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Metastasis is the leading cause of death in patients with breast cancer. Detecting high-risk breast cancer, including micrometastasis, at an early stage is vital for customizing the right and efficient therapies. In this study, we propose an enzyme-free isothermal cascade amplification-based DNA logic circuit in situ biomineralization nanosensor, HDNAzyme@ZIF-8, for simultaneous imaging of multidimensional biomarkers in live cells. Taking miR-21 and Ki-67 mRNA as the dual detection targets achieved sensitive logic operations and molecular recognition through the cascade hybridization chain reaction and DNAzyme. The HDNAzyme@ZIF-8 nanosensor has the ability to accurately differentiate breast cancer cells and their subtypes by comparing their relative fluorescence intensities. Of note, our nanosensor can also achieve visualization within breast cancer organoids, faithfully recapitulating the functional characteristics of parental tumor. Overall, the combination of these techniques offers a universal strategy for detecting cancers with high sensitivity and holds vast potential in clinical cancer diagnosis.

Fluorescent lateral flow immunoassay (LFA) systems are versatile tools for sensitive and quantitative detection of disease markers at the point of care. However, traditional fluorescent nanoparticle-based lateral flow immunoassays are not visible under room light, necessitate an additional fluorescent reader, and lack flexibility for different application scenarios. Herein, we report a dual-readout LFA system for the rapid and sensitive detection of C-reactive protein (CRP) in clinical samples. The system relied on the aggregation-induced emission nanobeads (AIENBs) encapsulated with red AIE luminogen, which possesses both highly fluorescent and colorimetric properties. The AIENB-based LFA in the naked-eye mode was able to qualitatively detect CRP levels as low as 8.0 mg/L, while in the fluorescent mode, it was able to quantitatively measure high-sensitivity CRP (hs-CRP) with a limit of detection of 0.16 mg/L. The AIENB-based LFA system also showed a good correlation with the clinically used immunoturbidimetric method for CRP and hs-CRP detection in human plasma. This dual-modal AIENB-based LFA system offers the convenience of colorimetric testing and highly sensitive and quantitative detection of disease biomarkers and medical diagnostics in various scenarios.

The accurate prediction of the strength of rocks after high-temperature treatment is important for the safety maintenance of rock in deep underground engineering. Five machine learning (ML) techniques were adopted in this study, i.e. back propagation neural network (BPNN), AdaBoost-based classification and regression tree (AdaBoost-CART), support vector machine (SVM), K-nearest neighbor (KNN), and radial basis function neural network (RBFNN). A total of 351 data points with seven input parameters (i.e. diameter and height of specimen, density, temperature, confining pressure, crack damage stress and elastic modulus) and one output parameter (triaxial compressive strength) were utilized. The root mean square error (RMSE), mean absolute error (MAE) and correlation coefficient (R) were used to evaluate the prediction performance of the five ML models. The results demonstrated that the BPNN shows a better prediction performance than the other models with RMSE, MAE and Rvalues on the testing dataset of 15.4 MPa, 11.03 MPa and 0.9921, respectively. The results indicated that the ML techniques are effective for accurately predicting the triaxial compressive strength of rocks after different high-temperature treatments.

Mesoporous carbon spheres (MCSs) are widely used in the field of pollutants adsorption, energy storage and various biomedicine applications such as targeted delivery vector, phototherapy sensitizers, bioimaging contrast agents, etc. Current synthetic strategies including soft templating and hard templating methods generally have the limits of using expensive surfactants or lack of control over the pore structures. Therefore, the complex and uncontrollable pore structures limit its further clinical application. Herein, we proposed a new synthetic strategy to control the uniformity of pore channel arrangement in MCSs which can modulate the photonic property and the corresponding light controlled drug release property in intelligent drug delivery. The as obtained MCSs with relative uniform pore channel arrangement and long pore channels are demonstrated to have the best NIR light-induced drug release performance. This work provides not only new synthetic method to modulate pore structure characteristics and biophotonic property of MCSs, but also uniform MCSs as novel delivery platforms with advanced controlled release performance.

Background: ATP-Binding Cassette subfamily G member 2 (ABCG2) is a semi-transport protein that plays a key role in human diseases, including bladder cancer and lung cancer, and maybe resistant to chemotherapy drugs. Objective: The present study aimed to determine the role and underlying mechanisms of breast cancer resistance protein (ABCG2) in breast cancer and to study the reversal effect of inhibiting ABCG2 expression on the drug resistance of breast cancer cells and provide new ideas for gene-targeted therapy of breast cancer. Methods: The structure and genomic alterations of ABCG2 were systematically investigated using GeneCards and cBioPortal to reveal the genetic alterations (including amplification and deep deletions) of ABCG2. We performed the correlation between ABCG2 expression and clinicopathological parameters using the data in bc-GenExMiner 4.4. Then, the protein-protein interaction and functional enrichment analysis of ABCG2 were performed based on the STRING, bc-GenExMiner 4.4, and Enrichr databases. Besides, we analyzed the pathway activity of genes that interact with ABCG2 using GSCALite and PharmGKB. Using magnetic nanoparticles polyMAG as the carrier of ABCG2-siRNA, polyMAG-ABCG2-siRNA was transfected into the Doxorubicin (DOX)-resistant breast cancer cell line MCF-7/ADR and directly into the tumors in nude mice. Patent US20150328485 points out that magnetic nanoparticles can be attached to an anti-cancer drug, such as an antibody-based anti-cancer drug. Results: We found a statistically significant correlation between ABCG2 expression and clinicopathological parameters, such as Estrogen Receptor (ER), Progesterone Receptor (PR), and human epidermal growth factor receptor-2 (HER2), and nodal status in breast cancer patients. ABCG2 is closely related to SLC2A9, KIT, ABCG1, and MRPS7, which suggests that these proteins may be functional partners of breast cancer. The expression of ABCG2 is correlated with the activation or inhibition of multiple oncogenic pathways. Moreover, we found that ABCG2 is involved in the DOX signaling pathway. The small interfering RNA (siRNA) carried by magnetic nanoparticles can reduce the expression of ABCG2, thereby significantly improving the therapeutic effect of DOX on tumors. Conclusion: Our findings provide a more in-depth understanding of ABCG2 as a biomarker for predicting DOX-resistance and insights into the development of related therapeutic targets in breast cancer.

Ammonia electro-oxidation is an extremely significant reaction with regards to the nitrogen cycle, hydrogen economy, and wastewater remediation. The design of efficient electrocatalysts for use in the ammonia electro-oxidation reaction (AOR) requires comprehensive understanding of the mechanism and intermediates involved. In this study, aggregation-induced emission (AIE), a robust fluorescence sensing platform, is employed for the sensitive and qualitative detection of hydrazine (N2H4), one of the important intermediates during the AOR. Here, we successfully identified N2H4as a main intermediate during the AOR on the model Pt/C electrocatalyst using 4-(1,2,2-triphenylvinyl)benzaldehyde (TPE-CHO), an aggregation-induced emission luminogen (AIEgen). We propose the AOR mechanism for Pt with N2H4being formed during the dimerization process (NH2coupling) within the framework of the Gerischer and Mauerer mechanism. The unique chemodosimeter approach demonstrated in this study opens a novel pathway for understanding electrochemical reactions in depth.

This article explores the potential ethical hazards of artificial intelligence (AI) on society from an ethical perspective. We introduce the development and application of AI, emphasizing its potential benefits and possible negative impacts. We particularly examine the application of AI in the medical field and related ethical and legal issues, and analyze potential hazards that may exist in other areas of application, such as autonomous driving, finance, and security. Finally, we offer recommendations to help policymakers, technology companies, and society as a whole address the potential hazards of AI. These recommendations include strengthening regulation and supervision of AI, increasing public understanding and awareness of AI, and actively exploring how to use the advantages of AI to achieve a more just, equal, and sustainable social development. Only by actively exploring the advantages of AI while avoiding its negative impacts can we better respond to future challenges.

The rock fracture toughness (RFT) is significantly influenced by thermal treatments. Accurate evaluation of RFT at different temperatures holds great importance in the fields of geotechnical engineering. Current analytical and empirical models, based on our current but incomplete understanding of the fracture mechanics theory, are unable to produce a priori predictions of RFT. As a result, researchers have to rely on experiments, which are often costly and time-consuming, to understand external environment, internal factors and RFT links in rocks. This research explores the potential of employing machine learning (ML) models as an effective approach to address such challenges. Six ML models are presented, including support vector machine (SVM), random forest (RF), back propagation neural network (BPNN), back propagation-particle swarm optimization (BP-PSO), convolutional neural network (CNN), and radial basis function neural network (RBF). These models are applied using a dataset of 297 samples derived from previous studies involving semi-circle bend tests. The dataset encompasses 15 input variables, including sample radius, sample thickness, notch length, support span, inclination angle of the notch, tensile strength, uniaxial compressive strength, density, quartz content, feldspar content, gypsum content, clay content, other minerals, loading rate, and temperature. The results of three statistical metrics (root mean square error (RMSE), coefficient of determination (R2), and mean absolute error (MAE)) confirm that the ML models are able to predict the temperature-dependent RFT in modes I, II and III with high accuracy. The results demonstrated that the SVM model shows a better performance than the other five models. In the case of testing dataset, the RMSE, MAE and R2values for SVM model are 0.1122 MPa·m1/2, 0.0829 MPa·m1/2and 0.9506, respectively. Additionally, feature importance analysis highlights that the temperature and inclination angle are the most influential variables affecting the RFT.

Smart materials and surfaces with tunable functionalities are of great interest, especially for intelligent devices. However, achieving high sensitivity, fast response, simple operations and multi-response is still challenging. Here, a new strategy that utilizes the formation or dissociation of anion–π+interactions to control the non-radiative decay of the molecules on the surface of the aggregation-induced emission (AIE) nanoparticles (NPs) is proposed for the first time. The ultrasensitive modulation of the fluorescence of the AIE NPs can be realized by a trace amount of acid. By using the AIE NPs to functionalize the silicon surface, a smart surface that possesses tunable fluorescence and wettability with an ultrafast response is obtained. Under acid vapor stimuli, multiple wetting status and wettability patterns can be precisely controlled on the AIE luminogen (AIEgen)-functionalized surface due to variation of the surface polarity. The introduced strategy is an innovative way of developing organic fluorescent NPs with tunable multi-functionalities, which can be used to develop ultrasensitive sensors and intelligent devices.

Photoacoustic imaging (PAI) is an attractive imaging modality, which is promising for clinical cancer diagnosis due to its advantages on deep tissue penetration and fine spatial resolution. However, few tumor catalytic/responsive PAI strategies are developed. Here, we design an exosome-like nanozyme vesicle for in vivoH2O2-responsive PAI of nasopharyngeal carcinoma (NPC). The intrinsic peroxidase-like activity of graphene quantum dot nanozyme (GQDzyme) effectively converts the 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) into its oxidized form in the presence of H2O2. The oxidized ABTS exhibits strong near-infrared (NIR) absorbance, rendering it to be an ideal contrast agent for PAI. Thus, GQDzyme/ABTS nanoparticle is a novel type of catalytic PAI contrast agent, which is sensitive to H2O2produced from NPC cells. Furthermore, we develop an approach to construct exosome-like nanozyme vesicle via biomimetic functionalization of GQDzyme/ABTS nanoparticle with natural erythrocyte membrane modified with folate acid. In vivoanimal experiments demonstrated that this exosome-like nanozyme vesicle effectively accumulated in NPC and selectively triggered catalytic PAI for NPC. In addition, our nanozyme vesicle exhibits excellent biocompatibility and stealth ability for long blood circulation. Together, we demonstrate that GQDzyme/ABTS based exosome-like nanozyme vesicle is an ideal nanoplatform for developing deep-tissue tumor-targeted catalytic PAI in vivo.

Apoptosis is an important process for maintaining tissue homeostasis and eliminating abnormal cells in multicellular organisms. Abnormality in apoptosis often leads to severe diseases such as cancers. Better understanding of its mechanisms and processes is therefore important. Accompanying molecular biology events of apoptosis is a series of cellular morphology changes: nucleus condensation, cell shrinkage and rounding, cell surface blebbing, dynamic blebbing, apoptotic membrane protrusions and nucleus fragmentations and finally, the formation and release of apoptotic bodies. It is difficult to detect cellular changes in the early phase of apoptosis due to the subtle changes at this phase. In the current study, we induced apoptosis in HeLa cells with H2O2and used nuclear dye Hoechst 33258, mitochondria, lysosome and cytoplasmic protein specific aggregation-induced emission fluorogens (AIEgens), TPE-Ph-In, 2M-DABS and BSPOTPE to successfully perform live cell multiplexed imaging to investigate early apoptosis cellular events. We showed the gradual dissipation of mitochondria membrane potential until it is nondetectable by TPE-Ph-In. Increased mitophagy detected by TPE-Ph-In and 2M-DABS, condensed nucleus detected by Hoechst 33258, increased permeability and/or reduced integrity of nuclear membrane, and increased intracellular vesicles detected by 2M-DABS are some of the early events of apoptosis.

Powder dusting method is the most practically useful approach for latent fingerprint development in the crime scene. Herein, a general powder dusting method has been explored for latent fingerprint development based on aggregation-induced emission luminogens (AIEgens). A series of tetraphenylethene (TPE) derivatives with multiple diphenylamine (DPA), namely, TPE-DPA, TPE-2DPA and TPE-4DPA, were selected as candidates to dope with magnetic powders and applied for latent fingerprint development. After screening, the magnetic powder 3doped with TPE-4DPA proves to be the best, in terms of fluorescent intensity, resolution and adhesiveness. Afterwards, the magnetic powder 3was applied for visualization of latent fingerprint on various smooth and porous substrates, including glass, stainless steel, leaf, ceram, plastic bag, lime wall, wood and paper money. Specific details, such as island, core, termination and bifurcation, can be clearly observed for the fluorescent fingerprint images.

Nanozymes are nanomaterials exhibiting intrinsic enzyme-like characteristics that have increasingly attracted attention, owing to their high catalytic activity, low cost and high stability. This combination of properties has enabled a broad spectrum of applications, ranging from biological detection assays to disease diagnosis and biomedicine development. Since the intrinsic peroxidase activity of Fe3O4nanoparticles (NPs) was first reported in 2007, >40 types of nanozymes have been reported that possess peroxidase-, oxidase-, haloperoxidase- or superoxide dismutase–like catalytic activities. Given the complex interdependence of the physicochemical properties and catalytic characteristics of nanozymes, it is important to establish a standard by which the catalytic activities and kinetics of various nanozymes can be quantitatively compared and that will benefit the development of nanozyme-based detection and diagnostic technologies. Here, we first present a protocol for measuring and defining the catalytic activity units and kinetics for peroxidase nanozymes, the most widely used type of nanozyme. In addition, we describe the detailed experimental procedures for a typical nanozyme strip–based biological detection test and demonstrate that nanozyme-based detection is repeatable and reliable when guided by the presented nanozyme catalytic standard. The catalytic activity and kinetics assays for a nanozyme can be performed within 4 h. Nanozymes are nanomaterials that possess intrinsic enzyme-like properties and are increasingly used in various biological applications. This protocol describes standardized assays of the catalytic activity and kinetics of peroxidase-like nanozymes.

ABSTRACTThe aim of this study was to construct recombinant adenovirus vector carrying a short hairpin RNA (shRNA) that can exclusively target cyclooxygenase-2 (COX-2) gene expression and observe its inhibitory effect on hepatic fibrosis. We designed and synthesized three oligonucleotide sequences, and cloned those into a shuttle vector, pYr-1.1-hU6-EGFP, after annealing. The restriction-enzyme digestion and sequencing analyses confirmed that the constructed recombinant eukaryotic expression vector was correct. A recombination reaction using LR Clonase was performed for the pYr-1.1-hU6-EGFP COX-2shRNA and the adenovirus vector pAd/BL-DEST to form Ad-COX-2shRNA. The adenoviruses containing the recombinant plasmids were transfected into hepatic stellate cells (HSCs). The transfection efficiency of the three COX-2 shRNAs exceeded 70%. Reverse transcription PCR (RT-PCR) and western blot confirmed that the target gene expression was decreased at the level of mRNA and protein, and the interference effect of COX-2 shRNA-1 was better than that of the other two COX-2 shRNAs. COX-2 shRNA-1 recombinant adenovirus vectors (1 × 109PFU/mL) were injected via the tail vein into rats fed a high-fat diet with a 40% carbon tetrachloride peanut oil lavage, which induced liver fibrosis. Rats were euthanized at the end of the 12th week, and their liver was removed. Liver expression of COX-2 mRNA and protein was detected by RT-PCR and immunohistochemistry, respectively. RT-PCR and immunohistochemistry showed that COX-2 shRNA-1 inhibited COX-2 expression in liver tissue. Hematoxylin/eosin and Masson staining showed that COX-2 shRNA-1 ameliorated the severity of liver fibrosis. The COX-2 shRNA eukaryotic expression vectors were constructed successfully and COX-2 shRNA-1 ameliorated liver fibrosis.

In this study, the concentration gradient inside evaporating binary sessile droplets of 30, 50, and 60 vol % tetrahydrofuran (THF)/water mixtures was investigated. The 5 μL THF/water droplets were evaporated on a transparent hydrophobic substrate. This is the first demonstration of local concentration mapping within an evaporating binary droplet utilizing the aggregation-induced emission material. During the first two evaporation stages of the binary droplet, the local concentration can be directly visualized by the change of fluorescence emission intensity. Time-resolved average and local concentrations can be estimated by using the pre-established function of fluorescence intensity versus water volume fraction.

Triphenylamine (TPA)‐based conjugated hyperbranched poly(aryleneethynylene)s (PAEs), hb‐P1/2, hb‐P1/3, and hb‐P1/4, were synthesized with high molecular weights and good solubilities through Sonogashira coupling reactions. These PAEs exhibited outstanding thermal stabilities and different emission behaviors. Tetraphenylethene (TPE)‐containing hb‐P1/2fluoresced faintly in THF, although its light emission was enhanced by aggregate formation in aqueous media or in thin films, thereby exhibiting an aggregation‐induced emission‐enhancement (AIEE) effect. Whereas 1,1,2,3,4,5‐hexaphenylsilole (HPS)‐bearing hb‐P1/3showed no significant change in emission intensity with increasing water content in aqueous media, hb‐P1/4, which consisted of TPA–fluorenone donor–acceptor groups, presented almost identical absorptions, but both positive and negative solvatochromic emissions in various solvents. A superquenching effect was observed in the picric‐acid‐detection process by using nanosuspensions of hb‐P1/2. All of the polymers possessed good film formability. UV irradiation of the thin films induced simultaneous photobleaching and cross‐linking, thus making them applicable in the fabrication of 2D and 3D patterns. Furthermore, the polymer films also showed high refractive indices, which were tunable upon exposure to UV light.

A silicon‐containing hyperbranched polymer (hb‐P1/2) with σ*–π* conjugation was prepared in a good yield and high molecular weight by rhodium‐catalyzed alkyne polyhydrosilylation of 1,2‐bis(4‐ethynylphenyl)‐1,2‐diphenylethene (1) with tris(4‐dimethylsilylphenyl)amine (2). The polymer was thermally stable, losing merely 5% of its weight when heated to ≈445 °C. Whereas hb‐P1/2was weakly luminescent when molecularly dissolved, it became highly emissive when supramolecularly aggregated, showing an aggregation‐induced emission (AIE) phenomenon. A superamplification effect was observed when the AIE nanoaggregates were used as fluorescent chemosensor for explosive detection: the quenching efficiency was greatly increased in a nonlinear fashion with increasing quencher concentration.

A comprehensive review of the recent development of two-dimensional (2D) PtSe2synthesis strategies has been extensively surveyed.The applications of 2D PtSe2materials in areas, including opto/electric devices, photocatalysis, hydrogen evolution reaction, and sensors, have been reviewed.Current challenges in the development of 2D PtSe2materials are identified, and outlooks toward unexplored research areas are suggested.