Noninvasive Diagnosis of Visceral Leishmaniasis:Development and Evaluation of Two Urine-Based Immunoassays for Detection of Leishmania donovani Infection in India

Visceral leishmaniasis (VL), one of the most prevalent parasitic diseasesin the developing world causes serious health concerns. Post kala-azar dermal leishmaniasis (PKDL) is a skin disease which occurs after treatment as a sequel to VL. Parasitological diagnosis involves invasive tissue aspiration which is tedious and painful. Commercially available immunochromatographic rapid diagnostic test such as rK39-RDT is used for field diagnosis of VL, detects antibodiesin serum samples. Urine sample is however, much easier in collection,storage and handling than serum and would be a better alternative where collection of tissue aspirate or blood is impractical. In this study, we have developed and evaluated the performance of two urine-based diagnostic assays, ELISA and dipstick test, and compared the results with serologicalrK39-RDT. Our study shows the capability of urinebased tests in detecting anti-Leishmania antibodies effectively for both VL and PKDL diagnosis. The ability of dipstick test to demonstrate negative results after six months in 90% of the VL cases after treatment could be useful as a test of clinical cure. Urine-based tests can therefore replace the need for invasive practices and ensure better diagnosi

Argo data 1999-2019: two million temperature-salinity profiles and subsurface velocity observations from a global array of profiling floats.

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Wong, A. P. S., Wijffels, S. E., Riser, S. C., Pouliquen, S., Hosoda, S., Roemmich, D., Gilson, J., Johnson, G. C., Martini, K., Murphy, D. J., Scanderbeg, M., Bhaskar, T. V. S. U., Buck, J. J. H., Merceur, F., Carval, T., Maze, G., Cabanes, C., Andre, X., Poffa, N., Yashayaev, I., Barker, P. M., Guinehut, S., Belbeoch, M., Ignaszewski, M., Baringer, M. O., Schmid, C., Lyman, J. M., McTaggart, K. E., Purkey, S. G., Zilberman, N., Alkire, M. B., Swift, D., Owens, W. B., Jayne, S. R., Hersh, C., Robbins, P., West-Mack, D., Bahr, F., Yoshida, S., Sutton, P. J. H., Cancouet, R., Coatanoan, C., Dobbler, D., Juan, A. G., Gourrion, J., Kolodziejczyk, N., Bernard, V., Bourles, B., Claustre, H., D'Ortenzio, F., Le Reste, S., Le Traon, P., Rannou, J., Saout-Grit, C., Speich, S., Thierry, V., Verbrugge, N., Angel-Benavides, I. M., Klein, B., Notarstefano, G., Poulain, P., Velez-Belchi, P., Suga, T., Ando, K., Iwasaska, N., Kobayashi, T., Masuda, S., Oka, E., Sato, K., Nakamura, T., Sato, K., Takatsuki, Y., Yoshida, T., Cowley, R., Lovell, J. L., Oke, P. R., van Wijk, E. M., Carse, F., Donnelly, M., Gould, W. J., Gowers, K., King, B. A., Loch, S. G., Mowat, M., Turton, J., Rama Rao, E. P., Ravichandran, M., Freeland, H. J., Gaboury, I., Gilbert, D., Greenan, B. J. W., Ouellet, M., Ross, T., Tran, A., Dong, M., Liu, Z., Xu, J., Kang, K., Jo, H., Kim, S., & Park, H. Argo data 1999-2019: two million temperature-salinity profiles and subsurface velocity observations from a global array of profiling floats. Frontiers in Marine Science, 7, (2020): 700, doi:10.3389/fmars.2020.00700.In the past two decades, the Argo Program has collected, processed, and distributed over two million vertical profiles of temperature and salinity from the upper two kilometers of the global ocean. A similar number of subsurface velocity observations near 1,000 dbar have also been collected. This paper recounts the history of the global Argo Program, from its aspiration arising out of the World Ocean Circulation Experiment, to the development and implementation of its instrumentation and telecommunication systems, and the various technical problems encountered. We describe the Argo data system and its quality control procedures, and the gradual changes in the vertical resolution and spatial coverage of Argo data from 1999 to 2019. The accuracies of the float data have been assessed by comparison with high-quality shipboard measurements, and are concluded to be 0.002°C for temperature, 2.4 dbar for pressure, and 0.01 PSS-78 for salinity, after delayed-mode adjustments. Finally, the challenges faced by the vision of an expanding Argo Program beyond 2020 are discussed.AW, SR, and other scientists at the University of Washington (UW) were supported by the US Argo Program through the NOAA Grant NA15OAR4320063 to the Joint Institute for the Study of the Atmosphere and Ocean (JISAO) at the UW. SW and other scientists at the Woods Hole Oceanographic Institution (WHOI) were supported by the US Argo Program through the NOAA Grant NA19OAR4320074 (CINAR/WHOI Argo). The Scripps Institution of Oceanography's role in Argo was supported by the US Argo Program through the NOAA Grant NA15OAR4320071 (CIMEC). Euro-Argo scientists were supported by the Monitoring the Oceans and Climate Change with Argo (MOCCA) project, under the Grant Agreement EASME/EMFF/2015/1.2.1.1/SI2.709624 for the European Commission

GUI based interactive system for Visual Quality Control of Argo data

580-586Argo program is aimed at maintaining an array of 3000 free drifting floats to measure temperature and salinity (T/S). Present study consists a PC-based system developed for visualization and quality control of T/S profiles obtained from Argo floats. The system, coded in Java, is user interactive and runs on Windows platform. Default the Argo T/S profiles pass through 19 automatic checks and quality flags are assigned. Using the system, T/S profiles that failed the automatic Argo tests undergo visual review. This visual review is done to determine whether automatic Argo tests were excessively flagging good measurements as bad or vice-versa, to motivate modifications to automatic Argo tests and to determine whether additional tests were necessary to catch problems that could not be detected by the existing tests. Visual review is done by comparing with 1° X 1° monthly climatologies from WOA01. Profile records deviating beyond 2 standard deviations from the mean are flagged as bad. Provision is also given to compare individual T/S profiles with previous 5 profiles via a waterfall plot

COASTAL OCEAN OBSERVING NETWORK – OPEN SOURCE ARCHITECTURE FOR DATA MANAGEMENT AND WEB-BASED DATA SERVICES

The observations from the oceans are the backbone for any kind of operational services, viz. potential fishing zone advisory services, ocean state forecast, storm surges, cyclones, monsoon variability, tsunami, etc. Though it is important to monitor open Ocean, it is equally important to acquire sufficient data in the coastal ocean through coastal ocean observing systems for re-analysis, analysis and forecast of coastal ocean by assimilating different ocean variables, especially sub-surface information; validation of remote sensing data, ocean and atmosphere model/analysis and to understand the processes related to air-sea interaction and ocean physics. Accurate information and forecast of the state of the coastal ocean at different time scales is vital for the wellbeing of the coastal population as well as for the socio-economic development of the country through shipping, offshore oil and energy etc. Considering the importance of ocean observations in terms of understanding our ocean environment and utilize them for operational oceanography, a large number of platforms were deployed in the Indian Ocean including coastal observatories, to acquire data on ocean variables in and around Indian Seas. The coastal observation network includes HF Radars, wave rider buoys, sea level gauges, etc. The surface meteorological and oceanographic data generated by these observing networks are being translated into ocean information services through analysis and modelling. Centralized data management system is a critical component in providing timely delivery of Ocean information and advisory services. In this paper, we describe about the development of open-source architecture for real-time data reception from the coastal observation network, processing, quality control, database generation and web-based data services that includes on-line data visualization and data downloads by various means

Quality control of oceanographic in situ data from Argo floats using climatological convex hulls

A new method of identifying anomalous oceanic temperature and salinity (T/S) data from Argo profiling floats is proposed. The proposed method uses World Ocean Database 2013 climatology to classify good against anomalous data by using convex hulls. An n-sided polygon (convex hull) with least area encompassing all the climatological points is constructed using Jarvis March algorithm. Subsequently Points In Polygon (PIP) principle implemented using ray casting algorithm is used to classify the T/S data as within or without acceptable bounds. It is observed that various types of anomalies associated with the oceanographic data viz., spikes, bias, sensor drifts etc can be identified using this method. Though demonstrated for Argo data it can be applied to any oceanographic data. • The patterns of variation of the parameter (temperature or salinity) corresponding to a particular depth, along the longitude or latitude can be used to build convex hulls. • This method can be effectively used for quality control by building Convex hulls for various observed depths corresponding to biogeochemical data which are sparsely observed. • This method has the advantage of treating the bulk of oceanographic in situ data in a single iteration which filters out anomalous data

Open Source Architecture for Web-Based Oceanographic Data Services

A GIS for ocean data applications named "Ocean Data and Information Systems (ODIS)" was designed and developed. The system is based on the University of Minnesota MapServer, an open source platform for publishing spatial data and interactive mapping applications to the web with MySQL as the backend database server. This paper discusses some of the details of the storage and organization of oceanographic data, methods employed for visualization of parameter plots, and mapping of the data. ODIS is conceived to be an end-to-end system comprising acquisition of data from a variety of heterogeneous ocean platforms, processing, integration, quality control, and web-based dissemination to users for operational and research activities. ODIS provides efficient data management and potential mapping and visualization functions for oceanographic data

Marine Data Services at National Oceanographic Data Centre-India

In this paper we introduce about the marine data archived at Indian National Centre for Ocean Information Services (INCOIS), Ministry of Earth Sciences, India. Heterogeneous data from in situ, remote sensing and ocean models are archived. In-situ ocean observations includes data from Lagrangian as well Eulerian platforms like Argo floats, moored buoys etc, while remote sensing include data from NOAA satellite series, OceanScat etc. The data generated is translated into ocean information services through analysis and modelling. Data is disseminated to users using variety of means like web with GIS features, ERDDAP, Live Access server with facilities to search, visualize and download

Bay of Bengal intraseasonal oscillations and the 2018 monsoon onset

Author Posting. © American Meteorological Society, 2021. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Bulletin of the American Meteorological Society 102(10), (2021): E1936–E1951, https://doi.org/10.1175/BAMS-D-20-0113.1.In the Bay of Bengal, the warm, dry boreal spring concludes with the onset of the summer monsoon and accompanying southwesterly winds, heavy rains, and variable air–sea fluxes. Here, we summarize the 2018 monsoon onset using observations collected through the multinational Monsoon Intraseasonal Oscillations in the Bay of Bengal (MISO-BoB) program between the United States, India, and Sri Lanka. MISO-BoB aims to improve understanding of monsoon intraseasonal variability, and the 2018 field effort captured the coupled air–sea response during a transition from active-to-break conditions in the central BoB. The active phase of the ∼20-day research cruise was characterized by warm sea surface temperature (SST > 30°C), cold atmospheric outflows with intermittent heavy rainfall, and increasing winds (from 2 to 15 m s−1). Accumulated rainfall exceeded 200 mm with 90% of precipitation occurring during the first week. The following break period was both dry and clear, with persistent 10–12 m s−1 wind and evaporation of 0.2 mm h−1. The evolving environmental state included a deepening ocean mixed layer (from ∼20 to 50 m), cooling SST (by ∼1°C), and warming/drying of the lower to midtroposphere. Local atmospheric development was consistent with phasing of the large-scale intraseasonal oscillation. The upper ocean stores significant heat in the BoB, enough to maintain SST above 29°C despite cooling by surface fluxes and ocean mixing. Comparison with reanalysis indicates biases in air–sea fluxes, which may be related to overly cool prescribed SST. Resolution of such biases offers a path toward improved forecasting of transition periods in the monsoon.This work was supported through the U.S. Office of Naval Research’s Departmental Research Initiative: Monsoon Intraseasonal Oscillations in the Bay of Bengal, the Indian Ministry of Earth Science’s Ocean Mixing and Monsoons Program, and the Sri Lankan National Aquatic Resources Research and Development Agency. We thank the Captain and crew of the R/V Thompson for their help in data collection. Surface atmospheric fields included fluxes were quality controlled and processed by the Boundary Layer Observations and Processes Team within the NOAA Physical Sciences Laboratory. Forecast analysis was completed by India Meteorological Department. Drone image was taken by Shreyas Kamat with annotations by Gualtiero Spiro Jaeger. We also recognize the numerous researchers who supported cruise- and land-based measurements. This work represents Lamont-Doherty Earth Observatory contribution number 8503, and PMEL contribution number 5193.2022-04-0

On the future of Argo: A global, full-depth, multi-disciplinary array

The Argo Program has been implemented and sustained for almost two decades, as a global array of about 4000 profiling floats. Argo provides continuous observations of ocean temperature and salinity versus pressure, from the sea surface to 2000 dbar. The successful installation of the Argo array and its innovative data management system arose opportunistically from the combination of great scientific need and technological innovation. Through the data system, Argo provides fundamental physical observations with broad societally-valuable applications, built on the cost-efficient and robust technologies of autonomous profiling floats. Following recent advances in platform and sensor technologies, even greater opportunity exists now than 20 years ago to (i) improve Argo’s global coverage and value beyond the original design, (ii) extend Argo to span the full ocean depth, (iii) add biogeochemical sensors for improved understanding of oceanic cycles of carbon, nutrients, and ecosystems, and (iv) consider experimental sensors that might be included in the future, for example to document the spatial and temporal patterns of ocean mixing. For Core Argo and each of these enhancements, the past, present, and future progression along a path from experimental deployments to regional pilot arrays to global implementation is described. The objective is to create a fully global, top-to-bottom, dynamically complete, and multidisciplinary Argo Program that will integrate seamlessly with satellite and with other in situ elements of the Global Ocean Observing System (Legler et al., 2015). The integrated system will deliver operational reanalysis and forecasting capability, and assessment of the state and variability of the climate system with respect to physical, biogeochemical, and ecosystems parameters. It will enable basic research of unprecedented breadth and magnitude, and a wealth of ocean-education and outreach opportunities