Do Spectra Live in the Matrix? A Brief Tutorial on Applications of Factor Analysis to Resolving Spectral Datasets of Mixtures

In spite of a rapid growth of data processing software, that has allowed for a huge advancement in many fields of chemistry, some research issues still remain problematic. A standard example of a troublesome challenge is the analysis of multi-component mixtures. The classical approach to such a problem consists of separating each component from a sample and performing individual measurements. The advent of computers, however, gave rise to a relatively new domain of data processing – chemometry – focused on decomposing signal recorded for the sample rather than the sample itself. Regrettably, still a very few chemometric methods are practically used in everyday laboratory routines. The Authors believe that a brief ‘user-friendly’ guide-like article on several ‘flagship’ algorithms of chemometrics may, at least partly, stimulate an increased interest in the use of these techniques among researchers specializing in many fields of chemistry. In the paper, five different techniques of factor analysis are used for the analysis of a three-component system of fluorophores. These algorithms, applied on the excitation-emission spectra, recorded for the ‘unknown’ mixture, allowed to unambiguously determine its composition without the need for physical separation of the components. An example of using chemometric methods for physical chemistry research is also provided. For each presented technique of the data analysis, a short description of its theoretical background followed by an example of its practical performance is given. In addition, the Reader is supplemented with a basic information on matrix algebra, detailed experimental ‘recipes’, reference specialist literature and ready-to-use MATLAB codes. Graphical abstract

Detection of Specific Components in a PCA Mixture

Taking a given mixture as an example, 25,000 samples were selected for the detection of 7 indicators. Firstly, the correlation between each indicator and the test result is analyzed, The T test is used to identify the main indicators that can be used to determine the existence of a specific component. Secondly, three comprehensive indexes are obtained by combining PCA. Determine whether there are specific components in the unknown mixture.

4497 Accessible False Discovery Rate Computation

OBJECTIVES/GOALS: To improve the implementation of FDRs in translation research. Current statistical packages are hard to use and fail to adequately convey strong assumptions. We developed a software package that allows the user to decide on assumptions and choose the hey desire. We encourage wider reporting of FDRs for observed findings. METHODS/STUDY POPULATION: We developed a user-friendly R function for computing FDRs from observed p-values. A variety of methods for FDR estimation and for FDR control are included so the user can select the approach most appropriate for their setting. Options include Efron’s Empirical Bayes FDR, Benjamini-Hochberg FDR control for multiple testing, Lindsey’s method for smoothing empirical distributions, estimation of the mixing proportion, and central matching. We illustrate the important difference between estimating the FDR for a particular finding and adjusting a hypothesis test to control the false discovery propensity. RESULTS/ANTICIPATED RESULTS: We performed a comparison of the capabilities of our new p.fdr function to the popular p.adjust function from the base stats-package. Specifically, we examined multiple examples of data coming from different unknown mixture distributions to highlight the null estimation methods p.fdr includes. The base package does not provide the optimal FDR usage nor sufficient estimation options. We also compared the step-up/step-down procedure used in adjusted p-value hypothesis test and discuss when this is inappropriate. The p.adjust function is not able to report raw-adjusted values and this will be shown in the graphical results. DISCUSSION/SIGNIFICANCE OF IMPACT: FDRs reveal the propensity for an observed result to be incorrect. FDRs should accompany observed results to help contextualize the relevance and potential impact of research findings. Our results show that previous methods are not sufficient rich or precise in their calculations. Our new package allows the user to be in control of the null estimation and step-up implementation when reporting FDRs.

Combining laser microdissection and microRNA expression profiling to unmask microRNA signatures in complex tissues

Neglecting tissue heterogeneity during the analysis of microRNA (miRNA) levels results in average signals from an unknown mixture of different cell types that are difficult to interpret. Here we demonstrate the technical requirements needed to obtain high-quality, quantitative miRNA expression information from tumor tissue compartments obtained by laser microdissection (LMD). Furthermore, we show the significance of disentangling tumor tissue heterogeneity by applying the newly developed protocols for combining LMD of tumor tissue compartments with RT-qPCR analysis to reveal compartment-specific miRNA expression signatures. An important advantage of this strategy is that the miRNA signature can be directly linked to histopathology. In summary, combining LMD and RT-qPCR is a powerful approach for spatial miRNA expression analysis in complex tissues, enabling discovery of disease mechanisms, biomarkers and drug candidates.

Task-Evoked Functional Connectivity Does Not Explain Functional Connectivity Differences Between Rest and Task Conditions

During complex tasks, patterns of functional connectivity (FC) differ from those in the resting state. What accounts for such differences remains unclear. Brain activity during a task reflects an unknown mixture of spontaneous activity and task-evoked responses. The difference in FC between a task state and resting state may reflect not only task-evoked connectivity, but also changes in spontaneously emerging networks. Here, we characterized the difference in apparent functional connectivity between the resting state and when human subjects were watching a naturalistic movie. Such differences were marginally (3-15%) explained by the task-evoked networks directly involved in processing the movie content, but mostly attributable to changes in spontaneous networks driven by ongoing activity during the task. The execution of the task reduced the correlations in ongoing activity among different cortical networks, especially between the visual and non-visual sensory cortices. Our results suggest that the interaction between spontaneous and task-evoked activities is not mutually independent or linearly additive, and that engaging in a task may suppress ongoing activity.

The Specific Aspects of Fuel Assessment by Fingerprint Method

We have tested typical samples of fuel (diesel, gasoline, technical gasoline and a mixture of unknown fuel). For fuel analysis we have used an analyzer IROX DIESE with an in-built infrared interferometer of Michelsons type. The results proved that within a wavemeter from 650 up to 1800 cm-1for each fuel is typical infrared spectrum. This spectrum can be compared with human fingerprints. It is possible to positively identify the majority of fuels with usage of these spectra. Moreover in case of unknown mixture, it is possible to use these spectra for determination of their mutual ratio.

Perfect posterior simulation for mixture and hidden Markov models

In this paper we present an application of the read-once coupling from the past algorithm to problems in Bayesian inference for latent statistical models. We describe a method for perfect simulation from the posterior distribution of the unknown mixture weights in a mixture model. Our method is extended to a more general mixture problem, where unknown parameters exist for the mixture components, and to a hidden Markov model.

Accurate Lacustrine and Wetland Sediment Accumulation Rates Determined from 14C Activity of Bulk Sediment Fractions

In the absence of identifiable macrofossils in lacustrine sediments, radiocarbon dating must rely on pollen or bulk sediment fractions. Bulk sediment fractions are not generally preferred because they contain an unknown mixture of organic material of variable age, they may contain dead carbon such as lignite that is difficult to eliminate, and material of aquatic origin may be subject to reservoir effects. If the various processes that contribute carbon to the system are relatively constant over time, however, changes in 14C activity with depth may be used to accurately estimate sediment accumulation rates even if the absolute ages are erroneous. In this study, fine-grained fractions (250–710 μm organic material, humic acids extracted from <250-μm fraction, and untreated <250-μm fraction combusted at low temperature) were analyzed and compared with terrestrial plant stems (twigs), charcoal, and wood fragments in sediments from an oxbow lake in Mississippi, USA. The 14C activities of the bulk fractions were highly linear with depth and produced consistent calculated sediment accumulation rates similar to, and perhaps more reliable than, rates determined using twigs or charcoal.

Effects of Common Viruses on Yield and Quality of Beauregard Sweetpotato in Louisiana

During cycles of vegetative propagation, sweetpotato accumulates viruses that are thought to contribute to decline in yield and quality of cultivars, but the effects of specific viruses, many of which have been described only recently, are unknown. Field plots planted with graft-inoculated plants of a virus-tested (VT) mericlone of cv. Beauregard were used to assess the effects of three common potyviruses, Sweet potato feathery mottle virus (SPFMV), Sweet potato virus G (SPVG), and Ipomoea vein mosaic virus (IVMV); and a begomovirus, Sweet potato leaf curlvirus (SPLCV), compared with natural inoculum introduced by grafting plants from farmers' stock. Single infections with SPFMV, SPVG, or IVMV did not significantly affect yield, whereas mixed infections with SPFMV + SPVG or SPFMV + SPVG + IVMV resulted in mean yields 14% less than the VT controls. Infection with SPLCV resulted in mean yields 26% less than the VT controls, despite not causing symptoms on the foliage. However, grafting with farmers' plants infected with an unknown mixture of pathogens resulted in mean yields 31 to 44% less than the VT controls. Infection with potyviruses resulted in storage roots with tan periderm and infection with SPLCV induced darker periderm than the rosy VT controls. Infection with the viruses known to occur commonly in the United States did not reproduce the magnitude of yield reduction that has been observed with naturally infected plants.