The fisheye camera has a field of view (FOV) of over 180°, which has advantages in the fields of medicine and precision measurement. Ordinary pinhole models have difficulty in fitting the severe barrel distortion of the fisheye camera. Therefore, it is necessary to apply a nonlinear geometric model to model this distortion in measurement applications, while the process is computationally complex. To solve the problem, this paper proposes a model-free stereo calibration method for binocular fisheye camera based on neural-network. The neural-network can implicitly describe the nonlinear mapping relationship between image and spatial coordinates in the scene. We use a feature extraction method based on three-step phase-shift method. Compared with the conventional stereo calibration of fisheye cameras, our method does not require image correction and matching. The spatial coordinates of the points in the common field of view of binocular fisheye camera can all be calculated by the generalized fitting capability of the neural-network. Our method preserves the advantage of the broad field of view of the fisheye camera. The experimental results show that our method is more suitable for fisheye cameras with significant distortion.

BACKGROUND: Hepatocellular carcinoma (HCC) is a highly heterogeneous disease, which makes prognostic prediction challenging.We aimed to investigate association of TNFRSF4 expression with the immune infiltration and gene mutation in HCC. METHODS: In this study, the expression profiles and corresponding clinical data of HCC patients were downloaded from the Cancer Genome Atlas (TCGA) database. Kaplan-Meier and Cox regression were used to evaluate the clinical value of TNFRSF4. ESTIMATE and CIBERSORT algorithms were applied to investigate the infiltration ratio of 22 immune cells. The WGCNA and LASSO COX algorithms were performed, establishing a prognostic risk model that was then validated by HCC samples from GEO. Finally, the effects on gene mutation occurring in HCC patients of TNFRSF4 expression and risk score were appraised. RESULTS: In HCC tissues, it was found the TNFRSF4 expression profile was significantly different with age, gender, tumor grade, disease stage, prominently affecting the survival outcome and prognosis of patients. Univariate and multivariate COX regression analysis suggested that TNFRSF4 was an independent prognostic marker. Samples of high/low expression of TNFRSF4 were screened for differential genes, and then the WGCNA and LASSO COX constructed a 13-gene signature, excellently dividing samples into hign/low risk groups. Compared with the low-risk group, the overall survival (OS) of high-risk group was markedly lower, with P< 0.0001. By ROC curve analysis, the predictive ability of the 13-gene signature was further confirmed. Both the high/low TNFRSF4 expression and the high/low risk score were demonstrated to exert effects on the frequency of gene mutation in HCC. CONCLUSIONS: As an independent prognostic marker of HCC, TNFRSF4 was found simultaneously to affect the immune infiltration of cells and the frequency of gene mutations.

PurposeFatty acid metabolism plays key role in cancer development, and free fatty acid receptors (FFARs) are involved in many cancers. However, the correlation between serum free fatty acids (FFAs)/FFARs levels and ovarian cancer (OC) prognosis remains largely unclear.MethodsA retrospective review of 534 primary OC patients and 1049 women with benign ovarian tumors was performed. Serum FFA levels data were extracted from the electronic medical record system. Repeated FFA results of 101 OC patients treated with standard chemotherapy were collected. The effects of FFAs on cells migration were evaluated in OC cell lines by Transwell assay. Gene Expression Profiling Interactive Analysis (GEPIA) was used to compare FFAR mRNA expression levels in cancer and noncancer tissues. Kaplan-Meier (KM) plotter was employed to analyze their prognostic values. SPSS 23.0 and Graphpad prism 7.0 software was used for analysis and graph construction.ResultsFFA levels in the serum of epithelial ovarian cancer (EOC) women were higher than in women with benign ovarian tumors independent of pathology, tumor stage,and grade. FFA levels decreased gradually after chemotherapy. FFAs enhanced the migration of OVCAR3 cells. FFAR1 mRNA expression was lower in OC cells than in control cells. FFAR3 was related to a better prognosis, and FFAR4 was related to poor prognosis in TP-53wild-type and mutated type OC, while FFAR1 and FFAR2 were related to a better prognosis in TP53 wild-type OC but FFAR2 was related to a poor prognosis in TP53-mutant OC.ConclusionThe FFA levels are increased in OC and decreased with chemotherapy. High expression of FFARs was related to the prognosis of OC. The prognostic value of different FFARs differs depending on whether it is a TP53 wild or TP53 mutant ovarian cancer.Targeting FFARs may be an attractive treatment strategy for EOC.

Although human epidermal growth factor receptor 2 (HER2)-targeted therapy significantly improves the prognosis of patients with HER2-positive breast cancer, most patients with advanced breast cancer eventually progress due to drug resistance. At present, there is no standard treatment after patients become resistant to HER2-targeted therapy. Previous studies have indicated that anti-angiogenesis drugs have potential efficacy in the treatment of advanced breast cancer. The present study reported on a case of a pretreated patient with HER2-positive advanced breast cancer with brain metastases who developed resistance to multiple lines of HER2-targeted treatment. The patient was treated with apatinib combined with trastuzumab and albumin-bound paclitaxel. The patient achieved partial response to the third-line treatment with a progression-free survival of 9 months. After combination treatment, the symptoms of headache and vomiting were relieved and all the brain metastases were significantly reduced. The present case indicated that apatinib may have anti-tumor activity in patients with HER2-positive breast cancer with HER2-targeted drug resistance. The present case provides valuable information and may offer a new possibility for the treatment of patients with breast cancer with brain metastases who progressed after clinical treatment with small-molecule anti-HER2 tyrosine kinase inhibitor drugs.

The compound eye system has many unique advantages, enabling organisms to quickly and accurately obtain the three-dimensional spatial information of the target. Therefore, its bionic applications have great potential in object localization, dynamic tracking, and 3D reconstruction. However, the current bionic compound eye systems still have great difficulties in target detection. Most of the bionic compound eye systems only verify the possibility of three-dimensional (3D) detection, and there is no suitable calibration and detection scheme. In this article, a fiber-optic stereo bionic compound eye is designed, and a simple and rapid calibration method suitable for this system is selected by comparing two effective optical information. Further, the system quantitatively analyzes the detection performance of the target to achieve precise positioning and dynamic trajectory tracking. In the static detection experiment, the average detection errors of the 3D position at the horizontal angle, the elevation angle and the depth are 0.33 • , 0.32 • and 1.84 mm, respectively. In the dynamic trajectory tracking experiment, the circle radius errors in the X-Z plane and Y-Z plane are 0.04 and 2.20 mm, respectively. The proposed system provides a new perspective to understand the nature of the compound eye. K E Y W O R D Sbionic compound eyes 1 , dynamic track tracking 4 , neural network 5 , stereo vision system 2 , three-dimensional detection 3 INTRODUCTIONAs a natural multi-aperture optical system, due to its special physiological structure, 1,2 the compound eyes have the characteristics of small size, high integration, large field of view, 3 high resolution rate, and sensitivity to moving objects. 4 So, it has great advantages in three-dimensional (3D) target detection. The bionic compound eyes are mainly divided into planar compound eye 5-13 and curved compound eye. [14][15][16][17][18][19][20][21] The planar compound eye is small in size and has a fast response, but is limited by the range of the field of view (FOV). The curved compound eye is the closest to the biological compound eye in terms of structure and performance, and it is also the main design idea at present. However, it is difficult to acquire accurate and distortion-free optical images in a large field of view. The nature is very mysterious, the computation principle [22][23][24][25][26][27] of the compound eye is an interesting topic.Research on object detection from existing bionic compound eye shows that such a vision system has the potential for at least qualitative object detection. Richard Hornsey's team proposed a DragonflEye system based on fiber bundle coupling, and realized the tracking of planar target through vanishing point and Z-translation image center calibration techniques. 18,19 The method has a complex structure and is difficult to manufacture, though it does not require calibration of a single sub-eye and has high detection accuracy. Song et al. explored the possibility of orientation and dis-