Dual Feature Fusion Tracking With Combined Cross-Correlation and Transformer

Siamese networks have found applications in various fields, notably object tracking, due to their remarkable speed and accuracy. Siamese tracking networks rely on cross-correlation to obtain the similarity score between the target template and the search region. However, since cross-correlation is a local matching operation, it cannot effectively capture the global context information. While the Transformer for feature fusion can better capture long-range dependencies and obtain more semantic information, more localized edge information is needed to distinguish the target from the background. Cross-correlation fusion and Transformer fusion have their advantages. They can complement each other, so we combine them and propose a dual feature fusion tracker (SiamCT) to obtain the local correlations and global dependencies between the target and the search region. Specifically, we construct two parallel feature fusion paths based on cross-correlation and Transformer. Among them, for cross-correlation fusion, we adopt the more efficient two-dimension pixel-wise cross-correlation (TDPC), which performs correlation operations from both spatial and channel dimensions, and the interaction of multidimensional information helps to realize more accurate feature fusion. Subsequently, the fused features are augmented by coordinate attention (CA) for orientation-dependent positional information. For Transformer fusion, we introduce cos-based linear attention(ClA) to improve Transformer’s ability to acquire global context information. Our SiamCT outperforms existing leading methods in GOT-10k, LaSOT, TrackingNet, and OTB100 benchmarks based on extensive experiments. In particular, the AO score on the GOT-10k benchmark is 70.6%, and the ${SR_{0.5}}$ and ${SR_{0.75}}$ scores are 80.5%, 65.9%, respectively, achieving state-of-the-art performance

Ginsenoside Rd alleviates mouse acute renal ischemia/reperfusion injury by modulating macrophage phenotype

Background: Ginsenoside Rd (GSRd), a main component of the root of Panax ginseng, exhibits anti-inflammation functions and decreases infarct size in many injuries and ischemia diseases such as focal cerebral ischemia. M1 Macrophages are regarded as one of the key inflammatory cells having functions for disease progression. Methods: To investigate the effect of GSRd on renal ischemia/reperfusion injury (IRI) and macrophage functional status, and their regulatory role on mouse polarized macrophages in vitro, GSRd (10–100 mg/kg) and vehicle were applied to mice 30 min before renal IRI modeling. Renal functions were reflected by blood serum creatinine and blood urea nitrogen level and histopathological examination. M1 polarized macrophages infiltration was identified by flow cytometry analysis and immunofluorescence staining with CD11b+, iNOS+/interleukin-12/tumor necrosis factor-α labeling. For the in vitro study, GSRd (10–100 μg/mL) and vehicle were added in the culture medium of M1 macrophages to assess their regulatory function on polarization phenotype. Results: In vivo data showed a protective role of GSRd at 50 mg/kg on Day 3. Serum level of serum creatinine and blood urea nitrogen significantly dropped compared with other groups. Reduced renal tissue damage and M1 macrophage infiltration showed on hematoxylin–eosin staining and flow cytometry and immunofluorescence staining confirmed this improvement. With GSRd administration, in vitro cultured M1 macrophages secreted less inflammatory cytokines such as interleukin-12 and tumor necrosis factor-α. Furthermore, macrophage polarization-related pancake-like morphology gradually changed along with increasing concentration of GSRd in the medium. Conclusion: These findings demonstrate that GSRd possess a protective function against renal ischemia/reperfusion injury via downregulating M1 macrophage polarization

GSGS: A Computational Approach to Reconstruct Signaling Pathway Structures from Gene Sets

Abstract—Reconstruction of signaling pathway structures is essential to decipher complex regulatory relationships in living cells. The existing computational approaches often rely on unrealistic biological assumptions and do not explicitly consider signal transduction mechanisms. Signal transduction events refer to linear cascades of reactions from the cell surface to the nucleus and characterize a signaling pathway. In this paper, we propose a novel approach, Gene Set Gibbs Sampling (GSGS), to reverse engineer signaling pathway structures from gene sets related to the pathways. We hypothesize that signaling pathways are structurally an ensemble of overlapping linear signal transduction events which we encode as Information Flows (IFs). We infer signaling pathway structures from gene sets, referred to as Information Flow Gene Sets (IFGSs), corresponding to these events. Thus, an IFGS only reflects which genes appear in the underlying IF but not their ordering. GSGS offers a Gibbs sampling like procedure to reconstruct the underlying signaling pathway structure by sequentially inferring IFs from the overlapping IFGSs related to the pathway. In the proof-of-concept studies, our approach is shown to outperform the existing state-of-the-art network inference approaches using both continuous and discrete data generated from benchmark networks in the DREAM initiative. We perform a comprehensive sensitivity analysis to assess the robustness of our approach. Finally, we implement GSGS to reconstruct signaling mechanisms in breast cancer cells

Ferroelectric BaTiO3/Pr2O3 heterojunction harvesting room-temperature cold–hot alternation energy for efficiently pyrocatalytic dye decomposition

The strong pyrocatalytic dye decomposition of the BaTiO3/Pr2O3 heterojunction catalyst under cold–hot alternation conditions has been demonstrated in this work. For pure BaTiO3 nanofibers, ~54% rhodamine B (RhB) dye is decomposed under the cold–hot alternation of 29–57 ℃. With the loading content of Pr2O3 increases from 0 to 4 wt%, the pyrocatalytic decomposition ratio of RhB solution increases first and then decreases, eventually achieving a maximum of 91% at 3 wt%. The enhanced pyrocatalytic performance after loading Pr2O3 can be attributed to an internal electric field of the heterojunction, which effectively separates positive and negative charges. The strongly pyrocatalytic performance of BaTiO3/Pr2O3 makes it hopeful for applications in the dye wastewater treatment through harvesting the environmental cold–hot temperature alternation thermal energy in future

Development and validation of a leukocyte‐associated immunoglobulin‐like receptor‐1 prognostic signature for lower‐grade gliomas

Abstract Objective Leukocyte‐associated immunoglobulin‐like receptor‐1 (LAIR‐1), is an immunosuppressive receptor, widely expressed by immune cells, but the part of LAIR‐1 in glioma progression remains unclear. The purpose of this study was to explore the relationship between LAIR‐1 expression and the development of lower‐grade glioma (LGG) using publicly available data sets. Methods We took advantage of The Cancer Genome Atlas (TCGA) to analyze the expression of LAIR‐1 in patients with LGG. Second, Kaplan‐Meier methods and univariate and multivariate Cox regression analyses were used to examine the clinical significance of LAIR‐1 expression in combination with CGGA databases, and then receiver operating characteristic curve analysis was used to verify the prognostic utility of LAIR‐1. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene set enrichment analysis (GSEA) were used to explore the function of LAIR‐1. Analysis of the correlation with immune infiltration was conducted using the ESTIMATE algorithm and single sample gene set enrichment analysis. Results Our results showed that LAIR‐1 expression to be positively correlated with malignant clinicopathologic features of LGG. Univariate analysis and multivariate analysis revealed that overexpression of LAIR‐1 was correlated with a worse prognosis in patients. A nomogram model combining LAIR‐1 was more useful in guiding clinical diagnosis, and functional enrichment analysis showed that malignant development of glioma was closely affiliated with the tumor immune microenvironment. Conclusion These results indicate that LAIR 1 is a latent marker for determining the prognosis of LGG patients. LAIR 1 may also participate a critical part in TIME of LGG by regulating the infiltration of immune cells, suggesting that LAIR 1 might be used as a therapeutic target to regulate the antitumor immune response