Can Forel–Ule Index Act as a Proxy of Water Quality in Temperate Waters? Application of Plume Mapping in Liverpool Bay, UK

The use of ocean colour classification algorithms, linked to water quality gradients, can be a useful tool for mapping river plumes in both tropical and temperate systems. This approach has been applied in operational water quality programs in the Great Barrier Reef to map river plumes and assess trends in marine water composition and ecosystem health during flood periods. In this study, we used the Forel–Ule colour classification algorithm for Sentinel-3 OLCI imagery in an automated process to map monthly, annual and long-term plume movement in the temperate coastal system of Liverpool Bay (UK). We compared monthly river plume extent to the river flow and in situ water quality data between 2017–2020. The results showed a strong positive correlation (Spearman’s rho = 0.68) between the river plume extent and the river flow and a strong link between the FUI defined waterbodies and nutrients, SPM, turbidity and salinity, hence the potential of the Forel–Ule index to act as a proxy for water quality in the temperate Liverpool Bay water. The paper discusses how the Forel–Ule index could be used in operational water quality programs to better understand river plumes and the land-based inputs to the coastal zones in UK waters, drawing parallels with methods that have been developed in the GBR and Citclops project. Overall, this paper provides the first insight into the systematic long-term river plume mapping in UK coastal waters using a fast, cost-effective, and reproducible workflow. The study created a novel water assessment typology based on the common physical, chemical and biological ocean colour properties captured in the Forel–Ule index, which could replace the more traditional eutrophication assessment regions centred around strict geographic and political boundaries. Additionally, the Forel–Ule assessment typology is particularly important since it identifies areas of the greatest impact from the land-based loads into the marine environment, and thus potential risks to vulnerable ecosystems

A probabilistic approach to mapping the contribution of individual riverine discharges into Liverpool Bay using distance accumulation cost methods on satellite derived ocean-colour data

Assessments of the water quality in coastal zones often rely on indirect indicators from contributing river inputs and the neighbouring ocean. Using a novel combination of distance accumulation cost methods and an ocean-colour product derived from SENTINEL-3 data, we developed a probabilistic method for the assessment of dissolved inorganic nitrogen (DIN) in Liverpool Bay (UK) for the period from 2017 to 2020. Using our approach, we showed the annual and monthly likelihood of DIN exposure from its 12 major contributory rivers. Furthermore, we generated monthly risk maps showing the probability of DIN exposure from all rivers, which revealed a seasonal variation of extent and location around the bay. The highest likelihood of high DIN exposure throughout the year was in the estuarine regions of the Dee, Mersey, and Ribble, along with near-shore areas along the north Wales coast and around the mouth of the rivers Mersey and Ribble. There were seasonal changes in the risk of DIN exposure, and this risk remained high all year for the Mersey and Dee estuary regions. In contrast, for the mouth and near the coastal areas of the Ribble, the DIN exposure decreased in spring, remained low during the summer and early autumn, before displaying an increase during winter. Our approach offers the ability to assess the water quality within coastal zones without the need of complex hydrodynamic models, whilst still having the potential to apportion nutrient exposure to specific riverine inputs. This information can help to prioritise how direct mitigation strategies can be applied to specific river catchments, focusing the limited resources for coastal zone and river basin management

Seaweed aquaculture through the lens of gender: Participation, roles, pay and empowerment in Bantayan, Philippines

Aquaculture is one of the fastest growing food-producing sectors worldwide. Of particular importance is the cultivation of seaweed, particularly in East and Southeast Asia where seaweeds dominate the production market, and are key for coastal communities both as main livelihood source and as alternative or supplementary income to fisheries. Women play a crucial role in various segments of the seaweed aquaculture value chain; yet few researchers have empirically examined the gendered impacts of women’s participation in aquaculture. Using the case study of Bantayan Island, in the Philippines, the objective of this study is to deepen our understanding of the impact of women’s participation in aquaculture by specifically investigating their roles, remuneration and empowerment related to the production node of seaweed aquaculture. Adopting a novel research approach, which combines the outcomes of a focus group discussion and the data collected through two questionnaires, we provide a comprehensive and robust understanding of gender issues in aquaculture. Results of the economic analysis of labour costs indicate that women constitute most of the workforce but are paid less than men; the average gender pay gap is 55.4%. Moreover, our study finds that there is a well-established gendered division of labour in seaweed aquaculture. Greater female participation is not mirrored by more women in leadership roles and decision-making power in the workplace, although participation may have a positive impact on female intrahousehold empowerment. An important contribution of our analysis is to show that gender stereotypes in aquaculture production persist and they affect roles, wages and decision-making power. Acknowledging the fundamental contribution of women in aquaculture can inform the development of gender-sensitive indicators, supporting the measurement of progress towards relevant Targets of the fifth Sustainable Development Goal (“ Achieve gender equality and empower all women and girls ”), therefore mainstreaming gender into resource management, and poverty alleviatio

CVID-Associated Tumors: Czech Nationwide Study Focused on Epidemiology, Immunology, and Genetic Background in a Cohort of Patients With CVID

Background: Common variable immunodeficiency disorder (CVID) is one of the most frequent inborn errors of immunity, increased occurrence of malignancies, particularly lymphomas, and gastric cancers, has long been noted among CVID patients. Multifactorial etiology, including immune dysregulation, infections, chronic inflammation, or genetic background, is suggested to contribute to tumor development. Here, we present the results of the first Czech nationwide study focused on epidemiology, immunology and genetic background in a cohort of CVID patients who also developed tumorsMethods: The cohort consisted of 295 CVID patients followed for 3,070 patient/years. Standardized incidence ratio (SIR) was calculated to determine the risk of cancer, and Risk ratio (RR) was established to evaluate the significance of comorbidities. Moreover, immunophenotyping, including immunoglobulin levels and lymphocyte populations, was assessed. Finally, Whole exome sequencing (WES) was performed in all patients with lymphoma to investigate the genetic background.Results: Twenty-five malignancies were diagnosed in 22 patients in a cohort of 295 CVID patients. SIR was more than 6 times greater in comparison to the general population. The most common neoplasias were gastric cancers and lymphomas. History of Immune thrombocytopenic purpura (ITP) was established as a potential risk factor, with over 3 times higher risk of cancer development. The B cell count at diagnosis of lymphoma was reduced in the lymphoma group; moreover, post-treatment B and T cell lymphopenia, associated with poorer outcome, was found in a majority of the patients. Intriguingly, no NK cell depression was observed after the chemotherapy. WES revealed heterogeneous genetic background among CVID patients with tumors, identifying gene variants associated with primary immunodeficiencies (such as CTLA4, PIK3CD, PMS2) and/or increased cancer susceptibility (including BRCA1, RABEP1, EP300, KDM5A).Conclusions: The incidence of malignancy in our CVID cohort was found to be more than 6 times greater compared to the general population. Gastric cancers and lymphomas were the most frequently diagnosed tumors. ITP was identified as a risk factor for malignancy in CVID patients. WES analysis confirmed a wide genetic heterogeneity among CVID patients. The identified causative or modifying gene variants pointed to errors in mechanisms contributing to both immunodeficiency and malignancy

Standardized next-generation sequencing of immunoglobulin and T-cell receptor gene recombinations for MRD marker identification in acute lymphoblastic leukaemia; a EuroClonality-NGS validation study

Amplicon-based next-generation sequencing (NGS) of immunoglobulin (IG) and T-cell receptor (TR) gene rearrangements for clonality assessment, marker identification and quantification of minimal residual disease (MRD) in lymphoid neoplasms has been the focus of intense research, development and application. However, standardization and validation in a scientifically controlled multicentre setting is still lacking. Therefore, IG/TR assay development and design, including bioinformatics, was performed within the EuroClonality-NGS working group and validated for MRD marker identification in acute lymphoblastic leukaemia (ALL). Five EuroMRD ALL reference laboratories performed IG/TR NGS in 50 diagnostic ALL samples, and compared results with those generated through routine IG/TR Sanger sequencing. A central polytarget quality control (cPT-QC) was used to monitor primer performance, and a central in-tube quality control (cIT-QC) wa

Standardized flow cytometry for highly sensitive MRD measurements in B-cell acute lymphoblastic leukemia

A fully-standardized EuroFlow 8–color antibody panel and laboratory procedure was stepwise designed to measure minimal residual disease (MRD) in B-cell precursor (BCP) acute lymphoblastic leukemia (ALL) patients with a sensitivity of £1025, comparable to real-time quantitative polymerase chain reaction (RQ-PCR)–based MRD detection via antigen-receptor rearrangements. Leukocyte markers and the corresponding antibodies and fluorochromes were selected based on their contribution in separating BCP-ALL cells from normal/regenerating BCP cells in multidimensional principal component analyses. After 5 multicenter design-test-evaluate-redesign phases with a total of 319 BCP-ALL patients at diagnosis, two 8-color antibody tubes were selected, which allowed separation between normal and malignant BCP cells in 99% of studied patients. These 2 tubes were tested with a new erythrocyte bulk-lysis protocol allowing acquisition of high cell numbers in 377 bone marrow follow-up samples of 178 BCP-ALL patients. Comparison with RQ-PCR–based MRD data showed a clear positive relation between the percentage concordant cases and the number of cells acquired. For those samples with >4 million cells acquired, concordant results were obtained in 93% of samples. Most discordances were clarified upon high-throughput sequencing of antigen-receptor rearrangements and blind multicenter reanalysis of flow cytometric data, resulting in an unprecedented concordance of 98% (97% for samples with MRD 98% of patients with sensitivities at least similar to RQ-PCR (£1025), if sufficient cells (>4 3 106, preferably more) are evaluated

Validation of the United Kingdom copy-number alteration classifier in 3239 children with B-cell precursor ALL

Genetic abnormalities provide vital diagnostic and prognostic information in pediatric acute lymphoblastic leukemia (ALL) and are increasingly used to assign patients to risk groups. We recently proposed a novel classifier based on the copy-number alteration (CNA) profile of the 8 most commonly deleted genes in B-cell precursor ALL. This classifier defined 3 CNA subgroups in consecutive UK trials and was able to discriminate patients with intermediate-risk cytogenetics. In this study, we sought to validate the United Kingdom ALL (UKALL)-CNA classifier and reevaluate the interaction with cytogenetic risk groups using individual patient data from 3239 cases collected from 12 groups within the International BFM Study Group. The classifier was validated and defined 3 risk groups with distinct event-free survival (EFS) rates: good (88%), intermediate (76%), and poor (68%) (P < .001). There was no evidence of heterogeneity, even within trials that used minimal residual disease to guide therapy. By integrating CNA and cytogenetic data, we replicated our original key observation that patients with intermediate-risk cytogenetics can be stratified into 2 prognostic subgroups. Group A had an EFS rate of 86% (similar to patients with good-risk cytogenetics), while group B patients had a significantly inferior rate (73%, P < .001). Finally, we revised the overall genetic classification by defining 4 risk groups with distinct EFS rates: very good (91%), good (81%), intermediate (73%), and poor (54%), P < .001. In conclusion, the UKALL-CNA classifier is a robust prognostic tool that can be deployed in different trial settings and used to refine established cytogenetic risk groups

UAV-Thermal Camera Remote Sensing for Monitoring Wild Rabbit (Oryctolagus cuniculus) Population

This paper addresses challenges of remote sensing to detect, count and track wild rabbits (Oryctolagus Cuniculus) in their natural habitat. A combination of UAV, thermal and RGB cameras was used to survey the wild rabbit population. Tarot 680 Pro UAV caused significant rabbit disturbance and Phantom 2 caused low to medium disturbance. Due to the rabbit disturbance, the thermal camera did not record any rabbit images. Consequently, airborne remote sensing had to be changed to the rabbit remote sensing from the ground, utilising a tripod and manually focused FLIR A655 thermal camera. The ground system was successful in monitoring the wild rabbit, causing no animal disturbance. OpenCV Python computer vision library automated the noise removal, rabbit detection and count from the thermal imagery. However, this analysis was not fully automated, as parameters for each sequence had to be treated individually. The Lucas-Kanade sparse optical flow tracking algorithm improved the rabbit counts by preventing from double-counting the same individual. This analysis can be enhanced by applying Template Matching Binary Mask (TMBM), which classifies and finds objects of the same size, colour in the rest of the frames. This study shows that remote sensing of wild rabbits in a plan view using RGB sensor is problematic due to the rabbit camouflage against bare soil. Using a thermal sensor, based on the relative temperature, is feasible in the wild rabbit monitoring as it allows for recognition between hot objects and background. However, noise created by warm bare soil needs to be removed from the thermal imagery. A mast and a thermal camera or a quadcopter UAV and a thermal camera are recommended for the rabbit monitoring. These systems need a further testing. Similarly, the rabbit behavioural responses to different UAV types necessitate future research