A Lanthanide-Complex-Based Ratiometric Luminescent Probe Specific for Peroxynitrite

A lanthanide-complex-based ratiometric luminescence probe specific for peroxynitrite (ONOO-), 4'-(2,4-dimethoxyphenyl)-2,2':6',2 ''-terpyridine- 6,6 ''-diyl]bis(methylenenitrilo)tetrakis-(acetate)-Eu3+/Tb3+ ([Eu3+/Tb3+ (DTTA)]), has been designed and synthesized. Both [Eu3+(DTTA)] and [Tb3+(DTTA)] are highly water soluble with large stability constants at approximate to 10(20), and strongly luminescent with luminescence quantum yields of 10.0 and 9.9%, respectively, and long luminescence lifetimes of 1.38 and 0.26 ms, respectively. It was found that the luminescence of [Tb3+(DTTA)] could be quenched by ONOO- rapidly and specifically in aqueous buffers, while that of [Eu3+(DTTA)] did not respond to the addition of ONOO-. Thus, by simply mixing [Eu3+(DTTA)] and [Tb3+(DTTA)] in an aqueous buffer, a ratiometric luminescence probe specific for time-gated luminescence detection of ONOO- was obtained. The performance of [Tb3+(DTTA).] and [Eu3+/Tb3+(DTTA)] as the probes for luminescence imaging detection of ONOO- in living cells was investigated. The results demonstrated the efficacy and advantages of the new ratiometric luminescence probe for highly sensitive luminescence bioimaging application

Assessing Database Contribution via Distributed Tracing for Microservice Systems

Microservice architecture is the latest trend in software systems development and transformation. In microservice systems, databases are deployed in corresponding services. To better optimize runtime deployment and improve system stability, system administrators need to know the contributions of databases in the system. For the high dynamism and complexity of microservice systems, distributed tracing can be introduced to observe the behavior of business scenarios on databases. However, it is challenging to evaluate the database contribution by combining the importance weight of business scenarios with their behaviors on databases. To solve this problem, we propose a business-scenario-oriented database contribution assessment approach (DBCAMS) via distributed tracing, which consists of three steps: (1) determining the importance weight of business scenarios in microservice system by analytic hierarchy process (AHP); (2) reproducing business scenarios and aggregating the same operations on the same database via distributed tracing; (3) calculating database contribution by formalizing the task as a nonlinear programming problem based on the defined operators and solving it. To the best of our knowledge, our work is the first research to study this issue. The results of a series of experiments on two open-source benchmark microservice systems show the effectiveness and rationality of our proposed method

Assessing Database Contribution via Distributed Tracing for Microservice Systems

Microservice architecture is the latest trend in software systems development and transformation. In microservice systems, databases are deployed in corresponding services. To better optimize runtime deployment and improve system stability, system administrators need to know the contributions of databases in the system. For the high dynamism and complexity of microservice systems, distributed tracing can be introduced to observe the behavior of business scenarios on databases. However, it is challenging to evaluate the database contribution by combining the importance weight of business scenarios with their behaviors on databases. To solve this problem, we propose a business-scenario-oriented database contribution assessment approach (DBCAMS) via distributed tracing, which consists of three steps: (1) determining the importance weight of business scenarios in microservice system by analytic hierarchy process (AHP); (2) reproducing business scenarios and aggregating the same operations on the same database via distributed tracing; (3) calculating database contribution by formalizing the task as a nonlinear programming problem based on the defined operators and solving it. To the best of our knowledge, our work is the first research to study this issue. The results of a series of experiments on two open-source benchmark microservice systems show the effectiveness and rationality of our proposed method

Sustainable and Clean Utilization of Yellow Phosphorus Slag (YPS): Activation and Preparation of Granular Rice Fertilizer

Yellow phosphorus slag (YPS) is a typical industrial solid waste, while it contains abundant silicon micronutrient required for the growth of rice. The key scientific problem to use the YPS as rice fertilizer is how to activate the slag efficiently during the phosphorite reduction smelting process. In this work, an alkaline rice fertilizer from the activated YPS was successfully prepared to use the micronutrients. Thermodynamic analyses of SiO2-CaO, SiO2-CaO-Al2O3, and SiO2-CaO-Al2O3-MgO systems were discussed to optimize the acidity for reduction smelting. Results showed that the reduction smelting followed by the water quenching process can realize the reduction of phosphorite and activation of YPS synchronously. Ternary acidity m(SiO2)/(m(CaO) + m(MgO)) of 0.92 is suitable for the reduction smelting and activation of the slag. After smelting, the molten YPS can be effectively activated by water quenching, and 78.28% P, 90.03% Ca, and 77.12% Si in the YPS are activated, which can be readily absorbed by the rice roots. Finally, high-strength granular rice fertilizers with a particle size of Φ2–4 mm were successfully prepared from the powdery nitrogen-phosphorus-potassium (NPK) and activated YPS mixture

Epidemic Situation of Brucellosis in Jinzhou City of China and Prediction Using the ARIMA Model

Objective. This study aimed to investigate the specific epidemiological characteristics and epidemic situation of brucellosis in Jinzhou City of China so as to establish a suitable prediction model potentially applied as a decision-supportive tool for reasonably assigning health interventions and health delivery. Methods. Monthly morbidity data from 2004 to 2013 were selected to construct the autoregressive integrated moving average (ARIMA) model using SPSS 13.0 software. Moreover, stability analysis and sequence tranquilization, model recognition, parameter test, and model diagnostic were also carried out. Finally, the fitting and prediction accuracy of the ARIMA model were evaluated using the monthly morbidity data in 2014. Results. A total of 3078 cases affected by brucellosis were reported from January 1998 to December 2015 in Jinzhou City. The incidence of brucellosis had shown a fluctuating growth gradually. Moreover, the ARIMA(1,1,1)(0,1,1)12 model was finally selected among quite a few plausible ARIMA models based upon the parameter test, correlation analysis, and Box–Ljung test. Notably, the incidence from 2005 to 2014 forecasted using this ARIMA model fitted well with the actual incidence data. Notably, the actual morbidity in 2014 fell within the scope of 95% confidence limit of values predicted by the ARIMA(1,1,1)(0,1,1)12 model, with the absolute error between the predicted and the actual values in 2014 ranging from 0.02 to 0.74. Meanwhile, the MAPE was 19.83%. Conclusion. It is suitable to predict the incidence of brucellosis in Jinzhou City of China using the ARIMA(1,1,1)(0,1,1)12 model

Core-Shell Nanoarchitectures: A Strategy To Improve the Efficiency of Luminescence Resonance Energy Transfer

The development of core-shell nanoparticles has shown a wide range of new applications in the fields of chemistry, bioscience, and materials science because of their improved physical and chemical properties over their single-component counterparts. In the present work, we took the core-shell nanoarchitectures as an example to research the luminescence resonance energy transfer (LRET) process between a luminescent Tb(3+) chelate, N,N,N(1),N(1)-[4`-phenyl-2,2`:6`,2`-terpyridine-6,6`-diyl]bis(methylenenitrilo)tetrakis(acetate)-Tb(3+) (PTTA-Tb(3+)), and an organic dye, 5-carboxytetramethylrhodamine (CTMR). PTTA-Tb(3+) and CTMR were chosen as the donor-acceptor pair of LRET in our model construction because of their effective spectral overlapping. The core shell nanoparticles featuring a CTMR-SiO(2) core surrounded by a concentric PTTA-Tb(3+)-SiO(2) shell were prepared using a reverse microemulsion method. These nanoparticles are spherical, uniform in size, and highly photostable. The results of LRET experiments show that the sensitized emission lifetime of the acceptor in the nanoparticles is significantly prolonged (similar to 246 mu s), which is attributed to the long emission lifetime of the Tb(3+) chelate donor. According to the results of the steady-state and time-resolved luminescence spectroscopy, an energy transfer efficiency of similar to 80% and a large Forster distance between the donor and the acceptor in the core-shell nanoparticles are calculated, respectively. The new core-shell nanoparticles with a high LRET efficiency and long Forster distance enable them to be promising optical probes for a variety of possible applications such as molecular imaging and multiplex signaling

Table_1_Case report: Enhancing prognosis in severe COVID-19 through human herpes virus coinfection treatment strategies.docx

BackgroundIn the context of increasing reports of co-infection with coronavirus disease 2019 (COVID-19), particularly with human herpes viruses (HHVs), it is important to consider the appropriate treatment options for HHVs that have been reactivated by COVID-19.Case presentationThis study presents two cases of severe COVID-19 with HHV co-infection. The first case involved a critically ill patient with COVID-19 co-infected with herpes simplex virus type 1, confirmed using metagenomic next-generation sequencing, and another patient with severe COVID-19 experiencing Epstein-Barr virus (EBV) reactivation, as evidenced by elevated EBV-DNA levels in the serum. Treatment included high-dose glucocorticoids and sivelestat sodium, with notable improvements observed after initiating ganciclovir anti-herpesvirus therapy.ConclusionThis study underscores the significance of recognizing HHV co-infections in severe COVID-19 cases and highlights the potential of combining anti-HHV treatment, increased glucocorticoid dosages, and anti-cytokine storm therapy to enhance prognosis.</p