Offensive language detection has received important attention and plays a crucial role in promoting healthy communication on social platforms, as well as promoting the safe deployment of large language models. Training data is the basis for developing detectors; however, the available offense-related dataset in Chinese is severely limited in terms of data scale and coverage when compared to English resources. This significantly affects the accuracy of Chinese offensive language detectors in practical applications, especially when dealing with hard cases or out-of-domain samples. To alleviate the limitations posed by available datasets, we introduce AugCOLD (Augmented Chinese Offensive Language Dataset), a large-scale unsupervised dataset containing 1 million samples gathered by data crawling and model generation. Furthermore, we employ a multiteacher distillation framework to enhance detection performance with unsupervised data. That is, we build multiple teachers with publicly accessible datasets and use them to assign soft labels to AugCOLD. The soft labels serve as a bridge for knowledge to be distilled from both AugCOLD and multiteacher to the student network, i.e., the final offensive detector. We conduct experiments on multiple public test sets and our well-designed hard tests, demonstrating that our proposal can effectively improve the generalization and robustness of the offensive language detector.

Acoustically actuated magnetoelectric (ME) antenna based on the efficient oscillation of magnetic dipoles has recently been considered as a promising solution for portable very-low-frequency communications. However, the severe nonlinear dynamic behavior in the case of strong-field excitation results in insufficient radiation capability and poor communication performance for a conventional ME antenna. In this work, we propose to suppress the nonlinearity of an ME antenna by neutralizing the spring-hardening effect in amorphous Metglas and the spring-softening effect in piezoelectric ceramics through an ME multilayered transmitter (ME-MLTx) design. With a driving voltage of 50 V_pp at the resonance frequency of 21.2 kHz, a magnetic flux density as high as 108 fT at a distance of 100 m is produced from a single ME-MLTx. In addition, ME-MLTx performs a decreased mechanical quality factor (Q_m) less than 40.65, and, thus, a broadened bandwidth of 500 Hz is generated. Finally, a communication link transmitting binary American Standard Code for Information Interchange-coded message is built, which allows for an error-free communication with a distance of 18 m and a data rate of 300 bit/s in the presence of heavy environment noise. The communication distance can be further estimated over 100 m when using a femtotesla-class-inductive magnetic field receiver. The obtained results are believed to bring ME antennas one step closer to being applicable in very-low-frequency communications.

Cancer immunotherapy has achieved tremendous successful clinical results and obtained historic victories in tumor treatments. However, great limitations associated with feeble immune responses and serious adverse effects still cannot be neglected due to the complicated multifactorial etiology and pathologic microenvironment in tumors. The rapid development of nanomedical science and material science has facilitated the advanced progress of engineering biomaterials to tackle critical issues. The supramolecular biomaterials with flexible and modular structures have exhibited unparalleled advantages of high cargo-loading efficiency, excellent biocompatibility, and diversiform immunomodulatory activity, thereby providing a powerful weapon for cancer immunotherapy. In past decades, supramolecular biomaterials were extensively explored as versatile delivery platforms for immunotherapeutic agents or designed to interact with the key moleculars in immune system in a precise and controllable manner. In this review, we focused on the crucial role of supramolecular biomaterials in the modulation of pivotal steps during tumor immunotherapy, including antigen delivery and presentation, T lymphocyte activation, tumor-associated macrophage elimination and repolarization, and myeloid-derived suppressor cell depletion. Based on extensive research, we explored the current limitations and development prospects of supramolecular biomaterials in cancer immunotherapy.

Insufficient sleep can produce a multitude of deleterious repercussions on various domains of human well-being. Concomitantly, the walnut (Juglans mandshurica) confers numerous salutary biological activities pertaining to sleep. Nevertheless, the sedative and hypnotic capacities of walnut’s functional constituents remain obscure. In this investigation, we analyzed the sedative and hypnotic components of the walnut Diaphragma juglandis fructus and innovatively discovered a compound, defined as 3-hydroxy-4-iminobutyric acid (HIBA), which disrupts motor activity and enhances sleep duration by regulating the neurotransmitters (GABA, DA, etc.) within the brain and serum of mice. Subsequently, a metabolomics approach of the serum, basal ganglia, hypothalamus, and hippocampus as well as the gut microbiota was undertaken to unravel the underlying molecular mechanisms of sleep promotion. Our data reveal that HIBA can regulate the metabolism of basal ganglia (sphingolipids, acylcarnitines, etc.), possibly in relation to HIBA’s influence on the gut microbiome (Muribaculum, Bacteroides, Lactobacillus, etc.). Therefore, we introduce a novel natural product, HIBA, and explicate the modulation of sleep promotion in mice based on the microbiota–gut–brain axis. This study contributes fresh insights toward natural product-based sleep research.

Nonoxidative coupling of methane exhibits promising prospect in that it affords value-added hydrocarbons and hydrogen with high atom economy. However, challenge remains in direct, selective conversion of methane to more valuable hydrocarbons like olefins. The current work presents a catalyst with well-dispersed Ta atoms anchored by graphitic C₃N₄-supported phthalocyanine. Such a catalyst is able to convert methane selectively to ethylene and propylene at a relatively low temperature (350 °C). The conception of the active center and construction of the catalyst have been described, and the origins of the catalytic performance are discussed.

Identifying pathogenetic variants and inferring their impact on protein–protein interactions sheds light on their functional consequences on diseases. Limited by the availability of experimental data on the consequences of protein interaction, most existing methods focus on building models to predict changes in protein binding affinity. Here, we introduced MIPPI, an end-to-end, interpretable transformer-based deep learning model that learns features directly from sequences by leveraging the interaction data from IMEx. MIPPI was specifically trained to determine the types of variant impact (increasing, decreasing, disrupting, and no effect) on protein–protein interactions. We demonstrate the accuracy of MIPPI and provide interpretation through the analysis of learned attention weights, which exhibit correlations with the amino acids interacting with the variant. Moreover, we showed the practicality of MIPPI in prioritizing de novo mutations associated with complex neurodevelopmental disorders and the potential to determine the pathogenic and driving mutations. Finally, we experimentally validated the functional impact of several variants identified in patients with such disorders. Overall, MIPPI emerges as a versatile, robust, and interpretable model, capable of effectively predicting mutation impacts on protein–protein interactions and facilitating the discovery of clinically actionable variants.

Genetic engineering technology can achieve specific gene therapy for a variety of diseases, but the current strategy still has some flaws, such as a complex system, single treatment, and large implantation trauma. Herein, the genetic engineering injectable hydrogels were constructed by ultrasonic technology for the first time to realize in vivo ultrasound-triggered in situ cross-linking and cell gene transfection, and finally complete in situ gene therapy to promote bone reconstruction. First, ultrasound-triggered calcium release was used to activate transglutaminase and catalyze the transamidation between fibrinogen. Simultaneously, liposome loaded with Zinc-finger E-box-binding homeobox 1 (ZEB1) gene plasmid (Lip-ZEB1) was combined to construct an ultrasound-triggered in situ cross-linked hydrogels that can deliver Lip-ZEB1. Second, ultrasound-triggered injectable hydrogel introduced ZEB1 gene plasmid into endothelial cell genome through Lip-ZEB1 sustained release, and then acted on the ZEB1/Notch signal pathway of cells, promoting angiogenesis and local bone reconstruction of osteoporosis through genetic engineering. Overall, this strategy provides an advanced gene delivery system through genetic engineered ultrasound-triggered injectable hydrogels.

Simulated reality encompasses virtual, augmented, and mixed realities—each characterized by different degrees of truthfulness in the visual perception: “all false,” “coexistence of true and false,” and “difficult distinction between true and false,” respectively. In all these technologies, however, the temperature rendering of virtual objects is still an unsolved problem. Undoubtedly, the lack of thermal tactile functions substantially reduces the quality of the user’s real-experience perception. To address this challenge, we propose theoretically and realize experimentally a technological platform for the in situ simulation of thermal reality. To this purpose, we design a thermal metadevice consisting of a reconfigurable array of radiating units, capable of generating the thermal image of any virtual object, and thus rendering it in situ together with its thermal signature. This is a substantial technological advance, which opens up new possibilities for simulated reality and its applications to human activities.

Photodynamic therapy with reactive oxygen species production is a prospective treatment to combat cancer stem cells (CSCs). However, the innate drawbacks, including short lifetime and diffusion distance of reactive oxygen species and hypoxia within solid tumors, have become bottlenecks for clinical applications of photodynamic therapy. Here, we develop a mitochondria-targeting hemicyanine–oleic acid conjugate (CyOA), which can self-assemble into supramolecular nanoparticles (NPs) without any exogenous excipients. CyOA is also shown for targeting the mitochondrial complex II protein succinate dehydrogenase to inhibit oxidative phosphorylation and reverse tumor hypoxia, resulting in 50.4-fold higher phototoxicity against breast cancer stem cells (BCSCs) compared to SO₃-CyOA NPs that cannot target to mitochondria. In 4T1 and BCSC tumor models, CyOA NPs achieve higher tumor inhibition and less lung metastasis nodules compared to the clinically used photosensitizer Hiporfin. This study develops a self-assembled small molecule that can serve as both oxidative phosphorylation inhibitor and photosensitizer for eradication of CSCs and treatment of solid tumors.

Tumor cells progressively remodel cytoskeletal structures and reduce cellular stiffness during tumor progression, implicating the correlation between cell mechanics and malignancy. However, the roles of tumor cell cytoskeleton and the mechanics in tumor progression remain incompletely understood. We report that softening/stiffening tumor cells by targeting actomyosin promotes/suppresses self-renewal in vitro and tumorigenic potential in vivo. Weakening/strengthening actin cytoskeleton impairs/reinforces the interaction between adenomatous polyposis coli (APC) and β-catenin, which facilitates β-catenin nuclear/cytoplasmic localization. Nuclear β-catenin binds to the promoter of Oct4, which enhances its transcription that is crucial in sustaining self-renewal and malignancy. These results demonstrate that the mechanics of tumor cells dictate self-renewal through cytoskeleton–APC–Wnt/β-catenin–Oct4 signaling, which are correlated with tumor differentiation and patient survival. This study unveils an uncovered regulatory role of cell mechanics in self-renewal and malignancy, and identifies tumor cell mechanics as a hallmark not only for cancer diagnosis but also for mechanotargeting.

The clinical efficacy of implanted biomaterials is often compromised by host immune recognition and subsequent foreign body responses (FBRs). During the implantation, biomaterials inevitably come into direct contact with the blood, absorbing blood protein and forming blood clot. Many studies have been carried out to regulate protein adsorption, thus manipulating FBR. However, the role of clot surface fibrin films formed by clotting shrinkage in host reactions and FBR is often ignored. Because of the principle of fibrin film formation being relevant to fibrinogen or clotting factor absorption, it is feasible to manipulate the fibrin film formation via tuning the absorption of fibrinogen and clotting factor. As biological hydroxyapatite reserved bone architecture and microporous structure, the smaller particle size may expose more microporous structures and adsorb more fibrinogen or clotting factor. Therefore, we set up 3 sizes (small, <0.2 mm; medium, 1 to 2 mm; large, 3 to 4 mm) of biological hydroxyapatite (porcine bone-derived hydroxyapatite) with different microporous structures to investigate the absorption of blood protein, the formation of clot surface fibrin films, and the subsequent FBR. We found that small group adsorbed more clotting factors because of more microporous structures and formed the thinnest and sparsest fibrin films. These thinnest and sparsest fibrin films increased inflammation and profibrosis of macrophages through a potential signaling pathway of cell adhesion–cytoskeleton–autophagy, leading to the stronger FBR. Large group adsorbed lesser clotting factors, forming the thickest and densest fibrin films, easing inflammation and profibrosis of macrophages, and finally mitigating FBR. Thus, this study deepens the understanding of the role of fibrin films in host recognition and FBR and demonstrates the feasibility of a strategy to regulate FBR by modulating fibrin films via tuning the absorption of blood proteins.

Asia stands out as a priority for urgent biodiversity conservation due to its large protected areas (PAs) and threatened species. Since the 21st century, both the highlands and lowlands of Asia have been experiencing the dramatic human expansion. However, the threat degree of human expansion to biodiversity is poorly understood. Here, the threat degree of human expansion to biodiversity over 2000 to 2020 in Asia at the continental (Asia), national (48 Asian countries), and hotspot (6,502 Asian terrestrial PAs established before 2000) scales is investigated by integrating multiple large-scale data. The results show that human expansion poses widespread threat to biodiversity in Asia, especially in Southeast Asia, with Malaysia, Cambodia, and Vietnam having the largest threat degrees (∼1.5 to 1.7 times of the Asian average level). Human expansion in highlands induces higher threats to biodiversity than that in lowlands in one-third Asian countries (most Southeast Asian countries). The regions with threats to biodiversity are present in ∼75% terrestrial PAs (including 4,866 PAs in 26 countries), and human expansion in PAs triggers higher threat degrees to biodiversity than that in non-PAs. Our findings provide novel insight for the Sustainable Development Goal 15 (SDG-15 Life on Land) and suggest that human expansion in Southeast Asian countries and PAs might hinder the realization of SDG-15. To reduce the threat degree, Asian developing countries should accelerate economic transformation, and the developed countries in the world should reduce the demands for commodity trade in Southeast Asian countries (i.e., trade leading to the loss of wildlife habitats) to alleviate human expansion, especially in PAs and highlands.

The development of self-powered flexible multicolor electrochromic (EC) systems that could switch different color without an external power supply has remained extremely challenging. Here, a new trilayer film structure for achieving self-powered flexible multicolor EC displays based on self-charging/discharging mechanism is proposed, which is simply assembled by sandwiching an ionic gel film between 2 cathodic nickel hexacyanoferrate (NiHCF) and Prussian blue (PB) nanoparticle films on indium tin oxide substrates. The display exhibits independent self-powered color switching of NiHCF and PB films with fast responsive time and high reversibility by selectively connecting the Al wire as anodes with the 2 EC films. Multicolor switching is thus achieved through a color overlay effect by superimposing the 2 EC films, including green, blue, yellow, and colorless. The bleaching/coloration process of the displays is driven by the discharging/self-charging mechanism for NiHCF and PB films, respectively, ensuring the self-powered color switching of the displays reversibly without an external power supply. It is further demonstrated that patterns can be easily created in the self-powered EC displays by the spray-coating method, allowing multicolor changing to convey specific information. Moreover, a self-powered ionic writing board is demonstrated based on the self-powered EC displays that can be repeatedly written freehand without the need of an external power source. We believe that the design concept may provide new insights into the development of self-powered flexible multicolor EC displays with self-recovered energy for widespread applications.

Spatially resolved transcriptomics (SRT) is capable of comprehensively characterizing gene expression patterns and providing an unbiased image of spatial composition. To fully understand the organizational complexity and tumor immune escape mechanism, we propose stMGATF, a multiview graph attention fusion model that integrates gene expression, histological images, spatial location, and gene association. To better extract information, stMGATF exploits SimCLRv2 for visual feature exaction and employs edge feature enhanced graph attention networks for the learning potential embedding of each view. A global attention mechanism is used to adaptively integrate 3 views to obtain low-dimensional representation. Applied to diverse SRT datasets, stMGATF is robust and outperforms other methods in detecting spatial domains and denoising data even with different resolutions and platforms. In particular, stMGATF contributes to the elucidation of tissue heterogeneity and extraction of 3-dimensional expression domains. Importantly, considering the associations between genes in tumors, stMGATF can identify the spatial dark genes ignored by traditional methods, which can be used to predict tumor-driving transcription factors and reveal tumor immune escape mechanisms, providing theoretical evidence for the development of new immunotherapeutic strategies.

Epilepsy severely impairs the cognitive behavior of patients. It remains unclear whether epilepsy-induced cognitive impairment is associated with neuronal activities in the medial entorhinal cortex (MEC), a region known for its involvement in spatial cognition. To explore this neural mechanism, we recorded the spikes and local field potentials from MEC neurons in lithium–pilocarpine-induced epileptic rats using self-designed microelectrode arrays. Through the open field test, we identified spatial cells exhibiting spatially selective firing properties and assessed their spatial representations in relation to the progression of epilepsy. Meanwhile, we analyzed theta oscillations and theta modulation in both excitatory and inhibitory neurons. Furthermore, we used a novel object recognition test to evaluate changes in spatial cognitive ability of epileptic rats. After the epilepsy modeling, the spatial tuning of various types of spatial cells had suffered a rapid and pronounced damage during the latent period (1 to 5 d). Subsequently, the firing characteristics and theta oscillations were impaired. In the chronic period (>10 d), the performance in the novel object experiment deteriorated. In conclusion, our study demonstrates the detrimental effect on spatial representations and electrophysiological properties of MEC neurons in the epileptic latency, suggesting the potential use of these changes as a “functional biomarker” for predicting cognitive impairment caused by epilepsy.

Topological data analysis can extract effective information from higher-dimensional data. Its mathematical basis is persistent homology. The persistent homology can calculate topological features at different spatiotemporal scales of the dataset, that is, establishing the integrated taxonomic relation among points, lines, and simplices. Here, the simplicial network composed of all-order simplices in a simplicial complex is essential. Because the sequence of nested simplicial subnetworks can be regarded as a discrete Morse function from the simplicial network to real values, a method based on the concept of critical simplices can be developed by searching all-order spanning trees. Employing this new method, not only the Morse function values with the theoretical minimum number of critical simplices can be obtained, but also the Betti numbers and composition of all-order cavities in the simplicial network can be calculated quickly. Finally, this method is used to analyze some examples and compared with other methods, showing its effectiveness and feasibility.

As extensively distributed tissues throughout the human body, glands play a critical role in various physiological processes. Therefore, the construction of biomimetic gland models in vitro has aroused great interest in multiple disciplines. In the biological field, the researchers focus on optimizing the cell sources and culture techniques to reconstruct the specific structures and functions of glands, such as the emergence of organoid technology. From the perspective of biomedical engineering, the generation of biomimetic gland models depends on the combination of engineered scaffolds and microfluidics, to mimic the in vivo environment of glandular tissues. These engineered stratagems endowed gland models with more biomimetic features, as well as a wide range of application prospects. In this review, we first describe the biomimetic strategies for constructing different in vitro gland models, focusing on the role of microfluidics in promoting the structure and function development of biomimetic glands. After summarizing several common in vitro models of endocrine and exocrine glands, the applications of gland models in disease modelling, drug screening, regenerative medicine, and personalized medicine are enumerated. Finally, we conclude the current challenges and our perspective of these biomimetic gland models.

Introducing and stabilizing oxygen vacancies in oxide catalysts is considered to be a promising strategy for improving catalytic activity and durability. Herein, we quantitatively create oxygen vacancies in the lattice of porous single-crystalline β-Ga₂O₃ monoliths by reduction treatments and stabilize them through the long-range ordering of crystal lattice to enhance catalytic activity and durability. The combination analysis of time-of-flight neutron powder diffraction and extended x-ray absorption fine structure discloses that the preferential generation of oxygen vacancy tends to occur at the site of tetrahedral coordination oxygen ions (O_III sites), which contributes to the formation of unsaturated Ga–O coordination in the monoclinic phase. The oxygen vacancies are randomly distributed in lattice even though some of them are present in the form of domain defect in the PSC Ga₂O₃ monoliths after the reduction treatment. The number of oxygen vacancies in the reduced monoliths gives 2.32 × 10¹³, 2.87 × 10¹³, and 3.45 × 10¹³ mg⁻¹ for the Ga₂O_2.952, Ga₂O_2.895, and Ga₂O_2.880, respectively. We therefore demonstrate the exceptionally high C₂H₄ selectivity of ~100% at the C₂H₆ conversion of ~37% for nonoxidative dehydrogenation of C₂H₆ to C₂H₄. We further demonstrate the excellent durability even at 620 °C for 240 h of continuous operation.

Classical-wave topological materials lacking intrinsic half-integer spins are less robust while more tunable. Here, we explore a single 3-dimensional phononic topological crystalline insulator that simultaneously exhibits a whole family of first-order quadratic surface, second-order hinge, and third-order corner states within the same bandgap. Such a topological crystalline insulator hosting all-order phases originates from the different topological nature when hierarchically projected onto different facets and lower dimensions, thus free from trivial cladding crystals. Our work offers an ideal platform for either robust wave propagation or localization in on-demand dimensions and may facilitate dimension division multiplexing technology.

The influence of a mechanical structure’s volume increment on the volume power density (VPD) of triboelectric nanogenerators (TENGs) is often neglected when considering surface charge density and surface power density. This paper aims to address this gap by introducing a standardized VPD metric for a more comprehensive evaluation of TENG performance. The study specifically focuses on 2 frequency-up mechanisms, namely, the integration of planetary gears (PG-TENG) and the implementation of a double-cantilever structure (DC-TENG), to investigate their impact on VPD. The study reveals that the PG-TENG achieves the highest volume average power density, measuring at 0.92 W/m³. This value surpasses the DC-TENG by 1.26 times and the counterpart TENG by a magnitude of 69.9 times. Additionally, the PG-TENG demonstrates superior average power output. These findings introduce a new approach for enhancing TENGs by incorporating frequency-up mechanisms, and highlight the importance of VPD as a key performance metric for evaluating TENGs.

The identification of protein–protein interaction (PPI) sites is essential in the research of protein function and the discovery of new drugs. So far, a variety of computational tools based on machine learning have been developed to accelerate the identification of PPI sites. However, existing methods suffer from the low predictive accuracy or the limited scope of application. Specifically, some methods learned only global or local sequential features, leading to low predictive accuracy, while others achieved improved performance by extracting residue interactions from structures but were limited in their application scope for the serious dependence on precise structure information. There is an urgent need to develop a method that integrates comprehensive information to realize proteome-wide accurate profiling of PPI sites. Herein, a novel ensemble framework for PPI sites prediction, EnsemPPIS, was therefore proposed based on transformer and gated convolutional networks. EnsemPPIS can effectively capture not only global and local patterns but also residue interactions. Specifically, EnsemPPIS was unique in (a) extracting residue interactions from protein sequences with transformer and (b) further integrating global and local sequential features with the ensemble learning strategy. Compared with various existing methods, EnsemPPIS exhibited either superior performance or broader applicability on multiple PPI sites prediction tasks. Moreover, pattern analysis based on the interpretability of EnsemPPIS demonstrated that EnsemPPIS was fully capable of learning residue interactions within the local structure of PPI sites using only sequence information. The web server of EnsemPPIS is freely available at http://idrblab.org/ensemppis.

Achieving color-tunable emission in single-component organic emitters with multistage stimuli-responsiveness is of vital significance for intelligent optoelectronic applications, but remains enormously challenging. Herein, we present an unprecedented example of a color-tunable single-component smart organic emitter (DDOP) that simultaneously exhibits multistage stimuli-responsiveness and multimode emissions. DDOP based on a highly twisted amide-bridged donor–acceptor–donor structure has been found to facilitate intersystem crossing, form multimode emissions, and generate multiple emissive species with multistage stimuli-responsiveness. DDOP pristine crystalline powders exhibit abnormal excitation-dependent emissions from a monomer-dominated blue emission centered at 470 nm to a dimer-dominated yellow emission centered at 550 nm through decreasing the ultraviolet (UV) excitation wavelengths, whereas DDOP single crystals show a wide emission band with a main emission peak at 585 nm when excited at different wavelengths. The emission behaviors of pristine crystalline powders and single crystals are different, demonstrating emission features that are closely related to the aggregation states. The work has developed color-tunable single-component organic emitters with simultaneous multistage stimuli-responsiveness and multimode emissions, which is vital for expanding intelligent optoelectronic applications, including multilevel information encryption, multicolor emissive patterns, and visual monitoring of UV wavelengths.

Photodeformable polymer materials have a far influence in the fields of flexibility and intelligence. The stimulation energy is converted into mechanical energy through molecular synergy. Among kinds of photodeformable polymer materials, liquid crystalline polymer (LCP) photodeformable materials have been a hot topic in recent years. Chromophores such as azobenzene, α-cyanostilbene, and 9,10-dithiopheneanthracene have been widely used in LCP, which are helpful for designing functional molecules to increase the penetration depth of light to change physical properties. Due to the various applications of photodeformable polymer materials, there are many excellent reports in intelligent field. In this review, we have systematized LCP containing azobenzene into 3 categories depending on the degree of crosslinking liquid crystalline elastomers, liquid crystalline networks, and linear LCPs. Other structural, typical polymer materials and their applications are discussed. Current issues faced and future directions to be developed for photodeformable polymer materials are also summarized.