsid proteins, analogous rRVs were recovered through modification of the segment 7 RNA of the RIX4414 vaccine strain. An immunoblot assay confirmed that rRVs expressed NoV capsid proteins as independent products. Moreover, VP1 expressed by rRVs underwent dimerization and was recognized by conformational-dependent anti-VP1 antibodies. Serially passaged rRVs that expressed the NoV P and P2 were genetically stable, retaining additional sequences of up to 1.1 kbp without change. However, serially passaged rRVs containing the longer 1.6-kb VP1 sequence were less stable and gave rise to virus populations with segment 7 RNAs lacking VP1 coding sequences. Together, these studies suggest that it may be possible to develop combined rotavirus-NoV vaccines using modified segment 7 RNA to express NoV P or P2. In contrast, development of potential rotavirus-NoV vaccines expressing NoV VP1 will need additional efforts to improve genetic stability. IMPORTANCE Rotavirus (RV) and norovirus (NoV) are the two most important causes of acute viral gastroenteritis (AGE) in infants and young children. While the incidence of RV AGE has been brought under control in many countries through the introduction of universal mass vaccination with live attenuated RV vaccines, similar highly effective NoV vaccines are not available. To pursue the development of a combined RV-NoV vaccine, we examined the potential of using RV as an expression vector of all or portions of the NoV capsid protein VP1. Our results showed that by replacing the NSP3 open reading frame in RV genome segment 7 RNA with a coding cassette for NSP3, a 2A stop-restart translation element, and VP1, recombinant RVs can be generated that express NoV capsid proteins. These findings raise the possibility of developing new generations of RV-based combination vaccines that provide protection against a second enteric pathogen, such as NoV.

Adapting Single-Image Super-Resolution Models to Video Super-Resolution: A Plug-and-Play Approach.

The quality of videos varies due to the different capabilities of sensors. Video super-resolution (VSR) is a technology that improves the quality of captured video. However, the development of a VSR model is very costly. In this paper, we present a novel approach for adapting single-image super-resolution (SISR) models to the VSR task. To achieve this, we first summarize a common architecture of SISR models and perform a formal analysis of adaptation. Then, we propose an adaptation method that incorporates a plug-and-play temporal feature extraction module into existing SISR models. The proposed temporal feature extraction module consists of three submodules: offset estimation, spatial aggregation, and temporal aggregation. In the spatial aggregation submodule, the features obtained from the SISR model are aligned to the center frame based on the offset estimation results. The aligned features are fused in the temporal aggregation submodule. Finally, the fused temporal feature is fed to the SISR model for reconstruction. To evaluate the effectiveness of our method, we adapt five representative SISR models and evaluate these models on two popular benchmarks. The experiment results show the proposed method is effective on different SISR models. In particular, on the Vid4 benchmark, the VSR-adapted models achieve at least 1.26 dB and 0.067 improvement over the original SISR models in terms of PSNR and SSIM metrics, respectively. Additionally, these VSR-adapted models achieve better performance than the state-of-the-art VSR models.

Super-resolution image reconstruction from sparsity regularization and deep residual-learned priors.

BACKGROUND: Computed tomography (CT) plays an important role in the field of non-destructive testing. However, conventional CT images often have blurred edge and unclear texture, which is not conducive to the follow-up medical diagnosis and industrial testing work. OBJECTIVE: This study aims to generate high-resolution CT images using a new CT super-resolution reconstruction method combining with the sparsity regularization and deep learning prior. METHODS: The new method reconstructs CT images through a reconstruction model incorporating image gradient L0-norm minimization and deep image priors using a plug-and-play super-resolution framework. The deep learning priors are learned from a deep residual network and then plugged into the proposed new framework, and alternating direction method of multipliers is utilized to optimize the iterative solution of the model. RESULTS: The simulation data analysis results show that the new method improves the signal-to-noise ratio (PSNR) by 7% and the modulation transfer function (MTF) curves show that the value of MTF50 increases by 0.02 factors compared with the result of deep plug-and-play super-resolution. Additionally, the real CT image data analysis results show that the new method improves the PSNR by 5.1% and MTF50 by 0.11 factors. CONCLUSION: Both simulation and real data experiments prove that the proposed new CT super-resolution method using deep learning priors can reconstruct CT images with lower noise and better detail recovery. This method is flexible, effective and extensive for low-resolution CT image super-resolution.

A silent gradient axis for soundless spatial encoding to enable fast and quiet brain imaging.

PURPOSE: A novel silent imaging method is proposed that combines a gradient insert oscillating at the inaudible frequency 20 kHz with slew rate-limited gradient waveforms to form a silent gradient axis that enable quiet and fast imaging. METHODS: The gradient insert consisted of a plug-and-play (45 kg) single axis z-gradient, which operated as an additional fourth gradient axis. This insert was made resonant using capacitors and combined with an audio amplifier to allow for operation at 20 kHz. The gradient field was characterized using field measurements and the physiological effects of operating a gradient field at 20 kHz were explored using peripheral nerve stimulation experiments, tissue heating simulations and sound measurements. The imaging sequence consisted of a modified gradient-echo sequence which fills k-space in readout lanes with a width proportional to the oscillating gradient amplitude. The feasibility of the method was demonstrated in-vivo using 2D and 3D gradient echo (GRE) sequences which were reconstructed using a conjugate-gradient SENSE reconstruction. RESULTS: Field measurements yielded a maximum gradient amplitude and slew rate of 40.8 mT/m and 5178T/m/s at 20 kHz. Physiological effects such as peripheral nerve stimulation and tissue heating were found not to be limiting at this amplitude and slew rate. For a 3D GRE sequence, a maximum sound level of 85 db(A) was measured during scanning. Imaging experiments using the silent gradient axis produced artifact free images while also featuring a 5.3-fold shorter scan time than a fully sampled acquisition. CONCLUSION: A silent gradient axis provides a novel pathway to fast and quiet brain imaging.

A Formal Performance Evaluation Method for Customised Plug-and-Play Manufacturing Systems Using Coloured Petri Nets.

Recent technological advancements and the evolution of industrial manufacturing paradigms have substantially increased the complexity of product-specific production systems. To reduce the time cost of modelling and verification and to enhance the degree of uniformity in the modelling process of system components, this article presents a componentised framework for domain modelling and performance analysis based on the concept of "multi-granularity and multi-view" for a production line of personalised and customised products, for plug-and-play manufacturing processes to involving a large number of model input parameters. The coloured Petri net tool is utilised as a simulation tool for mapping domain models to computational models for simulation and performance evaluation. This paper presents a method for setting the input parameters of a production system when using WIP, through-put and cycle time as metrics. The results of the performance analysis demonstrate the applicability of the proposed framework and provide direction for the production line's layout design and scheduling strategy.

A Plug-and-Play Solution for Smart Transducers in Industrial Applications Based on IEEE 1451 and IEC 61499 Standards.

In a cyberphysical production system, the connectivity between the physical entities of a production system with the digital component that controls and monitors that system takes fundamental importance. This connectivity has been increasing from the transducers' side, through gathering new functionalities and operating increasingly independently, taking the role of smart transducers, and from the applications' side, by being developed in a distributed and decentralized paradigm. This work presents a plug-and-play solution capable of integrating smart transducers compliant with the IEEE 1451 standard in industrial applications based on the IEC 61499 standard. For this, we implemented the NCAP module of the smart transducer defined in IEEE 1451, which, when integrated with 4diac IDE and DINASORE (development and execution tools compliant with IEC 61499), enabled a solution that presented automatically the smart sensors and actuators in the IDE application and embedded their functionalities (access to data and processing functions) in the runtime environment. In this way, a complete plug-and-play solution was presented from the connection of the transducer to the network until its integration into the application.

Expression of Separate Heterologous Proteins from the Rotavirus NSP3 Genome Segment Using a Translational 2A Stop-Restart Element.

The segmented 18.5-kbp dsRNA genome of rotavirus expresses 6 structural and 6 nonstructural proteins. We investigated the possibility of using the recently developed plasmid-based rotavirus reverse genetics (RG) system to generate recombinant viruses that express a separate heterologous protein in addition to the 12 viral proteins. To address this, we replaced the NSP3 open reading frame (ORF) of the segment 7 (pT7/NSP3) transcription vector used in the RG system with an ORF encoding NSP3 fused to a fluorescent reporter protein (i.e., UnaG, mRuby, mKate, or TagBFP). Inserted at the fusion junction was a teschovirus translational 2A stop-restart element designed to direct the separate expression of NSP3 and the fluorescent protein. Recombinant rotaviruses made with the modified pT7/NSP3 vectors were well growing and generally genetically stable, and they expressed NSP3 and a separate fluorescent protein detectable by live cell imaging. NSP3 made by the recombinant viruses was functional, inducing nuclear accumulation of cellular poly(A)-binding protein. Further modification of the NSP3 ORF showed that it was possible to generate recombinant viruses encoding 2 heterologous proteins (mRuby and UnaG) in addition to NSP3. Our results demonstrate that, through modification of segment 7, the rotavirus genome can be increased in size to at least 19.8 kbp and can be used to produce recombinant rotaviruses expressing a full complement of viral proteins and multiple heterologous proteins. The generation of recombinant rotaviruses expressing fluorescent proteins will be valuable for the study of rotavirus replication and pathogenesis by live cell imagining and suggest that rotaviruses will prove useful as expression vectors.IMPORTANCE Rotaviruses are a major cause of severe gastroenteritis in infants and young children. Recently, a highly efficient reverse genetics system was developed that allows genetic manipulation of the rotavirus segmented double-stranded RNA genome. Using the reverse genetics system, we show that it is possible to modify one of the rotavirus genome segments (segment 7) such that virus gains the capacity to express a separate heterologous protein in addition to the full complement of viral proteins. Through this approach, we have generated wild-type-like rotaviruses that express various fluorescent reporter proteins, including UnaG (green), mRuby (far red), mKate (red), and TagBFP (blue). Such strains will be of value in probing rotavirus biology and pathogenesis by live cell imagining techniques. Notably, our work indicates that the rotavirus genome is remarkably flexible and able to accommodate significant amounts of heterologous RNA sequence, raising the possibility of using the virus as a vaccine expression vector.

A plug-and-play, lightweight, single-axis gradient insert design for increasing spatiotemporal resolution in echo planar imaging-based brain imaging.

The goal of this study was to introduce and evaluate the performance of a lightweight, high-performance, single-axis (z-axis) gradient insert design primarily intended for high-resolution functional magnetic resonance imaging, and aimed at providing both ease of use and a boost in spatiotemporal resolution. The optimal winding positions of the coil were obtained using a genetic algorithm with a cost function that balanced gradient performance (minimum 0.30 mT/m/A) and field linearity (≥16 cm linear region). These parameters were verified using field distribution measurements by B0 -mapping. The correction of geometrical distortions was performed using theoretical field distribution of the coil. Simulations and measurements were performed to investigate the echo planar imaging echo-spacing reduction due to the improved gradient performance. The resulting coil featured a 16-cm linear region, a weight of 45 kg, an installation time of 15 min, and a maximum gradient strength and slew rate of 200 mT/m and 1300 T/m/s, respectively, when paired with a commercially available gradient amplifier (940 V/630 A). The field distribution measurements matched the theoretically expected field. By utilizing the theoretical field distribution, geometrical distortions were corrected to within 6% of the whole-body gradient reference image in the target region. Compared with a whole-body gradient set, a maximum reduction in echo-spacing of a factor of 2.3 was found, translating to a 344 µs echo-spacing, for a field of view of 192 mm, a receiver bandwidth of 920 kHz and a gradient amplitude of 112 mT/m. We present a lightweight, single-axis gradient insert design that can provide high gradient performance and an increase in spatiotemporal resolution with correctable geometrical distortions while also offering a short installation time of less than 15 min and minimal system modifications.

An Automatic Embedded Device Registration Procedure Based on the OGC SensorThings API.

Sensor Web and Internet of Things (IoT) (SW-IoT) have been attracting attention from various fields. Both of them deploy networks of embedded devices to monitor physical properties (i.e., sensing capability) or to be controlled (i.e., tasking capability). One of the most important tasks to realize the SW-IoT vision is to establish an open and interoperable architecture, across the device layer, gateway layer, service layer, and application layer. To achieve this objective, many organizations and alliances propose standards for different layers. Among the standards, Open Geospatial Consortium (OGC) SensorThings API is arguably one of the most complete and flexible service standards. However, the SensorThings API only address heterogeneity issues in the service layer. Embedded devices following proprietary protocols need to join closed ecosystems and then link to the SensorThings API ecosystem via customized connectors. To address this issue, one could first follow another device layer and gateway layer open standards and then perform data model mapping with the SensorThings API. However, the data model mapping is not always straightforward as the standards were designed independently. Therefore, this research tries to propose a more direct solution to unify the entire SW-IoT architecture by extending the SensorThings API ecosystem to the gateway layer and the device layer. To be specific, this research proposes SW-IoT Plug and Play (IoT-PNP) to achieve an automatic registration procedure for embedded devices. The IoT-PNP contains three main components: (1) A description file describing device metadata and capabilities, (2) a communication protocol between the gateway layer and the device layer for establishing connections, and (3) an automatic registration procedure for both sensing and tasking capabilities. Overall, we believe the proposed solution could help achieve an open and interoperable SW-IoT end-to-end architecture based on the OGC SensorThings API.

Simultaneous Classical Communication and Quantum Key Distribution Based on Plug-and-Play Configuration with an Optical Amplifier.

We propose a simultaneous classical communication and quantum key distribution (SCCQ) protocol based on plug-and-play configuration with an optical amplifier. Such a protocol could be attractive in practice since the single plug-and-play system is taken advantage of for multiple purposes. The plug-and-play scheme waives the necessity of using two independent frequency-locked laser sources to perform coherent detection, thus the phase noise existing in our protocol is small which can be tolerated by the SCCQ protocol. To further improve its capabilities, we place an optical amplifier inside Alice's apparatus. Simulation results show that the modified protocol can well improve the secret key rate compared with the original protocol whether in asymptotic limit or finite-size regime.

A rigid, stand-off hybrid dipole, and birdcage coil array for 7 T body imaging.

PURPOSE: To design a robust and patient friendly radiofrequency coil array (8-channel transmit and 16-channel receive) for cross-sectional body imaging at 7 T, and to improve our understanding of the combination of dipole and loop like elements for ultra high field strengths. METHODS: The hybrid coil array was optimized in eletromagnetic simulations. Considered array candidates were the dipole, loop and birdcage array. The winning design was constructed and the signal-to-noise (SNR) was compared to a close fitting array at 3 T. Transmit and receive properties for different body sizes were assessed, and multi-parametric maps were acquired with the Plug-and-Play MRF method. RESULTS: The winning design consists of a dipole array for transceive combined with a birdcage array for receive only. The central SNR improved by a factor of 3 as compared to a 3 T system with a local receive array. A transmit efficiency between 2.4 and 3.9 µT/kW, a specific absorption rate efficiency of 0.25 to 0.53 µT/W/kg, and a high SNR was achieved in the center for the targeted patient population. CONCLUSION: The constructed coil array is easy to handle, safe, and patient friendly, allowing further development of abdominal imaging at 7 T. Quantitative MRI in the abdomen is possible with Plug-and-Play MRF using the designed coil array. Magn Reson Med 80:822-832, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Multipotent Systems: Combining Planning, Self-Organization, and Reconfiguration in Modular Robot Ensembles.

Mobile multirobot systems play an increasing role in many disciplines. Their capabilities can be used, e.g., to transport workpieces in industrial applications or to support operational forces in search and rescue scenarios, among many others. Depending on the respective application, the hardware design and accompanying software of mobile robots are of various forms, especially for integrating different sensors and actuators. Concerning this design, robots of one system compared to each other can be classified to exclusively be either homogeneous or heterogeneous, both resulting in different system properties. While homogeneously configured systems are known to be robust against failures through redundancy but are highly specialized for specific use cases, heterogeneously designed systems can be used for a broad range of applications but suffer from their specialization, i.e., they can only hardly compensate for the failure of one specialist. Up to now, there has been no known approach aiming to unify the benefits of both these types of system. In this paper, we present our approach to filling this gap by introducing a reference architecture for mobile robots that defines the interplay of all necessary technologies for achieving this goal. We introduce the class of robot systems implementing this architecture as multipotent systems that bring together the benefits of both system classes, enabling homogeneously designed robots to become heterogeneous specialists at runtime. When many of these robots work together, we call the structure of this cooperation an ensemble. To achieve multipotent ensembles, we also integrate reconfigurable and self-descriptive hardware (i.e., sensors and actuators) in this architecture, which can be freely combined to change the capabilities of robots at runtime. Because typically a high degree of autonomy in such systems is a prerequisite for their practical usage, we also present the integration of necessary mechanisms and algorithms for achieving the systems' multipotency. We already achieved the first results with robots implementing our approach of multipotent systems in real-world experiments as well as in a simulation environment, which we present in this paper.

Fabrication of "Plug and Play" Channels with Dual Responses by Host-Guest Interactions.

The "Plug and Play" template can be individually or successively grafted by dual-responsive molecules on the α-CD modified channels by host-guest interactions and can be peeled off by UV irradiation. The artificial channels present six kinds of responses cycling among four states responding to three environment stimuli, as light, pH, and temperature.

Universal pulses: A new concept for calibration-free parallel transmission.

PURPOSE: A calibration-free parallel transmission method is investigated to mitigate the radiofrequency (RF) field inhomogeneity problem in brain imaging at 7 Tesla (T). THEORY AND METHODS: Six volunteers were scanned to build a representative database of RF and static field maps at 7T. Small-tip-angle and inversion pulses were designed with joint kT -points trajectory optimization to work robustly on all six subjects. The returned "universal" pulses were then inserted in an MPRAGE sequence implemented on six additional volunteers without further field measurements and pulse optimizations. Similar acquisitions were performed in the circularly polarized mode and with subject-based optimizations for comparison. Performance of the different approaches was evaluated by means of image analysis and computation of the flip angle normalized root mean square errors (NRMSE). RESULTS: For both the excitation and inversion, the universal pulses (NRMSE∼11%) outperformed the circularly polarized (NRMSE∼28%) and RF shim modes (NRMSE∼20%) across all volunteers and returned slightly worse results than for subject-based optimized pulses (NRMSE∼7%). CONCLUSION: RF pulses can be designed to robustly mitigate the RF field inhomogeneity problem over a population class. This appears as a first step toward another plug and play parallel transmission solution where the pulse design can be done offline and without measuring subject-specific field maps. Magn Reson Med 77:635-643, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

A Modular Plug-And-Play Sensor System for Urban Air Pollution Monitoring: Design, Implementation and Evaluation.

Urban air pollution has caused public concern globally because it seriously affects human life. Modern monitoring systems providing pollution information with high spatio-temporal resolution have been developed to identify personal exposures. However, these systems' hardware specifications and configurations are usually fixed according to the applications. They can be inconvenient to maintain, and difficult to reconfigure and expand with respect to sensing capabilities. This paper aims at tackling these issues by adopting the proposed Modular Sensor System (MSS) architecture and Universal Sensor Interface (USI), and modular design in a sensor node. A compact MSS sensor node is implemented and evaluated. It has expandable sensor modules with plug-and-play feature and supports multiple Wireless Sensor Networks (WSNs). Evaluation results show that MSS sensor nodes can easily fit in different scenarios, adapt to reconfigurations dynamically, and detect low concentration air pollution with high energy efficiency and good data accuracy. We anticipate that the efforts on system maintenance, adaptation, and evolution can be significantly reduced when deploying the system in the field.

Design and Practical Evaluation of a Family of Lightweight Protocols for Heterogeneous Sensing through BLE Beacons in IoT Telemetry Applications.

The Internet of Things (IoT) involves a wide variety of heterogeneous technologies and resource-constrained devices that interact with each other. Due to such constraints, IoT devices usually require lightweight protocols that optimize the use of resources and energy consumption. Among the different commercial IoT devices, Bluetooth and Bluetooth Low Energy (BLE)-based beacons, which broadcast periodically certain data packets to notify their presence, have experienced a remarkable growth, specially due to their application in indoor positioning systems. This article proposes a family of protocols named Lightweight Protocol for Sensors (LP4S) that provides fast responses and enables plug-and-play mechanisms that allow IoT telemetry systems to discover new nodes and to describe and auto-register the sensors and actuators connected to a beacon. Thus, three protocols are defined depending on the beacon hardware characteristics: LP4S-6 (for resource-constraint beacons), LP4S-X (for more powerful beacons) and LP4S-J (for beacons able to run complex firmware). In order to demonstrate the capabilities of the designed protocols, the most restrictive (LP4S-6) is tested after implementing it for a telemetry application in a beacon based on Eddystone (Google's open beacon format). Thus, the beacon specification is extended in order to increase its ability to manage unlimited sensors in a telemetry system without interfering in its normal operation with Eddystone frames. The performed experiments show the feasibility of the proposed solution and its superiority, in terms of latency and energy consumption, with respect to approaches based on Generic Attribute Profile (GATT) when multiple users connect to a mote or in scenarios where latency is not a restriction, but where low-energy consumption is essential.

ROSA: Resource-Oriented Service Management Schemes for Web of Things in a Smart Home.

A Pervasive-computing-enriched smart home environment, which contains many embedded and tiny intelligent devices and sensors coordinated by service management mechanisms, is capable of anticipating intentions of occupants and providing appropriate services accordingly. Although there are a wealth of research achievements in recent years, the degree of market acceptance is still low. The main reason is that most of the devices and services in such environments depend on particular platform or technology, making it hard to develop an application by composing the devices or services. Meanwhile, the concept of Web of Things (WoT) is becoming popular recently. Based on WoT, the developers can build applications based on popular web tools or technologies. Consequently, the objective of this paper is to propose a set of novel WoT-driven plug-and-play service management schemes for a smart home called Resource-Oriented Service Administration (ROSA). We have implemented an application prototype, and experiments are performed to show the effectiveness of the proposed approach. The results of this research can be a foundation for realizing the vision of "end user programmable smart environments".

Middleware for Plug and Play Integration of Heterogeneous Sensor Resources into the Sensor Web.

The study of global phenomena requires the combination of a considerable amount of data coming from different sources, acquired by different observation platforms and managed by institutions working in different scientific fields. Merging this data to provide extensive and complete data sets to monitor the long-term, global changes of our oceans is a major challenge. The data acquisition and data archival procedures usually vary significantly depending on the acquisition platform. This lack of standardization ultimately leads to information silos, preventing the data to be effectively shared across different scientific communities. In the past years, important steps have been taken in order to improve both standardization and interoperability, such as the Open Geospatial Consortium's Sensor Web Enablement (SWE) framework. Within this framework, standardized models and interfaces to archive, access and visualize the data from heterogeneous sensor resources have been proposed. However, due to the wide variety of software and hardware architectures presented by marine sensors and marine observation platforms, there is still a lack of uniform procedures to integrate sensors into existing SWE-based data infrastructures. In this work, a framework aimed to enable sensor plug and play integration into existing SWE-based data infrastructures is presented. First, an analysis of the operations required to automatically identify, configure and operate a sensor are analysed. Then, the metadata required for these operations is structured in a standard way. Afterwards, a modular, plug and play, SWE-based acquisition chain is proposed. Finally different use cases for this framework are presented.

Home Automation System Based on Intelligent Transducer Enablers.

This paper presents a novel home automation system named HASITE (Home Automation System based on Intelligent Transducer Enablers), which has been specifically designed to identify and configure transducers easily and quickly. These features are especially useful in situations where many transducers are deployed, since their setup becomes a cumbersome task that consumes a significant amount of time and human resources. HASITE simplifies the deployment of a home automation system by using wireless networks and both self-configuration and self-registration protocols. Thanks to the application of these three elements, HASITE is able to add new transducers by just powering them up. According to the tests performed in different realistic scenarios, a transducer is ready to be used in less than 13 s. Moreover, all HASITE functionalities can be accessed through an API, which also allows for the integration of third-party systems. As an example, an Android application based on the API is presented. Remote users can use it to interact with transducers by just using a regular smartphone or a tablet.

Unveiling the Power of Cloaking Metal-Organic Framework Platforms via Supramolecular Antibody Conjugation.

Targeted drug delivery systems based on metal-organic frameworks (MOFs) have progressed tremendously since inception and are now widely applicable in diverse scientific fields. However, translating MOF agents directly to targeted drug delivery systems remains a challenge due to the biomolecular corona phenomenon. Here, we observed that supramolecular conjugation of antibodies to the surface of MOF particles (MOF-808) via electrostatic interactions and coordination bonding can reduce protein adhesion in biological environments and show stealth shields. Once antibodies are stably conjugated to particles, they were neither easily exchanged with nor covered by biomolecule proteins, which is indicative of the stealth effect. Moreover, upon conjugation of the MOF particle with specific targeted antibodies, namely, anti-CD44, human epidermal growth factor receptor 2 (HER2), and epidermal growth factor receptor (EGFR), the resulting hybrid exhibits an augmented targeting efficacy toward cancer cells overexpressing these receptors, such as HeLa, SK-BR-3, and 4T1, as evidenced by flow cytometry. The therapeutic effectiveness of the antibody-conjugated MOF (anti-M808) was further evaluated through in vivo imaging and the assessment of tumor inhibition effects using IR-780-loaded EGFR-M808 in a 4T1 tumor xenograft model employing nude mice. This study therefore provides insight into the use of supramolecular antibody conjugation as a promising method for developing MOF-based drug delivery systems.