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Background: This study aimed to identify prognostic signatures to predict the prognosis of breast cancer (BRCA) patients based on a series of comprehensive analyses of gene expression data. Methods: The RNA-sequencing expression data and corresponding BRCA patient clinical data were collected from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) datasets. Firstly, the differently expressed genes (DEGs) related to prognosis between tumor tissues and normal tissues were ascertained by performing R package "limma". Secondly, the DEGs were used to construct a polygenic risk scoring model by the weighted gene co-expression network analysis (WGCNA) and the least absolute shrinkage and selection operator Cox regression (Lasso-cox) analysis method. Thirdly, survival analysis was performed to investigate the risk score values in the TCGA cohort. And the enrichment analysis, immune cell infiltration levels analysis, and protein-protein internet (PPI) analysis were performed. Simultaneously, the GEO cohort was used to validate the model. Lastly, we constructed a nomogram to explore the influence of polygenic risk score and other clinical factors on the survival probability of patients with BRCA. Results: A total of 1000 DEGs including 396 upregulated genes and 604 downregulated genes were identified from the TCGA-BRCA dataset. We obtained 5 prognosis-related genes, as the key biomarkers by Lasso-cox analysis (FBXL19, HAGHL, PHKG2, PKMYT1, and TXNDC17), all of which were significantly upregulated in breast tumors. The prognostic prediction of the 5 genes model was great in training and validation cohorts. Moreover, the high-risk group had a poorer prognosis. The Cox regression analysis showed that the comprehensive risk score for 5 genes was an independent prognosis factor. Conclusion: The 5 genes risk model constructed in this study had an independent predictive ability to distinguish patients with a high risk of death from those with a low-risk score, and it can be used as a practical and reliable prognostic tool for BRCA.
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Defects can greatly promote the catalytic activity of a carbon-based electrocatalyst due to charge redistribution of its electroneutral π-conjugated structure. However, it is still a huge challenge to introduce enough defects into carbon-based materials to improve their catalytic activity. Herein, we report a new method for defect generation by the pyrolysis of the sulfur-nitrogen-containing coordination polymer [Zn(ptt)2]n (ptt = 1-phenyl-1H-tetrazole-5-thiol). A series of controlled experiments clearly demonstrates that the carbothermal reduction reaction of zinc sulfide with carbon at a high temperature plays an important role in creating defects and enhancing the catalytic activity for the oxygen reduction reaction (ORR) of the carbon-based materials. The ZnS/C-1100 with a high content of defects and a small number of ZnS nanoparticles exhibits excellent ORR electrocatalytic performances in alkaline media, in which the half-wave potential (0.894 V vs. RHE), stability, and methanol tolerance are all superior to that of a 20 wt% Pt/C catalyst. Moreover, the ZnS/C-1100 driven ZAB (zinc air battery) exhibits a stable discharge at 10 mA, a peak power density of 134 mW cm-2 and a cathode current density of 265 mA cm-2, which are significantly better than that catalyzed by 20 wt% Pt/C under the same conditions. This research not only develops a new highly active catalyst, but also provides a new method for the preparation of defect-rich carbon materials.
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Novel 3D metal formate frameworks {[Ba4Cl][M3(HCO2)13]}n (M = Mn for 1, Co for 2, and Mg for 3) were successfully assembled via microwave-assisted synthesis. The complexes are rare coordination polymers crystallized at space group P4cc with the polar point group C4v. In the structure, the MII ions are bridged by two types of anti-anti formate in forming a 3D pcu framework, and additional formates coordinate to the unsaturated sites of the MII ions in the framework, giving an anionic M-formate net. Ba4Cl clusters take the cavities of the net as charge balance, in which the chloride ion deviates from the center of the barium ions. The asymmetric Ba4Cl structure is transmitted throughout the crystal resulting in polar structure, which is further confirmed by nonlinear optical and piezoelectric test. Nonlinear optical activity tests of 1 and 3 show SHG signals 0.32 and 0.28 times that of KDP, while 2 has a piezoelectric coefficient d33 of 6.8 pC/N along polar axis. Magnetic studies reveal antiferromagnetic coupling between MII ions in 1 and 2. Spin canting was found only in 2 with anisotropic CoII ions, and 2 is a canted antiferromagnetically with TN = 5 K. Further field-induced spin flop was also found in 2 with a critical field 0.9 T.
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BACKGROUND: Our study aimed to explore the relationship between body mass index (BMI) and bone mineral density (BMD) of lumbar vertebra and femoral neck in postmenopausal females. MATERIAL/METHODS: From September 2012 to September 2014, 236 healthy postmenopausal females who underwent physical examinations at the Women & Children's Health Care Hospital of Linyi were enrolled into our study. These subjects were divided into 3 groups: underweight group, normal weight group, and overweight group. In addition, there were 2 age stratifications: <60 years old and ≥60 years old. DPX-L type dual-energy X-ray bone densitometry (American Lunar Company) was used to measure the BMD of lumbar vertebra and femoral neck in the recruited subjects. Pearson test was used for correlation analysis. RESULTS: BMDs and T-scores of lumbar vertebra (L1-L4), femoral neck, proximal femur, and Ward's triangle region among the groups were ranked as follows: underweight group < normal weight group < overweight group. There were significant differences in body weight and BMI among the underweight, normal weight, and overweight groups (P<0.05). The T-scores of all examined anatomic locations showed significant differences between the underweight group and normal weight group, as well as between the underweight group and overweight group (both P<0.05). Only the T-scores of lumbar vertebra L2-L4 had significant differences between the normal weight group and overweight group (P<0.05). The BMDs of all anatomic components under study showed statistical differences in both age stratifications between the overweight group and underweight group, as well as between the overweight group and normal weight group (both P<0.05). When stratified above 60 years old, the BMDs of lumbar vertebra (L1, L2 and L4) showed statistical differences between the normal weight group and underweight group (P<0.05). Various factors could be ranked according to the absolute values of correlation coefficients as below: body weight, BMI, height, and age. Body weight, BMI, and height were positively correlated with the BMDs of all examined anatomic locations (P<0.05). However, age was negatively correlated with the various components of the body (lumbar vertebra L1, L2 and L4, femoral neck, proximal femur, Ward's triangle region: P<0.05; lumbar vertebra L3: P>0.05). CONCLUSIONS: Our study provides evidence that body weight and BMI are important factors affecting BMD. Postmenopausal females with low BMI are more likely to have osteopenia, and are likely to develop osteoporosis. BMI can be used as an important index to prevent osteoporosis.
