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General deep learning-based methods for infrared and visible image fusion rely on the unsupervised mechanism for vital information retention by utilizing elaborately designed loss functions. However, the unsupervised mechanism depends on a well-designed loss function, which cannot guarantee that all vital information of source images is sufficiently extracted. In this work, we propose a novel interactive feature embedding in a self-supervised learning framework for infrared and visible image fusion, attempting to overcome the issue of vital information degradation. With the help of a self-supervised learning framework, hierarchical representations of source images can be efficiently extracted. In particular, interactive feature embedding models are tactfully designed to build a bridge between self-supervised learning and infrared and visible image fusion learning, achieving vital information retention. Qualitative and quantitative evaluations exhibit that the proposed method performs favorably against state-of-the-art methods.

Hierarchical quotient space structure (HQSS), as a typical description of granular computing (GrC), focuses on hierarchically granulating fuzzy data and mining hidden knowledge. The key step of constructing HQSS is to transform the fuzzy similarity relation into fuzzy equivalence relation. However, on one hand, the transformation process has high time complexity. On the other hand, it is difficult to mine knowledge directly from fuzzy similarity relation due to its information redundancy, i.e., sparsity of effective information. Therefore, this article mainly focuses on proposing an efficient granulation approach for constructing HQSS by quickly extracting the effective value of fuzzy similarity relation. First, the effective value and effective position of fuzzy similarity relation are defined according to whether they could be retained in fuzzy equivalence relation. Second, the number and composition of effective values are presented to confirm that which elements are effective values. Based on these above theories, redundant information and sparse effective information in fuzzy similarity relation could be completely distinguished. Next, both isomorphism and similarity between two fuzzy similarity relations are researched based on the effective value. The isomorphism between two fuzzy equivalence relations is discussed based on the effective value. Then, the algorithm with low time complexity for extracting effective values of fuzzy similarity relation is introduced. On the basis, the algorithm for constructing HQSS is presented to realize efficient granulation of fuzzy data. The proposed algorithms could accurately extract effective information from the fuzzy similarity relation and construct the same HQSS with the fuzzy equivalence relation while greatly reducing the time complexity. Finally, relevant experiments on 15 UCI datasets, 3 UKB datasets, and 5 image datasets are shown and analyzed to verify the effectiveness and efficiency of the proposed algorithm.

To overcome the disadvantage of the Arrhenius constitutive (AC) equation in predicting complex nonlinear flow behaviors, this work employed an artificial neural network (ANN) to introduce a proportional coefficient reflecting changes in softening mechanisms under various hot deformation conditions, thereby enhancing the applicability of the AC model. The result demonstrates that, compared to the AC model, the ANN-AC model effectively compensates for errors resulting from different softening mechanisms during hot deformation, with RMSE and MAPE decreasing by 62.47% and 63.75%, respectively. Additionally, the microstructure aligns with the evolution of the power dissipation factor (η) predicted by the ANN-AC model, indicating the map's accuracy. Microstructure analysis shows that discontinuous dynamic recrystallization (DDRX) grains nucleate adjacent to the original grain boundaries at low temperatures and high strain rates, while continuous dynamic recrystallization (CDRX) grains primarily form within original grains at high temperatures and low strain rates. The results reveal the effect of grain orientation on DRX, with <001>//CD (compression direction) oriented grains capable of activating multiple slip systems, indicating a propensity for the CDRX mechanism, whereas <101>//CD oriented grains, with fewer slip systems, promote DDRX through coordinated deformation via grain boundary motion.

Multistage thermomechanical treatment experiments were conducted on Cu–Ni–Co–Si–Mg alloy strip prepared by the Heating Cooling Combined Mold (HCCM) horizontal continuous casting-cold rolling process. Effects of various heat treatments on the microstructure, mechanical properties, and electrical conductivity of the alloy were studied. The strengthening mechanisms and factors influencing the performance of each process has been analyzed. The tensile strength, yield strength, and electrical conductivity of Cu–Ni–Co–Si–Mg alloy can reach 894 MPa, 855 MPa, and 47.1 %IACS after a third-stage of thermomechanical treatment (TTMT). The cold rolling in first-stage of thermomechanical treatment (FTMT) not only caused work hardening of the alloy but also promoted the precipitation of solute atoms and the growth of second phase particles, limiting the increase in strength. Second-stage of thermomechanical treatment (STMT) effectively hindered the excessive growth of second phase particles in FTMT but shortened recrystallization process. The superior performance of Cu–Ni–Co–Si–Mg alloy after TTMT was attributed to dispersive precipitation of Ni, Co, and Si elements as (Ni, Co) 2Si phases in the copper matrix, strengthening the interaction between the precipitates and dislocations. A short process of HCCM horizontal continuous casting-cold rolling-thermomechanical treatment was developed to produce a high strength and highly electrically conductive Cu–Ni–Co–Si alloy strip used in lead frames.

In the field of medical chemistry and other organic chemistry, introducing a methyl group into a designed position has been difficult to achieve. However, owing to the vigorous developments in the field of enzymology, methyltransferases are considered potential tools for addressing this problem. Within the methyltransferase family, Fur6 catalyzes the methylation of C3 of 1,2,4,5,7-pentahydroxynaphthalene (PHN) using S-adenosyl-l-methionine (SAM) as the methyl donor. Here, we report the catalytic mechanism and substrate specificity of Fur6 based on computational studies. Our molecular dynamics (MD) simulation studies reveal the reactive form of PHN and its interactions with the enzyme. Our hybrid quantum mechanics/molecular mechanics (QM/MM) calculations suggest the reaction pathway of the methyl transfer step in which the energy barrier is 8.6 kcal mol–1. Our free-energy calculations with a polarizable continuum model (PCM) indicate that the final deprotonation step of the methylated intermediate occurs after it is ejected into the water solvent from the active center pocket of Fur6. Additionally, our studies on the protonation states, the highest occupied molecular orbital (HOMOs), and the energy barriers of the methylation reaction for the analogs of PHN demonstrate the mechanism of the specificity to PHN. Our study provides valuable insights into Fur6 chemistry, contributing to a deeper understanding of molecular mechanisms and offering an opportunity to engineer the enzyme to achieve high yields of the desired product(s).

Aqueous zinc-ion batteries (AZIBs) already become a potential candidate for high-efficiency energy storage in view of inherent safety and abundant zinc reserves. Nevertheless, the progress of AZIBs cathode materials with excellent comprehensive performance still retains formidable challenges. Herein, the three-dimensional amorphous vanadium pentoxide@graphene (3D a-V2O5@graphene) microspheres were prepared and investigated as the cathode material of AZIBs. The amorphous characteristics of a-V2O5and the three-dimensional graphene framework with outstanding conductivity synergistically enabled the 3D a-V2O5@graphene microspheres to expose more active sites and achieve rapid ion/electron transfer. Consequently, the obtained a-V2O5@graphene presented a promising specific capacity of 518 mAh g–1under 0.5 A g–1and a stable long-term cycle with an eminent remaining capacity of 177 mAh g–1over 2000 cycles under 40 A g–1. Meanwhile, the storage mechanism also was illuminated by various ex situ characterization tests. Hence, this study provides a new viewpoint for the design of advanced AZIBs based on amorphous cathode materials.

Low-resolution characteristics of multispectral images restrict their usability. Various approaches (e.g., single-image super-resolution reconstruction (SISR) and pansharpening method) have been proposed to enrich the spatial details of low-resolution multispectral images (LRMSs) to obtain high-resolution ones. While the pansharpening method inevitably depends on panchromatic (PAN) images, which limits its application scenarios, SISR does not need auxiliary images, yet the blurred edge details within the reconstructed super-resolution multispectral (SRMS) images still remain a big challenge. In this work, we propose a novel high-frequency feature transfer (HFFT-PAN) method for multispectral image super-resolution to tackle the above drawbacks. Specifically, we first exploit the inherent low-frequency features among LRMS images to facilitate the extraction of high-frequency features from PAN images. After that, the high-frequency features from PAN images are transferred to the reconstruction procedure of multispectral images so that the SRMS images can not only benefit from the edge detail information from PAN images but also avoid the utilization of any PAN images during inference. Moreover, we employ an additional contrastive loss during training to ensure the fidelity of the generated SRMS images. Qualitative and quantitative evaluations exhibit that the proposed method performs favorably against state-of-the-art methods. The model and code are available at https://github.com/wx0110wx/HFFT.

Sensitive and accurate determination of glyphosate (GLYP) is vital for food safety and environmental protection. Herein, a novel electrochemical ratiometric biosensor was designed for the accurate quantification of GLYP through one-step electrodeposition of MWCNTs-Cu MOF films. MWCNTs-Cu MOF nanostructures were directly electro-synthesized in situon the electrode from the precursor solution. The combination of Cu MOFs with MWCNTs not merely improved the conductivity of MOFs, but also enhanced the sensitivity of the biosensor. Furthermore, Cu sites within Cu MOFs were turned into CuCl to further amplify the current signal and enable the specific recognition of GLYP through competing reactions with the transformation of CuCl into non-electroactive Cu-GLYP. Meanwhile, internal reference molecules of methylene blue (MB) were incorporated to improve the measurement accuracy of GLYP for reducing unpredictable measurement errors aroused by environmental deviations. The ratiometric electrochemical sensor exhibited a high linearity with the logarithmic value of GLYP concentration from 0.5 nM to 400 nM. The detection limit was estimated to be as low as 0.014 nM. Finally, the present sensor with ratiometric signal export was applied for GLYP analysis in real samples with high sensitivity and accuracy. The simplicity and reliability of the ratiometric sensor make it a worthy and powerful tool for food and environmental monitoring. This design strategy also provides an avenue for the development of simple and efficient biosensors for other substances.

Granular computing is an umbrella term to cover a series of theories, methodologies, techniques, and tools that make use of information granules in complex problem solving. Rough sets, as one of the main concrete models of granular computing, has attracted considerable attention and has been successfully applied to numerous kinds of fields. To show the basic ideas and principles of granular computing from the perspective of rough sets, the main models, uncertainty measures and applications of rough sets are surveyed in the paper.

BackgroundCardiovascular diseases (CVDs) are the leading cause of death in the USA, and high blood pressure is a major risk factor for CVD. Despite the overall declining rates of CVD mortality in the USA in recent years, marked disparities between racial and ethnic groups persist, with black adults having a higher mortality rate than white adults. We investigated the extent to which blood pressure mediated the black-white disparity in CVD mortality.MethodsData came from the Multi-Ethnic Study of Atherosclerosis, a diverse longitudinal cohort. We included 1325 black and 2256 white community-based adults aged 45–80 years free of clinical CVD at baseline and followed for 14 years. We used causal mediation analysis to estimate the effect of race on CVD mortality that was mediated through blood pressure.ResultsBlack participants had a higher hazard of dying from CVD compared with white participants (adjusted hazard ratio (HR): 1.28 (95% CI 0.88, 1.88)), though estimates were imprecise. Systolic blood pressure mediated 27% (HR: 1.02, 95% CI 1.00, 1.06) and diastolic blood pressure mediated 55% (HR: 1.07, 95% CI 1.01, 1.10) of the racial disparities in CVD mortality between white and black participants. Mediation effects were present in men but not in women.ConclusionsWe found that black-white differences in blood pressure partially explain the observed black-white disparity in CVD mortality, particularly among men. Our findings suggest that public health interventions targeting high blood pressure prevention and management could be important strategies for reducing racial disparities in CVD mortality.

• Multi-objective genetic algorithm (NSGA-II) was used for developing new aluminum alloy. • Strength, plasticity, and corrosion resistance were simultaneously enhanced. • Designed low-alloyed aluminum alloy achieved mechanical properties similar to high-Cu-content alloys. Al-Mg-Si alloys with high strength and good corrosion resistance are regarded as desirable materials for all-aluminum vehicles. However, the traditional trial-and-error experimental methods are insufficient to address the trade-off between strength and corrosion resistance. In this work, a non-dominated sorting genetic machine-learning algorithm (NSGA-II) was employed to optimize the chemical composition, so as to simultaneously improve the strength and corrosion resistance. Three high-performance Al-Mg-Si alloys with low Mg, Si, and Cu contents were successfully developed, where the yield strength (YS), ultimate tensile strength (UTS), and the elongation (δ) reached 375–380 MPa, 410–416 MPa, and 13.7%–15.2%, respectively. Compared with higher-Cu-content 6013 alloy, the YS and UTS of the present alloys increase by about 60 MPa, and the intergranular corrosion resistance is also significantly improved. Microstructure characterization demonstrated that β'' and QP phases introduced a significant synergistic precipitation strengthening effect; the dispersoids formed by trace Mn, Cr, Fe, Zr, and Ti contributed dispersion strengthening effect; and the good pitting corrosion resistance is attributed to lower Mg and Si contents. [Display omitted] [ABSTRACT FROM AUTHOR]

The aim of weakly supervised object co-localization is to locate different objects of the same superclass in a dataset. Recent methods achieve impressive co-localization performance by multiple instance learning and self-supervised learning. However, these methods ignore the common part information shared by fine-grained objects and the influence of the complementary parts on the co-localization of the fine-grained objects. To solve these issues, we propose a complementary parts contrastive learning method for fine-grained weakly supervised object co-localization. The proposed method follows such an assumption that fine-grained object parts with the same/different semantic meaning should have similar/dissimilar feature representations in the feature space. The proposed method tackles two critical issues in this task: $i)$ how to spread the model’s attention and suppress the complex background noise, and $ii)$ how to leverage the cross-category common parts information to mitigate the context co-occurrence problem. To address $i)$ , we attempt to integrate local and context cues via three types of attention including self-supervised attention, channel, and spatial attention to spread the model’s attention toward automatically identifying and localizing most discriminative parts of objects in the fine-grained images. To solve $ii)$ , we propose a cross-category object complementarity part contrastive learning module to identify the extracted part regions with different semantic information by pulling the same part features closer and pushing different part features away, which can mitigate the confounding bias caused by the co-occurrence surroundings within specific classes. Extensive qualitative and quantitative evaluations demonstrate the effectiveness of the proposed method on four fine-grained co-localization datasets: CUB-200–2011, Stanford Cars, FGVC-Aircraft, and Stanford Dogs. Code and models are available at https://github.com/Zhao-fan/CPCL.

Monoubiquitination of histone H2B-K120/123 plays several roles in regulating transcription, DNA replication and the DNA damage response. The structure of a nucleosome in complex with the dimeric RING E3 ligase Bre1 reveals that one RING domain binds to the nucleosome acidic patch, where it can position the E2 ubiquitin conjugating enzyme Rad6, while the other RING domain contacts the DNA. Comparisons with H2A-specific E3 ligases suggest a general mechanism of tuning histone specificity via the non-E2-binding RING domain.

As one of the rapidly developing methodologies for dealing with complex problems in line with human cognition, granular computing has made significant achievements in knowledge discovery. Neighborhood classifier, as a typical description of granular computing, is an effective method for the classification of continuous data. However, in the phase of constructing neighborhood rules, the existing neighborhood classifiers are divided into the following two modes and both have defects: 1) the strategy driven by center: there are a lot of overlap and inclusion among neighborhood rules, that is, it needs to spend much time to reduce redundancy rules; and 2) the strategy driven by rule: there are many rules containing only one object, which cannot form an effective covering and would affect knowledge acquisition in the incremental environment. Therefore, in this article, fuzzy quotient space theory is introduced to construct neighborhood rules. Based on the optimal granularity of fuzzy quotient space, first, a neighborhood covering classifier, which has no redundant rules and could form the effective covering, is proposed without any artificial parameter. Second, comprehensively considering the knowledge purity and complexity, the quality measure of granularity is proposed, which guides the optimal granularity selection of hierarchical quotient space structure. Third, neighborhood rules are constructed in optimal granularity. Then, the offset of center is introduced to describe the membership degree of the test object to different neighborhood rules, and the neighborhood allocation strategy is proposed accordingly. Next, an algorithm for the neighborhood covering classifier based on these theories is proposed. Finally, experiments on 13 UCI datasets and three real datasets are carried out to verify the performance of the proposed classifier from four common classification indexes.

Granular computing, a new paradigm for solving large-scale and complex problems, has made significant progresses in knowledge discovery. Granular ball computing (GBC) is a novel granular computing method, which can rapidly generate scalable and robust information granules, that is, granular balls. However, a comprehensive index for measuring the performance of a granular ball does not exist. Furthermore, GBC lacks a mechanism to deal with dynamic decision systems. Therefore, in this study, the quality index of a granular ball is first formulated. Next, with this index, a novel granular ball rough sets model (GBRS) based on GBC is proposed. GBRS is more conducive to learning knowledge from uncertain datasets and more suited to incremental learning than the latest granular ball neighborhood rough sets model based on GBC. Subsequently, an incremental mechanism is introduced into GBRS, and two incremental learning models are developed for objects increasing in stream patterns and batch patterns, respectively. In the incremental learning process, three patterns of granular balls, that is, update, fusion, and split, were well studied when a set of objects was added to the decision system. Finally, to verify the effectiveness and efficiency, we apply GBRS and these two incremental learning models into classification tasks. Compared with four current state-of-the-art classification methods based on granular computing and four classical classifiers in machine learning, the proposed classifiers in this paper achieve higher classification accuracy as well as better efficiency on benchmark datasets.

The existing models for vestibulo-ocular reflex (VOR) and optokinetic response (OKR) learning utilize neural circuit structure and capture a few characteristics of these two learning systems. However, it remains unclear how the error signals guide these learning processes. Here, we propose novel dynamic learning models using error feedback in a flexible fashion to account for both VOR and OKR learning. We first used a feedback modulation model (FMM) and found the error signals play an essential guiding role in the gain compensation of wild-type mice. However, this FMM cannot accurately reproduce gain changes during the recovery period. Therefore, we propose a nonuniform FMM using flexible plasticity learning rules of different memory sites to take into account the effect of classical linearity models in both training and recovery periods. To further study learning characteristics of gain reduction, we introduce a reversal-phase FMM and explore the contribution of synaptic plasticity to adaptive learning, in which characteristics and bidirectional synaptic plasticity in the VOR-decrease learning mode can be fully recovered. Taken together, our results suggest that, to explain VOR and OKR learning systems, one needs dynamical models with flexible and multiple components at different or same sites of neuronal circuits.

Oxidative stress is a common phenomenon in poultry production. Several molecules, including antioxidant genes, miRNAs, and gut microbiota metabolites, have been reported to participate in redox regulation. Lactiplantibacillus plantarumP8 (P8) was shown to improve the antioxidant capacity of chickens, but the specific molecular mechanisms remain unclear. In this study, 400 broilers were allocated to 4 treatment groups: control diet (Con group), control diet + dexamethasone injection (DEX group), control diet containing 1 × 108 CFU/g P8 (P8 group), and control diet containing 1 × 108 CFU/g P8 + DEX injection (DEX_P8 group). Integrated analysis of the microbiome, metabolomics, and miRNAomics was conducted to investigate the roles of P8 in oxidative stress in broilers. Results demonstrated that P8 supplementation significantly improved growth performance, jejunal morphology, and antioxidant function in DEX-treated broilers. Analysis of the gut microbiota revealed a higher abundance of Barnesiella(P = 0.01) and Erysipelatoclostridium(P = 0.05) in the DEX_P8 group than in the DEX group. Functional prediction indicated that certain pathways, including the phenylacetate degradation pathway, were enriched in the DEX_P8 group compared to the DEX group. Metabolites in the cecal contents were distinct between the groups. P8 supplementation increased the content of metabolites with antioxidant capacity, e.g., urobilinogen (P < 0.01), and decreased that of metabolites related to oxidative stress, e.g., genistein (P < 0.01). Functional prediction indicated that metabolites that differed between the DEX_P8 and DEX groups were enriched in pathways including “tryptophan metabolism” and “primary bile acid biosynthesis”. The miRNAomics analysis further showed that, compared to the DEX group, several miRNAs in the jejunum, such as gga-miR-21-3p (P = 0.03), were increased, whereas gga-miR-455-3p (P = 0.02) was decreased in the DEX_P8 group. The PI3K-Akt, Ras, and Rap1 signaling pathways were enriched in the DEX_P8 group compared to the DEX group through KEGG analysis. Correlation analysis revealed potential interactions between growth performance, oxidation/antioxidation, jejunal morphology, gut microbiota, cecal content metabolites, and jejunal miRNAs. Overall, our results indicate that P8 supplementation may improve the growth performance, jejunal morphology and antioxidant capacity of DEX-treated broilers by regulating gut microbiota, its metabolites, and intestinal miRNAs.

Cu-1.3 wt%Ni-1.0 wt%Co-0.9 wt%Si-0.1 wt%Mg alloy strip with 10 mm in thickness produced by heating-cooling combined mold (HCCM) horizontal continuous casting was cold rolled. Microstructure evolution and mechanical properties of the cold-rolled alloy strips with different reduction were studied, and the deformation mechanism was clarified. The results showed that the continuous casting strips had axial columnar grain with main <001> orientations and straight small angle grain boundaries, the elongation after fracture was up to 25.0%, which can be directly processed by large deformation cold rolling, and the maximum cumulative cold deformation was up to 99%.When the reduction was 40% and 60%, the dislocation bands crossed each other and shear bands formed, and the alternating distribution of soft/hard oriented grains were conducive to improve the deformation coordination ability of micro-region under high strain. When the deformation exceeded 80%, deformation twins formed and the twins had strong interaction with the shear band and grain boundaries, resulting in strong shear and rotation of the local grains. The tensile strength and hardness increased from 464 MPa to 137HV of the as-cast strip to 629 MPa and 208HV with reduction 90%, respectively, while the elongation decreased from 25.0% to 4.1%. These results can lay a foundation for the development of compact method for producing high performance Cu–Ni–Co–Si alloy strips.

The formation of manganese (Mn) oxides is influenced by environmental conditions and, in some red soils, Mn oxides occur as coatings on the surface of kaolinite particles in the form of colloidal films or fine particles. The present study aimed to explore the types of formation mechanisms of Mn oxide minerals on the surface of kaolinite. Mn oxide minerals synthesized by reducing the Mn in KMnO4with a divalent Mn salt (MnSO4) were examined using X-ray diffraction (XRD) and scanning electron microscopy (SEM). The effects of various initial molar ratios of Mn2+/Mn7+(R = 1:0.67, 1:1, 1:2, and 1:4), cationic species (Na+or Mg2+), synthesis temperatures (30, 60, and 110°C), and amount of added kaolinite (0.25, 0.5, 1.0, 2.0, and 5.0 g) on the formation of Mn oxides were studied. The results showed that Mn oxide mineral types were affected by the initial R value and the background cation. With decreases in the initial R value, the synthesized minerals transformed from cryptomelane to birnessite. The relative mass ratios of kaolinite to Mn oxide were calculated as 1:0.92, 1:0.63, 1:1.15, and 1:1.63. The sodium cation (Na+) had a greater role than Mg2+in promoting the dissolution–recrystallization of birnessite to cryptomelane. The synthesis temperature had no effect on mineral types, but Mn content increased as temperature increased. When the amount of added kaolinite was increased from 0.25 to 5.0 g, Mn oxide minerals formed gradually and transformed from birnessite to cryptomelane. This work revealed a possible formation process and reaction mechanism on the surface of kaolinite particles in some red soils.

ERP vendors are rapidly updating their systems with emerging technology every year. Many companies are trying to catch up with the speed by upgrading their current ERP systems. Although various IS acceptance models, including the TAM model, were developed to understand the ERP end-users' behavioural intention, few studies have examined the effects of familiarity from a user perspective. This study focuses on usability issues of current ERP systems and gains an in-depth understanding of familiarity in the context of ERP continuance usage. We collected data from a user practice experiment to investigate how this cognitive and affective factor, familiarity, is interrelated with ERP users' continuance intention. The results support the criticism of TAM and show the importance of familiarity as an additional critical construct to the context of ERP adoption. Implications for both academic research and practice, as well as suggestions for future studies, are discussed.

A novel electrochemical microsensor was developed for the ratiometric and simultaneous determination of hydrogen peroxide (H2O2) and ascorbic acid (AA) based on the borate-phenol “switch” recognition mechanism and carbon nanotube (CNT) catalytic characteristics. First of all, a carbon fiber microelectrode (CFME) was coated with CNTs. Then, a specific probe, 9-anthraceneboronic acid pinacol ester (9-AP), was screened and decorated on CNTs through π–π stacking for the recognition of H2O2based on the transformation of boric acid ester into electroactive phenols. CNTs not only served as the amplifiers of current signals, but also as catalysts facilitating AA oxidation. Meanwhile, ferrocenecarboxylic acid (Fc), inert to H2O2and AA, was modified on another amino-functionalized CNT microelectrode viaan amide bond as an internal reference channel for avoiding errors caused by environmental discrepancies. The two-channel ratiometric microsensor enabled the sensitive and accurate detection of H2O2and AA simultaneously, and the detection limits were estimated to be 0.09 μM and 4.12 μM, respectively. The developed microsensor with remarkable analytical performance was finally applied for the simultaneous detection of H2O2and AA in the live rat brain.

Ischemia/reperfusion injury (IRI) is prone to occur after kidney transplantation, leading to delayed graft function (DGF). MicroRNAs play a crucial role in the pathogenesis of ischemia/reperfusion–induced acute kidney injury, and miR-20a-5p was found to be the most significantly upregulated gene in a DGF patient cohort. However, the roles of microRNAs in transplanted kidneys remain largely unknown. In this study, we found that miR-20a-5p was upregulated in the kidneys of acute kidney injury mice and in patients with DGF. We identified early growth response-1 as a critical upstream target and verified the binding of early growth response-1 to a predicted sequence in the promoter region of the miR-20a-5p gene. Functionally, the miR-20a-5p mimic attenuated IRI and postischemic renal fibrosis, whereas the miR-20a-5p inhibitor delivery aggravated IRI and fibrosis. Importantly, delivery of the miR-20a-5p mimic or inhibitor in the donor kidneys attenuated or aggravated renal loss and structural damage in cold storage transplantation injury. Furthermore, our study identified miR-20a-5p as a negative regulator of acyl-CoA synthetase long-chain family member 4 (ACSL4) by targeting the 3′ untranslated region of ACSL4 mRNA, thereby inhibiting ACSL4-dependent ferroptosis. Our results suggest a potential therapeutic application of miR-20a-5p in kidney transplantation through the inhibition of ACSL4-dependent ferroptosis.

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The greenhouse effect has always been a problem troubling various country, many fields have made corresponding technological improvements and regulations, and the shipping industry is no exception. In the shipping field, governments are actively looking for viable low-carbon/zero-carbon alternative fuels to reduce their dependence on traditional fossil fuels. This paper discusses the challenges and opportunities of replacing fuel oil with clean energies. Firstly, the alternative fuels that have been proposed frequently and widely in recent years are summarized, and their sources, adaptive power systems, and relationships among fuels are systematically summarized. Secondly, when evaluating the advantages and future development trends of each energy, the environmental, economic and safety factors are digitally quantified. Results show that the analysis focuses on the efficiency and economics of carbon reduction. Hydrogen, ammonia and nuclear energy show advantages in environmental quantification factors, while LNG, biofuels and alcohols show benefits in economic quantification factors considering calorific value and fuel price, and LNG and alcohols received high scores in safety assessment. Finally, the study predicts the evolution and development trend of ship fuels in the future, and evaluates the most suitable energy for ship development in different periods.

The ability to effectively detect bacterial infection in human tissues is important for the timely treatment of the infection. However, traditional techniques fail to visualize bacterial species adhered to host cells in situin a target-specific manner. Dihydropteroate synthase (DHPS) exclusively exists in bacterial species and metabolically converts p-aminobenzoic acid (PABA) to folic acid (FA). By targeting this bacterium-specific metabolism, we have developed a fluorescent imaging probe, PABA-DCM, based on the conjugation of PABA with a long-wavelength fluorophore, dicyanomethylene 4H-pyran (DCM). We confirmed that the probe can be used in the synthetic pathway of a broad spectrum of Gram-positive and negative bacteria, resulting in a significantly extended retention time in bacterial over mammalian cells. We validated that DHPS catalytically introduces a dihydropteridine group to the amino end of the PABA motif of PABA-DCM, and the resulting adduct leads to an increase in the FA levels of bacteria. We also constructed a hydrogel dressing containing PABA-DCMand graphene oxide (GO), termed PABA-DCM@GO, that achieves target-specific fluorescence visualization of bacterial infection on the wounded tissues of mice. Our research paves the way for the development of fluorescent imaging agents that target species-conserved metabolic pathways of microorganisms for the in situmonitoring of infections in human tissues.

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.compind.2009.12.005 Byline: Xiaowen Fang (a), Fan Zhao (b) Keywords: Sensation seeking; Self-forgetfulness; Personality; Computer game; Enjoyment Abstract: This paper introduces a research framework of game play based on a review of media enjoyment theories, personality theories, effects of computer game play, and technology acceptance model. The proposed framework suggests that an appropriate fit between characteristics of the player and gaming technology will result in greater enjoyment while social influence may moderate effects of the fit. An empirical study is carried out to investigate the relationship between enjoyment of computer game play and two personality traits (sensation seeking and self-forgetfulness). Hypotheses are proposed. A survey is conducted in two US universities. Results and implications are discussed. Author Affiliation: (a) School of Computing, College of Computing and Digital Media, DePaul University, United States (b) Lutgert College of Business, Florida Gulf Coast University, United States

Multi-scale decision system (MDS) is an effective tool to describe hierarchical data in machine learning. Optimal scale combination (OSC) selection and attribute reduction are two key issues related to knowledge discovery in MDSs. However, searching for all OSCs may result in a combinatorial explosion, and the existing approaches typically incur excessive time consumption. In this study, searching for all OSCs is considered as an optimization problem with the scale space as the search space. Accordingly, a sequential three-way decision model of the scale space is established to reduce the search space by integrating three-way decision with the Hasse diagram. First, a novel scale combination is proposed to perform scale selection and attribute reduction simultaneously, and then an extended stepwise optimal scale selection (ESOSS) method is introduced to quickly search for a single local OSC on a subset of the scale space. Second, based on the obtained local OSCs, a sequential three-way decision model of the scale space is established to divide the search space into three pair-wise disjoint regions, namely the positive, negative, and boundary regions. The boundary region is regarded as a new search space, and it can be proved that a local OSC on the boundary region is also a global OSC. Therefore, all OSCs of a given MDS can be obtained by searching for the local OSCs on the boundary regions in a step-by-step manner. Finally, according to the properties of the Hasse diagram, a formula for calculating the maximal elements of a given boundary region is provided to alleviate space complexity. Accordingly, an efficient OSC selection algorithm is proposed to improve the efficiency of searching for all OSCs by reducing the search space. The experimental results demonstrate that the proposed method can significantly reduce computational time.

Uncertain Knowledge Graphs (UKGs) are used to characterize the inherent uncertainty of knowledge and have a richer semantic structure than deterministic knowledge graphs. The research on the embedding of UKG has only recently begun, Uncertain Knowledge Graph Embedding (UKGE) model has a certain effect on solving this problem. However, there are still unresolved issues. On the one hand, when reasoning the confidence of unseen relation facts, the introduced probabilistic soft logic cannot be used to combine multi-path and multi-step global information, leading to information loss. On the other hand, the existing UKG embedding model can only model symmetric relation facts, but the embedding problem of asymmetric relation facts has not be addressed. To address the above issues, a Multiplex Uncertain Knowledge Graph Embedding (MUKGE) model is proposed in this paper. First, to combine multiple information and achieve more accurate results in confidence reasoning, the Uncertain ResourceRank (URR) reasoning algorithm is introduced. Second, the asymmetry in the UKG is defined. To embed asymmetric relation facts of UKG, a multi-relation embedding model is proposed. Finally, experiments are carried out on different datasets via 4 tasks to verify the effectiveness of MUKGE. The results of experiments demonstrate that MUKGE can obtain better overall performance than the baselines, and it helps advance the research on UKG embedding.

Both silicone gel and quercetin are effective in scar treatment but have different action mechanisms. Quercetin is mainly applied in the gel form and can lead to poor adhesion of silicone gel sheet; therefore, they cannot be combined in clinical use. In this study, a silicone gel sheet that releases quercetin in a sustained manner for 48 hours was successfully developed. Four round scars (Ø: 1 cm) were made in the ears of New Zealand albino rabbits (n = 10). After scar healing, the rabbits were divided into four groups: blank control group with no treatment, silicone gel sheet group with dressing change every 2 days, quercetin group with dressing change three times daily, and combination treatment group with dressing change every 2 days. Scar assessment was performed 3 months later. Transepidermal water loss showed no difference between the combination treatment group and the silicone gel sheet group, but was lower than that in the quercetin group and the blank control group. Immunohistochemistry of CD 31 and proliferating cell nuclear antigen showed the following results: combination treatment group < silicone gel sheet group = quercetin group < blank control group. Polymerase chain reaction results showed that the expression of type-I and type-III collagen in the combination treatment group and the quercetin group was significantly lower than that in the other two groups. Thus, quercetin-modified silicone gel sheet combines the advantages of the two treatments and is more effective at inhibiting cell proliferation in scar tissue than either of the two treatments alone.

Burns cause a loss of skin barrier function, rendering it prone to infection. The prevention of infection comprises a focus on the treatment of patients with burns. Therefore, we analysed the results of microbiological tests of patients with severe and extremely severe burns to provide a basis for the prevention and treatment of infection in patients with burns. The results of microbiological tests of patients with severe and extremely severe burns admitted to our burn centre between 2009 and 2019 were retrospectively reviewed. The overall positive rate of microbial detection was 40.67% and did not significantly decline over the 10-year study period. The most common positive sites were wounds, sputum, and urine. The most common bacterial species causing the infections were Acinetobacter baumannii, Klebsiella pneumoniae, and Pseudomonas aeruginosa. Furthermore, the predictors of a positive detection, overall and at various sites, mainly included the burn area and depth, inhalation injury, and length of the hospital stay. Positive detection was an important predictor of the prognosis. In particular, a positive blood culture and Klebsiella pneumoniaehad better predictive strength for mortality than other sites and strains. This study analysed the microbiological testing results at a single burn centre over a period of 10 years. The results provide information regarding the predictors of a positive detection and the influence of a positive detection on prognosis, and can be used as a basis for the development of clinical infection prevention and treatment strategies, as well as the selection of treatment measures.

Background: The association between vitamin D/calcium and risk of ovarian cancer is still a debatable point. The aim of our study was to systematically investigate the association between vitamin D/calcium, and the risk of ovarian cancer and estimate their dose-response association quantitatively. Methods: PubMed, EMBASE, and Web of Science databases were searched to identify relevant observational studies. Two investigators screened citations and extracted data independently. Data were extracted and the association between vitamin D/calcium and ovarian cancer risk was estimated by calculating pooled relative risks (RRs). Subgroup analyses, publication bias estimation, and dose-response analyses were carried out as well. Results: In total, 21 articles involving 980,008 participants were included in our present study. No significant association was observed between total vitamin D intake and ovarian cancer risk (RR: 1.02; 95% CI, 0.89–1.16, p= 0.81). Further subgroup analysis suggested that neither dietary vitamin D intake (RR: 0.80; 95% CI, 0.62–1.03, p= 0.09) nor supplementary vitamin D intake (RR: 0.98; 95% CI, 0.85–1.13, p= 0.80) was associated with the risk of ovarian cancer. As for calcium, total calcium intake was found to be statistically inversely associated with ovarian cancer risk in case–control studies (RR: 0.73; 95% CI, 0.63–0.86, p&lt; 0.001) but not in cohort studies (RR: 1.05; 95% CI, 0.90–1.24, p= 0.52). Besides, supplementation with calcium plus vitamin D was not effective for the prevention of ovarian cancer (p= 0.98). Of note, dose-response analysis based on cohort studies suggested a potential inverse U-shape relationship between calcium intake (including total calcium and dietary calcium) and ovarian cancer risk, which indicated that low dose of calcium intake might reduce ovarian cancer risk while high dose of calcium intake might not. Conclusions: Taken together, vitamin D could not decrease the risk of ovarian cancer. The role of calcium intake was not proven for reducing ovarian cancer risk. Besides, no evidence showed combinative use of calcium and vitamin D have additional benefits for ovarian cancer prevention.

Recent efforts have revealed that long non-coding RNAs exert crucial roles in cancer initiation and progression. RHPN1-AS1 is a 2030?bp transcript from human chromosome 8q24, and involved in tumorigenesis in uveal melanoma and non-small cell lung cancer, but it remains unknown in ovarian cancer. This study focused on the role of RHPN1-AS1 in ovarian cancer and found that RHPN1-AS1 was up-regulated in ovarian cancer tissues and cell lines. Overexpression of RHPN1-AS1 promoted ovarian cancer cell proliferation, migration, and invasion. Mechanistically, overexpression of RHPN1-AS1 decreased the expression of miR-665 and subsequently promoted the expression of Akt3 at posttranscriptional level. Taken together, RHPN1-AS1 positively regulated the expression of Akt3 through sponging miR-665, and exerted an oncogenic role in ovarian cancer progression, and indicates that RHPN1-AS1 may be a potential therapeutic target in ovarian cancer.

ABSTRACTThe structural integrity and functional stability of organelles are prerequisites for the viability and responsiveness of cells. Dysfunction of multiple organelles is critically involved in the pathogenesis and progression of various diseases, such as chronic obstructive pulmonary disease, cardiovascular diseases, infection, and neurodegenerative diseases. In fact, those organelles synchronously present with evident structural derangement and aberrant function under exposure to different stimuli, which might accelerate the corruption of cells. Therefore, the quality control of multiple organelles is of great importance in maintaining the survival and function of cells and could be a potential therapeutic target for human diseases. Organelle-specific autophagy is one of the major subtypes of autophagy, selectively targeting different organelles for quality control. This type of autophagy includes mitophagy, pexophagy, reticulophagy (endoplasmic reticulum), ribophagy, lysophagy, and nucleophagy. These kinds of organelle-specific autophagy are reported to be beneficial for inflammatory disorders by eliminating damaged organelles and maintaining homeostasis. In this review, we summarized the recent findings and mechanisms covering different kinds of organelle-specific autophagy, as well as their involvement in various diseases, aiming to arouse concern about the significance of the quality control of multiple organelles in the treatment of inflammatory diseases.Abbreviations:ABCD3: ATP binding cassette subfamily D member 3; AD: Alzheimer disease; ALS: amyotrophic lateral sclerosis; AMBRA1: autophagy and beclin 1 regulator 1; AMPK: AMP-activated protein kinase; ARIH1: ariadne RBR E3 ubiquitin protein ligase 1; ATF: activating transcription factor; ATG: autophagy related; ATM: ATM serine/threonine kinase; BCL2: BCL2 apoptosis regulator; BCL2L11/BIM: BCL2 like 11; BCL2L13: BCL2 like 13; BECN1: beclin 1; BNIP3: BCL2 interacting protein 3; BNIP3L/NIX: BCL2 interacting protein 3 like; CALCOCO2/NDP52: calcium binding and coiled-coil domain 2; CANX: calnexin; CAT: catalase; CCPG1: cell cycle progression 1; CHDH: choline dehydrogenase; COPD: chronic obstructive pulmonary disease; CSE: cigarette smoke exposure; CTSD: cathepsin D; DDIT3/CHOP: DNA-damage inducible transcript 3; DISC1: DISC1 scaffold protein; DNM1L/DRP1: dynamin 1 like; EIF2AK3/PERK: eukaryotic translation initiation factor 2 alpha kinase 3; EIF2S1/eIF2α: eukaryotic translation initiation factor 2 alpha kinase 3; EMD: emerin; EPAS1/HIF-2α: endothelial PAS domain protein 1; ER: endoplasmic reticulum; ERAD: ER-associated degradation; ERN1/IRE1α: endoplasmic reticulum to nucleus signaling 1; FBXO27: F-box protein 27; FKBP8: FKBP prolyl isomerase 8; FTD: frontotemporal dementia; FUNDC1: FUN14 domain containing 1; G3BP1: G3BP stress granule assembly factor 1; GBA: glucocerebrosidase beta; HIF1A/HIF1: hypoxia inducible factor 1 subunit alpha; IMM: inner mitochondrial membrane; LCLAT1/ALCAT1: lysocardiolipin acyltransferase 1; LGALS3/Gal3: galectin 3; LIR: LC3-interacting region; LMNA: lamin A/C; LMNB1: lamin B1; LPS: lipopolysaccharide; MAPK8/JNK: mitogen-activated protein kinase 8; MAMs: mitochondria-associated membranes; MAP1LC3B/LC3B: microtubule-associated protein 1 light chain 3 beta; MFN1: mitofusin 1; MOD: multiple organelles dysfunction; MTPAP: mitochondrial poly(A) polymerase; MUL1: mitochondrial E3 ubiquitin protein ligase 1; NBR1: NBR1 autophagy cargo receptor; NLRP3: NLR family pyrin domain containing 3; NUFIP1: nuclear FMR1 interacting protein 1; OMM: outer mitochondrial membrane; OPTN: optineurin; PD: Parkinson disease; PARL: presenilin associated rhomboid like; PEX3: peroxisomal biogenesis factor 3; PGAM5: PGAM family member 5; PHB2: prohibitin 2; PINK1: PTEN induced putative kinase 1; PRKN: parkin RBR E3 ubiquitin protein ligase; RB1CC1/FIP200: RB1 inducible coiled-coil 1; RETREG1/FAM134B: reticulophagy regulator 1; RHOT1/MIRO1: ras homolog family member T1; RIPK3/RIP3: receptor interacting serine/threonine kinase 3; ROS: reactive oxygen species; RTN3: reticulon 3; SEC62: SEC62 homolog, preprotein translocation factor; SESN2: sestrin2; SIAH1: siah E3 ubiquitin protein ligase 1; SNCA: synuclein alpha; SNCAIP: synuclein alpha interacting protein; SQSTM1/p62: sequestosome 1; STING1: stimulator of interferon response cGAMP interactor 1; TAX1BP1: Tax1 binding protein 1; TBK1: TANK binding kinase 1; TFEB: transcription factor EB; TICAM1/TRIF: toll-like receptor adaptor molecule 1; TIMM23: translocase of inner mitochondrial membrane 23; TNKS: tankyrase; TOMM: translocase of the outer mitochondrial membrane; TRIM: tripartite motif containing; UCP2: uncoupling protein 2; ULK1: unc-51 like autophagy activating kinase; UPR: unfolded protein response; USP10: ubiquitin specific peptidase 10; VCP/p97: valosin containing protein; VDAC: voltage dependent anion channels; XIAP: X-linked inhibitor of apoptosis; ZNHIT3: zinc finger HIT-type containing 3.

With the rapidly development of automobile, rail transit and aviation, the lightweight of modern transportation is becoming the common choice to conserve energy and reduce emission. At present, the development of lightweight technology focuses on the large-scale application of new lightweight materials such as high-strength steels, light alloys and composite materials, the problems of forming, jointing and processing technology in the material application process, and the cost reduction of new material application. In recent years, researchers of Beijing Laboratory of Metallic Materials and Processing for Modern Transportation (MMPMT) has made a series of progress in the study of new lightweight metal materials for modern transportation. This paper will introduce new high-strength steels, new aluminium alloys, copper-aluminium composite materials and their processing technologies.

ABSTRACTThere is growing evidence that circular RNAs (circRNAs) play a vital role in many kinds of diseases, including erectile dysfunction (ED). Nevertheless, the role of circRNAs in cavernous nerve-damaging ED (CNI-ED) is unknown. Here, we aimed to discover novel circRNAs, probed their potential role in the CNI-ED, and construct a ceRNA network of circRNAs. Twelve male Sprague Dawley rats were randomly divided into 2 groups by us: bilateral cavernous nerve crush (BCNC) and control groups. Four weeks after surgery, the spongy smooth muscle tissue of the rat penis was sequenced using high-throughput full transcriptome sequencing. We analyzed the expression of circRNAs, miRNAs, and mRNAs in the two groups. Twenty circRNAs with significantly different expressions were selected for RT-qPCR. CeRNA network of circRNAs was established using Cytoscape. GO and KEGG analysis was done by R package. Sequencing showed that 4,587 circRNAs, 762 miRNAs, and 21,661 mRNAs were dysregulated in the BCNC group. The top 20 differentially expressed circRNAs were further verified via RT-qPCR. The ceRNA network contained ten circRNAs, six miRNAs, and 227 mRNAs, including 23 circRNA-miRNA pairs and 227 miRNA-mRNA pairs. GO and KEGG analysis suggested that these ten circRNAs could main regulate energy metabolism processes. A protein‐protein interaction network was constructed with the mRNAs in ceRNA network, and five hub genes were identified. Our study revealed a potential link between circRNAs, miRNAs, and mRNAs in CNI-ED, suggesting that circRNAs may contribute to the occurrence of ED by regulating the cellular energy metabolism in CNI-ED.

Effect of titanium microalloying on the microstructure and mechanical properties of vanadium microalloyed steels for hot forging was studied. Titanium microalloying improves the mechanical properties mainly through refining the austenite grains. When the heating temperature is in the range of 1050–1300 °C, the austenite grain diameter is decreased from 77–133 to 26–68 μm by titanium microalloying. With the decrease in austenite grain diameter, the final microstructure is refined significantly, and the high misorientation boundaries are increased. After the steel is heated at 1200 °C (the common hot forging temperature) and cooled slowly, titanium microalloying decreases the yield strength from 548.4 to 519.4 MPa, and the tensile strength decreases from 842.7 to 808.7 MPa. However, the elongation increases from 19.0% to 21.4%, and the impact energy increases from 9.8 to 38.2 J. V–Ti steel has a better combination of strength, plasticity and toughness than V steel. In addition, the nucleation of intragranular ferrite idiomorphs is promoted by titanium microalloying, which may have a beneficial effect on the property of steels with coarse microstructure caused by the critical deformation in hot die forging.

Vague set, as well as intuitionistic fuzzy set, is an extended model of fuzzy sets. On the basis of fuzzy sets, vague sets describe the membership degree of a vague concept by using an interval value instead of a single value. To a certain degree, vague sets have a more powerful ability to process fuzzy information than fuzzy sets. Thus, when characterizing a target concept by vague sets, identifying methods to make scientific and reasonable decisions has become an essential issue. However, existing decision methods always focus on the decisions based on fuzzy concepts, and research on how to make three-way decisions based on vague concepts is still lacking. Therefore, in this paper, the concept of rough vague sets is proposed to construct a rough approximation framework of vague concepts. Then, the fuzziness of the existing approximation approaches is analyzed. Next, improved step-vague set model which is a better approximation approach than existing approaches and the algorithm used to search for a improved step-vague set are proposed. Furthermore, based on the improved step-vague sets, probabilistic rough vague sets and a three-way approximation model with shadowed sets are introduced. Finally, several illustrative examples and relative experiment are listed to verify the effectiveness and significance of the proposed models. [ABSTRACT FROM AUTHOR]

Natural gas resources in the Qaidam Basin are abundant and of various types. On the basis of the natural gas carbon isotope distribution characteristics, the western Qaidam Basin mainly comprises oil-type gas, whereas the northern margin of the basin primarily contains coal-type gas. These types are of thermal origin. Thermogenic natural gas has the same characteristics in terms of distribution regularities and main controlling factors of reservoir accumulation. In this study, geochemical, geophysical, geological, and basin simulations were comprehensively completed to investigate the thermogenic gas distribution and the main controlling factors of its accumulation in the Qaidam Basin. The distribution of oil and gas accumulation zones based on source rock maturity maps indicates that the oil is distributed in and near low-maturity to mature (0.5% < Ro < 0.8%) source rock areas. Meanwhile, natural gas is distributed in mature (0.8% < Ro < 1.3%) to highly mature (Ro > 1.3%) source rock areas. The areas wherein oil and gas coexist are near and in mature (0.8% < Ro < 1.3%) source rock areas. Thus, the tectonic evolutionary history, paleostructural map, source–reservoir–cap assemblage, and gas accumulation model were analyzed. The results indicated that the main controlling factors for natural gas reservoir formation are as follows: mature source rocks control the horizontal distribution of natural gas, ancient uplifts or slopes control natural gas migration direction, faults and an unconformity control gas migration channels, and high-quality reservoirs regulate the reserve scale. Moreover, locating favorable reservoirs can be the subsequent step in natural gas exploration near and in mature to highly mature source rock areas along paleouplifts and ancient slopes with deep faults. Therefore, this study is significant when conducting natural gas exploration in this area.

AbstractVoltage-gated sodium (Nav) channels are transmembrane proteins composed of four homologous domains (DI–DIV) that play important roles in membrane excitability in neurons and muscles. Analgesic-antitumour peptide (AGAP) is a neurotoxin from the scorpion Buthus martensiiKarsch, and has been shown to exert analgesic effect by binding on site 4 of human Nav1.7 (hNav1.7). Mechanistic details about this binding, however, remain unclear. To address this issue, we compared the binding modes of AGAP/AGAPW38G/AGAPW38Fand the hNav1.7 voltage-sensing domain on DII (VSD2hNav1.7) using homology modeling, molecular docking, molecular dynamics simulation and steered molecular dynamics. Results revealed the key role of tryptophan at position 38 on the binding of AGAP to VSD2hNav1.7. Pivotal roles are played also by residues on the β-turn and negatively charged residues at the C-terminal. We further show that electrostatic interaction is the main contributor to the binding free energy of the complex. Agreement between our computational simulation findings and prior experimental data supports the accuracy of the described mechanism. Accordingly, these results can provide valuable information for designing potent toxin analgesics targeting hNav1.7 with high affinity.Communicated by Ramaswamy H. Sarma

Our aim was to apply a composite braided biodegradable stent (CBBS) made from poly p-dioxanone (PPDO) and polycaprolactone (PCL) as an alternative to metallic stents for the treatment of pediatric endovascular disease. CBBS properties after adjunctive post-dilatation were assessed using radial force testing. CBBS degradation was assessed using in vitromeasurements. Self-expandable CBBSs (8 × 20 mm) were implanted in abdominal aortas with an oversizing ratio of 1.1–1.4 (group A, n= 12) and in common iliac arteries with an oversizing ratio >1.4 (group B, n= 12). Self-expandable metal WALLSTENTs (8 × 21 mm) were implanted in common iliac arteries with an oversizing ratio >1.4 and served as controls (group C, n= 12). Artery evaluations including angiography and histological examinations were performed at 1, 4, 6 and 12 months after stent implantation. Eight millimeter CBBSs delivered in 8Fr sheaths with adjunctive post-dilatation had properties similar to those of metallic benchmark stents and were degraded in 12 months, with mild to moderate inflammation-induced neointimal hyperplasia and vessel restenosis. Post-dilatation and oversizing are suggested when using CBBSs for polymeric strut tissue embedding and optimal wall apposition, but an overextended ratio should be avoided because of the induction of less-desirable neointimal hyperplasia. Mid-term outcomes of CBBSs with adjunctive post-dilatation were better than those of WALLSTENTs in a swine endovascular disease model.

Longju temple, located in Guanghan County, Sichuan province of China, is a Buddhist temple with great cultural significance. It has preserved polychrome relics since 1466 of the Ming dynasty. The deterioration of these ancient colored paintings is posing an extremely serious issue, it is exceptionally critical to propose an appropriate protection plan. In this paper, pigments and binding media were analyzed from ten polychrome samples collected from the central hall of Longju temple. A series of analysis methods were adopted, including the Raman spectrum, scanning electron microscopy–energy disperse spectrometer (EDS–SEM), and enzyme-linked immunosorbent assay (ELISA). Results demonstrate the existence of atacamite, azurite, carbon black, cinnabar, and gold in the color layer of the samples. Egg white, animal glue, and casein were found to be used as binders in the colored paintings. This study not only offered essential data for the follow-up protection and repair projects but also provided a reference to further explore the polychrome relics of other Buddhist temples in the Ming dynasty of China.

Feeding silkworms with functional materials as additives to produce naturally modified silk is a facile, diverse, controllable, and environmentally friendly method with a low cost of time and investment. Among various additives, carbon dots (CDs) show unique advantages due to their excellent biocompatibility and fluorescence stability. Here, a new type of green fluorescent carbon dots (G-CDs) is synthesized with a high oil–water partition ratio of 147, a low isoelectric point of 5.16, an absolute quantum yield of 71%, and critically controlled surface states. After feeding with G-CDs, the silkworms weave light yellow cocoons whose green fluorescence is visible to the naked eye under UV light. The luminous silk is sewn onto the cloth to create striking patterns with beautiful fluorescence. Such G-CDs have no adverse effect on the survival rate and the life cycle of silkworms and enable their whole bodies to glow under UV light. Based on the strong fluorescence, chemical stability, and biological safety, G-CDs are found in the digestive tracts, silk glands, feces, cocoons, and even moth bodies. G-CDs accumulate in the posterior silk glands where fibroin protein is secreted, indicating its stronger combination with fibroin than sericin, which meets the requirements for practical applications.

Calcium-overload-mediated tumor therapy has received considerable interest in oncology. However, its efficacy has been proven to be inadequate due to insufficient calcium ion concentration at the tumor site coupled with challenges in facilitating efficient calcium uptake by tumors, leading to unsatisfactory therapeutic outcomes. In the present study, calcium carbonate nanoshell mineralized ferric polydopamine nanoparticles (Fe-PDA@CaCO3NPs) were prepared for achieving Ca2+-overload-mediated tumor therapy. Upon entering the tumor site, the pH-responsive CaCO3layer, acting as a “Ca2+storage pool”, rapidly degraded and released high quantities of free Ca2+within the weakly acidic environment. The Fe-PDA core, with its excellent photothermal conversion properties, could significantly increase the temperature upon exposure to near-infrared (NIR) light irradiation, thereby activating the TRPV1 channel and leading to a large influx of released Ca2+into the cytoplasm. Furthermore, the exposed Fe-PDA core could react with the tumor-overexpressed hydrogen peroxide (H2O2) to efficiently produce hydroxyl radicals (•OH), significantly increasing intracellular reactive oxygen species (ROS) levels and thus inhibiting the activity of the Ca2+efflux pump, resulting in a high intracellular Ca2+concentration. Ultimately, the increase in calcium/ROS levels could disrupt mitochondrial homeostasis and activate the apoptosis pathway. The current work presents a promising approach for tumor therapy using photothermal-enhanced calcium-overload-mediated ion interference therapy and chemodynamic therapy.

Combination chemotherapy has been proved to be an effective strategy in the clinic, and nanoformulations have drawn much attention in the field of drug delivery. However, conventional nanocarriers suffer from shortcomings such as inefficient coloading and undesired molar ratios of the combined drugs, preleakage of cargos during systemic circulation, and lack of cancer-selective drug release. To achieve tumor-specific codelivery of cisplatin (CDDP) and norcantharidin (NCTD) for synergistic treatment of liver cancer, a novel linear–dendritic polymer, termed as G1(PPDC)x, was designed and synthesized, where a prodrug consisting of cisplatin (CDDP) and norcantharidin (NCTD) was conjugated to PEG2000 viaester bonds to fabricate linear polymer–drug conjugates, and the conjugates were subsequently grafted to the terminal hydroxyls of a dendritic polycarbonate core. Benefiting from the hydrogen bond interactions, G1(PPDC)xcould spontaneously self-assemble into a unique type of raspberry-like multimicelle clusters in solution (G1(PPDC)x-PMs). G1(PPDC)x-PMs possessed an optimal synergistic ratio of CDDP and NCTD, without obvious premature release or disassembly in biological environments. Intriguingly, upon extravasation into the interstitial tumor tissues, G1(PPDC)x-PMs (132 nm in diameter) could disassemble and reassemble into smaller micelles (40 nm in diameter) in response to the mildly acidic tumor microenvironment, which would enhance the deep tumor penetration and cellular accumulation of drugs. In vivodelivery of G1(PPDC)x-PMs led to a significantly prolonged blood circulation half-life, which is beneficial to achieve sufficient tumor accumulation through the enhanced permeability and retention (EPR) effect. G1(PPDC)x-PMs displayed the best antitumor activity in H22 tumor-bearing mice with a tumor inhibition rate of 78.87%. Meanwhile, G1(PPDC)x-PMs alleviated both myelosuppression toxicities of CDDP and vascular irritation of NCTD. Our results demonstrated that G1(PPDC)x-PMs could serve as an effective drug delivery system for codelivery of CDDP and NCTD to treat liver cancer efficiently.