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Abstract As a form of body language, the gesture plays an important role in smart homes, game interactions, and sign language communication, etc. The gesture recognition methods have been carried out extensively. The existing methods have inherent limitations regarding user experience, visual environment, and recognition granularity. Millimeter wave radar provides an effective method for the problems lie ahead gesture recognition because of the advantage of considerable bandwidth and high precision perception. Interfering factors and the complexity of the model raise an enormous challenge to the practical application of gesture recognition methods as the millimeter wave radar is applied to complex scenes. Based on multi-feature fusion, a gesture recognition method for complex scenes is proposed in this work. We collected data in variety places to improve sample reliability, filtered clutters to improve the signal’s signal-to-noise ratio (SNR), and then obtained multi features involves range-time map (RTM), Doppler-time map (DTM) and angle-time map (ATM) and fused them to enhance the richness and expression ability of the features. A lightweight neural network model multi-CNN-LSTM is designed to gestures recognition. This model consists of three convolutional neural network (CNN) for three obtained features and one long short-term memory (LSTM) for temporal features. We analyzed the performance and complexity of the model and verified the effectiveness of feature extraction. Numerous experiments have shown that this method has generalization ability, adaptability, and high robustness in complex scenarios. The recognition accuracy of 14 experimental gestures reached 97.28%.

Abstract Background and objectives Helicobacter pylori (H. pylori) infection is the most common etiology of chronic gastric. H. pylori gastritis would gradually evolve into gastric atrophy, intestinal metaplasia, dysplasia and malignant lesions. Herein, this study aimed to investigate the potential impact of H. pylori colonization density and depth on the severity of histological parameters of gastritis. Methods A prospective monocentric study was conducted from December 2019 to July 2022, enrolling patients with confirmed chronic H. pylori infection via histopathological evaluation. H. pylori colonization status was detected by immunohistochemical staining, pathological changes of gastric specimens were detected by hematoxylin eosin staining. Epidemiological, endoscopic and histopathological data were collected. Results A total of 1120 patients with a mean age of 45.8 years were included. Regardless of the previous history of H. pylori eradication treatment, significant correlations were observed between the density and depth of H. pylori colonization and the intensity of gastritis activity (all P

T-cell immunoglobulin domain and mucin domain-3 (Tim-3) is a versatile immunomodulator that protects against intestinal inflammation. Necroptosis is a type of cell death that regulates intestinal homeostasis and inflammation. The mechanism(s) underlying the protective role of macrophage Tim-3 in intestinal inflammation is unclear; thus, we investigated whether specific Tim-3 knockdown in macrophages drives intestinal inflammation via necroptosis. Tim-3 protein and mRNA expression were assessed via double immunofluorescence staining and single-cell RNA sequencing (sc-RNA seq), respectively, in the colonic tissues of patients with inflammatory bowel disease (IBD) and healthy controls. Macrophage-specific Tim3-knockout (Tim-3M−KO) mice were generated to explore the function and mechanism of Tim-3 in dextran sodium sulfate (DSS)-induced colitis. Necroptosis was blocked by pharmacological inhibitors of receptor-interacting protein kinase (RIP)1, RIP3, and reactive oxygen species (ROS). Additionally, in vitro experiments were performed to assess the mechanisms of neutrophil necroptosis induced by Tim-3 knockdown macrophages. Although Tim-3 is relatively inactive in macrophages during colon homeostasis, it is highly active during colitis. Compared to those in controls, Tim-3M−KO mice showed increased susceptibility to colitis, higher colitis scores, and increased pro-inflammatory mediator expression. Following the administration of RIP1/RIP3 or ROS inhibitors, a significant reduction in intestinal inflammation symptoms was observed in DSS-treated Tim-3M−KO mice. Further analysis indicated the TLR4/NF-κB pathway in Tim-3 knockdown macrophages mediates the TNF-α-induced necroptosis pathway in neutrophils. Macrophage Tim-3 regulates neutrophil necroptosis via intracellular ROS signaling. Tim-3 knockdown macrophages can recruit neutrophils and induce neutrophil necroptosis, thereby damaging the intestinal mucosal barrier and triggering a vicious cycle in the development of colitis. Our results demonstrate a protective role of macrophage Tim-3 in maintaining gut homeostasis by inhibiting neutrophil necroptosis and provide novel insights into the pathogenesis of IBD.

Background and aimsTumor-associated macrophage (TAM) is a highly abundant immune population in tumor microenvironment, which plays an important role in tumor growth and progression. The aim of our study was to explore the development trends and research hotspots of TAM by bibliometric method.MethodsThe publications related to TAM were obtained from the Web of Science Core Collection database. Bibliometric analysis and visualization were conducted using VOSviewer, CiteSpace and R software.ResultsA total of 6,405 articles published between 2001 and 2021 were included. The United States and China received the most citations, whereas the University of Milan, the university of California San Francisco and Sun Yat-sen University were the main research institutions. Mantovani, Alberto from Humanitas University was the most productive authors with the most citations. Cancer Research published the most articles and received the most co-citations. Activation, angiogenesis, breast cancer, NF-κB and endothelial growth factor were important keywords in TAM research. Among them, PD-1/L1, nanoparticle, PI3Kγ, resistance and immune microenvironment have become the focus of attention in more recent research.ConclusionsThe research on TAM is rapidly evolving with active cooperation worldwide. Anticancer therapy targeting TAM is emerging and promising area of future research, especially in translational application. This may provide guidance and new insights for further research in the field of TAM.

Background: Colon adenocarcinoma (COAD), a malignant gastrointestinal tumor, has the characteristics of high mortality and poor prognosis. Even in the presence of oxygen, the Warburg effect, a major metabolic hallmark of almost all cancer cells, is characterized by increased glycolysis and lactate fermentation, which supports biosynthesis and provides energy to sustain tumor cell growth and proliferation. However, a thorough investigation into glycolysis- and lactate-related genes and their association with COAD prognosis, immune cell infiltration, and drug candidates is currently lacking.Methods: COAD patient data and glycolysis- and lactate-related genes were retrieved from The Cancer Genome Atlas (TCGA) and Gene Set Enrichment Analysis (GSEA) databases, respectively. After univariate Cox regression analysis, a nonnegative matrix factorization (NMF) algorithm was used to identify glycolysis- and lactate-related molecular subtypes. Least absolute shrinkage and selection operator (LASSO) Cox regression identified twelve glycolysis- and lactate-related genes (ADTRP, ALDOB, APOBEC1, ASCL2, CEACAM7, CLCA1, CTXN1, FLNA, NAT2, OLFM4, PTPRU, and SNCG) related to prognosis. The median risk score was employed to separate patients into high- and low-risk groups. The prognostic efficacy of the glycolysis- and lactate-related gene signature was assessed using Kaplan–Meier (KM) survival and receiver operating characteristic (ROC) curve analyses. The nomogram, calibration curves, decision curve analysis (DCA), and clinical impact curve (CIC) were employed to improve the clinical applicability of the prognostic signature. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed on differentially expressed genes (DEGs) from the high- and low-risk groups. Using CIBERSORT, ESTIMATE, and single-sample GSEA (ssGSEA) algorithms, the quantities and types of tumor-infiltrating immune cells were assessed. The tumor mutational burden (TMB) and cytolytic (CYT) activity scores were calculated between the high- and low-risk groups. Potential small-molecule agents were identified using the Connectivity Map (cMap) database and validated by molecular docking. To verify key core gene expression levels, quantitative real-time polymerase chain reaction (qRT–PCR) assays were conducted.Results: We identified four distinct molecular subtypes of COAD. Cluster 2 had the best prognosis, and clusters 1 and 3 had poor prognoses. High-risk COAD patients exhibited considerably poorer overall survival (OS) than low-risk COAD patients. The nomogram precisely predicted patient OS, with acceptable discrimination and excellent calibration. GO and KEGG pathway enrichment analyses of DEGs revealed enrichment mainly in the “glycosaminoglycan binding,” “extracellular matrix,” “pancreatic secretion,” and “focal adhesion” pathways. Patients in the low-risk group exhibited a larger infiltration of memory CD4+ T cells and dendritic cells and a better prognosis than those in the high-risk group. The chemotherapeutic agent sensitivity of patients categorized by risk score varied significantly. We predicted six potential small-molecule agents binding to the core target of the glycolysis- and lactate-related gene signature. ALDOB and APOBEC1 mRNA expression was increased in COAD tissues, whereas CLCA1 and OLFM4 mRNA expression was increased in normal tissues.Conclusion: In summary, we identified molecular subtypes of COAD and developed a glycolysis- and lactate-related gene signature with significant prognostic value, which benefits COAD patients by informing more precise and effective treatment decisions.

With the increasing popularity of smart devices, users can control their mobile phones, TVs, cars, and smart furniture by using voice assistants, but voice assistants are susceptible to intrusion by outsider speakers or playback attacks. In order to address this security issue, a millimeter-wave radar-based voice security authentication system is proposed in this paper. First, the speaker’s fine-grained vocal cord vibration signal is extracted by eliminating static object clutter and motion effects; second, the weighted Mel Frequency Cepstrum Coefficients (MFCCs) are obtained as biometric features; and finally, text-independent security authentication is performed by the WMHS (Weighted MFCCs and Hog-based SVM) method. This system is highly adaptable and can authenticate designated speakers, resist intrusion by other unspecified speakers as well as playback attacks, and is secure for smart devices. Extensive experiments have verified that the system achieves a 93.4% speaker verification accuracy and a 5.8% miss detection rate for playback attacks.

Millimeter-wave SAR (Synthetic Aperture Radar) imaging is widely studied as a common means of RF (Radio Frequency) imaging, but there are problems of the ghost image in Sparsely-Sampled cases and the projection of multiple targets at different distances. Therefore, a robust imaging algorithm based on the Analytic Fourier Transform is proposed, which is named mmSight. First, the original data are windowed with Blackman window to take multiple distance planes into account; then, the Analytic Fourier Transform that can effectively suppress the ghost image under Sparsely-Sampled is used for imaging; finally, the results are filtered using a Mean Filter to remove spatial noise. The experimental results show that the proposed imaging algorithm in this paper, relative to other algorithms, can image common Fully-Sampled single target, hidden target, and multiple targets at the same distance, and solve the ghost image problem of single target in the case of Sparsely-Sampled, as well as the projection problem of multiple targets at different distances; the Image Entropy of the mmSight is 4.6157 and is on average 0.3372 lower than that of other algorithms. Compared with other algorithms, the sidelobe and noise of the Point Spread Function are suppressed, so the quality of the image obtained from imaging is better than that of other algorithms.

The experimental data for the shear modulus and yield strength of shocked aluminum, copper and tungsten are analyzed. The analysis concludes that the shear modulus and yield stress exhibit analogous variation with temperature and pressure for aluminum up to shock pressures of 50 GPa, copper under 100 GPa, and tungsten under 200 GPa.

Steinberg-Guinan constitutive model is widely used in impact engineering simulations. Shock wave profile measurements of Al, Cu, and W under shock pressures ranging from 4 GPa to 200 GPa were analyzed, and shear modulus G and yield strength Y of these materials were obtained by using the high-pressure sonic velocities and rate independent Lagrange analysis results. Then values of derivatives of G and Y with respect to pressure or temperature at the reference state of these three metals were determined. By analyzing the pressure and temperature dependence of shear modulus and yield strength, we conclude that the relations of Steinberg-Guinan constitutive model, Y/G=constant, are approximately correct on Hugoniot state for these materials. So this is a probable approach to solve the difficulty of measurement of Y under high-pressure and high-temperature directly. [ABSTRACT FROM AUTHOR]