Deriving inherent optical properties from classical water color measurements: Forel-ule index and secchi disk depth

Secchi disk depth (ZSD) and Forel-Ule index (FUI) are the two oldest and easiest measurements of water optical properties based on visual determination. With an overarching objective to obtain water inherent optical properties (IOPs) using these historical measurements, this study presents a model for associating remote-sensing reflectance (Rrs) with FUI and ZSD. Based upon this, a scheme (FZ2ab) for converting FUI and ZSD to absorption (a) and backscattering coefficients (bb) is developed and evaluated. For a data set from HydroLight simulations, the difference is < 11% between FZ2ab-derived a and known a, and < 28% between FZ2ab-derived bb and known bb. Further, for a data set from field measurements, the difference is < 30% between FZ2ab-derived a and measured a. These results indicate that FZ2ab can bridge the gap between historical measurements and the focus of IOP measurements in modern marine optics, and potentially extend our knowledge on the bio-optical properties of global seas to the past century through the historical measurements of FUI and ZSD

UWB ranging errors mitigation with novel CIR feature parameters and two-step NLOS identification

The effective identification and mitigation of non-line-of-sight (NLOS) ranging errors are essential for achieving high-precision positioning and navigation with ultra-wideband (UWB) technology in harsh indoor environments. In this paper, an efficient UWB ranging-error mitigation strategy that uses novel channel impulse response parameters based on the results of a two-step NLOS identification, composed of a decision tree and feedforward neural network, is proposed to realize indoor locations. NLOS ranging errors are classified into three types, and corresponding mitigation strategies and recall mechanisms are developed, which are also extended to partial line-of-sight (LOS) errors. Extensive experiments involving three obstacles (humans, walls, and glass) and two sites show an average NLOS identification accuracy of 95.05%, with LOS/NLOS recall rates of 95.72%/94.15%. The mitigated LOS errors are reduced by 50.4%, while the average improvement in the accuracy of the three types of NLOS ranging errors is 61.8%, reaching up to 76.84%. Overall, this method achieves a reduction in LOS and NLOS ranging errors of 25.19% and 69.85%, respectively, resulting in a 54.46% enhancement in positioning accuracy. This performance surpasses that of state-of-the-art techniques, such as the convolutional neural network (CNN), long short-term memory–extended Kalman filter (LSTM-EKF), least-squares–support vector machine (LS-SVM), and k-nearest neighbor (K-NN) algorithms

Water color from Sentinel-2 MSI data for monitoring large rivers: Yangtze and Danube

Rivers provide key ecosystem services that are inherently engineered and optimized to meet the strategic and economic needs of countries around the world. However, limited water quality records of a full river continuum hindered the understanding of how river systems response to the multiple stressors acting on them. This study highlights the use of Sentinel-2 Multi-Spectral Imager (MSI) data to monitor changes in water color in two optically complex river systems: the Yangtze and Danube using the Forel-Ule Index (FUI). FUI divides water color into 21 classes from dark blue to yellowish brown stemming from the historical Forel-Ule water color scale and has been promoted as a useful indicator showing water turbidity variations in water bodies. The results revealed contrasting water color patterns in the two rivers on both spatial and seasonal scales. Spatially, the FUI of the Yangtze River gradually increased from the upper reaches to the lower reaches, while the FUI of the Danube River declined in the lower reaches, which is possibly due to the sediment sink effect of the Iron Gate Dams. The regional FUI peaks and valleys observed in the two river systems have also been shown to be related to the dams and hydropower stations along them. Seasonally, the variations of FUI in both systems can be attributed to climate seasonality, especially precipitation in the basin and the water level. Moreover, land cover within the river basin was possibly a significant determinant of water color, as higher levels of vegetation in the Danube basin were associated with lower FUI values, whereas higher FUI values and lower levels of vegetation were observed in the Yangtze system. This study furthers our knowledge of using Sentinel-2 MSI to monitor and understand the spatial-temporal variations of river systems and highlights the capabilities of the FUI in an optically complex environment

MiR-543 Promotes Migration, Invasion and Epithelial-Mesenchymal Transition of Esophageal Cancer Cells by Targeting Phospholipase A2 Group IVA

Background/Aims: The aim of this study was to investigate the roles of miR-543 and phospholipase A2 group IVA (PLA2G4A) in cell mobility and the invasiveness cascade in esophageal squamous cell carcinoma (ESCC) and to validate the interactive relationship between miR-543 and PLA2G4A. Methods: Microarray analysis showed the different expression levels of PLA2G4A in two ESCC cell lines (KYSE30 and KYSE180). The expression levels of miR-543 and PLA2G4A in ESCC tissues were confirmed by qRT-PCR and Western blotting. The targeted relationship between miR-543 and PLA2G4A was studied and verified by a luciferase activity assay. Then, the invasion and metastasis ability of ESCC cell lines transfected with miR-543 mimics, miR-543 inhibitor, or PLA2G4A and miR-543 mimics were analyzed separately by Transwell migration and invasion assays. In addition, the roles of miR-543 and PLA2G4A in the expression of E-cadherin and vimentin were also investigated. Results: PLA2G4A up-regulated the level of E-cadherin and down-regulated the level of vimentin, which curbed ESCC cell mobility and invasion. In ESCC cells, the expression of miR-543 was significantly higher, whereas the expression of PLA2G4A was markedly lower. MiR-543 facilitated ESCC cell mobility and invasion by repressing PLA2G4A. Conclusions: MiR-543 enhanced the cell mobility and the invasiveness cascade in ESCC cells via the down-regulation of PLA2G4A expression

Changes of water clarity in large lakes and reservoirs across China observed from long-term MODIS

Water clarity is a well-established first-order indicator of water quality and has been used globally by water regulators in their monitoring and management programs. Assessments of water clarity in lakes over large temporal and spatial scales, however, are rare, limiting our understanding of its variability and the driven forces. In this study, we developed and validated a robust Secchi disk depth (ZSD) algorithm for lakes across China based on two water color parameters, namely Forel-Ule Index (FUI) and hue angle α, retrieved from MODIS data. The MODIS ZSD model shows good results when compared with in-situ measurements from 17 lakes, with a 27.4% mean relative difference (MRD) in the validation dataset. Compared with other empirical ZSD models, our FUI and α-based model demonstrates improved performance and adaptability over a wide range of water clarity and trophic states. This algorithm was subsequently applied to MODIS measurements to provide a comprehensive assessment of water clarity in large lakes (N = 153) across China for the first time. The mean summer ZSD of the studied lakes between 2000 and 2017 demonstrated marked spatial and temporal variations. Spatially, the ZSD of large lakes presented a distinct spatial pattern of “high west and low east” over China. This spatial pattern was found to be associated with the significant differences in lake depth and altitude between west and east China while China's population, GDP, temperature, and precipitation distribution have also contributed to a certain extent. Temporally, the ZSD of most lakes increased during this period, with an overall mean rate of 3.3 cm/yr for all lakes. Here, 38.6% (N = 59) of the lakes experienced a significant increase in their ZSD value during the past 18 years while only 8.5% (N = 13) showed a significant decreasing trend. Significant increases in lake ZSD were observed in west China, which were found to correlate with the increase of air temperature and lake surface area. This is possibly a response of the lakes in west China to climate change. In the lake systems of east China, which are predominately used as a drinking water source, the increase in lake ZSD was found to be strongly correlated with changes in local GDP (gross domestic production), NDVI (normalized difference vegetation index) and lake surface area, suggesting a combined effect of the implemented management practices and climatic variability. The results of this study provide important information for water quality conservation and management in China, and also highlight the value of satellite remote sensing in monitoring water quality over lakes at a large scale and long-term

Trophic state assessment of global inland waters using a MODIS-derived Forel-Ule index

Eutrophication of inland waters is considered a serious global environmental problem. Satellite remote sensing (RS) has been established as an important source of information to determine the trophic state of inland waters through the retrieval of optically active water quality parameters such as chlorophyll-a (Chl-a). However, the use of RS techniques for assessment of the trophic state of inland waters on a global scale is hindered by the performance of retrieval algorithms over highly dynamic and complex optical properties that characterize many of these systems. In this study, we developed a new RS approach to assess the trophic state of global inland water bodies based on Moderate Resolution Imaging Spectroradiometer (MODIS) imagery and the Forel-Ule index (FUI). First, the FUI was calculated from MODIS data by dividing natural water colour into 21 indices from dark blue to yellowish-brown. Then the relationship between FUI and the trophic state index (TSI) was established based on in-situ measurements and MODIS products. The water-leaving reflectance at 645 nm band was employed to distinguish coloured dissolved organic matter (CDOM)-dominated systems in the FUI-based trophic state assessment. Based on the analysis, the FUI-based trophic state assessment method was developed and applied to assess the trophic states of 2058 large inland water bodies (surface area >25 km2) distributed around the world using MODIS data from the austral and boreal summers of 2012. Our results showed that FUI can be retrieved from MODIS with a considerable accuracy (92.5%, R2 = 0.92) by comparing with concurrent in situ measurements over a wide range of lakes, and the overall accuracy of the FUI-based trophic state assessment method is 80.0% (R2 = 0.75) validated by an independent dataset. Of the global large water bodies considered, oligotrophic large lakes were found to be concentrated in plateau regions in central Asia and southern South America, while eutrophic large lakes were concentrated in central Africa, eastern Asia, and mid-northern and southeast North America

Utility of clinical metagenomics in diagnosing malignancies in a cohort of patients with Epstein-Barr virus positivity

BackgroundsDifferentiation between benign and malignant diseases in EBV-positive patients poses a significant challenge due to the lack of efficient diagnostic tools. Metagenomic Next-Generation Sequencing (mNGS) is commonly used to identify pathogens of patients with fevers of unknown-origin (FUO). Recent studies have extended the application of Next-Generation Sequencing (NGS) in identifying tumors in body fluids and cerebrospinal fluids. In light of these, we conducted this study to develop and apply metagenomic methods to validate their role in identifying EBV-associated malignant disease.MethodsWe enrolled 29 patients with positive EBV results in the cohort of FUO in the Department of Infectious Diseases of Huashan Hospital affiliated with Fudan University from 2018 to 2019. Upon enrollment, these patients were grouped for benign diseases, CAEBV, and malignant diseases according to their final diagnosis, and CNV analysis was retrospectively performed in 2022 using samples from 2018 to 2019.ResultsAmong the 29 patients. 16 of them were diagnosed with benign diseases, 3 patients were diagnosed with CAEBV and 10 patients were with malignant diseases. 29 blood samples from 29 patients were tested for mNGS. Among all 10 patients with malignant diagnosis, CNV analysis suggested neoplasms in 9 patients. Of all 19 patients with benign or CAEBV diagnosis, 2 patients showed abnormal CNV results. The sensitivity and specificity of CNV analysis for the identification for tumors were 90% and 89.5%, separately.ConclusionsThe application of mNGS could assist in the identification of microbial infection and malignancies in EBV-related diseases. Our results demonstrate that CNV detection through mNGS is faster compared to conventional oncology tests. Moreover, the convenient collection of peripheral blood samples adds to the advantages of this approach

Moving towards global satellite based products for monitoring of inland and coastal waters. Regional examples from Europe and South America

Surface waters are a fundamental resource. They fulfil key function in global biogeochemical cycles and are core to our water, food and energy security. The rapidly increasing rate of data collection from different Earth observation (EO) missions suitable for observing water bodies has promoted satellite remote sensing (RS) as a more widely recognised source of information on a number of indicators of water quality and ecosystem condition at local and global scales. In parallel, advances in optical sensors support new and more detailed characterisation of the Earth surface and could lead to innovative EO-based products. Nonetheless, RS of water colour of inland and coastal systems, especially in larger scales and over long-term time series, faces unique challenges. This study provides an overview of the challenges and solutions of developing a global observation platform, including the diverse and complex optical properties of inland waters and guided algorithm selection procedure required to deliver reliable data. The development and validation of a global satellite data processing chain (Calimnos) has been supported by access to an extensive in situ data from more than thirty partners around the world that are now held in the LIMNADES community-owned database. This approach has resulted in a step-change in our ability to produce regional and global water quality products for optically complex waters. Local examples of the data outputs will be explored and the opportunities in how these data can be embedded within local and national monitoring schemes to facilitate better management of water will be discussed