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Dacryocystitis diagnosis is important for preventing rapid blurring and vision loss. Existing state-of-the-art methods focus on routine clinical examinations and objective scattering index-based statistical analysis. Such approaches are invasive operations or lack quantitative indicators, and their application is limited. in addition, little attention has been paid to the explainability and clinical utility of models. This paper proposes an explainable dacryocystitis prediction model from noninvasive ocular indicators. The proposed model is based on an deep stacked network with 4 improvements: a multivariable feature extraction module, obtaining comprehensive predictive factors including the quantitative ocular indictors, conventional texture features, and deep learning features from shallow to deep convolutional layers; a multifeature fusion and attribute selection module based on the ReliefF method, guiding the network to focus on useful information at variables; Decision curve analysis the model is introduced into the model to evaluates the risks and benefits; and appending a SHapley Additive exPlanations (SHAP) module to the framework to automatically and efficiently interpret the prediction of the models. By integrating the above improvements in series, the models' performances are gradually enhanced. Real labeled data samples are used to train and test the model, and our model achieves high accuracy and reliability.

Background The KiSS1 gene is considered a tumor suppressor in various cancers. MicroRNAs are involved in many important life processes, and their regulation of gene expression may be as important as that of transcription factors. Here, we explore the roles of miR-124-3p and miR-378-3p in colorectal cancer and their relationships with the KiSS1 gene. Methods The effects of miR-124-3p and miR-378-3p on KiSS1 protein expression were observed by transfecting colorectal cancer cells (SW-480) with miR-124-3p and miR-378-3p mimics and inhibitors. Moreover, cell proliferation, migration and invasion were evaluated by ethynyl-20-deoxyuridine and Transwell experiments. Results The KiSS1 mRNA and protein expression levels were significantly increased in mimic-transfected cells compared with those in untransfected cells, and the proliferation, migration and invasion abilities of the former were decreased; in addition, opposing results were obtained in the inhibitor and mimic groups. Conclusions In conclusion, our studies indicate that miR-124-3p and miR-378-3p upregulate the expression of KiSS1 and are associated with colorectal cancer metastasis and progression. miR-124-3p, miR-378-3p and KiSS1 may play important roles in colorectal cancer.

Backgroud: Tumour recurrence and metastasis lead to poor prognosis incolon cancer(COAD). Therefore We aimed to identify a lncRNA signature through an integrative analysis of copy number variation, mutation and transcriptome data to predict prognosis and explore its internal mechanism.Methods: The lncRNA expression profile were collected fromThe Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). TCGA data was randomly divided 3:1 intotraining andtesting cohort. In the training, weperformed integrated analyses of three candidate lncRNA sets that correlated with prognosis, copy number variations and mutations to establish a signature through Cox regression analysis. The robustness was determined in the testing and GEO.Results: An 11-lncRNA signature that was significantly associated with prognosiswas constructed in the training (PP=0.0019, HR=3.374) and GSE17536(P=0.0076, HR=1.864). The signature is significantly related to MSI status and clinical prognostic factors. The prognostic-relatedrisk scores were significantly excellent than the other five models have been reported. Furthermore, GSEA suggested that the signature was involved in COAD development and metastasis-related pathways.Conclusions: We identifiedansignature has strong robustness and can stably predict the prognosis of COAD in different platformsand may be implicated in COAD pathogenesis and metastasis and applied clinically as a prognostic marker.

Colorectal cancer (CRC) has become the second most common digestive tract tumor. Even though the means to treat colon cancer have improved, patients prognosis is low due to the lack of accurate molecular targets. Hence, it urgently demanded better biomarkers for prognosis and progression of colon cancer. This study explores the hub gene associated with the prognosis of colorectal cancer and further analyzes the hub gene function. In this study, all genes mRNA expression data were from the cancer genome atlas (TCGA) colon cancer database and the Gene Expression Omnibus (GEO). These databases were used to screen the differentially expressed co-genes between colon cancer tissue and normal tissue. Weighted Gene Co-expression Network Analysis screened out a total of 103 differential co-expression genes (WGCNA). According to the R cluster profile package annotation analysis, these genes biological functions mainly concentrate on energy metabolism. Moreover, in the protein-protein interaction (PPI) network, the CytoHubba plugin of Cytoscape was used to screen out ten genes (CLCA1, ZG16, GUCA2B, GUCA2A, CLCA4, SLC26A3, MS4A12, GCG, SI, and NR1H4). According to the survival analysis results, high expression of CLCA1has better overall survival and disease-free survival in patients with CRC. Simultaneously, the mRNA expression of CLCA1 in normal tissues was higher than that in CRC tissues. Besides, there were significant differences in the expression of CLCA1 in pathological stage, T stage, and M stage. By using a gene set enrichment analysis, we found several considerable enrichment pathways in the high-groups. CIBERSORT analysis for the proportion of TICs revealed that B-cell naive, dendritic cells, plasma cells, and CD4+ T cells were positively correlated with CLCA1 expression, suggesting that CLCA1 might be responsible for the preservation of immune-dominant status for TME. Finally, in the Human Protein Atlas (HPA) database, the protein level of CLCA1 in the colorectal cancer samples decreased, consistent with the down-regulation of the mRNA expression level CLCA1. To sum up, by integrating WGCNA with differential gene expression analysis, this research generated a significant survival correlative gene called CLCA1 that can predict prognosis prediction in colon cancer.

The prognostic value of the genotype of the PRSS1 gene in patients with pancreatic ductal adenocarcinoma (PDAC) remains poorly understood. The aim of the present study was to evaluate the association between the PRSS1 genotype and clinicopathological characteristics of patients with PDAC, as well as to explore the prognostic significance of the PRSS1 genotype in patients with PDAC. A total of 124 patients with PDAC patients were included in the current study and the PRSS1 genotype of the enrolled patients was determined by the polymerase chain reaction. Associations between the PRSS1 genotype and clinicopathological characteristics were subsequently analyzed using the Chi-square test. The impact of the PRSS1 genotype on patient prognosis was assessed using the Kaplan-Meier method, and predictive factors of overall survival (OS) time were analyzed by Cox regression. A total of 56 patients with PDAC (45.16%) had the T/C PRSS1 genotype, which was associated with large tumor sizes (P=0.027) and higher tumor node metastasis (TNM) stages (P=0.041). Following a median follow-up of 19 months, the T/C genotype of PRSS1 genotype was associated with a shorter OS time (P=0.037) compared with the C/C or T/T PRSS1 genotypes. Univariate and multivariate analyses revealed that PRSS1 genotype was identified to be an independent prognostic factor for the OS time of patients with PDAC. The results obtained in the current study suggested that the PRSS1 genotype, as well as factors such as the serum level of carbohydrate antigen 19-9 and the TNM stage, may act as independent prognostic factors for the OS time of patients with PDAC.

51 Background: Gastric cancer (GC) is a highly heterogeneous disease. Cell-free DNA (cfDNA) has been a research hotspot in molecular tumor profiling. In advanced GC patients, malignant pleural effusion (MPE) and ascites provide a wealth of tumor cells that can be investigated. The aim of this study is to investigate fusion landscape in advanced GC. Methods: A multicenter study in China was initiated from Aug. 2016, and GC patients have been enrolled as of Aug. 2018. To determine the fusion frequency in GC, we analyzed data from 371clinical GC cases, each of which had results from next-generation sequencing (NGS)-based 381 genes panel assay, analogous to the index patient. Results: Of this entire cohort, 61 patients (16.44%) were identified with fusions, including TMEM45B-FGF3 (3), AXIN1-SMPD3 (3), B3GNTL1-ERBB2 (2), ERBB2-LAMA3 (2), ERBB2-ACLY (2), TRIM24-BRAF (2), ARHGEF1-CD79A (2), FGFR4-UIMC1 (2), MSH2-TTC7A (2), SMARCA4-LDLR (2), GON4L-RIT1 (2), AKT1-CPSF2 (2), GATA6-COLEC12 (2), RICTOR-EFNA5 (2), KAT6A-PLAT (2), ROCK1-CCDC178 (2), HBS1L-MYB (2), SLC30A2-ARID1A (2), MSI2-BIRC5 (2), NOTCH3-UCA1 (2), PIK3C2B-KISS1 (2), RICTOR-OSMR (2), FGFR2-MIR5694 (2), FGFR2-FGFR1 (2), MAN2A2-BLM (2), EGFR-MED15 (1), EML4-ALK(1), GOPC-ROS1 (1), FXR2-TP53 (1), NF1-PSMD11 (1), IRS2-PRKCI (1), FGFR2-KIAA1217(1), FGFR2-TACC2 (1), FGFR3-TACC3 (1). ERBB2, BRAF, EGFR, ALK and ROS1 fusionswere seen in 18.03% (11/61) of advanced Chinese gastric cancer fusion landscape patients. Conclusions: Advanced Chinese gastric cancer fusion landscape is rich, ERBB2, BRAF, EGFR, ALK and ROS1 fusions are rare but potentially druggable in TKIs. Detection of ERBB2, BRAF, EGFR, ALK and ROS1 fusions should be part of comprehensive profiling panels to determine TKIs and direct appropriate combination therapeutic strategies.

Objective To investigate the clinical features, pathological characteristics and immunophenotype of solid-pseudopapillary tumor of the pancreas(SPTP). Methods Nine surgically treated cases of SPTP were retrospectively reviewed. Hematoxylin and Eosin(HE) staining and immunohistochemical staining were used to analyze all cases, and the general clinical data was collected. Results Six patients were asymptomatic except for a palpable mass. Two patients complained of vague-epigastric pain. One patient appeared jaundice. The tumor was encapsulated and solid tissues alternately with cystic tissues. Histologically, the histological structure of solid portion was pseudopapillary with a fibrovascular core. Tumor cells were uniform and medium-sized which were arranged in sheets ets or nests or pseudopapillary patterns. Immunohistochemical studies demonstrated that SPTP proved positive in vimentin(9/9 cases), AAT(9/9 cases), NSE(9/9 cases), ACT(7/9 cases), CK20(2/9 cases), CgA(1/9 cases), S-100(3/9cases), PR(4/9cases), Syn(3/9 cases) and CD56(5/9cases), negative in CEA and ER. Conclusion SPTP is a tumor predominantly occurring in young women frequently without special symptoms. This tumor has various characteristical histological patterns with different immunophenotype.

According to the needs of emergency thematic cartography and the China's existing ‘Specification for the military symbols’, the types of situation symbols that may be used in emergency thematic cartography were summed up in this paper. A comprehensive modeling was raised for these situation symbols and it is flexible for emergency thematic cartography. There are four kinds of situation symbols: contour symbol, simple arrow symbols, single arrow symbols and combined arrow symbols in this paper. The position line of the symbols is a Bezier curve or a polyline. The oblique axis parabolic algorithm and the Hermite interpolation algorithm are selected for smoothing the position lines of the symbols. The Douglas-Peucker algorithm is picked out for scattering the position curve. At last, this paper developed a cartographic system based on the national fundamental geographic information, and realized the modeling and drawing of the situation symbols with the cartographic system.

The traditional methods for model absolute orientation of aerial imagery are mainly based on some ground control points whose three-dimensional co-ordinates are available and use highly accurate positioning algorithms or semi-automatically manual arrangement to locate them on the image plain. Usually, it is difficult to find some control point features in 3D-vector map using model absolute orientation of aerial imagery. However, the existed 3D vector map can provide sufficient details both on the maps and the images to ensure a lot of well-distributed and unchanged linear features can be used for absolute orientation of aerial imagery. In order to meet the requirements of quickly updating 3D-vector map, this paper will discuss a method for semi-automatic model absolute orientation by extracting some liner features from image and then matching with 3D line object in vector map. It can resolve the problem of model absolute orientation instead of using ground control points for quickly updating 3D vector map.