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News personalization in one-party dominant countries has been understudied or often analyzed through a Western lens. This study unpacked this phenomenon in one-party dominant country with the theory of leadership cult and soft power and compared news personalization of Xi Jinping in China with that of Donald Trump in the U.S. against the backdrop of the U.S.–China trade conflict. This study also investigated the influence of press ideology, political–geographical scope of news coverage and the trade conflict period on the presence and valence of personalization within each country. Results showed that leadership personalization was less prominent in China than in the U.S. The manifestation of news personalization in the U.S. was affected more by press ideology, while contextual factors, such as news political scope and the conflict period, played bigger roles in China. These findings provide insights into how news personalization is displayed in divergent political and media systems. [ABSTRACT FROM AUTHOR]

Drawing from agenda building theory, this study explores the impact of factors like journalistic culture, national stance and conflict periods on the similarity and dissimilarity of network agendas in China-U.S. trade conflict news across China, the United States, Singapore and Ireland. Findings revealed significant correlations in network agendas across countries, albeit with disparities between China and the United States. Notably, the correlation weakened in both Chinese and U.S. news following the trade war's eruption. [ABSTRACT FROM AUTHOR]

Previous studies mainly focused on individual-level factors that influence the adoption and usage of mobile technology and social networking sites, with little emphasis paid to the influences of household situations. Using multilevel modelling approach, this study merges household- (n1 = 1,455) and individual-level (n2 = 2,570) data in the U.K. context to investigate (a) whether a household economic capital (HEC) can affect its members' Twitter adoption, (b) whether the influences are mediated by the member's activity variety and self-reported efficacy with mobile technology, and (c) whether the members' traits, including educational level, gross income and residential area, moderate the relationship between HEC and Twitter adoption. Significant direct and indirect associations were discovered between HEC and its members' Twitter adoption. The educational level and gross income of household members moderated the influence of HEC on individuals' Twitter adoption. [ABSTRACT FROM AUTHOR]

Background: The assessment of human papillomavirus (HPV) genotype distribution in terms of age and cervical lesions could contribute to the adoption of more targeted preventive approaches to specific populations against cervical cancer. The current study was conducted in Ordos City, China, with the aim of analyzing the HPV genotypes prevalence and infection patterns within a hospital-based population. Methods: The analysis included a total of 26,692 women aged 25–64 who underwent cervical cancer screening between January 1st, 2019, and June 30th, 2022, in Ordos City. These women had valid results for both the polymerase chain reaction (PCR)-reverse dot blot (RDB) HPV test and the liquid-based cytology (thinprep cytologic test/TCT). Data were extracted from the database of KingMed Diagnostics laboratories. The prevalence of HPV genotypes within different age groups and cytology diagnoses were calculated. Results: Among 26,692 women, 7136 (26.73%) women were HPV positive, 5696 (21.34%) women were high-risk HPV (HR-HPV) positive, and 2102 (7.88%) women had multiple HPV infections. The most frequently detected HPV genotypes were HPV16 (4.72%) and HPV52 (4.15%), ranking as the first and second most prevalent genotypes, respectively. The prevalence of HR-HPV increased with age groups and severity of cervical lesions. Notably, the positive rate of HR-HPV among women aged 35–64 years showed a decreasing trend over the respective years, ranging from 26.00 to 19.70% (Ptrend < 0.001). Conclusion: In conclusion, the epidemiology of HPV genotypes partly reflects the effectiveness of regional cervical cancer prevention and control efforts in the past. These findings can inform future initiatives concerning HPV vaccination and screening in the region. [ABSTRACT FROM AUTHOR]

Linking survey and social media data has gained popularity. However, obtaining consent from respondents to link social media is a known challenge. Using data from a nationally representative survey of the U.K. this study investigated whether respondents’ a) activity frequency, b) activity variety and c) technical skills with smartphones are associated with consent to link Twitter data to survey responses. Additionally, this study explored mediating role of privacy and security concern and moderating effects of age, gender, employment and educational level to better understand the influences of privacy concern on Twitter linkage consent. Results showed that activity variety with smartphones is positively associated with Twitter linkage consent, and privacy concern mediated the effects of activity frequency and activity variety with smartphones on linkage consent. Age and employment status moderated the associations between privacy concern and linkage consent, with younger and employed respondents being more likely to be affected by privacy concern. [ABSTRACT FROM AUTHOR]

We show here that hyperpolarization‐activated current (Ih) unexpectedly acts to inhibit the activity of dorsal root ganglion (DRG) neurons expressing WT Nav1.7, the largest inward current and primary driver of DRG neuronal firing, and hyperexcitable DRG neurons expressing a gain‐of‐function Nav1.7 mutation that causes inherited erythromelalgia (IEM), a human genetic model of neuropathic pain. In this study we created a kinetic model of Ih and used it, in combination with dynamic‐clamp, to study Ih function in DRG neurons. We show, for the first time, that Ih increases rheobase and reduces the firing probability in small DRG neurons, and demonstrate that the amplitude of subthreshold oscillations is reduced by Ih. Our results show that Ih, due to slow gating, is not deactivated during action potentials (APs) and has a striking damping action, which reverses from depolarizing to hyperpolarizing, close to the threshold for AP generation. Moreover, we show that Ih reverses the hyperexcitability of DRG neurons expressing a gain‐of‐function Nav1.7 mutation that causes IEM. In the aggregate, our results show that Ih unexpectedly has strikingly different effects in DRG neurons as compared to previously‐ and well‐studied cardiac cells. Within DRG neurons where Nav1.7 is present, Ih reduces depolarizing sodium current inflow due to enhancement of Nav1.7 channel fast inactivation and creates additional damping action by reversal of Ih direction from depolarizing to hyperpolarizing close to the threshold for AP generation. These actions of Ih limit the firing of DRG neurons expressing WT Nav1.7 and reverse the hyperexcitability of DRG neurons expressing a gain‐of‐function Nav1.7 mutation that causes IEM. Key points: Hyperpolarization‐activated cyclic nucleotide‐gated (HCN) channels, the molecular determinants of hyperpolarization‐activated current (Ih) have been characterized as a 'pain pacemaker', and thus considered to be a potential molecular target for pain therapeutics.Dorsal root ganglion (DRG) neurons express Nav1.7, a channel that is not present in central neurons or cardiac tissue. Gain‐of‐function mutations (GOF) of Nav1.7 identified in inherited erythromelalgia (IEM), a human genetic model of neuropathic pain, produce DRG neuron hyperexcitability, which in turn produces severe pain.We found that Ih increases rheobase and reduces firing probability in small DRG neurons expressing WT Nav1.7, and demonstrate that the amplitude of subthreshold oscillations is reduced by Ih.We also demonstrate that Ih reverses the hyperexcitability of DRG neurons expressing a GOF Nav1.7 mutation (L858H) that causes IEM.Our results show that, in contrast to cardiac cells and CNS neurons, Ih acts to stabilize DRG neuron excitability and prevents excessive firing. [ABSTRACT FROM AUTHOR]

Mining, smelting and tailing deposition activities can cause metal(loid) contamination in surrounding soils, threatening ecosystems and human health. Microbial indicators are sensitive to environmental factors and have a crucial role in soil ecological risk assessment. Xikuangshan, the largest active antimony (Sb) mine in the world, was taken as the research area. The soil properties, metal(loid) contents and microbial characteristics were investigated and their internal response relationships were explored by multivariate statistical analysis. The assessment of the single pollution index and Nemerow synthetic pollution index (P N) showed that the soils were mainly polluted by Sb, followed by Cd and As, in which sampling site S1 had a slight metal(loid) pollution and the other sampling sites suffered from severe synthetic metal(loid) pollution. The microbial characteristics were dissimilar among sampling points at different locations from the mining area according to hierarchical cluster analysis. The correlation analysis indicated that fluorescein diacetate hydrolase, acid phosphatase, soil basal respiration and microbial biomass carbon were negatively correlated with P N , indicating their sensitivity to combined metal(loid) contamination; that dehydrogenase was positively correlated with pH; and that urease, potential ammonia oxidation and abundance of ammonia-oxidizing bacteria and archaea were correlated with N (nitrogen) contents. However, β-glucosidase activity had no significant correlations with physicochemical properties and metal(loid) contents. Principal components analysis suggested bioavailable Sb and pH were the dominant factors of soil environment in Xikuangshan Sb mining area. Our results can provide a theoretical basis for ecological risk assessment of contaminated soil. [Display omitted] [ABSTRACT FROM AUTHOR]

Exploiting an adsorbent with superb selectivity is of utmost importance for the remediation of Cr (VI)-laden wastewater. In this work, a novel nitrogen and sulfur functionalized 3D macroporous cellulose material (MPS) was prepared by homogeneous cross-link cellulose and polyvinylimidazole, followed by ion exchange with MoS42−. MPS exhibited high removal efficiency at a broad pH range (1.0–8.0) and large adsorption capacity (379.78 mg/g) toward Cr (VI). Particularly, outstanding selectivity with an enormous partition coefficient (1.01 × 107 mL/g) was achieved on MPS. Replacing MoS42− with Cl− and MoO42− led to a sharp decline in adsorption selectivity, demonstrating that MoS42− contributed substantially to the selectivity. Results of FTIR, XPS, and apparent kinetic analysis revealed that Cr (VI) was first pre-enriched on the MPS surface via electrostatic and dispersion forces, and then reacted with MoS42− to generate Cr (III), which deposited on MPS by forming Cr(OH)3 and chromium(III) sulfide. This study provides a new idea for designing adsorbents with a superior selectivity for removing Cr (VI) from sewage. [ABSTRACT FROM AUTHOR]

Subspace clustering supposes that hyperspectral image (HSI) pixels lie in a union vector spaces of multiple sample subspaces without considering their dual space, i.e., spectral space. In this article, we propose a promising dual subspace clustering (DualSC) for improving spectral-spatial HSIs clustering by relaxing subspace clustering. To this end, DualSC simultaneously optimizes row and column subspace-representations of HSI superpixels to capture the intrinsic connection between spectral and spatial information. From the new perspective, the original subspace clustering can be treated as a special case of DualSC that has larger solution space, so tends to finding better sample representation matrix for applying spectral clustering. Besides, we provide theoretical proofs that show the proposed method relaxes the subspace space clustering with dual subspace, and can recover subspace-sparse representation of HSI samples. To the best of our knowledge, this work could be one of the first dual clustering method leveraging sample and spectral subspaces simultaneously. As a result, we conduct several clustering experiments on four canonical data sets, implying that our proposed method with strong interpretability reaches comparable performance and computing efficiency with other state-of-the-art methods. • Dual subspace clustering can capture spectral-spatial information of HSI. • Dual subspace clustering is a convex relaxation of subspace clustering. • Dual subspace clustering has sparse solution, good complexity and convergence. [ABSTRACT FROM AUTHOR]

Objective*To establish an efficient method to obtain a high throughput mammalian cell surface display library of IgG antibody Fc combined mutations based on the screening results of the single point mutation library and the introduction of combined mutations by multiple degenerate primers. Methods*Multiple degenerate primers were designed according to the mutated amino acids at 233-240 of EU numbering with high affinity to Fcγ receptor IIB screened by fluorescence-activated cell sorting from the single point mutation library; the DNA fragments containing combined mutations were obtained through PCR by using the degenerate primers mixed with equal proportion, or according to the proportion of mutation diversity; the recombinant enzyme was used to ligate the fragment to the vector in one step and then transformed into E. coli DH5α, and the plasmid library was obtained. The plasmid library was used to transfect Pheonix cells to prepare retroviruses, and then 3T3 cells were infected with the retroviruses to obtain mammalian cell library that expressed Fc mutations on the surface. Flow cytometry was used to analyze the transfection efficiency of Pheonix cells to package retroviruses and the infection efficiency of 3T3 cells by the retroviruses. The quality of the plasmid library and the cell library was evaluated by next generation sequencing (NGS). Results*According to the point mutation library screening results, 32 degenerate primers were designed, which could cover all desired combined mutations, and the actual library diversity was 3.6 times that of the expected library (41 600/11 520). The results of NGS showed that the plasmid library obtained by using proportionally mixed primers according to the primer diversity had better homogeneity and integrity, and could cover 99.58% of the expected combinational mutations (11 472/11 520). Sanger sequencing results showed that 3 sequences among 10 sequences were the expected mutations, which were consistent with the diversity calculated during degenerate primers design. Flow cytometry showed that the transfection efficiency of Pheonix cells was 51.6%, and the infection efficiency of 3T3 cells was 47.4%. NGS results showed that the cell library could cover 85.92% of the expected combinational mutations (9 898/11 520). Conclusion*Based on the amino acid mutations screened from the single point mutation library, multiple degenerate primers were designed, and then through PCR, plasmid transfection and retrovirus infection, an IgG Fc combined mutation plasmid library and mammalian cell surface display library with more than 85% coverage of the expected combined mutations can be obtained efficiently at low cost. [ABSTRACT FROM AUTHOR]

The Southeast Pacific (SEP) has distinct climate features that are governed by interactions among processes at multiple spatial scales and thus are hard to represent in climate models. This study investigates the local and remote impacts of various physical processes on surface fluxes over SEP in the Community Atmosphere Model version 5 by using a limited‐area parameter perturbation approach. In this approach, physical parameters from the Zhang‐McFarlane (ZM) convection scheme and the turbulence parameterization scheme of Cloud Layers Unified by Binormals (CLUBB) are perturbed in specific regions, but fixed outside. Three limited‐area perturbed parameter ensembles are performed over SEP, the Intertropical Convergence Zone (ITCZ) and the South Pacific convergence zone (SPCZ), respectively, with the simulations over SEP the primary focus that can respond to both local impacts and remote impacts from ITCZ and SPCZ. Results show that most of the variability of surface radiative fluxes is explained by the local impacts of sub‐grid physical processes and those related to shallow convection are most important. By contrast, a considerable portion of the variability of the surface latent heat flux is attributed to the remote effects from ITCZ and SPCZ, which are mainly contributed by the ZM parameters that can affect the large‐scale circulation by modulating the diabatic heating related to precipitation. Both the latent heat flux and shortwave radiative flux over SEP increase with the eastern‐ITCZ precipitation due to the stronger surface wind and less clouds, respectively. Overall, our results help better understand the sources of uncertainties in the simulated SEP climate. [ABSTRACT FROM AUTHOR]

Cellulose acetate film, as a biodegradable and biomass-derived material, has great potential applications in food packaging. However, the poor mechanical and antibacterial properties limit its applications. Herein, a highly flexible carbon nitride-polyethylene glycol-cellulose acetate (CN-PEG-CA) film was successfully prepared by combining graphitic carbon nitride (g-C 3 N 4) photocatalyst with cellulose acetate (CA). The g-C 3 N 4 enables the film with antibacterial activity, as a green photocatalyst. PEG softens the rigid polymer CA and crosslinks CA, PEG, and g-C 3 N 4 together by hydrogen bonding, as a flexible crosslinker. X-ray diffractometer (XRD), scanning electron microscope (SEM), and Fourier transform infrared spectrum (FT-IR) characterizations confirmed the successful preparation of the CN-PEG-CA film. The mechanical property tests demonstrated that adding PEG increased the elongation at break of the film by about 4 times. The composite film had high antibacterial activity, and the bactericidal rates on Escherichia coli and Staphylococcus aureus were 99.98 % and 99.89 %, respectively. It effectively extended the shelf life of strawberries to 96 h and effectively maintained the quality of strawberries during storage. After 96 h, the weight loss rate of strawberries packaged with 15 % CN-PEG-CA film was 21.83 %, vitamin C content was 45.47 %, titratable acidity content was 0.89 %, and color, hardness and total soluble solids were well maintained. And biocompatibility test results showed that the film was safe and nontoxic. From the ecological and economic point of view, the highly flexible and biodegradable films with efficient photocatalytic antibacterial activity synthesized in this paper have great potential in the field of food packaging. [Display omitted] [ABSTRACT FROM AUTHOR]

There is a great demand for the extraction of organ models from three-dimensional (3D) medical images in clinical medicine diagnosis and treatment. We aimed to aid doctors in seeing the real shape of human organs more clearly and vividly. The method uses the minimum eigenvectors of Laplacian matrix to automatically calculate a group of basic matting components that can properly define the volume image. These matting components can then be used to build foreground images with the help of a few user marks. We propose a direct 3D model segmentation method for volume images. This is a process of extracting foreground objects from volume images and estimating the opacity of the voxels covered by the objects. The results of segmentation experiments on different parts of human body prove the applicability of this method. [ABSTRACT FROM AUTHOR]

Potato pulp waste is a potential biomass material and easily acidified substrate for anaerobic digestion. The present study evaluated the methane yield and microbial community resulted from biochar amendment for the co-digestion of potato pulp waste and dairy manure at different feed-to-inoculum ratios (2:1, 1:1, 1:2, and 1:3) and potato pulp waste to dairy manure ratios (4:0, 3:1 and 1:1). The results indicated that the digesters with a high feed-to-inoculum ratio (2:1, 1:1) and without biochar lead to volatile fatty acid accumulation and process failure, whereas the addition of biochar and/or co-digestion can increase the buffer capacity and improve the digestion efficiency. The biogas and methane yields of the digesters with biochar were 1.1–2.8 and 1.4–5.3 times higher, respectively, than those without biochar. The maximum biogas and methane yields of 476 and 200 mL/g TS, respectively, were achieved with a feed-to-inoculum ratio of 1:2, potato pulp waste to dairy manure ratio of 4:0, and biochar addition. Biochar and co-digestion can also enhance the relative abundance of the bacterial community. Methanomicrobiales and Methanosaetaceae were the main methanogens present in the anaerobic digestion of PPW. This paper provides a theoretical basis of easily acidified substrates used for biogas production. • Potato pulp waste is a potential feedstock for biogas production but easily acidifies. • Effects of biochar and co-digestion on anaerobic digestion were evaluated. • Different ratios of feedstocks and feed to inoculum were considered. • Diversity of the microbial community was analyzed. • Biochar and co-digestion increase the buffer capacity and digestion efficiency. [ABSTRACT FROM AUTHOR]

The detection and identification of cigarette ash in fire debris can be meaningful in fire investigations caused by burning cigarettes. In this work, a novel analytical method based on negative chemical ionization time-of-flight mass spectrometry (NCI/TOFMS) combined with a phosphoric-acid-enhanced evaporation strategy has been developed for the discrimination of cigarette ash samples (CAs) and common household decoration material ash samples (CHDMAs). A series of characteristic ions representing the acidified products HNCO and formic acid in the CAs were achieved, whose signal responses were enhanced with the help of mechanical agitation operation. To account for both the signal responses of the characteristic ions and acid corrosion of the ion source, the dynamic-purge gas was chosen to be 200 mL/min. The whole time for analysis was only 5 min, which is suitable for high-throughput measurements of large quantities of fire debris. As a result, a preliminary discrimination was achieved between the CAs and CHDMAs by virtue of the chemometric tool of principal components analysis (PCA) based on intensity differences of the characteristic ions. The results are encouraging and highlight the potential of NCI/TOFMS without complicated sample preparation steps for the accurate and high-throughput identification of cigarette ash on substrates in fire debris. [ABSTRACT FROM AUTHOR]

Compressed sensing (CS) significantly accelerates magnetic resonance imaging (MRI) by allowing the exact reconstruction of image from highly undersampling k-space data. In this process, the high sparsity obtained by the learned dictionary and exploitation of correlation among patches are essential to the reconstructed image quality. In this paper, by a use of these two aspects, we propose a novel CS-MRI model based on analysis dictionary learning and manifold structure regularization (ADMS). Furthermore, a proper tight frame constraint is used to obtain an effective overcomplete analysis dictionary with a high sparsifying capacity. The constructed manifold structure regularization nonuniformly enforces the correlation of each group formed by similar patches, which is more consistent with the diverse nonlocal similarity in realistic images. The proposed model is efficiently solved by the alternating direction method of multipliers (ADMM), in which the fast algorithm for each sub-problem is separately developed. The experimental results demonstrate that main components in the proposed method contribute to the final reconstruction performance and the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

• The Savitzky-Golay filter optimizes the feature expression of the training set of the deep learning model and indirectly improves the prediction performance of the model. • A novel parallel architecture TCN-LSTM hybrid model for wind power prediction is constructed by the tensor concatenate module. • The parallel architecture TCN-LSTM has relatively fewer training parameters but higher prediction performance. • Diebold-Mariano test is employed for further model comparison validation. Wind energy is experiencing rapid global growth. However, wind power generation time series data often exhibit nonlinear and non-stationary characteristics, which make precise estimation challenging. Consequently, wind power prediction assumes an increasingly vital role in the planning and deployment of power and energy systems. Recently, many hybrid deep learning prediction models have been developed to improve the prediction performance of wind power, but their deeper network layer and complex structure also bring higher computing costs and reduced prediction efficiency. In order to achieve higher prediction performance, reduce the complexity and computational cost of hybrid deep learning models, and improve prediction efficiency, this study proposed a hybrid deep learning model based on parallel architecture by using a tensor concatenate module to combine a temporal convolution network (TCN) and a long short-term memory (LSTM) neural network for wind power prediction, and the Savitzky-Golay (SG) filter is used to remove noise and smooth the input wind speed time series in the model training stage. Using a wind turbine case from Turkey, three sets of comparison experiments are conducted. The effectiveness and superiority of the proposed model are validated by comparing a variety of single and hybrid models using current evaluation metrics and the Diebold-Mariano test. Among them, the number of training parameters and computing time of the proposed parallel architecture TCN-LSTM hybrid model are reduced by 6.59% and 25.82%, respectively, when compared to the conventional TCN-LSTM hybrid model with the same hyperparameter settings. nMAE, nMSE, and nRMSE are reduced by 2.00%, 9.21%, and 4.74%, respectively. The Diebold-Mariano test results also reveal that the proposed model performed better in terms of prediction performance. Moreover, the proposed innovative architecture hybrid model provides a novel approach to developing a hybrid model of deep learning networks for wind power prediction. [ABSTRACT FROM AUTHOR]

Abstract Compressed sensing MRI (CS-MRI) has demonstrated its potential in image reconstruction from undersampling k-space data to accelerate scanning time. Exact CS-MRI reconstruction is based on the image prior information of sparsity, and therefore, it relies on two important aspects of sparse domain and sparse coding. In this work, a patch based uniform model according to orthogonal dictionary learning and l p norm minimization (ODNM) is developed. First, image patches are classified into multi-classes by a use of a modified clustering method and the corresponding orthogonal dictionary is learned for each class. In addition, the non-convex l p norm regularization is employed to promote the sparsity of patch coefficients. In order to solve the proposed reconstruction model, the alternating direction method (ADM) steps are developed in which orthogonal dictionary learning, non-convex sparse coding, and image reconstruction are simultaneously conducted. In the special case of p = 0.5 , a fast shrinkage operator is proposed to reduce the computational complexity. Extensive experiments on real complex valued MR images under various sampling patterns demonstrate that the proposed method achieves a better performance than several state-of-the-art algorithms. [ABSTRACT FROM AUTHOR]

Abstract Effective condition monitoring and fault diagnosis of wind turbines are crucial for avoiding serious damages to wind turbines. The supervisory control and data acquisition (SCADA) system of a wind turbine provides valuable insights into turbine performance. In order to make full use of such valuable information, this paper investigates fault diagnosis of wind turbines by using Gaussian process classifiers (GPC) to the operational data collected from the SCADA system. Both real-time and predictive fault diagnosis were considered. As an alternative to the support vector machine (SVM) technique, the GPC possesses the capability of providing probabilistic information about the fault types, which is valuable for making maintenance plan in real practice. The comparison results show that the GPC method is able to provide more accurate fault diagnosis results than the SVM technique on average. Highlights • Suggest a new model based on Gaussian process classification for wind turbine diagnosis. • The suggested model is computationally more efficient than the support vector machine. • The suggested model can take the operational information into account. • The comparison results favor the new model. [ABSTRACT FROM AUTHOR]

When the compression quality factor (QF) is low, JPEG images are usually accompanied by very severe block artifacts. The conventional image deblocking models based on low-rank regularization focus on eliminating block artifacts, but lack the capacity of recovering texture details on image edges. In this paper, an image deblocking model which combines sparse representation and low-rank regularization based on fractional norm is proposed. To avoid the abrupt increase in computational complexity, multiple orthogonal dictionary learning is proposed to enhance the ability to sparsify diverse image structures and eliminate correlations among the atoms in the overcomplete dictionary. To further improve the image deblocking effect, a quantization constraint and fractional norm are used to more effectively enforce the low-rank property. Finally, an alternating minimization strategy is applied to solve the derived optimization problem. The model proposed in this paper preserves more texture details while effectively removing image block artifacts compared with the mainstream image deblocking model utilizing low-rank regularization alone. Experimental results show that the proposed method outperforms the current state-of-the-art image deblocking models in terms of both subjective metrics and objective perception. [ABSTRACT FROM AUTHOR]

In this paper, we give the global existence of L p bounded entropy solutions for the Cauchy problem of a system of conservation laws in chromatography with geometry effects. The main difficulty lies in establishing the L p estimate of the viscosity solutions because the initial data may not be L ∞ bounded and the principle of invariant regions developed by Conley–Chuey–Smoller is invalid here. We obtain the existence of the global weak solutions using the compensated compactness method and BV estimates on viscosity solutions. [ABSTRACT FROM AUTHOR]

This paper proposes a novel method for compressed sensing MRI (CS-MRI) reconstruction that combines both the sparse representation and statistical estimation. In this work, the low-rank property is observed and utilized to sparsely represent the similar patches based on group singular value decomposition (SVD), and the linear minimum mean square error (LMMSE) estimation is exploited to perform sparse coefficients estimation. Based on this, the proposed approach is named group-based eigenvalue decomposition and estimation (GEDE). Furthermore, in order to improve the estimation accuracy of the coefficients, the original problem is reformulated into an equivalent noise model and a novel method is proposed to assess the noise variance of similar patches. Extensive experimental results on the MRI data demonstrate that the proposed method outperforms the state-of-the-art reconstruction methods in terms of removing artifacts and reconstruction errors. [ABSTRACT FROM AUTHOR]

In this paper, a new approach to perform compressed sensing MRI (CS-MRI) reconstruction based on enhanced group sparsity and nonconvex regularization (GSNR) is presented. A new framework is developed at attempt to improve the group sparsity and the accuracy of estimated coefficients. To that end, first, we establish a generalized reordering model to train the optimal permutation, which reveals the inner structure of group and benefits to promote the sparsity of group for an arbitrarily fixed transform. Second, with the nonconvex log-sum regularization, a fast shrinkage operator to solve the corresponding nonconvex optimization problem is developed in which the optimal solution is accurately and quickly obtained. The effectiveness of GSNR is demonstrated for both noiseless and noisy real MR images. In both cases, the proposed algorithm generates high-quality images that are superior in terms of visual inspection and objective evaluations to the state-of-the-art approaches. In addition, the effects of reordering and nonconvex regularization are verified by simulations, respectively, to illustrate the superior performance of GSNR because of the proposed framework. [ABSTRACT FROM AUTHOR]

Bladder cancer ranks as the 10th most common cancer worldwide, with deteriorating prognosis as the disease advances. While immune checkpoint inhibitors (ICIs) have shown promise in clinical therapy in both operable and advanced bladder cancer, identifying patients who will respond is challenging. Anoikis, a specialized form of cell death that occurs when cells detach from the extracellular matrix, is closely linked to tumor progression. Here, we aimed to explore the anoikis-based biomarkers for bladder cancer prognosis and immunotherapeutic decisions. Through consensus clustering, we categorized patients from the TCGA-BLCA cohort into two clusters based on anoikis-related genes (ARGs). Significant differences in survival outcome, clinical features, tumor immune environment (TIME), and potential ICIs response were observed between clusters. We then formulated a four-gene signature, termed "Ascore", to encapsulate this gene expression pattern. The Ascore was found to be closely associated with survival outcome and served as an independent prognosticator in both the TCGA-BLCA cohort and the IMvigor210 cohort. It also demonstrated superior predictive capacity (AUC = 0.717) for bladder cancer immunotherapy response compared to biomarkers like TMB and PD-L1. Finally, we evaluated Ascore's independent prognostic performance as a non-invasive biomarker in our clinical cohort (Gulou-Cohort1) using circulating tumor cells detection, achieving an AUC of 0.803. Another clinical cohort (Gulou-Cohort2) consisted of 40 patients undergoing neoadjuvant anti-PD-1 treatment was also examined. Immunohistochemistry of Ascore in these patients revealed its correlation with the pathological response to bladder cancer immunotherapy (P = 0.004). Impressively, Ascore (AUC = 0.913) surpassed PD-L1 (AUC = 0.662) in forecasting immunotherapy response and indicated better net benefit. In conclusion, our study introduces Ascore as a novel, robust prognostic biomarker for bladder cancer, offering a new tool for enhancing immunotherapy decisions and contributing to the tailored treatment approaches in this field. [ABSTRACT FROM AUTHOR]

Compressed sensing (CS) as an efficient means has been widely applied in magnetic resonance imaging (MRI). As a regularization term to enforce the sparsity in the finite difference domain, the conventional total variation (TV) has been introduced in this field, where the staircase effect is presented. To overcome this issue, a new framework in the difference domain called joint constraint patch-based total variation (JCTV) is proposed. First, the image patch is utilized as the unit for TV norm to improve the adaptativity. Second, JCTV introduces a new nonlocal constraint term that exploits the estimated coefficients of the fully sampled image via linear minimum mean square error (LMMSE) criterion to improve the reconstruction performance. Finally, an alternative minimization algorithm is developed to seek the solution. Extensive experiments on a set of in vivo MR images demonstrate that the proposed algorithm outperforms the state-of-the-art approaches in terms of peak signal-to-noise ratio and visual quality. [ABSTRACT FROM AUTHOR]

Nonlocally centralized sparse representation (CSR) is an effective approach for estimating original image in noise. In order to promote sparse coefficients more accurate than CSR, we present a new framework where another nonlocal sparsity constraint term is introduced to work with the original term alternatively. To gain the two nonlocal sparsity constraint terms, we classify the image into different types according to the statistical characteristics of speckle in SAR image firstly. Then, we choose the appropriate methods to denoise different types of image and utilize the projected coefficients of these denoising results to estimate the nonlocal sparsity constraints. Our method not only modifies the well-salgortudied method of CSR, but also applialgories to despeckle SAR image. Experimental results, carried out on both simulated SAR images and real SAR images, demonstrate that the proposed approach has a competitive despeckling performance in terms of both evaluation indicators and visual quality assessment. [ABSTRACT FROM AUTHOR]

Chitosan (CS) is an excellent raw material for the preparation of food packaging films due to its good film-forming properties, non-toxicity, and biodegradability. However, pure chitosan films have drawbacks such as weak mechanical properties and limited antimicrobial activity. In this work, novel food packaging films containing chitosan, polyvinyl alcohol (PVA) and porous graphitic carbon nitride (g-C 3 N 4) were successfully prepared. The PVA served to improve the mechanical properties of the chitosan-based films, whilst the porous g-C 3 N 4 acted as a photocatalytically-active antibacterial agent. The tensile strength (TS) and elongation at break (EAB) of the g-C 3 N 4 /CS/PVA films both increased by ~4 times compared to the pristine CS/PVA films at the optimum g-C 3 N 4 loading of ~10 wt%. The addition of g-C 3 N 4 increase the water contact angle (WCA) of the films from 38° to 50°, whilst decreasing the water vapor permeability (WVP) from 160 × 10−12 to 135 × 10−12 g∙Pa−1 s−1 m−1. The shelf life of strawberries covered with g-C 3 N 4 /CS/PVA films at room temperature could be extended up to 96 h, compared to 48 h and 72 h for strawberries covered with polyethylene (PE) films or CS/PVA films, respectively. The g-C 3 N 4 /CS/PVA films offered good antibacterial properties against Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus). Further, the composite films could be easily recycled with the regenerated films offering almost identical mechanical properties and activities as the original films. The prepared g-C 3 N 4 /CS/PVA films thus offer promise for low-cost antimicrobial packaging applications. [Display omitted] • g-C 3 N 4 /CS/PVA photocatalytic packaging film was successfully prepared. • g-C 3 N 4 enhanced the barrier ability and antibacterial activity of the film. • PVA enhanced the mechanical properties and flexibility of the film. • The composite film showed better strawberries packaging properties. • The composite film can be easily recycled to prepare renewable film. [ABSTRACT FROM AUTHOR]

[Display omitted] • The recombinant BT GAD possessed high catalytic efficiency of 614.94 mM−1·min−1. • Crystal structures of BT GAD in different states were determined for the first time. • NTS, CTS, and β-hairpin coordinately regulated BT GAD activity at different pH. Glutamate decarboxylase catalyzes the conversion of glutamate to γ-aminobutyric acid, which plays a vital role in the gut-brain axis. Herein, a novel glutamate decarboxylase from Bacteroides thetaiotaomicron (BT GAD) was heterologously expressed. BT GAD possessed high catalytic efficiency at 60℃ and pH 3.6. As pH response, N-terminal sequence (NTS), C-terminal sequence (CTS), and β-hairpin in BT GAD coordinately regulated its activity under different pH. NTS folded into a loop under acidic pH, and the truncation of NTS severely reduced its activity to 4.2%. While CTS occupied the active site under neutral pH and became disordered to release the inhibition effect under acidic conditions. The β-hairpin, located near the active site, swung and formed open and closed conformations, which acted as an activity switch. This study provides the molecular basis for the coordinated regulation mechanism of BT GAD and lays a theoretical foundation for understanding the metabolism of dietary glutamate and its interaction relationships with the gut-brain axis. [ABSTRACT FROM AUTHOR]

Low-rank models have been widely applied for visual analysis. However, the conventional global low rank on a single whole image and the patch-level low rank have difficulty in perfectly preserving dependence (or correlation) and the latent structures in the image. Inspired by recent advances in low-rank tensor analysis, a wavelet-based low rank tensor regularization model (WLTR) is proposed in this work. Utilizing the fact that the coefficients of an image under wavelet transform exhibit sparsity, the low-rank regularization can be obtained by imposing the nuclear norm constraint on the tensor composed of wavelet subbands coefficients. Considering all structure information of intrascale and interscale coefficients under the tensor representation, the proposed method characterizes the local and global elements in a unified manner. To make the proposed WLTR tractable and robust, the alternative direction of multiplier method (ADMM) is adopted to efficiently and effectively solve this convex optimization problem. Extensive experiments on various types of image restoration problems, including inpainting, deblurring and denoising, validate WLTR outperforms several existing state-of-the-art approaches in terms of peak signal-to-noise ratio and visual quality. [ABSTRACT FROM AUTHOR]

In this work, noise enhanced parameter estimation problems are investigated for a general nonlinear system, where an additive noise is added to the nonlinear system input and a Bayesian estimator is developed based on the noise modified output. The optimal probability distribution of the additive noises is formulated successively for minimizing the mean square error (MSE) of the optimal Bayesian estimation and the Cramer–Rao lower bound (CRLB). Then the optimal additive noises for the two different noise enhanced optimization problems are explicitly derived as constant vectors, which implies the randomization of constant vectors is not beneficial to these optimizations. Finally, numerical results are presented to illustrate the theoretical results. • Exploration for the Mechanism of SR benefits Bayesian estimation problem. • Formulation of the noise enhanced Bayesian estimation model for nonlinear system. • Derivation of the noise minimizes MSE between parameter and its Bayesian estimator. • Investigation of the noise that minimizes CRLB of MSE. [ABSTRACT FROM AUTHOR]

[Display omitted] • Ecosystem services (ESs) increased in Guiyang City during 1995–2019. • Landscape composition had a greater impact on ESs than landscape configuration. • Woodland proportion and SHDI had the most significant effect on total ESs synergies. • The trade-offs and synergies of ESs might be reversed while their interaction is weak. Exploring the effects of landscape pattern changes on ecosystem services (ESs) and its interactions could provide a new method to reduce the trade-offs between ESs from the perspective of landscape pattern optimization, thus contributing to the sustainable management of ESs. In this study, the Guiyang City which is a typical karst mountainous city in China was used as the study region, using InVEST model, Spearman's correlation and Multiscale Geographically Weighted Regression (MGWR) model, the study assessed the changes and trade-offs of four key types of ESs (i.e., carbon storage (CS), habitat quality (HQ), soil conservation (SC), water yield (WY)) from 1995 to 2019, and analyzed the impacts of landscape pattern on the synergies of ESs. The results showed that ESs in Guiyang City steadily increased during 1995–2019, with CS, HQ, SC, WY, and total ecosystem services (TES) increased by 6.67%, 7.66%, 27.16%, 13.08%, and 11.81%, respectively. The relationship of CS-SC and SC-WY were mainly trade-offs, while the other ESs types were mainly synergies. Moreover, the interaction of static ESs was reversed with that of dynamic spatiotemporal ESs when the lower interaction relationship between static ESs. The effects of landscape pattern changes on ESs and ESs interactions have obvious spatial and scale heterogeneity. Landscape composition had a greater impact on ESs than landscape configuration. Proportion of woodland (Wood_per) and Shannon's Diversity Index (SHDI) were the main factors influencing the synergies effect of TES. The results could provide practical references for ESs improvement-oriented landscape pattern planning and ecosystem service management in the Guiyang City and in similar fragile ecological regions, which is helpful for the improvement of ESs and high-quality sustainable development. [ABSTRACT FROM AUTHOR]

In this paper, we give the existence of global L ∞ bounded entropy solutions for the Cauchy problem of a generalized n × n hyperbolic system of quadratic type. The main difficulty lies in establishing some compactness estimates of the viscosity solutions because the system has been generalized from 2 × 2 to n × n and some linearly degenerate characteristic fields emerged. We obtain the existence of the global weak solutions using the compensated compactness method coupled with the construction of entropy–entropy flux and BV estimates on viscosity solutions. [ABSTRACT FROM AUTHOR]

Magnetic Fe 3 O 4 –polydopamine (PDA) hybrid hollow microspheres, in which Fe 3 O 4 nanoparticles were firmly incorporated in the cross-linked PDA shell, have been prepared through the formation of core/shell PS/Fe 3 O 4 –PDA composites based on template-induced covalent assembly method, followed by core removal in a tetrahydrofuran solution. The morphology, composition, thermal property and magnetic property of the magnetic hybrid hollow microspheres were characterized by SEM, TEM, FT-IR, XRD, TGA, and vibrating sample magnetometer, respectively. Results revealed that the magnetic hybrid hollow microspheres had about 380 nm of inner diameter and about 30 nm of shell thickness, and 13.6 emu g −1 of magnetization saturation. More importantly, the Fe 3 O 4 –PDA hybrid hollow microspheres exhibited intrinsic peroxidase-like activity, as they could quickly catalyze the oxidation of typical substrates 3,3′,5,5′-tetramethylbenzidine (TMB) in the presence of hydrogen peroxide. Compared with PDA/Fe 3 O 4 composites where Fe 3 O 4 nanoparticles were loaded on the surface of PDA microspheres, the stability of Fe 3 O 4 –PDA hybrid hollow microspheres was greatly improved. As-prepared magnetic hollow microspheres might open up a new application field in biodetection, biocatalysis, and environmental monitoring. [ABSTRACT FROM AUTHOR]

In this paper, we give the global existence of L p bounded entropy solutions for the Cauchy problem of a symmetric system of Keyfitz–Kranzer type. The main difficulty lies in establishing the L p estimate of the viscosity solutions because the initial data may not be L ∞ bounded and the principle of invariant regions developed by Conley–Chuey–Smoller is invalid here. We obtain the existence of the global weak solutions using the compensated compactness method and BV estimates on viscosity solutions. [ABSTRACT FROM AUTHOR]

With the widespread and successful application of hyperspectral imaging, the task of classifying hyperspectral images has become a meaningful endeavor. This paper introduces a new approach to clustering hyperspectral images called CTNSC, which incorporates an attention mechanism to improve performance. In comparison to many current convolution-based methods for deep subspace clustering, our approach incorporates an attention mechanism to effectively capture the extensive spatial relationships that exist between objects in hyperspectral images. We combine convolution and attention through the use of Conformer blocks, enabling the network to simultaneously capture both local and global features of objects. As a result, our network can identify a more optimal deep affinity matrix, which can be utilized for spectral clustering to achieve better clustering results. We conducted experiments on three real-world datasets, and the results showed that CTNSC achieved excellent clustering performance compared to many commonly used clustering methods. [ABSTRACT FROM AUTHOR]

Co-digestion of lignocellulosic biomass and animal manure is a common approach to increase the efficiency of methane production, but the niche differentiation and microbial metabolism of the anaerobic digestion (AD) process remain to be determined. To further explore the effect of the interaction between species and their compositional niches, the methane yield and resulting microbial community were determined by machine learning (ML) and 16S rRNA gene sequencing in mixed high-solid anaerobic digestion (HS-AD) with spray-enhanced conditions to explore the internal relationship between physical and chemical parameters and microorganisms and to speculate on the enhancement mechanism of co-digestion. In this study, three ML models (extreme learning machine (ELM), artificial neural network (ANN), and random forest (RF)) were applied to analyse and model AD of dry fermentation. The results showed that the best prediction model, based on ELM, could best predict the material biogas production in this experiment with a mean absolute error (MAE/10) of 0.678 and a coefficient of determination (R2) of 0.9574, whereas the characteristic percentage analysis of the RF model showed that butyric acid, acetic acid, and pH had three important influences on the biogas production values. Meanwhile, the results of high-throughput 16S rRNA gene sequencing and PICRUSt showed that the addition of manure containing ammonia nitrogen improved the metabolism of amino acids, enriched species capable of Clostridiales and Methanosarcinales , promoted the electronic transfer of nutrient metabolism, and thus enhanced AD. Moreover, the co-occurrence network showed that seven niches were differentiated within the HS-AD system to reduce the shock of ammonia nitrogen for methanogens. Overall, microbial analysis and ML can help understand the dynamic processes of methanogenic microorganisms and predict biogas production for the efficient operation of AD. [Display omitted] • PICRUSt showed that the addition of manure containing ammonia nitrogen enhanced archaeal methanogenesis. • ELM is the most accurate model for predicting biogas production. • The characteristic factors influencing biogas production can be derived from RF. • Network analysis shows seven niches have differentiated within the HS-AD system. [ABSTRACT FROM AUTHOR]

Hyperreflexia and spasticity are chronic complications in spinal cord injury (SCI), with limited options for safe and effective treatment. A central mechanism in spasticity is hyperexcitability of the spinal stretch reflex, which presents symptomatically as a velocity-dependent increase in tonic stretch reflexes and exaggerated tendon jerks. In this study we tested the hypothesis that dendritic spine remodeling within motor reflex pathways in the spinal cord contributes to H-reflex dysfunction indicative of spasticity after contusion SCI. Six weeks after SCI in adult Sprague-Dawley rats, we observed changes in dendritic spine morphology on α-motor neurons below the level of injury, including increased density, altered spine shape, and redistribution along dendritic branches. These abnormal spine morphologies accompanied the loss of H-reflex ratedependent depression (RDD) and increased ratio of H-reflex to Mwave responses (H/M ratio). Above the level of injury, spine density decreased compared with below-injury spine profiles and spine distributions were similar to those for uninjured controls. As expected, there was no H-reflex hyperexcitability above the level of injury in forelimb H-reflex testing. Treatment with NSC23766, a Rac1-specific inhibitor, decreased the presence of abnormal dendritic spine profiles below the level of injury, restored RDD of the H-reflex, and decreased H/M ratios in SCI animals. These findings provide evidence for a novel mechanistic relationship between abnormal dendritic spine remodeling in the spinal cord motor system and reflex dysfunction in SCI. [ABSTRACT FROM AUTHOR]

• Adopting density functional theory screening method to evaluate MOFs adsorbent. • Three adsorbents were found the best activity with adsorption energy <−1.21 eV. • The adsorption units in action consists of metal centers and coordination atoms. • D-band center of units remain unchanged is the origin of high performance. Sulfides, widely found in fossil fuels, not only corrode equipment but also pollute the atmosphere. Adsorption desulphurization can not only remove sulfide effectively, but also reduce energy consumption, it is very necessary to develop desulphurization adsorbent. Metal-organic framework materials (MOFs) have great potential in adsorption desulfurization due to the unique structural properties. However, selecting high-performance adsorbents in the growing sea of MOFs by experiment still needs theoretical guidance. Therefore, the screening method based on density functional theory was adopted to develop the thiophene adsorbents and explore the overall picture of thiophene adsorption. Through applying a three-step screening strategy which involves, we evaluated adsorption performance of 12,020 computationally-ready experimental MOFs candidates. Three adsorbents were found the best activity with adsorption energy <-1.21 eV. According to the classification and electronic structure analysis, it is found that different combinations of ligand atoms and open metal site can induce different strength of d -band center movement during the adsorption process. The high-performance adsorbents are those d -band center of metal sites remain unchanged in the adsorption of thiophene. These results emphasize the importance of the structure-performance relationship of potential MOFs in adsorption desulfurization. [Display omitted] We evaluated the origin of adsorption capacity of MOFs for thiophene through high-throughput method in this work. By concentrating on the composition, structure and coordination environment, all candidates were subsumed into the 'twenty-two kinds of metal sites, two ligand atoms and four coordination number' matrix of Figure c. Three structures were proved the best thiophene adsorption activity (pentagram represented). [ABSTRACT FROM AUTHOR]

Background and Aims According to the floral ABC model, B-function genes appear to play a key role in the origin and diversification of the perianth during the evolution of angiosperms. The basal angiosperm Hedyosmum orientale (Chloranthaceae) has unisexual inflorescences associated with a seemingly primitive reproductive morphology and a reduced perianth structure in female flowers. The aim of this study was to investigate the nature of the perianth and the evolutionary state of the B-function programme in this species. Methods A series of experiments were conducted to characterize B-gene homologues isolated from H. orientale, including scanning electron microscopy to observe the development of floral organs, phylogenetic analysis to reconstruct gene evolutionary history, reverse transcription–PCR, quantitative real-time PCR and in situ hybridization to identify gene expression patterns, the yeast two-hybrid assay to explore protein dimerization affinities, and transgenic analyses in Arabidopsis thaliana to determine activities of the encoded proteins. Key Results The expression of HoAP3 genes was restricted to stamens, whereas HoPI genes were broadly expressed in all floral organs. HoAP3 was able to partially restore the stamen but not petal identity in Arabidopsis ap3-3 mutants. In contrast, HoPI could rescue aspects of both stamen and petal development in Arabidopsis pi-1 mutants. When the complete C-terminal sequence of HoPI was deleted, however, no or weak transgenic phenotypes were observed and homodimerization capability was completely abolished. Conclusions The results suggest that Hedyosmum AP3-like genes have an ancestral function in specifying male reproductive organs, and that the activity of the encoded PI-like proteins is highly conserved between Hedyosmum and Arabidopsis. Moreover, there is evidence that the C-terminal region is important for the function of HoPI. Our findings indicate that the development of the proposed perianth in Hedyosmum does not rely on the B homeotic function. [ABSTRACT FROM PUBLISHER]

Small-fiber neuropathy (SFN) is characterized by injury to small-diameter peripheral nerve axons and intraepidermal nerve fibers (IENF). Although mechanisms underlying loss of IENF in SFN are poorly understood, available data suggest that it results from axonal degeneration and reduced regenerative capacity. Gain-of-function variants in sodium channel NaV1.7 that increase firing frequency and spontaneous firing of dorsal root ganglion (DRG) neurons have recently been identified in ∼30% of patients with idiopathic SFN. In the present study, to determine whether these channel variants can impair axonal integrity, we developed an in vitro assay of DRG neurite length, and examined the effect of 3 SFN-associated variant NaV1.7 channels, I228M, M932L/V991L (ML/VL), and I720K, on DRG neurites in vitro. At 3 days after culturing, DRG neurons transfected with I228M channels exhibited ∼20% reduced neurite length compared to wild-type channels; DRG neurons transfected with ML/VL and I720K variants displayed a trend toward reduced neurite length. I228M-induced reduction in neurite length was ameliorated by the use-dependent sodium channel blocker carbamazepine and by a blocker of reverse Na-Ca exchange. These in vitro observations provide evidence supporting a contribution of the I228M variant NaV1.7 channel to impaired regeneration and/or degeneration of sensory axons in idiopathic SFN, and suggest that enhanced sodium channel activity and reverse Na-Ca exchange can contribute to a decrease in length of peripheral sensory axons. Ann Neurol 2012 [ABSTRACT FROM AUTHOR]

Summary: How inflammation causes cancer is unclear. Interleukin-15 (IL-15) is a pro-inflammatory cytokine elevated in human large granular lymphocyte (LGL) leukemia. Mice overexpressing IL-15 develop LGL leukemia. Here, we show that prolonged in vitro exposure of wild-type (WT) LGL to IL-15 results in Myc-mediated upregulation of aurora kinases, centrosome aberrancies, and aneuploidy. Simultaneously, IL-15 represses miR-29b via induction of Myc/NF-κBp65/Hdac-1, resulting in Dnmt3b overexpression and DNA hypermethylation. All this is validated in human LGL leukemia. Adoptive transfer of WT LGL cultured with IL-15 led to malignant transformation in vivo. Drug targeting that reverses miR-29b repression cures otherwise fatal LGL leukemia. We show how excessive IL-15 initiates cancer and demonstrate effective drug targeting for potential therapy of human LGL leukemia. [ABSTRACT FROM AUTHOR]

Abstract: Personalized medicine aims to deliver the right drug to a right patient at the right time. It offers unique opportunities to integrate new technologies and concepts to disease prognosis, diagnosis and therapeutics. While selective personalized therapies are conceptually impressive, the majority of cancer therapies have dismal outcome. Such therapeutic failure could result from no response, drug resistance, disease relapse or severe side effect from improper drug delivery. Nanomedicine, the application of nanotechnology in medicine, has a potential to advance the identification of diagnostic and prognostic biomarkers and the delivery of right drug to disease sites. Epigenetic aberrations dynamically contribute to cancer pathogenesis. Given the individualized traits of epigenetic biomarkers, epigenetic considerations would significantly refine personalized nanomedicine. This review aims to dissect the interface of personalized medicine with nanomedicine and epigenetics. I will outline the progress and highlight challenges and areas that can be further explored perfecting the personalized health care. [Copyright &y& Elsevier]