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There are disease-causing biohazards in the blood that cannot be treated with modern medicines. Here we show that an intelligently designed safe biomaterial can precisely identify, tow and dump a targeted biohazard from the blood into the small intestine. Positively charged mesoporous silica nanoparticles (MSNs) functionalized with EGFR-targeting aptamers (MSN-AP) specifically recognize and bind blood-borne negatively charged oncogenic exosomes (A-Exo), and tow A-Exo across hepatobiliary layers and Oddi’s sphincter into the small intestine. MSN-AP specifically distinguish and bind A-Exo from interfering exosomes in cell culture and rat and patient blood to form MSN-AP and A-Exo conjugates (MSN-Exo) that transverse hepatocytes, cholangiocytes, and endothelial monolayers via endocytosis and exocytosis mechanisms, although Kupffer cells have been shown to engulf some MSN-Exo. Blood MSN-AP significantly decreased circulating A-Exo levels, sequentially increased intestinal A-Exo and attenuated A-Exo-induced lung metastasis in mice. This study opens an innovative avenue to relocate blood-borne life-threatening biohazards to the intestine. Oncogenic exosomes can circulate in the blood, but their selective removal has not been possible. Here the authors show that aptamer-functionalised mesoporous silica nanoparticles can find to a specific population of circulating exosomes and eliminate them via the hepatobiliary route.

We here propose a novel Raman spectroscopy method that permits the noninvasive measurement of blood glucose concentration. To reduce the effects of the strong background signals produced by surrounding tissue and to obtain the fingerprint Raman lines formed by blood analytes, a laser was focused on the blood in vessels in the skin. The Raman spectra were collected transcutaneously. Characteristic peaks of glucose (1125 cm(-1)) and hemoglobin (1549 cm(-1)) were observed. Hemoglobin concentration served as an internal standard, and the ratio of the peaks that appeared at 1125 cm(-1) and 1549 cm(-1) peaks was used to calculate the concentration of blood glucose. We studied three mouse subjects whose blood glucose levels became elevated over a period of 2 hours using a glucose test assay. During the test, 25 Raman spectra were collected transcutaneously and glucose reference values were provided by a blood glucose meter. Results clearly showed the relationship between Raman intensity and concentration. The release curves were approximately linear with a correlation coefficient of 0.91. This noninvasive methodology may be useful for the study of blood glucose in vivo.

Under the context of urban–rural integration, exploring the complex process and general patterns of rural transformation is a critical issue for advancing sustainable rural development. This study develops a theoretical framework for rural transformation from the perspective of the rural–urban continuum. By analyzing the shifting urban–rural dominance relationships across different periods in township units, we extracted the main paths of rural transformation. Empirical analysis of 46 townships in Suzhou, China from 1990 to 2020 reveals the following key findings: (1) The urban–rural dominance relationships in township units have undergone an evolution from “differentiation to intensification to stabilization” over the past three decades, shaped by two pivotal moments—the Sunan Model and the New Sunan Model. (2) By combining four modes (enhancement, weakening, stabilization, and exchange) across different time periods, three primary paths of rural transformation in Suzhou emerge: a continuous stabilization type, a mid-late enhancement type, and a mid-term weakening type. (3) The spatial heterogeneity of the driving mechanisms is particularly evident in the northern region’s modernization of agriculture, the southern region’s characteristic fisheries, the western region’s localized urbanization, and the eastern region’s integration of industry, city, and population (I-C-P). The diverse paths identified in this study offer a deeper understanding of the simplified macro trend in which rurality weakens and urbanity strengthens, providing valuable insights for the tailored promotion of rural revitalization.

DNA‐binding proteins, including transcription factors (TFs), play essential roles in various cellular processes and pathogenesis of diseases, deeming to be potential therapeutic targets. However, these proteins are generally considered undruggable as they lack an enzymatic catalytic site or a ligand‐binding pocket. Proteolysis‐targeting chimera (PROTAC) technology has been developed by engineering a bifunctional molecule chimera to bring a protein of interest (POI) to the proximity of an E3 ubiquitin ligase, thus inducing the ubiquitination of POI and further degradation through the proteasome pathway. Here, the development of oligonucleotide‐based PROTAC (O'PROTACs), a class of noncanonical PROTACs in which a TF‐recognizing double‐stranded oligonucleotide is incorporated as a binding moiety of POI is reported. It is demonstrated that O'PROTACs of lymphoid enhancer‐binding factor 1 (LEF1) and ETS‐related gene (ERG), two highly cancer‐related transcription factors, successfully promote degradation of these proteins, impede their transcriptional activity, and inhibit cancer cell growth in vitro and in vivo. The programmable nature of O'PROTACs indicates that this approach is also applicable to destruct other TFs. O'PROTACs not only can serve as a research tool but also can be harnessed as a therapeutic arsenal to target DNA binding proteins for effective treatment of diseases such as cancer. DNA binding proteins including transcription factors remain as challenging targets in drug discovery. oligonucleotide‐based proteolysis‐targeting chimeras (O'PROTACs), which employ unique DNA sequences as natural “ligand” of targeting proteins, are developed to effectively destruct lymphoid enhancer‐binding factor 1 (LEF1) and ETS‐related gene (ERG) and inhibit prostate cancer cell growth. O'PROTAC represents an attractive approach for treatment of diseases including cancer.

Recent development of new immune checkpoint inhibitors has been particularly successfully in cancer treatment, but still the majority patients fail to benefit. Converting resistant tumors to immunotherapy sensitive will provide a significant improvement in patient outcome. Here we identify Mi-2β as a key melanoma-intrinsic effector regulating the adaptive anti-tumor immune response. Studies in genetically engineered mouse melanoma models indicate that loss of Mi-2β rescues the immune response to immunotherapy in vivo. Mechanistically, ATAC-seq analysis shows that Mi-2β controls the accessibility of IFN-γ-stimulated genes (ISGs). Mi-2β binds to EZH2 and promotes K510 methylation of EZH2, subsequently activating the trimethylation of H3K27 to inhibit the transcription of ISGs. Finally, we develop an Mi-2β-targeted inhibitor, Z36-MP5, which reduces Mi-2β ATPase activity and reactivates ISG transcription. Consequently, Z36-MP5 induces a response to immune checkpoint inhibitors in otherwise resistant melanoma models. Our work provides a potential therapeutic strategy to convert immunotherapy resistant melanomas to sensitive ones. Mi-2β is an enzyme of the chromodomain helicase DNA family with roles in chromatin assembly, genomic stability and gene repression. Here the authors report that Mi-2β promotes immune evasion by activating EZH2 methylation and that loss of Mi-2β or its inhibition promote anti-tumor immune responses in preclinical melanoma models.

To accurately predict the remaining useful life (RUL) of rolling bearings under limited data and fluctuating load conditions, we propose a new method for constructing health indicators (HI) and a transfer learning prediction framework, which integrates Convolutional Neural Networks (CNN), Gated Recurrent Units (GRU), and Multi-head attention (MHA). Firstly, we combined Convolutional Neural Networks (CNN) with Gated Recurrent Units (GRU) to fully extract temporal and spatial features from vibration signals. Then, the Multi-head attention mechanism (MHA) was added for weighted processing to improve the expression ability of the model. Finally, a new method for constructing Health indicators (HIs) was proposed in which the noise reduction and normalized vibration signals were taken as a HI, the L1 regularization method was added to avoid overfitting, and the model-based transfer learning method was used to realize the RUL prediction of bearings under small samples and variable load conditions. Experiments were conducted using the PHM2012 dataset from the FEMTO-ST research institute and XJTU-SY dataset. Three sets of 12 migration experiments were conducted under three different operating conditions on the PHM2012 dataset. The results show that the average RMSE of the proposed method was 0.0443, indicating high prediction accuracy under variable loads and small sample conditions. Three different operating conditions and two sets of four migration experiments were conducted on the XJTU-SY dataset, and the results show that the average RMSE of the proposed method was 0.0693, verifying the good generalization of the model under variable load conditions. In summary, the proposed HI construction method and prediction framework can effectively reduce the differences between features, with high stability and good generalizability.

Recent global deregulation of ginseng as the table food raises our concern about the possible ginseng-warfarin interaction that could be life-threatening to patients who take warfarin for preventing fatal strokes and thromboembolism while using ginseng products for bioenergy recovery. Here we show that quality-control ginsenosides, extracted from ginseng and containing its major active ingredients, produce dose- and time-dependent antagonism in rats against warfarin’s anti-coagulation assessed by INR and rat thrombosis model. The interactions between ginsenosides and warfarin on thrombosis, pharmacokinetics, activities of coagulation factors and liver cytochrome P450 isomers are determined by using thrombosis analyzer, UPLC/MS/MS, ELISA and real-time PCR, respectively. The antagonism correlates well with the related pharmacokinetic interaction showing that the blood plateaus of warfarin reached by one-week warfarin administration are significantly reduced after three-week co-administration of warfarin with ginsenosides while 7-hydroxywarfarin is increased. The one-week warfarin and three-week warfarin-ginsenosides regimen result in restoring the suppressed levels by warfarin of the coagulating factors II, VII and protein Z, and significantly enhance activities of P450 3A4 and 2C9 that metabolize warfarin. The present study, for the first time, provides the solid evidence to demonstrate the warfarin-ginsenoside interaction, and warns the warfarin users and regulation authorities of the dangerous interaction.

Federated learning (FL) is a distributed machine learning approach that can enable Internet of Things (IoT) edge devices to collaboratively learn a machine learning model without explicitly sharing local data in order to achieve data clustering, prediction, and classification in networks. In previous works, some online multi-armed bandit (MAB)-based FL frameworks were proposed to enable dynamic client scheduling for improving the efficiency of FL in underwater wireless IoT networks. However, the security of online dynamic scheduling, which is especially essential for underwater wireless IoT, is increasingly being questioned. In this work, we study secure dynamic scheduling for FL frameworks that can protect against malicious clients in underwater FL-assisted wireless IoT networks. Specifically, in order to jointly optimize the communication efficiency and security of FL, we employ MAB-based methods and propose upper-confidence-bound-based smart contracts (UCB-SCs) and upper-confidence-bound-based smart contracts with a security prediction model (UCB-SCPs) to address the optimal scheduling scheme over time-varying underwater channels. Then, we give the upper bounds of the expected performance regret of the UCB-SC policy and the UCB-SCP policy; these upper bounds imply that the regret of the two proposed policies grows logarithmically over communication rounds under certain conditions. Our experiment shows that the proposed UCB-SC and UCB-SCP approaches significantly improve the efficiency and security of FL frameworks in underwater wireless IoT networks.

Concrete is widely used in large-scale hydraulic structures, which often need to undergo multiple pouring operations due to construction demands, temperature-induced shrinkage phenomena, and structural reinforcement and repair, which in turn creates the bonding surface of old and new concrete. Therefore, it is of great significance to study the strength of the bond between old and new concrete. We designed and completed a split tension test to investigate the evolution of the tensile strength of concrete joint surfaces with age at early ages. The test groups included three sets of matured concrete aged 3 days, 5 days, and 10 days, respectively. Within each group, multiple test specimens were prepared with different ages of the interface, ranging from 1 day to 15 days. The test utilized ready-mixed concrete materials from a commercial batching plant. To ensure uniform and standard roughness of the interface between new and matured concrete, a method employing non-destructive surface roughening tapes was employed. During the test, each specimen was subjected to tensile failure at its corresponding age. The maximum load applied by the testing machine at the point of tensile failure was recorded for each age group. Based on the fundamental principles of material mechanics and relevant formulas, the tensile strength of the interface at different ages was determined for each test group. The obtained data were then used to fit a curve representing the relationship between the early-age tensile strength of concrete and its age, using MATLAB R2020b software. The results show that there is a small increase in the tensile strength of the bonding surface as the age of the old test blocks is increased. This experiment revealed the changing pattern of early-age tensile strength of concrete at the interface with age, providing a basis for accurately simulating the mechanical properties of the interface during numerical simulations. Then, based on the existing temperature-controlled simulation program, a simplified simulation and calculation method of concrete cracking is proposed to make it possible to determine the tensile cracking (vertical cracking) when the stress exceeds the standard. The validity is verified by simulation calculations of a simplified model, using the tensile strength curves obtained from the tests.

Nanotechnology has been extensively explored for drug delivery. Here, we introduce the concept of a nanodrug based on synergy of photothermally-activated physical and biological effects in nanoparticle-drug conjugates. To prove this concept, we utilized tumor necrosis factor-alpha coated gold nanospheres (Au-TNF) heated by laser pulses. To enhance photothermal efficiency in near-infrared window of tissue transparency we explored slightly ellipsoidal nanoparticles, its clustering and laser-induced nonlinear dynamic phenomena leading to amplification and spectral sharpening of photothermal and photoacoustic resonances red-shifted relatively to linear plasmonic resonances. Using a murine carcinoma model, we demonstrated higher therapy efficacy of Au-TNF conjugates compared to laser and Au-TNF alone or laser with TNF-free gold nanospheres. The photothermal activation of low toxicity Au-TNF conjugates, which are in phase II trials in humans, with a laser approved for medical applications opens new avenues in the development of clinically relevant nanodrugs with synergistic antitumor theranostic action.