Intrinsic Capability Research Articles

Facile fabrication of transparent slippery coatings with dual self-healing ability

Slippery surfaces are highly effective in repelling low-surface tension fluids due to their oleophobicity, anti-adhesive, and drag-reduction properties. However, it should be noted that while these surfaces show promising performance under normal conditions, they may lose their efficacy under harsh conditions, particularly in outdoor applications. In this study, we developed a transparent slippery coating with dual self-healing abilities by a 3D-grafting method. The coating can be formed on various substrates, and the coated glass is highly transparent. Additionally, the coating shows exceptional slipperiness on water and most oils, making it highly effective at repelling liquids. Moreover, the coating exhibits remarkable intrinsic and surface self-healing capabilities, enabling it to restore its slippery effect even in the presence of scratches or damage. This outstanding self-healing property results in a long-lasting, durable coating that can resist wear and tear. The exceptional slipperiness and self-healing properties of coating make them suitable for various industrial, medical, and consumer products.

Gas-solid photoelectrocatalytic CO2 reduction using solid planar photoelectrocatalytic device ITO/RGO/ITO

Photoelectric co-catalysis is a promising method for carbon dioxide (CO2) reduction due to its greater flexibility and higher reaction efficiency. However, the development of gas-phase photoelectrocatalysis is still in progress. Additionally, there is limited information available regarding the intrinsic photocatalytic capability of reduced graphene oxide (RGO) and its “structure-activity” relationship. In this study, solid planar photoelectrocatalytic (PEC) devices ITO/RGO/ITO were designed to enable gas-solid PEC CO2 reduction. The device consists of two strip electrodes functioning as the cathode and anode, biased to create a horizontal electric field that facilitates the separation of photogenerated electron-hole pairs. RGO-130 (heat treatment at 130 °C) presented the best PEC CO2 reduction efficiency, 2.2 times higher than photocatalysis under visible light irradiation. This enhancement can be attributed to its moderate oxygen content (48.8%), 001 crystal face and “layer upon layer” structure, all of which facilitate the separation and transfer of photogenerated carriers. Therefore, RGO is capable of acting as a stand-alone catalyst for the photocatalytic CO2 reduction, and the appropriate design of RGO in surface and structure can improve its activity. This work provides a new perspective on research and application of PEC CO2 reduction, in view of its environmentally safe and conducive to large-scale applications.

Using a Xenogeneic Acellular Dermal Matrix Membrane to Enhance the Reparability of Bone Marrow Mesenchymal Stem Cells for Cartilage Injury.

Due to its avascular organization and low mitotic ability, articular cartilage possesses limited intrinsic regenerative capabilities. The aim of this study is to achieve one-step cartilage repair in situ via combining bone marrow stem cells (BMSCs) with a xenogeneic Acellular dermal matrix (ADM) membrane. The ADM membranes were harvested from Sprague-Dawley (SD) rats through standard decellularization procedures. The characterization of the scaffolds was measured, including the morphology and physical properties of the ADM membrane. The in vitro experiments included the cell distribution, chondrogenic matrix quantification, and viability evaluation of the scaffolds. Adult male New Zealand white rabbits were used for the in vivo evaluation. Isolated microfracture was performed in the control (MF group) in the left knee and the tested ADM group was included as an experimental group when an ADM scaffold was implanted through matching with the defect after microfracture in the right knee. At 6, 12, and 24 weeks post-surgery, the rabbits were sacrificed for further research. The ADM could adsorb water and had excellent porosity. The bone marrow stem cells (BMSCs) grew well when seeded on the ADM scaffold, demonstrating a characteristic spindle-shaped morphology. The ADM group exhibited an excellent proliferative capacity as well as the cartilaginous matrix and collagen production of the BMSCs. In the rabbit model, the ADM group showed earlier filling, more hyaline-like neo-tissue formation, and better interfacial integration between the defects and normal cartilage compared with the microfracture (MF) group at 6, 12, and 24 weeks post-surgery. In addition, neither intra-articular inflammation nor a rejection reaction was observed after the implantation of the ADM scaffold. This study provides a promising biomaterial-based strategy for cartilage repair and is worth further investigation in large animal models.

Cancer Bioenergetics and Tumor Microenvironments-Enhancing Chemotherapeutics and Targeting Resistant Niches through Nanosystems.

Cancer is an impending bottleneck in the advanced scientific workflow to achieve diagnostic, prognostic, and therapeutic success. Most cancers are refractory to conventional diagnostic and chemotherapeutics due to their limited targetability, specificity, solubility, and side effects. The inherent ability of each cancer to evolve through various genetic and epigenetic transformations and metabolic reprogramming underlies therapeutic limitations. Though tumor microenvironments (TMEs) are quite well understood in some cancers, each microenvironment differs from the other in internal perturbations and metabolic skew thereby impeding the development of appropriate diagnostics, drugs, vaccines, and therapies. Cancer associated bioenergetics modulations regulate TME, angiogenesis, immune evasion, generation of resistant niches and tumor progression, and a thorough understanding is crucial to the development of metabolic therapies. However, this remains a missing element in cancer theranostics, necessitating the development of modalities that can be adapted for targetability, diagnostics and therapeutics. In this challenging scenario, nanomaterials are modular platforms for understanding TME and achieving successful theranostics. Several nanoscale particles have been successfully researched in animal models, quite a few have reached clinical trials, and some have achieved clinical success. Nanoparticles exhibit an intrinsic capability to interact with diverse biomolecules and modulate their functions. Furthermore, nanoparticles can be functionalized with receptors, modulators, and drugs to facilitate specific targeting with reduced toxicity. This review discusses the current understanding of different theranostic nanosystems, their synthesis, functionalization, and targetability for therapeutic modulation of bioenergetics, and metabolic reprogramming of the cancer microenvironment. We highlight the potential of nanosystems for enhanced chemotherapeutic success emphasizing the questions that remain unanswered.

Theoretical isotherm equation for adsorption-induced structural transition on flexible metal–organic frameworks

Flexible metal-organic frameworks (MOFs) exhibit an adsorption-induced structural transition known as "gate opening" or "breathing," resulting in an S-shaped adsorption isotherm. This unique feature of flexible MOFs offers significant advantages, such as a large working capacity, high selectivity, and intrinsic thermal management capability, positioning them as crucial candidates for revolutionizing adsorption separation processes. Therefore, the interest in the industrial applications of flexible MOFs is increasing, and the adsorption engineering for flexible MOFs is becoming important. However, despite the establishment of the theoretical background for adsorption-induced structural transitions, no theoretical equation is available to describe S-shaped adsorption isotherms of flexible MOFs. Researchers rely on various empirical equations for process simulations that can lead to unreliable outcomes or may overlook insights into improving material performance owing to parameters without physical meaning. In this study, we derive a theoretical equation based on statistical mechanics that could be a standard for the structural transition type adsorption isotherms, as the Langmuir equation represents type I isotherms. The versatility of the derived equation is shown through four examples of flexible MOFs that exhibit gate opening and breathing. The consistency of the formula with existing theories, including the osmotic free energy analysis and intrinsic thermal management capabilities, is also discussed. The developed theoretical equation may lead to more reliable and insightful outcomes in adsorption separation processes, further advancing the direction of industrial applications of flexible MOFs.

A 64k pixel CMOS-DEPFET module for the soft X-rays DSSC imager operating at MHz-frame rates

The 64k pixel DEPFET module is the key sensitive component of the DEPFET Sensor with Signal Compression (DSSC), a large area 2D hybrid detector for capturing and measuring soft X-rays at the European XFEL. The final 1-megapixel camera has to detect photons with energies between 250,text{eV} and 6,text{keV}, and must provide a peak frame rate of 4.5,text{MHz} to cope with the unique bunch structure of the European XFEL. This work summarizes the functionalities and properties of the first modules assembled with full-format CMOS-DEPFET arrays, featuring 512,times ,128 hexagonally-shaped pixels with a side length of 136 μm. The pixel sensors utilize the DEPFET technology to realize an extremely low input capacitance for excellent energy resolution and, at the same time, an intrinsic capability of signal compression without any gain switching. Each pixel of the readout ASIC includes a DEPFET-bias current cancellation circuitry, a trapezoidal-shaping filter, a 9-bit ADC and a 800-word long digital memory. The trimming, calibration and final characterization were performed in a laboratory test-bench at DESY. All detector features are assessed at 18,^{circ }text{C}. An outstanding equivalent noise charge of 9.8e−rms is achieved at 1.1-MHz frame rate and gain of 26.8 Analog-to-Digital Unit per keV (,text {ADU}/text{keV}). At 4.5,text{MHz} and 3.1,,text {ADU}/text{keV}, a noise of 25.5 e−rms and a dynamic range of 26,text{k}text {e}^{-} are obtained. The highest dynamic range of 1.345,text{M}text {e}^{-} is reached at 2.25,text{MHz} and 1.6,text {ADU}/text{keV}. These values can fulfill the specification of the DSSC project.

Tunable organic active neural probe enabling near-sensor signal processing.

Neural recording systems have significantly progressed to provide an advanced understanding and treatment for neurological diseases. Flexible transistor-based active neural probes exhibit great potential in electrophysiology applications due to their intrinsic amplification capability and tissue-compliant nature. However, most current active neural probes exhibit bulky back-end connectivity since the output is current, and the development of an integrated circuit for voltage output is crucial for near-sensor signal processing at the abiotic/biotic interface. Here, wepresent inkjet-printed organic voltage amplifiers by monolithically integrating organic electrochemical transistors and thin-film polymer resistors on a single, highly flexible substrate for in vivo brain activity recording. Additive inkjet printing enables the seamless integration of multiple active and passive components on the somatosensory cortex, leading to significant noise reduction over the externally connected typical configuration. It also facilitates fine-tuning of the voltage amplification and frequency properties. Wevalidate the organic voltage amplifiers as electrocorticography devices in a rat in vivo model, showing their ability to record local field potentials in an experimental model of spontaneous and epileptiform activity. Ourresults bring organic active neural probes to the forefront in applications where efficient sensory data processing is performed at sensor endpoints. This article is protected by copyright. All rights reserved.

Religious dialogue and the challenges of sustainable development (The problems of poverty and hunger as a model)

Purpose: The research aims to evaluate the prevailing concept of development, and it also aims to clarify the components of religion in achieving sustainable development goals in general, and the problem of poverty and hunger in particular. Findings: The research concluded that religions have an original and comprehensive view of development, that they have intrinsic capabilities and a strong civilizational experience in facing the dilemma of poverty, and that the way to activate this is cooperation through the means of development dialogue. Keywords: religion -Sustainable development, interfaith dialogue, poverty, hunger.

Nonviral technologies can pave the way for CAR-NK cell therapy.

Natural killer cells are a promising platform for cancer immunotherapy. Natural killer cells have high intrinsic killing capability, and the insertion of a chimeric antigen receptor can further enhance their antitumor potential. In first-in-human trials, chimeric antigen receptor-natural killer cells demonstrated strong clinical activity without therapy-induced side effects. The applicability of natural killer cells as an "off-the-shelf" product makes them highly attractive for gene-engineered cell therapies. Traditionally, viral transduction has been used for gene editing; however, the use of viral vectors remains a safety concern and is associated with high costs and regulatory requirements. Here, we review the current landscape of nonviral approaches for chimeric antigen receptor-natural killer cell generation. This includes transfection of vector particles and electroporation of mRNA and DNA vectors, resulting in transient modification and chimeric antigen receptor expression. In addition, using nonviral transposon technologies, natural killer cells can be stably modified ensuring long-lasting chimeric antigen receptor expression. Finally, we discuss CRISPR/Cas9 tools to edit key genes for natural killer cell functionality.

Recent development in multizonal scaffolds for osteochondral regeneration.

Osteochondral (OC) repair is an extremely challenging topic due to the complex biphasic structure and poor intrinsic regenerative capability of natural osteochondral tissue. In contrast to the current surgical approaches which yield only short-term relief of symptoms, tissue engineering strategy has been shown more promising outcomes in treating OC defects since its emergence in the 1990s. In particular, the use of multizonal scaffolds (MZSs) that mimic the gradient transitions, from cartilage surface to the subchondral bone with either continuous or discontinuous compositions, structures, and properties of natural OC tissue, has been gaining momentum in recent years. Scrutinizing the latest developments in the field, this review offers a comprehensive summary of recent advances, current hurdles, and future perspectives of OC repair, particularly the use of MZSs including bilayered, trilayered, multilayered, and gradient scaffolds, by bringing together onerous demands of architecture designs, material selections, manufacturing techniques as well as the choices of growth factors and cells, each of which possesses its unique challenges and opportunities.

Thermoresponsive M1 macrophage-derived hybrid nanovesicles for improved in vivo tumor targeting

Despite the efforts and advances done in the last few decades, cancer still remains one of the main leading causes of death worldwide. Nanomedicine and in particular extracellular vesicles are one of the most potent tools to improve the effectiveness of anticancer therapies. In these attempts, the aim of this work is to realize a hybrid nanosystem through the fusion between the M1 macrophages-derived extracellular vesicles (EVs-M1) and thermoresponsive liposomes, in order to obtain a drug delivery system able to exploit the intrinsic tumor targeting capability of immune cells reflected on EVs and thermoresponsiveness of synthetic nanovesicles. The obtained nanocarrier has been physicochemically characterized, and the hybridization process has been validated by cytofluorimetric analysis, while the thermoresponsiveness was in vitro confirmed through the use of a fluorescent probe. Tumor targeting features of hybrid nanovesicles were in vivo investigated on melanoma-induced mice model monitoring the accumulation in tumor site through live imaging and confirmed by cytofluorimetric analysis, showing higher targeting properties of hybrid nanosystem compared to both liposomes and native EVs. These promising results confirmed the ability of this nanosystem to combine the advantages of both nanotechnologies, also highlighting their potential use as effective and safe personalized anticancer nanomedicine.Graphical

Cluster-Guided Contrastive Graph Clustering Network

Benefiting from the intrinsic supervision information exploitation capability, contrastive learning has achieved promising performance in the field of deep graph clustering recently. However, we observe that two drawbacks of the positive and negative sample construction mechanisms limit the performance of existing algorithms from further improvement. 1) The quality of positive samples heavily depends on the carefully designed data augmentations, while inappropriate data augmentations would easily lead to the semantic drift and indiscriminative positive samples. 2) The constructed negative samples are not reliable for ignoring important clustering information. To solve these problems, we propose a Cluster-guided Contrastive deep Graph Clustering network (CCGC) by mining the intrinsic supervision information in the high-confidence clustering results. Specifically, instead of conducting complex node or edge perturbation, we construct two views of the graph by designing special Siamese encoders whose weights are not shared between the sibling sub-networks. Then, guided by the high-confidence clustering information, we carefully select and construct the positive samples from the same high-confidence cluster in two views. Moreover, to construct semantic meaningful negative sample pairs, we regard the centers of different high-confidence clusters as negative samples, thus improving the discriminative capability and reliability of the constructed sample pairs. Lastly, we design an objective function to pull close the samples from the same cluster while pushing away those from other clusters by maximizing and minimizing the cross-view cosine similarity between positive and negative samples. Extensive experimental results on six datasets demonstrate the effectiveness of CCGC compared with the existing state-of-the-art algorithms. The code of CCGC is available at https://github.com/xihongyang1999/CCGC on Github.

Stress and damage-sensing capabilities of asphalt mixtures incorporating graphene nanoplatelets

The development of innovative sensing technologies is essential for implementing smart road pavement monitoring systems. The design of asphalt-based materials with intrinsic self-sensing capabilities represents a promising solution in that regard. Despite this, this technology is still not mature and further efforts should be made for its development. With this aim, the present paper evaluates the self-sensing response of asphalt mixtures incorporating graphene nanoplatelets (GNPs), and proposes the use of a digital signal processing technique, based on wavelet transform, for the analysis of the electrical signals generated by the mixture. The results showed that the mixtures exhibited both stress and damage sensing functions, albeit some issues related to the dispersion of GNPs should be further investigated. In addition, wavelet transform analysis seems to be able to capture insightful information about the electrical response of the mixture, as well as its structural condition, useful for traffic and pavement health monitoring purposes.

Non-Line-of-Sight Detection Based on Neuromorphic Time-of-Flight Sensing

Non-line-of-sight (NLOS) detection and ranging aim to identify hidden objects by sensing indirect light reflections. Although numerous computational methods have been proposed for NLOS detection and imaging, the post-signal processing required by peripheral circuits remains complex. One possible solution for simplifying NLOS detection and ranging involves the use of neuromorphic devices, such as memristors, which have intrinsic resistive-switching capabilities and can store spatiotemporal information. In this study, we employed the memristive spike-timing-dependent plasticity learning rule to program the time-of-flight (ToF) depth information directly into a memristor medium. By coupling the transmitted signal from the source with the photocurrent from the target object into a single memristor unit, we were able to induce a tunable programming pulse based on the time interval between the two signals that were superimposed. Here, this neuromorphic ToF principle is employed to detect and range NLOS objects without requiring complex peripheral circuitry to process raw signals. We experimentally demonstrated the effectiveness of the neuromorphic ToF principle by integrating a HfO2 memristor and an avalanche photodiode to detect NLOS objects in multiple directions. This technology has potential applications in various fields, such as automotive navigation, machine learning, and biomedical engineering.

Sodium-mediated plateau potentials in an identified decisional neuron contribute to feeding-related motor pattern genesis in Aplysia.

Motivated behaviors such as feeding depend on the functional properties of decision neurons to provide the flexibility required for behavioral adaptation. Here, we analyzed the ionic basis of the endogenous membrane properties of an identified decision neuron (B63) that drive radula biting cycles underlying food-seeking behavior in Aplysia. Each spontaneous bite cycle arises from the irregular triggering of a plateau-like potential and resultant bursting by rhythmic subthreshold oscillations in B63's membrane potential. In isolated buccal ganglion preparations, and after synaptic isolation, the expression of B63's plateau potentials persisted after removal of extracellular calcium, but was completely suppressed in a tetrodotoxin (TTX)- containing bath solution, thereby indicating the contribution of a transmembrane Na+ influx. Potassium outward efflux through tetraethylammonium (TEA)- and calcium-sensitive channels was found to contribute to each plateau's active termination. This intrinsic plateauing capability, in contrast to B63's membrane potential oscillation, was blocked by the calcium-activated non-specific cationic current (ICAN) blocker flufenamic acid (FFA). Conversely, the SERCA blocker cyclopianozic acid (CPA), which abolished the neuron's oscillation, did not prevent the expression of experimentally evoked plateau potentials. These results therefore indicate that the dynamic properties of the decision neuron B63 rely on two distinct mechanisms involving different sub-populations of ionic conductances.

A High Power Factor LED Driver with Intrinsic Current Balancing Capability

The research proposed a novel LED driver with the functions of power-factor correction (PFC) and current balancing. A flyback converter and a Class-D series resonant converter were integrated by sharing an active switch to form a single-stage circuit topology. The flyback converter played the role of a PFC circuit. The component parameters were designed to make the flyback converter to operate at discontinuous-conduction mode (DCM). In this way, the input line current can be sinusoidal, resulting in near unity power factor and low total harmonic distortion in current (THDi). The resonant converter was connected in series with a differential-mode transformer with a turns ratio of 1 to drive four LED strings. The current of the four LED strings will be automatically and evenly balanced by using the 1:1 transformer. This article analyzed the different modes of operation in detail, derived the mathematical equations and designed the parameters of the circuit components. Finally, a 72-W prototype LED driver was implemented and tested. A satisfactory performance has verified the feasibility of the proposed LED driver.

A Complete Extension of Classical Hepatic Clearance Models Using Fractional Distribution Parameter [formula omitted] in Physiologically Based Pharmacokinetics

The classical organ clearance models have been proposed to relate the plasma clearance CLp to probable mechanism(s) of hepatic clearance. However, the classical models assume the intrinsic capability of drug elimination (CLu,int) that is physically segregated from the vascular blood but directly acts upon the unbound drug concentration in the blood (fubCavg), and do not handle the transit-time delay between the inlet/outlet concentrations in their closed-form clearance equations. Therefore, we propose unified model structures that can address the internal blood concentration patterns of clearance organs in a more mechanistic/physiological manner, based on the fractional distribution parameter fd operative in PBPK. The basic partial/ordinary differential equations for four classical models are revisited/modified to yield a more complete set of extended clearance models, i.e., the Rattle, Sieve, Tube, and Jar models, which are the counterparts of the dispersion, series-compartment, parallel-tube, and well-stirred models. We demonstrate the feasibility of applying the resulting extended models to isolated perfused rat liver data for 11 compounds and an example dataset for in vitro-in vivo extrapolation of the intrinsic to the systemic clearances. Based on their feasibilities to handle such real data, these models may serve as an improved basis for applying clearance models in the future.

Modeling variability in self-adapting robotic systems

Autonomous robots operating in everyday environments, such as hospitals, private houses, and public roads, are context-aware self-adaptive systems, i.e. they exploit knowledge about their resources and the environment to trigger runtime adaptation, so that they exhibit a behavior adequate to the current context. For these systems, context-aware self-adaptation requires to design the robot control application as a dynamically reconfigurable software architecture and to specify the adaptation logic for reconfiguring its variable aspects (e.g. the modules that implement various obstacle detection algorithms or control different distance sensors) according to specific criteria (e.g. enhancing robustness against variable illumination conditions). Despite self-adaptation is an intrinsic capability of autonomous robots, ad-hoc approaches are used in practice to design reconfigurable robot architectures. In order to enhance system maintainability, the control logic and the adaptation logic should be loosely coupled. For this purpose, the adaptation logic should be defined against an explicit representation of software variability in the robot control architecture. In this paper we propose a modeling approach, which consists in explicitly representing robot software variability with the MARTE::ARM-Variability metamodel, which has been designed as an extension of the UML MARTE profile. We evaluate the applicability of the proposed approach by exemplifying the software architecture design of a robot navigation framework and by analyzing the support provided by the ROS infrastructure for runtime reconfiguration of its variable aspects.

Incorporation of Tb and Gd improves the diagnostic functionality of magnetotactic bacteria.

Magnetotactic bacteria are envisaged as potential theranostic agents. Their internal magnetic compass, chemical environment specificity and natural motility enable these microorganisms to behave as nanorobots, as they can be tracked and guided towards specific regions in the body and activated to generate a therapeutic response. Here we provide additional diagnostic functionalities to magnetotactic bacteria Magnetospirillum gryphiswaldense MSR-1 while retaining their intrinsic capabilities. These additional functionalities are achieved by incorporating Tb or Gd in the bacteria by culturing them in Tb/Gd supplemented media. The incorporation of Tb provides luminescence properties, enabling potential applications of bacteria as biomarkers. The incorporation of Gd turns bacteria into dual contrast agents for magnetic resonance imaging, since Gd adds T1 contrast to the existing T2 contrast of unmodified bacteria. Given their potential clinical applications, the diagnostic ability of the modified MSR-1 has been successfully tested in vitro in two cell models, confirming their suitability as fluorescent markers (Tb-MSR-1) and dual contrast agents for MRI (Gd-MSR-1).

Carbon Nanomaterials (CNMs) in Cancer Therapy: A Database of CNM-Based Nanocarrier Systems.

Carbon nanomaterials (CNMs) are an incredibly versatile class of materials that can be used as scaffolds to construct anticancer nanocarrier systems. The ease of chemical functionalisation, biocompatibility, and intrinsic therapeutic capabilities of many of these nanoparticles can be leveraged to design effective anticancer systems. This article is the first comprehensive review of CNM-based nanocarrier systems that incorporate approved chemotherapy drugs, and many different types of CNMs and chemotherapy agents are discussed. Almost 200 examples of these nanocarrier systems have been analysed and compiled into a database. The entries are organised by anticancer drug type, and the composition, drug loading/release metrics, and experimental results from these systems have been compiled. Our analysis reveals graphene, and particularly graphene oxide (GO), as the most frequently employed CNM, with carbon nanotubes and carbon dots following in popularity. Moreover, the database encompasses various chemotherapeutic agents, with antimicrotubule agents being the most common payload due to their compatibility with CNM surfaces. The benefits of the identified systems are discussed, and the factors affecting their efficacy are detailed.