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We investigated in vivo changes in Schlemm's canal and the trabecular meshwork in eyes with primary open angle glaucoma (POAG). Relationships between Schlemm's canal diameter, trabecular meshwork thickness, and intraocular pressure (IOP) were examined. Forty POAG patients and 40 normal individuals underwent 80-MHz Ultrasound Biomicroscopy examinations. The Schlemm's canal and trabecular meshwork were imaged in superior, inferior, nasal and temporal regions. Normal individuals had an observable Schlemm's canal in 80.3% of sections, a meridional canal diameter of 233.0±34.5 μm, a coronal diameter of 44.5±12.6 μm and a trabecular meshwork thickness of 103.9±11.1 μm, in POAG patients, Schlemm's canal was observable in 53.1% of sections, a meridional canal diameter of 195.6±31.3 μm, a coronal diameter of 35.7±8.0 μm, and a trabecular meshwork thickness of 88.3±13.2 μm, which significantly differed from normal (both p 21 mmHg) IOP, respectively (χ = 1.159, p = 0.282). Coronal canal diameter was significantly lower in the elevated IOP group (32.6±4.9 μm) than in the normal IOP group (35.7±8.0 μm, p < 0.001). This was also true of trabecular meshwork thickness (81.9±10.0 μm vs. 97.1±12.0 μm, p < 0.001). In conclusion, eyes with POAG had fewer sections with an observable Schlemm's canal. Canal diameter and trabecular meshwork thickness were also lower than normal in POAG patients. Schlemm's canal coronal diameter and trabecular meshwork thickness were negatively correlated with IOP.

BACKGROUND:Previous studies demonstrated that primary open angle glaucoma (POAG) is associated with abnormal brain structure; however, little is known about the changes in the local synchronization of spontaneous activity. The main objective of this study was to investigate spontaneous brain activity in patients with POAG using regional homogeneity (ReHo) analysis based on resting state functional magnetic resonance imaging (rs-fMRI). METHODOLOGY/PRINCIPAL FINDINGS:Thirty-nine POAG patients and forty-one age- and gender- matched healthy controls were finally included in the study. ReHo values were used to evaluate spontaneous brain activity and whole brain voxel-wise analysis of ReHo was carried out to detect differences by region in spontaneous brain activity between groups. Compared to controls, POAG patients showed increased ReHo in the right dorsal anterior cingulated cortex, the bilateral medial frontal gyrus and the right cerebellar anterior lobe, and decreased ReHo in the bilateral calcarine, bilateral precuneus gryus, bilateral pre/postcentral gyrus, left inferior parietal lobule and left cerebellum posterior lobe. A multiple linear regression analysis was performed to explore the relationships between clinical measures and ReHo by region showed significant group differences in the POAG group. Negative correlations were found between age and the ReHo values of the superior frontal gyrus (r = -0.323, p = 0.045), left calcarine (r = -0.357, p = 0.026) and inferior parietal lobule (r = -0.362, p = 0.024). A negative correlation was found between the ReHo values of the left precuneus and the cumulative mean defect (r = -0.400, p = 0.012). CONCLUSIONS:POAG was associated with abnormal brain spontaneous activity in some brain regions and such changed regional activity may be associated with clinical parameters. Spontaneous brain activity may play a role in POAG initiation and progression.

Essential proteins are crucial to living cells. Identification of essential proteins from protein-protein interaction (PPI) networks can be applied to pathway analysis and function prediction, furthermore, it can contribute to disease diagnosis and drug design. There have been some experimental and computational methods designed to identify essential proteins, however, the prediction precision remains to be improved. In this paper, we propose a new method for identifying essential proteins based on Participation degree of a protein in protein Complexes and Subgraph Density, named as PCSD. In order to test the performance of PCSD, four PPI datasets (DIP, Krogan, MIPS and Gavin) are used to conduct experiments. The experiment results have demonstrated that PCSD achieves a better performance for predicting essential proteins compared with some competing methods including DC, SC, EC, IC, LAC, NC, WDC, PeC, UDoNC, and compared with the most recent method LBCC, PCSD can correctly predict more essential proteins from certain numbers of top ranked proteins on the DIP dataset, which indicates that PCSD is very effective in discovering essential proteins in most case.

Recent reports have demonstrated that endothelial cells are involved in vascular inflammatory injury in systemic sclerosis (SSc) and interleukin-17A (IL-17A) plays a crucial role in the pathogenesis of SSC. However, little is known about the effects of IL-17A on endothelial cell inflammation in SSC. The aim of our study was to investigate the role of IL-17A in endothelial inflammation. Here, we showed that IL-17A mRNA and protein levels were augmented in the peripheral blood and more IL-17⁺ lymphocytes infiltrated in the perivascular areas in the involved skin of SSC patients. SSC patient serum induced chemokine and adhesion molecule expression in HUVECs, which was blocked by IL-17A neutralization. IL-17A alone induced chemokine and adhesion molecule expression and promoted T cell-HUVEC adhesion. Extracellular signal-regulated kinase (ERK) inhibition and IL-17A neutralization prominently inhibited chemokine and adhesion molecule expression and blocked T cell-HUVEC adhesion. IL-17A derived from SSC patient serum mediated endothelial cells inflammation by up-regulating chemokines and adhesion molecules, which was blocked by ERK inhibition. These data imply that ERK signal pathway might play a key role in the progression of endothelial injury induced by IL-17A in SSC.

BACKGROUND:Lung adenocarcinom (AC) is the most common form of lung cancer. Currently, the number of medical options to deal with lung cancer is very limited. In this study, we aimed to investigate potential therapeutic compounds for lung adenocarcinoma based on integrative analysis. METHODOLOGY/PRINCIPAL FINDINGS:The candidate therapeutic compounds were identified in a two-step process. First, a meta-analysis of two published microarray data was conducted to obtain a list of 343 differentially expressed genes specific to lung AC. In the next step, expression profiles of these genes were used to query the Connectivity-Map (C-MAP) database to identify a list of compounds whose treatment reverse expression direction in various cancer cells. Several compounds in the categories of HSP90 inhibitor, HDAC inhibitor, PPAR agonist, PI3K inhibitor, passed our screening to be the leading candidates. On top of the list, three HSP90 inhibitors, i.e. 17-AAG (also known as tanespimycin), monorden, and alvespimycin, showed significant negative enrichment scores. Cytotoxicity as well as effects on cell cycle regulation and apoptosis were evaluated experimentally in lung adenocarcinoma cell line (A549 or GLC-82) with or without treatment with 17-AAG. In vitro study demonstrated that 17-AAG alone or in combination with cisplatin (DDP) can significantly inhibit lung adenocarcinoma cell growth by inducing cell cycle arrest and apoptosis. CONCLUSIONS/SIGNIFICANCE:We have used an in silico screening to identify compounds for treating lung cancer. One such compound 17-AAG demonstrated its anti-lung AC activity by inhibiting cell growth and promoting apoptosis and cell cycle arrest.