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Abstract Background The present study was performed to assess the association between the neutrophil-to-apolipoprotein A1 ratio (NAR) and outcomes in patients with acute decompensated heart failure (ADHF) at different glucose metabolism states. Methods We recruited 1233 patients with ADHF who were admitted to Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University from December 2014 to October 2019. The endpoints were defined as composites of cardiovascular death, nonfatal myocardial infarction, nonfatal ischemic stroke and exacerbation of chronic heart failure. The restricted cubic spline was used to determine the best cutoff of NAR, and patients were divided into low and high NAR groups. Kaplan-Meier plots and multivariable Cox proportional hazard models were used to investigate the association between NAR and the risk of adverse outcomes. Results During the five-year follow-up period, the composite outcome occurred in 692 participants (56.1%). After adjusting for potential confounding factors, a higher NAR was associated with a higher incidence of composite outcomes in the total cohort (Model 1: HR = 1.42, 95% CI = 1.22–1.65, P0.05). Conclusions The NAR has predictive value for adverse outcomes of ADHF with DM, which implies that the NAR could be a potential indicator for the management of ADHF.

Abstract Background The impact of fibroblasts on the immune system provides insight into the function of fibroblasts. In various tissue microenvironments, multiple fibroblast subtypes interact with immunocytes by secreting growth factors, cytokines, and chemokines, leading to wound healing, fibrosis, and escape of cancer immune surveillance. However, the specific mechanisms involved in the fibroblast‐immunocyte interaction network have not yet been fully elucidated. Main body and conclusion Therefore, we systematically reviewed the molecular mechanisms of fibroblast‐immunocyte interactions in fibrosis, from the history of cellular evolution and cell subtype divisions to the regulatory networks between fibroblasts and immunocytes. We also discuss how these communications function in different tissue and organ statuses, as well as potential therapies targeting the reciprocal fibroblast‐immunocyte interplay in fibrosis. A comprehensive understanding of these functional cells under pathophysiological conditions and the mechanisms by which they communicate may lead to the development of effective and specific therapies targeting fibrosis.

An ecological safety pattern is the basic guarantee for pollution control, ecological environmental protection, economic construction, and sustainable social development, and is an important means of integrated and coordinated development, protection, and governance. This study proposes a research method to identify ecological source sites based on the evaluation of the importance of ecosystem services and ecological sensitivity, and to identify ecological corridors using the minimum cumulative resistance model. The empirical analysis was carried out in Yangxin County, Hubei Province, as an example. The results show that the study area has 16 key corridors and 29 potential corridors, a total of 45 ecological corridors, with a total length of 452 km. In addition, these ecological corridors present a network-like intertwined distribution, connecting various ecological source sites and ensuring the connectivity between ecological source sites, while the well-developed water source sites in the study area provide excellent ecosystem service functions such as water containment for the area.

Abstract A Fano resonance originates from the resonant coupling between interacting multipoles inside nanostructures. It breaks the symmetry of spectral line shape and enables Fano‐resonant media to present unusual scattering properties. However, understanding the mechanical effects of such multipolar coupling systems is highly complex compared with the traditional simple dipole. In this work, using single Si nanospheres as the Fano‐resonant media, optical forces arising from different types of Fano resonances including the electric, magnetic, and magnetoelectric Fano resonances are investigated. It is shown that the directions of these types of forces are tunable in three dimensions. The necessary condition to realize a direction change of the Fano‐resonance‐induced forces and elucidate the underlying physics are presented. Furthermore, it is found that the Fano‐resonance‐induced forces exhibit strong polarization‐dependent properties which traditional optical (dipolar) forces cannot possess.

The human spatial perception of urban streets has a high complexity and traditional research methods often focus on access surveys of human perception. Urban streets serve as both a direct conduit for pedestrians’ impressions of a city and a reflection of the spatial quality of that city. Street-view images can provide a large amount of primary data for the image semantic segmentation technique. Deep learning techniques were used in this study to collect the boring, beautiful, depressing, lively, safe, and wealthy perception scores of street spaces based on these images. Then, the spatial pattern of urban street-space quality perception was analyzed by global Moran’s I and GIS hotspot analyses. The findings demonstrate that various urban facilities affect street quality perception in different ways and that the strength of an influencing factor’s influence varies depending on its geographical location. The results of the influencing factors reveal the difference in the degree of influence of positive and negative influencing factors on various perceptions of the visual dimension of pedestrians. The primary contribution of this study is that it reduces the potential bias of a single data source by using multi-dimensional impact analysis to explain the relationship between urban street perception and urban facilities and visual elements. The study’s findings offer direction for high-quality urban development as well as advice for urban planning and enhanced design.

The visual quality and spatial distribution of architectural styles represent a city’s image, influence inhabitants’ living conditions, and may have positive or negative social consequences which are critical to urban sensing and designing. Conventional methods of identifying architectural styles rely on human labor and are frequently time-consuming, inefficient, and subjective in judgment. These issues significantly affect the large-scale management of urban architectural styles. Fortunately, deep learning models have robust feature expression abilities for images and have achieved highly competitive results in object detection in recent years. They provide a new approach to supporting traditional architectural style recognition. Therefore, this paper summarizes 22 architectural styles in a study area which could be used to define and describe urban architectural styles in most Chinese urban areas. Then, this paper introduced a Faster-RCNN general framework of architectural style classification with a VGG-16 backbone network, which is the first machine learning approach to identifying architectural styles in Chinese cities. Finally, this paper introduces an approach to constructing an urban architectural style dataset by mapping the identified architectural style through continuous street view imagery and vector map data from a top-down building contour map. The experimental results show that the architectural style dataset created had a precision of 57.8%, a recall rate of 80.91%, and an F1 score of 0.634. This dataset can, to a certain extent, reflect the geographical distribution characteristics of a wide variety of urban architectural styles. The proposed approach could support urban design to improve a city’s image.

Breast cancer is the most common malignant tumor in adult women. Its common metastatic sites are lymph nodes, bones, lungs, the liver, and the brain. It is so rare for a patient with breast cancer to have metastases of the gastrointestinal tract, peritoneum, and ovary at the same time that the clinical reporting rate is low. We present a case of a 61-year-old woman who underwent right mastectomy and chemoradiotherapy 3 years ago because of mixed invasive ductal-lobular breast cancer. This time, she came to the hospital due to the symptom of stomach discomfort for 2 weeks. The gastroscopy biopsy result showed gastric metastasis from breast cancer. Then, 18F-FDG imaging and 68Ga-FAPI PET/CT imaging were performed for further diagnosis; 68Ga-FAPI PET/CT demonstrated a significantly elevated FAPI activity in the thickened gastric wall, peritoneum, and bilateral adnexal areas, which was superior to that of 18F-FDG. Finally, a biopsy of suspicious lesions was taken for pathological and histochemical examination, which confirmed that, in addition to the gastric metastasis, the peritoneum and bilateral ovaries were all consistent with metastatic breast cancer.

Tumor neoantigens are aberrant polypeptides produced by tumor cells as a result of genomic mutations. They are also tumor-specific antigens (TSA). Neoantigens are more immunogenic than tumor-related antigens and do not induce autoimmunity. Based on the rapid development of bioinformatics and the continuous update of sequencing technology, cancer immunotherapy with tumor neoantigens has made promising breakthroughs and progress. In this review, the generation, prediction, and identification of novel antigens, as well as the individualized treatments of neoantigens, were first introduced. Secondly, the mechanism of Chimeric Antigen Receptor T-Cell Immunotherapy (CAR-T) therapy and immune checkpoint blockade therapy in the treatment of tumors were outlined, and the three treatment methods were compared. Thirdly, the application of neoantigens in CAR-T therapy and PD-1/PD-L1 blockade therapy was briefly described. The benefits of the neoantigen vaccines over common vaccines were summarized as well. Finally, the prospect of neoantigen therapy was presented.

Abstract Due to their similarity to some bio‐architectures, for example, extracellular matrix, hydrogels are considered as bio‐inspired networks with bio‐mimetic and bio‐functional properties. With natural cytocompatibility and biocompatibility, hydrogels nowadays are more and more involved in various bio‐applications including shape morphing, artificial muscles, soft robotics, regenerative medicine, and so on. As an important subclass, stimuli‐responsive hydrogels have been attracting interest within decades. In response to single or multi‐triggers in biological microenvironment, stimuli‐responsive hydrogels can undergo phase transition, stiffness change, or biochemical properties activation, which make them intriguing biomaterials with broad applications including sensing, drug delivery, tissue engineering, and wound healing. This review presents typical synthetic and natural gelators comprising small molecules and polymers as building blocks of functional architectures. The fabrication strategies of hydrogels varied from supramolecular assembly to dynamic covalent binding are detailed. Various exogenous or endogenous, physical or chemical, and synthetic or natural stimuli together with response mechanism, design principle are demonstrated. Through recent examples from different perspectives, such as bionic devices, wound dressing, and cargo carrier, the benefits and opportunities of stimuli‐responsive hydrogels for biological applications are highlighted. Finally, the current challenges and future prospects in view of translation from fundamental researches to clinical application are briefly discussed.

Abstract Food traceability and authentication systems play an important role in ensuring food quality and safety. Current techniques mainly rely on direct measurement by instrumental analysis, which is usually designed for one or a group of specific foods, not available for various food categories. To develop a general strategy for food identification and discrimination, a novel method based on fluorescence sensor arrays is proposed, composed of supramolecular assemblies regulated by non‐covalent interactions as an information conversion system. The stimuli‐responsiveness and tunability of supramolecular assemblies provided an excellent platform for interacting with various molecules in different foods. In this work, five sensor arrays constructed by supramolecular assemblies composed of pyrene derivatives and perylene derivatives are designed and prepared. Assembly behavior and sensing mechanisms are investigated systematically by spectroscopy techniques. The traceability and authentication effects on several kinds of food from different origins or grades are evaluated and verified by linear discriminant analysis (LDA). It is confirmed that the cross‐reactive signals from different sensor units encompassing all molecular interactions can generate a unique fingerprint pattern for each food and can be used for traceability and authentication toward universal food categories with 100% accuracy.

The energy demand has increased significantly in recent years and it is urgent to develop a renewable energy system that is highly efficient and non-noble metal-based. Hydrogen energy is an environmentally friendly energy source with abundant resources, which can be used to solve the problem of high energy demand without greenhouse gas emissions. However, the development of catalysts for hydrogen production technology by electrolysis of water is slow, mainly due to the complexity of the electrolysis hydrogen generation process, low hydrogen production efficiency, weak electrode material activity and high cost. Among the non-noble metal-based catalysts, carbon-based materials have high conductivity, tunable chemical bonding, and easily modified morphology, making them beneficial to achieving efficient hydrogen production, though pure carbon composites suffer from few surface-active sites and unmoderated hydrogen bonding energy, which need to be further optimized. The principle of electrocatalytic hydrogen production from the perspectives of reaction thermodynamics and kinetics is analyzed and discussed in this paper. Thermodynamics of electrocatalytic hydrogen production is reflected by the Gibbs free energy of hydrogen adsorption (ΔGH*) and electrode potential (E). Reaction kinetics of the electrocatalytic hydrogen production process are reflected by overpotential, Tafel slope and exchange current density. Structural optimization methods of carbon-based composite materials and hydrogen production performance after structural optimization are also summarized. Structural optimization methods of carbon-based composite materials mainly include introducing active sites, improving conductivity, increasing specific surface area and introducing self-supporting materials. Finally, prospects are proposed for the development direction and existing problems of electrocatalytic hydrogen production performance of carbon-based composites.

Abstract Cervical cancer (CC) is the most common gynecologic malignancy, which seriously threatens the health of women. Lipid metabolism is necessary for tumor proliferation and metastasis. However, the molecular mechanism of the relationship between CC and lipid metabolism remains poorly defined. We revealed the expression of IGF2BP3 in CC exceeded adjacent tissues, and was positively associated with tumor stage using human CC tissue microarrays. The Cell Counting Kit-8, colony formation assay, 5-ethynyl-2′-deoxyuridine assay, transwell assays, wound-healing assays, and flow cytometry assessed the role of IGF2BP3 in proliferation and metastasis of CC cells. Besides, exploring the molecular mechanism participating in IGF2BP3-driven lipid metabolism used RNA-seq, which determined SCD as the target of IGF2BP3. Further, lipid droplets, cellular triglyceride (TG) contents, and fatty acids were accessed to discover that IGF2BP3 can enhance lipid metabolism in CC. Moreover, RIP assay and methylated RNA immunoprecipitation experiments seeked the aimed-gene-binding specificity. Lastly, the IGF2BP3 knockdown restrained CC growth and lipid metabolism, after which SCD overexpression rescued the influence in vitro and in vivo using nude mouse tumor-bearing model. Mechanistically, IGF2BP3 regulated SCD mRNA m6A modifications via IGF2BP3-METTL14 complex, thereby enhanced CC proliferation, metastasis, and lipid metabolism. Our study highlights IGF2BP3 plays a crucial role in CC progression and represents a therapeutic latent strategy. It is a potential tactic that blocks the metabolic pathway relevant to IGF2BP3 with the purpose of treating CC.

To investigate the extraction efficiency of polyphenols from passion fruit (Passiflora edulis Sims) peel by using different solvents and to identify the characteristic polyphenols with high contribution to antioxidant activity, ethanolic crude extract (CE) was sequentially extracted with petroleum ether (PE), ethyl acetate (EE), n-butanol (BE) and water (WE). The total content of phenolics and flavonoids was then measured by using spectrophotometry. Phenolic compounds in the extracts were profiled by using ultra performance liquid chromatography tandem mass spectrometry (UPLC-MS), and differential metabolites were screened and quantified by using an untargeted metabolomics approach. Antioxidant activities in vitro were assessed through DPPH free radical scavenging, ABTS+ free radical scavenging and FRAP methods. Furthermore, the phenolic markers of antioxidant activity in the peels were explored through pearson correlation analysis. The results indicated obvious variations in the total phenolic and flavonoid content among the extracts (PBE>CE>WE>PE. A total of 33 phenolic compounds were identified from both CE and each fractional extract, while CE, EE, and BE exhibited a greater variety and quantity of phenolic compounds. Principal component analysis (PCA) distinguished the metabolites of extracts, while orthogonal partial least squares discriminant analysis (OPLS-DA) identified p-hydroxybenzoic acid, protocatechuic acid, isoquercitrin and iso-orientin as differential compounds. EE exhibited the highest levels of p-hydroxybenzoic acid (653.44 μg/g), isoquercitrin (2420.64 μg/g) and iso-orientin (113.23 μg/g), while CE showed the highest content of proto-catechuic acid (152.40 μg/g). The in vitro antioxidant activity of passion fruit peel varied significantly among extracts, with EE showing the strongest capacity, suggesting its potential as a premium antioxidant agent. The correlation analysis revealed that the total phenols and flavonoids formed the basis of antioxidant active substances, while iso-orientin and isoquercitrin were the antioxidant active phenolic markers. The finding provided fundamental data for establishing quality control standards of antioxidant products derived from passion fruit peels, as well as for the precise development and utilization of phenolic compounds in the peels.

Breast cancer is the most common malignant tumor in adult women. Its common metastatic sites are lymph nodes, bones, lungs, the liver, and the brain. It is so rare for a patient with breast cancer to have metastases of the gastrointestinal tract, peritoneum, and ovary at the same time that the clinical reporting rate is low. We present a case of a 61-year-old woman who underwent right mastectomy and chemoradiotherapy 3 years ago because of mixed invasive ductal-lobular breast cancer. This time, she came to the hospital due to the symptom of stomach discomfort for 2 weeks. The gastroscopy biopsy result showed gastric metastasis from breast cancer. Then, 18F-FDG imaging and 68Ga-FAPI PET/CT imaging were performed for further diagnosis; 68Ga-FAPI PET/CT demonstrated a significantly elevated FAPI activity in the thickened gastric wall, peritoneum, and bilateral adnexal areas, which was superior to that of 18F-FDG. Finally, a biopsy of suspicious lesions was taken for pathological and histochemical examination, which confirmed that, in addition to the gastric metastasis, the peritoneum and bilateral ovaries were all consistent with metastatic breast cancer. [ABSTRACT FROM AUTHOR]

Abstract As a new type of secondary ion battery, aqueous zinc‐ion battery has a broad application prospect in the field of large‐scale energy storage due to its characteristics of low cost, high safety, environmental friendliness, and high‐power density. In recent years, manganese dioxide (MnO2)‐based materials have been extensively explored as cathodes for Zn‐ion batteries. Based on the research experiences of our group in the field of aqueous zinc ion batteries and combining with the latest literature of system, we systematically summarize the research progress of Zn−MnO2 batteries. This article first reviews the current research progress and reaction mechanism of Zn−MnO2 batteries, and then respectively expounds the optimization of MnO2 cathode, Zn anodes, and diverse electrolytes and their effects on battery performance. Additionally, primary challenges related to different components and their respective strategies for mitigating them are discussed, with the ultimate objective of offering comprehensive guidance for the design and fabrication of high‐performance Zn−MnO2 batteries. Finally, the future research and development direction of aqueous Zn−MnO2 batteries with high energy density, high safety and long life is envisioned.

Abstract Deep learning technology is changing the landscape of cybersecurity research, especially the study of large amounts of data. With the rapid growth in the number of malware, developing of an efficient and reliable method for classifying malware has become one of the research priorities. In this paper, a new method, BIR-CNN, is proposed to classify of Android malware. It combines convolution neural network (CNN) with batch normalization and inception-residual (BIR) network modules by using 347-dim network traffic features. CNN combines inception-residual modules with a convolution layer that can enhance the learning ability of the model. Batch Normalization can speed up the training process and avoid over-fitting of the model. Finally, experiments are conducted on the publicly available network traffic dataset CICAndMal2017 and compared with three traditional machine learning algorithms and CNN. The accuracy of BIR-CNN is 99.73% in binary classification (2-classifier). Moreover, the BIR-CNN can classify malware by its category (4-classifier) and malicious family (35-classifier), with a classification accuracy of 99.53% and 94.38%, respectively. The experimental results show that the proposed model is an effective method for Android malware classification, especially in malware category and family classifier.

In boxing, the wrong training methods can easily cause physical injury, so many sports protective clothing will use new materials to reduce the impact of boxing training. The aim of this paper is to design a boxing suit based on graphene composite fiber seamless knitted fabric, so as to reduce the injury of boxers during training. In this paper, the head yarn, inner yarn and knitting structure of graphene composite fiber seamless knitted fabrics are discussed, and nine kinds of fabrics are determined by orthogonal matrix method; then, a comprehensive evaluation of the wear resistance of fabrics was proposed based on sequence entropy weight technology, and the ideal solution similarity (TOPSIS) method was used to calculate the wear resistance; finally, this paper designed the boxing protective suit according to the best combination of performance. The experimental results in this paper showed that the veil of sample No. 7 is 70D/48F graphene nylon, the inner yarn is 30D graphene spandex/70D graphene nylon covered yarn, and the fabric with the knitted structure of 1 + 3 false rib has the best comprehensive performance and the highest relative proximity, reaching 0.862. The actual wearing test proves that the comfort of anti-impact boxing suit is slightly better than that of ordinary boxing suit. The clothing designed in this paper has good anti-impact effect. Therefore, on the whole, the boxing suit with graphene composite fiber seamless knitted fabric has good protective effect and can be used for boxing training.