Immune compromise in HIV-1/HTLV-1 coinfection with paradoxical resolution of CD4 lymphocytosis during antiretroviral therapy: a case report

Human immunodeficiency virus type-1 (HIV-1) and human T lymphotropic virus type-1 (HTLV-1) infections have complex effects on adaptive immunity, with specific tropism for, but contrasting effects on, CD4 T lymphocytes: depletion with HIV-1, proliferation with HTLV-1. Impaired T lymphocyte function occurs early in HIV-1 infection but opportunistic infections (OIs) rarely occur in the absence of CD4 lymphopenia. In the unusual case where a HIV-1 infected individual with a high CD4 count presents with recurrent OIs, a clinician is faced with the possibility of a second underlying comorbidity. We present a case of pseudo-adult T cell leukemia/lymphoma (ATLL) in HIV-1/HTLV-1 coinfection where the individual fulfilled Shimoyama criteria for chronic ATLL and had pulmonary Mycobacterium kansasii, despite a high CD4 lymphocyte count. However, there was no evidence of clonal T-cell proliferation by T-cell receptor gene rearrangement studies nor of monoclonal HTLV-1 integration by high-throughput sequencing. Mutually beneficial interplay between HIV-1 and HTLV-1, maintaining high level HIV-1 and HTLV-1 viremia and proliferation of poorly functional CD4 cells despite chronicity of infection is a postulated mechanism. Despite good microbiological response to antimycobacterial therapy, the patient remained systemically unwell with refractory anemia. Subsequent initiation of combined antiretroviral therapy led to paradoxical resolution of CD4 T lymphocytosis as well as HIV-1 viral suppression and decreased HTLV-1 proviral load. This is proposed to be the result of attenuation of immune activation post-HIV virological control. This case illustrates the importance of screening for HTLV-1 in HIV-1 patients with appropriate clinical presentation and epidemiological risk factors and explores mechanisms for the complex interactions on HIV-1/HTLV-1 adaptive immunity

Data base establishment of rice breeding program in Laos

One of the national research priorities is to improve the efficiency of the current breeding and variety testing program in order to accelerate the introduction of better varieties for farmer’s adoption. The database for the rice breeding is the key to achieve the breeding program and would provide valuable scientific information to improve the efficiency of the breeding program for target environments. The objectives of this database were to collect, document and utilize the available data from the national rice breeding program in Laos. Rice breeding program was established at Rice and Cash Crop Research Center in 1991, in collabolation with IRRI, and supported of funding by the government of Switzerland. From 1991 to Philippines and from Thai-IRRI program. Out of 1.627 lines of F2 population, 4 lines were released as TDK and PNG varieties. Out of 64 imported promising lines, 13 lines were released as TDK, TSN, PNG and NTN varieties for different agro climatic zones in Lao PDR. Hybridization at RCCRC was started in 1994, since than, about 272 crosses were made by the Lao breeders. Out of 272 crosses made, so far 8 clones were released as TDK and TSN vareieties and 34 lines were identified as promising lines. Among all parents used in the crossing program at RCCRC, TDK 1 was the dominant parent for evolving promising lines for Lao PDR

Application of local and global sensitivity analysis methods to a north sea hydrodynamic model – study case of sffshore blue mussels and seaweed farms

Increasing demand for marine resources is a significant concern in today's world due to the limited availability of resources and the rapid population growth. The multi-use of offshore platforms has been introduced as a sustainable solution for resource utilization by many countries worldwide. However, researches are still being carried out to check the feasibility of these offshore platforms in aquaculture activities, renewable energy generation, tourism, and many other sectors. Before designing these infrastructures, it is essential to identify the suitable marine environments for each activity based on the required conditions and characteristics of the marine environments. Thus, numerical models play a vital role in simulating these marine environments and consequently will be used as a decision-making tool in feasibility studies and operational activities. The calibration of these numerical models is essential to have more reliable model outputs. However, these numerical models have many inputs parameters and physical variables on which the outputs depend. Sensitivity analysis can reduce the effort to calibrate complex numerical models with many input parameters by identifying the most influential inputs to an output variable. The main objective of the current research was to select the most significant input parameters to two selected outputs of a hydrodynamic model. DCSM is a hydrodynamic model developed for the North Sea by Deltares using the D-Flow FM model suite of Delft3D. Two selected local and global sensitivity analysis methods were applied to the above hydrodynamic model to test the sensitivities of temperature and current velocities to a selected subset of input parameters. The Morris method is used as a screening method to identify the order of the significance of input parameters. The variance-based Sobol’ method was used in global sensitivity analysis for the input parameters screened from the Morris method

Comparación de la dinámica socioeconómica y el desempeño del mercado en las cadenas de valor de la langosta y el camarón gigante de agua dulce en Sri Lanka

Wild-captured lobster fisheries and cultured giant freshwater prawns (GFP) in Sri Lanka cater to high-end markets with significant exports. However, there is a notable gap in existing literature on value chain analysis and market performance aspects in both sectors. This study identified actor profiles and value chain dynamics in both sectors using structural mapping. Market performance was assessed through costs, margins, price spread, and marketing efficiency, with differentiation strategies proposed for sectoral growth. Data collection involved interviewer-administered questionnaires and in-depth interviews with 748 fishers, 44 collectors, and 12 exporters from December 2022 to March 2024. Results highlighted that the lobster value chain was highly export-driven, with a concentration on live trade and premium pricing. Fishers and collectors faced risks from fluctuating stocks and strict regulations, while exporters dealt with logistical and market volatility. Upstream actors often overexploit resources to increase yields, rather than improve quality, leading to unsustainable practices. To mitigate market challenges, actions like promoting products under branding tags such as ‘wild-caught lobster’ and ‘conventionally cultured GFP’, maintaining food safety and quality standards and optimizing logistics are essential for enhancing competitiveness. The GFP sector operates in both domestic and export markets, competing with commodity shrimp. While it provides employment, its financial performance is moderate, limited by high farming costs and pricing competitiveness. Differentiation efforts should focus on sustainable labeling, value-added products, direct exports, and catering to niche markets to boost profitability and reduce dependence on bulk markets.Las pesquerías de langosta silvestre y langostino gigante de agua dulce (GFP) de cultivo en Sri Lanka abastecen a mercados de alta gama con exportaciones significativas. Sin embargo, existe una notable brecha en la literatura sobre el análisis de la cadena de valor y los aspectos del desempeño del mercado en ambos sectores. Este estudio identificó los perfiles de los actores y la dinámica de la cadena de valor en ambos sectores mediante un mapeo estructural. El desempeño del mercado se evaluó a través de costos, márgenes, diferencial de precios y eficiencia de comercialización, y se propusieron estrategias de diferenciación para el crecimiento sectorial. La recopilación de datos incluyó cuestionarios administrados por entrevistadores y entrevistas en profundidad con 748 pescadores, 44 recolectores y 12 exportadores, entre diciembre de 2022 y marzo de 2024. Los resultados destacaron que la cadena de valor de la langosta estaba altamente orientada a la exportación, concentrándose en el comercio de ejemplares vivos y precios prémium. Los pescadores y recolectores se enfrentaban a los riesgos derivados de la fluctuación de las poblaciones y las estrictas regulaciones, mientras que los exportadores lidiaban con la volatilidad logística y del mercado. Los actores aguas arriba a menudo sobreexplotan los recursos para aumentar la producción, en lugar de mejorar la calidad, lo que conduce a prácticas insostenibles. Para mitigar los desafíos del mercado, acciones como la promoción de productos con etiquetas como “langosta silvestre” y “GFP de cultivo convencional”, el mantenimiento de los estándares de inocuidad y calidad alimentaria y la optimización logística son esenciales para mejorar la competitividad. El sector de GFP opera tanto en el mercado nacional como en el de exportación, compitiendo con el camarón comercial. Si bien genera empleo, su rendimiento financiero es moderado, limitado por los altos costos de cultivo y la competitividad de precios. Los esfuerzos de diferenciación deben centrarse en el etiquetado sostenible, los productos con valor añadido, la exportación directa y la atención a nichos de mercado para impulsar la rentabilidad y reducir la dependencia de los mercados a granel.

Federated learning for enhanced sensor reliability of automated wireless networks

Autonomous mobile robots working in-proximity humans and objects are becoming frequent and thus, avoiding collisions becomes important to increase the safety of the working environment. This thesis develops a mechanism to improve the reliability of sensor measurements in a mobile robot network taking into the account of inter-robot communication and costs of faulty sensor replacements. In this view, first, we develop a sensor fault prediction method utilizing sensor characteristics. Then, network-wide cost capturing sensor replacements and wireless communication is minimized subject to a sensor measurement reliability constraint. Tools from convex optimization are used to develop an algorithm that yields the optimal sensor selection and wireless information communication policy for aforementioned problem. Under the absence of prior knowledge on sensor characteristics, we utilize observations of sensor failures to estimate their characteristics in a distributed manner using federated learning. Finally, extensive simulations are carried out to highlight the performance of the proposed mechanism compared to several state-of-the-art methods