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Global warming and sea-level rise (SLR) induced by rising atmospheric CO2 concentrations can cause coral bleaching, death, and submergence of the world’s coral reefs. Adopting the GIS and RS methods, we modeled how these two stressors combine to influence the future growth of the atolls and table reefs of three archipelagoes in the South China Sea (SCS), based on geomorphic and ecological zones. A large-scale survey of the coral communities in Xisha Islands in 2014, Dongsha Islands in 2014–2016 and Nansha Islands in 2007 provided zone-specific process datasets on the range of reef accretion rates. Sea surface temperature and extreme (minimum and maximum) SLR data above 1985–2005 levels by 2100 in the SCS were derived from the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) models forced with the Representative Concentration Pathways (RCPs). Our model projected that: (1) the Xisha Islands and Dongsha Islands may have a better growth status, because the reef flat biotic sparse zone may be recolonized with hard coral and become a biotic dense zone; (2) the southern Nansha Islands reefs have a risk of stopping growing due to their earlier annual bleaching years. The increasing of water depths of these reefs is stronger in the RCP with more emissions. Our approach offers insights into the best-case and worst-case impacts of two global environmental pressures on potential future reef growth under a changing climate.

Active remote sensing technology represented by multi-beam and lidar provides an important approach for the effective acquisition of underwater coral reef geomorphological information. A spatially continuous surface model of coral reef geomorphology reconstructed from active remote sensing datasets can provide important geomorphological parameters for the research of coral reef geomorphological and ecological changes. However, the surface modeling methods commonly used in previous studies, such as ordinary kriging (OK) and natural neighborhood (NN), often represent a “smoothing effect”, which causes the strong spatial variability of coral reefs to be imprecisely reflected by the reconstructed surfaces, thus affecting the accurate calculation of subsequent geomorphological parameters. In this study, a spatial variability modified OK (OK-SVM) method is proposed to reduce the impact of the “smoothing effect” on the high-precision reconstruction of the complex geomorphology of coral reefs. The OK-SVM adopts a collaborative strategy of global parameter transformation, local residual correction, and extremum correction to modify the spatial variability of the reconstructed model, while maintaining high local accuracy. The experimental results show that the OK-SVM has strong robustness to spatial variability modification. This method was applied to the geomorphological reconstruction of the northern area of a coral atoll in the Nansha Islands, South China Sea, and the performance was compared with that of OK and NN. The results show that OK-SVM has higher numerical accuracy and attribute accuracy in detailed morphological fidelity, and is more adaptable in the geomorphological reconstruction of coral reefs with strong spatial variability. This method is relatively reliable for achieving high-precision reconstruction of complex geomorphology of coral reefs from active remote sensing datasets, and has potential to be extended to other geomorphological reconstruction applications.

Coral bleaching, caused by elevated sea surface temperature (SST), is occurring more frequently and seriously worldwide. Due to the lack of field observations, we understand little about the large-scale variability of thermal stress in the South China Sea (SCS) and its effect on China’s coral reefs. This paper used 4-km high resolution gap-filled SST (FilledSST) data and thermal stress data related to coral bleaching derived from Coral Reef Temperature Anomaly Database (CoRTAD) to quantify the spatial and temporal characteristics of chronic thermal stress and acute thermal stress to China’s coral reefs in SCS from 1982 to 2009. We analyzed the trend of SST in summer and the thermal stress frequency, intensity and duration during this period. The results indicate that, as a chronic thermal stress, summer mean SST in SCS shows an average upward trend of 0.2 °C/decade and the spatial pattern is heterogeneous. Waters of Xisha Islands and Dongsha Islands of the northern SCS are warming faster through time compared to Zhongsha Islands and Nansha Islands sea areas of the southern SCS. High frequency bleaching related thermal stress events for these reefs are seen in the area to the northwest of Luzon Island. Severe anomaly thermal stress events are more likely to occur during the subsequent year of the El Niño year for these coral reefs. Besides, the duration of thermal stress varies considerably by anomaly year and by region.

Coral reefs in the Xisha Islands (also known as the Paracel Islands in English), South China Sea, have experienced dramatic declines in coral cover. However, the current regional scale hard coral distribution of geomorphic and ecological zones, essential for reefs management in the context of global warming and ocean acidification, is not well documented. We analyzed data from field surveys, Landsat-8 and GF-1 images to map the distribution of hard coral within geomorphic zones and reef flat ecological zones. In situ surveys conducted in June 2014 on nine reefs provided a complete picture of reef status with regard to live coral diversity, evenness of coral cover and reef health (live versus dead cover) for the Xisha Islands. Mean coral cover was 12.5% in 2014 and damaged reefs seemed to show signs of recovery. Coral cover in sheltered habitats such as lagoon patch reefs and biotic dense zones of reef flats was higher, but there were large regional differences and low diversity. In contrast, the more exposed reef slopes had high coral diversity, along with high and more equal distributions of coral cover. Mean hard coral cover of other zones was <10%. The total Xisha reef system was estimated to cover 1 060 km2, and the emergent reefs covered ~787 m2. Hard corals of emergent reefs were considered to cover 97 km2. The biotic dense zone of the reef flat was a very common zone on all simple atolls, especially the broader northern reef flats. The total cover of live and dead coral can reach above 70% in this zone, showing an equilibrium between live and dead coral as opposed to coral and algae. This information regarding the spatial distribution of hard coral can support and inform the management of Xisha reef ecosystems.

The technique of incremental updating,which can better guarantee the real-time situation of navigational map,is the developing orientation of navigational road network updating.The data center of vehicle navigation system is in charge of storing incremental data,and the spatio-temporal data model for storing incremental data does affect the efficiency of the response of the data center to the requirements of incremental data from the vehicle terminal.According to the analysis on the shortcomings of several typical spatio-temporal data models used in the data center and based on the base map with overlay model,the reverse map with overlay model （RMOM） was put forward for the data center to make rapid response to incremental data request.RMOM supports the data center to store not only the current complete road network data,but also the overlays of incremental data from the time when each road network changed to the current moment.Moreover,the storage mechanism and index structure of the incremental data were designed,and the implementation algorithm of RMOM was developed.Taking navigational road network in Guangzhou City as an example,the simulation test was conducted to validate the efficiency of RMOM.Results show that the navigation database in the data center can response to the requirements of incremental data by only one query with RMOM,and costs less time.Compared with the base map with overlay model,the data center does not need to temporarily overlay incremental data with RMOM,so time-consuming of response is significantly reduced.RMOM greatly improves the efficiency of response and provides strong support for the real-time situation of navigational road network.

The amount of live and dead coral is related to recruitment, but differentiating them by remote sensing techniques is difficult. We measured change in the amount of live, bleached, and recently (<6 months) dead coral cover (CCA6) for an island archipelago in the South China Sea. Six Landsat 4/7 ETM/8 OLI images from 1989–1990, 2005, and 2014 were analyzed to assess changes in CCA6 at 14 coral reefs in the western Xisha Islands. Satellite images were georectified and calibrated to remote sensing reflectance. Models for three shallow water (<6 m) geomorphic zones throughout the western Xisha Islands are proposed based on ground-truthed data collected in 2014 and satellite-determined spectral values for 2014 images. Nonlinear models based on Landsat image blue spectral bands for reef slope and lagoon habitats, and green bands for reef flat habitats, are determined as optimal models. Significant changes in CCA6 from 2005 to 2014, and changes in coral reefs and geomorphic zones, correlate with increased numbers of both crown-of-thorns starfish, and sea surface temperature in 2007. Detecting change in CCA6 by remote sensing can provide large-scale information of value for coral reef management, restoration, and protection.

Coral bleaching, caused by elevated sea surface temperature（SST）, is occurring more frequently and seriously worldwide. Due to the lack of field observations, we understand little about the large-scale variability of thermal stress in the South China Sea（SCS） and its effect on China＇s coral reefs. This paper used 4-km high resolution gap-filled SST（Filled SST） data and thermal stress data related to coral bleaching derived from Coral Reef Temperature Anomaly Database（Co RTAD） to quantify the spatial and temporal characteristics of chronic thermal stress and acute thermal stress to China＇s coral reefs in SCS from 1982 to 2009. We analyzed the trend of SST in summer and the thermal stress frequency, intensity and duration during this period. The results indicate that, as a chronic thermal stress, summer mean SST in SCS shows an average upward trend of 0.2℃/decade and the spatial pattern is heterogeneous. Waters of Xisha Islands and Dongsha Islands of the northern SCS are warming faster through time compared to Zhongsha Islands and Nansha Islands sea areas of the southern SCS. High frequency bleaching related thermal stress events for these reefs are seen in the area to the northwest of Luzon Island. Severe anomaly thermal stress events are more likely to occur during the subsequent year of the El Nino year for these coral reefs. Besides, the duration of thermal stress varies considerably by anomaly year and by region.

Background Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb) complex infection, is a leading cause of death worldwide from a single infectious agent. The emergence of drug resistance Mtb clinical strains makes the situation more serious. The role of Mtb outer membrane protein A (OmpA) in antimicrobial resistance remains unclear. This study aimed to evaluate the effect of OmpA expression on mycobacterial drug resistance. In this study, a Mycobacterium smegmatis (Ms) strain overexpressing OmpA (Ms-OmpA) and a Mycobacterium bovis (Mb) strain overexpressing OmpA (Mb-OmpA) were constructed, and their susceptibility to anti-TB drugs was determined by performing the minimal inhibitory concentrations (MICs), the plate assay and the macrophage infection assays. Results The streptomycin MIC of the overexpressing strain was 2-fold lower than those of the wide-type (Ms) and empty plasmid strains (pMV-261) as well as amikacin and gentamicin. Moreover, both the plate and the macrophage infection assays indicate that overexpression of OmpA increases streptomycin sensitivity in Mycobacteria. The other aminoglycosides like amikacin and gentamicin have the same phenotypes as streptomycin on the plates for the virulent strain Mb-OmpA. The porin inhibitor spermidine can increase streptomycin tolerance in the overexpressing strain, and overexpressing OmpA can increase the intracellular accumulation of hydrophilic ethidium bromide, which indicates that porin protein OmpA contributes to aminoglycosides sensitivity in Mycobacteria. Conclusions In this study, we have characterized the contribution of OmpA in the antimicrobial resistance phenotype of Mycobacteria, which may provide valuable insights for understanding antibiotic resistance and designing new strategies for TB treatment.

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb) complex infection, is a leading cause of death worldwide from a single infectious agent. The emergence of drug resistance Mtb clinical strains makes the situation more serious. The role of Mtb outer membrane protein A (OmpA) in antimicrobial resistance remains unclear. This study aimed to evaluate the effect of OmpA expression on mycobacterial drug resistance. In this study, a Mycobacterium smegmatis (Ms) strain overexpressing OmpA (Ms-OmpA) and a Mycobacterium bovis (Mb) strain overexpressing OmpA (Mb-OmpA) were constructed, and their susceptibility to anti-TB drugs was determined by performing the minimal inhibitory concentrations (MICs), the plate assay and the macrophage infection assays. The streptomycin MIC of the overexpressing strain was 2-fold lower than those of the wide-type (Ms) and empty plasmid strains (pMV-261) as well as amikacin and gentamicin. Moreover, both the plate and the macrophage infection assays indicate that overexpression of OmpA increases streptomycin sensitivity in Mycobacteria. The other aminoglycosides like amikacin and gentamicin have the same phenotypes as streptomycin on the plates for the virulent strain Mb-OmpA. The porin inhibitor spermidine can increase streptomycin tolerance in the overexpressing strain, and overexpressing OmpA can increase the intracellular accumulation of hydrophilic ethidium bromide, which indicates that porin protein OmpA contributes to aminoglycosides sensitivity in Mycobacteria. In this study, we have characterized the contribution of OmpA in the antimicrobial resistance phenotype of Mycobacteria, which may provide valuable insights for understanding antibiotic resistance and designing new strategies for TB treatment.

Background Lymphovascular invasion (LVI) status in rectal cancer (RC) without lymph node metastasis (LNM) can significantly influence the patient’s treatment decisions. This study aims to develop and validate a combined model based on MRI radiomics features integrated with clinical immune-inflammatory biomarkers for the prediction of LVI status in RC without LNM. The Shapley Additive Explanation (SHAP) method was employed to visualize the prediction process and enhance interpretability for clinical application. Methods We retrospectively collected data from 257 RC patients without LNM from two centers. Univariate and multivariate logistic regression analyses were performed on clinical data to identify independent predictors of LVI. Volumes of interest were manually delineated on T2WI and ADC sequences, and corresponding radiomic features were extracted. A combined model was constructed by combining rad-score and clinical immune-inflammatory biomarkers, and the SHAP was used to visualize the prediction process. Results The area under the curve (AUC) of the combined model was based on intratumoral features (training vs. testing vs. validation datasets: 0.813 vs. 0.854 vs. 0.807). The AUC of the combined model was based on both intra- and peritumoral features (training vs. testing vs. validation datasets: 0.855 vs. 0.841 vs. 0.860). After comparison, the combined model (C + Q) based on intra- and peritumoral MRI radiomics features integrated with clinical immune-inflammatory biomarkers demonstrated better predictive performance. Conclusion The combined model (C + Q) has great potential in the non-invasive prediction of LVI in RC without LNM, providing a basis for stratified management and individualized treatment decisions for RC patients.