#jamming transition

"Jammed Cells Expose the Physics of Cancer"

In 1995, while he was a graduate student at McGill University in Montreal, the biomedical scientist Peter Friedl saw something so startling it kept him awake for several nights. Coordinated groups of cancer cells he was growing in his adviser’s lab started moving through a network of fibers meant to mimic the spaces between cells in the human body.

For more than a century, scientists had known that individual cancer cells can metastasize, leaving a tumor and migrating through the bloodstream and lymph system to distant parts of the body. But no one had seen what Friedl had caught in his microscope: a phalanx of cancer cells moving as one. It was so new and strange that at first he had trouble getting it published. “It was rejected because the relevance [to metastasis] wasn’t clear,” he said. Friedl and his co-authors eventually published a short paper in the journal Cancer Research.

Two decades later, biologists have become increasingly convinced that mobile clusters of tumor cells, though rarer than individual circulating cells, are seeding many — perhaps most — of the deadly metastatic invasions that cause 90 percent of all cancer deaths. But it wasn’t until 2013 that Friedl, now at Radboud University in the Netherlands, really felt that he understood what he and his colleagues were seeing. Things finally fell into place for him when he read a paper by Jeffrey Fredberg, a professor of bioengineering and physiology at Harvard University, which proposed that cells could be “jammed” — packed together so tightly that they become a unit, like coffee beans stuck in a hopper.

Nice piece I came across in Quanta magazine last week, after my own post on 'jamming' — biochemistri.es/jammed

I'll write again about this topic soon as it's quite a lovely mix of biophysical, biochemical and translational research, along with a long and elegantly communicated history to pick through.

Code-switching

I'm going to return to using this blog more often, but it'll be more free form than long dives into papers and subject areas (I was working on a system earlier this semester to facilitate that process, queck, but it's still bouncing around the drawing board).

One of the notions in the aforementioned is to provide little collections of links (codified as 'eggs', long story), so in that spirit... some papers, blogs, and links I fancy throwing in after the above:

Note for new followers:

I also have a stream of papers, articles, blogs etc., naïve locus:

sync'd to Twitter here

...and posts to a blog you can follow through Tumblr at naivelocus.com / or using its RSS feed is here.

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"Nice set of intro articles on key concepts in statistical analysis of biological data. Useful teaching resource." in Nature, via Anshul Kundaje, Stanford, who works on machine learning - a key application of statistics in biology at the moment.

Two recent papers from the lab of Jacky Goetz on tumour biomechanics:

Seeing is believing: multi-scale spatio-temporal imaging towards in vivo cell biology. Journal of Cell Science, August 2016

Intravital Correlative Microscopy: Imaging Life at the Nanoscale. Trends in Cell Biology, August 2016

Network biology concepts in complex disease comorbidities fresh off the press at Nature Reviews Genetics

Scaling in complex systems: A link between the dynamics of networks and growing interfaces. Scientific Reports, December 2014

Feynman's original treatise on nanotechnology: 'There's Plenty of Room at the Bottom' (web page, PDF)

Many of these ideas are now possible (so says Subutai Ahmad, at machine learning company Numenta)

Plenty of Room Revisited (Nature Nanotechnology, 2008)

Fedde Benedictus, What is a dimension?

while you're on his blog, How natural is the natural logarithm?

... and Probability 0 is not impossibility

Bonus, more on the physics side of matters:

Space Emerging from Quantum Mechanics by Sean Carroll, theoretical physicist at Caltech

I'm not usually into that sort of thing, but this podcast interview with him apparently namechecks: Thomas Bayes, Rod Thorn, Albert Camus, Fitz Dixon, Christoper Nolan, Brian Greene, Orlando Woolridge...