You have a multitude of decisions to make in your life. But now you are facing a particularly important decision, and you don’t know what to do. You keep mulling through the choices, scared to make a mistake and fixed on the worst thing that could happen.

You feel stuck, frustrated and drained of energy. You’d rather make the decision, yet you still can’t decide…

Why can’t you decide?

Then why is it so difficult to make a decision sometimes? Common reasons are that…

• You think that what you decide is going to be permanent
• You are obsessing on making the “best” decision (which incidentally would entail you predicting the future)
• You don’t want to make a mistake
• You feel pressurized by what other people think and expect of you.

Wow! Did you just read all that? No wonder you are struggling… too much pressure, too many expectations and you even have to foresee the future!

Here is some simple advice about making decisions

• You already know what to do. Yes, you do. Either you want it or you don´t. Be honest with yourself.
• The number of reasons you have for doing something is inversely proportional to how much you want to do it. Think of any time you really wanted something. Did you need any reasons for that? Nope. When you really want to do something you don´t need reasons. If you are giving yourself a list of reasons you are probably trying to justify an irrational decision or action.
• You can almost always change your mind. We usually think that our decisions are irrevocable, and of course that causes anxiety and struggling. But most of them are not, and it’s fine if you change your mind later.
• What you decide will never have as much significance in your life as how you handle the consequences of that decision. That means almost all your decisions can turn out well if you know how to deal with the result. Did you make a mistake? That’s not a bad decision, a bad decision would be to hold on to your mistake and do nothing about it.
• Shift your mindset. Stop focusing on making the best choice, focus instead on the choice that involves the most growth. And if after a while you are not happy anymore, you didn’t make a mistake, you just stop growing.

So what is the simplest way to make a decision?

Easy – just ask yourself these two questions ‘Do I want to?’ and ‘Will it make me grow?’

And what if the options you are pondering are equally compelling? Listen to your inner voice (actually always do that). Try this, a method I frequently use when I’m stuck with two similar options: grab a coin (I’m not joking, keep reading), promise yourself you’re going to actually do what the coin says. Flip the coin. See the result.

How did you feel while the coin was in the air? What result where you expecting? And after it landed? Relieved, disappointed, excited? That will tell you what you want to know.

Will these always lead to making the best possible decisions? No. Nor does it have to be. Remember it´s OK to make mistakes. You learn from mistakes, you grow, you’ll do better next time. How many scientific discoveries came from a mistake…

1. Tailor your resume to the position for which you are applying – include specific elements of the job description in your resume (make it easy for them to see that you are a good fit).
2. Do not rely on a cover letter to explain why you are a fit. You may want to use it to explain reasons for relocation, but your skills and experience need to be evident within your customized resume. If anything, the cover letter may be used to weed you out.
3. Do not apply for more than one position within one company. It creates the perception that you are not sure which position is best for you. We recommend applying to one but including a variety of skill sets on your resume so that you indicate you are qualified for more than one position.
4. Keep everything positive – in your resume and in your communication with the company. Don’t dwell on bad experiences, frustrations, or ineffective bosses. Talk about what you learned, why you are better for it and how you will leverage those experiences to make your new company successful.
5. Honesty rules – the biotech industry tends to be a tight-knit community. Hiring managers and HR professionals will do informal reference checks with people they know at other firms and you do not want them to be surprised.
6. Answer salary questions definitively and transparently. Do not try to circumvent these questions. Tell them specifically what you were making and what you are looking to make.
7. Don’t be shy – let your personality come through in your answers. During an interview, you might be thrown some questions that are asked to assess how your brain works or to find out more about your personality.
8. When accepting an offer, be enthusiastic. They want to hear the smile and excitement in your voice. This will lay the foundation of a very positive transition into your new company.
9. Don’t engage in a counteroffer negotiations – you risk alienating yourself from the new hiring manager and your old company. Consider the offer and decide.
10. Being overqualified is a serious concern for companies, but the solution is not to remove things from your resume as it may create the perception of dishonesty.
11. End interviews with assertiveness and proactivity. It is very appropriate to end interviews by asking “When would it be appropriate for me to follow-up?”.
12. Be prepared for behavioral interview questions. Come to the interview prepared with several anecdotes about challenges you have faced before and how you dealt with them. Demonstrate a positive and measurable result whenever possible.
13. Do your best to incorporate the firm’s core values into your interview responses.
14. Keep up your knowledge. Companies understand that people may have been out of work for extended periods of time in this economy. However, you must demonstrate your ability to stay current (seminars, certifications, etc.) and to get up to speed quickly.
15. LinkedIn is a recognized tool, but they disregard most of what they see, including recommendations. Be prepared to provide a supplemental reference sheet during interviews.
16. Identify and ease their pain. Ask hiring managers about “gaps in their department” to find out where their pain is – and suggest how you can help ease that pain. They need to be sure they are hiring someone who can help with their issues.
17. Ask good questions. Like, “What does success look like 6 months into this position?” and “What obstacles might I run into?”
18. Be careful with Facebook – they review these pages and screen people out as a result!

This event covered a multitude of topics; but it’s great insight to see how HR and hiring managers are thinking in the current environment.

What a great idea I thought. A cheap, quick-to-build plate centrifuge that also worked pretty well for a quick spin just before PCR. So, we tried to built one in my lab and we loved it so much that we now have one sitting near almost EVERY PCR plate instrument, and have even gifted a couple to others!

Building one for your lab is simple, here is how…

You will need

1. A salad spinner – We use the Zyliss brand pull-cord salad spinner.
2. Multi-purpose cable ties found at any hardware store.
3. 96-well plate inserts – We use the ones from ABI

Gathering the components is as complicated as it gets! All you need to do now is use those cable ties to secure the 96-well plate inserts to the inner bowl of the spinner as shown below. Then start using the new mini-plate-fuge!

Question:

I would like your help to assign copy numbers to plasmid standard dilutions. I cloned a portion of the mitochondrial D-loop gene and after plasmid prep of a single clone made serial dilutions (1:10). In my lab previously they would do a lightcycler run on those serial dilutions using SYBR Green and then assign copy numbers based on the crossing points. The theory used was that a crossing point (CP) of 32.7 would be equal to 10 copies. So the dilution closest to CP of 32.7 would be 10 copies with increasing 10 fold copies for the earlier dilutions (because I had made 1:10 serial dilutions: 1:10, 1:100, 1:1000, etc.

Then I learned from a co-worker that it is better to use the following website:
http://www.uri.edu/research/gsc/resources/cndna.html

So I entered the nanodrop reading of the undiluted plasmid standard and the length of template (TOPO vector and length of my insert) and got the copy number.

The problem is that there is a 10 fold difference between these two methods. 1:1000 dilution of the plasmid standard gives me 8.44E7 copies using the website and 9.99E6 using lightcycler CP.

******

Thanks for your question!

There are a couple things to keep in mind here and I think you’ll be able to solve this problem.

1- The standard curve results and crossing point or Cq numbers are not going to be identical every time. You didn’t mention whether the original standard curve data was performed with the cloned gene or with gDNA or with the PCR product for the gene itself.  If the original standard curves were determined with one type of template and now you have a plasmid template, there will be a difference. Even a change of 1 cycle can have a big effect in absolute quantification.

2- Have you checked the efficiency of the plasmid template? How does it compare to the efficiency of the template used to generate the previous standard curve? If they are different, the quantification will be different.  Ideally you want the efficiency to be above 90%. If the efficiency is below 80%, you won’t want to use this data and you may need to redesign the primers or optimize the chemistry or running times.

2- Every time you order new primers or a new enzyme kit (of a different lot#), you will want to repeat the standard curve results because the numbers can shift. As long as PCR efficiency is high, the data will be accurate, but the Cq may very well be different with new reagents.

3- If you used a plasmid for a standard curve, did you linearize it for qPCR? Many people report that using supercoiled plasmid for standards can cause some variance in results. Try linearizing it first. Here is a recent publication on the subject.

4- When calculating the copy numbers, you may use the length of the PCR amplicon or the entire plasmid. When using the website above, if you use the size of just the amplicon as your input, make sure to adjust the amount of DNA going in to reflect the proportion of the plasmid (see the example in the comments).  If you do not, your reading will be 10 fold off.

5- Make sure your negative controls are negative. Working with plasmids can be tricky because they can easily contaminate solutions. Make sure you have negative controls that are not amplifying because this will boost the real samples and result in inaccurate quantification.

6- Always do the melt curve analysis when using SYBR green and make sure you amplified a single product. Amplification from dimers will add fluorescence and result in an artificially low Cq. You can remedy this by performing an extra data acquisition step at a temperature above where the dimers melt and below where the real product melts. Alternatively, you may want to redesign the primers if dimer formation occurs even in samples with the highest amount of plasmid.

7- With plasmids, it is easy to overload the reaction and have Cq values so early that the detection won’t be accurate. Some instruments have a pre-set baseline setting where they subtract any fluorescent signals generated too early, assuming it is background noise. If you have too much signal in cycles 1-10, this can happen. You don’t want to have samples coming up early so dilute until the first sample has a Cq of 15-18. The subtraction of strong fluorescence in the early cycles will cause all of the data from the more dilute samples to shift right, causing later Cq values than what they are.

Summary:

When using a new plasmid as a standard in qPCR, do an efficiency check  first and compare to the efficiency of the previous assay. For best results, an assay needs to have >90% efficiency, although there are formulas you can use that normalize for differences in efficiency. It is not uncommon that the Ct values are not exactly the same from user to user and from assay to assay for the same gene but with different primers. Just make sure that when calculating copy numbers, you are using the length of the template being amplified and not the entire plasmid which is probably 30 fold bigger than the template and could be the cause of the 10 fold difference in copy number results between the two methods you are comparing. Finally, it’s always good to re-check your standard curve with each new purchase of reagents to make sure no new variables are introduced that could throw off the quantification and make months of work unusable.

A Butane Torch
If your OCD is as bad as mine, then watching a bubble flow out of the flask onto the Petri plate you’re pouring bothers you… a lot. A short (~6 inch) butane torch comes in quite handy for flaming bubbles off the top of freshly poured plates. I also use this to pop bubbles that form while pouring agarose gels, but you have to be particularly careful while doing this not to damage the casting tray or any other part of the gel rig. In addition, these guys come in real handy as a portable Bunsen burner when you need to work away from a gas outlet.

What to look for: Almost all of them can be refilled with the generic cans of butane, but double-check to be sure the one your looking at doesn’t require some proprietary refill system, which will almost certainly be more expensive. In addition, make sure that it has an auto-start feature. If you think you might use it as a Bunsen burner, make sure that it has a large, stable base and a button to lock the trigger ‘on’.

What I use: Ronson Tech Torch

An Infrared Thermometer
Ideally, you would cool a flask of autoclaved agar in a waterbath, but that isn’t always possible. And once you leave it cooling on the counter, the gamble begins. Pull it too early, and you risk inactivating your antibiotic. Pull it too late, and you’ll end up with lumpy plates. (Did I mention my OCD?) One solution to use an infrared thermometer to monitor the flask.

After acquiring mine, I set up a test where I outfitted a flask of boiling water with a stir bar and a traditional thermometer, and compared the readings of the IR thermometer (aimed at the outside of the flask, below the fluid level) and traditional thermometer (in the fluid) as the water cooled on a stirplate. The two readings didn’t differ by more than a degree or so the entire time the flask cooled. This is particularly valuable if you have inexperienced people (ie – undergrads) making the plates in your lab. In addition, these things are great for getting an immediate temperature on anything without having to wait for a traditional thermometer to equilibrate. Once you have one of these, you will use it more than you think.

What to look for: Make sure that the thermometer you’re looking at can be switched to output Celsius (if you’re in the US or Canada). Also, you might want to get one that has “adjustable emissivity”. Emissivity is the ability of a material to radiate energy, and in practical term this means that glass at a particular temperature will emit a different amount of infrared radiation than aluminum at that same temperature. If you find that you want high sensitivity for one particular application, then you can adjust this parameter to fine tune the thermometer. (A quick Google search for “emissivity coefficient” will turn up tables of emissivity settings for common materials.)

What I use: Advanced Tool Design Deluxe Infrared Thermometer

Strap Wrenches
As a group, we scientists aren’t known for our intimidating physiques, and this is usually revealed in the lab when the liquid nitrogen knob, or the top of a centrifuge canister or bottle gets stuck. You then have to go find the largest scientist you can think of to help you out of the jam, which for guys is “The Walk of Shame”. Strap wrenches will save your pride or even save your experiment if nobody is around to help. These tools consist of a flexible strap that wraps around and grips the object, with a straight handle that allows you to get some leverage on the beast. (If you’ve ever watched a mechanic change your oil, he likely used a specialized version of this tool to remove your oil filter.)

What to look for: Choose ones that have a urethane coated nylon strap to make sure that it doesn’t damage anything you might use it on. They are adjustable, so choose ones with a large capacity (~5 inch diameter), as they will also likely adjust down to less than 2 inches for smaller tops. You will want two, since you may have to wrap one around the bottle and a second (in the opposite direction) around the lid. Of course, be careful if you are removing the stuck top off a glass bottle.

What I use: Klein 12-Inch Strap Wrench

Are there any tools that I missed?

The key to delivering a strong talk is designing a well-crafted PowerPoint presentation to serve as your framework. Here are my thoughts on how to create a PowerPoint presentation that will enable you to effectively communicate your results, benefit from your colleagues’ invaluable input and maybe even show off a little!

The title slide
This is the easy part. The title of your talk is a phrase describing the topic of your presentation. Make it large, simple, and readable. Your title slide should also have your name, your lab and school affiliations, and the date. If you have a really nice image from your work (for example, a microscopy picture), you can include it as the background of the title slide, as long as it doesn’t interfere with the readability of the title. Some schools require that the school crest or symbol is also included on the title slide. Check this with your institution.

Background
The background section of your talk is where you set your audience up to be able to understand your experiments and the significance of your results. The background information you present should be tightly focused: provide just enough information to understand your talk, and nothing more.

You generally want to stick to two to three slides of background, depending on the length of your talk. Use bullet points, and try to avoid slides that are all text. Using images from preliminary data or small model figures is a good way to break up the text in this portion of the presentation. If you use figures from someone else’s work, cite them in the lower right hand corner of the slide. A simple format such as “Smith et al., PNAS 2006” is appropriate. Unpublished preliminary data should be cited as “Jones, unpublished”. It’s up to you whether you cite your own unpublished data, but you must cite all data that you did not generate.

The most important thing to do before you get into your results is to state the main question that your research is addressing, and put it in context. Don’t leave the audience wondering why you’re doing what you’re doing. It is your job to convince them that this is an important question that you are addressing in a thoughtful manner.

Results
The results section is the meat of the presentation, when you get to talk about all the exciting work you’re doing. Keep in mind that while you have been thinking about these experiments day in and day out, it will all be new to the majority of your audience, so keep things as simple and clear as possible.

Each slide should contain one figure only, whether it is a graph, a set of microscopy images, or a blot. The title of the slide should state the conclusion drawn from the data shown on the slide, as a sort of shorthand for people who may have zoned out during your explanation of the experiment, and need to catch up quickly. If you used any unusual techniques, be sure to explain them before presenting data from the relevant experiments.

Use a consistent color scheme throughout the presentation. Black and white is always a good choice for the text and background color, respectively. Stick to two to three “contrast colors” within one presentation, and keep it constant. For example, if sample “A” shows up as a blue bar in a graph on slide two, then it should be a blue line in the graph on slide three. Use animation in moderation, and only if it helps clarify your point.

Conclusions
When you’ve finished presenting the data, you need to sum it all up to show that your work forms a cohesive whole and tells a compelling story. In most cases, your conclusions should be limited to a single slide. Use bullet points to list the main conclusions, without going into experimental detail; this is the time to show what you learned, not how you did it. Conclude by referring back to your main question: did you answer it? Are you on your way to answering it? Did you encounter anything unexpected? Depending on the forum in which you are presenting, you may want to include a slide of future directions after your summary slide. This is especially appropriate for graduate students, and is always important for lab meetings.

Acknowledgments
The final slide of your presentation is the acknowledgments slide. You must cite every person and every funding source that was involved in your research. Most people list all the members of their lab; you can choose to mention only those individuals who actually contributed when you give the presentation. Graduate students should be sure to thank the members of their thesis committee. If you borrowed materials from another lab, remember to thank the PI as well as the individual that gave them to you.

General tips

• You can usually count on an average of one minute per slide, excluding the title and acknowledgments. So, if you are giving a 45 minute talk, shoot for around 45 slides.
• Keep in mind that there may be color-blind scientists in your audience: avoid using close shades of color on a single slide, and specifically avoid using red and green to distinguish between two items.
• Upload your presentation ahead of time, so you can deal with Mac/PC conversion issues or compatibility problems caused by different versions of Windows or Microsoft Office.

Good luck with your presentations! Let us know in the comments what your favorite presentation tips are…

To paraphrase one of my favorite books (So What Are You Going to Do With That?: A Guide for M.A.’s and Ph.D’s Seeking Careers Outside the Academy by Susan Basalla and Maggie Debelius), what will you have to show for yourself besides teaching and research at the end of it all? For most people, the answer is “probably not much”. But what Basalla, Debelius and I suggest is that it would be very beneficial for you to actively pursue other interests or hobbies while in grad school or doing a post doc.

Why you should make time for your interests and hobbies

Teaching and research involve a variety skills, including project management, organization, complex problem-solving, and analytical skills, to name just a few. But expanding your skillset by pursuing other interests or hobbies is well worth your time. Not only will it make you a more interesting person, it will also make you more marketable to both academic and non-academic employers. But the most important reason of all is that it will make you feel alive, and maintain your sanity. Science is exciting  and it’s your passion (or is it?), but it’s also demanding so having other passions can help you keep your life balanced.

Consider new options

It’s always a good thing to be open to new possibilities and options that you might never have considered before. My hobby is learning, and consequently, I am a raving fan of courses. In doing one of these courses I discovered that I love translating, and that I’m good at it (so my alternative career could be in translating scientific texts, I’d love that), and it was also through a course that I discovered my affinity for life coaching. Both of these courses began as hobbies, just for fun, and developed into something more.  Just pick something that interests you and go for it — you’ll have lots of fun and recharge your batteries at the same time.

The career benefits

Apart from personal satisfaction, having a hobby has added benefits to your career. New activities will broad your experience, add important skills (for example group activities will show your ability to work as a part of a team), strengthen your network and expand you options. You can also get recommendations, and it’s an ideal way to learn about a new field and experience first hand if you’d enjoy or not doing something similar professionally.

This is especially important if you are considering a career outside academia as you can show potential employers that you have other interests and abilities beyond the lab. But even if you’re happy inside academia, it will serve you well too.

Fitting it all in

I know you’re busy and don’t have much time. Or that’s what you tell yourself. But how much time do you spend actually working? And how much time do you spend pretending to be working, feeling guilty because you should be working or avoiding getting to work? If you track down how you use your time (and how you waste your time) you can be more efficient and find time for other things. Check out this article on measuring your fudge factor to get some ideas on how to do this.

So what are you waiting for? Make the most out of you grad school and postdoc years. There are lots of different things you can do, from learning a new language, to developing skills like leadership or communication, or volunteering your time, taking a part time job, writing for a university publication or writing a blog…. Take advantage of your University or department programs.

And if you don’t know what to do, drop me a comment, I’d love to help you find out.

But there is another receptor, called CB2, that can bind THC and other natural ligands for the cannabinoid receptor. The CB2 receptor is found on cells comprising the immune system and have a multitude of anti-inflammatory and immunosuppressive effects upon activation. In most cases, immunosuppressive effects are undesirable, but sometimes that can be beneficial. Today’s article is an example.

New research from the lab of Dr. Guy Cabral at Virginia Commonwealth University shows that stimulation of the CB2 receptor on macrophages inhibits migration of healthy immune cells towards the HIV Tat protein.  Tat is an essential viral regulatory protein used by HIV to stimulate inflammatory responses and wreak havoc in the body. Tat protein looks suspiciously like some of our own chemokine proteins and can bind to a variety of receptors on immune cells causing activation of cascades that lead to migration of uninfected macrophages towards the HIV infected cells.

The paper by Erinn S. Raborn and Guy A. Cabral, published in the January 2010 issue of the Journal of Pharmacology and Experimental Therapeutics is titled: Cannabinoid Inhibition of Macrophage Migration to the Tat Protein of HIV-1 is Linked to the CB2 Cannabinoid Receptor.  The authors used a macrophage cell line in a migration model system to demonstrate very specifically that when the CB2 receptor is stimulated, macrophages no longer respond to the Tat protein.  The chemoattractant effects are abolished.

Here is an summary of their work.

Introduction:

Macrophages are the primary target for HIV infection and once infected, cells begin producing viral Tat (trans activating factor) protein and GP120 protein in addition to stimulating the production of cellular cytokines and chemokines that induce changes in the immunoregulation of the host. The HIV Tat protein has an additional role of acting as a potent chemoattractant for monocytes, thus contributing to the spread of infected cells.

Most drugs of abuse (opiates, cocaine, amphetamines and cannabinoids) have an adverse effect on immunity, increasing susceptibility to infection. The cannabinoids in particular have been shown to have anti-inflammatory properties, downregulating some of the chemokines and cytokines involved in stimulating macrophage to migrate to infections and inhibiting macrophage function.  Cannabinoids have also been shown to down-regulate the expression of chemokine receptors, notably CCR5, one of the co-receptors used for HIV entry into cells. Thus, a link between the potential anti-HIV effects of the CB2 cannabinoid receptor has been established.

The purpose of this study was to determine whether cannabinoids exert any effect on the chemoattractant properties of Tat in macrophages. In the presence of cannabinoid agonists delta-9- tetrahydrocannabinol and CP55940, human macrophage-like cells (U937 cells) were inhibited from migrating towards Tat protein and this effect was due specifically to CB2. The results show a clear link between CB2 and the ability of macrophages to respond to the HIV protein in a cell culture system.  This work provides the basis for a novel therapeutic target for preventing or reducing HIV associated immunopathology and dissemination in vivo.

Materials and methods:

Cells: The human leukemic monocyte cell line U-937 was used.

Drugs: CB1 and CB2 receptor agonists used were: THC and CP55940. The CB2 specific agonist was O-2137-2 and the CB1 specific agonist was ACEA. The CB1 and CB2 receptor antagonists were SR141716 (SR1) and SR144528 (SR2), respectively. The full names of the drugs and the Ki information is described in the paper.

Tat: Recombinant human HIV Tat protein was obtained from Immunodiagnostics, Inc.

Cell Migration Assay: 35 mm tissue culture plates with upper and lower compartments separated by a polycarbonate 8 micron pore membrane were used. Drug treated  or control treated U937 cells were incubated on the top chamber and Tat protein or serum-free media plus vehicle was in the bottom chamber. Migration of cells to the bottom chamber was visualized with an Olympus CK2 inverted microscope connected to a digital video camera. The number of cells were manually enumerated. A greater than 2-fold increase in the number of cells in the presence of chemoattractant compared to no Tat was a positive response. The EC 50 or inhibitory concentration was the concentration of cannabinoid that results in a 50% reduction in macrophage migration.

Knockdown of CB2 expression using siRNA and RT-qPCR:   siRNA for the CB2 receptor was used for transient transfection of cells and knock-down shown using Western blot analysis.  SYBR Green was used for qPCR analysis after reverse transcription of RNA, qPCR was performed using the SmartCycler. Full details of the experimental design for qPCR and transfection are provided in the paper.

Results:

To begin, the authors first confirmed the expression of the CB2 receptor in U937 cells, both on the RNA and protein level. The CB1 receptor, typically expressed in cells of the brain, was not found in U937 cells using RT-qPCR. Their second set of confirmatory experiments proved that the U937 cells would migrate in response to Tat protein as has been previously described for human monocytes in blood.  The migratory response was maximum at 50 nM Tat and so the authors used this concentration for their studies.

The next experiments looked at the  migration of macrophages in the presence of the different drugs. All results were compared to vehicle controls (ethanol was used to dilute the drugs). Using vehicle alone with Tat protein in the bottom compartment, migration was the same as with no vehicle. When cells were treated with THC, however, migration of macrophage was inhibited by 50%. And using the agonist CP55940, migration was inhibited by 58%. Using the CB2 receptor specific agonist, the same effect of >50% inhibition was observed, however, but not suprisingly, using a CB1 receptor agonist, ACEA, had no effect on migration.

These results clearly indicate that the CB2 receptor on the human macrophage-like U937 cells plays a role in migration in the presence of the HIV Tat protein and this effect can be blocked when the receptor is activated.

To confirm the effect of migration was due to the CB2 receptor, the receptor antagonists were used to demonstrate that when signalling through the receptor is blocked, the effect is reversed.  The antagonist will bind the receptor but not activate the signalling cascade in the cell, thus blocking it from being activated by the ligand CP55940. Using the CB2 specific antagonist SR2 alone, migration in the presence of Tat is the same as controls- it is not inhibited. When CP55940 is combined with the SR2 compound, inhibition of migration is reversed.  SR2 prevents the protective anti-migration effect of CP55940.

To further prove the role of CB2 in this effect, siRNA mediated CB2 knockout cells were employed in the cell migration assay. The authors confirmed that neither the transfection reagent nor the siRNA itself had any effect on cell migration. Using the CB2 knockout cells in the presence of THC, migration was observed similarly to untreated cells. This is consistent with the results of blocking the CB2 receptor with antagonist. The CB2 receptor was not available for activation by the THC and thus no protective anti-migration effect was observed.

Discussion:

Chemokines are cytokines that function by directing the flow of inflammatory cells to sites of injury or infection in the body.  HIV uses our immune system cascade meant to protect us for its own benefit, by producing the viral Tat protein to bind the receptors meant for chemokines and stimulate the migration of more healthy macrophages to the HIV infected cells, increasing their opportunity to spread. The stimulation of chemokines also increases the number of receptors on the surface, making it easier for HIV to infect new cells.

The ability to slow down the migration of healthy cells towards HIV infected cells and to down regulate the expression of chemokine receptors would slow the progression of HIV associated disease. In this paper, the authors demonstrate a connection between the cannabinoid receptor on immune cells, CB2, and the migration of macrophages towards Hiv Tat protein. When the CB2 receptor is stimulated with an agonist, migration is inhibited. Whether this is due to down regulation of the chemokine receptors used for binding or due to down regulation of chemokines from CB2 activated cells has yet to be determined.

But the fact remains that the cannabinoid receptor CB2 may be a therapeutic target for preventing hyperactivation of the immune system by HIV and potentially, in the future, to help stop widespread infection.

Final note:

I found this paper to be an exciting advance in the fields of HIV and drugs of abuse. A therapy involving cannabinoids would be far less toxic than current drugs used to stop the progression of HIV. With all the ways HIV has found to use our own immune system against us to survive, an approach that counteracts HIV by taking back control of the immune system could be far more effective than developing toxic drugs that target HIV directly or using cytokines that further activate a tired immune system.

Be careful about what you Tweet!
Pictures and statements of wild parties, drinking or just a friends’ night out on the town may seem fun and innocuous, but they may cost you your next job. More and more articles are appearing citing examples of people whose social networking profiles (i.e. Twitter, Facebook, etc) are causing them to be passed over for job opportunities. A recent study in Time Magazine cited that 70% of HR professionals claim they have passed over a job candidate because of their internet profile. These sites are checked by a growing number of firms and you must be mindful of your public image. None of these are truly private. Most of us have found friends or colleagues’ profiles who were supposed to be “private”. Be mindful of how you present yourself.

Would you “friend” your boss on Facebook?
It’s worth noting that this is not limited to job seekers. Many of us have had a co-worker or boss ask to “friend” us on Facebook. This is a potential minefield. What are your options? Tell them “no” and risk causing an issue? Tell them yes and insist all of your friends keep comments “professional”? (I don’t know about you, but I would worry about what my friends would post if I suggested this!) You could ignore the request..until they ask you about it face-to-face at work

So what’s the solution?
These are the image struggles of the 21st century and they are very real to each of us. The easiest solutions are to stay off of social networking sites or keep them “professional” in content or appearance. But seeing how this is not a realistic option for many, I would suggest that at the very least, you “clean up” your site, remove comments you have made that could reflect poorly, and change out the pictures on your site to make them a bit more conservative until you have started your new job.

I would strongly encourage you to objectively review any of your social networking sites (I am confident your professional networking sites like LinkedIn are already “professional”). If there is anything you would not want your employer, prospective employer, co-workers or your grandmother to see, remove it. If you can’t/won’t/don’t want to do this, you should ensure your accounts are set to the most private settings possible; this will help prevent unwanted visitors to your profile.

The 21st century is full of electronic marvels; just don’t let them interfere with your 21st century career.

This is due to some recent experiences I’ve had with papers published in both the larger highly reputable journals and smaller niche journals that has left me wondering.  I review papers for Current Issues in Molecular Biology and I have run the peer review process for them so I understand what is expected as an editor or a reviewer. The journal is counting on me to ensure that a high quality paper is approved and nothing less. As an editor running the peer review process and selecting reviewers of the paper, it is my responsibility to make sure I choose people who will be fair, unbiased, and have the time to actually read the paper.

I am incredibly busy, but this is a responsibility I take seriously because not only does a poorly written paper reflect badly on the journal and on the authors, it reflects on the editor.

How did this get published?

Recently I came across a paper that was published in a popular journal for microbiologists despite the fact that it had no control experiments, the conclusions didn’t match the data (see the previous article on the importance of reading a paper thoroughly), and the entire study missed the opportunity to make any scientific contribution to the field by focusing on the wrong points.  How did this make it through peer-review, I asked myself?

Letters can be written to the authors and the editor, however, it doesn’t correct the problem. How does a scientific study gone awry get published anyway? How does every reviewer miss such obvious flaws in a paper?

More examples…

Recently I read a paper from a smaller niche journal for microbiologists that a scientist/friend asked me to comment on. We both came to the same conclusions: the paper was garbage. The authors used the incorrect name for their organism, making one up that doesn’t exist and mislabeled a figure so that the results section did not match the figure legend, making interpretation confusing. Furthermore, they left a key piece of information out of their methods (how much bacteria they used to inoculate the soil), so the data obtained was uninterpretable, and to cap it all they misinterpreted their very own data in the conclusions.

How does this get published? Was it reviewed at all? A paper of this low quality brings down the journal and its editors, and affects the whole field.

It’s not just microbiology journals!

The popular science and general methods type journals are not immune to this problem. Several months ago I read an article in a very popular magazine that used qPCR for their study and attempted to use the MIQE guidelines to validate their work. It was great to see people attempting to use the guidelines.

However, upon opening the attached spreadsheet in the Supplemental Data, I was shocked to see that most of it was empty. The authors actually wrote “NA” in almost every field of the MIQE checklist and didn’t provide any information on yields, purities, etc.  How many people do you think took the time to go to the Supplemental Data and actually see the checklist? I’ll hazard a guess that it is very few since no one else noticed the alarming lack of information contained in their “supplemental data”.

I know we are all busy and I know that we want to help our colleagues to get published, but there needs to be more measures in place that ensure that the standards are high. 

Here’s what I suggest

My suggestion is that if the journal allows the authors to choose reviewers for the paper, the editor running the peer-review process should use only one name from their list and the others are not. Chances are that the reviewers suggested by the authors are going to be very lenient (after all, they are going to ask for the return favor when they publish their next paper) and the one with nothing to gain by approving the paper will give a more accurate assessment.

And editors need to stay objective to the body of work regardless if the authors are friends or collaborators.  It is just like referring someone for a job- it reflects on us as editors if we recommend a piece of work that really is not up to par. No journal wants to publish papers that need erratum published later, or worse, no one takes the time to let the journal or authors know that an article needs erratum and instead the community decides that that the journal is too low tier to even publish there or that the people who publish there are those who get rejected everywhere else.  And of course, no one wants to cite a paper with obvious flaws so the citation index continues to go down.

Ok, so maybe it’s not ALL broken…

I know that the peer-review process does work successfully and that there are many journals making sure that their review process is stringent. It’s probably no coincidence that these journals usually have the highest citation indexes as well.

My advice to all the readers out there preparing papers for submission to journals is to step back and look at your data as objectively as you can. I know you have a theory or model you are trying to prove and want the data to support you. So knowing that, step back and read it again from an outside point of view. What other interpretations could there be? What else could be going on? Let the data tell you what is going on.  Be open to other interpretations of the data and write it up objectively.

Not only will you have a stronger paper that more people will cite, but, it will mean that you were the first to think of it and when other people follow your lead and build on your work, they will have to say you suggested it first. 

And don’t be disappointed if you need to make revisions to the paper when it comes back for review. Thank the reviewers for taking the time to read your work carefully and know that you will be able to re-submit a much stronger and more citable paper in the next round.