Monodisperse Low-Bandgap Macromolecule-Based 5,5′-Bibenzo[c][1,2,5]thiadiazole Swivel Cruciform for Organic Solar Cells

A novel low bandgap star-like macromolecule was synthesized and applied as electron donor material in the bulk heterojunction solar cells, in which the 5,5′-bibenzo­[c]­[1,2,5]­thiadiazole was used as the central node, in conjunction with four conjugated donor–acceptor arms. Compared with the corresponding small molecule with first generation arms, the macromolecule with second generation branches exhibited significantly enhanced photovoltaic device performances (blended with PC71BM as the active layer) due to dramatically improved short-circuit current density (<i>J</i>_sc) and fill factor (FF). The improvement in <i>J</i>_sc and FF can be attributed to the more broad absorption and the more favorable phase separation when comparing a monodisperse macromolecule with the second generation arms (SFTBT) with a small molecule with first generation branches (DFTBT)

Correlation analysis of NgBR and survivin transcripts in different stages of ductal adenocarcinoma.

*<p><i>p</i><0.05; N: case number; (%): percentage of total case number.</p

Details of antibody and dilution.

<p>Details of antibody and dilution.</p

Expression of NgBR Is Highly Associated with Estrogen Receptor Alpha and Survivin in Breast Cancer

<div><p>NgBR is a type I receptor with a single transmembrane domain and was identified as a specific receptor for Nogo-B. Our recent findings demonstrated that NgBR binds farnesylated Ras and recruits Ras to the plasma membrane, which is a critical step required for the activation of Ras signaling in human breast cancer cells and tumorigenesis. Here, we first use immunohistochemistry and real-time PCR approaches to examine the expression patterns of Nogo-B and NgBR in both normal and breast tumor tissues. Then, we examine the relationship between NgBR expression and molecular subtypes of breast cancer, and the roles of NgBR in estrogen-dependent survivin signaling pathway. Results showed that NgBR and Nogo-B protein were detected in both normal and breast tumor tissues. However, the expression of Nogo-B and NgBR in breast tumor tissue was much stronger than in normal breast tissue. The statistical analysis demonstrated that NgBR is highly associated with ER-positive/HER2-negative breast cancer. We also found that the expression of NgBR has a strong correlation with the expression of survivin, which is a well-known apoptosis inhibitor. The correlation between NgBR and survivin gene expression was further confirmed by real-time PCR. In vitro results also demonstrated that estradiol induces the expression of survivin in ER-positive T47D breast tumor cells but not in ER-negative MDA-MB-468 breast tumor cells. NgBR knockdown with siRNA abolishes estradiol-induced survivin expression in ER-positive T47D cells but not in ER-negative MDA-MB-468 cells. In addition, estradiol increases the expression of survivin and cell growth in ER-positive MCF-7 and T47D cells whereas knockdown of NgBR with siRNA reduces estradiol-induced survivin expression and cell growth. In summary, these results indicate that NgBR is a new molecular marker for breast cancer. The data suggest that the expression of NgBR may be essential in promoting ER-positive tumor cell proliferation via survivin induction in breast cancer.</p></div

NgBR regulates estradiol-induced survivin expression in estrogen receptor positive breast tumor cells.

<p>T47D is an estrogen receptor positive breast tumor cell line. MDA-MB-468 is an estrogen receptor negative breast tumor cell line. NgBR was knockdown in both T47D and MDA-MB-468 cells using siRNA as described in methods. Both tumor cells were treated with 10 nM estradiol for 48 hours. Protein levels of NgBR, ER-alpha and survivin were determined by Western blot analysis. Beta-Actin is applied as a housekeeping protein. The density of each band was measured using NIH ImageJ and presented as relative intensity of survivin after normalized with beta-actin housekeeping protein. (A) NgBR knockdown diminished estradiol-induced survivin expression in T47D breast tumor cells. (B) Quantitative analysis of survivin protein level change in T47D cells by measuring intensity of survivin western blot band. Data is presented as fold changes of estradiol treatment group as compared to the non-treatment group (n = 3; * siNgBR vs NS <i>p</i><0.05). (C) NgBR knockdown has no effect on survivin expression in MDA-MB-468 breast tumor cells. (D) Quantitative analysis of survivin protein level change in MDA-MB-468 cells by measuring intensity of survivin western blot band. Data is presented as fold changes of estradiol treatment group as compared to the non-treatment group. (n = 3; siNgBR vs NS <i>p</i> = 0.092).</p

NgBR is essential for estradiol-induced survivin expression and cell growth of MCF-7 breast tumor cells.

<p>MCF-7 is an estrogen-dependent breast cancer cell line. NgBR was knocked down in MCF-7 cells using siRNA. (A) NgBR knockdown diminished estradiol-induced survivin expression in MCF-7 breast tumor cells. MCF-7 cells were treated with 10 nM estradiol for 6 and 48 hours. Protein levels of NgBR and survivin were determined by Western blot analysis. Beta-Actin is applied as a housekeeping protein. The density of each band was measured using NIH ImageJ and presented as relative intensity of survivin after normalized with beta-actin housekeeping protein. (B) Folds of survivin increase were determined by measuring relative western blot intensity of survivin. Data is presented as fold changes of estradiol treatment group as compared to the non-treatment group (n = 3; 6 hrs estradiol treatment, NS vs siNgBR <i>p</i> = 0.178; * 48 hrs estradiol treatment, NS vs siNgBR <i>p</i><0.05). (C) NgBR knockdown impaired estradiol-stimulated cell growth of MCF-7 breast tumor cells. MCF-7 cells were treated with 10 nM estradiol for 24 and 48 hours. Viable cell numbers were counted using the Bio-Rad TC10™ Automated Cell Counter. Data is presented as mean±SEM (n = 3, # 24 hrs or 48 hrs estradiol treatment vs baseline <i>p</i><0.05; * siNgBR vs NS <i>p</i><0.05); E2: estradiol.</p

NgBR and survivin transcripts in breast tumor tissues determined by real-time PCR.

<p>Normalized human breast tumor qPCR panels were utilized (Origene). The copy number of NgBR and survivin was determined by real-time PCR. (A) NgBR RNA levels in ductal adenocarcinoma specimens were presented as fold changes as compared to the average NgBR RNA levels of all normal breast tissue (* tumor vs normal, <i>p</i><0.05). (B) Survivin RNA levels in ductal adenocarcinoma specimens were presented as fold changes as compared to the average survivin RNA levels of all normal breast tissue (* tumor vs normal, <i>p</i><0.05).</p

In-Depth Proteome Coverage by Improving Efficiency for Membrane Proteome Analysis

Although great achievement has been made in the mapping of human proteome, the efficiency of sample preparation still needs to be improved, especially for membrane proteins. Herein, we presented a novel method to deepen proteome coverage by the sequential extraction of proteins using urea and 1-dodecyl-3- methylimidazolium chloride (C12Im-Cl). With such a strategy, the commonly lost hydrophobic proteins by 8 M urea extraction could be further recovered by C12Im-Cl, as well as the suppression effect of high abundance soluble proteins could be decreased. Followed by the in situ sample preparation and separation with different stationary phases, more than 9810 gene products could be identified, covering 8 orders of magnitude in abundance, which was, to the best of our knowledge, the largest data set of HeLa cell proteome. Compared with previous work, not only the number of proteins identified was obviously increased, but also the analysis time was shortened to a few days. Therefore, we expect that such a strategy has great potential applications to achieve unprecedented coverage for proteome analysis

In-Depth Proteome Coverage by Improving Efficiency for Membrane Proteome Analysis

Although great achievement has been made in the mapping of human proteome, the efficiency of sample preparation still needs to be improved, especially for membrane proteins. Herein, we presented a novel method to deepen proteome coverage by the sequential extraction of proteins using urea and 1-dodecyl-3- methylimidazolium chloride (C12Im-Cl). With such a strategy, the commonly lost hydrophobic proteins by 8 M urea extraction could be further recovered by C12Im-Cl, as well as the suppression effect of high abundance soluble proteins could be decreased. Followed by the in situ sample preparation and separation with different stationary phases, more than 9810 gene products could be identified, covering 8 orders of magnitude in abundance, which was, to the best of our knowledge, the largest data set of HeLa cell proteome. Compared with previous work, not only the number of proteins identified was obviously increased, but also the analysis time was shortened to a few days. Therefore, we expect that such a strategy has great potential applications to achieve unprecedented coverage for proteome analysis

In-Depth Proteome Coverage by Improving Efficiency for Membrane Proteome Analysis

Although great achievement has been made in the mapping of human proteome, the efficiency of sample preparation still needs to be improved, especially for membrane proteins. Herein, we presented a novel method to deepen proteome coverage by the sequential extraction of proteins using urea and 1-dodecyl-3- methylimidazolium chloride (C12Im-Cl). With such a strategy, the commonly lost hydrophobic proteins by 8 M urea extraction could be further recovered by C12Im-Cl, as well as the suppression effect of high abundance soluble proteins could be decreased. Followed by the in situ sample preparation and separation with different stationary phases, more than 9810 gene products could be identified, covering 8 orders of magnitude in abundance, which was, to the best of our knowledge, the largest data set of HeLa cell proteome. Compared with previous work, not only the number of proteins identified was obviously increased, but also the analysis time was shortened to a few days. Therefore, we expect that such a strategy has great potential applications to achieve unprecedented coverage for proteome analysis