Search

Abstract Pulmonary hypertension (PH) presents a puzzling sex bias, being more prevalent in women yet often less severe than in men, and the underlying reasons remain unclear. Studies using animal models, and limited clinical data have revealed a protective influence of exogenous estrogens, known as the estrogen paradox. Research suggests that beyond its receptor-mediated effects, estrogen acts through metabolites such as 2-ME2, 4-OHE2, and 16-OHE2, which are capable of exhibiting protective or detrimental effects in PH, prompting the need to explore their roles in PH to untangle sex differences and the estrogen paradox. Hypoxia disrupts the balance of estrogen metabolites by affecting the enzymes responsible for estrogen metabolism. Delving into the role of these metabolic enzymes not only illuminates the sex difference in PH but also provides a potential rationale for the estrogen paradox. This review delves into the intricate interplay between estrogen metabolites, metabolic enzymes, and PH, offering a deeper understanding of sex-specific differences and the perplexing estrogen paradox in the context of this condition. Graphic Abstract

Skin photodamage caused by ultraviolet (UV) radiation is a major public health concern. UVB rays penetrate the epidermis, inducing oxidative stress and compromising essential cellular components. The demand for natural ingredients with properties such as moisturization, anti-inflammatory effects, antioxidant protection, and compatibility is increasing to combat the impact of photodamage on the skin. Herein, the carboxymethyl chitosan oligosaccharide (CM-COS) enzymatic hydroxylates were used on the topical application of skin photodamage for the first time. CM-COS, the degradation product of carboxymethyl chitosan, has high water solubility and multiple biological activities. Results showed that CM-COS promoted human epidermal cell (HaCaT) migration without causing cytotoxicity. In photodamaged HaCaT cells, CM-COS maintained cell viability and cytoskeletal integrity while inhibiting reactive oxygen species accumulation, apoptosis, and cell cycle arrest. CM-COS regulates gene expression related to cell cycle, oxidative stress, and inflammation in UVB-radiated HaCaT based on transcriptomic and qPCR data. In UVB-exposed mice, topical treatment of CM-COS significantly alleviated redness and scab formation and increased the moisture content of photodamaged skin. Histological analyses revealed reduced epidermal thickness and increased collagen I and collagen III deposition in photodamaged skin following CM-COS treatment. Additionally, gene expression related to the cell cycle, extracellular matrix, and inflammation were significantly activated by CM-COS based on transcriptomic and qPCR data. CM-COS modulated the levels of collagen and inflammation-related proteins. Collectively, the data confirm the therapeutic effect of CM-COS against skin photodamage and highlight the potential of natural marine oligosaccharides for treating skin diseases such as aging, wounds, and burns.

The adipose tissue surrounding blood vessels is known as perivascular adipose tissue (PVAT), which represents a distinct ectopic fat depot that adheres to the majority of the vasculature. In recent years, owing to its unique location and function, PVAT has been regarded as a new type of adipose tissue distinct from traditional visceral fat. It releases adipokines with vasoconstrictive functions, which regulate vascular function through paracrine and endocrine mechanisms. Interestingly, PVAT can be categorized as white, brown or a mixture of both depending on its anatomical location. Brown adipose tissue (BAT) is located adjacent to the thoracic aorta in rodents, while a mix of brown and white tissue surrounds the abdominal aorta. PVAT exhibits regional phenotypic differences in different parts of the vasculature bed, which may lead to heterogeneity in the secretion profiles and norepinephrine (NE) content in regional PVAT and subsequently affect the regulation of specific adipokine signaling pathways in regional PVAT, resulting in differences in the regulation of vascular function. The aim of this review was to explore the potential factors that influence the anticontractile function of regional PVAT in the vasculature, including the heterogeneity of regional PVAT, the anticontractile function mediated by endothelial nitric oxide synthase (eNOS) in regional PVAT, the activity of the adiponectin-eNOS pathway in regional PVAT adipocytes, and the concentration of the sympathetic neurotransmitter NE in regional PVAT.

As the communication needs in the smart distribution grid continue to rise, using existing resources to meet this growing demand poses a significant challenge. This paper researches on spectrum allocation strategies utilizing cognitive radio (CR) technology. We consider a model containing strong time-sensitive and regular communication service requirements such as distribution terminal communication services, which can be seen as a user with primary data (PD) and weak time-sensitive services such as power quality monitoring, which can be seen as a user with secondary data (SD). To fit the diversity of services in smart distribution grids (SDGs), we formulate an optimization problem with two indicators, including the sum of SD transmission rates and the maximum latency of them. Then, we analyze the two convex sub-problems and utilize convex optimization methods to obtain the optimal power and frequency bandwidth allocation for the users with SD. The simulation results indicate that, when the available transmission power of SD is low, Maximization of Transmission Sum Rate (MTSR) achieves lower maximum transmit time. Conversely, when the available transmission power is high, the performance of Minimization of the Maximum Latency (MML) is better, compared with MTSR.

Abstract The interplay between magnetism and electronic band topology enriches topological phases and has promising applications. However, the role of topology in magnetic fluctuations has been elusive. Here, we report evidence for topology stabilized magnetism above the magnetic transition temperature in magnetic Weyl semimetal candidate CeAlGe. Electrical transport, thermal transport, resonant elastic X-ray scattering, and dilatometry consistently indicate the presence of locally correlated magnetism within a narrow temperature window well above the thermodynamic magnetic transition temperature. The wavevector of this short-range order is consistent with the nesting condition of topological Weyl nodes, suggesting that it arises from the interaction between magnetic fluctuations and the emergent Weyl fermions. Effective field theory shows that this topology stabilized order is wavevector dependent and can be stabilized when the interband Weyl fermion scattering is dominant. Our work highlights the role of electronic band topology in stabilizing magnetic order even in the classically disordered regime.

Objectives Multiple lung cancers may present as multiple primary lung cancers (MPLC) or intrapulmonary metastasis (IPM) with variations in clinical stage, treatment, and prognosis. However, the existing differentiation criteria based on histology do not fully meet the clinical needs. Next-generation sequencing (NGS) may play an important role in assisting the identification of different pathologies. Here, we extended the relevant data by combining histology and NGS to develop detailed identification criteria for MPLC and IPM. Materials and Methods Patients with lung cancer (each patient had ≥2 tumors) were enrolled in the training (n = 22) and validation (n = 13) cohorts. Genomic profiles obtained from 450-gene-targeted NGS were analyzed, and the new criteria were developed based on our findings and pre-existing Martini & Melamed criteria and molecular benchmarks. Results The analysis of the training cohort indicated that patients identified with MPLC had no (or

The steel industry is an important foundation of the national economy and the livelihood of the people, producing a large amount of carbon dioxide gas, accounting for about 70% of the carbon dioxide gas generated in the steel industry, which occurs during the ironmaking process. Therefore, the key technology to reduce the pollution and improve competitiveness is to increase the stability of blast furnace production and the quality of hot metal. Since the operation requirements for temperature control in the vanadium-titanium blast furnace are dramatically different compared to the traditional ones due to the low fluidity of vanadium-titanium slag, maintaining the required hot metal temperature within a narrow range with smaller fluctuations is essential. In addition, the adjustment parameters of the lower part have a significant influence on the tuyere combustion flame temperature during the daily operation of blast furnaces. At present, there is no relevant research on the online detection and analysis of vanadium-titanium blast furnace tuyere combustion flame temperature. In this study, the temperature of four tuyeres in a 500 m3 vanadium and titanium blast furnace at Jianlong Steel was detected by an online detection system. The tuyere combustion flame temperature was then calculated using colorimetric temperature measuring methodology at various times and at four distinct locations. After that, the calibration analyses, imaging parameter and the temperature tendencies in different directions of the blast furnace were investigated. This study not only offers new methods for understanding the regularity of operation and increasing the degree of visualization in vanadium and titanium smelting blast furnaces but also provides technical support for intelligent and low-carbon operation in blast furnaces.

ObjectiveThis study aimed to investigate RING-Finger Protein 6 (RNF6) expression in esophageal squamous cell carcinoma (ESCC) cells and whether it affects cell proliferation, invasion, and migration by regulating the TGF-β1/c-Myb pathway.MethodsTCGA database was used to analyze RNF6 expression in normal tissues and esophageal cancer tissues. Kaplan–Meier method was used to examine the correlation between RNF6 expression and patient prognosis. SiRNA interference vector and RNF6 overexpression plasmid were constructed, and RNF6 was transfected into Eca-109 and KYSE-150 esophageal cancer cell line. In vitro scratch assay and Transwell assay were conducted to investigate the effects of RNF6 on the migration and invasion of Eca-109 and KYSE-150 cells. RT-PCR detected the expression of Snail, E-cadherin, and N-cadherin, and TUNEL detected the apoptosis of cells.ResultsRNF6 up-regulation promoted the progression of esophageal cancer and predicted poor prognosis. RNF6 also enhanced the migration and invasion of ESCC cells in vitro. RNF6 silencing inhibited the migration and invasion of ESCC cells. TGF-β inhibitors reversed the oncogenic effects of RNF6. RNF6 regulated the migration and invasion of ESCC cells by activating the TGF-β pathway. RNF6/TGF-β1 promoted esophageal cancer progression through c-Myb.ConclusionRNF6 promotes the proliferation, invasion, and migration of ESCC cells possibly by activating the TGF-β1/c-Myb pathway and affects the progression of ESCC.

Electrospinning (ES) of ceramic fibers has mostly remained in the research level, which can be because of the hard process and parameters controlling the low rate of production. The yield of fiber production by solution blow spinning (SBS) is exciting but the production process is unstable due to the reverse flow phenomenon. In this paper, we prepared high-performance ceramic fibers by gas-assisted electrospinning (GES), which combined the advantages of ES and SBS. Also, comprehensive numerical and experimental analysis for nanofibers produced using GES are provided. The gas flow characteristics through different parameters' nozzle were investigated numerically using computational fluid dynamics and experimentally in a custom-built gas-assisted electrospinning setup to produce SiO2 nanofibers.

4D millimeter wave (mmWave) imaging radar is a new type of vehicle sensor technology that is critical to autonomous driving systems due to its lower cost and robustness in complex weather. However, the sparseness and noise of point clouds are still the main problems restricting the practical application of 4D imaging radar. In this paper, we introduce SMIFormer, a multi-view feature fusion network framework based on 4D radar single-modal input. SMIFormer decouples the 3D point cloud scene into 3 independent but interrelated perspectives, including bird’s-eye view (BEV), front view (FV), and side view (SV), thereby better modeling the entire 3D scene and overcoming the shortcomings of insufficient feature representation capabilities under single-view built from extremely sparse point clouds. For multi-view features, we proposed multi-view feature interaction (MVI) to exploit the inner relationship between different views by integrating features from intra-view interaction and cross-view interaction. We evaluated the proposed SMIFormer on the View-of-Delft (VoD) dataset. The mAP of our method reached 48.77 and 71.13 in the fully annotated area and the driving corridor area, respectively. This shows that 4D radar has great development potential in the field of 3D object detection.

Three-dimensional multimodality multi-object tracking has attracted great attention due to the use of complementary information. However, such a framework generally adopts a one-stage association approach, which fails to perform precise matching between detections and tracklets, and, thus, cannot robustly track objects in complex scenes. To address this matching problem caused by one-stage association, we propose a novel multi-stage association method, which consists of a hierarchical matching module and a customized track management module. Specifically, the hierarchical matching module defines the reliability of the objects by associating multimodal detections, and matches detections with trajectories based on the reliability in turn, which increases the utilization of true detections, and, thus, guides accurate association. Then, based on the reliability of the trajectories provided by the matching module, the customized track management module sets maximum missing frames with differences for tracks, which decreases the number of identity switches of the same object and, thus, further improves the association accuracy. By using the proposed multi-stage association method, we develop a tracker called MSA-MOT for the 3D multi-object tracking task, alleviating the inherent matching problem in one-stage association. Extensive experiments are conducted on the challenging KITTI benchmark, and the results show that our tracker outperforms the previous state-of-the-art methods in terms of both accuracy and speed. Moreover, the ablation and exploration analysis results demonstrate the effectiveness of the proposed multi-stage association method.

Multiple object tracking (MOT) in unmanned aerial vehicle (UAV) videos is a fundamental task and can be applied in many fields. MOT consists of two critical procedures, i.e., object detection and re-identification (ReID). One-shot MOT, which incorporates detection and ReID in a unified network, has gained attention due to its fast inference speed. It significantly reduces the computational overhead by making two subtasks share features. However, most existing one-shot trackers struggle to achieve robust tracking in UAV videos. We observe that the essential difference between detection and ReID leads to an optimization contradiction within one-shot networks. To alleviate this contradiction, we propose a novel feature decoupling network (FDN) to convert shared features into detection-specific and ReID-specific representations. The FDN searches for characteristics and commonalities between the two tasks to synergize detection and ReID. In addition, existing one-shot trackers struggle to locate small targets in UAV videos. Therefore, we design a pyramid transformer encoder (PTE) to enrich the semantic information of the resulting detection-specific representations. By learning scale-aware fine-grained features, the PTE empowers our tracker to locate targets in UAV videos accurately. Extensive experiments on VisDrone2021 and UAVDT benchmarks demonstrate that our tracker achieves state-of-the-art tracking performance.

Electrospinning technology is considered to be one of the efficient, convenient, and low-cost technologies for preparing nanofibers, which can be applied in various industries, including filtration, catalysis, and energy. Here, aiming at the performance requirements of the nanometer fiber filter membrane for filtering PM2.5, the preparation of the nanofiber filter membrane was realized based on multi-needle electrospinning equipment. Meanwhile, by adding silver nitrate to the spinning solution, a polyvinylidene fluoride antibacterial nanofiber filter layer with high filtration efficiency and low resistance was successfully prepared on the traditional air conditioning filter meshes. We found that four key factors affecting the filtration performance include ambient humidity, substrate meshes, voltage, and production rate. Among them, voltage and production rate are the key factors affecting the filtration performance. According to the development trend of multifunctional nanofiber membranes, the preparation of air conditioning filters with nanofibers as the main filter material was realized, producing air conditioning filter membranes with antibacterial and deodorizing functions. This article provides a reliable experimental basis and empirical reference for the preparation of nanofiber membranes based on multi-needle electrospinning technology.

Lane and road marker segmentation is crucial in autonomous driving, and many related methods have been proposed in this field. However, most of them are based on single-frame prediction, which causes unstable results between frames. Some semantic multi-frame segmentation methods produce error accumulation and are not fast enough. Therefore, we propose a deep learning algorithm that takes into account the continuity information of adjacent image frames, including image sequence processing and an end-to-end trainable multi-input single-output network to jointly process the segmentation of lanes and road markers. In order to emphasize the location of the target with high probability in the adjacent frames and to refine the segmentation result of the current frame, we explicitly consider the time consistency between frames, expand the segmentation region of the previous frame, and use the optical flow of the adjacent frames to reverse the past prediction, then use it as an additional input of the network in training and reasoning, thereby improving the network’s attention to the target area of the past frame. We segmented lanes and road markers on the Baidu Apolloscape lanemark segmentation dataset and CULane dataset, and present benchmarks for different networks. The experimental results show that this method accelerates the segmentation speed of video lanes and road markers by 2.5 times, increases accuracy by 1.4%, and reduces temporal consistency by only 2.2% at most.

Multi-needle electrospinning technology is a method for mass production of nanofibers, which can improve the production efficiency of nanofibers by increasing the number and density of needles for multi-needle electrospinning. However, when the arrangement density of the needle is high, the electric field of the needle tip is not uniform, causing instability such as jet dripping and broken jet. In this paper, the electric field uniformity optimization problem of multi-needle electrospinning technology is used to simulate the needle tip electric field by using COMSOL finite element analysis software. The influence of the needle size and the dielectric material on the electric field of the tip was studied. Finally, the method of using dielectric material on the tip of the middle part of the needle is beneficial to the electric field uniformity. The uniformity of the needle tip electric field in the case of high-density arrangement of the needle is realized, and the nozzle is provided for mass production of nanofibers by multi-needle electrospinning.

The mass electrospinning is the key way to promote the industrial application of nanofibrous membrane, in which the multi-parameter controlling is the challenge for the multi-needle electrospinning. A constant temperature and humidity environment was introduced to studied the effect of process parameters on the ejection process of multi-needle electrospinning process. This article focused on the nanofiber deposition behaviors of multi-needle electrospinning from two different polymer solution of aqueous solution of poly (ethylene oxide) and the non-aqueous solution of polyvinylidene fluoride. We found that the same humidity has opposite effects on the deposition morphology of the water-soluble material PEO and the non-water-soluble material PVDF electrospun fiber. At the same time, we explored the effects of solution conductivity, solvent volatility, temperature and viscosity on electrospinning on water-insoluble and water-soluble materials. What this paper aim is to provide a process debugging reference for the batch preparation of nanofibers of different materials by multi-needle electrospinning.

Laser-induced graphene (LIG) has the advantages of one-step fabrication, prominent mechanical performance, as well as high conductivity; it acts as the ideal material to fabricate flexible strain sensors. In this study, a wearable flexible strain sensor consisting of three-dimensional (3D) wavy LIG and silicone rubber was reported. With a laser to scan on a polyimide film, 3D wavy LIG could be synthesized on the wavy surface of a mold. The wavy-LIG strain sensor was developed by transferring LIG to silicone rubber substrate and then packaging. For stress concentration, the ultimate strain primarily took place in the troughs of wavy LIG, resulting in higher sensitivity and less damage to LIG during stretching. As a result, the wavy-LIG strain sensor achieved high sensitivity (gauge factor was 37.8 in a range from 0% to 31.8%, better than the planar-LIG sensor), low hysteresis (1.39%) and wide working range (from 0% to 47.7%). The wavy-LIG strain sensor had a stable and rapid dynamic response; its reversibility and repeatability were demonstrated. After 5000 cycles, the signal peak varied by only 2.32%, demonstrating the long-term durability. Besides, its applications in detecting facial skin expansion, muscle movement, and joint movement, were discussed. It is considered a simple, efficient, and low-cost method to fabricate a flexible strain sensor with high sensitivity and structural robustness. Furthermore, the wavy-LIG strain senor can be developed into wearable sensing devices for virtual/augmented reality or electronic skin.

The electrospinning electric field is the main factor responsible for the jet stretching force. Previous studies showed that nonhomogeneous electric field would affect the jets formed during the multi-needles electrospinning. Therefore, a multitude of methods were explored to optimize the electric field in multi-needles electrospinning, such as adjusting the supplied voltage on each needle, varying the space of the needles and spatial distribution of the needles. In this paper, three categories of needles distribution were explored for a homogeneous electric field and the design of a higher needles density of electrospinning head. The theoretical and experimental results showed that the homogeneous electric field formed with the trapezoidal head at 15mm distance while the others’ head required over 30mm. Hence, the trapezoidal arrangement is a better multi-needles distribution for electrospinning head, and has much more significance for high yield of electrospinning nanofibers.

Electric vehicles (EVs) provide environmentally friendly transport and they are considered to be an important component of distributed and mobile electric energy storage and supply system. It is possible that EVs can be used to store and transport energy from one geographical area to another as a supportive energy supply. Electricity consumption management should consider carefully the inclusion of EVs. One critical challenge in the consumption management for EVs is the optimization of battery charging. This paper provides a dynamic game theoretic optimization framework to formulate the optimal charging problem. The optimization considers a charging scenario where a large number of EVs charge simultaneously during a flexible period of time. Based on stochastic mean field game theory, the optimization will provide an optimal charging strategy for the EVs to proactively control their charging speed in order to minimize the cost of charging. Numerical results are presented to demonstrate the performance of the proposed framework.

Dirac cone, one of the main characters of topological materials, provides us an approach to explore topological phase transitions and topological states. Single-element 2D-Xenes are prominent candidates for hosting Dirac cones. Till now, the multiple Dirac cones, Dirac-like cones, and semi-metal Dirac point have been discovered in them. However, it is still difficult to realize the tunable Dirac cones due to the lack of appropriate materials. Using first-principles calculations, this paper proposes that monolayer selenium with square lattice could achieve tunable Dirac cones and a topological phase transition. Double structural phases of the monolayer selenium can be distinguished according to strain applied, i.e., buckled square and buckled rectangular phases, which have rich Dirac physics. There exist four anisotropic Dirac cones in the buckled square phase, owing to fourfold symmetry. The buckled rectangular phase hosts a topological phase transition from a 2D topological insulator with double Dirac cones to a simple insulator, with a Dirac semi-metal having single Dirac point as the phase transition point. Moreover, the topological insulator has a global band gap of 0.16 eV, suggesting its potential utilizations in room-temperature devices. These studies will greatly promote the development of the Dirac physics and widen the application ranges of 2D-Xenes.

In order to avoid using toxic or harmful operational conditions, shorten synthesis time, enhance adsorption capacity, and reduce operational cost, a novel magnetic nano-adsorbent of CoFe2O4@SiO2 with core–shell structure was successfully functionalized with polypyrrole (Ppy). The physical and chemical properties of CoFe2O4@SiO2-Ppy are examined by various means. The as-prepared CoFe2O4@SiO2-Ppy nanomaterial was used to adsorb Hg2+ from water. During the process, some key effect factors were studied. The adsorption process of Hg2+ onto CoFe2O4@SiO2-Ppy was consistent with the pseudo-second-order kinetic and Langmuir models. The Langmuir capacity reached 680.2 mg/g, exceeding those of many adsorbents. The as-prepared material had excellent regeneration ability, dispersibility, and stability. The fitting of kinetics, isotherms, and thermodynamics indicated the removal was endothermic and spontaneous, and involved some chemical reactions. The application evaluation of electroplating wastewater also shows that CoFe2O4@SiO2-Ppy is an excellent adsorbent for Hg2+ ions from water.

Topologically protected fermionic quasiparticles appear in metals, where band degeneracies occur at the Fermi level, dictated by the band structure topology. While in some metals these quasiparticles are direct analogues of elementary fermionic particles of the relativistic quantum field theory, other metals can have symmetries that give rise to quasiparticles, fundamentally different from those known in high-energy physics. Here, we report on a new type of topological quasiparticles—triple point fermions—realized in metals with symmorphic crystal structure, which host crossings of three bands in the vicinity of the Fermi level protected by point group symmetries. We find two topologically different types of triple point fermions, both distinct from any other topological quasiparticles reported to date. We provide examples of existing materials that host triple point fermions of both types and discuss a variety of physical phenomena associated with these quasiparticles, such as the occurrence of topological surface Fermi arcs, transport anomalies, and topological Lifshitz transitions.

Although it is well known that the interface relaxation plays the crucial role for the electronic properties in semiconductor epitaxial layers, there is lack of a clear definition of relationship between interfacial bond-energy variation and interface bond-nature-factor (IBNF) in epitaxial layers before and after relaxation. Here we establish an analytical method to shed light on the relationship between the IBNF and the bond-energy change, as well as the relation with band offset in epitaxial layers from the perspective of atomic-bond-relaxation consideration and continuum mechanics. The theoretical predictions are consistent with the available evidences, which provide an atomistic understanding on underlying mechanism of interface effect in epitaxial nanostructures. Thus, it will be helpful for opening up to tailor physical-chemical properties of the epitaxial nanostructures to the desired specifications.