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text:
Australia tops Norway as world's happiest nation
12:14 23.05.2012
text: Kazinform
views: [866]
Related articles
IMF backs tax and interest rate cuts to dig UK out of recession
Hong Kong faces huge budget surplus
9.3% GNP growth is forecasted in Kazakhstan in 2004
Australia is the world's happiest nation based on criteria including income, jobs, housing and health, the Organization for Economic Cooperation and Development said.
Australia led Norway and the U.S., the Paris-based group's Better Life Index showed, when each of 11 categories surveyed in 36 nations is given equal weight.
Life expectancy at birth in Australia is almost 82 years, two years higher than the OECD average, the survey showed. More than 72 percent of people aged 15 to 64 in Australia have a paid job, above the OECD average of 66 percent.
Australia was the only major developed nation to avoid the 2009 worldwide recession and the government is aiming to return its budget to surplus in the fiscal year beginning July 1. A mining investment boom has spurred hiring and driven the unemployment rate below 5 percent, even as an elevated currency hurts manufacturing and tourism, Kazinform quotes Bloomberg.
"Australia performs exceptionally well in measures of well-being, as shown by the fact that it ranks among the top countries in a large number of topics in the Better Life Index," the OECD said.
As Europe faces years of fiscal austerity, Australia's budget surplus would make it one of the first developed nations to emerge from an era of red ink caused by the worldwide financial crisis that started in 2008. Even so, the nation's Labor-led government trails the opposition in opinion polls.
'Dodged That Bullet'
"We've all just lived through the biggest economic meltdown since the Great Depression," Prime Minister Julia Gillard said in a May 9 interview, when asked why her government has low poll ratings. "While Australia has largely dodged that bullet -- we didn't have a recession, for example -- it has had an impact on people. We're a government with a big reform agenda. I'm not surprised there's some nervousness in the community."
Australia's unemployment rate will rise to the highest level since 2009 as industries outside of mining struggle with an elevated currency, the OECD said in its economic outlook released in Paris yesterday.
The nation's jobless rate will climb to 5.7 percent in 2013 from 5.4 percent this year. That would match a level reached in September 2009 and be higher than the average in the past decade of 5.2 percent.
"Mining expansion will continue, but some other sectors are having to adjust to the high level of the exchange rate and raise their productivity, which can be expected to weigh on the labor market," the OECD said in the report. "Faster fiscal consolidation will also weigh somewhat on demand."
Also in the news
16:28 01.02.2013 Kazakh First Vice PM urges to check up state material reserve
11:58 01.02.2013 New tool for waste management introduced in Kazakhstan
11:57 01.02.2013 Pollutant emissions volume decreased by 1.3% and 1.7%
10:28 01.02.2013 Clinton says U.S. failing to explain policies to Muslims
10:25 01.02.2013 Assassination attempt made on Armenian presidential candidate

subset: commoncrawl


text:
Buy this item and earn 13,498 reward points.
View Clip
Leather Briefcase INCLUDED with Appearing STOOL!Casually walk in carrying your Briefcase & set it next to you.Unlatch the Briefcase lid and slowly pull out a Two foot Four legged Stool. Pull the stool out slowly. It grows & grows, the laughs get stronger & stronger!This wooden topped stool is a solid looking 3 dimensional object & will fool you even close up. It looks just like an ordinary everyday kitchen utility stool. The Briefcase interior is designed with a built in combination rolling & stabilizer system.Show all 4 sides, the top & bottom of the Briefcase!


text:
Presents home theater buying guides, tips and tools, product reviews, and photo reports.
Contains staff product reviews, discussion forums, consumer reviews, set-up tips and online shopping for receivers, speakers, furniture, cables and other must-haves for your home theater.
Presents the thoughts and musings of UK consumers over a variety of audio visual products. Reviews also presented.
Comprehensive presentation exploring general AV systems, interconnects, digital and analogue audio and video, and format conversions.
UK-based (hence Home Cinema rather than Home Theater) site that offers consumer reviews on a variety of components of Home Cinema systems. Search reviews by component name or by brand.
A simple site that sells an ebook explaining Home Theater. Read an excerpt (60 pages) of the book online for free.
Collection of forums designed to help users become better informed in regards to home theater equipment.
Discussion forums covering all aspects of home theater systems including electronics equipment, design, construction, and acoustics.
Reviews and product information on the latest and greatest remote controls.
Features news, reviews, and opinions on the latest home theater equipment and accessories.
Directory of home theater information, reviews, and opinion.


text:
One of the big challenges for an ambitious film like Life of Piis that it seeks a wide audience without box-office star power - thefilm relies on first-time Indian actor Suraj Sharma and an intricatelycomputer-generated Bengal tiger.
Director Ang Lee even made the decision to remove Spider-Man actor Tobey Maguire from the film entirely because he was too famous for his small part.
Maguire, who worked with Lee on 1997's The Ice Storm, had filmed the role of a writer interviewing the older Pi (played by actor Irrfan Khan), which sets the story in motion.
Afterfilming was complete, Lee found that Maguire's star power was dwarfingthe performance. He called for the scenes to be shot again with Britishactor Rafe Spall stepping in as the writer.
"I misjudged the situation," says Lee. "I underestimated the power of stars."
"Ilove Tobey. But it's a small part," he adds. "So when it's a movie starsitting there, it captures attention. It didn't really work out."
Khan admits he was taken aback to find he would be shooting the scenes again with a different actor.
"Iwas finished with the film. I had deleted everything from my system,"says Khan. "And to do it again, it needs a huge emotional investment."
Khan turned it into a positive by reworking aspects of his performance.
"It gave me an opportunity to work on it again," says Khan. "I learned that from Ang, to use it constructively."
"We knew exactly what we needed," says Lee. "So the shooting went by very smoothly."
Lee says Maguire understood the decision to change actors.
"He said, 'Whatever works for your movie,' " Lee recalls.


text:
LYNDON B. JOHNSON NATIONAL GRASSLAND. The Lyndon B. Johnson National Grassland is on Red Deer Road six miles north of Farm Road 670 in Wise and Montague counties. The 20,315-acre preserve was purchased by the United States Department of the Interior during the 1930s under the Bankhead-Jones Farm Tenant Act in an effort to return some the badly eroded land of the region to its natural state. The grassland area, which consists of numerous unconnected parcels, is administered by the United States Department of Agriculture Forest Service regional office in Lufkin under a policy of multiple use for range, watershed, recreation, and wildlife. In it, open grasslands and woodlands provide habitat for a variety of wildlife ranging from deer and rabbits to quail and turkeys. Facilities at the grassland include camping and picnicking areas and equestrian trails; boating and fishing are possible on Black Creek and Cottonwood Lake.
George Oxford Miller, Texas Parks and Campgrounds: Central, South, and West Texas (Austin: Texas Monthly Press, 1984).
The following, adapted from the Chicago Manual of Style, 15th edition, is the preferred citation for this article.Christopher Long, "LYNDON B. JOHNSON NATIONAL GRASSLAND," Handbook of Texas Online (http://www.tshaonline.org/handbook/online/articles/gkl23), accessed October 03, 2015. Uploaded on June 15, 2010. Published by the Texas State Historical Association.


text:
MS Dynamics CRM 3.0
- donald
connection.instance_variable_get(:@connection).handle. instance_variable_get(:@handle).setproperty('CommandTimeout', 3600)
Sure would be nice if something this useful could be manipulated more elegantly. Perhaps something to add to the todo list for DBI2 if and when Kirk gets that project off the ground.
Actually, on that note, I just ran into another problem with DBD-ADO, specifically with the autocommit mode. When it's on, it only commits after a statement is executed if it thinks it's a read operation. One problem is, the algorithm fails to treat SELECT INTO statements as write operations. I would think one would want to commit after all operations anyway if one's in autocommit mode; it would seem you don't really care about getting a consistent view of the database in that case.


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The news has included positive jobs growth, increased consumer spending and increased consumer confidence. Each number, while positive, still reminds us that we have a long way to go.
If we look at the markets you would think we are free and clear from recession and bad news. Oil prices, the stock market and rates have all moved up significantly. On the other hand, if we look at the recovery statistics, we are far from free and clear. A few hundred thousand jobs do not make up for eight million in losses.
Yes, consumer confidence is up. The Conference Board, a New York-based research group, said its Consumer Confidence index rose to 52.5 in March from 46.0 in February. However, a reading of 90.0 is supposed to describe a stable economy and 100.0 a growing economy.
If the numbers are still dismal, why are the markets celebrating? For one, we are climbing out of such a large hole, any move in the right direction feels good.
This quote from CNN/Money seems to give us a second explanation: It's a growing optimism that can best be seen in consumers' actions, not their answers to various polls.
"If you look at what they're saying, they're still very nervous," said Mark Zandi, chief economist at Moody's Economy.com. "But if you look at what they're doing, they're more convinced that things have turned the corner."
Consumer spending is improving at a faster pace than many had expected at this stage in the recovery. We have said this time and time again. This is a crisis of confidence and this malaise does not end until confidence returns. Even if this is the beginning of the cycle, any evidence of a bolder consumer is going to be good news. Despite this theory, it is still possible that the markets are getting ahead of themselves with regard to the recent gains we have seen. Expect some pull-backs along the way.
The Markets
Rates rose again in the past week to their highest levels since August of last year. Freddie Mac announced that for the week ending April 8, 30-year fixed rates averaged 5.21 percent, up from 5.08 percent the week before. The average for 15-year fixed also rose to 4.52 percent. Adjustables increased as well with the average for one-year adjustables rising to 4.14 percent and five-year adjustables increasing to 4.25 percent. A year ago 30-year fixed rates were at 4.87 percent.
"Once again, rates on home loans followed bond yields higher amid a positive March employment report," said Frank Nothaft, Freddie Mac vice president and chief economist. "The economy added 162,000 jobs, which was the largest monthly gain over the past three years. In addition, revisions raised the January and February figures by a combined 61,000 workers. Excluding government employees, private payrolls rose for the third consecutive month and were the strongest increase since May 2007.
Following its extension in early November of last year, the homebuyer tax credit is showing some impact on housing market activity. Pending existing home sales jumped 8.2 percent in February, well above the market consensus and represented the second largest increase since records began in 2001, the National Association of Realtors reported. Homebuyers must enter a housing contract by April 30 and close by June 30 in order to receive the tax credit."
Sales of homes priced above $750,000 are starting to pick up after being frozen at a very low level last year. For most of last year, first time homebuyers were driving sales and they were focused "almost exclusively" on foreclosed properties and other bargains priced under $250,000, according to Walter Moloney, economics spokesman for the National Association of Realtors.
"Beginning in October for the first time we started seeing increases in other sales categories," Maloney said. "Sales of homes priced from $750,000 to $1 million jumped 40 percent in January from a year ago, yet accounted for only 1.3 percent of total sales. Over 70 percent of sales in January involved properties priced under $250,000.
Sales in all price classes rose in January.
Despite this movement in the top tier, foreclosure and short sales are expected to remain at a very high level. Last year, distressed sales comprised 36 percent of existing home sales. In a normal market, distressed sales make up 15 percent of sales.
"Maybe it will come down to 33 percent this year," said NAR chief economist Lawrence Yun. "By historical standards, we have never seen anything like this before."
Real estate investors are back, according to the National Association of Realtors and other market observers. Investors made more than 17 percent of home purchases in January, with 26 percent of all sales transacted in cash.
"We bottomed out in 2008, and in late 2009, prices stabilized and investors have returned," says Mark Fleming, chief economist at research firm First American CoreLogic. "It's a different type of investor going after foreclosed properties and expecting to hold on for longer time frames."
These buyers believe that the only direction housing values can go is up, because it costs more to build than it does to buy. Leonard Baron, a real estate professor at San Diego State University, said. "It's because prices have dropped so much and rents really haven't. The deals were unbelievable."
Despite the challenges facing the housing market, 65 percent of Americans would still prefer to own a home rather than rent, according to a Fannie Mae national housing survey. In addition, 43 percent of respondents cite safety as a key reason to buy, while 33 percent are motivated to buy because they perceive schools to be better in neighborhoods where most homes are owned by their residents.
The survey results released Tuesday show that both buyers and renters are more cautious than they used to be. About 23 percent of renters say they will buy a home, but later than they once hoped. A full 70 percent said they believe buying a home continues to be one of the safest investments available. This compares to 74 percent who think putting money into a bank account is safe. Only 17 percent believe buying stocks is a safe investment. Also, 60 percent believe that it will be harder for them to get a loan to purchase a home than it was for their parents.


text:
This April 11, 2012 photo shows Detroit Red Wings forward Darren Helm (43) moving the puck ahead of Nashville Predators center Mike Fisher (12) in the first period of Game 1 of a first-round NHL hockey playoff series on Wednesday, April 11, 2012, in Nashville, Tenn. (AP Photo/Mark Humphrey)
2012-06-19 12:37:00
DETROIT - The Detroit Red Wings have agreed to a four-year contract with Darren Helm.
The 25-year-old centre from Winnipeg has been with the Wings since they drafted him in the fifth round in 2005.
He had nine goals, 17 assists and 12 penalty minutes in 68 games last season.
What do you make of Raffi Torres' 41-game suspension?


text:
Where am I?
Americans with Disabilities Act Accommodations
Fontbonne University offers academic accommodations to students with physical or mental impairments. Any Fontbonne student is eligible for academic accommodations or special services if:
1. The student self-identifies that he or she has a physical or mental impairment and needs an academic accommodation based on his or her individual needs;
2. The student submits a request for an academic accommodation to the Director of the Kinkel Center for Academic Resources, along with any supporting documentation, at least 30 days before the semester begins or soon as reasonably possible; and
3. The student provides reasonable, appropriate, and verifiable supporting documentation of the physical or mental impairment at the time of the request for an academic accommodation or within 30 days after the request, unless extenuating circumstances exist.
For requests or inquiries regarding other accommodations, including auxiliary aids or services, or modifications of policies or procedures to participate in a program, service, or activity, or the existence and location of services, activities and facilities that are accessible to and usable by individuals with disabilities, please contact the Section 504/ADA Coordinator at 314-889-4175.
The booklet, Access to Education at Fontbonne University, Academic Accommodations for Students with Disabilities, is available upon request and online at www.fontbonne.edu/kinkel.
For additional information or view Downloads, contact Kevin Pelzel, Director of the Kinkel Center for Academic Resources/ADA Coordinator, at (314)719-3627 or firstname.lastname@example.com.
- Students who receive academic accommodations must fill out a Request for Academic Accommodations each academic year.
You may Request for Academic Accommodations (pdf, 123.45KB) by downloading this form.
- You may also download the ADA Manual online.


text:
By C.J. McMANUSSun Advocate reporter
East Carbon officials have placed residents on watering restrictions. The city will also inform Sunnyside Cogeneration in writing that water storage in Grassy Trail Reservoir is dangerously low.
During a special meeting July 2, the City Council voted unanimously to limit outside watering to between the hours of 8 p.m. and 9 a.m. daily. The council also asked that city attorney Jeremy Humes draft a letter to Sunnyside Cogeneration letting the company know that their intake must slow because the reservoir has no surplus water.
The issue resurfaced during Tuesday night's council session as Mayor Orlando LaFontaine questioned why the cogeneration plant had yet to slow its consumption.
"There is still no conservation from the power plant," said LaFontaine. "Yesterday, I was told their intake was 549,000 gallons for a single day, the whole of East Carbon used 200,000 gallons. What is going on?"
Humes reported that current contracts keep the city from restricting the plant's consumption without 180 days notice. He also informed the mayor that while the council has power to place the residents on restriction, a city ordinance keeps them from restricting businesses.
"If the city wants to look at changing that ordinance to give this body power to restrict businesses they can do that," said Humes. "The city has taken action with regard to the sale of surplus water to Sunnyside city, but unfortunately we are bound by the terms of that contract which states that any change can't kick in for 180 days."
The Sunnyside Cogeneration Plant obtains its water through a 1983 contract with Sunnyside city.
LaFontaine asked that Humes contact water rights attorney Steve Clyde to see if any superceding state ordinance could push conservation on the plant before water levels become "dangerously low."
City maintenance officials have told the council that the reservoir is dropping between five and seven inches per week, a number that will only increase as the summer wears on.
"I've never seen that lake down this low at this time of the year," said LaFontaine. "It's down seven feet from the spillway and we are in July. It's usually three feet below the spillway in September and October. I'm really concerned about the reservoir."


text:
Grey's Anatomy doctor on Sesame Street
by Adam Finley, posted May 16th 2006 9:02AM
Despite everyone saying it's one of the best shows on TV right now, I've never watched Grey's Anatomy. I suppose I should check it out at some point just to see what all the woo-wa is about, but until then I thought I'd mention that TR Knight, the actor who plays Dr. George O'Malley on the program, will be appearing on an episode of Seasame Street. He won't play a doctor, however, he'll play the letter I. More specifically, he'll play a Private I. Give Me My Remote has some pics from the scene with Knight using those keen detective skills you can only learn on Seasame Street.


text:
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text:
Yesterday afternoon I did a Channel 9 video talking about the Reference Source program we announced yesterday, plus doing a live demo of how it works. That's the first time I've done one of the Channel 9 videos. It's a little disconcerting at first - there's no script or practice or even editing. Some guys pretty much just show up in your office with a handheld camera and a tripod and start filming. Fortunately, it seems like it turned out pretty well. But I'm definitely not expecting any Oscar nods.
In the video, you'll see me actually run the debugger on a simple Windows Forms project, and then load the symbols for System.Windows.Forms.dll and mscorlib.dll. In the video, VS was already configured, but here's some more detail on exactly how that's going to work.
As noted in Scott's blog, you need to do some setup in Tools/Options/Debug. Here's the full list of steps, just to show how easy this is to set up. Also note, this functionality isn't present in the VS 2008 Beta 2 release - it's been added for RTM.
First, you need to enable Source Server support, and then turn off "Just My Code" (because its, uh, not your code that you want to debug!). If you leave this on two things happen. First, you won't see the .NET frames in the call-stack. Second, even if you enable "Show External Code" on the call stack, you won't be able to set breakpoints. "Just My Code" disables setting breakpoints in optimized code.
Next, you enter the symbol server path. One thing Scott didn't call out is that the URL for this is still TBD - the one we put in there is temporary. Once the servers are ready to come online, we'll have a final URL for this. I put that URL in there just because the server I'm currently using for testing is, well, under my desk. No, you can't have that URL. ;)
Note you're also required to add a caching path as well.
I've seen some questions about why I used the Right-Click -> Load Symbols method on the call-stack, so let me dig into this a bit.
The two settings that are relevant here are the "Manual Load" setting (red), and the "Load 'Em Now" setting (green).
"Load 'Em Now" means that it will attempt to load all the symbols when you close the dialog.
When using the Reference Source stuff, I think most people will want to use Manual Load, strictly for performance reasons. We all know how critical it is for F5 to be snappy, and that's at issue here.
Two things impact this.
Problem number 1: There may be lots of symbols out there and they tend to be large (10+ MB). If you're on a slower connection, it could take a fair amount of time to launch your first debugging session. You could easily be looking at 50 megs of symbols. Fortunately, these do get cached locally. (Hint: I do recommend doing this on your first debugging session, and then going to lunch or something just as a way to get all of the symbols downloaded and cached at once).
Problem number 2: And this is the big one. VS doesn't really have any way of remembering which symbols it found and which ones it didn't between debugging sessions. Since you've added an external server for lookup, it's going to go out and ping that server for every symbol that it doesn't find locally/cached. It doesn't know that the symbols for user32 or ntdll aren't on that server, so it's going to ask EVERY time you launch the debugger.
Again, depending on how fast your Internet connection is, and how fast the servers are, this may or may not be an issue. But ASP.NET loads something like 18 DLLs into it's process space, and in my quick testing (over a purposely slower connection) it made the F5 time go from ~2 seconds to 5-or-6, which just isn't acceptable.
By doing the manual load, you avoid this problem altogether. Also note you can multi-select in the Call Stack to do multiple DLLs at once. I have been talking with the VS debugger guys about ways to make this smarter/more efficient but we haven't found a robust solution quite yet, and in any case the behavior we have today is the behavior you'll get for RTM.
So it will work either way, and you can decide which is better for your scenarios when you actually start using it.
We also announced that we'll be making the source available as a download as well. Note that this won't be online immediately. The debugging experience really is the major piece of the value here for most people, so I've been focused on delivering that first, and that will be ready close to the VS 2008 ship day (the plan is for the servers to go live on the same day, I think it's going to happen, but it's aggressive, so there may be a small lag there).
Anyway, that's V1 of the server-side piece. We're looking to get the downloadable source functionality into the V2 server-side, which will likely be rolled out after the New Year. You might be saying to yourself "geez, just zip up the darn source, what's so hard about that?" Good question.
One of my top goals here was to make sure that the cost for any individual team releasing source was very close to zero. If this process is expensive, or error prone, or cumbersome, then it won't happen as often, which is bad for everyone. So on this front, I'd like to see if we can't make the server-side build the download distro's dynamically so that it happens for "free" and maybe, just maybe, users can then download source that exactly matches their version in the way the debuggable source does with no extra packaging work. Hey, a kid can dream, right?
Hope that helps...
PingBack from http://msdnrss.thecoderblogs.com/2007/10/04/channel-9-video-more-details-on-reference-source/
Scott just announced it: http://weblogs.asp.net/scottgu/archive/2007/10/03/releasing-the-source-code
This was asked in Scott's annoucement blog, but maybe you can answer it as well (I don't think it got answered - probably got burried under the 600odd comments on his blog :) )
Can we use this functionality (of loading symbols manually / automatically) for our own code? That is, if we as a product publish our own set of APIs for the customers, and now want them to debug into our code (similar to what you are presenting here for .NET). Would your framework allow for that? If I didn't know much, I'd say that we just load another server onto that list, and try to load the symbols (right-click as in your example).
Ofcourse, we need to what the "symbols server" implements.
Symbol Server actually doesn't implement anything - it's actually just a method of laying out the symbol files in a way that a debugger can figure out which one is the right version. Other than that, it's a plain web server, and it's already available, see:
But most of this is already available there. The piece that Orcas provides - being able to get a file via HTTP out of a PDB reference - will allow you to do the Source Server part (also documented in the Debugging Tools for Windows). After this gets shipped I'll sit down and see what it would take for someone to implement this and then do a blog post about it. Feel free to remind me post-VS2008 ship. :)
Hope that helps!
Great video! If possible, I want to say, could you speak more slowly next time for the people who are not good at English?
To have the debugging not try to load symbols for modules that won't have symbols (and therefore not incur the performance cost of searching in vain), there is a solution.
The debugger can maintain a list of modules for which to not load symbols. This would be the full path name from the pdb.
The user could add an item to this list from a new context menu item on the Call Stack and Modules windows: "Exclude from Symbol Search" (or some better name).
The Symbols dialog can provide this list, and a means to add and remove from this list. There could also be import and export, and there could be a default list of the managed symbols that wouldn't be found, or the list could be imported by the user.
You could make this happen automatically. The debugger can add a module to this list when the debugger can't find symbols for it. After the symbol path is modified, the debugger can scan for these modules again that first time, so you take the perf hit only once.
These changes would work for both native and managed debugging, and could really help start debugging performance.
Just some suggestions...
Hi Adam -
Yes there are several possible solutions to this problem that we've discussed, including those you've outlined above.
Unfortunately none of those will be available in the Visual Studio 2008 upcoming release.
You make a good point - however - that this would be generally useful as a way to prevent loading of symbols for binaries you'll never care about debugging.
By now I'm sure you've heard that Visual Studio 2008 & the .NET Framework 3.5 shipped on Monday .
By now I'm sure you've heard that Visual Studio 2008 & the .NET Framework 3.5 shipped on


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G protein coupled receptors (GPCRs) are one of the most widely studied gene superfamilies. Thousands of GPCR research studies have utilized heterologous expression systems such as human embryonic kidney cells (HEK293). Though often treated as 'blank slates', these cell lines nevertheless endogenously express GPCRs and related signaling proteins. The outcome of a given GPCR study can be profoundly influenced by this largely unknown complement of receptors and/or signaling proteins. Little easily accessible information exists that describes the expression profiles of the GPCRs in cell lines. What is accessible is often limited in scope - of the hundreds of GPCRs and related proteins, one is unlikely to find information on expression of more than a dozen proteins in a given cell line. Microarray technology has allowed rapid analysis of mRNA levels of thousands of candidate genes, but though often publicly available, the results can be difficult to efficiently access or even to interpret.
To bridge this gap, we have used microarrays to measure the mRNA levels of a comprehensive profile of non-chemosensory GPCRs and over a hundred GPCR signaling related gene products in four cell lines frequently used for GPCR research: HEK293, AtT20, BV2, and N18.
This study provides researchers an easily accessible mRNA profile of the endogenous signaling repertoire that these four cell lines possess. This will assist in choosing the most appropriate cell line for studying GPCRs and related signaling proteins. It also provides a better understanding of the potential interactions between GPCRs and those signaling proteins.
The G protein-coupled receptor (GPCR) gene superfamily consists of hundreds of members that are widely expressed in all tissues and serve as receptors for a diverse complement of ligands. Approximately 100 of these receptors are considered orphan GPCRs, in that no endogenous ligand has been confirmed for them [1]. Characterized by having seven transmembrane alpha-helical domains [2], GPCRs mediate a wide spectrum of cellular processes ranging from cell growth to neurotransmission [1-3]. A number of classification systems for GPCRs have been developed as bioinformatic tools[3-5]. One of the most commonly used GPCR classification systems, the one set forth by Kolakowski and developed by Vriend [4,6,7], groups GPCRs into six classes based on structural similarities to prototypical receptors. Class A GPCRs are the most abundant (>80% of all GPCRs), defined by a high sequence homology to rhodopsin, and include the chemosensory receptors. Class B GPCRs are also known as secretin-like receptors. Class C GPCRs are the metabotropic glutamate-like receptors. Class F/S receptors consist of frizzled/smoothened receptors, though there is debate about their ability to couple to G proteins [2]. Class D/Fungal pheromone and Class E/cAMP receptors are absent in mammals.
On activation via ligand binding, GPCRs couple to heterotrimeric G proteins composed of three subunits: Gα, β and γ. G protein α subunits are classified as members of one of four groups: Gi/o, Gs, Gq, and G12/13 [8]. Each subunit couples to specific cellular protein targets (e.g. adenylyl cyclases) through which cellular activity is modulated. The Gβ/γ G protein subunits are capable of acting at their own specific targets, such as modulating ion channel activity [9-11]. The available complement of heterotrimeric G proteins will therefore affect its response profile.
A regulatory system controls the timing and duration of GPCR signaling. GPCR kinases (GRKs) phosphorylate agonist-occupied receptors, typically leading to receptor desensitization. Beta-arrestins are scaffolding proteins that are recruited to activated GPCRs and prevent G protein association with the receptor. They also serve to spatially segregate GPCR signaling to molecules such as mitogen-activated protein kinases [12,13]. The Regulators of G protein signaling (RGS) proteins, which enhance the GTPase activity of Gα subunits, is another large family of proteins important in fine-tuning GPCR signaling [14,15].
Due to their central roles in many cellular functions, GPCRs are important therapeutic targets. Different reports estimate that between 30 and 50% of all prescription drugs target GPCRs. Interestingly, these drugs only target ~10% of the non-chemosensory receptors, leaving hundreds of GPCRs as potential drug targets [2,9,16].
Identifying ligands, studying receptor protein interactions, and measuring cellular effects of receptor activation is often achieved by heterologous expression of GPCRs in cell lines such as HEK293 and AtT20 [17,18]. They also serve as models of cell types from which they are drawn (e.g. BV2 for microglia and N18 for neurons) [19-21]. However these cell lines have remained something of a black box; researchers make use of them without full knowledge of the complement of GPCRs and related proteins. The presence of an unknown protein in these cell lines may confound an otherwise sound series of experiments and differential expression of GPCRs and their regulatory proteins may explain differences in reported results across cell lines [13,17,22-25]. It is also clear that GPCRs can form oligomers with other GPCRs. These oligomers may confer different signaling properties to a transfected GPCR of interest, and can add layers of variability and complexity.
Efforts to define expression of GPCRs, on a receptor-by-receptor basis, using polymerase chain reaction (PCR)-based methods have only scratched the surface. Even for the widely used HEK293 cells, the expression of fewer than thirty GPCRs has been described [17,26]. Recently developed high-throughput methods have made possible the simultaneous assay of mRNA levels for thousands of genes. Microarray analyses have matured sufficiently in terms of accessibility and cost to make their application to this question tractable. We are not the first to make use of microarray technology to examine mRNA expression levels in HEK293 cells [26], however, most studies that have used microarray analyses on these cell lines have examined specific gene products of interest and reported data only for those gene products [20,26-28]. Their full data sets are available through NCBI, but are difficult for the non-specialist user to access and collate.
As a consequence, we sought to identify and make accessible the full complement of endogenously expressed non-chemosensory GPCRs of four cell lines used in GPCR research: the HEK293, AtT20, BV2 and N18 lines. Using microarray analysis we measured the mRNA levels from each of these four cell lines specifically identifying the expression levels of GPCRs and over a hundred of GPCR-related gene products and report them here.
We first examined HEK293 cells, a cell line that was made by transforming human embryonic kidney cells with adenovirus type 5 DNA. Developed in 1977, HEK293 cells may be the single most widely used cell line for heterologous expression (both transient and stable expression) of GPCRs and other proteins of interest [17]. Figures 1,2,3,4,5 and 6 show the mRNA levels of GPCR and GPCR-related gene products found in HEK293 cells. Of Class A GPCRs, shown in figures 1 and 2, HEK293 cells express mRNA for several different types of receptors within specific families of receptors: multiple types of adenosine, lysophospholipid, purinergic, prostanoid, and protease-activated receptors, among others. In results relevant to the study of orphan GPCRs (figure 3), HEK293 cells contain high message levels of GPR37, 2 types of orphan-LGR (glycoprotein hormone) receptors--LGR4 and LGR5, GPR39--and very high levels of the melatonin-related receptor GPR50. HEK293 cells may therefore be suitable tools for deorphanization of these receptors. Interestingly, HEK293 cells contain relatively little mRNA for Class B GPCRs with known ligands (figure 4A), but quite high levels of many orphan Class B GPCRs. The same is true for Class C GPCRs as seen in figure 4B though they do appear to contain high levels of GABABR1 receptor message, though lacking mRNA for GABABR2, necessary to form a fully functional GABA-B receptor. Finally, for GPCRs, HEK293 cells contain a number of types of frizzled receptors as well as smoothened receptor (figure 4C). Figures 5 and 6 show the mRNA levels of various types of GPCR signaling-related gene products such as the G proteins and a number of their targets and downstream effectors as well as proteins that regulate GPCR signaling, the GRK, beta-arrestin (ARRB) and RGS proteins. Interestingly HEK293 cells express mRNA for numerous isoforms of adenylyl cyclase and protein kinases A and C (PRKA, PRKC) and phospholipase C (PLC), while having a limited diversity of phospholipase A (PLA) and RGS proteins. HEK293 cells also appear to have an almost full complement of G protein isoforms for each subunit, making these cells an attractive environment to express any number of GPCRs to study downstream G protein-mediated signaling.
Figure 1. mRNA expression levels of Class A GPCRs. Microarray analysis of mRNA levels of Class A GPCRs with known ligands for HEK293, AtT20, BV2 and N18 cell lines. The gray line indicates the threshold of statistical significance and the dark bars are proteins for which statistically significant levels of mRNA were detected. White bars indicate levels of mRNA for proteins that were present, but did not reach statistical significance. Abbreviation: 5-HT = 5-hydroxytryptamine; GNRH = Gonadotrophin-releasing hormone.
Figure 2. mRNA expression levels of Class A GPCRs. Microarray analysis of mRNA levels of Class A GPCRs with known ligands for HEK293, AtT20, BV2 and N18 cell lines. The gray line indicates the threshold of statistical significance and the dark bars are proteins for which statistically significant levels of mRNA were detected. White bars indicate levels of mRNA for proteins that were present, but did not reach statistical significance. Abbreviation: MCH = Melanin-concentrating hormone; TRH = Thyrotropin-releasing hormone.
Figure 3. mRNA expression levels of Class A Orphan GPCRs. Microarray analysis of mRNA levels of Class A GPCRs with unknown ligands for HEK293, AtT20, BV2 and N18 cell lines. The gray line indicates the threshold of statistical significance and the dark bars are proteins for which statistically significant levels of mRNA were detected. White bars indicate levels of mRNA for proteins that were present, but did not reach statistical significance. Abbreviation: ND = not determined.
Figure 4. mRNA expression levels of Class B, C, and F/S GPCRs. Microarray analysis of mRNA levels of GPCRs with known ligands for HEK293, AtT20, BV2 and N18 cell lines. A: Class B GPCRs. B: Class C GPCRs. C: Class F/S GPCRs. The gray lines indicate the threshold of statistical significance and the dark bars are proteins for which statistically significant levels of mRNA were detected. White bars indicate levels of mRNA for proteins that were present, but did not reach statistical significance. Abbreviations: BAI = Brain-specific angiogenesis inhibitor; CELSR = Cadherin EGF LAG seven-pass G-type receptor; CRF = Corticotropin-releasing factor; ND = Not determined; PACAP = pituitary adenylyl cyclase-activating polypeptide; VIP = Vasoactive intestinal peptide.
Figure 5. mRNA expression analysis of GPCR related signaling proteins. Microarray analysis of mRNA levels of GPCR related signaling proteins for HEK293, AtT20, BV2 and N18 cell lines. The gray lines indicate the threshold of statistical significance and the dark bars are proteins for which statistically significant levels of mRNA were detected. White bars indicate levels of mRNA for proteins that were present, but did not reach statistical significance. Abbreviations: GRK = GPCR Kinase; PKA = Protein kinase A; PKC = Protein kinase C.
Figure 6. mRNA expression analysis of GPCR related signaling proteins. Microarray analysis of mRNA levels of GPCR related signaling proteins for HEK293, AtT20, BV2 and N18 cell lines. The gray lines indicate the threshold of statistical significance and the dark bars are proteins for which statistically significant levels of mRNA were detected. White bars indicate levels of mRNA for proteins that were present, but did not reach statistical significance. Abbreviations: ND = Not determined; PLA = Phospolipase A; PLC = Phospholipase C; PLD = Phospholipase D; RGS = Regulator of G protein signaling.
Next we analyzed the AtT20 cell line, a neuroendocrine line derived from a mouse pituitary tumor that has neuron-like properties [29]. This cell line is often used as a model neuroendocrine cell line and has been a useful cell line to study of ion channel modulation by GPCRs [18,30,31]. Unlike HEK293 cells, there has been relatively little work performed to identify the GPCRs and related signaling molecules present in AtT20 cells. Our current results highlight that AtT20 cells express a diverse range of GPCR mRNAs. Figures 1 and 2 show that they possess a number of types of Class A receptors with a few isoforms of each type. According to our analysis here, they express a few different isoforms of adenosine, chemokine, dopamine, neuropeptide FF, prostanoid and somatostatin receptors with a number of other individual members from other types. Figure 3 shows that AtT20 cells have a limited breadth of Class A orphan GPCRs. In Class B, AtT20 cells express mRNA for a number of glucagon, orphan brain-specific angiogenesis inhibitor (BAI), and orphan latrophilin receptors (figure 4A). Like HEK293 cells, AtT20 cells express mRNA for GABABR1 (with a detectable, but not significant level of GABABR2 mRNA), but unlike HEK293s they express several metabotropic glutamate receptor genes (figure 4B). For Class F/S in AtT20s we detected mRNA for six frizzled receptors but not smoothened receptor mRNA (figure 4C). AtT20's have a somewhat sparser repertoire of GPCR signaling-related gene products than HEK293s, especially within the G protein subunits (figures 5 and 6).
We next examined BV2 cells, a cell line that is often used as a model system for the study of microglial function [32]. As shown in figures 1 and 2, BV2 cells predominately possess mRNA for anaphylatoxin, chemokine, and prostanoid Class A GPCRs as would be expected from an immune system-derived cell line. They also express mRNA for a scattering of other receptor types, such as a few muscarinic, somatostatin, and lipid receptors, among others. As has been reported in the literature, BV2 cells express CB2 cannabinoid receptors (Cnr2) [33], which makes them unique among the other cell lines examined here. We also observed the expression of a large number of different Class A orphan GPCR mRNAs as seen in figure 3, though a much less diverse repertoire of orphans from Class B (figure 4A) or Class C (figure 4B) receptors were present. BV2 cells express only one Class C GPCR at a significant, albeit, low mRNA level: the metabotropic glutamate receptor, mGluR1 (Grm1). Figure 4C shows that BV2 cells possess mRNA for a few different types of frizzled receptors as well as the smoothened receptor. BV2 cells have a wide complement of GPCR signaling-related gene products (figures 5 and 6). Though not quite as extensive as HEK293 cells, BV2 cells possess numerous isoforms of different phospholipases, PKA, PKC, and adenylyl cyclase. Their beta-arrestin, RGS protein, and GRK levels suggest the capacity to highly regulate GPCR signaling as well.
Lastly we investigated the N18 cell line. This cell line is derived from a neuroblastoma and is commonly employed as a neuron-like cell line. It has been used as a tool to analyze ion channel function in response to toxins and other regulators [19,34-37]. We found that N18 cells have mRNA for a broad range of different Class A GPCRs as seen in figures 1 and 2. N18 cells have mRNA for a few types of muscarinic acetylcholine, adenosine, chemokine, neuropeptides, prostanoids, protease-activated, and somatostatin receptors with a few other individual types such as CB1 cannabinoid receptors (Cnr1). Like the BV2 cells, N18 cells have mRNA for quite a few Class A orphan GPCRs (figure 3) with a similar profile as well. They further express mRNA for a broad complement of Class B GPCRs (figure 4A) but express a limited profile of Class C GPCRs (figure 4B). They also have mRNA for a number of different types of frizzled receptors, but lack mRNA for a smoothened receptor (figure 4C). N18 cells express high levels of many of the GPCR signaling-related gene products. They have abundant levels of G proteins and numerous isoforms of PKA. N18 cells' GPCRs are also presumably tightly regulated based on the assortment of GRK, RGS and beta-arrestin mRNAs detected (figures 5 and 6).
In order to validate our findings with the microarray analyses, we performed quantitative real-time PCR (qPCR) analysis on these four cell lines. We chose a range of GPCRs, mostly orphan receptors (Cnr1, Cnr2, Gpr3, Gpr12, Gpr35, Gpr83, and Gpr119), as well as two phospholipases (Plcb1 and Plcb4) as candidates to measure their mRNA levels using this alternative method. We selected genes that had distinct and differential expression profiles across the four cell lines. The data are plotted in figure 7 in a manner that correlates the copy number of mRNAs measured in each cell line using qPCR with the levels of mRNA determined from our microarray experiments. The qPCR data were broadly consistent with our microarray data. We observed higher copy numbers for all genes for which we had observed statistically significant microarray expression, suggesting an overall good correlation between our microarray and qPCR data. The qPCR did detect mRNA for a few genes whose levels of expression did not reach statistical significance in the microarray analyses. These genes are Plcb4, Gpr3, and Gpr92 in AtT20 cells and Plcb1, Gpr83 and Gpr92 in N18 cells.
Figure 7. Quantitative polymerase chain reaction validation of microarray analysis. Quantitative PCR analysis of 10 genes from (A) HEK293, (B) AtT20, (C) BV2, and (D) N18 cell lines. mRNA levels determined from qPCR analysis were plotted against the mRNA levels measured in the microarray analyses in figures 1, 3 and 6. The dashed lines indicate the threshold of statistical significance for the microarray data. Points that fall between 0 and this threshold indicate genes that were detected with the microarray analysis but failed to meet statistical significance. Lower critical threshold (Ct) values indicate high mRNA copy numbers.
The ability to induce expression of a known protein in a model cellular system, such as the cell lines analyzed here, has served as a remarkable, vital tool. However, the GPCR research community that makes use of these cell lines has had only limited data on the complement of GPCRs and related signaling machinery expressed in them. When a cell line is used for heterologous expression, ignorance of the endogenous protein expression profile of a cell line may lead to false conclusions about the nature of receptor function. Indeed, the cellular milieu can have a dramatic impact on GPCR signaling (see [22]. Microarray technology is now sufficiently accessible and mature to determine the mRNA expression for cell lines from species whose genomes have been sequenced. Yet even where microarray studies have been conducted, their data remains only nominally accessible to those with sufficient means, experience and time to extract useful information. The absence of a systematic published study of mRNA expression for signaling proteins of general interest hinders research using these important cell lines. This study provides data examining the presence of several hundred different GPCRs and related signaling proteins in four phenotypically diverse cell lines frequently used in GPCR research.
HEK293 cells are perhaps the most widely used cell line, cited in over four thousand publications and initial work has identified a number of endogenous receptors (see below). We expanded upon this knowledge by demonstrating that HEK293 cells express at least 75 different GPCR mRNAs. Much of what has been reported about GPCR mRNA expression patterns in HEK293 cells was confirmed by our analysis: ADORA2B, CHRM3, F2R, F2RL1, GABABR1, GPCR5A, GPR19, LGR5, LPAR1, LPAR2, P2YR1, PTGER2, S1PR, and SSTR5 [17,26,38-46]. HEK293 cells have been reported to possess mRNA for a number of receptors that were not found to be expressed at statistically significant levels in our study: 5HT1D, 5HT6, 5HT7, ADRA2(a-c), ADRAB2, AGTR1, BDKRB2, DRD2, GPR1, GPR161, GRM4, P2YR2 and SSTR2 [17,26,46-50]. Our results also indicate that HEK293 cells express mRNA for most G protein subunit isoforms, and numerous isoforms of adenylyl cyclase, protein kinases A and C, and phospholipase C. In addition they are useful for studying regulation of G protein mediated signaling as significant levels of mRNA for beta-arrestin1 and 2, GRK3-5 and a number of RGS subtypes were seen.
Much less is known of the expression patterns of GPCRs in AtT20 cells. We confirmed the presence of Sstr1 and Sstr2 mRNA in AtT20 cells [30], but did not observe significant levels of any of the other receptors that have previously been reported such as Chrm4 [51], Vipr1a, Adcyap1r1, or Sstr5 [30,52,53]. The lack of significant levels of CRF receptor mRNA was of interest as AtT20 cells have been reported to be sensitive to CRF [54]. mRNA for Hrh3 or Hrh4 histamine receptors were not detectable, despite reports of their presence [55,56], but a low level of Hrh2 was found. Tacr1 [31] was not detected, nor were Tacr2 and Tacr3. We also did not detect the orphan Cmkor1/Cxcr7 [57]. It is worth noting that there are at least two AtT20 clones available and this may explain some of the differences we found. Generally speaking, AtT20 cells possess a much less diverse complement of GPCR-related signaling and regulatory gene products than the other cell lines tested. Of the approximately 120 GPCR signaling gene products that we studied here, AtT20 cells had 45 significantly expressed signaling related proteins compared to 72 or more in each of the 3 other cell lines. AtT20 cells were the only ones to not have significant levels of beta-arrestin1 (Arrb1) or GRK3-5. Only three RGS gene products were found at significantly high levels: Rgs14, Rgs20, and Snx13.
BV2 cells are commonly used to study microglial biology. These cells exist in a continuum between two states: a resting state and an activated state. For example, upon interferon gamma treatment (primed state), BV2 cells increase both Cnr2 and Gpr55 mRNA levels, whereas with lipopolysaccharide treatment (activated state) these levels decrease [58]. In our case, BV2 cells were cultured under conditions expected to promote a resting state. We can confirm that as reported in the literature BV2 cells express Adora3 [59], Cnr2 [33,58], Mtnr1a [60], Galr2 [61], Ccr5, Cxcr3 [62] and Rgs2, 10, 12 [27,28,63]. We also detected mRNA for receptors that have been reported to be upregulated in response to stimulation such as Ccrl2 [28,64], Ptafr, Ptigr [64] and Rgs7 [65]. Here, too, we identified a few receptors that have been reported present for which we found levels of mRNA below the levels that we defined as statistically significant: Hcrtr1 [66], Gpr55 [58] and the receptor for Cx3cr1 [67]. We did not detect Prokr1 which is upregulated with activation [27], nor for Oprm1, P2ry1 and Gpr149 which are downregulated following activation [27,28]. Several reports have identified the presence of mGluRs in BV2 and primary microglia [21,68,69]. Interestingly, Grm1 is generally thought not to be present in BV2 cells, yet it was the only one that we significantly detected. We did find low, non-significant levels of Grm3, 6, and 8. The differences may be due to differences in the activation state of the cell lines. BV2 cells appear have a diverse receptor and signaling gene product profile.
Of the cell lines tested, the least well characterized is the N18 neuroblastoma line. They are known to express Cnr1 [70], which we confirmed with our analysis. It has been reported by some that they do not express muscarinic receptors [71], but our analysis shows that they have mRNA for three different types (Chrm2, 3, and 4) consistent with other reports [72,73]. These studies also found evidence for secretin, prostacyclin, opioid and alpha2-adrenergic receptors In support of this we found significantly high levels of mRNA for Ptgir1, Ptger1, Ptger3, Ptger4, Oprd1, Oprl1 and Adra2b. There were also levels of mRNA for Sctr, Adra2a, Oprk1 and Oprm1 that did not reach statistical significance. Another report describes P2ry2 expression [74], but for this we only found low non-significant levels. Beyond these reports there seems to be little known of GPCR signaling in this cell line and this analysis substantially extends our knowledge of its complement of GPCR expression, at least at the mRNA level. Like BV2 cells, N18 cells appear to have a large repertoire of GPCRs, effectors, and regulating proteins, being consistently one of the highest expressers in each receptor class analyzed.
Interestingly, even the most prolific cell line expressed only a small portion of the full repertoire of non-chemosensory GPCRs (~360). Of these four cell types, BV2 cells expressed the highest total number of GPCRs (108) followed by N18 (105), AtT20 (79), and HEK293 cells (73). BV2 cells had the greatest total abundance of Class A receptors (88), but had equal numbers of Class A orphan GPCRs as N18 cells (figure 3). On the other hand, HEK293 cells have mRNA for the greater number of Class B and Class C orphans (figure 4). It is interesting that the BV2 and the N18 cell lines, which are more often used as models for specific cell types, express mRNA for the most diverse set of receptors. This presumably results in a greater sensitivity to a broad spectrum of ligands and the large number of signaling proteins for which we measured high mRNA levels in these two cell lines attest to this. It is also of interest that HEK293 and AtT20 cells have the lowest numbers of GPCRs of these four lines. Low expression (both of amount and type) may allow these cell lines to serve as a better-differentiated cell model, and, from an experimental perspective, may make a given cell line more attractive as a 'clean slate' into which gene products of interest can be introduced.
mRNA expression levels do not guarantee that a specific mRNA is properly translated, folded, and trafficked to produce functional protein. Discrepancies between our findings and those that have been reported using PCR-based methods may be due to differences that appear in cell lines with time, passage number and growth conditions. Discrepancies may also be attributed to the PCR-based techniques generally employed to extract and amplify mRNA: in some cases the techniques used in many of the studies cited here, some of which do not allow for relative quantification, may have detected very low levels of receptor mRNA that did not reach our threshold for statistical significance. In light of the potential discrepancies between microarray and PCR-based techniques, we employed qPCR analysis to test the validity of our microarray results (figure 7). The overall consistency between our qPCR results and microarray data lend confidence to the concept that the microarray analyses accurately reflect the presence of mRNA for these GPCRs and their signaling proteins.
In conclusion, this microarray analysis of the nearly full complement of non-chemosensory GPCRs and related signaling proteins in these four cell lines greatly expands our understanding of their potential signaling repertoire. These cell lines are used frequently as models of specific cell types, in heterologous expression, and as controls for antibody screening. The present work provides accessible profiles of mRNA expression that we hope will assist investigators of the GPCR superfamily in choosing the appropriate cell line to study a particular GPCR or related protein of interest and further to better understand potential functional interactions between GPCRs and related proteins in these lines. It is our hope that this work can eventually be extended to other commonly used cell lines such as CHO and COS7 cells when their host genomes (in this case hamster and green monkey, respectively) have been sequenced and made available for gene microarray analysis.
Cell cultures
Human Embryonic Kidney (HEK) (catalog #CRL-1573) and AtT20 (catalog #CRL-1795) cells were purchased from American Type Culture Collection (Boston, MA). BV2 microglia cells were obtained from Dr. Nephi Stella (University of Washington) [32,33]. N18 neuroblastoma cells were obtained from Dr. William Catterall (University of Washington)[75]. Dulbecco's modified Eagle's medium (DMEM), penicillin, streptomycin, and fetal bovine serum (FBS) were purchased from Gibco Life Technologies (Rockville, MD). All cell lines were grown in DMEM with 10% FBS, 100 units ml-1 penicillin, and 100 μg ml-1 streptomycin at 37°C in 5% CO2 humidified air. Importantly, BV2 cells were maintained in conditions that push BV2 cells towards a resting, non-activated state.
Cell preparation, mRNA extraction & microarray analysis
Hybridization and sample imaging/quantification was performed by Indiana University's Center for Genomics and Bioinformatics. To study mouse and human mRNA expression, we used Nimblegen 4 × 72 k arrays (NCBI MM8, and NCBI HG18, respectively; 60 mer probe lengths). These are four-plex arrays that allow for the examination of mRNA expression of ~20,000 genes from four samples. The layout provides for three probes per target, the values of which we averaged to obtain a sample value. We cultured four 10 cm plates of each cell line, performing separate extractions when the cells grew to confluence. Total RNA was extracted from cells using TRIzol reagent (Invitrogen) under RNase-free conditions, followed by chloroform treatment (100 ul/ml). After centrifugation, the aqueous phase containing total RNA is then extracted and treated with isopropanol (500 uL/mL) for 5-10 mins. After centrifugation, the RNA pellet was isolated, washed with ethanol (75%; 1 ml/1 mL of reagent solution), followed by another centrifugation and air-dried. The RNA pellet was resuspended in RNase-free water. Total RNA quantity was assessed using NanoDrop ND-1000, and the Bioanalyzer 2100 determined the 28S/18S ratio for quality assessment. To synthesize targets for hybridization, we began with 10.0 μg of total RNA and used Invitrogen's SuperScript Double-Stranded cDNA Synthesis kit using oligo (dT) primer (Promega) followed by DNA labeling using 1 O.D. CY3-labeled random nonamer primer (TriLink Biotechnologies) and 100 U Klenow fragment 3' > 5' exo-(NEB) per 1.0 μg double-stranded cDNA. Single-color hybridization, post-hybridization washing and scanning were done with NimbleGen reagents and according to the NimbleGen's User's Guide for Expression Analysis. Images were acquired using a GenePix 4200A scanner with GenePix 6.0 software. The data from these arrays were extracted using the software NimbleScan 2.4 (Roche NimbleGen) and processed into PAIR files.
We used two separate NimbleGen high-density arrays for expression analysis (design name = HG18 60 mer expr 4plex and design name = MM8 60 mer expr X4). The 4-plex arrays each consisted of 4 × 72,000 isothermal long-oligo nucleotide probes that are 60 nucleotides in length. The first was based on HG18, Build 36 version from NCBI of Homo sapiens gene catalog, which represented 24,000 protein-encoding genes with 3 probes per target and 1 replicate, and the second was MM8 version from NCBI of Mus musculus gene catalog, which represented 18,869 protein-encoding genes with 3 probes per target and 1 replicate.
Quantitative polymerase chain reaction analysis
Primers for selected GPCRs and enzymes were designed using Primer-Blast (http://www.ncbi.nlm.nih.gov/tools/primer-blast webcite). The mouse gene was used as template in the primer design, and either mouse or human genome was used to screen for non-specific targets. Suitable primers were determined in this way and were commercially produced (Integrated DNA Technologies, Coralville, Iowa). AtT20, BV-2, HEK293 and N18 cell lines were grown on 10 cm dishes until each monolayer was 50-95% confluent. Total RNA was prepared and reverse transcribed using a Retroscript Kit as per manufacturer's protocol (Cat# AM1710; Ambion Inc. Austin, Texas). Two micrograms of total RNA from each line was reverse transcribed, samples were diluted and qPCR was performed using a Stratagene Mx3000P thermocycler and Sybr Green/Low Rox polymerase mix (Cat.# 95056-100, Quanta Biosciences, Gaithersburg, MD). In the case of N18, the "no RT" control showed significant genomic DNA contamination. To compensate for this, the total RNA for this sample was treated with DNase 1 for 1 hour and again purified just prior to RT. Primers for glutaraldehyde-3-phosphate dehydrogenase (GADPH) were used to make an internal control for each cell line with the threshold cycle set at 16. Once the standard critical threshold (Ct) was set, the relative expression levels for genes within each cell line were determined.
Database information
All data is MIAME compliant and has been deposited in GEO (accession number GSE25901).
Statistical analysis
For statistical analysis of the microarray data, we first transformed the values from the microarray into log2 format for ease of comparison and data representation [76]. We then obtained values for 10-11 assorted seminal proteins that were unlikely to be expressed in these cell lines. For the human-derived HEK293 cells these were: PYY2, PSP94, SPATA3, SPATA4, SPATA5, SPATA13, SPATS1, SPESP1, SPERT, ODF1, and SPAM1. For the three murine cell lines we selected: Svs2, Svs3, Svs5, Svs6, Svs7, Sva, Svp2, Sval1, Sval2, Sval3. We averaged the expression level of each of these proteins for each of the four plates to determine the mean and standard deviation of their expression. We took these mean values to represent zero expression. To determine statistically significant expression, we added the mean plus two standard deviations of the expression levels of these seminal proteins for each plate. We then subtracted this value from the value for each receptor and protein for which we obtained a signal. The mean plus two standard deviations was considered to be the baseline for our proteins of interest as any values at this level or higher would be considered statistically significant (95% confidence that the true mean of the seminal protein expression would fall within the mean plus two standard deviations). Thus any protein remaining with a positive expression value is considered to be significantly expressed [76]. All graphs and statistical analyses were generated using GraphPad Prism 4.0 software (Hearne Scientific Software, Chicago, IL).
CRF: corticotropin releasing factor; DMEM: Dulbecco's modified Eagle's medium; FBS: fetal bovine serum; GPCR: G Protein Coupled Receptor; GRK: G protein coupled receptor kinase; HEK: Human Embryonic Kidney; mGluR: metabotropic glutamate receptor; PCR: polymerase chain reaction; RGS: Regulator of G protein signaling.
Authors' contributions
BKA carried out the drafting of the manuscript and the statistical analysis. JL performed the microarray analysis and assisted in drafting the manuscript. JWM performed the cell line preparation, mRNA extraction and qPCR experiments. KM participated in the design and coordination of the study. AS conceived of the study, participated in the design and coordination of the study, critical review of the manuscript, and performed the data extraction. All authors contributed to writing, reading, and approving the final manuscript.
This work was supported by the NIH (grants DA11322, DA21696, DA24122, NIH/NCRR RR025761), the Center for Genomics and Bioinformatics at Indiana University and the Indiana METACyt Initiative of Indiana University, through a major grant from the Lilly Endowment, Inc.
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by Cody Dumont
October 10, 2013
This report provides an executive summary of the current Mobile Device Management (MDM) status. The report was created using the new features within SecurityCenter 4.7 and the features within Nessus to collect mobile data from the MDM solution. There are three chapters with components showing a summary of mobile device types, charts displaying the current vulnerability count, and tables with user and device summaries. The currently supported MDM solutions are Apple Profile Manager, Microsoft ActiveSync, and Good for Enterprise.
The report is available in the SecurityCenter 4.7 app feed, an app store of dashboards, reports and assets. The report requirements are:
- SecurityCenter 4.7
- Nessus 5.2.1
The first chapter has two sections, one with pie chart data and the other with bar chart data.
- The pie chart provides a model summary of the managed devices with the MDM solution. Using the "Model Summary" tool and sorting devices based on the Model column, the device count is used to create a pie chart that is easy to read and understand. From a quick glance, the user can understand the number of managed mobile devices.
- The bar chart displays device count, critical severity, and high severity. Using the device model as the sort column with a descending sort direction, the component provides an easy to view status of all managed device models, with a bar representing the count of device with critical and high severities.
The second chapter contains a table listing the users with the most mobile devices registered to MDM. The table is based on the "User Summary" tool, and displays all users based on the total number of mobile devices. The sort column is based on the device total count and is sorted in descending order. The user, low, medium, high, critical, and total columns are displayed.
The third and final chapter provides a table of mobile devices discovered within each calendar year from 2011 – 2014.