Recent research progress on tumour-specific responsive hydrogels.

Most existing hydrogels, even recently developed injectable hydrogels that undergo a reversible sol-gel phase transition in response to external stimuli, are designed to gel immediately before or after implantation/injection to prevent the free diffusion of materials and drugs; however, the property of immediate gelation leads to a very weak tumour-targeting ability, limiting their application in anticancer therapy. Therefore, the development of tumour-specific responsive hydrogels for anticancer therapy is imperative because tumour-specific responses improve their tumour-targeting efficacy, increase therapeutic effects, and decrease toxicity and side effects. In this review, we introduce the following three types of tumour-responsive hydrogels: (1) hydrogels that gel specifically at the tumour site; (2) hydrogels that decompose specifically at the tumour site; and (3) hydrogels that react specifically with tumours. For each type, their compositions, the mechanisms of tumour-specific responsiveness and their applications in anticancer treatment are comprehensively discussed.

Design of a high-performance NIR-II nanoprobe by steric regulation for in vivo vasculature and tumor imaging.

A novel NIR-II nanoprobe was developed through regulating the steric effect of an A-DA'D-A dye. The probe features the properties of strong fluorescence, high stability, and a large Stokes shift, thereby serving as a remarkable contrast agent for the fluorescence imaging of hindlimb vasculature and tumors in live mice.

Nonlinear encoding in diffractive information processing using linear optical materials.

Nonlinear encoding of optical information can be achieved using various forms of data representation. Here, we analyze the performances of different nonlinear information encoding strategies that can be employed in diffractive optical processors based on linear materials and shed light on their utility and performance gaps compared to the state-of-the-art digital deep neural networks. For a comprehensive evaluation, we used different datasets to compare the statistical inference performance of simpler-to-implement nonlinear encoding strategies that involve, e.g., phase encoding, against data repetition-based nonlinear encoding strategies. We show that data repetition within a diffractive volume (e.g., through an optical cavity or cascaded introduction of the input data) causes the loss of the universal linear transformation capability of a diffractive optical processor. Therefore, data repetition-based diffractive blocks cannot provide optical analogs to fully connected or convolutional layers commonly employed in digital neural networks. However, they can still be effectively trained for specific inference tasks and achieve enhanced accuracy, benefiting from the nonlinear encoding of the input information. Our results also reveal that phase encoding of input information without data repetition provides a simpler nonlinear encoding strategy with comparable statistical inference accuracy to data repetition-based diffractive processors. Our analyses and conclusions would be of broad interest to explore the push-pull relationship between linear material-based diffractive optical systems and nonlinear encoding strategies in visual information processors.

Effect of ultrasound/CaCl2 co-treatment on the microstructure, gelatinization, and film-forming properties of high amylose corn starch.

The effect of ultrasound/CaCl2 co-treatment on aggregation structure, thermal stability, rheological, and film properties of high amylose corn starch (HACS) was investigated. The scanning electron microscopy (SEM) images revealed the number of starch fragments and malformed starch granules increased after co-treatment. The differential scanning calorimetry (DSC) results showed the co-treated HACS got a lower gelatinization temperature (92.65 ±â€¯0.495 °C) and enthalpy values (ΔH, 4.14 ±â€¯0.192 J/g). The optical microscope images indicated that lesser Maltase crosses were observed in co-treated HACS. The results of X-ray diffraction (XRD) and Fourier transform infrared spectroscopy (FTIR) indicated ultrasound influenced the compactness of amorphous zone and CaCl2 damaged the crystalline region of HACS granules. Additionally, the rheology properties of HACS dispersion demonstrated the apparent viscosity of co-treated dispersion increased as the ultrasound time prolonged. The mechanical strength and structural compactness of HACS films were improved after ultrasound treatment. The mechanism of ultrasound/CaCl2 co-treatment improved the gelatinization and film-forming ability of HACS was that (i) ultrasound wave loosened the HACS granules shell, promoted the treatment of CaCl2 on HACS granules, and (ii) ultrasound wave improved the uniform distribution of HACS dispersion, increased the interaction between CaCl2 and starch chains during the process of film-forming.

Mesoporous Oxidized Mn-Ca Nanoparticles as Potential Antimicrobial Agents for Wound Healing.

Managing chronic non-healing wounds presents a significant clinical challenge due to their frequent bacterial infections. Mesoporous silica-based materials possess robust wound-healing capabilities attributed to their renowned antimicrobial properties. The current study details the advancement of mesoporous silicon-loaded MnO and CaO molecules (HMn-Ca) against bacterial infections and chronic non-healing wounds. HMn-Ca was synthesized by reducing manganese chloride and calcium chloride by urotropine solution with mesoporous silicon as the template, thereby transforming the manganese and calcium ions on the framework of mesoporous silicon. The developed HMn-Ca was investigated using scanning electron microscopy (SEM), transmission electron microscope (TEM), ultraviolet-visible (UV-visible), and visible spectrophotometry, followed by the determination of Zeta potential. The production of reactive oxygen species (ROS) was determined by using the 3,3,5,5-tetramethylbenzidine (TMB) oxidation reaction. The wound healing effectiveness of the synthesized HMn-Ca is evaluated in a bacterial-infected mouse model. The loading of MnO and CaO inside mesoporous silicon enhanced the generation of ROS and the capacity of bacterial capture, subsequently decomposing the bacterial membrane, leading to the puncturing of the bacterial membrane, followed by cellular demise. As a result, treatment with HMn-Ca could improve the healing of the bacterial-infected wound, illustrating a straightforward yet potent method for engineering nanozymes tailored for antibacterial therapy.

Information-hiding cameras: Optical concealment of object information into ordinary images.

We introduce an information-hiding camera integrated with an electronic decoder that is jointly optimized through deep learning. This system uses a diffractive optical processor, which transforms and hides input images into ordinary-looking patterns that deceive/mislead observers. This information-hiding transformation is valid for infinitely many combinations of secret messages, transformed into ordinary-looking output images through passive light-matter interactions within the diffractive processor. By processing these output patterns, an electronic decoder network accurately reconstructs the original information hidden within the deceptive output. We demonstrated our approach by designing information-hiding diffractive cameras operating under various lighting conditions and noise levels, showing their robustness. We further extended this framework to multispectral operation, allowing the concealment and decoding of multiple images at different wavelengths, performed simultaneously. The feasibility of our framework was also validated experimentally using terahertz radiation. This optical encoder-electronic decoder-based codesign provides a high speed and energy efficient information-hiding camera, offering a powerful solution for visual information security.

Skin Comfort Sensation with Mechanical Stimulus from Electronic Skin.

The field of electronic skin has received considerable attention due to its extensive potential applications in areas including tactile sensing and health monitoring. With the development of electronic skin devices, electronic skin can be attached to the surface of human skin for long-term health monitoring, which makes comfort an essential factor that cannot be ignored in the design of electronic skin. Therefore, this paper proposes an assessment method for evaluating the comfort of electronic skin based on neurodynamic analysis. The holistic analysis framework encompasses the mechanical model of the skin, the modified Hodgkin-Huxley model for the transduction of stimuli, and the gate control theory for the modulation and perception of pain sensation. The complete process, from mechanical stimulus to the generation of pain perception, is demonstrated. Furthermore, the influence of different factors on pain perception is investigated. Sensation and comfort diagrams are provided to assess the mechanical comfort of electronic skin. The comfort assessment method proposed in this paper provides a theoretical basis when assessing the comfort of electronic skin.

Strategy to Efficient Photodynamic Therapy for Antibacterium: Donor-Acceptor Structure in Hydrogen-Bonded Organic Framework.

While the construction of a donor-acceptor (D-A) structure has gained great attention across various scientific disciplines, such structures are seldomly reported within the field of hydrogen-bonded organic frameworks (HOFs). Herein, a D-A based HOF is synthesized, where the adjacent D-A pairs are connected by hydrogen bonds instead of the conventionally employed covalent bonds. This structural feature imparts material with a reduced energy gap between excited state and triplet state, thereby facilitating the intersystem crossing (ISC) and boosting the generation rate of single oxygen (quantum yield = 0.98). Consequently, the resulting material shows high performance for antimicrobial photodynamic therapy (PDT). The impact of D-A moiety is evident when comparing this finding to a parallel study conducted on an isoreticular HOF without a D-A structure. The study presented here provides in-depth insights into the photophysical properties of D-A pair in a hydrogen-bonded network, opening a new avenue to the design of innovative materials for efficient PDT.

All-optical phase conjugation using diffractive wavefront processing.

Optical phase conjugation (OPC) is a nonlinear technique used for counteracting wavefront distortions, with applications ranging from imaging to beam focusing. Here, we present a diffractive wavefront processor to approximate all-optical phase conjugation. Leveraging deep learning, a set of diffractive layers was optimized to all-optically process an arbitrary phase-aberrated input field, producing an output field with a phase distribution that is the conjugate of the input wave. We experimentally validated this wavefront processor by 3D-fabricating diffractive layers and performing OPC on phase distortions never seen during training. Employing terahertz radiation, our diffractive processor successfully performed OPC through a shallow volume that axially spans tens of wavelengths. We also created a diffractive phase-conjugate mirror by combining deep learning-optimized diffractive layers with a standard mirror. Given its compact, passive and multi-wavelength nature, this diffractive wavefront processor can be used for various applications, e.g., turbidity suppression and aberration correction across different spectral bands.

Inhibition of GTPase KRASG12D: a review of patent literature.

INTRODUCTION: KRAS is a critical oncogenic protein intricately involved in tumor progression, and the difficulty in targeting KRAS has led it to be classified as an 'undruggable target.' Among the various KRAS mutations, KRASG12D is highly prevalent and represents a promising therapeutic target, yet there are currently no approved inhibitors for it. AREA COVERED: This review summarizes numerous patents and literature featuring inhibitors or degraders of KRASG12D through searching relevant information in PubMed, SciFinder and Web of Science databases from 2021 to February 2024, providing an overview of the research progress on inhibiting KRASG12D in terms of design strategies, chemical structures, biological activities, and clinical advancements. EXPERT OPINION: Since the approval of AMG510 (Sotorasib), there has been an increasing focus on the inhibition of KRASG12D, leading to numerous reports of related inhibitors and degraders. Among them, MRTX1133, as the first KRASG12D inhibitor to enter clinical trials, has demonstrated excellent tumor suppression in various KRASG12D-bearing human tumor xenograft models. It is important to note, however, that understanding the mechanisms of acquired resistance caused by KRAS inhibition and developing additional combination therapies is crucial. Moreover, seeking covalent inhibition of KRASG12D also holds significant potential.

Evaluation Method for Underwater Ultrasonic Energy Radiation Performance Based on the Spatial Distribution Characteristics of Acoustic Power.

In recent years, underwater wireless ultrasonic energy transmission technology (UWUET) has attracted much attention because it utilizes the propagation characteristics of ultrasound in water. Effectively evaluating the performance of underwater ultrasonic wireless energy transmission is a key issue in engineering design. The current approach to performance evaluation is usually based on the system energy transfer efficiency as the main criterion, but this criterion mainly considers the overall energy conversion efficiency between the transmitting end and the receiving end, without an in-depth analysis of the characteristics of the distribution of the underwater acoustic field and the energy loss that occurs during the propagation of acoustic waves. In addition, existing methods focusing on acoustic field analysis tend to concentrate on a single parameter, ignoring the dynamic distribution of acoustic energy in complex aquatic environments, as well as the effects of changes in the underwater environment on acoustic propagation, such as spatial variability in temperature and salinity. These limitations reduce the usefulness and accuracy of models in complex marine environments, which in turn reduces the efficiency of acoustic energy management and optimization. To solve these problems, this study proposes a method to evaluate the performance of underwater ultrasonic energy radiation based on the spatial distribution characteristics of acoustic power. By establishing an acoustic power distribution model in a complex impedance-density aqueous medium and combining numerical simulation and experimental validation, this paper explores the spatial variation of acoustic power and its impact on the energy transfer efficiency in depth. Using high-resolution spatial distribution data and actual environmental parameters, the method significantly improves the accuracy of the assessment and the adaptability of the model in complex underwater environments. The results show that, compared with the traditional method, this method performs better in terms of the accuracy of the acoustic energy radiation calculation results, and is able to reflect the energy distribution and spatial heterogeneity of the acoustic source more comprehensively, which provides an important theoretical basis and practical guidance for the optimal design and performance enhancement of the underwater ultrasonic wireless energy transmission system.

Even-Odd Layer-Dependent Exchange Bias Effect in MnBi2Te4 Chern Insulator Devices.

Magnetic topological materials with coexisting magnetism and nontrivial band structures exhibit many novel quantum phenomena, including the quantum anomalous Hall effect, the axion insulator state, and the Weyl semimetal phase. As a stoichiometric layered antiferromagnetic topological insulator, thin films of MnBi2Te4 show fascinating even-odd layer-dependent physics. In this work, we fabricate a series of thin-flake MnBi2Te4 devices using stencil masks and observe the Chern insulator state at high magnetic fields. Upon magnetic field training, a large exchange bias effect is observed in odd but not in even septuple layer (SL) devices. Through theoretical calculations, we attribute the even-odd layer-dependent exchange bias effect to the contrasting surface and bulk magnetic properties of MnBi2Te4 devices. Our findings reveal the microscopic magnetic configuration of MnBi2Te4 thin flakes and highlight the challenges in replicating the zero magnetic field quantum anomalous Hall effect in odd SL MnBi2Te4 devices.

Single immunization of non-adjuvanted recombinant TTFC-mi3 nanoparticle vaccine elicited a rapid and potent protective immunity against tetanus.

The conventional inactivated tetanus toxin plays an instrumental role in preventing tetanus. Nevertheless, the challenges associated with its production process, the potential for adverse reactions, and reduced effectiveness in vulnerable populations such as neonates and the elderly rise the need for a novel tetanus toxin vaccine. Recombinant subunit vaccine offer a viable solution, and the tetanus toxin fragment C (TTFC) is emerging as a promising candidate. In this study, through spontaneous isopeptide bond formation we conjugated the recombinant TTFC to self-assembled mi3 nanoparticle, which derived from an optimized KDPG aldolase, and generated the TTFC-mi3 protein nanoparticle vaccine. We found that TTFC-mi3 is stable, uniform spherical nanoparticles. Comparing with the free TTFC alone, TTFC-mi3 enhances the uptake and subsequent activation of dendric cells (DCs). In addition, a single dose of adjuvant-free TTFC-mi3 elicited a more rapid and potent protective immunity in mice. Moreover, TTFC-mi3 is of favorable safety in vitro and in vivo. Our findings indicate that TTFC-mi3 is a rapid-response, non-aluminum-adjuvanted vaccine against tetanus.

Insight into the Contact Mechanism of Ag/Al-Si Interface for the Front-Side Metallization of TOPCon Silicon Solar Cells.

For N-type tunnel-oxide-passivated-contact silicon solar cells, optimal Ag/Al-Si contact interface is crucial to improve the efficiency. However, the specific roles of Ag and Al at the interface have not been clearly elucidated. Hence, this work delves into the sintering process of Ag/Al paste and examines the impact of the Ag/Al-Si interface structure on contact quality. By incorporating TeO2 into PbO-based Ag/Al paste, the Ag/Al-Si interface structure can be modulated. It can be found that TeO2 accelerates the sintering of Ag powder and increases Ag colloids within glass layer, while it simultaneously impedes the diffusion of molten Al. It leads to a reduced Al content near the Ag/Al-Si interface and a shorter diffusion distance of Al into Si. Notably, it can be demonstrated that the diffusion of Al in Si layer is more effective to reduce the contact resistance than the precipitation of Ag colloids. Therefore, the PbO-based Ag/Al paste, which favors Al diffusion, leads to solar cells with lower contact resistance and series resistance, higher fill factor, and superior photoelectric conversion efficiency. In brief, this work is significant for optimizing metallization of silicon solar cells and other semiconductor devices.

Do we really need a large number of visual prompts?

Due to increasing interest in adapting models on resource-constrained edges, parameter-efficient transfer learning has been widely explored. Among various methods, Visual Prompt Tuning (VPT), prepending learnable prompts to input space, shows competitive fine-tuning performance compared to training of full network parameters. However, VPT increases the number of input tokens, resulting in additional computational overhead. In this paper, we analyze the impact of the number of prompts on fine-tuning performance and self-attention operation in a vision transformer architecture. Through theoretical and empirical analysis we show that adding more prompts does not lead to linear performance improvement. Further, we propose a Prompt Condensation (PC) technique that aims to prevent performance degradation from using a small number of prompts. We validate our methods on FGVC and VTAB-1k tasks and show that our approach reduces the number of prompts by ∼70% while maintaining accuracy.

Enhancing weatherability and mechanical properties of tung oil wood finishes through natural rubber modification via the Diels-Alder reaction.

Tung oil is commonly utilized for coating protection in wooden products, often attracting attention for its appearance, antimicrobial capabilities, and insect-resistant coatings. However, its poor mechanical properties and poor weather resistance stem from excessive self-crosslinking of surplus conjugated double bonds and molecular chains, resulting in poor film wrinkling. Therefore, this study introduces natural rubber via the Diels-Alder reaction to consume the residual double bonds in tung oil, resulting in tung oil/natural rubber composite coatings (NRTO) with excellent mechanical properties and weather resistance. The results indicate that NRTO exhibits excellent mechanical properties, including high elongation (32 %) and strong adhesion (4.55 MPa). Furthermore, NRTO demonstrates outstanding acid resistance and UV aging resistance. Given its many benefits, NRTO film emerges as a promising candidate for substantially protecting wood surfaces in demanding environments.

Dual-Locked Fluorescent Probes Activated by Aminopeptidase N and the Tumor Redox Environment for High-Precision Imaging of Tumor Boundaries.

Clear delineation of tumor margins is essential for accurate resection and decreased recurrence rate in the clinic. Fluorescence imaging is emerging as a promising alternative to traditional visual inspection by surgeons for intraoperative imaging. However, traditional probes lack accuracy in tumor diagnosis, making it difficult to depict tumor boundaries accurately. Herein, we proposed an offensive and defensive integration (ODI) strategy based on the "attack systems (invasive peptidase) and defense systems (reductive microenvironment)" of multi-dimensional tumor characteristics to design activatable fluorescent probes for imaging tumor boundaries precisely. Screened out from a series of ODI strategy-based probes, ANQ performed better than traditional probes based on tumor unilateral correlation by distinguishing between tumor cells and normal cells and minimizing false-positive signals from living metabolic organs. To further improve the signal-to-background ratio in vivo, derivatized FANQ, was prepared and successfully applied to distinguish orthotopic hepatocellular carcinoma tissues from adjacent tissues in mice models and clinical samples. This work highlights an innovative strategy to develop activatable probes for rapid diagnosis of tumors and high-precision imaging of tumor boundaries, providing more efficient tools for future clinical applications in intraoperative assisted resection.

High spin axion insulator.

Axion insulators possess a quantized axion field θ = π protected by combined lattice and time-reversal symmetry, holding great potential for device applications in layertronics and quantum computing. Here, we propose a high-spin axion insulator (HSAI) defined in large spin-s representation, which maintains the same inherent symmetry but possesses a notable axion field θ = (s + 1/2)2π. Such distinct axion field is confirmed independently by the direct calculation of the axion term using hybrid Wannier functions, layer-resolved Chern numbers, as well as the topological magneto-electric effect. We show that the guaranteed gapless quasi-particle excitation is absent at the boundary of the HSAI despite its integer surface Chern number, hinting an unusual quantum anomaly violating the conventional bulk-boundary correspondence. Furthermore, we ascertain that the axion field θ can be precisely tuned through an external magnetic field, enabling the manipulation of bonded transport properties. The HSAI proposed here can be experimentally verified in ultra-cold atoms by the quantized non-reciprocal conductance or topological magnetoelectric response. Our work enriches the understanding of axion insulators in condensed matter physics, paving the way for future device applications.

All-optical complex field imaging using diffractive processors.

Complex field imaging, which captures both the amplitude and phase information of input optical fields or objects, can offer rich structural insights into samples, such as their absorption and refractive index distributions. However, conventional image sensors are intensity-based and inherently lack the capability to directly measure the phase distribution of a field. This limitation can be overcome using interferometric or holographic methods, often supplemented by iterative phase retrieval algorithms, leading to a considerable increase in hardware complexity and computational demand. Here, we present a complex field imager design that enables snapshot imaging of both the amplitude and quantitative phase information of input fields using an intensity-based sensor array without any digital processing. Our design utilizes successive deep learning-optimized diffractive surfaces that are structured to collectively modulate the input complex field, forming two independent imaging channels that perform amplitude-to-amplitude and phase-to-intensity transformations between the input and output planes within a compact optical design, axially spanning ~100 wavelengths. The intensity distributions of the output fields at these two channels on the sensor plane directly correspond to the amplitude and quantitative phase profiles of the input complex field, eliminating the need for any digital image reconstruction algorithms. We experimentally validated the efficacy of our complex field diffractive imager designs through 3D-printed prototypes operating at the terahertz spectrum, with the output amplitude and phase channel images closely aligning with our numerical simulations. We envision that this complex field imager will have various applications in security, biomedical imaging, sensing and material science, among others.