BackgroundThe results of randomized controlled studies on aspirin for the prevention of preeclampsia (PE) are conflicting, and some of the related meta-analyses also have limitations or flaws.Data sourcesA search was conducted on PubMed, Embase, and Cochrane Central Register of Controlled Trials databases, with no time or language restrictions.Study eligibility criteriaRandomized controlled studies comparing aspirin for the prevention of PE were conducted.MethodsSystematic reviews were performed according to the Cochrane Manual guidelines. A fixed-effects model or a random-effects model was chosen to calculate pooled relative risks with 95% confidence intervals based on the heterogeneity of the included studies. The study aimed to investigate the effect of aspirin on the development of PE in high-risk and general populations of women. Publication bias was assessed by funnel plots. All included studies were assessed for bias by the Cochrane Manual of Bias Assessment. Subgroup analyses were conducted on the aspirin dose, time of initial aspirin intervention, and the region in which the research was conducted, to explore the effective dose of aspirin and time of initial aspirin intervention and to try to find sources of heterogeneity and publication bias.ResultsA total of 39 articles were included, including 29 studies involving pregnant women at high risk for PE (20,133 patients) and 10 studies involving a general population of pregnant women (18,911 patients). Aspirin reduced the incidence of PE by 28% (RR 0.72, 95% CI 0.62–0.83) in women at high risk for PE. Aspirin reduced the incidence of PE by 30% in the general population (RR 0.70, 95% CI 0.52–0.95), but sensitivity analyses found that aspirin in the general population was not robust. A subgroup analysis showed that an aspirin dose of 75 mg/day (RR 0.50, 95% CI 0.32–0.78) had a better protective effect than other doses. Starting aspirin at 12–16 weeks (RR 0.62, 95% CI 0.53–0.74) of gestation or 17–28 weeks (RR 0.62, 95% CI 0.44–0.89) reduced the incidence of PE by 38% in women at high risk for PE, but the results were more reliable for use at 12–16 weeks. Heterogeneity and publication bias of the included studies may be mainly due to the studies completed in Asia.ConclusionAspirin is recommended to be started at 12–16 weeks of pregnancy in women at high risk for PE. The optimal dose of aspirin to use is 75 mg/d.Systematic review registration[www.ClinicalTrials.gov], identifier [CRD42022319984].
This
work pertains to a novel continuous column process for As(III)
oxidation using commercial activated carbon as a promising catalyst
in acidic solutions on a minipilot scale. Notable efficiency of arsenic
oxidation is validated in continuous column tests treating 5 g/L As(III)
acidic solutions with activated carbon in the presence of oxygen.
Residence time, pH, dissolved oxygen, and initial As(III) concentration
are proved to be the significant impacting parameters on the arsenic
oxidation process. Insights into the oxidation pathway by Fourier-transform
infrared (FTIR) spectroscopy and X-ray photoelectron spectroscopy
(XPS) illustrate that the efficient oxidation of arsenic is attributed
to the ample oxygen functionalities on the carbon surfaces, which
play a role in the in situ formation of hydrogen peroxide. This study
provides a promising process for the application of activated carbon
in arsenic oxidation from highly concentrated arsenic waste solutions
in the mining and metal industries.
Abstract. In this paper, a novel algorithm is introduced to group contours from clutter images by integrating high-level information (prior of part segments) and low-level information (edges of segmentations of clutter images). The partial shape similarity between these two levels of information is embedded into the particle filter framework, an effective recursively estimating model. The particles in the framework are modeled as the paths on the edges of segmentation results by Normalized Cuts. At prediction step, the paths extend along the edges of Normalized Cuts; while, at the update step, the weights of particles update according to their partial shape similarity with priors of the trained contour segments. Successful results are achieved against the noise of the testing image, the inaccuracy of the segmentation result as well as the inexactness of the similarity between the contour segment and edges segmentation. The experimental results also demonstrate robust contour grouping performance in the presence of occlusion and large texture variation within the segmented objects.
In recent years, due to the accelerated pace of life and increased life stress, more and more people are stepping into subhealthy state, which has caused widespread concern in the society. This project aims to analyze the footprint stress image, extract some of the footprint characteristic values from it, use the multi-dimensional health indices such as BMI, Broca's formula, body fat percentage to assess the human health level, analyze the user's physical health to output data, including height, weight, BMI, standard weight, body fat percentage, body posture assessment, in order to provide some implications for the field of health detection through footprint pressure images.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.