Mechanical motion promotes expression of Prg4 in articular cartilage via multiple CREB-dependent, fluid flow shear stress-induced signaling pathways

Lubricin is a secreted proteoglycan encoded by the Prg4 locus that is abundantly expressed by superficial zone articular chondrocytes and has been noted to both be sensitive to mechanical loading and protect against the development of osteoarthritis. In this study, we document that running induces maximal expression of Prg4 in the superficial zone of knee joint articular cartilage in a COX-2-dependent fashion, which correlates with augmented levels of phospho-S133 CREB and increased nuclear localization of CREB-regulated transcriptional coactivators (CRTCs) in this tissue. Furthermore, we found that fluid flow shear stress (FFSS) increases secretion of extracellular PGE2, PTHrP, and ATP (by epiphyseal chondrocytes), which together engage both PKA- and Ca++-regulated signaling pathways that work in combination to promote CREB-dependent induction of Prg4, specifically in superficial zone articular chondrocytes. Because running and FFSS both boost Prg4 expression in a COX-2-dependent fashion, our results suggest that mechanical motion may induce Prg4 expression in the superficial zone of articular cartilage by engaging the same signaling pathways activated in vitro by FFSS that promote CREB-dependent gene expression in this tissue.National Institute of Arthritis and Musculoskeletal and Skin Diseases (U.S.) (Grant AR60331

High-bandwidth AFM-based rheology is a sensitive indicator of early cartilage aggrecan degradation relevant to mouse models of osteoarthritis

Murine models of osteoarthritis (OA) and post-traumatic OA have been widely used to study the development and progression of these diseases using genetically engineered mouse strains along with surgical or biochemical interventions. However, due to the small size and thickness of murine cartilage, the relationship between mechanical properties, molecular structure and cartilage composition has not been well studied. We adapted a recently developed AFM-based nano-rheology system to probe the dynamic nanomechanical properties of murine cartilage over a wide frequency range of 1 Hz to 10 kHz, and studied the role of glycosaminoglycan (GAG) on the dynamic modulus and poroelastic properties of murine femoral cartilage. We showed that poroelastic properties, highlighting fluid–solid interactions, are more sensitive indicators of loss of mechanical function compared to equilibrium properties in which fluid flow is negligible. These fluid-flow-dependent properties include the hydraulic permeability (an indicator of the resistance of matrix to fluid flow) and the high frequency modulus, obtained at high rates of loading relevant to jumping and impact injury in vivo. Utilizing a fibril-reinforced finite element model, we estimated the poroelastic properties of mouse cartilage over a wide range of loading rates for the first time, and show that the hydraulic permeability increased by a factor ~16 from k[subscript normal] = 7.80 × 10[superscript −16] ± 1.3 × 10[superscript −16] m[superscript 4]/N s to k[subscript GAG-depleted] = 1.26 × 10[superscript −14] ± 6.73 × 10[superscript −15] m[superscript 4]/N s after GAG depletion. The high-frequency modulus, which is related to fluid pressurization and the fibrillar network, decreased significantly after GAG depletion. In contrast, the equilibrium modulus, which is fluid-flow independent, did not show a statistically significant alteration following GAG depletion.National Institutes of Health (U.S.) (Grant 060331)Whitaker Foundation (Health Sciences Fund Fellowship)Arthritis Australi

Transient Global Amnesia Linked to Impairment of Brain Venous Drainage: An Ultrasound Investigation

Background: Previous neuroimaging and ultrasound studies suggested that compression and stenosis of the internal jugular vein (IJV) in patients with transient global amnesia (TGA) may impair IJV drainage, while a patent IJV releases intracranial pressure caused by the Valsalva maneuver (VM).Methods: Seventy-nine TGA patients with complete ultrasound examination data during admission were recruited prospectively to evaluate IJV drainage, which included the time-averaged mean velocity, and the cross-sectional lumen area of the IJV at the vein's middle (J2) and distal (J3) segments and the cross-sectional area during a 10-s VM to test for any retrograde or anti-grade flow. Forty-five TGA patients and 45 age- and sex-matched control subjects underwent complete contrast-enhanced magnetic resonance (MR) venous studies, which included time-resolved imaging of contrast kinetics, contrast-enhanced axial T1-weighted MR imaging, and phase-contrast-based non-contrast enhanced magnetic resonance venography (MRV).Results: In those subjects with complete MRV studies, the flow volumes exhibited at both the J2 and J3 segments of the left IJV and left vertebral vein (VV) were significantly lower in the TGA patients than in the control subjects. Although there was no significant difference in the flow volume of right IJV, the total of bilateral IJV, and VV flow volumes was still significantly lower in the TGA patients. As compared with the control subjects, the TGA patients exhibited significantly higher prevalence of completely blocked right IJV drainage at the J3 segment during the VM, but non-significantly higher for the left IJV at the J3 segment and for the right IJV at the J2 segment.Conclusion: Our results confirmed that the total venous flow decreases in the IJVs and VVs of the patients with TGA. This is consistent with the findings of previous MR imaging studies that have reported about compression and stenosis of the draining veins. We also found that IJV drainage is relatively compromised during the VM in the patients with TGA

Bmi-1 Regulates Snail Expression and Promotes Metastasis Ability in Head and Neck Squamous Cancer-Derived ALDH1 Positive Cells

Recent studies suggest that ALDH1 is a putative marker for HNSCC-derived cancer stem cells. However, the regulation mechanisms that maintain the stemness and metastatic capability of HNSCC-ALDH1+ cells remain unclear. Initially, HNSCC-ALDH1+ cells from HNSCC patient showed cancer stemness properties, and high expression of Bmi1 and Snail. Functionally, tumorigenic properties of HNSCC-ALDH1+ cells could be downregulated by knockdown of Bmi-1. Overexpression of Bmi-1 altered in expression property ALDH1− cells to that of ALDH1+ cells. Furthermore, knockdown of Bmi-1 enhanced the radiosensitivity of radiation-treated HNSCC-ALDH1+ cells. Moreover, overexpression of Bmi-1 in HNSCC-ALDH1− cells increased tumor volume and number of pulmonary metastatic lesions by xenotransplant assay. Importantly, knock-down of Bmi1 in HNSCC-ALDH1+ cells significantly decreased distant metastases in the lungs. Clinically, coexpression of Bmi-1/Snail/ALDH1 predicted the worst prognosis in HNSCC patients. Collectively, our data suggested that Bmi-1 plays a key role in regulating Snail expression and cancer stemness properties of HNSCC-ALDH1+ cells

Statistical identification of gene association by CID in application of constructing ER regulatory network

<p>Abstract</p> <p>Background</p> <p>A variety of high-throughput techniques are now available for constructing comprehensive gene regulatory networks in systems biology. In this study, we report a new statistical approach for facilitating <it>in silico </it>inference of regulatory network structure. The new measure of association, coefficient of intrinsic dependence (CID), is model-free and can be applied to both continuous and categorical distributions. When given two variables X and Y, CID answers whether Y is dependent on X by examining the conditional distribution of Y given X. In this paper, we apply CID to analyze the regulatory relationships between transcription factors (TFs) (X) and their downstream genes (Y) based on clinical data. More specifically, we use estrogen receptor α (ERα) as the variable X, and the analyses are based on 48 clinical breast cancer gene expression arrays (48A).</p> <p>Results</p> <p>The analytical utility of CID was evaluated in comparison with four commonly used statistical methods, Galton-Pearson's correlation coefficient (GPCC), Student's <it>t</it>-test (STT), coefficient of determination (CoD), and mutual information (MI). When being compared to GPCC, CoD, and MI, CID reveals its preferential ability to discover the regulatory association where distribution of the mRNA expression levels on X and Y does not fit linear models. On the other hand, when CID is used to measure the association of a continuous variable (Y) against a discrete variable (X), it shows similar performance as compared to STT, and appears to outperform CoD and MI. In addition, this study established a two-layer transcriptional regulatory network to exemplify the usage of CID, in combination with GPCC, in deciphering gene networks based on gene expression profiles from patient arrays.</p> <p>Conclusion</p> <p>CID is shown to provide useful information for identifying associations between genes and transcription factors of interest in patient arrays. When coupled with the relationships detected by GPCC, the association predicted by CID are applicable to the construction of transcriptional regulatory networks. This study shows how information from different data sources and learning algorithms can be integrated to investigate whether relevant regulatory mechanisms identified in cell models can also be partially re-identified in clinical samples of breast cancers.</p> <p>Availability</p> <p>the implementation of CID in R codes can be freely downloaded from <url>http://homepage.ntu.edu.tw/~lyliu/BC/</url>.</p

Hubba: hub objects analyzer—a framework of interactome hubs identification for network biology

One major task in the post-genome era is to reconstruct proteomic and genomic interacting networks using high-throughput experiment data. To identify essential nodes/hubs in these interactomes is a way to decipher the critical keys inside biochemical pathways or complex networks. These essential nodes/hubs may serve as potential drug-targets for developing novel therapy of human diseases, such as cancer or infectious disease caused by emerging pathogens. Hub Objects Analyzer (Hubba) is a web-based service for exploring important nodes in an interactome network generated from specific small- or large-scale experimental methods based on graph theory. Two characteristic analysis algorithms, Maximum Neighborhood Component (MNC) and Density of Maximum Neighborhood Component (DMNC) are developed for exploring and identifying hubs/essential nodes from interactome networks. Users can submit their own interaction data in PSI format (Proteomics Standards Initiative, version 2.5 and 1.0), tab format and tab with weight values. User will get an email notification of the calculation complete in minutes or hours, depending on the size of submitted dataset. Hubba result includes a rank given by a composite index, a manifest graph of network to show the relationship amid these hubs, and links for retrieving output files. This proposed method (DMNC || MNC) can be applied to discover some unrecognized hubs from previous dataset. For example, most of the Hubba high-ranked hubs (80% in top 10 hub list, and >70% in top 40 hub list) from the yeast protein interactome data (Y2H experiment) are reported as essential proteins. Since the analysis methods of Hubba are based on topology, it can also be used on other kinds of networks to explore the essential nodes, like networks in yeast, rat, mouse and human. The website of Hubba is freely available at http://hub.iis.sinica.edu.tw/Hubba

Role of aggrecanase 1 in Lyme arthritis

Objective Arthritis is one of the hallmarks of late-stage Lyme disease. Previous studies have shown that infection with Borrelia burgdorferi , the causative agent of Lyme disease, results in degradation of proteoglycans and collagen in cartilage. B burgdorferi do not appear to produce any exported proteases capable of digesting proteoglycans and collagen, but instead, induce and activate host proteases, such as matrix metalloproteinases (MMPs), which results in cartilage degradation. The role of aggrecanases in Lyme arthritis has not yet been determined. We therefore sought to delineate the contribution of aggrecanases to joint destruction in Lyme arthritis. Methods We examined the expression patterns of aggrecanases 1 and 2 (ADAMTS 4 and 5, respectively) in B burgdorferi –infected primary human chondrocyte cell cultures, in synovial fluid samples from patients with active Lyme arthritis, and in the joints of mice by real-time quantitative reverse transcription–polymerase chain reaction and immunoblotting techniques. Bovine cartilage explants were used to determine the role of aggrecanases in B burgdorferi –induced cartilage degradation. Results ADAMTS-4, but not ADAMTS-5, was induced in human chondrocytes infected with B burgdorferi . The active forms of ADAMTS-4 were increased in synovial fluid samples from patients with active Lyme arthritis and were elevated in the joints of mice infected with B burgdorferi . Using cartilage explant models of Lyme arthritis, it appeared that the cleavage of aggrecan was predominantly mediated by “aggrecanases” rather than MMPs. Conclusion The induction of ADAMTS-4 by B burgdorferi results in the cleavage of aggrecan, which may be an important first step that leads to permanent degradation of cartilage.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/55825/1/22128_ftp.pd

Oct-4 Expression Maintained Cancer Stem-Like Properties in Lung Cancer-Derived CD133-Positive Cells

CD133 (prominin-1), a 5-transmembrane glycoprotein, has recently been considered to be an important marker that represents the subset population of cancer stem-like cells. Herein we report the isolation of CD133-positive cells (LC-CD133+) and CD133-negative cells (LC-CD133−) from tissue samples of ten patients with non-small cell lung cancer (LC) and five LC cell lines. LC-CD133+ displayed higher Oct-4 expressions with the ability to self-renew and may represent a reservoir with proliferative potential for generating lung cancer cells. Furthermore, LC-CD133+, unlike LC-CD133−, highly co-expressed the multiple drug-resistant marker ABCG2 and showed significant resistance to chemotherapy agents (i.e., cisplatin, etoposide, doxorubicin, and paclitaxel) and radiotherapy. The treatment of Oct-4 siRNA with lentiviral vector can specifically block the capability of LC-CD133+ to form spheres and can further facilitate LC-CD133+ to differentiate into LC-CD133−. In addition, knock-down of Oct-4 expression in LC-CD133+ can significantly inhibit the abilities of tumor invasion and colony formation, and increase apoptotic activities of caspase 3 and poly (ADP-ribose) polymerase (PARP). Finally, in vitro and in vivo studies further confirm that the treatment effect of chemoradiotherapy for LC-CD133+ can be improved by the treatment of Oct-4 siRNA. In conclusion, we demonstrated that Oct-4 expression plays a crucial role in maintaining the self-renewing, cancer stem-like, and chemoradioresistant properties of LC-CD133+. Future research is warranted regarding the up-regulated expression of Oct-4 in LC-CD133+ and malignant lung cancer