STGC3 inhibits xenograft tumor growth of nasopharyngeal carcinoma cells by altering the expression of proteins associated with apoptosis

STGC3 is a potential tumor suppressor that inhibits the growth of the nasopharyngeal carcinoma cell line CNE2; the expression of this protein is reduced in nasopharyngeal carcinoma compared with normal nasopharyngeal tissue. In this study, we investigated the tumor-suppressing activity of STGC3 in nude mice injected subcutaneously with Tet/pTRE-STGC3/CNE2 cells. STGC3 expression was induced by the intraperitoneal injection of doxycycline (Dox). The volume mean of Tet/pTRE-STGC3/CNE2+Dox xenografts was smaller than that of Tet/pTRE/CNE2+Dox xenografts. In addition, Tet/pTRE-STGC3/CNE2+Dox xenografts showed an increase in the percentage of apoptotic cells, a decrease in Bcl-2 protein expression and an increase in Bax protein expression. A proteomic approach was used to assess the protein expression profile associated with STGC3-mediated apoptosis. Western blotting confirmed the differential up-regulation of prohibitin seen in proteomic analysis. These results indicate that overexpression of STGC3 inhibits xenograft growth in nude mice by enhancing apoptotic cell death through altered expression of apoptosis-related proteins such as Bcl-2, Bax and prohibitin. These data contribute to our understanding of the function of STGC3 in human nasopharyngeal carcinoma and provide new clues for investigating other STGC3-associated tumors

Sesquiterpenes and Dimeric Sesquiterpenoids from Sarcandra glabra

Two new sesquiterpenes, sarcandralactones A (1) and B (2), and five new dimeric sesquiterpenoids, sarcandrolides A-E (3-7), along with 10 known compounds were isolated from the whole plants of Sarcandra glabra. Their structures were elucidated on the basis of spectroscopic analysis. Some of the new isolates exhibit significant cytotoxicities when tested against a small panel of tumor cell lines

Identification of quality markers of Xiaojin Pills using a combination of high-performance liquid chromatographtandem mass spectrometry and multivariate analysis

Purpose: To establish an appropriate quality control method for Xiaojin pills using high-performance liquid chromatograph-tandem mass spectrometry combined with multivariate analysis.Methods: High-performance liquid chromatograph-tandem mass spectrometry was established to detect and quantify 13 chemical components of Xiaojin Pills. In order to evaluate the quality difference between diverse specimens of Xiaojin Pills, several multivariate statistical techniques were applied to analyze the dissimilarity between different batches of samples, including principal composition analysis method and clustering methodology.Results: Five chemical components were identified as primary quality markers, which can be used to accurately distinguish various samples and command the quality of Xiaojin Pills.Conclusion: The results afford a professionally scientific basis for the quality monitoring of Xiaojin Pills and also furnishes reasonable ideas and suggestions for the quality control of other traditional drugs.Keywords: Xiaojin Pills, HPLC-MS/MS, Quality control, Chemometrics, Quality marker

Effects of current on nanoscale ring-shaped magnetic tunnel junctions

We report the observation and micromagnetic analysis of current-driven magnetization switching in nanoscale ring-shaped magnetic tunnel junctions. When the electric current density exceeds a critical value of the order of $6\times 10^{6}$A/cm$^2$, the magnetization of the two magnetic rings can be switched back and forth between parallel and antiparallel onion states. Theoretical analysis and micromagnetic simulation show that the dominant mechanism for the observed current-driven switching is the spin torque rather than the current-induced circular Oersted field

(meso-5,5,7,12,12,14-Hexamethyl-1,4,8,11-tetra­azacyclo­tetra­deca­ne)nickel(II) bis­(O,O′-dibenzyl dithio­phosphate)

In the title salt-type 1:2 adduct, [Ni(C16H36N4)](C14H14O2PS2)2 or [Ni(tet-a)][S2P(OCH2Ph)2]2, where tet-a is meso-5,5,7,12,12,14-hexa­methyl-1,4,8,11-tetra­azacyclo­tetra­decane, the [Ni(tet-a)]2+ complex cation exhibits a relatively undistorted square-planar geometry about the Ni atom, which lies on an inversion centre and is coordinated by four macrocyclic N atoms. The two O,O′-bis­(2-phenyl­meth­yl) dithio­phosphate anions act as counter-ions to balance the charge and they inter­act with the complex through N—H⋯S hydrogen bonds. Important geometric data include Ni—N distances of 1.958 (3) and 1.963 (3) Å

Abnormal magnetoresistance behavior in Nb thin film with rectangular antidot lattice

Abnormal magnetoresistance behavior is found in superconducting Nb films perforated with rectangular arrays of antidots (holes). Generally magnetoresistance were always found to increase with increasing magnetic field. Here we observed a reversal of this behavior for particular in low temperature or current density. This phenomenon is due to a strong 'caging effect' which interstitial vortices are strongly trapped among pinned multivortices.Comment: 4 pages, 2 figure

Prediction models for solitary pulmonary nodules based on curvelet textural features and clinical parameters

Lung cancer, one of the leading causes of cancer-related deaths, usually appears as solitary pulmonary nodules (SPNs) which are hard to diagnose using the naked eye. In this paper, curvelet-based textural features and clinical parameters are used with three prediction models [a multilevel model, a least absolute shrinkage and selection operator (LASSO) regression method, and a support vector machine (SVM)] to improve the diagnosis of benign and malignant SPNs. Dimensionality reduction of the original curvelet-based textural features was achieved using principal component analysis. In addition, non-conditional logistical regression was used to find clinical predictors among demographic parameters and morphological features. The results showed that, combined with 11 clinical predictors, the accuracy rates using 12 principal components were higher than those using the original curvelet-based textural features. To evaluate the models, 10-fold cross validation and back substitution were applied. The results obtained, respectively, were 0.8549 and 0.9221 for the LASSO method, 0.9443 and 0.9831 for SVM, and 0.8722 and 0.9722 for the multilevel model. All in all, it was found that using curvelet-based textural features after dimensionality reduction and using clinical predictors, the highest accuracy rate was achieved with SVM. The method may be used as an auxiliary tool to differentiate between benign and malignant SPNs in CT images