Background/Aims: Relevant markers of cancer stem cells (CSCs) may serve as commonly used biomarkers of ovarian cancer (OC). However, their actual clinicopathological and prognostic significance remains inconclusive. Thus, we conducted a meta-analysis to quantitatively evaluate the association between the expression of CSC-relevant markers (ALDH1, CD117, CD133, and CD44) and OC. Methods: We used an odds ratio (OR) and a hazard ratio (HR) with a 95% confidence interval (CI) to estimate the effects by analyzing 52 studies from a literature search. Heterogeneity and sensitivity were evaluated, as well. Publication bias was assessed using funnel plots and Egger tests. Results: ALDH1 expression was statistically associated with FIGO stage (OR=1.872, 95%CI=1.14-3.076, P=0.013) and lymph invasion (OR=2.78, 95%CI=1.08-7.152, P=0.034). CD117 expression was significantly associated with FIGO stage (OR=2.01, 95%CI=1.35-2.98, P=0.001). CD133 expression was correlated with FIGO stage (OR=3.410, 95%CI=2.196-5.294, P< 0.001) and differentiation grade (OR=2.672, 95%CI=1.354-5.272, P=0.005). CD44s was related to chemotherapy resistance (OR=3.218, 95%CI=1.148-9.016, P=0.026). Furthermore, overexpression of ALDH1 (HR=1.494, 95%CI=1.207-1.849, P< 0.001), CD117 (HR=1.395, 95%CI=1.025-1.898, P=0.034) or CD44s (HR=1.725, 95%CI=1.135-2.623, P=0.011) was associated with poor OS. Further, overexpression of both ALDH1 (HR=1.524, 95%CI=1.158-2.007, P=0.003) and CD44s (HR=2.12, 95%CI=1.692-2.657, P< 0.001) was correlated with worse DFS. Conclusion: CSC markers are useful predictive or prognostic biomarkers for OC in clinical assessments. Combined detection of CSC marker expression may be a powerful tool for prognostic predictions in clinical practice for patients with OC.

Background:CD133 has been identified as a putative cancer stem cell marker in colorectal cancer (CRC). However, the clinicopathological and prognostic significance of CD133 in CRC patients remains controversial. Thus, we conducted a meta-analysis to quantitatively evaluate the above issues.Methods:We collected a comprehensive literature search from PubMed, Web of Science, and Embase database up to September 20, 2016 examining CD133 and clinical features of colorectal cancer patients. We used the odds ratio (OR) with 95% confidence interval (CI) to estimate the effects by overall and stratified analysis.Results:The overall result of our meta-analysis indicated that CD133 expression was positively correlated with T category, distant metastasis, lymphatic invasion, and vascular invasion. Moreover, patients with higher CD133 expression had a poorer overall survival (OS) (HR=2.01, P < .001) and a lower 5-year OS rate (OR = 3.26, P < .001) than those with lower expression. Disease-free survival (DFS) and 5-year DFS rate were similar with the above results. Though the correlation between CD133 expression with the clinical characteristic was not positive in some ways when we analyzed the different subgroup. The prognostic value of CD133 expression for 5-year OS rate of CRC patients was noticeable in spite of different patients’ region, multiple antibodies used in studies, various cut-off values of CD133 expression, and adjuvant therapy situation of patients.Conclusion:CD133 is a useful predictive or prognostic biomarker for CRC in clinical assessment and may serve as a potential therapeutic target for CRC.

Background/Aims: CTLA-4 polymorphisms are associated with susceptibility to various cancers, but the results are often conflicting. Hence, we performed a comprehensive meta-analysis to quantitatively investigate the association between CTLA-4 polymorphisms (rs231775, rs4553808，rs5742909, rs3087243 or rs733618) and cancer risk. Methods: Data were collected from PubMed and Web of Science. A total of 67 case-control studies were selected for quantitative analysis. Stata (Version 12) software was used to calculate the odds ratio (OR) and 95% confidence interval (CI) to evaluate the strength of the associations. Subgroup meta-analysis was conducted based on ethnicity and cancer type. Heterogeneity tests, sensitivity analysis, and publication bias assessments were also performed. Results: rs231775, rs4553808 and rs5742909 but not rs3087243 and rs733618 were significantly related to cancer risk. In analyses stratified by ethnicity, both rs231775 and rs4553808 were significant susceptibility polymorphisms in an Asian population but not in a Caucasian population. Moreover, there were stronger associations between the rs231775 polymorphism and increased risk of bone, breast, liver, head and neck and pancreatic cancers. Additionally, rs4553808 was associated with significantly increased susceptibility to breast cancer and head and neck cancer. Conclusion: rs231775, rs4553808 and rs5742909 may be used as predictive genetic biomarkers for cancer predisposition. Combined detection of CTLA-4 SNPs could be a useful tool for prediction of cancer susceptibility in clinical practice.

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Shallow water depth measurements using multispectral images are crucial for marine surveying and mapping. At present, relevant studies either depend on the use of other auxiliary data (such as field water depths or water column data) or contain too many unknown variables, thus making these studies suitable only for images that contain enough visible wavebands. To solve this problem, a Quasi-Analytical Algorithm (QAA) approach is proposed in this paper for estimating the water depths around Weizhou Island by developing a QAA to estimate the diffuse attenuation coefficients and simplifying the parameterization of the bathymetric model. The approach contains an initialization sub-approach and a novel global adjustment sub-approach. It is not only independent of other auxiliary data but also greatly reduces the number of unknowns. Experimental results finally demonstrated that the Root Mean Square Errors (RMSEs) were 1.01 m and 0.77 m for the ZY-3 image and the WorldView-3 (WV-3) image, respectively, so the approach is competitive to other QAA bathymetric methods. Besides, the global adjustment sub-approach was also seen to be superior to common smoothing filters: if the Signal-to-Noise Ratio (SNR) is as low as 42, i.e., ZY-3, it can smooth the water depths and improve the accuracies, otherwise can avoid the over-smoothing of water depths.

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Registration of large-scale optical images with airborne LiDAR data is the basis of the integration of photogrammetry and LiDAR. However, geometric misalignments still exist between some aerial optical images and airborne LiDAR point clouds. To eliminate such misalignments, we extended a method for registering close-range optical images with terrestrial LiDAR data to a variety of large-scale aerial optical images and airborne LiDAR data. The fundamental principle is to minimize the distances from the photogrammetric matching points to the terrestrial LiDAR data surface. Except for the satisfactory efficiency of about 79 s per 6732 × 8984 image, the experimental results also show that the unit weighted root mean square (RMS) of the image points is able to reach a sub-pixel level (0.45 to 0.62 pixel), and the actual horizontal and vertical accuracy can be greatly improved to a high level of 1/4–1/2 (0.17–0.27 m) and 1/8–1/4 (0.10–0.15 m) of the average LiDAR point distance respectively. Finally, the method is proved to be more accurate, feasible, efficient, and practical in variety of large-scale aerial optical image and LiDAR data.