[Clinicopathological characteristics of the CD8+ T lymphocytes infiltration and its mechanism in distinct molecular subtype of medulloblastoma].

OBJECTIVE: To investigate the characteristics of the CD8+ T cells infiltration from the 4 subtypes in medulloblastoma (MB), to analyze the relationship between CD8+ T cells infiltration and prognosis, to study the function of C-X-C motif chemokine ligand 11 (CXCL11) and its receptor in CD8+ T cells infiltration into tumors and to explore the potential mechanism, and to provide the necessary clinicopathological basis for exploring the immunotherapy of MB. METHODS: In the study, 48 clinical MB samples (12 cases in each of 4 subtypes) were selected from the multiple medical center from 2012 to 2019. The transcriptomics analysis for the tumor of 48 clinical samples was conducted on the NanoString PanCancer IO360TM Panel (NanoString Technologies). Immunohistochemistry (IHC) staining of formalin-fixed, paraffin-embedded sections from MB was carried out using CD8 primary antibody to analyze diffe-rential quantities of CD8+ T cells in the MB four subtypes. Through bioinformatics analysis, the relationship between CD8+T cells infiltration and prognosis of the patients and the expression differences of various chemokines in the different subtypes of MB were investigated. The expression of CXCR3 receptor on the surface of CD8+T cells in MB was verified by double immunofluorescence staining, and the underlying molecular mechanism of CD8+T cells infiltration into the tumor was explored. RESULTS: The characteristic index of CD8+T cells in the WNT subtype of MB was relatively high, suggesting that the number of CD8+T cells in the WNT subtype was significantly higher than that in the other three subtypes, which was confirmed by CD8 immunohistochemical staining and Gene Expression Omnibus (GEO) database analysis by using R2 online data analysis platform. And the increase of CD8+T cells infiltration was positively correlated with the patient survival. The expression level of CXCL11 in the WNT subtype MB was significantly higher than that of the other three subtypes. Immunofluorescence staining showed the presence of CXCL11 receptor, CXCR3, on the surface of CD8+T cells, suggesting that the CD8+T cells might be attracted to the MB microenvironment by CXCL11 through CXCR3. CONCLUSION: The CD8+T cells infiltrate more in the WNT subtype MB than other subtypes. The mechanism may be related to the activation of CXCL11-CXCR3 chemokine system, and the patients with more infiltration of CD8+T cells in tumor have better prognosis. This finding may provide the necessary clinicopathological basis for the regulatory mechanism of CD8+T cells infiltration in MB, and give a new potential therapeutic target for the future immunotherapy of MB.

Primary gliosarcoma with widespread extracranial metastases-spatiotemporal morphological variation.

BACKGROUND: We summarize 5 cases of primary gliosarcoma with widespread extracranial metastases including our case. The glial components are eliminated due to the needs of the living environment in the process of parasitism and survival of brain glioma-sarcoma cells in lung metastasis. METHODS: A PubMed search using the keywords "gliosarcoma" and "extracranial metastases" was performed followed by a review of cited literature. Our case was a 50-year-old female presented with headache and dizziness. MRI examination showed that there was a cystic solid tumor in the right temporal lobe. The tumor was removed totally. Seven months after the operation, the patient suffered recurrent intermittent headache. The resection for the recurrent tumor was performed. Postoperative pathology confirmed the recurrent gliosarcoma. A needle biopsy was performed for the nodular on the right lung. The lung tumor pathology suggested a sarcoma structure. RESULTS: There was a female patient in five cases. The age range is 47 to 69 years old. The tumor recurred within a year. A combination of treatment modalities may extend survival; however, the prognosis remains poor. CONCLUSION: Primary gliosarcoma with extracranial metastases is extremely rare. Some findings uncovered an unexpected spatiotemporal morphological variation in the different foci of the same malignancy.

A Defect Detection Method for Rail Surface and Fasteners Based on Deep Convolutional Neural Network.

As a result of long-term pressure from train operations and direct exposure to the natural environment, rails, fasteners, and other components of railway track lines inevitably produce defects, which have a direct impact on the safety of train operations. In this study, a multiobject detection method based on deep convolutional neural network that can achieve nondestructive detection of rail surface and fastener defects is proposed. First, rails and fasteners on the railway track image are localized by the improved YOLOv5 framework. Then, the defect detection model based on Mask R-CNN is utilized to detect the surface defects of the rail and segment the defect area. Finally, the model based on ResNet framework is used to classify the state of the fasteners. To verify the robustness and effectiveness of our proposed method, we conduct experimental tests using the ballast and ballastless railway track images collected from Shijiazhuang-Taiyuan high-speed railway line. Through a variety of evaluation indexes to compare with other methods using deep learning algorithms, experimental results show that our method outperforms others in all stages and enables effective detection of rail surface and fasteners.

Research on track fastener positioning method based on local unidirectional template matching.

Commonly used fastener positioning methods include pixel statistics (PS) method and template matching (TM) method. For the PS method, it is difficult to judge the image segmentation threshold due to the complex background of the track. For the TM method, the search in both directions of the global is easily affected by complex background, as a result, the locating accuracy of fasteners is low. To solve the above problems, this paper combines the PS method with the TM method and proposes a new fastener positioning method called local unidirectional template matching (LUTM). First, the rail positioning is achieved by the PS method based on the gray-scale vertical projection. Then, based on the prior knowledge, the image of the rail and the surrounding area of the rail is obtained which is referred to as the 1-shaped rail image; then, the 1-shaped rail image and the produced offline symmetrical fastener template is pre-processed. Finally, the symmetrical fastener template image is searched from top to bottom along the rail and the correlation is calculated to realize the fastener positioning. Experiments have proved that the method in this paper can effectively realize the accurate locating of the fastener for ballastless track and ballasted track at the same time.

AFI-Net: Attention-Guided Feature Integration Network for RGBD Saliency Detection.

This article proposes an innovative RGBD saliency model, that is, attention-guided feature integration network, which can extract and fuse features and perform saliency inference. Specifically, the model first extracts multimodal and level deep features. Then, a series of attention modules are deployed to the multilevel RGB and depth features, yielding enhanced deep features. Next, the enhanced multimodal deep features are hierarchically fused. Lastly, the RGB and depth boundary features, that is, low-level spatial details, are added to the integrated feature to perform saliency inference. The key points of the AFI-Net are the attention-guided feature enhancement and the boundary-aware saliency inference, where the attention module indicates salient objects coarsely, and the boundary information is used to equip the deep feature with more spatial details. Therefore, salient objects are well characterized, that is, well highlighted. The comprehensive experiments on five challenging public RGBD datasets clearly exhibit the superiority and effectiveness of the proposed AFI-Net.

Numerical and Experimental Research on Identifying a Delamination in Ballastless Slab Track.

This paper aims to adopt the total focusing method (TFM) and wavenumber method for characterizing a delamination in ballastless slab track. Twelve dry point contact (DPC) transducers located at the upper surface of the slab track compose a linear array. These transducers are employed to actuate shear waves, which are suitable for identifying the delamination. The technique of removing the surface wave has been implemented for only retaining the scattered wave caused by the delamination and the reflected wave from the bottom of bed plate. Numerical and experimental results demonstrate that the delamination and bottom of the bed plate can be identified by the proposed methods. Furthermore, the near-surface pseudomorphism is distinctly restrained after removing the surface wave. Compared to TFM, the wavenumber method has the great advantages of improving computational performance and lateral resolution. However, they have no significant difference in the longitudinal resolution. Furthermore, it has been confirmed that the lateral resolution can be affected by the amount of transducers. This paper can provide valuable suggestions on improving the computational performance and the imaging accuracy when we identify a delamination in ballastless slab track.