I have been thinking about art lately. The University of Sheffield's annual Festival of Academic Writing is coming up and I have just finished reviewing a few papers and grant applications. Mostly, this has made me consider how scientists can suffocate enthusiasm for even the most exciting finding in a single passive paragraph (never mind … Continue reading Art+Science
Excellent post by Small Pond Science on why 'pipeline' is a problematic metaphor for the scientific career path. When we talk about increasing the representation of women and ethnic minorities in STEM, the path towards a professional career is often characterized as a “pipeline.” The pipeline metaphor is so entrenched, it affects how people think … Continue reading Reblog: “We need to stop calling professional development a “pipeline”
Collaborators are highly valuable for a researcher. For many of us in experimental fields, they are the only way to get enough data to fulfil the publication demands each year (a requirement that warrants a separate, full blog post in its own right). But how does one get good collaborators? The Think Ahead blog has … Continue reading Reblog: “Collaboration – seek and ye shall find?”
Pulmonary rehabilitation is one of the most effective treatments for breathlessness in chronic obstructive pulmonary disease (COPD), yet its effect is variable. While up to 60% of patients who complete a course of treatment see an improvement, that leaves 40% that do not. Understanding why it works for some and not for others can help … Continue reading Pulmonary rehab: changing the signal
Magnetic resonance imaging is sensitive to motion. Just like with other images, movement may cause blurring and distortion ('artefacts'). To counteract this, motion correction methods are often used. These include devices that track motion as well as software that can correct some of the artefacts after the images have been collected. We have just published … Continue reading MRI and motion correction
I planned my career, but not all went exactly as I envisioned. Opportunities emerged, unexpected findings were too interesting not to pursue, new studies arose from old ones, new collaborators came up with exciting suggestions, and pints with colleagues often turned into interesting, half-crazy ideas that somehow worked. As a result, I have worked across several … Continue reading Reblog: “I fell into this by accident”
“All hypotheses emerge from assumptions, whether we recognize them or not.”
Ambika Kamath, a graduate student at Harvard University working on lizards and how their habitat, behaviour, and morphology influence eachother, has written an excellent blog post in the wake of a human dimorphism debate. The post is not about human dimorphism, but instead highlights how our assumptions can shape experimental design and therefore results. It can be easy to accept oft-cited facts without critical thought, particularly if they are in line with personal opinion.
Ambika Kamath’s post is reblogged below, and I encourage you to read it.
Over the last few months, there’s been a slow-boiling battle underway between Holly Dunsworth and Jerry Coyne about the evolution of sexual dimorphism in humans, surrounding the question of why male and female humans, on average, differ in size. The battlefield ranged from blogposts to twitter to magazine articles. In a nutshell, Coyne argued that “sexual dimorphism for body size (difference between men and women) in humans is most likely explained by sexual selection” because “males compete for females, and greater size and strength give males an advantage.” His whole argument was motivated by this notion that certain Leftists ignore facts about the biology of sex differences because of their ideological fears, and are therefore being unscientific.
Dunsworth’s response to Coyne’s position was that “it’s not that Jerry Coyne’s facts aren’t necessarily facts, or whatever. It’s that this point of view is too simple and is obviously biased toward some stories, ignoring others. And…
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MRI images are created from raw data contained in a raw data space, called k-space. This is a matrix where MR signals are stored throughout the scan. K-space is considered a bit of a tricky topic, so I will only outline a brief explanation of what k-space is and how it relates to the MR image. This is a … Continue reading MRI and k-space
Say you want to give an orange an MRI scan. You pop it in the scanner, apply your radiofrequency pulse, and receive the signal. This signal will differ depending on which part of the orange it comes from, for example whether it is the flesh or the peel. But how would you be able to tell where … Continue reading MRI: location, location, location
MRI is complex, but the basic events in the scanner are quite straight-forward. Below is a short, simple guide to what happens during an MRI scan without too much physics to complicate matters. It explains the actual events in the scanner and a simplified overview of the parameters we can use to change the images we … Continue reading What happens during an MRI?