Tafel Slope Plot as a Tool to Analyze Electrocatalytic Reactions
Ontology highlight
ABSTRACT:
SUBMITTER:
PROVIDER: S-EPMC11019648 | biostudies-literature | 2024 Apr
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Next-generation sequencing and metabolomics have become very cost and work efficient and are integrated into an ever-growing number of life science research projects. Typically, established software pipelines analyze raw data and produce quantitative data informing about gene expression or concentrations of metabolites. These results need to be visualized and further analyzed in order to support scientific hypothesis building and identification of underlying biological patterns. Some of these tools already exist, but require installation or manual programming. We developed "Gene Expression Plotter" (GXP), an RNAseq and Metabolomics data visualization and analysis tool entirely running in the user's web browser, thus not needing any custom installation, manual programming or uploading of confidential data to third party servers. Consequently, upon receiving the bioinformatic raw data analysis of RNAseq or other omics results, GXP immediately enables the user to interact with the data according to biological questions by performing knowledge-driven, in-depth data analyses and candidate identification via visualization and data exploration. Thereby, GXP can support and accelerate complex interdisciplinary omics projects and downstream analyses. GXP offers an easy way to publish data, plots, and analysis results either as a simple exported file or as a custom website. GXP is freely available on GitHub (see introduction).
| S-EPMC8952246 | biostudies-literature
Project description:The Tafel slope represents a critical kinetic parameter for mechanistic studies of electrochemical reactions, including the hydrogen evolution reaction (HER). Linear fitting of the polarization curve in a N2-saturated electrolyte is commonly used to determine Tafel slopes, which is, however, frequently plagued with inconsistencies. Our systematic studies reveal that the Tafel slopes derived from this approach are loading- and potential-dependent, and could substantially exceed the theoretical limits. Our analyses indicate that this discrepancy is largely attributed to the locally trapped HER-generated H2 in the catalyst layer. A non-negligible hydrogen oxidation reaction (HOR) current more prominently offsets the HER current at the smaller HER overpotential regime, resulting in an artificially smaller Tafel slope. On the other hand, at the higher overpotential where the HOR current becomes negligible, the locally trapped H2 substantially suppresses further HER current growth, leading to an artificially larger Tafel slope. The Butler-Volmer method accounts for both the HER and HOR currents in the fitting, which offers a more reliable method for pure Pt catalysts but is less applicable to transition-metal decorated Pt surfaces with distinct HER/HOR kinetics. Our studies underscore the challenges in Tafel slope analysis and the need for strict controls for reliable comparisons among different catalyst systems.
| S-EPMC10979421 | biostudies-literature
Project description:Networks are widely used to represent relationships between objects, including microorganisms within ecosystems, based on high-throughput sequencing data. However, challenges arise with appropriate statistical algorithms, handling of rare taxa, excess zeros in compositional data, and interpretation. This work introduces a novel Slope-Matrix-Graph (SMG) algorithm to identify microbiome correlations primarily based on slope-based distance calculations. SMG effectively handles any proportion of zeros in compositional data and involves: (1) searching for correlated relationships (e.g., positive and negative directions of changes) based on a "target of interest" within a setting, and (2) quantifying graph changes via slope-based distances between objects. Evaluations on simulated datasets demonstrated SMG's ability to accurately cluster microbes into distinct positive/negative correlation groups, outperforming methods like Bray-Curtis and SparCC in both sensitivity and specificity. Moreover, SMG demonstrated superior accuracy in detecting differential abundance (DA) compared to ZicoSeq and ANCOM-BC2, making it a robust tool for microbiome analysis. A key advantage is SMG's natural capacity to analyze zero-inflated compositional data without transformations. Overall, this simple yet powerful algorithm holds promise for diverse microbiome analysis applications.
| S-EPMC11434172 | biostudies-literature
Project description: Not available
| S-EPMC9638995 | biostudies-literature
Project description:Live-cell imaging has become state of the art to accurately identify the nature of mitotic and cell cycle defects. Low- and high-throughput microscopy setups have yield huge data amounts of cells recorded in different experimental and pathological conditions. Tailored semi-automated and automated image analysis approaches allow the analysis of high-content screening data sets, saving time and avoiding bias. However, they were mostly designed for very specific experimental setups, which restricts their flexibility and usability. The general need for dedicated experiment-specific user-annotated training sets and experiment-specific user-defined segmentation parameters remains a major bottleneck for fully automating the analysis process. In this work we present LiveCellMiner, a highly flexible open-source software tool to automatically extract, analyze and visualize both aggregated and time-resolved image features with potential biological relevance. The software tool allows analysis across high-content data sets obtained in different platforms, in a quantitative and unbiased manner. As proof of principle application, we analyze here the dynamic chromatin and tubulin cytoskeleton features in human cells passing through mitosis highlighting the versatile and flexible potential of this tool set.
| S-EPMC9262191 | biostudies-literature
Project description:The action of various DNA topoisomerases frequently results in characteristic changes in DNA topology. Important information for understanding mechanistic details of action of these topoisomerases can be provided by investigating the knot types resulting from topoisomerase action on circular DNA forming a particular knot type. Depending on the topological bias of a given topoisomerase reaction, one observes different subsets of knotted products. To establish the character of topological bias, one needs to be aware of all possible topological outcomes of intersegmental passages occurring within a given knot type. However, it is not trivial to systematically enumerate topological outcomes of strand passage from a given knot type. We present here a 3D visualization software (TopoICE-X in KnotPlot) that incorporates topological analysis methods in order to visualize, for example, knots that can be obtained from a given knot by one intersegmental passage. The software has several other options for the topological analysis of mechanisms of action of various topoisomerases.
| S-EPMC2441796 | biostudies-literature
Project description:The "solid catalyst with ionic liquid layer" (SCILL) is an extremely successful new concept in heterogeneous catalysis. The idea is to boost the selectivity of a catalyst by its modification with an ionic liquid (IL). Here, we show that it is possible to use the same concept in electrocatalysis for the selective transformation of organic compounds. We scrutinize the electrooxidation of 2,3-butanediol, a reaction which yields two products, singly oxidized acetoin and doubly oxidized diacetyl. When adding the IL (1-ethyl-3-methyl-imidazolium trifluormethanesulfonate, [C2 C1 Im][OTf]), the selectivity for acetoin increases drastically. By in situ spectroscopy, we analyze the underlying mechanism: Specific adsorption of the IL anions suppresses the activation of water for the second oxidation step and, thus, enhances the selectivity for acetoin. Our study demonstrates the great potential of this approach for selective transformation of organic compounds.
| S-EPMC9400977 | biostudies-literature
Project description:Funnel plots have been widely used to detect small-study effects in the results of univariate meta-analyses. However, there is no existing visualization tool that is the counterpart of the funnel plot in the multivariate setting. We propose a new visualization method, the galaxy plot, which can simultaneously present the effect sizes of bivariate outcomes and their standard errors in a 2-dimensional space. We illustrate the use of the galaxy plot with 2 case studies, including a meta-analysis of hypertension trials with studies from 1979-1991 (Hypertension. 2005;45(5):907-913) and a meta-analysis of structured telephone support or noninvasive telemonitoring with studies from 1966-2015 (Heart. 2017;103(4):255-257). The galaxy plot is an intuitive visualization tool that can aid in interpreting results of multivariate meta-analysis. It preserves all of the information presented by separate funnel plots for each outcome while elucidating more complex features that may only be revealed by examining the joint distribution of the bivariate outcomes.
| S-EPMC7438574 | biostudies-literature
Project description:MotivationTag density plots are very important to intuitively reveal biological phenomena from capture-based sequencing data by visualizing the normalized read depth in a region.ResultsWe have developed iTagPlot to compute tag density across functional features in parallel using multicores and a grid engine and to interactively explore it in a graphical user interface. It allows us to stratify features by defining groups based on biological function and measurement, summary statistics and unsupervised clustering.Availability and implementationhttp://sourceforge.net/projects/itagplot/.
| S-EPMC4495303 | biostudies-literature
Project description:BackgroundCommonly, several traits are assessed in agronomic experiments to better understand the factors under study. However, it is also common to see that even when several traits are available, researchers opt to follow the easiest way by applying univariate analyses and post-hoc tests for mean comparison for each trait, which arouses the hypothesis that the benefits of a multi-trait framework analysis may have not been fully exploited in this area.ResultsIn this paper, we extended the theoretical foundations of the multi-trait genotype-ideotype distance index (MGIDI) to analyze multivariate data either in simple experiments (e.g., one-way layout with few treatments and traits) or complex experiments (e.g., with a factorial treatment structure). We proposed an optional weighting process that makes the ranking of treatments that stands out in traits with higher weights more likely. Its application is illustrated using (1) simulated data and (2) real data from a strawberry experiment that aims to select better factor combinations (namely, cultivar, transplant origin, and substrate mixture) based on the desired performance of 22 phenological, productive, physiological, and qualitative traits. Our results show that most of the strawberry traits are influenced by the cultivar, transplant origin, cultivation substrates, as well as by the interaction between cultivar and transplant origin. The MGIDI ranked the Albion cultivar originated from Imported transplants and the Camarosa cultivar originated from National transplants as the better factor combinations. The substrates with burned rice husk as the main component (70%) showed satisfactory physical proprieties, providing higher water use efficiency. The strengths and weakness view provided by the MGIDI revealed that looking for an ideal treatment should direct the efforts on increasing fruit production of Albion transplants from Imported origin. On the other hand, this treatment has strengths related to productive precocity, total soluble solids, and flesh firmness.ConclusionsOverall, this study opens the door to the use of MGIDI beyond the plant breeding context, providing a unique, practical, robust, and easy-to-handle multi-trait-based framework to analyze multivariate data. There is an exciting possibility for this to open up new avenues of research, mainly because using the MGIDI in future studies will dramatically reduce the number of tables/figures needed, serving as a powerful tool to guide researchers toward better treatment recommendations.
| S-EPMC9652799 | biostudies-literature