Activity

Kurtosis-based projection pursuit analysis (kPPA) has demonstrated the ability to visualize multivariate data in a way that complements other exploratory data analysis tools, such as principal components analysis (PCA). It is especially useful for partitioning binary data sets (2k classes) with a balanced design. Since kPPA is not a variance-based method, it can often provide unsupervised class separation where other methods fail. However, when multiple classifications are possible (e.g. by gender, age, disease state, etc.), the projection provided by kPPA (corresponding to the global minimum kurtosis) will not necessarily be the one of greatest interest to the researcher. Fortunately, the optimization algorithm for kPPA allows for interrogation of projections obtained from numerous local minima. This strategy provides the basis of a new method described here, referred to as combinatorial projection pursuit analysis (CombPPA) because it presents alternative combinations of class separation. The method is truly exploratory in that it allows the landscape of interesting projections to be more fully probed. The approach uses Procrustes rotation to map local minima among the kPPA solutions, whereupon the researcher can visualize different projections. To demonstrate the new method, the clustering of grape juice samples using visible spectroscopy is presented as a model problem. This problem is well-suited to this type of study because there are eight classes of samples symmetrically partitioned into two classes by type (organic/non-organic) or four classes by brand. signaling pathway Results presented show the different combinations of projections that can be obtained, including the desired partitions. In addition, this work describes new enhancements to the kPPA algorithm that improve the orthogonality of solutions obtained.Circulating microRNAs (miRNAs) have the potential to become reliable and noninvasive biomarkers for ovarian cancer (OC) diagnosis; however, the conventional miRNAs detection techniques exhibit enduring limitations of low sensitivity and specificity. Graphene oxide (GO), a novel nanomaterial, is at the forefront of material design for extensive biomedical applications. Owing to the excellent water affinity and single-stranded DNA (ssDNA) adsorption characteristics of GO, we designed and developed a GO-based qRT-PCR assay for the detection of miRNAs associated with OC. In the GO-based qRT-PCR system, GO could significantly improve the sensitivity and specificity of the qRT-PCR assay by noncovalently interacting with primers and ssDNA and reducing the occurrence of non-specific amplification. Moreover, the detection of miRNAs associated with OC confirmed that GO-based qRT-PCR assay could differentiate benign ovarian tumors from OC (sensitivity, 0.91; specificity, 1.00). Collectively, these findings provide robust evidence that GO-based qRT-PCR assay can be effectively used as a promising method to detect miRNAs for the screening of OC patients.Based on the sulfuric acid-ultraviolet assay (SA-UV, developed by Albalasmeh et al., 2013), we have further expanded this method for the simultaneous quantification of saccharides (carbohydrates) and proteins by ultraviolet spectrophotometry. The absorbance of saccharides depends on the formation of furfurals by dehydration in the presence of concentrated sulfuric acid, whereas proteins are unaffected and can be quantified by UV active peptide bonds and aromatic amino acid residues. In saccharide/protein mixtures the SA-UV assay offers a good alternative and substitutes the need for two different methods, like the phenol-sulfuric acid (PSA, developed by DuBois et al., 1951) and bicinchoninic acid (BCA, developed by Smith et al., 1985) assays. For the development of this method, we used glucose and BSA as model substrates and performed a method validation in terms of linearity, LOD, LOQ, accuracy, and precision. Simultaneous quantification in glucose/BSA mixtures is possible down to 20 mg/L from 30 μL sample volumes, and even low content mixtures with concentrations down to 2 mg/L can appropriately be quantified from higher volumes by an evaporation technique.Quick and visual detection of component contents, such as water, in a mixed solvent is important for many practical applications, and a full range detection is especially preferred. In this work, a carbon dots based ratiometric fluorescent sensor was synthesized by grafting fluorescent group (Rhodamine B, RhB) on carbon dots, and the dual emission peaks exhibited a linear ratiometric response with the change of polarity and hydrogen bond of Solvent Hansen solubility parameters. This responsive behavior is attributed to surface state photoluminescence mechanisms, and has been used for the quantitative detection of water content in ethanol with an excellent linear relationship (R2 = 0.996), a low detection limit (0.2%), and a full detection range (0-100%). Furthermore, a paper-based ratiometric fluorescence sensing strip is also demonstrated, which exhibits good storage stability and sensitivity. This study suggests that RhB grafted carbon dots could be feasibly and effectively used as ratiometric fluorescent sensors for solvent content detection.Print and media technologies were used uncommonly in the field of chromatography and explored in application to create a miniaturized all-in-one LabToGo system. This novel research field termed Office Chromatography (OC) uses additive manufacturing in terms of 3D printing of operational parts as well as open-source hard- and software. The OCLab2 presented here has been considerably extended in its functionalities. For inkjet printing of solutions, a newly designed printhead was manufactured controlled by a self-constructed ink-jet board, allowing to check the nozzles’ resistance heating circuit. Plate heating was newly integrated, especially favorable for the demonstrated application of higher volumes of aqueous samples. The UV/Vis/FLD plate images were captured by a Raspberry Pi V2 camera module under illumination by novel light emitting diodes (LEDs) for highly selective RGBW color (Vis), UVC 278-nm (UV) and UVA 366-nm (FLD) detection, installed in a newly created miniature cabinet to protect from extraneous light.