A statistical comparison of platinum plant digestion data obtained from GFAAS and ICP-OES

To date, to our knowledge there have not been reports on the comparison between Graphite Furnace Atomic Absorption Spectroscopy (GFAAS) and Inductively Coupled Plasma Optical Emission Spectroscopy (ICPOES) for the determination of low levels of platinum. Although GFAAS and ICP-OES are very different instrumental techniques, the analysis of environmental platinum plant digestion samples showed that there was no significant difference between the two techniques at the 95% confidence interval. The result of the variance tests or F-test was much smaller than the tabulated F-test value. The F-test values obtained for the analysis ranged from 0.00 to 2.67 and the tabulated value was 19.16. In addition, a comparison of the means at the 95% confidence interval showed that the means obtained for each sample were not significantly different. The values obtained by the comparison ranged from 1.63 to 0.039 and the tabulated Student\u27s t-test value was 3.182

Tracking species recovery status to improve U.S. endangered species act decisions

Abstract Currently 1677 species are listed under the U.S. Endangered Species Act (ESA), yet only a small percentage have been delisted due to recovery. In the fall of 2021, the U.S. Fish and Wildlife Service proposed delisting 23 species due to extinction. Tracking changes in species ‘recovery status over time is critical to understanding species’ statuses, informing adaptive management strategies, and assessing the performance of the ESA to prevent further species loss. In this paper, we describe four key obstacles in tracking species recovery status under the ESA. First, ESA 5‐year reviews lack a standardized format and clear documentation. Second, despite having been listed for decades, many species still suffer major data gaps in their biology and threats, rendering it difficult if not impossible to track progress towards recovery. Third, many species have continued declining after listing, yet given the above (1 & 2), understanding potential causes (proximate and/or ultimate) can be difficult. Fourth, many species currently have no path to clear recovery, which represents a potential failing of the process. We conclude with a discussion of potential policy responses that could be addressed to enhance the efficacy of the ESA

Tracking Species Recovery Status to Improve Endangered Species Act Decisions

The U.S. Endangered Species Act (ESA) protects over 2,000 species, but no concise, standardized metrics exist for assessing changes in species recovery status. Tracking these changes is crucial to understanding species status, adjusting conservation strategies, and assessing the performance of the ESA. We helped develop and test novel metrics that track changes in recovery status using six components. ESA 5-year status reviews provided all of the information used to apply the recovery metrics. When we analyzed the reviews, we observed several key challenges to species recovery. First, the reviews lack a standardized format and clear documentation. Second, despite having been listed for decades, many species still lack basic information about their biology and threats. Third, many species have continued to decline after listing. Fourth, many species currently have no path to recovery. Applying the recovery metrics allowed us to gain these and other insights about ESA implementation. We urge the U.S. Fish and Wildlife Service to adopt the metrics as part of future status reviews in order to inform public discourse on improving conservation policy and to systematically track the recovery progress of all ESA species

Parameter Trajectory Analysis to Identify Treatment Effects of Pharmacological Interventions

<p>The field of medical systems biology aims to advance understanding of molecular mechanisms that drive disease progression and to translate this knowledge into therapies to effectively treat diseases. A challenging task is the investigation of long-term effects of a (pharmacological) treatment, to establish its applicability and to identify potential side effects. We present a new modeling approach, called Analysis of Dynamic Adaptations in Parameter Trajectories (ADAPT), to analyze the long-term effects of a pharmacological intervention. A concept of time-dependent evolution of model parameters is introduced to study the dynamics of molecular adaptations. The progression of these adaptations is predicted by identifying necessary dynamic changes in the model parameters to describe the transition between experimental data obtained during different stages of the treatment. The trajectories provide insight in the affected underlying biological systems and identify the molecular events that should be studied in more detail to unravel the mechanistic basis of treatment outcome. Modulating effects caused by interactions with the proteome and transcriptome levels, which are often less well understood, can be captured by the time-dependent descriptions of the parameters. ADAPT was employed to identify metabolic adaptations induced upon pharmacological activation of the liver X receptor (LXR), a potential drug target to treat or prevent atherosclerosis. The trajectories were investigated to study the cascade of adaptations. This provided a counter-intuitive insight concerning the function of scavenger receptor class B1 (SR-B1), a receptor that facilitates the hepatic uptake of cholesterol. Although activation of LXR promotes cholesterol efflux and -excretion, our computational analysis showed that the hepatic capacity to clear cholesterol was reduced upon prolonged treatment. This prediction was confirmed experimentally by immunoblotting measurements of SR-B1 in hepatic membranes. Next to the identification of potential unwanted side effects, we demonstrate how ADAPT can be used to design new target interventions to prevent these.</p>