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Idiopathic pulmonary fibrosis (IPF) is the most common and fatal diffuse fibrotic lung disease accompanied by macrophage M2 activation. ErbB4 is involved in and affects the process of inflammation. In this study, we determined that the mRNA level and protein expression of ErbB4 and M2 cytokine members were increased in the serum of IPF patients. In mouse alveolar macrophage MH-S cells, after knocking down ErbB4 by siRNA, the mRNA level and protein expression of M2 activator induced by interleukin (IL)-4 were decreased compared with the control group. Activating by ErbB4 agonist neuromodulatory protein (NRG)-1, IL-4-induced M2 program was promoted. Mechanistically, treated with NRG-1 in MH-S cells, the phosphorylation level of Akt did not change, while the phosphorylation level of ERK increased. Using SCH772984 to inhibit ERK pathway, the increasing IL-4-induced M2 activation by NRG-1 was inhibited, and the high level of M2 activator protein expression and mRNA expression was restored. Collectively, our data support that ErbB4 and M2 programs are implicated in IPF, and ErbB4 participates in the regulation of M2 activation induced by IL-4 through the ERK pathway.

Accurate segmentation of COVID-19 lesion regions in lung CT images aids physicians in analyzing and diagnosing patients' conditions. However, the varying morphology and blurred contours of these regions make this task complex and challenging. Existing methods utilizing Transformer architecture lack attention to local features, leading to the loss of detailed information in tiny lesion regions. To address these issues, we propose a multi-scale feature fusion network, ECF-Net, based on channel enhancement. Specifically, we leverage the learning capabilities of both CNN and Transformer architectures to design parallel channel extraction blocks in three different ways, effectively capturing diverse lesion features. Additionally, to minimize irrelevant information in the high-dimensional feature space and focus the network on useful and critical information, we develop adaptive feature generation blocks. Lastly, a bidirectional pyramid-structured feature fusion approach is introduced to integrate features at different levels, enhancing the diversity of feature representations and improving segmentation accuracy for lesions of various scales. The proposed method is tested on four COVID-19 datasets, demonstrating mIoU values of 84.36%, 87.15%, 83.73%, and 75.58%, respectively, outperforming several current state-of-the-art methods and exhibiting excellent segmentation performance. These findings provide robust technical support for medical image segmentation in clinical practice. [ABSTRACT FROM AUTHOR]

This study investigates the enhancement of hydraulic lime mortar (HLM) using varying contents of metakaolin (MK) to improve its application in the restoration of historic buildings. Samples from historic structures were analyzed, and the effects of different MK contents on the physical and mechanical properties of HLM were examined. The reaction mechanism and microstructural changes were evaluated using XRD and SEM analysis. The results indicated that increasing MK levels in HLM led to a decrease in fluidity, with fluidity reducing by 4.8% at 12% MK. The addition of MK increased water consumption for standard consistency by 5.4% and shortened the final setting time by 10.2%. MK consumption promoted secondary hydration, enhancing compressive strength by up to 98.1% and flexural strength by up to 55.1%, and increasing bonding strength by 26.9%. The density of HLM improved with MK addition, slightly reducing moisture content by 4.5% and water absorption by 4.6%, while the water vapor transmission properties decreased by 50.9%, indicating reduced porosity. The elastic modulus of the mortar increased significantly from 2.19 GPa to 7.88 GPa with the addition of MK, enhancing rigidity and crack resistance. The optimal blend for restoration materials was found to be 9.0% MK and 25.0% heavy calcium carbonate and was characterized by moderate mechanical strength, enhanced early strength, commendable permeability, minimal risk of cracking, and ease of application. This blend is highly suitable for the rehabilitation of historic structures. [ABSTRACT FROM AUTHOR]

N6-methyladenosine (m6A) plays a role in various diseases, but it has rarely been reported in acute lung injury (ALI). The FTO (fat mass and obesity-associated) protein can regulate mRNA metabolism by removing m6A residues. The aim of this study was to examine the role and mechanism of the m6A demethylase FTO in LPS-induced ALI. Lung epithelial FTO-knockout mice and FTO-knockdown/overexpression human alveolar epithelial (A549) cell lines were constructed to evaluate the effects of FTO on ALI. Bioinformatics analysis and a series of in vivo and in vitro assays were used to examine the mechanism of FTO regulation. Rescue assays were conducted to examine whether the impact of FTO on ALI depended on the TXNIP/NLRP3 pathway. In LPS-induced ALI, RNA m6A modification amounts were upregulated, and FTO expression was downregulated. In vivo, lung epithelial FTO knockout alleviated alveolar structure disorder, tissue edema, and pulmonary inflammation and improved the survival of ALI mice. In vitro, FTO knockdown reduced A549 cell damage and death induced by LPS, whereas FTO overexpression exacerbated cell damage and death. Mechanistically, bioinformatics analysis revealed that TXNIP was a downstream target of FTO. FTO deficiency mitigated pyroptosis in LPS-induced ALI via the TXNIP/NLRP3 pathway. Rescue assays confirmed that the impact of FTO on the TXNIP/NLRP3 pathway was significantly reversed by the TXNIP inhibitor SRI-37330. Deficiency of FTO alleviates LPS-induced ALI via TXNIP/NLRP3 pathway–mediated alveolar epithelial cell pyroptosis, which might be a novel therapeutic strategy for combating ALI. [ABSTRACT FROM AUTHOR]

AbstractBackground Prostate cancer (PCa) is poor response to the immunotherapy for its high heterogeneity of immune microenvironment. In this study, we aim to introduce a new immune subtype for PCa involving M2 tumour associated macrophages (M2-TAMs).Methods Three hundred and sixty-two PCa patients and matched normal prostate tissues were selected from the Cancer Genome Atlas and Gene Expression Omnibus databases. Patients’ immune infiltration characters were then analyzed based on the gene expressions. The immune subtypes were identified by the method of unsupervised hierarchical clustering. Finally, the relationship between the M2-TAMs infiltration and anti-programmed death-ligand-1 (PD-L1) therapy was investigated in the IMvigor210 cohort.Results PCa expressed lower immune-related genes levels compared with the adjacent normal tissues. Based on the proved immunosuppressive mechanisms in PCa, tumour patients were classified into three independent subclasses with high infiltrated cytolytic activity (CYT), M2-TAMs and regulatory T cell (Tregs), respectively. Among these subtypes, M2-TAMs infiltration subtype showed the worst clinicopathological features and prognosis compared with the other two subtypes. The results of the IMvigor210 cohort demonstrated poor response of anti-PD-L1 therapy for patients with high M2-TAMs infiltration.Conclusion Prostate tumours involved in significant immunosuppression, and high infiltration of M2-TAMs can be applied to predict the effect of anti-PD-L1 therapy.Key MessagesPCa patients can be classified into three immunotypes of high infiltrated CYT, M2-TAMS, and Tregs according to the immunosuppressive mechanisms.High M2-TAMs infiltration subtype reflected the worst clinical characters, immune infiltration, and lowest expression of immune checkpoint inhibitors among the three subclasses in PCa.High M2-TAMs infiltration predicts the low response rate of anti-PD-L1 therapy.

Sensor-related indoor localization has attracted considerable attention in recent years. The accuracy of conventional fingerprint solutions based on a single sensor, such as a Wi-Fi sensor, is affected by multipath interferences from other electronic devices that are produced as a result of complex indoor environments. Light sensors and magnetic (i.e., geomagnetic) field sensors can be used to enhance the accuracy of a system since they are less vulnerable to disturbances. In this paper, we propose a deep feedforward (DFF)-neural-network-based method, termed DFF-WGL, which integrates the data from the embedded Wi-Fi sensor, geomagnetic field sensor, and light sensor (WGL) in a smart device to localize the device in an indoor environment. DFF-WGL does not require complex and expensive auxiliary equipment, except for basic fluorescent lamps and low-density Wi-Fi signal coverage, conditions that are easily satisfied in modern offices or educational buildings. The proposed system was implemented on a commercial off-the-shelf android device, and performance was evaluated through an experimental analysis conducted in two different indoor testbeds, one measuring 60.5 m2 and the other measuring 38 m2, with 242 and 60 reference points, respectively. The results indicate that the model prediction with an input consisting of the combination of light, a magnetic field sensor, and two Wi-Fi RSS signals achieved mean localization errors of 0.01 m and 0.04 m in the two testbeds, respectively, compared with any subset of combination of sensors, verifying the effectiveness of the proposed DFF-WGL method. [ABSTRACT FROM AUTHOR]

The growth of a high‐quality complete graphene layer is successfully achieved for Ir(111) and Ru(0001) substrates using liquid ethanol as a precursor. Metallic substrates, which are cleaned in ultra‐high vacuum conditions, were ex‐situ immersed in liquid ethanol followed by the controlled in situ thermal annealing. The process of graphene formation and its quality are carefully monitored using X‐ray photoelectron spectroscopy, low‐energy electron diffraction, and scanning tunneling microscopy methods. It is found that graphene formation starts at 400 °C via ethanol decomposition and desorption of oxygen from the surface leading to the formation of the high‐quality complete graphene layer at 1000 °C. The results of the systematic angular‐resolved photoelectron spectroscopy experiments confirm the high quality of the obtained graphene layer, and it concludes that such an approach offers an easy, quick, and reproducible method to synthesize large‐scale graphene on different metallic substrates. [ABSTRACT FROM AUTHOR]

The technology for human activity recognition has diverse applications within the Internet of Things spectrum, including medical sensing, security measures, smart home systems, and more. Predominantly, human activity recognition methods have relied on contact sensors, and some research uses inertial sensors embedded in smartphones or other devices, which present several limitations. Additionally, most research has concentrated on recognizing discrete activities, even though activities in real-life scenarios tend to be continuous. In this paper, we introduce a method to classify continuous human activities, such as walking, running, squatting, standing, and jumping. Our approach hinges on the micro-Doppler (MD) features derived from continuous-wave radar signals. We first process the radar echo signals generated from human activities to produce MD spectrograms. Subsequently, a bidirectional gate recurrent unit (Bi-GRU) network is employed to train and test these extracted features. Preliminary results highlight the efficacy of our approach, with an average recognition accuracy exceeding 90%. [ABSTRACT FROM AUTHOR]

Device-free localization (DFL) is a technology designed to determine the positions of targets without the need for them to carry electronic devices. It achieves this by analyzing the shadowing effects of radio links within wireless sensor networks (WSNs). However, obtaining high precision in DFL often results in increased energy consumption, severe electromagnetic interference, and other challenges that impact positioning accuracy. Most DFL schemes for accurate tracking require substantial memory and computing resources, which make them unsuitable for resource-constrained applications. To address these challenges, we propose an intelligent mesh cluster (IMC) algorithm that achieves accurate tracking by adaptively activating a subset of wireless links. This approach not only reduces electromagnetic interference but also saves energy. The IMC algorithm leverages geometric objects, such as meshes and mesh clusters formed by wireless links, to achieve low computational complexity. By scanning a subset of mesh cluster-related wireless links near the DFL target, the algorithm significantly reduces the computational requirements. The target's location estimate is determined based on the connection information among the mesh clusters. We conducted numerous simulations to evaluate the performance of the IMC algorithm. The results demonstrate that the IMC algorithm outperforms grid-based and particle filter-based DFL methods, confirming its effectiveness in achieving accurate and efficient localization. [ABSTRACT FROM AUTHOR]

This study investigates the therapeutic effect and the underlying mechanisms of ergothioneine (EGT) on the testicular damage caused by varicocele (VC) in vivo, in vitro, and in silico. This preclinical study combines a series of biological experiments and network pharmacology analyses. A total of 18 Sprague Dawley (SD) male rats were randomly and averagely divided into three groups: the sham‐operated, VC model, and VC model with EGT treatment (VC + EGT) groups. The left renal vein of the VC model and the VC + EGT groups were half‐ligated for 4 weeks. Meanwhile, the VC + EGT group was intragastrically administrated with EGT (10 mg/kg). GC1 and GC2 cells were exposed to H2O2 with or without EGT treatment to re‐verify the conclusion. The structure disorder of seminiferous tubules ameliorated the apoptosis decrease in the VC rats receiving EGT. EGT can also increase the sperm quality of the VC model rats (p < 0.05). The exposure to H2O2 decreased proliferation and increased apoptosis of GC1 and GC2 cells, which was revisable by adding EGT to the plates (p < 0.05). The network pharmacology and molecular docking were conducted to explore the potential targets of EGT in VC, and HSP90AA1 was identified as the pivotal gene, which was validated by western blot, immunohistochemistry, and RT‐qPCR both in vivo and in vitro (p < 0.05). Overall, EGT attenuates the testicular injury in the VC model both in vivo and in vitro by potentially potentiating the expression of HSP90AA1. [ABSTRACT FROM AUTHOR]

Polyurethane acrylate prepolymers with different contents of HIPIH and HIH were synthesized via reacting excessive isophorone diisocyanate (IPDI) with poly(propylene glycol) (PPG) and then end-capping with 2-hydroxypropyl methacrylate (HPMA) in isobornyl methacrylate (IBOMA). After the addition of the photoinitiator PI 1173, the resulting prepolymer resins were irradiated by UV light to form cured materials. The structures of the prepolymers were confirmed by 1H NMR, FT-IR, and GPC. SEM analyses proved that no obvious phase separation was observed within the cured sample. As the content of HIH increased, the viscosity of the prepolymers increased slightly. In addition, the gel content, solvent resistance, Shore hardness, Young's modulus, and the tensile strength of the cured films increased, whereas the elongation at break decreased gradually. The volume shrinkage of the cured samples ranged between 4.5% and 4.8%. DMA analyses showed that the Tgs of the cured samples increased as more HIH structures existed. TGA analyses revealed that the cured samples had high thermal stability. This solvent-free fabrication process was simple, convenient, and controllable. By simply regulating the contents of HIPIH and HIH in the prepolymers, the performances of the cured materials could be adjusted to a wide range. [ABSTRACT FROM AUTHOR]

In the tracking scheme in which global navigation satellite system (GNSS) measurement is temporally lost or the sampling frequency is insufficient, dead reckoning based on the inertial measurement unit (IMU) and other location-related information can be fused as a supplement for real-time trajectory recovery. The tracking scheme based on interval analysis outputs interval results containing the ground truth, which gives it the advantage of convenience in multi-source information fusion. In this paper, a trajectory-recovery algorithm based on interval analysis is proposed, which can conveniently fuse GNSS measurement, IMU data, and map constraints and then output an interval result containing the actual trajectory. In essence, the location-related information such as satellite measurement, inertial data, and map constraints is collected by practical experiments and then converted into interval form. Thereby, the interval-overlapping calculation is performed through forward and backward propagation to accomplish the trajectory recovery. The practical experimental results show that the trajectory recovery accuracy based on the proposed algorithm performs better than the traditional Kalman filter algorithm, and the estimated interval results deterministically contain the actual trajectory. More importantly, the proposed interval algorithm is approved to be convenient to fuse additional location-related information. [ABSTRACT FROM AUTHOR]

Background. Triple-negative breast cancer (TNBC) is a subtype of breast cancer with limited therapeutic options. Eupalinolide O (EO) was reported to inhibit tumor growth. This study is aimed at exploring the role of EO on TNBC both in vivo and in vitro. Methods. In in vitro experiments, 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) and clonogenic assay were conducted to measure the impact of EO on TNBC cell growth at different concentrations and time points. Flow cytometry was conducted to evaluate cell apoptosis. Mitochondrial membrane potential (MMP) loss, caspase-3 activity, and reactive oxygen species (ROS) generation were assessed. The expressions of apoptosis-related mRNAs and Akt/p38 MAPK signaling pathway-related proteins were measured. In in vivo experiments, by injecting TNBC cells into the nude mice to induce xenograft tumor, mice were treated with EO for 20 days. Then, in vivo bioluminescence imaging system was utilized to monitor the growth and distribution of TNBC cells. Tumor volume and weight were also recorded. Hematoxylin-eosin (HE) staining and ELISA assay were applied to observe tumor tissue morphology and ROS levels. Furthermore, western blotting was conducted to observe the expression of apoptosis-related proteins and Akt/p38 MAPK signaling pathway-associated proteins. Results. EO inhibited the cell viability and proliferation of TNBC cells but not normal epithelial cells. Furthermore, EO induced apoptosis, decreased MMP, and elevated caspase-3 activity and ROS content in TNBC cells. Meanwhile, the expression of apoptosis-related mRNAs and Akt/p38 MAPK pathway-related proteins was regulated by EO treatment. Besides, in vivo experiments demonstrated EO not only suppressed tumor growth, Ki67 expression, ROS generation, and Akt phosphorylation but also upregulated caspase-3 expression and p-38 phosphorylation. Conclusion. EO may induce cell apoptosis in TNBC via regulating ROS generation and Akt/p38 MAPK pathway, indicating EO may be a candidate drug for TNBC. [ABSTRACT FROM AUTHOR]

Background. Lung adenocarcinoma is the most common lung cancer subtype and accounts for the highest proportion of cancer-related deaths. The tumor microenvironment influences prognostic outcomes in lung adenocarcinoma (LUAD). Materials and Methods. We used the ESTIMATE algorithm (Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data) to investigate the role of microenvironment-related genes and stromal cells in lung adenocarcinoma prognosis. This analysis was done on lung adenocarcinoma cases from The Cancer Genome Atlas (TCGA). The cases were divided into high and low groups on the basis of immune and stromal scores, respectively. Results. There were close correlations between immune scores with prognosis and disease stage. There were 367 differentially expressed genes. Combining the Gene Expression Omnibus (GEO) database, we found 14 prognosis-related genes. Results. Based on the enrichment levels of the immune cell types, we clustered LUAD into Immunity_H and Immunity_L subtypes. Most of these genes were upregulated in Immunity_H subtype. Finally, using the Human Protein Atlas (HPA) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC) databases, most of the proteins corresponding to prognostic genes were verified to be differentially expressed between the tumor and normal groups. Conclusions. The key genes identified in this study are involved in molecular mechanisms of LUAD. [ABSTRACT FROM AUTHOR]

Aerosol extinction coefficient profile (ECP) is important in radiative transfer modeling, however, knowledge of ECP in some area has not been clearly recognized. To get a full understanding of statistical characteristics of ECP in three Asian regions: the Mongolian Plateau, the North China Plain and the Yellow Sea, CALIPSO aerosol product in 2012 is processed by conventional statistical methods. Orbit averaged ECP turns out to be mainly exponential and Gaussian patterns. Curve fitting shows that the two ECP patterns account for more than 50 percent of all the samples, especially in the Yellow Sea where the frequency of occurrence even reaches over 80 percent. Parameters determining fitting curves are provided consequently. To be specific, Gaussian pattern is the main ECP distribution in the Mongolian Plateau and the Yellow Sea, and exponential pattern predominates in the North China Plain. Besides, aerosol scale height reaches its maximum in summer and in the Mongolian Plateau. Meanwhile, the uplifting and deposition of dust during transportation are potentially explanations to the occurrence of Gaussian ECP. The results have certain representativeness, and contribute to reducing uncertainties of aerosol model in relevant researches.

Recently, traffic flow prediction has drawn significant attention because it is a prerequisite in intelligent transportation management in urban informatics. The massively available traffic data collected from various sensors in transportation cyber–physical systems brings the opportunities in accurately forecasting traffic trend. Recent advances in deep learning shows the effectiveness on traffic flow prediction though most of them only demonstrate the superior performance on traffic data from a single type of vehicular carriers (e.g., cars) and does not perform well in other types of vehicles. To fill this gap, in this article, we propose a wide-attention and deep-composite (WADC) model, consisting of a wide-attention module and a deep-composite module, in this article. In particular, the wide-attention module can extract global key features from traffic flows via a linear model with self-attention mechanism. The deep-composite module can generalize local key features via convolutional neural network component and long short-term memory network component. We also perform extensive experiments on different types of traffic flow datasets to investigate the performance of WADC model. Our experimental results exhibit that WADC model outperforms other existing approaches. [ABSTRACT FROM AUTHOR]

Long noncoding RNAs (lncRNAs) are involved in the pathology of various tumours, including non‐small cell lung cancer (NSCLC). However, the underlying molecular mechanisms of their specific association with NSCLC have not been fully elucidated. Here, we report that a cytoplasmic lncRNA, DUXAP9‐206 is overexpressed in NSCLC cells and closely related to NSCLC clinical features and poor patient survival. We reveal that DUXAP9‐206 induced NSCLC cell proliferation and metastasis by directly interacting with Cbl‐b, an E3 ubiquitin ligase, and reducing the degradation of epidermal growth factor receptor (EGFR) and thereby augmenting EGFR signaling in NSCLC. Notably, correlations between DUXAP9‐206 and activated EGFR signaling were also validated in NSCLC patient specimens. Collectively, our findings reveal the novel molecular mechanisms of DUXAP9‐206 in mediating the progression of NSCLC and DUXAP9‐206 may serve as a potential target for NSCLC therapy. [ABSTRACT FROM AUTHOR]

Carbon‐based transition metal/nitrogen material is one of the most promising non‐precious metal catalysts for the oxygen reduction reaction. And N‐containing polymers are considered as a kind of excellent N precursor because they are more likely to form ordered and stable carbon‐based active layer during heat treatment. However, further research is still needed due to the inferior oxygen reduction catalytic activity compared with Pt in acidic condition. Herein, we design the Fe/N/C catalyst through synthesize a special nitrogen‐rich polymer poly‐hexaazatrinaphthylene as N source and subsequently calcine with the mixture of ferric chloride and Vulcan XC‐72. The physical results indicate that the oxygen reduction catalytic activity is mainly related to the amorphous carbon, pyridinic‐N, and Fe‐N4 coordination geometry. Electrochemical tests indicated that the sample pyrolyzed at 800°C presents relative high oxygen reduction activity in 0.5 mol L−1 H2SO4 via an efficient four‐electron‐dominant pathway. We synthesis a kind of special N‐containing polymer poly‐hexaazatrinaphthylene (PHANT) as precursor to build Fe/N/C catalyst towards oxygen reduction in acidic conditions. It owns Fe‐N4 moiety and shows good catalytic activity with onset potential 0.78 V. [ABSTRACT FROM AUTHOR]