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BACKGROUND: Starch and its products are used in a variety of ways for both the food and nonfood industries. A factorial experiment is carried out with two factors to explain the behavior of the percentage of starch, where the factors correspond to the extraction method and to the raw material. METHOD: Three methods were used in triplicate: the first followed the official technique of the Association of Official Analytical Chemists (AOAC), to perform acid hydrolysis and quantification of starch by Titulation; the second method involved the colorful reaction with iodine using the UV equipment to measure the absorbance and calculate the percentage of starch; as a third method the FTIR was used, through which the concentration of the starch was calculated by the area under the curve obtained from the spectrum. RESULTS: there is an effect of both the method and the raw material on the percentage of starch, while there was no effect of the interaction; the Tukey test indicates that the highest average percentage of extraction occurs with the extraction method by Titulation and with the starch of Manihot esculenta. CONCLUSION: It is used as raw material. The method of quantification of starch by UV-VIS spectroscopy was the best for the study samples because it presented less deviation in relation to the FTIR and Titulation methods.
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The optical absorption of UiO-66-NH2 MOF was red-shifted using a diazo-coupling reaction. The modifications performed with naphthols and aniline yielded reddish samples, and the modifications with diphenylaniline yielded dark violet ones. The photocatalytic activity of these modified MOFs was assessed for methylene blue degradation, showing a good performance relative to traditional TiO2. The degradation performance was found to correlate with the red shift of the absorption edge. These findings suggest potential applications of these materials in photocatalysis and in dye sensitized solar cells.
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MOTIVATION: PAR-CLIP, a CLIP-seq protocol, derives a transcriptome wide set of binding sites for RNA-binding proteins. Even though the protocol uses stringent washing to remove experimental noise, some of it remains. A recent study measured three sets of non-specific RNA backgrounds which are present in several PAR-CLIP datasets. However, a tool to identify the presence of common background in PAR-CLIP datasets is not yet available. RESULTS: We used the measured sets of non-specific RNA backgrounds to build a common background set. Each element from the common background set has a score that reflects its presence in several PAR-CLIP datasets. We present a tool that uses this score to identify the amount of common backgrounds present in a PAR-CLIP dataset, and we provide the user the option to use or remove it. We used the proposed strategy in 30 PAR-CLIP datasets from nine proteins. It is possible to identify the presence of common backgrounds in a dataset and identify differences in datasets for the same protein. This method is the first step in the process of completely removing such backgrounds. AVAILABILITY: The tool was implemented in python. The common background set and the supplementary data are available at https://github.com/phrh/BackCLIP. CONTACT: phreyes@gmail.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.