Analysis on the Live Coral Cover around Weizhou Island Using MODIS Data.

Coral reefs are important as they can help to maintain ecological balance, biological resources, and species diversity on earth. However, they are globally threatened by human activities and climate change. As live coral cover (LCC) is regarded as an important measure of the health of coral reefs, analysis on LCC change associated with environmental parameters, such as chlorophyll-a concentration (Chl-a), sea surface temperature (SST), and photosynthetically active radiation (PAR), is of great value. Research on this front would help us comprehend the changes in coral reefs induced by human activities and global changes. Instead of using spasmodically in-field-measured environmental parameters, in this study, we chose to combine the successive Chl-a, SST, and PAR products of the Moderate Resolution Imaging Spectroradiometer (MODIS) with historic LCC records to establish an empirical relationship using nonlinear optimization. Thereafter, the established relationship was further used to discuss some possible developments of LCCs. According to the experiments, we concluded that the degradation of the LCC around Weizhou Island may be mainly caused by human-activity-caused eutrophication. Besides, we also showed that even if the Chl-a and the PAR can keep constant with current average levels, the corals around Weizhou Island may still be in a risk of disappearing between 2120-2140 as the SST continues to rise.

Association of Five Snps in Cytotoxic T-Lymphocyte Antigen 4 and Cancer Susceptibility: Evidence from 67 Studies.

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.

Clinicopathological and Prognostic Significance of Cancer Stem Cell Markers in Ovarian Cancer Patients: Evidence from 52 Studies.

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.

Method to design a live coral cover sensitive index for multispectral satellite images.

Live coral cover (LCC) is regarded as the most efficient indicator of coral reef health. However, LCCs are usually sampled with standardized transect or photo quadrat techniques in field, which are incomplete and labour-intensive. To overcome such difficulties, we study a model to transfer the pixels of multispectral satellite images to quantitative LCCs. The idea is to extend band ratio-based (BR) indices to a novel index constructed using the ratio of different linear combinations (RDLC) of band reflectance and water depths. On the basis of field surveyed LCCs, an empirical process is further proposed to solve the unknown parameters of this RDLC. This approach provides new thinking for designing LCC-sensitive indices for given multispectral satellite images. The experimental results on Weizhou Island and Palmyra Atoll demonstrate that the method is effective and feasible, where the mean relative errors (MREs) are improved from 45 to 56% for BRs to 23-29% for RDLCs for Weizhou Island.

Registration of Aerial Optical Images with LiDAR Data Using the Closest Point Principle and Collinearity Equations.

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.

Cross-scale cost aggregation integrating intrascale smoothness constraint with weighted least squares in stereo matching.

Cross-scale cost aggregation (CSCA) allows pixel-wise multiscale interaction in the aggregated cost computation. This kind of multiscale constraint strengthens the consistency of interscale cost volume and behaves well in a textureless region, compared with single-scale cost aggregation. However, the relationship between neighbors' cost is ignored. Based on the prior knowledge that costs should vary smoothly, except at object boundaries, the smoothness constraint on cost in a neighborhood system is integrated into the CSCA model with weighted least squares for reliable matching in this paper. Our improved algorithm not only has the advantage of CSCA in computational efficiency, but also performs better than CSCA, especially on the KITTI data sets. Experimental evidence demonstrates that the proposed algorithm outperforms CSCA in textureless and discontinuous regions. Quantitative evaluations demonstrate the effectiveness and efficiency of the proposed method for improving disparity estimation accuracy.

Spatio-temporal distribution of sea surface chlorophyll-a in coral reefs of the South China Sea over the past decade based on Landsat-8 Operational Land Images.

The concentration of chlorophyll-a (Chl-a) in seawater reflects phytoplankton growth and water eutrophication, which are usually assessed for evaluation of primary productivity and carbon source/sink of coral reefs. However, the precise delineation of Chl-a concentration in coral reefs remains a challenge when ocean satellites with low spatial resolution are utilized. In this study, a remote sensing inversion model for Chl-a was developed in fringing reefs (R2 = 0.76, RMSE =0.41 µg/L, MRE = 14 %) and atolls (R2 = 0.79, RMSE =0.02 µg/L, MRE = 8 %), utilizing reflectance data from the sensitive band of the Landsat-8 Operational Land Imagers (OLI) with a spatial resolution of 30 m. The aforementioned model was utilized to invert high-resolution distribution maps of Chl-a concentration in six major coral reef regions of the South China Sea from 2013 to 2022 and subsequently used to analyze the variations in Chl-a concentration and its influencing factors. The results indicate a Chl-a concentration gradient among coral reefs Daya Bay, Weizhou Island, Luhuitou, Xuwen, Huangyan Island, and Xisha Island in that order. The Chl-a concentration in coral reefs exhibited an overall increasing trend, with significant seasonal fluctuations, characterized by higher concentrations during winter and spring and lower concentrations during summer and autumn. The concentration of Chl-a in coral reefs was positively correlated with the average wind speed.

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Given its high root regeneration ability and adaptation capacity, Spartina alterniflora would predominate the resource competition with other plant species. As an invasive alien species, it has caused serious damages to the coastal ecosystem of China. We explored the impacts of S. alterniflora invasion on the growth and expansion of mangroves around the coastal zones around Guangxi Shankou Mangrove National Nature Reserve (GSMNNR). The area of S. alterniflora and mangroves in the GSMNNR was analyzed based on a sequence of Landsat satellite multispectral images collected during 1995 to 2019. The results showed that S. alterniflora predominated in the competition with mangroves without human intervention. The area of S. alterniflora decreased under the conditions of cutting, rooting and other management measures, while the average annual growth rate of mangrove area correspondingly increased. It indicated that the invasion of S. alterniflora would inhibit the growth and expansion of mangroves. The S. alterniflora management measures, such as mowing and rooting, could weaken the negative impacts of S. alterniflora on mangroves. Mangroves could thus be effectively protected. This study could provide quantitative scientific data for S. alterniflora management and the protection of the mangrove ecosystem in the GSMNNR, and thus be a valuable reference to the prevention on a larger scale of S. alterniflora and the formulation of further protective measures for mangroves.

CD133 expression correlates with clinicopathologic features and poor prognosis of colorectal cancer patients: An updated meta-analysis of 37 studies.

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.