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Abstract Background Recent Convolutional Neural Networks (CNNs) perform low-error reconstruction in fast Magnetic Resonance Imaging (MRI). Most of them convolve the image with kernels and successfully explore the local information. Nonetheless, the non-local image information, which is embedded among image patches relatively far from each other, may be lost due to the limitation of the receptive field of the convolution kernel. We aim to incorporate a graph to represent non-local information and improve the reconstructed images by using the Graph Convolutional Enhanced Self-Similarity (GCESS) network. Methods First, the image is reconstructed into the graph to extract the non-local self-similarity in the image. Second, GCESS uses spatial convolution and graph convolution to process the information in the image, so that local and non-local information can be effectively utilized. The network strengthens the non-local similarity between similar image patches while reconstructing images, making the reconstruction of structure more reliable. Results Experimental results on in vivo knee and brain data demonstrate that the proposed method achieves better artifact suppression and detail preservation than state-of-the-art methods, both visually and quantitatively. Under 1D Cartesian sampling with 4 × acceleration (AF = 4), the PSNR of knee data reached 34.19 dB, 1.05 dB higher than that of the compared methods; the SSIM achieved 0.8994, 2% higher than the compared methods. Similar results were obtained for the reconstructed images under other sampling templates as demonstrated in our experiment. Conclusions The proposed method successfully constructs a hybrid graph convolution and spatial convolution network to reconstruct images. This method, through its training process, amplifies the non-local self-similarities, significantly benefiting the structural integrity of the reconstructed images. Experiments demonstrate that the proposed method outperforms the state-of-the-art reconstruction method in suppressing artifacts, as well as in preserving image details.

The electron-phonon (el-ph) and phonon-phonon interactions play a key role in determining electronic and thermal transport properties, respectively, in promising two-dimensional (2D) semiconductor devices. In this study, we investigated el-ph interactions using Wannier-Fourier interpolation method and renormalized phonon scattering considering finite-temperature effects in Bi2TeSe2 monolayer. The results show that the optical phonon modes dominate the carrier scattering, where level repulsion induced by crystal field splitting and spin-orbit coupling (SOC) effect effectively suppresses intervalley scattering, leading to high hole mobility. Moreover, the strong anharmonicity in Bi2TeSe2 monolayer results in the temperature-dependent softening of its optical phonons, along with a corresponding variation in interatomic force constants (IFCs). As a result, the lattice thermal conductivity is remarkably low and exhibits weak temperature dependence. Finally, the predicted dimensionless thermoelectric figure of merit exceeds unity in the range of 200–800 K, indicating the potential of Bi2TeSe2 monolayer for thermoelectric applications. This work provides new insights into the elimination of intervalley scattering by crystal field splitting and SOC effects, and paves the way for the evaluation of thermoelectric properties of materials with complex scattering mechanisms and strong anharmonicity.

Abstract As a potential solution to improve wireless security, specific emitter identification is a lightweight access authentication technology. However, the existed deep learning‐based specific emitter identification methods are highly dependent on the training sample size, leading to serious overfitting problem when the training samples are inadequate, which obstructs their practical applications. To address this issue, an innovative data augmentation method to effectively expand the sample size is proposed. In this design, after data preprocessing, a random integration based data augmentation is applied to integrate several initial samples and generate new samples. Furthermore, compared with the existed methods, chaotic sequences are utilized to randomly set the integration weight of each initial sample, and thus enhancing the diversity of augmented samples. The superiority of the proposed chaotic integration‐based data augmentation method in accuracy, generalization ability and robustness is validated by the hardware implementation on digital mobile radio portable radios.

Multi-contrast magnetic resonance imaging can bring convenience to medical diagnosis and decision-making. However, due to the long acquisition time, the images are easily disturbed by motion artifacts. To accelerate MRI, the approach of under-sampling k-space data has been used. This approach leads to the deterioration of MR image quality. To restore images, we proposed a Residual Convolution Swin Transformer Block (RCSTB), which includes local feature representation in a convolutional neural network module and global long-term feature extraction in the transformer. Additionally, similarities reflected by structure information in high frequency among multi-contrast magnetic resonance images are separated and are fused with a cross-self-attention mechanism to assist reconstruction of under-sampled magnetic resonance images. The residual information in frequency domain separation from the RCSTB reconstructed images was used to complete the final reconstruction. Experimental results show that our method outperforms state-of-art in Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM), and Relative L2 Norm Error (RLNE) under different sampling patterns. The reconstruction of details has achieved visible improvements to the naked eye.

Particle surface thermal field (PSTF) is an inhomogeneous thermal field that concentrates the heat effect on the surface of particles, and it can be utilized to fabricate composite materials with large differences in physical properties. However, it is difficult to form PSTF with large temperature gradients to meet the preparation requirement of materials with extreme differences in physical properties. In our work, a PSTF is proposed and realized by an ultra-high pulse pressure (UHPP) to prepare W–Al composite, the PSTF has a heating effect on the powder interface with a low-temperature interior of the powders. The combination of ex-situ microstructural observation and in-situ molecular dynamic simulation microstructural snapshot is used to demonstrate the densification mechanism. The PSTF is characterized as the temperature higher than 1200 °C on the W–Al powders interface but lower than 200 °C interior of the powders. The densification mechanisms are explained as interfacial jet penetration, interfacial friction welding and interfacial melting. In addition, interfacial temperature distribution creating gradient pressure on the W–Al interface illustrated the generation of gradient Al grains on the W surface, thus creating a high mechanical micro-hardness of 249.8 Hv and compressive strength of 473.2 MPa for the W–Al composite.

Adolescent binge drinking leads to long-lasting disorders of the adult central nervous system, particularly aberrant hippocampal neurogenesis. In this study, we applied in vivo fluorescent tracing using NestinCreERT2::Rosa26-tdTomato mice and analyzed the endogenous neurogenesis lineage progression of neural stem cells (NSCs) and dendritic spine formation of newborn neurons in the subgranular zone of the dentate gyrus. We found abnormal orientation of tamoxifen-induced tdTomato+ (tdTom+) NSCs in adult mice 2 months after treatment with EtOH (5.0 g/kg, i.p.) for 7 consecutive days. EtOH markedly inhibited tdTom+ NSCs activation and hippocampal neurogenesis in mouse dentate gyrus from adolescence to adulthood. EtOH (100 mM) also significantly inhibited the proliferation to 39.2% and differentiation of primary NSCs in vitro. Adult mice exposed to EtOH also exhibited marked inhibitions in dendritic spine growth and newborn neuron maturation in the dentate gyrus, which was partially reversed by voluntary running or inhibition of the mammalian target of rapamycin-enhancer of zeste homolog 2 pathway. In vivo tracing revealed that EtOH induced abnormal orientation of tdTom+ NSCs and spatial misposition defects of newborn neurons, thus causing the disturbance of hippocampal neurogenesis and dendritic spine remodeling in mice.

Highlights An ionization-engineered hydrogel with electronegativity polymer chains to impede salt ions was designed. The hydrogel evaporator exhibited salt impedance in 20 wt% brine for 15 days with a high evaporation efficiency of 95.6%. An all-day high-salinity brine treatment with zero liquid discharge was proposed.

Abstract With the rapid development of wind power, the pressure on peak regulation of the power grid is increased. Electrochemical energy storage is used on a large scale because of its high efficiency and good peak shaving and valley filling ability. The economic benefit evaluation of participating in power system auxiliary services has become the focus of attention since the development of grid-connected hundred megawatt-scale electrochemical energy storage systems (ESS). Based on the relationship between power and capacity in the process of peak shaving and valley filling, a dynamic economic benefit evaluation model of peak shaving assisted by hundred megawatt-scale electrochemical ESS considering the equivalent life of the battery is proposed. The model considers the investment cost of energy storage, power efficiency, and operation and maintenance costs, and analyzes the dynamic economic benefits of different energy storage technologies participating in the whole life cycle of the power grid. Then, according to the current ESS market environment, the auxiliary service compensation price, peak-valley price difference and energy storage cost unit price required to make the energy storage technology achieve the balance of payments are calculated, and the economic balance points of different energy storage types are clarified. Finally, based on the measured data of different provincial power grids, the economies of six energy storage types applied to three provincial power grids are compared and analyzed, and the rationality and effectiveness of the relevant models proposed are verified. The work has theoretical guiding significance for the economic benefit evaluation of hundred megawatt-scale electrochemical energy storage.

To exploit aquatic animals’ feed resources and functional ingredients and additives, this experiment investigated the effects (a 2 × 2 factorial trial) and mechanism of woody plants and probiotics on Nile tilapia. Each treatment group was randomly assigned triplicate nets of 40 fish (initial body weight of 35.04 ± 0.01 g) in 12 tanks for 56 days. Fish were fed four diets, including a CON–CON diet (with no supplementation) and CON–Ba (basal diet + 1 × 107 CFU/g B. amyloliquefaciens), MO-CON (basal diet + 10% Moringa oleifera) and MO-Ba (basal diet + 1 × 107 CFU/g B. amyloliquefaciens + 10% Moringa oleifera) until apparent satiation (2 meals/day). The results showed that the MO diet had a lower feed conversion ratio than the non-MO diets (P

Abstract Background N6-methyladenosine (m6A) is a universal RNA modification pattern regulated by multiple m6A regulators. In osteoarthritis (OA), m6A regulators influence disease progression by regulating cartilage degradation. However, the function of m6A regulators in synovial tissue remains unclear. In this work, we investigated the biological significance of m6A regulators in osteoarthritic synovitis. Methods Datasets were acquired from Gene Expression Omnibus. Differential analysis of merged data identified the differentially expressed m6A regulators. Machine learning models were used to evaluate genetic importance. To predict disease risk, a nomogram was constructed based on above m6A regulators. Cluster analysis divided the OA sample into different subgroups. Immune infiltration revealed the immune m6A regulators, which were validated using clinical samples. Eventually, a competing endogenous RNA (ceRNA) network was constructed. Results We acquired five differentially expressed m6A regulators and a random forest model. The nomogram accurately predicted disease risk. We identified 122 differentially expressed genes between two m6A subgroups. The analysis of immune infiltration showed that YTHDF2 was an immune-related m6A regulator closely related with macrophages. In clinical samples, the protein and mRNA contents of YTHDF2 were consistent with the results of bioinformatic analysis. The ceRNA network based on YTHDF2 revealed 75 lncRNA nodes and 19 miRNA nodes. Conclusion YTHDF2 has a high diagnostic value in the synovitis of OA and significantly influences the immune status of patients. Hence, YTHDF2, a critical m6A regulator, may provide a biomarker for diagnosis and immune therapy of osteoarthritic synovitis.

A 12-wk trial was conducted to compare the tolerance of tilapia to high carbohydrate and high lipid diets. Three isonitrogenous and isoenergetic diets, whose carbohydrate and lipid levels were the following: 35.0% and 8% (control), 44.2% and 4% (D1, high carbohydrate), and 25.8% and 12% (D2, high lipid), respectively. Three hundred tilapias (27 ± 0.11 g) were fed the diets for 10 wk (4 replicates per group); 72 fish from the D1 group were continually fed the D1 (D1D1) and 72 fish from the D2 were continually fed the D2 (D2D2) diet for 2 wk (3 replicates each group) to evaluate the tilapia's capacity to tolerate high carbohydrate and high lipid diets, respectively. Another 36 fish from D1 group were continually fed D2 (D1D2) for comparison with D1D1 and D2D2 groups. In phase 1, hepatosomatic index, liver triglycerides (TG), glucose tolerance (GT) and crude protein in the whole body in D1 group were higher than those in D2 group (P

Two-dimensional materials are promising platforms for the realization of an excitonic insulator state. Here the authors report evidence for an excitonic insulator in a single-layer ZrTe2 based on ARPES measurements.

This paper introduces the Long Short-Term Memory with Dual-Stage Attention (LSTM-MSA) model, an approach for analyzing electromyography (EMG) signals. EMG signals are crucial in applications like prosthetic control, rehabilitation, and human-computer interaction, but they come with inherent challenges such as non-stationarity and noise. The LSTM-MSA model addresses these challenges by combining LSTM layers with attention mechanisms to effectively capture relevant signal features and accurately predict intended actions. Notable features of this model include dual-stage attention, end-to-end feature extraction and classification integration, and personalized training. Extensive evaluations across diverse datasets consistently demonstrate the LSTM-MSA’s superiority in terms of F1 score, accuracy, recall, and precision. This research provides a model for real-world EMG signal applications, offering improved accuracy, robustness, and adaptability.

The attention mechanism is one of the most influential ideas in the deep learning community, which has shown excellent efficiency in various computer vision tasks. Thus, this article proposes the convolution neural network method with the attention mechanism to enhance the feature extraction of light detection and ranging (LiDAR) data. Meanwhile, our elaborately designed cascaded block contains a short path architecture beneficial for multistage information exchange. With the full exploitation of elevation information from LiDAR data and efficient utilization of the spatial-spectral information underlying hyperspectral data, our method provides a novel solution for multimodal feature fusion. Experiments are conducted on the LiDAR and hyperspectral dataset provided by the 2013 IEEE GRSS Data Fusion Contest and multisource Trento dataset to demonstrate the effectiveness of the proposed method. The experimental results have shown the superior results of the proposed method on both LiDAR and multimodality remote sensing data in comparison with several popular baselines.

In the machining process of 440C stainless steel using ball-end milling, the generation of machined traces is an inevitable outcome. Traditional polishing methods, when applied to the milling surfaces of small conical holes, exhibit significant limitations. However, the application of nanosecond pulsed laser polishing while maintaining dimensional integrity has proven effective in mitigating these issues. The parameters for the laser and scanning strategy were empirically determined through planar experiments. The results showed a reduction in surface roughness to a minimum value, representing a decrease of approximately 41.7%. Further validation experiments were conducted on the ball-milled surface of small conical holes. The rate of roughness reduction in these experiments surpassed that of planar surface polishing with an improvement of approximately 73.6%. The scanning strategy’s applicability was confirmed, and the post-polishing surface morphology was found to be largely in line with the prediction. The remelt layer and heat-affected zone resulting from nanosecond laser polishing were observed to be below 5 μm, significantly preserving the dimensional integrity of the conical hole’s internal surface. Moreover, nanosecond laser polishing was found to substantially enhance the surface hardness of the material, with an increase ranging from 100% to 180%. This study underscores the efficacy of nanosecond laser polishing in enhancing the internal surface of small conical holes, thereby improving the surface properties. Consequently, this method presents a reliable solution for the removal of machined traces from complex internal surfaces.

The development of a dynamic network for commodity polymer systems via feasible methods has been explored in the context of a society-wide focus on the environment and sustainability. Herein, we demonstrate an adaptive post-curing method used to build a self-healable network of waterborne polyurethane–acrylate (WPUA) composite latex. The composite latex was synthesized via the miniemulsion polymerization of acrylates in the dispersion of waterborne polyurethane (PU), with commercial acetoacetoxyethyl methacrylate (AAEM) serving as the functional monomer. Then, a dynamic disulfide (S–S)-bearing diamine was applied as the crosslinking agent for the post-curing of the hybrid latex via keto-amine condensation, which occurred during the evaporation of water for film formation. It was revealed that the microphase separation in the hybrid films was suppressed by the post-curing network. The mechanical performance exhibited a high reliability as regards the contents of the crosslinking agents. The reversible exchange of S–S bonds meant that the film displayed associative covalent-adaptive networks in the range of medium temperature in stress relaxation tests, and ≥95% recovery in both the stress and the strain was achieved after the cut-off films were self-healed at 70 °C for 2 h. The rebuilding of the network was also illustrated by the >80% recovery in the elongation at break of the films after three crushing–hot pressing cycles. These findings offer valuable insights, not only endowing the traditional WPUA with self-healing and reprocessing properties, but broadening the field of study of dynamic networks to polymer hybrid latex.

ABSTRACT Rhizoctonia cerealis is the pathogen of wheat sharp eyespot, which occurs throughout temperate wheat-growing regions of the world. In this project, the genomes of viruses from four strains of R. cerealis were analyzed based on Illumina high-throughput transcriptome sequencing (RNA-Seq) data. After filtering out reads that mapped to the fungal genome, viral genomes were assembled. In total, 131 virus-like sequences containing complete open reading frames (ORFs), belonging to 117 viruses, were obtained. Based on phylogenetic analysis, some of them were identified as novel members of the families Curvulaviridae, Endornaviridae, Hypoviridae, Mitoviridae, Mymonaviridae, and Phenuiviridae, while others were unclassified viruses. Most of these viruses from R. cerealis were significantly different from the viruses already reported. We propose the establishment of a new family, Rhizoctobunyaviridae, and two new genera, Rhizoctobunyavirus and Iotahypovirus. We further clarified the distribution and coinfection of these viruses in the four strains. Surprisingly, 39 viral genomes of up to 12 genera were found in strain R1084. Strain R0942, containing the fewest viruses, also contained 21 viral genomes belonging to 10 genera. Based on the RNA-Seq data, we estimated the accumulation level of some viruses in host cells and found that the mitoviruses in R. cerealis generally have very high accumulation. In conclusion, in the culturable phytopathogenic fungus R. cerealis, we discovered a considerable diversity of mycoviruses and a series of novel viruses. This study expands our understanding of the mycoviral diversity in R. cerealis and provides a rich resource for the further use of mycoviruses to control wheat sharp eyespot. IMPORTANCE Rhizoctonia cerealis is a binucleate fungus that is widely distributed worldwide and can cause sharp eyespot disease in cereal crops. In this study, 131 virus-like sequences belonging to 117 viruses were obtained based on analysis of high-throughput RNA-Seq data from four strains of R. cerealis. Many of these viruses were novel members of various virus families, while others were unclassified viruses. As a result, a new family named Rhizoctobunyaviridae and two new genera, Rhizoctobunyavirus and Iotahypovirus, were proposed. Moreover, the discovery of multiple viruses coinfecting a single host and the high accumulation levels of mitoviruses have shed light on the complex interactions between different viruses in a single host. In conclusion, a significant diversity of mycoviruses was discovered in the culturable phytopathogenic fungus R. cerealis. This study expands our understanding of mycoviral diversity, and provides a valuable resource for the further utilization of mycoviruses to control wheat diseases.

Objective Evidence of therapy for dysfunctional coronary circulation in patients with ST-segment elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (pPCI) is limited. This study was performed to compare the effects of atorvastatin and rosuvastatin on dysfunctional coronary circulation. Methods This retrospective study enrolled 597 consecutive patients with STEMI who underwent pPCI in 3 centers from June 2016 to December 2019. Dysfunctional coronary circulation was defined by the thrombolysis in myocardial infarction (TIMI) grade and the TIMI myocardial perfusion grade (TMPG). Logistic regression analysis was used to evaluate the impact of different statin types on dysfunctional coronary circulation. Results The incidence of TIMI no/slow reflow did not differ between the two groups, but the incidence of TMPG no/slow reflow was significantly lower in the atorvastatin than rosuvastatin group (44.58% vs. 57.69%, respectively). After multivariate adjustment, the odds ratio with 95% confidence interval of rosuvastatin was 1.72 (1.17–2.52) for after pretreatment TMPG no/slow reflow and 1.73 (1.16–2.58) for after stenting TMPG no/slow reflow. Atorvastatin and rosuvastatin showed no significant differences in clinical outcomes during hospitalization. Conclusions Compared with rosuvastatin, atorvastatin was associated with better coronary microcirculatory perfusion in patients with STEMI who underwent pPCI.

While homodimeric prodrug assemblies can improve drug loading and limit toxicity in cancer therapy, bioactivation within the target site is limited. Here, the authors introduce a hybrid chalcogen bond linker to a docetaxel dimeric prodrug nanoassembly and demonstrate its improved selfassembly, redox-responsivity and antitumor efficacy.

Cables are very important in urban power system due to the small occupied area and excellent electrical properties. However, the breakage defect caused by manufacturing errors and improper installation can lead to great loss to the power system. Thus, the localization and assessment of breakage defect is necessary. In this paper, a non-destructive method based on time–frequency​ domain reflectometry is utilized, and the position and degree of breakage defect can be obtained by the peaks of the localization curve. Besides, pseudo Wigner–Ville distribution is proposed to avoid the cross-term interference problem in time–frequency domain reflectometry. In experiments, breakage defects of different degrees were caused to the same position of the target cable. The defects are localized accurately with errors less than 1% of the entire cable length, and as the degree of damage increases, the peak value of the assessment curve at the defect becomes larger accordingly.

Modern power systems contain different types of cables and that makes it important to diagnose defects before they result in faults. Existing cable inspection methods, such as dielectric loss measurement and partial discharge, still fail to detect and locate weak cable defects. This paper presents a novel non-destructive method for detecting wear and aging defects based on broadband impedance spectroscopy (BIS) is proposed. A digital model of the cable distribution parameters is developed in this paper. The effects of different angular wear defects on the impedance spectroscopy were compared, and the degree of defects was successfully distinguished by discrete Fourier transform (DFT). The severity of the defect can be determined from the difference in peak height at the defect location after normalization. By using DFT and the Chebyshev Window it was also possible to identify two defects in the cable within 0.47% deviation of the defect position.

In order to better control the quality of Flos Puerariae (FP), qualitative and quantitative analyses were initially performed by using chemical fingerprint and chemometrics methods in this study. First, the fingerprint of FP was developed by HPLC and the chemical markers were screened out by similarity analysis (SA), hierarchical clustering analysis (HCA), principal components analysis (PCA), and orthogonal partial least squares discriminant analysis (OPLS-DA). Next, the chemical constituents in FP were profiled and identified by HPLC coupled to Fourier transform ion cyclotron resonance mass spectrometry (HPLC-FT-ICR MS). Then, the characteristic constituents in FP were quantitatively analyzed by HPLC. As a result, 31 common peaks were assigned in the fingerprint and 6 of them were considered as qualitative markers. A total of 35 chemical constituents were detected by HPLC-FT-ICR MS and 16 of them were unambiguously identified by comparing retention time, UV absorption wavelength, accurate mass, and MS/MS data with those of reference standards. Subsequently, the contents of glycitin, genistin, tectoridin, glycitein, genistein, and tectorigenin in 13 batches of FP were detected, ranging from 0.4438 to 11.06 mg/g, 0.955 to 1.726 mg/g, 9.81 to 57.22 mg/g, 3.349 to 41.60 mg/g, 0.3576 to 0.989 mg/g, and 2.126 to 9.99 mg/g, respectively. In conclusion, fingerprint analysis in combination with chemometrics methods could discover chemical markers for improving the quality control standard of FP. It is expected that the strategy applied in this study will be valuable for further quality control of other traditional Chinese medicines.

Abstract Background p16, p53, and proliferating cell nuclear antigen (pcna) genes play significant roles in many chromatin modifications and have been found to be highly expressed in a variety of tumor tissues. Therefore, they have been used as target genes for some tumor therapies. However, the differential expressions of the p16, p53, and pcna genes in human sarcomas and their effects on prognosis have not been widely reported. Methods The Oncomine dataset was used to analyze the transcription levels of p16, p53, and pcna genes, and the gene expression profile interactive analysis (GEPIA) dataset was used to analyze the differential expressions of p16, p53, and pcna. The expression levels of p16, p53, and pcna were further analyzed by Western Blotting. GEPIA and Kaplan–Meier analyses were used to analyze the prognostic value of p16, p53, and pcna. Furthermore, p16, p53, and pcna gene mutations and their association with overall survival (OS) and disease-free survival (DFS) were analyzed using cBioPortal datasets. In addition, genes co-expressed with p16, p53, and pcna were analyzed using Oncomine. The DAVID dataset was used to analyze the functional enrichment of p16, p53, pcna, and their co-expressed genes by Gene Ontology (GO) and Metascape were used to construct a network map. Finally, the immune cell infiltration of p16, p53, and pcna in patients with sarcoma was reported by Tumor Immune Estimation Resource (TIMER). Results p16, p53, and pcna were up-regulated in human sarcoma tissues and almost all sarcoma cell lines. Western Blotting showed that the expression of p16, p53, and pcna was elevated in osteosarcoma cell lines. The expression of pcna was correlated with OS, the expression of p16, p53, and pcna was correlated with relapse-free survival, and the genetic mutation of p16 was negatively correlated with OS and DFS. We also found that p16, p53, and pcna genes were positively/negatively correlated with immune cell infiltration in sarcoma. Conclusions The results of this study showed that p16, p53, and pcna can significantly affect the survival and immune status of sarcoma patients. Therefore, p16, p53, and pcna could be used as potential biomarkers of prognosis and immune infiltration in human sarcoma and provide a possible therapeutic target for sarcoma.

The water depth bias of LiDAR point cloud data has to be corrected. The previous models, which used the fixed parameters for an entire water area, cannot efficiently correct the bias due to the different water environments. Therefore, this paper develops an adaptive model for the correction of the water depth bias. A coordinate system, in which the water depth is taken as the X-axis and the water depth bias is taken as the Y-axis, is defined. All of the sample points are normalized, and then projected into the defined coordinate system according to their water depths and water depth biases. Second, the scatter points are clustered into several different clusters using the developed subdivision algorithm. With the clusters, an entire water area is subdivided into several sub-regions. Finally, each sub-region is fitted using a model, which is used to correct the water depth bias. Experimental verification and comparison analysis are conducted in three different environments: an indoor tank, an outdoor pond and the Beihai sea. The experimental results demonstrate that the Mean Absolute Error (MAE) and the Root Mean Squared Error (RMSE) from the adaptive model are reduced by approximately 61% and 59%, respectively, relative to those from the traditional models. Therefore, it can be concluded that the proposed model can adapt to changes of the different water environments and achieve a higher accuracy for water depth bias correction than traditional methods do.

Wetlands provide important ecosystem services, such as water conservation, biodiversity protection, and carbon sequestration. The Zoige alpine wetland is the largest high-altitude swamp in the world and plays a critical role in regional ecological balance and climate change. However, little is known about the fate of its soil organic carbon (SOC) storage. In this study, we estimated the degradation status of the wetland over the past 35 years and used machine learning to investigate the dynamics and driving factors of SOC at different soil depths of the Zoige wetland in 1985, 2000, and 2020. We also simulated the future SOC balance under different scenarios. The results showed that the area of Zoige wetland has degraded by 378.71 km2 in the past 35 years. Increased precipitation and solar radiation offset the adverse effects of global warming, making the soil act as a carbon sink in the past 35 years. The total SOC storage of the wetland soils in 1985, 2000, and 2020 was estimated to be 2.03 Pg, 2.05 Pg, and 2.21 Pg, respectively, with 46.95% of SOC distributed in the subsoil layers. Climate change was the most important driving factor controlling the SOC storage of the Zoige wetland, explaining 51.33% of the SOC changes in the soil. Temperature change was always the most important factor controlling wetland SOC, and precipitation had a greater impact on the topsoil. Under the temperature control targets of 1.5 °C and 2 °C, the SOC pool of the Zoige wetland will decrease by 60.21 Tg C and 69.19 Tg C, respectively. Under scenarios of a 10% and 20% increase in precipitation, the wetland soil will accumulate an additional 46.53 Tg C and 118.89 Tg C, respectively. The study results provide important references for the sustainable management of the Zoige wetland under the background of global climate change.

Abstract Differential subcarrier index modulation (DSIM) system provides resource efficient information transmission without the need of channel state information and equalisation. However, maximum likelihood detector applied in DSIM possesses high complexity, which obstructs its practical application. To address this issue, in this letter, an intelligent detector is proposed to learn the transmission patterns of DSIM to demodulate the received signals with lower complexity. In this design, the received signals are pre‐processed based on the domain knowledge at first, and then input to the deep neural network composed of multi‐layer perceptrons for further bit data estimation. Complexity analysis is provided to demonstrate the superiority of the proposed design, and simulation results validate that the intelligent detector can achieve similar average bit error rate with higher robustness compared with the benchmark system.

This paper reports a simulation-based dynamic confined compression analysis of coral sand under an impact load using the discrete element method (DEM). The evolution of particle breakage on the mesoscale was studied by investigating force chain distributions, crack development, and breakage modes. Crushable sand particles were simulated by replacing rigid particles with flexible basic unit aggregates. The Weibull parameters were incorporated within the mesoscopic parameters of particles, and random numbers were introduced. The obtained results for particle strengths were consistent with the experimental data. The numerical results demonstrated that the force chain was significantly strengthened along the loading axis during loading and weakened during unloading. The cracks were primarily generated along the strong force chain, and particle breakage caused the strong force chain to move towards relatively more complete fragments nearby. The crack was primarily oriented along the loading axis, and its anisotropy was observed to decrease with an increase in the load. Before yielding, particle breakage in the specimen was dominated by attrition at the edges and corners. After yielding, the crack extended into the particle perpendicular to the intergranular contact surface and was deflected by the simultaneous influence of pores. The fracture and shattering of particles occurred successively, and the consequent fall-off and slip filling of the fragments promoted the deformation development.

Abstract Hydrogels, a highly versatile material platform, are poised to become a promising candidate for interfacial solar evaporators on account of their record‐high evaporation rates. Nevertheless, conventional hydrogels with loose crosslinking, low solid content, and isotropic network structure are plagued by fragile mechanical tolerance, impairing their application in severe seawater environments. Herein, we develop a skeleton‐construct polyelectrolyte hydrogel (SCPH) evaporator by a universal, simple strategy that maintains not only the original properties of hydrogels, but also endows a high mechanical strength. By virtue of this strategy, the SCPH increased its mechanical strength to 1 MPa, 500 times higher than the original hydrogel. Surprisingly, the strategy also endows the SCPH with some extra properties, such as a high salt rejection ratio, a high water‐pumping rate, and low thermal conductivity, which render the SCPH a perfect evaporator. Specifically, this SCPH material significantly improves the long‐term stability of evaporators, enabling the evaporator to be capable of evaporating for 30 days in 20 wt% brine at a stable evaporation rate, exceeding the longest evaporation time ever reported. In addition, it achieves an evaporation rate of up to 2.13 kg m−2 h−1, which is twice that of the currently existing polyelectrolyte hydrogel evaporators. The skeleton construction has the potential to significantly improve the efficiency, stability, and durability of evaporators, hence bringing interfacial desalination technology toward practical applications.

Background Mitochondrial fusion and fission were identified to play key roles during multiple biology process. Thus, we aim to investigate the roles of OPA1 in mitochondria fusion and immune evasion of non-small cell lung cancer cells. Methods The transcriptional activation of genes related to mitochondrial dynamics was determined by using multi-omics data in lung adenocarcinoma (LUAD). We elucidated the molecular mechanism and roles of OPA1 promoting lung cancer through single-cell sequencing and molecular biological experiments. Results Here, we found that copy number amplification of OPA1 and MFN1 were co-occurring and synergistically activated in tumor epithelial cells in lung cancer tissues. Both of OPA1 and MFN1 were highly expressed in LUAD tumor tissues and OPA1 high expression was associated with poor prognosis. In terms of mechanism, the damaged mitochondria activated the apoptotic signaling pathways, inducing cell cycle arrest and cell apoptosis. More interestingly, OPA1 deficiency damaged mitochondrial dynamics and further blocked the respiratory function to increase the sensitivity of tumor epithelial to CD8+ T cells in non-small cell lung cancer. Conclusions Our study demonstrated the high co-occurrence of copy number amplification and co-expression of OPA1 and MFN1 in LUAD tissue, and further revealed the contribution of OPA1 in maintaining the mitochondria respiratory function and the ability of immune evasion to CD8+ T cells of LUAD.

The transport of air pollutants from areas surrounding the Tibetan Plateau (TP) has recently been studied. However, the major sources of atmospheric total suspended particulate matter (TSP) on the central TP remain unclear due to a lack of in-situ observations on aerosol physico-chemical properties. Therefore, to quantitatively investigate the physico-chemical properties and reveal the major sources of atmospheric aerosols, a comprehensive field campaign was conducted at the site of Nam Co from August 6 to September 11, 2020. Aerosol loading was low during the campaign with average TSP mass concentration, scattering coefficient at 550 nm, and absorption coefficient at 670 nm being 10.11 ± 5.36 μg m−3, 1.71 ± 1.36 Mm−1, and 0.26 ± 0.20 Mm−1, respectively. Organic matter (63.9%) and mineral dust (27.8%) accounted for most of the TSP mass concentrations. The average scattering Ångström exponent of 0.59 ± 0.14 reflected the influence of mineral dust, and the elemental fractions and the results of enrichment factor illustrated that crustal materials were the main contributors of mineral dust. The organic to elemental carbon ratio of 15.33 is probably caused by the aging that occurs during the transport of aerosols. The strong correlation between organic carbon and Ca2+ and the results of the electron microscopy analysis of single particles indicated that organic carbon and mineral dust had the same sources; however, the weak relation between mineral dust and wind speed indicated that local wind erosion was not the main contributor to the mineral dust. The potential source contribution function further illustrated that the summertime TSP in the central TP was mainly characterized by background biomass and mineral dust aerosols originating regionally from the ground within the TP.

Abstract Background Melanoma is the most serious type of skin cancer, and surgery is an effective method to treat melanoma. Unfortunately, local residual micro-infiltrated tumour cells and systemic circulating tumour cells (CTCs) are significant causes of treatment failure, leading to tumour recurrence and metastasis. Methods Small EVs were isolated from platelets by differential centrifugation, and doxorubicin-loaded small EVs (PexD) was prepared by mixing small EVs with doxorubicin (DOX). PexD and an anti-PD-L1 monoclonal antibody (aPD-L1) were co-encapsulated in fibrin gel. The synergistic antitumour efficacy of the gel containing PexD and aPD-L1 was assessed both in vitro and in vivo. Results Herein, we developed an in situ-formed bioresponsive gel combined with chemoimmunotherapeutic agents as a drug reservoir that could effectively inhibit both local tumour recurrence and tumour metastasis. In comparison with a DOX solution, PexD could better bind to tumour cells, induce more tumour immunogenic cell death (ICD) and promote a stronger antitumour immune response. PexD could enter the blood circulation through damaged blood vessels to track and eliminate CTCs. The concurrent release of aPD-L1 at the tumour site could impair the PD-1/PD-L1 pathway and restore the tumour-killing effect of cytotoxic T cells. This chemoimmunotherapeutic strategy triggered relatively strong T cell immune responses, significantly improving the tumour immune microenvironment. Conclusion Our findings indicated that the immunotherapeutic fibrin gel could “awaken” the host innate immune system to inhibit both local tumour recurrence post-surgery and metastatic potential, thus, it could serve as a promising approach to prevent tumour recurrence. Graphical Abstract

Aiming to provide feasible solutions for the realization of the robust and natural myoelectric control systems, a novel myoelectric control scheme supporting gesture recognition and muscle force estimation is proposed in this study. Eleven grasping gestures abstracted from daily life are selected as the target gesture set. The high-density surface electromyography (HD-sEMG) of the forearm flexor and the grasping force signal are collected simultaneously. The synchronous prediction of gesture category and instantaneous force is realized by the multi-task learning (MTL) technique. Especially, a post-processing algorithm based on threshold method is conducted to overcome the influence of force variation on the accuracy of gesture recognition. The experimental results show that the proposed post-processing method can decrease the classification error significantly. Specifically, the overall gesture classification error is reduced by 27 ~ 30 percent compared with not using the post-processing method; and 16 ~ 24 percent compared with using classical post-processing methods. The whole scheme can realize the synchronous gesture recognition and force estimation with 9.35 ± 11.48% gesture classification error and 0.1479 ± 0.0436 root-mean-square deviation force estimation accuracy. Meanwhile, it is feasible in different number of electrodes and well meets the real-time requirement of the EMG control system in response time delay (about 28.22 ~ 113.16ms on average). The proposed framework provides the possibility for myoelectric control supporting synchronous gesture recognition and force estimation, which can be extended and applied in the fields of myoelectric prosthesis and exoskeleton devices.

Patients with breast cancer undergoing chemotherapy are susceptible to prolonged and severe neutropenia. Multiple biosimilars of long-acting granulocyte colony-stimulating factors (LA-G-CSFs) have been newly developed to prevent this disease. Nonetheless, which LA-G-CSF regimen has the optimal balance of efficacy and safety remains controversial. Moreover, there is a lack of evidence supporting clinical decisions on LA-G-CSF dose escalation in poor conditions. PubMed, Embase, Cochrane Library, Web of Science, and several Chinese databases were searched (December 2022) to collect randomized controlled trials (RCTs) about LA-G-CSFs preventing chemotherapy-induced neutropenia in breast cancer patients. No restrictions were imposed on language. A Bayesian network meta-analysis was performed. We assessed the incidence of severe neutropenia (SN) and febrile neutropenia (FN), the duration of SN (DSN), and the absolute neutrophil account recovery time (ANCrt) for efficacy, while the incidence of severe adverse events (SAE) was assessed for safety. The study was registered in PROSPERO (CRD42022361606). A total of 33 RCTs were included. Our network meta-analysis demonstrated that lipegfilgrastim 6 mg and eflapegrastim 13.2 mg outperformed other LA-G-CSFs with high efficacy rates and few safety concerns (SUCRA of lipegfilgrastim 6 mg: ANC rt 95.2%, FN 97.4%; eflapegrastim 13.2 mg: FN 87%, SN 89.3%). Additionally, 3.6 mg, 4.5 mg, 6 mg, and 13.2 mg dosages all performed significantly better than 1.8 mg in reducing the duration of SN (3.6 mg: DSN, SMD −0.68 [−1.13, −0.22; moderate]; 4.5 mg: −0.87 [−1.57, −0.17; low]; 6 mg: −0.89 [−1.49, −0.29; moderate]; 13.2 mg: −1.02 [1.63, −0.41; high]). Increasing the dosage from the guideline-recommended 6 mg to 13.2 mg can reduce both the duration and incidence of SN (SMD −0.13 [−0.24 to −0.03], RR 0.65 [0.43 to 0.96], respectively), with no significant difference in SAE. For patients with breast cancer, lipegfilgrastim 6 mg and eflapegrastim 13.2 mg might be the most effective regimen among LA-G-CSFs. Higher doses of LA-G-CSF may enhance efficacy without causing additional SAEs.

Tumor metastasis is responsible for chemotherapeutic failure and cancer-related death. Moreover, circulating tumor cell (CTC) clusters play a pivotal role in tumor metastasis. Herein, we develop cancer-specific calcium nanoregulators to suppress the generation and circulation of CTC clusters by cancer membrane-coated digoxin (DIG) and doxorubicin (DOX) co-encapsulated PLGA nanoparticles (CPDDs). CPDDs could precisely target the homologous primary tumor cells and CTC clusters in blood and lymphatic circulation. Intriguingly, CPDDs induce the accumulation of intracellular Ca2+ by inhibiting Na+/K+-ATPase, which help restrain cell–cell junctions to disaggregate CTC clusters. Meanwhile, CPDDs suppress the epithelial–mesenchymal transition (EMT) process, resulting in inhibiting tumor cells escape from the primary site. Moreover, the combination of DOX and DIG at a mass ratio of 5:1 synergistically induces the apoptosis of tumor cells. In vitro and in vivo results demonstrate that CPDDs not only effectively inhibit the generation and circulation of CTC clusters, but also precisely target and eliminate primary tumors. Our findings present a novel approach for anti-metastasis combinational chemotherapy.

Abstract Disease relapse after allogeneic stem cell transplantation is a major cause of treatment-related morbidity and mortality in patients with myeloproliferative neoplasms (MPNs). The cellular and molecular mechanisms for MPN relapse are not well understood. Here, we established a murine model of MPN relapse, in which ~ 60% of the MPN recipient mice develop disease relapse after receiving stem cell transplantation with wild-type marrow donor. Using this model, we find that impaired wild-type cell function is associated with MPN disease relapse. We also show that competition between wild-type and JAK2V617F mutant cells can modulate the immune cell composition and PD-L1 expression induced by the JAK2V617F oncogene. These results suggest that cell competition between wild-type donor cells and JAK2V617F mutant recipient cells can prevent MPN disease relapse after stem cell transplantation.

“AI & Drug Discovery” mode has significantly promoted drug development and achieved excellent performance, especially with the rapid development of deep learning, making remarkable contributions to protecting human physiological health. However, due to the “black‐box” characteristic of the deep learning model, the decision route and predicted results in different research stages assisted by deep models are usually unexplainable, limiting their application in practice and more in‐depth research of drug discovery. Focusing on the drug molecules, an explainable fragment‐based molecular property attribution technique is proposed for analyzing the influence of particular molecule fragments on properties and the relationship between the molecular properties herein. Quantitative experiments on 42 benchmark property tasks demonstrate that 325 attribution fragments, which account for 90% of the overall attribution results obtained by the proposed method, have positive relevance to the corresponding property tasks. More impressively, most of the attribution results randomly selected are consistent with the existing mechanism explanations. The discovery mentioned above provides a reference standard for assisting researchers in developing more specific and practical drug molecule studies, such as synthesizing molecule with the targeted property using a fragment obtained from the attribution method. An interactive preprint version of the article can be found at: https://www.authorea.com/doi/full/10.22541/au.165279262.29589148.

Abstract Solar interfacial evaporation holds great potential for desalination. Currently, abundant and renewable biomass appears to be the most sustainable evaporator candidate for addressing environmental and energy challenges. However, the widespread use of biomass‐based evaporators is hampered by the formation and deposition of salt on the evaporation surface. Herein, we present a hierarchical photothermal aerogel inspired by the leaves‐on‐stems architecture in pristine plants. It is formed with microchannels severing as stems and nanospikes as leaves. Microchannels with large pores enable quick brine replenishment, while numerous nanospikes increase the available surface area for vapor generation. In contrast to the macro‐scale salt‐resistant design, which ruins the overall structure of the evaporator, we modified the microchannel structure within the biomass, allowing the biomass evaporator to effectively resist salt while maintaining efficient evaporation performance. The unique hierarchical micro‐nano structure of this photothermal aerogel allows it to achieve a high evaporation rate of 1.78 kg m−2 h−1 under 1 sun and a continuous evaporation time of 100 h without salt deposition in a high‐salinity brine (15 wt%), outperforming most previously reported evaporators derived from biomass. Additionally, the anti‐biofouling capacity of the evaporator is effectively demonstrated for long‐term operation through the development of an enhanced freshwater collection prototype, highlighting the potential for sustainable off‐grid solar desalination.

Phototherapy has been intensively investigated as a non-invasive cancer treatment option. However, its clinical translation is still impeded by unsatisfactory therapeutic efficacy and severe phototoxicity. To achieve high therapeutic efficiency and high security, a nanoassembly of Forster Resonance Energy Transfer (FRET) photosensitizer pairs is developed on basis of dual-mode photosensitizer co-loading and photocaging strategy. For proof-of-concept, an erythrocyte-camouflaged FRET pair co-assembly of chlorine e6 (Ce6, FRET donor) and 1,1′-dioctadecyl-3,3,3′,3′-tetramethylindotricarbocyanine iodide (DiR, FRET acceptor) is investigated for breast cancer treatment. Notably, Ce6 in the nanoassemby is quenched by DiR and could be unlocked for photodynamic therapy (PDT) only when DiR is photobleached by 808-nm laser. As a result, Ce6-caused phototoxicity could be well controlled. Under cascaded laser irradiation (808–660 nm), tumor-localizing temperature rise following laser irradiation on DiR not only induces tumor cell apoptosis but also facilitates the tumor penetration of NPs, relieves tumor hypoxia, and promotes the PDT efficacy of Ce6. Such FRET pair-based nanoassembly provides a new strategy for developing multimodal phototherapy nanomedicines with high efficiency and good security.

It is widely believed that science and technology (sci-tech) finance can pave the way to combat environmental degradation by promoting innovation in environment-related technologies. However, limited research is available to support this argument, and literature is silent on how sci-tech finance pilot policies influence carbon emissions in China. Therefore, this study investigates the impact of technology and financial integration pilot policy (TFIP) on carbon emissions and its dynamic effects, heterogeneity, and mechanisms in 252 cities in China. To do this, the yearly data from 2006 to 2019 were used in the propensity score matching–difference in differences (PSM-DID) method. The results unveiled that 1) the TFIP can effectively reduce the scale and intensity of carbon emissions in pilot cities. The TFIP shows a U-shaped distribution with CO2_Size and CO2_intensity, reaching a minimum in the fifth year. The TFIP has a lagging effect on carbon emissions, which significantly reduces carbon emissions in the second year. The robustness test verifies our conclusion. 2) The heterogeneity test results show that the effect of the TFIP is heterogeneous depending on the spatial and city attributes. The TFIP can effectively reduce carbon emissions in the eastern region and resource-based cities. However, in the central, western, and non-resource–based cities, the reduction effect of the TFIP is not obvious. 3) The impact mechanism finds that the TFIP reduces the scale of carbon emissions by enhancing the green innovation capacity and rationalizing the production structure in the pilot cities. Several policy recommendations are proposed based on the findings such as vigorous development of sci-tech finance to achieve sustainable development of the economy.

In order to solve the engineering problem that the bolt tail is often broken under the impact of rock pressure, mining stress and the damage to the support structure contribute to great hidden danger to the safety of mining and tunneling. A new anti-impact bolt support structure is designed that can absorb energy under pressure. The double laminated springs and the inner spring deform under the impact load to achieve the purpose of absorbing most of the impact energy. The composition and working principle of the energy-absorbing structure is introduced. The static axial compression tests of the single laminated springs with cone angles of 30°, 45°, and 60° are carried out. The mechanical characteristics of the laminated springs in the three stages of energy absorption are investigated. It is found that the 45° laminated spring has the best energy absorption effect. The simulation method was used to analyze and optimize the energy absorption effect of anti-scour composite components. Double laminated spring anti-shock composite components absorb the impact energy and avoid the damage to the bolt support structure, which reduces the roadway support cost and has important engineering application value for ensuring the safety of deep tunneling and mining.

Long noncoding RNAs (lncRNAs) have emerged as vital regulators of gene expression during embryonic stem cell (ESC) self-renewal and differentiation. Here, we systemically analyzed the differentially regulated lncRNAs during ESC-derived cardiomyocyte (CM) differentiation. We established a perspicuous profile of lncRNA expression at four critical developmental stages and found that the differentially expressed lncRNAs were grouped into six distinct clusters. The cluster with specific expression in ESC enriches the largest number of lncRNAs. Investigation of lncRNA-protein interaction network revealed that they are not only controlled by classic key transcription factors, but also modulated by epigenetic and epitranscriptomic factors including N6-methyladenosine (m6A) effector machineries. A detailed inspection revealed that 28 out of 385 lncRNAs were modified by methylation as well as directly recruited by the nuclear m6A reader protein Ythdc1. Unlike other 27 non-coding transcripts, the ESC-specific lncRNA Gm2379, located in both nucleus and cytoplasm, becomes dramatically upregulated in response to the depletion of m6A or Ythdc1. Consistent with the role of m6A in cell fate regulation, depletion of Gm2379 results in dysregulated expressions of pluripotent genes and crucial genes required for the formation of three germ layers. Collectively, our study provides a foundation for understanding the dynamic regulation of lncRNA transcriptomes during ESC differentiation and identifies the interplay between epitranscriptomic modification and key lncRNAs in the regulation of cell fate decision.

Undoubtedly, resource-based cities (RBCs) have significantly contributed to the socio-economic development of China; however, energy consumption intensified due to this development. Reducing energy consumption in RBCs and transforming the energy structure of RBCs are major challenges. To promote the energy structure transformation of RBCs, the Chinese government has introduced the Sustainable Development Policy for Resource Cities (SDPRC), but the effectiveness of SDPRC is still unclear. Therefore, this study uses the difference-in-difference (DID) approach to explore the impact of SDPRC on energy consumption scale (ECS) and energy consumption intensity (ECI) in RBCs based on panel data of 280 cities from 2006 to 2019. Firstly, the empirical results indicate that the implementation of SDPRC significantly reduces energy consumption in RBCs. The findings unfold that the inverted U-shaped relationship between SDPRC and ECS, while the effect on ECI has a certain lag, which is significant from the second year, and its impact increases persistently with the advancement of the policy. The stability test also verifies our conclusion. Secondly, the heterogeneity results show that the effect of SDPRC implementation varies across RBCs in different regions and development stages. Thirdly, the impact mechanism test result shows that controlling pollutant emissions and getting rid of resource dependency are important ways to reduce energy consumption in RBCs. However, the implementation of SDPRC does not promote the rationalization and transformation of industrial structure in RBCs. Based on the findings, policy recommendations are proposed for energy transformation and sustainable development of RBCs.

Land use is a major source of anthropogenic carbon emissions and a driver of climate change, so it is necessary to explore the spatial and temporal distribution characteristics of carbon emissions from different land use types. Based on the land use type data and fossil energy consumption data in the same period, we analyzed the spatial and temporal distribution characteristics of carbon emissions in the Yellow River Delta from 2000 to 2019 by constructing a carbon emission model, carbon footprint and Moran’s I index. The empirical results show that total net carbon emissions in the Yellow River Delta increased from 3.1×1010kg to 1.5×1011kg during 2000–2019. Construction land is the main source of carbon, while forest land and water contribute more to the total carbon sink in the study area. Carbon emissions in the Yellow River Delta were spatially clustered, characterized by a larger distribution of carbon emissions in the “east-west” direction than in the “north-south” direction. The results of the study are conducive to a comprehensive understanding of the spatial distribution pattern of land use carbon sources/sinks in the Yellow River Delta, and provide a certain reference basis for the formulation of low-carbon economic policies in the region.

Many studies have shown that clustered Wireless Sensor Networks (WSNs) have a better performance in terms of the balance of energy and lifetime. However, due to the harsh environment and open communication, the clustered WSNs are easy to be attacked. The selective forwarding attack is one of the most difficult attacks to be detected. When a malicious sensor node launches the selective forwarding attacks, it drops part of or all the data packets it received. In this paper, we propose a Noise-Based Density Peaks Clustering (NB-DPC) algorithm for detecting selective forwarding attacks. It can detect selective forwarding attacks by clustering the Cumulative Forwarding Rates (CFRs) of all sensor nodes. The NB-DPC algorithm has been improved by defining noise points specifically for identifying malicious behavior and deleting the unnecessary steps in Density Peaks Clustering (DPC) for faster detection speed. The NB-DPC has a low Missed Detection Rate (MDR) and False Detection Rate (FDR) of below 1% according to the simulation results.

In this study, polyurea was experimentally tested under various spraying temperatures and pressures. The number of holes and the pore size produced after the tensile fracture of the polyurea were counted to illustrate the effect of the various spraying temperatures and pressures on the performance of the polyurea. The tensile characteristics of polyurea were greatly influenced by the spraying temperatures and pressures, according to the experimental findings and statistical analysis. The polyurea tensile performance was best when the spraying pressure was 17.25 MPa with a spraying temperature of 70 °C. The fracture mechanism was illustrated by the silver streaking phenomenon generated during the tensile stretching process. The fracture energy was absorbed by the fracture holes and pores during silver streaking, thus creating the huge gap in tensile properties.

One of the major barriers in utilizing prodrug nanocarriers for cancer therapy is the slow release of parent drug in tumors. Tumor cells generally display the higher oxidative level than normal cells, and also displayed the heterogeneity in terms of redox homeostasis level. We previously found that the disulfide bond-linkage demonstrates surprising oxidation-sensitivity to form the hydrophilic sulfoxide and sulphone groups. Herein, we develop oxidation-strengthened prodrug nanosystem loaded with pyropheophorbide a (PPa) to achieve light-activatable cascade drug release and enhance therapeutic efficacy. The disulfide bond-driven prodrug nanosystems not only respond to the redox-heterogeneity in tumor, but also respond to the exogenous oxidant (singlet oxygen) elicited by photosensitizers. Once the prodrug nanoparticles (NPs) are activated under irradiation, they would undergo an oxidative self-strengthened process, resulting in a facilitated drug cascade release. The IC50 value of the PPa@PTX-S-S NPs without irradiation was 2-fold higher than those of NPs plus irradiation. In vivo, the PPa@PTX prodrug NPs display prolonged systemic circulation and increased accumulation in tumor site. The PPa@PTX-S-S NPs showed much higher efficiency than free PTX or the PPa@PTX-C-C NPs to suppress the growth of 4T1 tumors. Therefore, this novel oxidation-strengthened disulfide-bridged prodrug-nanosystem has a great potential in the enhanced efficacy of cancer synergetic photochemotherapy.

Abstract Thrombotic cardio‐cerebrovascular diseases seriously threaten human health. Currently, conventional thrombolytic treatments are challenged by the low utilization, inferior thrombus penetration, and high off‐target bleeding risks of most thrombolytic drugs, resulting in unsatisfactory treatment outcomes. Herein, it is proposed that these challenges can be overcome by precisely integrating the conventional thrombolytic strategy with photothermal therapy. After co‐assembly engineering optimization, a fibrin‐targeting peptide‐decorated nanoassembly of DiR (a photothermal probe) and ticagrelor (TGL, an antiplatelet drug) is prepared for thrombus‐homing delivery, abbreviated as FT‐DT NPs. The elaborately engineered nanoassembly shows multiple advantages, including simple preparation with high drug co‐loading capacity, synchronous delivery of two drugs with long systemic circulation, thrombus‐targeted accumulation with self‐indicating function, as well as photothermal‐potentiated thrombus penetration and thrombolysis with high therapeutic efficacy. As expected, FT‐DT NPs not only show bright fluorescence signals in the embolized vessels, but also perform photothermal/antiplatelet synergistic thrombolysis in vivo. This study offers a simple and versatile co‐delivery nanoplatform for imaging‐guided photothermal/antiplatelet dual‐modality thrombolysis.

Internal ribosome entry sites (IRESs) are functional RNA elements that can directly recruit ribosomes to an internal position of the mRNA in a cap-independent manner to initiate translation. Recently, IRES elements have attracted much attention for their critical roles in various processes including translation initiation of a new type of RNA, circular RNA (circRNA), with no 5′ cap to support classical cap-dependent translation. Thus, an integrative data resource of IRES elements with experimental evidence will be useful for further studies. In this study, we present IRESbase, a comprehensive database of IRESs, by curating the experimentally validated functional minimal IRES elements from literature and annotating their host linear and circular RNAs. The current version of IRESbase contains 1328 IRESs, including 774 eukaryotic IRESs and 554 viral IRESs from 11 eukaryotic organisms and 198 viruses, respectively. As IRESbase collects only IRES of minimal length with functional evidence, the median length of IRESs in IRESbase is 174 nucleotides. By mapping IRESs to human circRNAs and long non-coding RNAs (lncRNAs), 2191 circRNAs and 168 lncRNAs were found to contain at least one entire or partial IRES sequence. IRESbase is available at http://reprod.njmu.edu.cn/cgi-bin/iresbase/index.php.

Although it is reported that the targeting ability of hyaluronic acid (HA)-based nanoparticles (NPs) is molecular weight (MW) dependent, the influence of HA MW on targeting efficiency of HA-functionalized NPs and the underlying mechanism remain elusive. In this study, we constituted three HA-functionalized Dox-loaded NPs (Dox/HCVs) different HA MWs (7, 63, and 102 kDa) and attempted to illustrate the effects of HA MW on the targeting efficiency. The three Dox/HCVs had similar physiochemical and pharmaceutical characteristics, but showed different affinity to CD44 receptor. Furthermore, Dox/HCV-63 exerted the best targeting effect and the highest cytotoxicity compared with Dox/HCV-7 and Dox/HCV-102. It was interesting to found that both the HA-CD44 binding affinity and induced CD44 clustering by HA-based NPs were HA MW-dependent, the two of which determine the apparent targeting efficacy of Dox/HCV NPs in the conflicting directions. Those results laid a good foundation for rationally designing HA-based NPs in cancer therapy. Keywords: Hyaluronic acid, Molecular weight, Active targeting efficiency, CD44 receptor, Potential mechanism

Self-nanoemulsifying drug delivery system (SNEDDS) has emerged as a promising platform to improve oral absorption of drugs with poor solubility and low permeability. However, large polarity molecules with insufficient lipid solubility, such as paclitaxel (PTX), would suffer from inferior formulation of SNEDDS due to poor compatibility. Herein, phospholipid-drug complex (PLDC) and SNEDDS were integrated into one system to facilitate oral delivery of PTX. First, PTX was formulated into PLDC in response to its inferior physicochemical properties. Then, the prepared PLDC was further formulated into SNEDDS by integrating these two drug delivery technologies into one system (PLDC-SNEDDS). After PLDC-SNEDDS dispersed in aqueous medium, nanoemulsion was formed immediately with an average particle size of ∼30 nm. Furthermore, the nanomulsion of PLDC-SNEDDS showed good colloidal stability in both HCl solution (0.1 mol/l, pH 1.0) and phosphate buffer solution (PBS, pH 6.8). In vivo, PTX-PLDC-SNEDDS showed distinct advantages in terms of oral absorption efficiency, with a 3.42-fold and 2.13-fold higher bioavailability than PTX-PLDC and PTX solution, respectively. Our results suggest that the integration of PLDC into SNEDDS could be utilized to facilitate the oral delivery of hydrophobic drugs with large polarity. Keywords: PTX, PLDC, SNEDDS, PLDC-SNEDDS, Oral delivery