A global pandemic has been declared for coronavirus disease 2019 (COVID-19), which has serious impacts on human health and healthcare systems in the affected areas, including Vietnam. None of the ...previous studies have a framework to provide summary statistics of the virus variants and assess the severity associated with virus proteins and host cells in COVID-19 patients in Vietnam. In this paper, we comprehensively investigated SARS-CoV-2 variants and immune responses in COVID-19 patients. We provided summary statistics of target sequences of SARS-CoV-2 in Vietnam and other countries for data scientists to use in downstream analysis for therapeutic targets. For host cells, we proposed a predictive model of the severity of COVID-19 based on public datasets of hospitalization status in Vietnam, incorporating a polygenic risk score. This score uses immunogenic SNP biomarkers as indicators of COVID-19 severity. We identified that the Delta variant of SARS-CoV-2 is most prevalent in southern areas of Vietnam and it is different from other areas in the world using various data sources. Our predictive models of COVID-19 severity had high accuracy (Random Forest AUC = 0.81, Elastic Net AUC = 0.7, and SVM AUC = 0.69) and showed that the use of polygenic risk scores increased the models' predictive capabilities. We provided a comprehensive analysis for COVID-19 severity in Vietnam. This investigation is not only helpful for COVID-19 treatment in therapeutic target studies, but also could influence further research on the disease progression and personalized clinical outcomes.
New neutral nickel and palladium ethylene polymerization catalysts have been prepared that incorporate an anionic (N,O) chelating ligand. Extensive axial shielding is provided by two 3,5-dichloroaryl ...moieties in a “sandwich” orientation. Such shielding results in an exceptionally slow rate of chain transfer relative to migratory insertion in the nickel catalyst, and thus highly controlled polymerization of ethylene is observed, leading to lightly branched ultra-high molecular weight polyethylene with M n values up to 4.1 × 106 g/mol. The analogous palladium catalysts provide the means for a detailed mechanistic study of chain propagation in an electronically asymmetric neutral palladium catalyst. Both isomers of the methyl ethylene complex can be generated and observed at low temperatures allowing experimental elucidation of mechanistic details of chain propagation probed in other electronically asymmetric systems only through DFT studies or by examination of model studies. The barrier to migratory insertion in these complexes is ca. 19.2 kcal/mol. Investigation of the equilibration of the methyl ethylene isomers in the presence of excess ethylene showed the isomerization rate is dependent on ethylene concentration. This is the first direct proof that isomerization in these alkyl ethylene intermediates is catalyzed by ethylene. Furthermore, isomer equilibration is much faster than migratory insertion so that the barriers for insertion of individual isomers cannot be determined.
Difficulties in dewatering of biosludge result in economical and environmental issues for wastewater treatment plants. Various attempts have been made to overcome this problem by achieving some ...pretreatment on biosludge. The main purpose of all pretreatment methods is to modify the biosludge characteristics in such a way to boost settling of cells and solid particles of sludge, and to ease the release of water molecules from extracellular polymeric substances and cells and to facilitate flow of water through forming filter cake. The present work presents an overview of different properties of sludge and their measurement, the main reasons of sludge dewatering difficulty, the fundamentals of sludge dewatering and various proposed methods for sludge pretreatment. The advantages and drawbacks of different methods are described and the dominance of one over the others is discussed mostly with respect to energy requirement and environmental impacts. Some recommendations have been made for optimal application of each method.
•A state of the art review that describes the fundamental properties of biosludge related to water.•Review of the main methods to measure the types of water contained in biosludge.•Comparison of the pretreatment methods to dewater biosludges on their own and in combination with primary solids.
Type 1 diabetes (T1D) is an autoimmune disease, characterized by the presence of autoantibodies to protein and non-protein antigens. Here we report the identification of specific anti-carbohydrate ...antibodies (ACAs) that are associated with pathogenesis and progression to T1D. We compare circulatory levels of ACAs against 202 glycans in a cross-sectional cohort of T1D patients (n = 278) and healthy controls (n = 298), as well as in a longitudinal cohort (n = 112). We identify 11 clusters of ACAs associated with glycan function class. Clusters enriched for aminoglycosides, blood group A and B antigens, glycolipids, ganglio-series, and O-linked glycans are associated with progression to T1D. ACAs against gentamicin and its related structures, G418 and sisomicin, are also associated with islet autoimmunity. ACAs improve discrimination of T1D status of individuals over a model with only clinical variables and are potential biomarkers for T1D.
The World Health Organization has set ambitious targets for the global elimination of tuberculosis. However, these targets will not be achieved at the current rate of progress.
We performed a ...cluster-randomized, controlled trial in Ca Mau Province, Vietnam, to evaluate the effectiveness of active community-wide screening, as compared with standard passive case detection alone, for reducing the prevalence of tuberculosis. Persons 15 years of age or older who resided in 60 intervention clusters (subcommunes) were screened for pulmonary tuberculosis, regardless of symptoms, annually for 3 years, beginning in 2014, by means of rapid nucleic acid amplification testing of spontaneously expectorated sputum samples. Active screening was not performed in the 60 control clusters in the first 3 years. The primary outcome, measured in the fourth year, was the prevalence of microbiologically confirmed pulmonary tuberculosis among persons 15 years of age or older. The secondary outcome was the prevalence of tuberculosis infection, as assessed by an interferon gamma release assay in the fourth year, among children born in 2012.
In the fourth-year prevalence survey, we tested 42,150 participants in the intervention group and 41,680 participants in the control group. A total of 53 participants in the intervention group (126 per 100,000 population) and 94 participants in the control group (226 per 100,000) had pulmonary tuberculosis, as confirmed by a positive nucleic acid amplification test for
(prevalence ratio, 0.56; 95% confidence interval CI, 0.40 to 0.78; P<0.001). The prevalence of tuberculosis infection in children born in 2012 was 3.3% in the intervention group and 2.6% in the control group (prevalence ratio, 1.29; 95% CI, 0.70 to 2.36; P = 0.42).
Three years of community-wide screening in persons 15 years of age or older who resided in Ca Mau Province, Vietnam, resulted in a lower prevalence of pulmonary tuberculosis in the fourth year than standard passive case detection alone. (Funded by the Australian National Health and Medical Research Council; ACT3 Australian New Zealand Clinical Trials Registry number, ACTRN12614000372684.).
The coexistence of multiple toxic water pollutants (heavy metals, organic dyes, oils, and organic solvents) limits the sustainable supply of clean water worldwide and urges the development of ...advanced water purification technology that can remove these contaminants simultaneously. Since its discovery, graphene‐based materials have gained substantial attention toward development of new‐generation sorbents for water purification. Despite several recently published reviews on water purification technology using graphene and its derivatives, there is still a gap in the review considering multiple water‐pollutant remediation using advanced graphene materials. In this review, in the first instance, a comparative structure–function–performance relationship between graphene‐based sorbents and the multipollutants in water is established. A fundamental correlation is made between the sorption performance for diverse pollutants in water with the more specific adsorption properties (surface area, pore size, type of functional groups, C/O, C/N, and C/S atomic ratio) of advanced graphene sorbents. Second, the underlying interaction mechanisms are uncovered between different classes of water pollutants using single graphene‐based sorbents. Third, the rational design of advanced multipollutant sorbents based on graphene is elaborated. The reality, challenges, and opportunities of advanced graphene materials as emerging sorbents for sustainable water purification technology are finally presented in the last section.
Herein, the recent development of graphene‐based sorbents for the uptake of multipollutants are reviewed to establish a structure‐function‐performance relationship based on graphene doping and its functionalization. A link is made between the adsorption properties with the sorption performance of advanced graphene sorbents with multipollutants. The reality, challenges, and opportunities for advanced graphene materials as sustainable water purification technology are highlighted.
In this paper, a label-free and reagentless microRNA sensor based on an interpenetrated network of carbon nanotubes and electroactive polymer is described. The nanostructured polymer film presents ...very well-defined electroactivity in neutral aqueous medium in the cathodic potential domain from the quinone group embedded in the polymer backbone. Addition of microRNA miR-141 target (prostate cancer biomarker) gives a “signal-on” response, i.e. a current increase due to enhancement of the polymer electroactivity. On the contrary, non-complementary miRNAs such as miR-103 and miR-29b-1 do not lead to any significant current change. A very low detection limit of ca. 8fM is achieved with this sensor.
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•MicroRNA detection.•Label-free and direct electrochemical detection.•Conducting polymer nanostructured by carbon nanotubes.•Prostate cancer biomarker miR-141.
Federated learning (FL) rests on the notion of training a global model in a decentralized manner. Under this setting, mobile devices perform computations on their local data before uploading the ...required updates to improve the global model. However, when the participating clients implement an uncoordinated computation strategy, the difficulty is to handle the communication efficiency (i.e., the number of communications per iteration) while exchanging the model parameters during aggregation. Therefore, a key challenge in FL is how users participate to build a high-quality global model with communication efficiency. We tackle this issue by formulating a utility maximization problem, and propose a novel crowdsourcing framework to leverage FL that considers the communication efficiency during parameters exchange. First, we show an incentive-based interaction between the crowdsourcing platform and the participating client's independent strategies for training a global learning model, where each side maximizes its own benefit. We formulate a two-stage Stackelberg game to analyze such scenario and find the game's equilibria. Second, we formalize an admission control scheme for participating clients to ensure a level of local accuracy. Simulated results demonstrate the efficacy of our proposed solution with up to 22% gain in the offered reward.
In this paper, we study the resource slicing problem in a dynamic multiplexing scenario of two distinct 5G services, namely Ultra-Reliable Low Latency Communications (URLLC) and enhanced Mobile ...BroadBand (eMBB). While eMBB services focus on high data rates, URLLC is very strict in terms of latency and reliability. In view of this, the resource slicing problem is formulated as an optimization problem that aims at maximizing the eMBB data rate subject to a URLLC reliability constraint, while considering the variance of the eMBB data rate to reduce the impact of immediately scheduled URLLC traffic on the eMBB reliability. To solve the formulated problem, an optimization-aided Deep Reinforcement Learning (DRL) based framework is proposed, including: 1) eMBB resource allocation phase , and 2) URLLC scheduling phase . In the first phase, the optimization problem is decomposed into three subproblems and then each subproblem is transformed into a convex form to obtain an approximate resource allocation solution. In the second phase, a DRL-based algorithm is proposed to intelligently distribute the incoming URLLC traffic among eMBB users. Simulation results show that our proposed approach can satisfy the stringent URLLC reliability while keeping the eMBB reliability higher than 90%.
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