Identification of key candidate genes and pathways in anaplastic thyroid cancer by bioinformatics analysis.

Background: Anaplastic thyroid carcinoma (ATC) is a refractory and poor prognosis tumor Present study aimed to investigate the underlying biological functions and pathways involved in the development of ATC and to identify potential hub genes and candidate biomarkers of ATC.

Materials And Methods: Bioinformatics analyses were performed to identify the differentially expressed genes (DEGs) between ATC tissue samples and adjacent normal tissue samples. Protein-protein interaction (PPI) networks of the DEGs were constructed using Search Tool for the Retrieval of Interacting Genes online tool and Cytoscape software and divided into sub-networks using the Molecular Complex Detection (MCODE) plug-in.

Orthogonal projection to latent structures combined with artificial neural networks in non-destructive analysis of Ampicillin powder.

A new method orthogonal projection to latent structures (O-PLS) combined with artificial neural networks is investigated for non-destructive determination of Ampicillin powder via near-infrared (NIR) spectroscopy. The modern NIR spectroscopy analysis technique is efficient, simple and non-destructive, which has been used in chemical analysis in diverse fields. Be a preprocessing method, O-PLS provides a way to remove systematic variation from an input data set X not correlated to the response set Y, and does not disturb the correlation between X and Y.

[Nondestructive quantitative analysis of Cofrel medicines by improved partial least squares-NIR spectroscopy].

In the present paper, improved partial least squares (PLS) method was used to parse near infrared (NIR) reflectance spectrum of Cofrel medicine. The contents of benproperine phosphate, a availability pharmaceutical in Cofrel medicine, were accurately nondestructively quantitatively predicted. The best number of principal components (PC) was designed by scores plot of samples in PC.

[Study on extraction of coumarins in Cnidium monieri by supercritical CO2 and separation of compositions analysis].

Objective: To analyze the chemical constituents of supercritical carbon dioxide extraction products from Cnidium monieri.

Method: Four-factor and three-level orthogonal experimental design was used to optimize the SFE conditions as guided by the content of total coumarins in the extract. The chemical constituents were separated and identified by recrystalization.

[Studies on the chemistry of two new compounds of Hemistepta lyrata].

Aim: To study the chemical constituents of Hemistepta lyrata.

Methods: To separate compounds with various chromatography technology and to elucidate their structures by chemical and spectral analysis.

Results: Two compounds were isolated from Hemistepta lyrata and their structures were determined as hemiceramide (I), hemisterpene ether (II).