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Steel is a crucial material that is extensively utilized in various aspects of daily life and holds significant importance. However, during its production, there is a possibility of certain defects arising that could have a negative impact on the quality of the steel. Only by accurately detecting the defects on the steel surface can we avoid the harm caused by defects in steel. Because the steel surface defect detection algorithm is prone to misdetection, missed detection, and other problems, a steel surface defect detection algorithm based on improved YOLOX is proposed. First, the CSPCrossLayer module proposed in this paper is used to replace the CSPLayer structure in the backbone network to enrich the gradient information of the network and strengthen the feature extraction capability; Then, the SA (Shuffle Attention) module is added after the output of the backbone network, highlighting the general information to input high-quality features for the feature fusion network; Finally, the PSblock module is proposed to replace the CSPLayer structure in the feature fusion network, which reduces redundant computations to efficiently perform feature fusion on feature layers of different scales and improves the feature fusion capability of the model. The experiments involved testing the algorithm on two datasets: the publicly available NEU-DET dataset and a steel rail dataset collected in this paper. The algorithm can reach 77% mAP on the NEU-DET dataset, while the detection speed is 100 FPS. It reaches 88.8% mAP on the steel rail dataset, and the detection speed is 93FPS. These results demonstrate that the proposed algorithm is capable of swiftly and accurately detecting surface defects in steel materials.

The pyramid-type lattice sandwich panel is known for its exemplary mechanical characteristics. In this study, we draw inspiration from the local resonance mechanisms observed in acoustic metamaterials and introduce a resonant ring to enhance the capabilities of the panel for damping low-frequency vibrations. We use the finite element method to develop a model to explore the band structure and the corresponding vibrational responses, with a particular emphasis on the significant influence of the bandgap. A comprehensive comparison between the results of experiments and those of simulations unequivocally validated our proposed model. Crucially, our findings underscore that the damping-related effect can be enhanced and the desired range of frequencies can be fine-tuned by appropriately selecting the geometric and periodic parameters of the lattice sandwich panel. These insights have important implications for tailoring materials to specific engineering applications.

Exposure to microgravity during spaceflight induces the alterations in endothelial cell function associated with post-flight cardiovascular deconditioning. PIEZO1 is a major mechanosensitive ion channel that regulates endothelial cell function. In this study, we used a two-dimensional clinostat to investigate the expression of PIEZO1 and its regulatory mechanism on human umbilical vein endothelial cells (HUVECs) under simulated microgravity. Utilizing quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot analysis, we observed that PIEZO1 expression was significantly increased in response to simulated microgravity. Moreover, we found microgravity promoted endothelial cells migration by increasing expression of PIEZO1. Proteomics analysis highlighted the importance of C-X-C chemokine receptor type 4(CXCR4) as a main target molecule of PIEZO1 in HUVECs. CXCR4 protein level was increased with simulated microgravity and decreased with PIEZO1 knock down. The mechanistic study showed that PIEZO1 enhances CXCR4 expression via Ca2+ influx. In addition, CXCR4 could promote endothelial cell migration under simulated microgravity. Taken together, these results suggest that the upregulation of PIEZO1 in response to simulated microgravity regulates endothelial cell migration due to enhancing CXCR4 expression via Ca2+ influx.

ObjectiveVestibular provocation is one of the main causes of flight illusions, and its occurrence is closely related to the susceptibility of motion sickness (MS). However, existing training programs have limited effect in improving the resistance to motion sickness. In this study, we investigated the effects of hypoxia acclimatization training (HAT) on the resistance to motion sickness.MethodsHealthy military college students were identified as subjects according to the criteria. MS model was induced by a rotary chair. Experimental groups included control, HAT, 3D roller training (3DRT), and combined training.ResultsThe Graybiel scores were decreased in the HAT group and the 3DRT group and further decreased in the combined training group in MS induced by the rotary chair. Participants had a significant increase in blood pressure after the rotary chair test and a significant increase in the heart rate during the rotary chair test, but these changes disappeared in all three training groups. Additionally, LFn was increased, HFn was decreased, and LF/HF was increased accordingly during the rotary chair test in the control group, but the changes of these three parameters were completely opposite in the three training groups during the rotary chair test. Compared with the control group, the decreasing changes in pupillary contraction velocity (PCV) and pupillary minimum diameter (PMD) of the three training groups were smaller. In particular, the binocular PCV changes were further attenuated in the combined training group.ConclusionOur research provides a possible candidate solution for training military pilots in the resistance to motion sickness.

Intervertebral disk degeneration (IDD) is a chronic inflammatory disease with intricate connections between immune infiltration and oxidative stress (OS). Complex cell niches exist in degenerative intervertebral disk (IVD) and interact with each other and regulate the disk homeostasis together. However, few studies have used longitudinal approach to describe the immune response of IDD progression. Here, we conducted conjoint analysis of bulk-RNA sequencing and single-cell sequencing, together with a series of techniques like weighted gene co-expression network analysis (WGCNA), immune infiltration analysis, and differential analysis, to systematically decipher the difference in OS-related functions of different cell populations within degenerative IVD tissues, and further depicted the longitudinal alterations of immune cells, especially monocytes/macrophages in the progression of IDD. The OS-related genes CYP1A1, MMP1, CCND1, and NQO1 are highly expressed and might be diagnostic biomarkers for the progression of IDD. Further landscape of IVD microenvironment showed distinct changes in cell proportions and characteristics at late degeneration compared to early degeneration of IDD. Monocytes/macrophages were classified into five distinct subpopulations with different roles. The trajectory lineage analysis revealed transcriptome alterations from effector monocytes/macrophages and regulatory macrophages to other subtypes during the evolution process and identified monocytes/macrophage subpopulations that had rapidly experienced the activation of inflammatory or anti-inflammatory responses. This study further proposed that personalized therapeutic strategies are needed to be formulated based on specific monocyte/macrophage subtypes and degenerative stages of IDD.

Sonodynamic therapy (SDT) has attracted widespread interest in biomedicine, owing to its novel and noninvasive therapeutic method triggered by ultrasound (US). Herein, the Ti3C2 MXene nanosheets (Ti3C2 NSs) are developed as good sonosensitizers via a two-step method of chemical exfoliation and high-temperature treatment. With the high-temperature treatment, the oxygen defect of Ti3C2 MXene nanosheets (H–Ti3C2 NSs) is greatly increased. Therefore, the electron (e−) and hole (h+) generated by US can be separated faster due to the improved degree of oxidation, and then the recombination of e−-h+ can be prevented with the abundant oxygen defect under US irradiation, which induced the sonodynamic efficiency greatly to improve around 3.7-fold compared with Ti3C2 NSs without high-temperature treatment. After PEGylation, the H–Ti3C2-PEG NSs show good stability and biocompatibility. In vitro studies exhibit that the inherent property of mild photothermal effect can promote the endocytosis of H–Ti3C2-PEG NSs, which can improve the SDT efficacy. In vivo studies further display that the increased blood supply by the mild photothermal effect can significantly relieve hypoxia in the tumor microenvironment, showing photothermal therapy (PTT) enhanced SDT. Most importantly, the H–Ti3C2-PEG NSs can be biodegraded and excreted out of the body, showing no significant long-term toxicity. Our work develops the defective H–Ti3C2 NSs as high-efficiency and safe sonosensitizers for photothermal-enhanced SDT of cancer, extending the biomedical application of MXene-based nanoplatforms.

African swine fever (ASF) is the most dangerous pig disease, and causes enormous economic losses in the global pig industry. However, the mechanisms of ASF virus (ASFV) infection remains largely unclear. Hence, this study investigated the host response mechanisms to ASFV infection. We analyzed the differentially expressed proteins (DEPs) between serum samples from ASFV-infected and uninfected pigs using quantitative proteomics. Setting the p-value < 0.05 and |log2 (fold change)| > 1.5, we identified 173 DEPs, comprising 57 upregulated and 116 downregulated proteins, which belonged to various biological processes and pathways based on the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. The enriched pathways include immune responses, metabolism, and inflammation signaling pathways. Western blot analysis validated the DEPs identified using quantitative proteomics. Furthermore, our proteomics data showed that C1QTNF3 regulated the inflammatory signaling pathway. C1QTNF3 knockdown led to the upregulation of pro-inflammatory factors IL-1β, IL-8, and IL-6, thus inhibiting ASFV replication. These results indicated that C1QTNF3 was critical for ASFV infection. In conclusion, this study revealed the molecular mechanisms underlying the host-ASFV interaction, which may contribute to the development of novel antiviral strategies against ASFV infection in the future.

Abstract Objectives This study aimed to identify novel targets in the carcinogenesis, therapy and prognosis of osteosarcoma from genomic level, together with screening ideal lead compounds with potential inhibition regarding MMP-9. Methods Gene expression profiles from GSE12865, GSE14359, GSE33382, GSE36001 and GSE99671 were obtained respectively from GEO database. Differentially expressed genes were identified, and functional enrichment analysis, such as GO, KEGG, GSEA, PPI were performed to make a comprehensive understanding of the hub genes. Next, a series of high-precision computational techniques were conducted to screen potential lead compounds targeting MMP9, including virtual screening, ADME, toxicity prediction, and accurate docking analysis. Results 10 genes, MMP9, CD74, SPP1, CXCL12, TYROBP, FCER1G, HCLS1, ARHGDIB, LAPTM5 and IGF1R were identified as hub genes in the initiation of osteosarcoma. Machine learning, multivariate Cox analysis, ssGSEA and survival analysis demonstrated that these genes had values in prognosis, immune-correlation and targeted treatment. Tow novel compounds, ZINC000072131515 and ZINC000004228235, were screened as potential inhibitor regarding MMP9, and they could bind to MMP9 with favorable interaction energy and high binding affinity. Meanwhile, they were precited to be efficient and safe drugs with low-ames mutagenicity, none weight evidence of carcinogenicity, as well as non-toxic with liver. Conclusions This study revealed the significance of 10-gene signature in the development of osteosarcoma. Besides, drug candidates identified in this study provided a solid basis on MMP9 inhibitors’ development.

Influenza A virus (IAV) poses a serious threat to human life and property. The IAV matrix protein 2 (M2) is significant in viral budding. Increasing studies have proven the important roles of host factors in IAV replication. In this study, immunoprecipitation combined with mass spectrometry revealed that the host protein tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein gamma (YWHAG), which belongs to the 14-3-3 protein scaffold family, interacts with M2. Their interactions were further confirmed by co-immunoprecipitation (Co-IP), immunofluorescence, and confocal microscopy of virus-infected HeLa cells. Moreover, we constructed YWHAG-KO and YWHAG-overexpressing cells and found that YWHAG knockout significantly increased viral production, whereas its overexpression reduced the titer of virus progeny. Therefore, YWHAG is a negative regulatory factor during IAV infection. Further, YWHAG knockout or overexpression had no effect on the binding, entry, or viral RNA replication in the early stages of the virus life cycle. On the contrary, it impaired the release of virions at the plasma membrane as determined using transmission electron microscopy and suppressed the M2-mediated budding of the influenza virus. Importantly, the H158F mutation of YWHAG was found to affect interaction with M2 and its budding. Collectively, our work demonstrates that YWHAG is a novel cellular regulator that targets and mediates the interaction and release of M2.

The effect of cardiovascular dysfunction including orthostatic intolerance and disability on physical exercise is one of the health problems induced by long-term spaceflight astronauts face. As an important part of vascular structure, the vascular endothelium, uniquely sensitive to mechanical force, plays a pivotal role in coordinating vascular functions. Our study found that simulated microgravity induced PINK1-dependent mitophagy in human umbilical vein endothelial cells (HUVECs). Here, we explored the underlying mechanism of mitophagy induction. The ER stress induced by proteostasis failure in HUVECs promoted the Ca2+ transfer from ER to mitochondria, resulting in mitochondria Ca2+ overload, decreased mitochondrial membrane potential, mitochondria fission, and accumulation of Parkin and p62 in mitochondria and mitophagy under simulated microgravity. Moreover, we assumed that mitophagy played a vital role in functional changes in endothelial cells under simulated microgravity. Using mdivi-1 and PINK1 knockdown, we found that NLRP3 inflammasome activation was enhanced after mitophagy was inhibited. The NLRP3 inflammasome contributed to endothelial hyperpermeability and cellular migration by releasing IL-1β. Thus, mitophagy inhibited cell migration ability and hyperpermeability in HUVECs exposed to clinostat-simulated microgravity. Collectively, we here clarify the mechanism of mitophagy induction by simulated microgravity in vitro and demonstrate the relationship between mitophagy and vascular endothelial functional changes including cellular migration and permeability. This study deepens the understanding of vascular functional changes under microgravity.

The vibration suppression performance of the pyramid lattice core sandwich plates is receiving increasing attention and needs further investigation for technical upgrading of potential engineering applications. Inspired by the localized resonant mechanism of the acoustic metamaterials and considering the integrity of the lattice sandwich plate, we reshaped a sandwich pyramid lattice core with resonant rings (SPLCRR). Finite element (FE) models are built up for the calculations of the dispersion curves and vibration transmission. The validity of the bandgap of the SPLCRR and remarkable vibration suppression are verified by experimental observations and the numerical methods. Furthermore, the effects of geometric parameters, material parameters and period parameters on the bandgaps of the SPLCRR are systematically investigated, which offers a deeper understanding of the underlying mechanism of bandgap and helps the SPLCRR structure meet the technological update requirements of practical engineering design.

ABSTRACTCOVID-19 is a new respiratory illness caused by SARS-CoV-2, and has constituted a global public health emergency. Cat is susceptible to SARS-CoV-2. However, the prevalence of SARS-CoV-2 in cats remains largely unknown. Here, we investigated the infection of SARS-CoV-2 in cats during COVID-19 outbreak in Wuhan by serological detection methods. A cohort of serum samples were collected from cats in Wuhan, including 102 sampled after COVID-19 outbreak, and 39 prior to the outbreak. Fifteen sera collected after the outbreak were positive for the receptor binding domain (RBD) of SARS-CoV-2 by indirect enzyme linked immunosorbent assay (ELISA). Among them, 11 had SARS-CoV-2 neutralizing antibodies with a titer ranging from 1/20 to 1/1080. No serological cross-reactivity was detected between SARS-CoV-2 and type I or II feline infectious peritonitis virus (FIPV). In addition, we continuously monitored serum antibody dynamics of two positive cats every 10 days over 130 days. Their serum antibodies reached the peak at 10 days after first sampling, and declined to the limit of detection within 110 days. Our data demonstrated that SARS-CoV-2 has infected cats in Wuhan during the outbreak and described serum antibody dynamics in cats, providing an important reference for clinical treatment and prevention of COVID-19.

In view of the present situation of “learning difficulty” in health statistics, this paper proposes a video visualization technology based on the convolutional neural network, which updates parameters by calculating the gradient of loss function to obtain accurate or nearly accurate loss function. Taking the students from 2014 to 2017 in a university in Henan as the research object, this paper analyzes the video visualization technology and its application effect on the teaching of college students’ health statistics from the aspects of students’ course awareness, learning behavior, communication between teachers and students, knowledge mastery, and course satisfaction. The results show that the external model load difference between each explicit variable and latent variable is statistically significant. Learning behavior and communication between teachers and students have a direct impact on the mastery of knowledge, and the degree of influence from high to low is as follows: learning behavior and communication between teachers and students. The teaching effect model of health statistics based on video visualization technology of the convolutional neural network has certain practicability.

With the rapid development of the Internet, the traditional Internet financial risk prediction methods can no longer meet the needs of individuals and enterprises, so the concept of cloud computing arises at the historic moment. Cloud computing has subverted the traditional financial risk prediction method and has been widely studied and applied for its distributed, dynamic and autonomous characteristics. How to efficiently and reasonably schedule the resources of cloud data center and improve the accuracy of financial risk prediction is the focus of current research. How to quantify financial risk and financial risk early warning is one of the urgent problems to be solved. Under the framework of cloud computing, this paper combines the feature extraction and data weighting to study the user’s basic attribute data and a large number of downloaded APP types. After that, linear regression with penalty is used to construct the prediction model to improve insolvency. The accuracy of customer default judgment can realize local optimization, so as to improve the prediction and control of hidden risks of customer commercial bank loans and greatly reduce the default risk of bank loans.

ABSTRACT The influenza A virus (IAV) infection is usually restricted to the respiratory tract and only rarely enters the central nervous system (CNS) and causes neurological symptoms. However, the roles of host factors involved in IAV infection in the CNS remain largely undetermined. Therefore, we aimed to characterize the host responses to IAV infection in the brain. We isolated a strain of IAV H5N6, which is neurotoxic and highly pathogenic to mice. High-throughput RNA sequencing (RNA-seq) revealed 240 differentially expressed genes in IAV-infected brains. Among the significantly downregulated genes, we focused on the gene encoding progesterone receptor membrane component-1 (PGRMC1) and observed that IAV H5N6 infection clearly inhibited PGRMC1 in both neuroblastoma and glioma cells. Furthermore, treatment with AG205, a PGRMC1-specific inhibitor, or PGRMC1 knockout promoted H5N6 multiplication in vitro, while overexpression of PGRMC1 resulted in opposite effects. Furthermore, AG205 treatment or PGRMC1 knockout significantly inhibited the retinoic acid-inducible gene I (RIG-I)-mediated interferon beta (IFN-β) signaling pathway and reduced the levels of several antiviral proteins (Mx1 and ISG15). In addition, PGRMC1-mediated regulation of IFN signaling relied on inhibition of the expression and ubiquitination of RIG-I. The loss of PGRMC1 leads to an increased susceptibility of mice (brain and lung) to influenza A virus infection. Conclusively, our results show for the first time that IAV H5N6 downregulates PGRMC1 expression to contribute to virus proliferation by inhibiting RIG-I-mediated IFN-β production in the brain. These findings may offer new insights regarding the interplay between IAV and host factors that may impact IAV pathogenicity in the brain. IMPORTANCE Central nervous system (CNS) disease is one of the most common extra-respiratory tract complications of influenza A virus (IAV) infections. However, there is still little knowledge about IAV regulating host responses in brain. In this study, we identified progesterone receptor membrane component-1 (PGRMC1) as a novel host factor involved in the replication and propagation of IAV H5N6 in the host brain. We also observed that PGRMC1 antagonism was required for viral evasion from the host immune response during IAV infection via inhibition of the retinoic acid-inducible gene I (RIG-I)-mediated interferon beta (IFN-β) signaling pathway and downstream antiviral gene expression. This study revealed a newly identified regulatory mechanism used by IAV H5N6 to ensure its life cycle in the CNS.

Avian influenza A (H7N9) viruses emerged in China in 2013 and caused a zoonotic disease associated with a high case-fatality ratio of more than 30%. Transcriptional profiles obtained using animal models reveal host responses to the disease, thereby providing insights into disease pathogenesis. Therefore, we aimed to characterize the host responses of the H7N9 virus infected-mouse lungs in this study. First, we isolated an avian-originated H7N9 strain, which was shown to be highly pathogenic to both chickens and mice. Genomic analysis results suggested that a 12-nucleotide-insertion was present at the hemagglutinin cleavage site, and both the hemagglutinin and neuraminidase genes belonged to the Yangtze River Delta lineage. RNA sequencing results revealed 566 differentially expressed genes in the H7N9-infected lungs. Moreover, transcriptome analysis revealed that over-activated antiviral signals and intense interferon-stimulated gene products possibly contributed to the high virulence of the virus in mice. Importantly, lung concentrations of inflammatory cytokines, including interleukin-1β and interleukin-6, interferon-β, and tumor necrosis factor-α, were upregulated in response to H7N9 virus infection. Overall, the present study provided a comprehensive understanding of H7N9 virus pathogenicity and correlated host immune responses.

Because of the significant environmental pollution produced by human activities, there is an ongoing need to develop transportable, simple, and reliable techniques for determining trace contaminants on the spot. This work reported a colorimetric detection method for aqueous Cr(VI) sensing by maleic acid-functionalized gold nanoparticles with high sensitivity and selectivity. The wine-red color of the probe solution can change to gray even in the presence of 1.0 µg L−1 of aqueous Cr(VI). Moreover, with the assistance of a smartphone installed with a commercially available color scan application software, its concentration of could be readily quantified on the spot without the help of UV-Vis spectrometer. The detection limit could reach as low as 0.1 µg L−1 with linear range from 0.2 to 2.0 µg L−1. Most importantly, the coefficient variation of the proposed smartphone-based method was equivalent to that of colorimetry, demonstrating the high accuracy of the proposed method for accurate detection of Cr(VI) in resource-constrained countries. Conclusively, with the help of the smartphone, this nanomaterials-based probe demonstrated the potential in the field of environment monitoring for on-site quantitative detection of any pollutants in resource-constrained countries.

Influenza is a highly known contagious viral infection that has been responsible for the death of many people in history with pandemics. These pandemics have been occurring every 10 to 30 years in the last century. The most recent global pandemic prior to COVID-19 was the 2009 influenza A (H1N1) pandemic. A decade ago, the H1N1 virus caused 12,500 deaths in just 19 months globally. Now, again, the world has been challenged with another pandemic. Since December 2019, the first case of a novel coronavirus (COVID-19) infection was detected in Wuhan. This infection has risen rapidly throughout the world; even the World Health Organization (WHO) announced COVID-19 as a worldwide emergency to ensure human health and public safety. This review article aims to discuss important issues relating to COVID-19, including clinical, epidemiological, and pathological features of COVID-19 and recent progress in diagnosis and treatment approaches for the COVID-19 infection. We also highlight key similarities and differences between COVID-19 and influenza A to ensure the theoretical and practical details of COVID-19.

Microseismic source location is crucial for the early warning of rockburst risks. However, the conventional methods face challenges in terms of the microseismic wave velocity and arrival time accuracy. Intelligent techniques, such as the full convolutional neural network (FCNN), can capture spatial information but struggle with complex microseismic sequence. Combining the FCNN with the long short-term memory (LSTM) network enables better time-series signal classification by integrating multi-scale information and is therefore suitable for waveform location. The LSTM-FCNN model does not require extensive data preprocessing and it simplifies the microseismic source location through feature extraction. In this study, we utilized the LSTM-FCNN as a regression learning model to locate the seismic focus. Initially, the method of short-time-average/long-time-average (STA/LTA) arrival time picking was employed to augment spatiotemporal information. Subsequently, oversampling the on-site data was performed to address the issue of data imbalance, and finally, the performance of LSTM-FCNN was tested. Meanwhile, we compared the LSTM-FCNN model with previous deep-learning models. Our results demonstrated remarkable location capabilities with a mean absolute error (MAE) of only 7.16 m. The model can realize swift training and high accuracy, thereby significantly improving risk warning of rockbursts.

Abstract N-Myc is a key driver of neuroblastoma and neuroendocrine prostate cancer (NEPC). One potential way to circumvent the challenge of undruggable N-Myc is to target the protein homeostasis (proteostasis) system that maintains N-Myc levels. Here, we identify heat shock protein 70 (HSP70) as a top partner of N-Myc, which binds a conserved “SELILKR” motif and prevents the access of E3 ubiquitin ligase, STIP1 homology and U-box containing protein 1 (STUB1), possibly through steric hindrance. When HSP70’s dwell time on N-Myc is increased by treatment with the HSP70 allosteric inhibitor, STUB1 is in close proximity with N-Myc and becomes functional to promote N-Myc ubiquitination on the K416 and K419 sites and forms polyubiquitination chains linked by the K11 and K63 sites. Notably, HSP70 inhibition significantly suppressed NEPC tumor growth, increased the efficacy of aurora kinase A (AURKA) inhibitors, and limited the expression of neuroendocrine-related pathways.