For those of you who are wondering what became of me — in 2012 I left the lab; since then, I’ve been working as a scientific language editor and developing two book proposals (including one about the biology of aging). Blogging here at Ouroboros was a joy, and I hope to get back to it someday.

At the moment, my main online activity is the new blog Life on Mars, which describes my ongoing participation in the Mars One Project, an audacious effort to send a human crew to Mars by 2025. As it matures, the blog will encompass an increasing number of topics, ranging from Mars One news to new science about Mars and planetary exploration in general. (For those of you who prefer Facebook, I have a page there too: A Biologist on Mars, and I also provide various Mars-related updates on Twitter as @DoNotGoGently.) Feel free to stop by and say hello!



As I was wandering the net today I found a very nice writeup about the 2009 report of an association between the FOXO3A gene and human aging. I found the article at the apparently quite popular but new-to-me blog Singularity Hub.

We mentioned this work in a brief post last year. The overall conclusion is that natural variants in this gene that are associated with extreme longevity. (The FOXO3A gene is a homolog of DAF-16, a longevity determinant in worms.) The 2009 paper describes a study of German centenarians, and is consistent with similar results in Japanese-Americans, published in 2008. Other genetic variants associated with lifespan include the hTERT and hTERC loci, recently described in a study of Ashkenazi Jewish centenarians.

Mostly I’m writing this post to introduce our readers to an interesting site: Singularity Hub contains a lot of excellent biogerontology coverage (in their longevity category). Much of the writing on that topic is by senior editor Aaron Saenz, who does a great job of critically addressing the newest findings in a very reader-friendly and accessible style. I’m going to subscribe to their feed and start reading regularly. Overall it’s a very professional and well-written site, and I’d recommend it to Ouroboros readers.

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I just learned of an excellent new blog – @ging, dedicated to “scientific findings on aging and its underlying mechanisms / Los avances científicos sobre el envejecimiento y sus mecanismos reguladores.” That’s right, it’s bilingual in English and Spanish, with almost every article appearing in both languages.

Authors Shaday and Layla Michán state their site’s mission succinctly as follows:

This space is devoted to analyze and discuss the advances on aging research.

Este espacio esta dedicado a analizar y discutir los avances en los etudios de envejecimiento.

The site has been up less than a month; so far, posts have dealt with a wide variety of subject, from demographics to genetics to molecular details of aging. The writing is concise and very readable, in both languages (so far as I can tell; my Spanish is functional but weak). Overall, I’m very favorably impressed. There’s also a great sidebar with links to recent articles in aging-related journals.

Whether you’ve been longing for biogerontología en español or you’re strictly inglés-only, be sure to add @ging to your daily reading list.

A somewhat belated happy birthday to Fight Aging!, an important resource for lifespan extension advocates that also has some of the best (and constantly improving) scientific coverage in the field. Fight Aging! (and its older companion effort The Longevity Meme) are two fine websites that this humble blog is proud to count as friends. We might not agree on everything, but then again, who does?

If you’re not reading Fight Aging!, you should be.

Congratulations to FA’s proprietor, Reason. Happy sixth blogiversary, and many (many, many…) happy returns!

A couple of months ago I lamented that scientific blogging would probably be unable to serve as an effective “filter” for the scientific literature. Scientists struggle to keep up with the literature in their own field (let alone related fields), and it would be nice if someone could pre-screen emerging papers in a way that would decrease the time and effort involved in keeping current. For a variety of reasons, I think it’s unlikely that science blogs will be able to serve this function.

But filtering isn’t the only justification for the existence of science blogs, as is made clear by a recent bumper crop of blog posts and articles about science blogging. Blogging can help an individual scientist share ideas with colleagues and spread the word about one’s own work. Some see blogs as increasingly essential to the process of self-promotion, whereas others see an opportunity to fill growing holes in the fabric of conventional science journalism. There is a consensus that blogging is less prestigious than other kinds of scientific publishing, but as participation grows, this may change.

In rough order of the ideas presented in the previous paragraph, I present these pieces here for your delectation:

There are a number of good science-related shows on Public Radio: Science Friday, Radiolab, and Tech Nation top my personal list, and there are many others. This type of programming is an important means of disseminating scientific ideas to a general audience, and as I scientist I think I enjoy the shows more than the average listener. Still, I often find myself wanting more: more detail, more description of methods and controls used to obtain results, more erudite discussion about the context of a given finding within the larger edifice of scientific inquiry. More.

So it’s been with great satisfaction that I’ve discovered several podcasts administered by scholarly journals:

This is “science radio” but with a twist: the intended audience is us. The producers aren’t targeting a general audience, and as a result they’re free to include highly technical content. Especially with the Science Signaling podcast, which often involves an interview with the author of a recent paper featured in STKE, the stories sound more like a lab group meeting than a radio show.

Granted, this comes at a cost: the journal podcasts have high production values but not quite as high as on general-audience NPR shows, and sometimes the phone interviews sound like they were conducted underwater, making it harder to listen in noisy environments like a car moving at 70 MPH down a California freeway.

But that’s a small price to pay. This is exciting! Podcasting is democratizing broadcasting to the extent that people are creating high-quality professional programming for a small minority of people diffusely scattered all over the world.

What are you waiting for? Check it out. All three of the podcasts I’ve mentioned are available (for free) via iTunes and the websites linked above

Two questions:

  1. Does anyone else have a science-for-scientists podcasts they’d like to share?
  2. When will an open-access journal step up to the mike?

You know by now that I love literature search tools (check out the small but growing “Links: Search” category in the right-hand column on the main page). I am strongly motivated by a desire to filter the huge and growing biological literature so that I can find the most relevant papers with the least amount of effort. Therefore, I’m always curious when I hear of a tool that purports to do an old task (searching Medline) in a new and unusual way.

A company called Cognition (“Giving technologies new meaning”) claims to enable the user to use semantic natural language processing to search the literature. Here’s their elevator pitch:

Cognition’s Semantic Natural Language Processing (NLP) technologies add word and phrase meaning and understanding to computer applications, providing a technology and/or end-user with actionable content based upon semantic knowledge. This understanding results in simultaneously much higher precision and recall of salient data within the universe of possible results. Cognition’s Semantic NLPTM makes technologies and applications more human-like in their understanding of language, thereby resulting in more robust applications, greater user satisfaction and new capabilities available for exploitation. On the Web in particular, powering applications with Cognition’s semantic understanding technology drives these applications ever closer to Web 3.0 (the semantic Web).

They have various commercial applications for sale but their semantic MEDLINE product is freely available on the web.

I’m not going to lie to you — it’s pretty great. You can ask the interface a real English question, like “Which genes are expressed in senescent fibroblasts?” and get real answers. (OK, to be fair, it’s fine with just “genes expressed senescent fibroblasts”, but I enjoy being able to use my native language when I talk to a computer.) I encourage you to play around with it; it’s fun.

One feature that seemed promising at first didn’t seem to work well at all. On the right-hand side of the search results screen are a series of dropdown menus; each menu contains several different meanings for keywords within the query. The idea is that one could refine a search by choosing the specific meaning of an ambiguous term, rather than having to slog through a search result that allows all meanings of the term in question. Unfortunately, this feature doesn’t deliver. Allow me to illustrate.

In the query example mentioned above, the dropdowns allowed for six meanings for the word “express”. The results had initially come back with one of these meanings (“6. to make a protein in bacteria or cells in culture”) already selected (I assume because this meaning gave the largest number of hits: ~12 papers, a totally manageable number, all of which were good answers to the question).

That definition is OK but I felt like another meaning (“5. to make a protein from a gene”) was slightly closer to the original intent, so I chose that definition and resubmitted. This culled the list down to only 1 paper, which wasn’t a very good match, and eliminated all the excellent answers from the earlier version of the search.

I can’t even begin to guess how the “sense” of a word is determined algorithmically by the Cognition software, but I do know that the outcome of my twiddling didn’t conform to my intuitive understanding of the words involved — which, after all, is the whole point of natural language processing. So I have to list this under “room for improvement”.

Which is all just to say that this search engine isn’t perfect yet — but please don’t let that stop you from checking it out. I like a lot of things about Cognition semantic Medline, and I’m going to be using it a lot.

What do you think? I’d love to hear about other people’s experience with the software.

(Hat tip to Code-Itch. Yes, I’ve had that post bookmarked since September.)

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