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Amplifying intracellular oxidative stress by organelle‐targeted reactive oxygen species (ROS) production combined with tumor cell‐specific gene disruption is a promising strategy for tumor treatment. However, due to the vulnerability of CRISPR/Cas9 ribonucleoproteins (RNPs) to ROS, co‐delivery of CRISPR/Cas9 RNPs and ROS generators to enhance the sensitivity of tumor cells to oxidative stress remains challenging. Herein, a cascade‐responsive "oxidative stress amplifier" (named DR‐TAF‐pHT/FA) is proposed, which can successively respond to cathepsin B, localized laser irradiation and ATP to generate ROS on the lysosomal membrane of tumor cells and release Cas9/sgNrf2 RNPs for efficient gene disruption. It is demonstrated that, under near infrared (NIR) irradiation, DR‐TAF‐pHT/FA achieves targeted rupture of lysosomal membranes, inducing significant intracellular oxidative stress. Meanwhile, due to the protective function of TAF coating (TA‐Fe3+ coordination self‐assembled networks), Cas9/sgNrf2 RNPs can safely escape into the cytoplasm and be released in response to ATP, further amplifying oxidative stress and promoting tumor cell apoptosis through efficient Nrf2 gene disruption. Treatment with DR‐TAF‐pHT/FA + NIR significantly improves tumor ablation efficiency and extends median survival time (over 70 days) in Hela xenograft models. This "oxidative stress amplifier" provides a new paradigm for multimodal and synergistic tumor therapy through precise lysosomal membrane bursting together with efficient Nrf2 gene disruption. [ABSTRACT FROM AUTHOR]

Large deformation and complex fluid flow interactions, known as the fluid–structure interaction (FSI), are common in geotechnical and coastal projects. To address FSI problems involving crack development, block contact and large movement, a numerical model that utilises smoothed particle hydrodynamics for fluid field spatial discretisation and numerical manifold method for solid block domain solution is proposed in the present study. Specifically, to restore the particle inconsistency near the interface and the overflow issue around the sharp corner in traditional coupled methods, a recommended boundary particle approach is designed to provide full support for particles near the interface, regardless of the interface's geometry. Moreover, this approach enables the choice of different spatial resolutions tailored to requirements of solid and fluid domains. Six numerical examples were conducted to verify the reliability, accuracy and robustness of the new method. Results showed that relative errors around the sharp corner are lower than those in previous studies. Furthermore, the new model performs well in dealing with the motion of blocks with arbitrary shapes, including large movements, block contacts, crack propagations, and large deformations. Additionally, various inner-variable field evolutions between fluids and solids were visualised, which is beneficial for the prediction of multi-hazard scenario outcomes. [ABSTRACT FROM AUTHOR]

In this paper, a hybrid numerical manifold method with node-based strain smoothing and double-interpolation is proposed for crack analysis and propagation. By introducing an allocation scheme, the empty strain smoothing domain issue encountered in the numerical manifold method framework is avoided, while the flexibility in smooth domain formulation is preserved. Our method's hybrid approach stems from the double-interpolation locally implemented on the tip domain, where strain smoothing becomes cumbersome and costly. High accuracy and continuous nodal stress solutions were achieved in whole domains. The proposed model is validated through several comparisons of analytical and experimental results, and the results obtained for crack analysis and growths are shown to be accurate and efficient. • Empty strain smoothing domain issue existed in numerical manifold method is avoided. • Flexible layout of mathematical mesh is preserved by our proposed allocation scheme. • Continuous nodal stresses in tip domains can be achieved by double-interpolation. • Potential of our hybrid method for crack analysis and propagation is demonstrated. [ABSTRACT FROM AUTHOR]

Liver fibrosis is a progressive histological manifestation that happens in almost all chronic liver diseases. An unabated liver fibrosis may eventually develop into liver cirrhosis or hepatocellular carcinoma. Yet, the strategy for reversal of liver fibrosis is still limited. Herein, a biomimetic nano‐regulator (P‐ZIF8‐cirDNAzyme) is developed to affect both collagen synthesis and degradation in liver to remodel collagen microenvironment. It is found that Zn (II) interference can efficiently inhibit collagen synthesis in activated hepatic stellate cells (aHSC) by inactivating proline 4 hydroxylase and affecting many fibrosis‐related signaling pathways. Meanwhile, Zn (II)‐dependent circular DNAzymes (cirDNAzymes) are used to efficiently silence tissue inhibitors of metalloproteinase‐1, accelerating the degradation of collagen. They act in concert to recover the balance between collagen deposition and degradation. Additionally, ZIF‐8‐cirDNAzyme is coated by platelet membrane (PM) for precisely targeting aHSC via PM's inflammatory tropism and CD62p–CD44 interaction. In carbon tetrachloride‐induced fibrotic mice, P‐ZIF‐8‐cirDNAzyme shows a potent anti‐fibrotic effect, greatly reducing the expression of collagen by 73.12% and restoring liver function nearly to normal. This work proposes a prospective platform enabling ion interference and gene silencing, collectively acting in aHSC for reversal of liver fibrosis. [ABSTRACT FROM AUTHOR]

Impact treatment methods that increase surface roughness usually cause near-to-surface damage to concrete. Quantitative analysis of this damage on the bond strength is rare. In this article, a concrete surface was reproduced by an undamaged engraving method, and then surface curing agents were used to repair the damage. Direct tension tests show that the bond strengths of new to old concrete caused by surface damage of low-frequency high-energy (LFHE) and low-frequency medium-energy (LFME) impacts were reduced by 41.96% and 41.42%, respectively. Concrete surface curing agents led to the formation of crystalline films that negatively affected the interfacial bond strength. • Quantifying how surface damage from varied impact strengths affects bond strength. • Engraving replicates concrete surface roughness without damage. • Pigment tech gauges aggregate 2D ratio; same-batch concrete shows minor dispersion. • Silicate-based curing agent negatively affects bonding due to crystal film formation. [ABSTRACT FROM AUTHOR]

Rainfall is one of the most significant natural factors for inducing landslides. The shallow saturated zone formed in slopes during rainfall is an important factor in inducing shallow landslides. In this paper, the characteristics and influencing factors of the saturated zone in soil slopes, and the relationship between the soil surface permeability coefficient and the rainfall intensity are analyzed. In this research, the equation that characterizes the rainfall intensity by the soil saturation is built based on the Mualem-van Genuchten model, which mathematically describes the soil water characteristics of unsaturated soils. Using this model, the target saturation of the slope surface during rainfall can be determined accurately, with an average deviation of − 0.008. Based on the equations, the innovative critical curve model of the rainfall intensity−time required to form the shallow saturated zone is established and calculated. The influence of the soil material, slope angle, rainfall intensity and antecedent rainfall on the critical curve for the shallow saturated zone is analyzed. The results indicate that for slopes of 30°~40°, it is easy for the shallow saturated zone to form, and the previous rainfall after more than 16 days has little impact on the critical curve. Furthermore, an innovative landslide prediction model, based on the critical curve for the shallow saturated zone and I-D modeling, is proposed to provide benchmarks for the prediction-specific characteristics of deep or shallow landslides, which is verified by the case of the Madiwan landslide. [ABSTRACT FROM AUTHOR]

• The ceramic polishing powder can be taken as a supplementary cementitious material. • The chloride penetration resistance of concrete was improved by ceramic polishing powder and seawater mixing. • Ceramic polishing powder promoted the formation of Friedel's salt in concrete for mixing with seawater and cement-CPP. Waste ceramic polishing powder (CPP) is a by-product created during the grinding and polishing process of the ceramic industry, which adversely affects the environment. In this research, it was used as auxiliary material to partially replace cement during the casting of the test specimens. The effect of cement substitution by 0%, 5%, 10%, 20%, 30%, 40% and 50% of the CPP with seawater and freshwater mixing on the compressive strength and resistance to chloride penetration of the concrete is compared. Moreover, the microstructure development and hydration products of both pastes are determined by different methods. Experimental results show that the compressive strength and resistance to chloride penetration of concrete samples, with the CPP and seawater mixing, is superior to that of the freshwater specimen, with the CPP mixing at the same curing time and the same CPP content. The compressive strength of both types of concrete tends to decrease with increasing content of CPP replacing cement. The compressive strength of concrete meets design requirements when the rate of cement replacement is up to 30% of CPP content when mixed with seawater, but the compressive strength of concrete meets design requirements when the rate of substitution cement reaches a maximum of 10 wt% CPP content mixed with freshwater. In contrast, the resistance to chloride penetration of both types of concrete mixed with CPP is better than that of the specimen without CPP and with the increase of cement replacement rate with CPP, the chloride resistance of concrete shows a rising trend. Under the same CPP substitution and the same curing time, the resistance of chloride penetration of concrete with freshwater mixing is lower than that of concrete mixed with seawater. In addition, the main hydration products in freshwater and seawater pastes with that CPP mixing were CH, ettringite and CSH. In particular, the component of the CPP promoted the formation of Friedel's salt in concrete mixed with seawater. Seawater increased CH content at an early age (7 days) and decreased later (28 days). At a later age, most of the chlorides in seawater with that CPP component were immobilized by hydrocalumite, which microstructure became denser and compacted structure of concrete. [ABSTRACT FROM AUTHOR]

• Deep learning-based instantaneous cutting force model of CNC milling is presented. • Comprehensive geometric and processing information is encoded into images. • Deep learning network named MF-CNN is designed to predict the cutting force. • Interpretation of MF-CNN is analyzed toward the theoretical cutting force model. • Proposed approach can predict cutting force with outstanding accuracy. Accurate cutting force modeling is the basis for good planning and optimization of the process and parameter of Computerized Numerical Control (CNC) milling. Traditional cutting force prediction models suffer from problems of oversimplifications on the model's input and framework, making it difficult to predict the cutting force accurately in the complex machining process. This paper proposes a novel deep learning-based instantaneous cutting force prediction model with superior modeling precision. According to the mechanism of cutting force generation, the comprehensive geometric and processing information in the machining process is creatively expressed as multi-channel digital images named Image of Comprehensive Geometric Processing Information (ICGPI). A deep learning network called Milling Force Convolutional Neural Network (MF-CNN) is then designed that takes the ICGPI as the input and the three-dimensional instantaneous cutting forces as the output. To address the challenging problem of interpretation of the deep learning network, the MF-CNN is analyzed toward the theoretical mechanistic cutting force model, validating that the proposed method can fully cover all the geometric information and mathematical operations involved in the theoretical model. Finally, some physical cutting experiments are conducted to validate the effectiveness and superiority of the proposed method, showing that our MF-CNN can predict the instantaneous cutting force with outstanding accuracy and is much superior to the three most popular benchmarks. [Display omitted] [ABSTRACT FROM AUTHOR]