Planning vs doing

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Success in a cycling event is much more likely if you’ve previously ridden a bike. Image: jjd.fitness

Lab work always benefits from planning. A good experimental design drawn from a solid hypothesis based on current literature is essential for good science. And yet all the planning in the world can’t prepare you for the reality of what will happen in the lab. Kind of like a triathlon.

My entire triathlon career consists only of two such events. Ok, mini events. Training for the first triathlon encompassed the two weeks between the actual event and me first hearing about it. Sure, I could have waited a year and actually put in some proper training. Or I could just wing it this time and learn for next time.

Due to several errors in judgement, I opted for the latter. The swim leg turned out to be less to do with swimming as attempting to breath in the seething, churning mass of bodies. The ride leg also wasn’t the best leg, with that event being my first time on a bike in over a decade. The part I most excelled at was the change-over. All my training efforts had gone into putting on my shoes quickly and that’s where I gained most ground. Probably not the best training strategy but at the time it was certainly the most feasible.

Ok, so I probably came about dead last in that event. But at least the practice had taught me a great deal about mini triathlons and about training properly for them. The following year, I was prepared, knew what to expect and finished in a respectable time.

Lab work is much the same in many ways.

No matter how detailed and thorough the planning, there is always something extra to consider. Usually it’s something that no one would ever think of and it won’t be obvious until you get in the lab and try it for the first time.

In theory, the proposed method should work. In reality it might not and this might be due to something as ridiculous as the lack of available glassware. Or that the piece of equipment required for one critical step happens to be in use for the next month.

Little things that can’t be imagined on paper can have a huge impact on experiments.

Proper experiment planning is essential. But before launching into the full experiment, just getting into the lab and trying out some new ideas can be enormously beneficial and time-saving in the long run.

Like actually riding a bike before a cycling event.

 

Embracing the permanence of change

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Managing change can be the mental equivalent of a Cirque du Soleil performance. Image: cleveland.com

The truest of truisms is that everything changes and nothing is certain. Except, of course, for death, taxes and the alignment of grant application deadlines with the busiest times of year.

Change is a permanent state of being in research, where topics can switch direction on the whim of a funding body embracing a new buzzword, and everything that you’ve been working towards for months or years becomes suddenly irrelevant. It’s enough to drive anyone under their lab bench in a foetal position.

Change-management needs to be considered an essential ability of researchers and yet this is one skill that’s not usually part of PhD training. During a PhD, there is one project that continues until completion, regardless of any shifts in research interests. Even when the entire topic disappears, like when a government stopped global warming, the PhDs continued.

And as tough as PhD research is and as many problems that crop during this research, it is nowhere near as psychologically traumatising as shelving all your research just before the project bears fruit.

Shifting project directions on a proverbial pin-head takes a kind of mental dexterity that would make any Cirque-de-Soleil performer jealous. Developing these abilities should be encouraged more during PhDs but probably not to the extent of forcing major change onto students.

With experience and practice in research skills, suddenly changing topics is not only possible but also potentially exciting. But only after the researcher has been coaxed from under their bench. There must be an adjustment phase. Usually involving both chocolate and wine.

Shelved research doesn’t have to die and so there’s no need for an extended period of mourning. With proper labels* and document management, such research can be put into temporary stasis from which it can be reborn. Probably in a new and improved format with a funky new buzzword in the title.

In the meantime, there is opportunity to take on another challenge and a new topic full of exciting problems to tackle. The new collaborations formed and approaches developed may even assist in solving past research problems.

With change comes opportunity and with the right skills and sufficient supplies of chocolate, it can be embraced.

*A hard lesson well learnt!

Fun times, lab style

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Almost as hilarious as putting biohazard tape on your lunchbox

Working in the lab could be repetitive if not for the collective efforts of fellow researchers. Every week someone in the lab makes the effort to do something frivolous, purely for entertainment.tumblr_n04zgvjn8m1rqudgzo1_1280

Printout appears on noticeboards reminding giving helpful advice for researchers and lab visitors. I have a magnet that moves around this pictograph depending on how the week is going.

Inspirational quotes are also written on the whiteboard once a week by a diligent part-timer.  Motivational stuff like “If opportunity doesn’t knock, build a door” and sometimes truth: “a clear conscience is a sign of a bad memory”.

The drive of light-heartedness even creates highly sophisticated equipment with bullet-hole stickers on the sides and hilarious names for these instruments. We have the complete set of Thunderbirds characters for our instruments and we’re starting on a set of animated characters from Toy Story.

Oddly, justifications for new instruments such as “because if we just get a Buzz Lightyear we’ll have a complete set” don’t get much traction with the funding body.

While the general motivation is good-natured, there are tensions arising from such displays. Currently a silent battle rages in our lab played out by the Stop sign on the door to one lab. Sometimes it reads “Stop – Food-grade glassware only”, but more often it reads “Stop – in the name of love” and recently Stop – Hammer time.” This is likely to change again as the next wave of PhD students build the courage to add their version.

Little things like this make the lab more enjoyable. And reassures us that we are hilarious. Even if only other researchers think so.

Engaging the work experience kid

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Making routine science interesting for work experience kids can be a challenge. Image: pinecrestdayschool.com

Work experience is a valuable lesson for all school kids. Particularly when it makes you realise exactly what you don’t want to do in life. Ever. And that’s an important lesson.

So when it was announced that we would be taking on a work experience kid for a few days, I was keen to show her how cool and amazing science can be to encourage her to want to pursue a scientific career.

Unfortunately, when it came to my turn to dazzle the WEK with science, I was changing the water for my dialysis samples. I tried to make it interesting and gave her some hands-on experience by letting her refill the container with water but it still lacked some scientific sparkle.

Then I tried to impress the WEK with scientific equipment and showed her how compounds are separated using HPLC. I explained the principles of compound separation and then demonstrate how to prepare the samples. It was pretty complex stuff but she was very quick and could summarise the procedure:

Me: Now we need to pipette 40 µL of sample into 2 mL screw-capped HPLC vials with 300 µL inserts.

WEK: So like, transfer the samples from one container to another?

Me: Um…yeah.

And that, my friends, is science in action. Transferring samples into different containers is the basis of my day-to-lab work. It didn’t get much better when I showed her the resulting chromatogram and explained the very scientific way in which these data are processed:

Me: We now need to draw little lines under these curves on the computer and record the numbers that come up.

WEK: <smiles and nods politely>

While work experience teaches students about the real world, it is also educational for those already in the real world. For example, I learned that a Year 10 chemistry student can do my job. At least, the lab component. And that’s a pretty big component.

One thing that must be learned by aspiring researchers is that the most interesting and challenging part of science is not conducting the experiments. It is identifying a knowledge gap, designing the experiments to give the required information, and, my favourite bit, making sense of the data from those experiments.

This is the fun part of research but unfortunately it is not necessarily communicated to a student on a few days of work experience. Not even with my repeated explanations that may have only served to make me feel better.

I just hope the novelty of working in a real lab with real experiments was interesting enough so that science isn’t on the list of things the WEK never wants to do again.

Coordinating the Great Research Project Conjunction

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The converging of research projects in this world is almost as disastrous as a Great Planetary Conjunction in other worlds. Image: greatconjunction.tumblr.com

 

Timing is the greatest challenge with natural products. No matter how beautifully constructed an experimental design and the hours that go into planning each experiment, inevitably Nature will come along and mess it all up. This week, despite my well-constructed project proposals with suitable distances between each set of analyses, I’ve ended up with three large projects converging on a single analytical time point.

Two projects are just kicking off thanks to harvest times coming together and one is the final time point of an existing project and none of them have any rights to be invading on the other.

After my inevitable melt down that came with the Great Realisation of the Impending Conjunction and the subsequent hours of therapy, I’ve realised that things might not be as bad as they seem. The key to controlling such as dilemma always comes back to the basic principles of Do, Delegate or Delete.

Ideally, I’d like to Do everything. This is mostly because I have a few control issues and difficulty letting go but that’s a topic for a-whole-nother therapy session. In this case I simply can’t do everything without sacrificing a few things, like sleep. And that’s not happening. So, grudgingly, I will prioritise the very long list of analyses and do only those in the absolutely-essential-must-be-done-now category.

Other tasks will have to be Delegated to colleagues who might have a spare moment from their own trials to run a few samples for me. Usually the analysis itself isn’t difficult, just time consuming, and unfortunately that’s something I’m short on. Borrowing some minutes from other people is enormously beneficial to me and not a burden on them, kind of like crowd-funding for time.

Delegating to work experience students might also be an option. Piling work on an unsuspecting student is apparently fine as long as the forms say ‘work experience’ and not ‘slave labour’, even if the latter is more accurate. Not that I’ve tried this yet, but at the moment, anything is looking good. And I’m sure the experience will be enjoyable for the student in an eye-opening, real-life experience kind of way.

As for anything else that can’t be met in the required timeframe for analysis, it might have to be Deleted from the to do list. This is where prioritisation is critical. Do I really need to measure everything possible just because I can?

In these days of being able to measure absolutely everything, we really need to assess if it is worth the amount of work if nothing is significantly different. So maybe I can cull a few experiments or samples and only look at only the most influential without compromising the integrity of the experimental design. Not that I’d actually dispose of those other samples, just in case there was a difference. I would need more a lot more therapy to get over that kind of trauma.

Things are looking much less stressful now with my new and improved planning strategy for the Great Project Conjunction. I might even have time for a coffee.

On the brink of greatness

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Research papers can lead to Nobel Prizes, but usually they just lead to more research. Image: http://www.japantimes.co.jp   

One of the key things l love about my job as a research scientist is data. Months of slog work in the lab produces great swathes of data and finally getting a chance to process it and understand what is happening is pure happiness. Particularly when combined with varying concentrations of coffee and chocolate.

This is a particular characteristic of all research scientists, I’m sure. (And yes, I am aware of the irony of proclaiming a love of data and then ignoring any such data to make sweeping generalisations about a large portion of the population. But it’s for the good of making me feel more normal so I’m willing to go with it.)

Processing data is the point at which we can see if all our efforts and hypotheses have made any inroads into the unknown. If they have, either by proving or disproving a hypothesis, it is triumphant.

The process involves turning spreadsheets into works of art, although admittedly a peculiar brand of art. I enjoy turning reams of numbers in to very pretty graphs and, ideally, correlations and trend lines. Constructing those is rewarding on a level that is second only to writing the paper.

A research project isn’t finished until it is published in a peer-reviewed journal. At least, that’s my opinion. I know many scientists who disagree with me on this one. For them, the true joy lies in discovering something new and broadening their knowledge but getting the word out there to the broader communities of scientists and non-scientists is nothing but a chore.

But publications are the bread and butter of research and while the peer-reviewed process might be flawed, it is still the best system for ensuring the majority of science is carried out in a reproducible manner and that the conclusions are matched by the data.

Now, after many, many months of producing data, I have finally had a chance to sit down and process it. And it worked! I have evidence that supports my hypothesis and I have made tiny inroads in hitherto unknown regions of knowledge.

Now all I have to do is write the paper, get the co-authors (my managers and other people who helped produce the data) to read it, get them to agree with how it should be written, get the reviewers to agree that the work is of sufficient quality, incorporating all possible controls and blanks, and voila! Another science paper published. Greatness will be mine! I might just go call the Nobel Prize committee and give them a heads up. I’m sure they’ll want to know.

In reality, even without a Nobel Prize, it’s being able to shine a torch onto new knowledge after months of slog work in the lab is what makes all the effort worthwhile.

Coffee for the good of science

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Coffee breaks help generate a rapport between colleagues and avoid the need to settle disputes with cage matches. Image: mmaweekly.com

 

Locked away in our laboratories, researchers tussle for access to equipment and resources. The overriding sensation is a tense mutual respect. We generally acknowledge each other’s space and equipment but this respect is tenuous and can breakdown in an instant.

Something can go slightly wrong on a project and suddenly next week’s deadline is ominously close and that person needs all the equipment RIGHT NOW. This then encroaches on other people’s deadlines as resources they have booked and planned to use are suddenly inaccessible, and the whole ‘mutual respect’ thing descends into cage matches.

That isn’t quite true. We haven’t got a cage in the lab yet but I’m sure it’s included in next year’s budget.

This is one of the key reasons why research institutes usually have a ‘social club’. It’s a way of forcing people to get to know each other outside the lab in friendly environments and even footing. The same can be said for such activities as ‘lunch’ or ‘coffee breaks’.

Anything that involves the coming together of people – preferably in combination with food and drink intake – can improve relations.

As science becomes more multidisciplinary, being able to get along with other people who are not quite in the same team or have the same objectives is an increasingly important skill. Getting out of the lab and gathering around food with colleagues is a simple but effective method for creating better relationships and building stronger teams.

So go on, put down that pipette and have a coffee. It’s for the good of science.