Naked mole rats have more than one weapon against aging | Hacker News Reader

Naked mole rats have more than one weapon against aging

phenomena.nationalgeographic.com

78 pointsbane16 comments

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In general, when you read statements like this in an article: "lthough we cannot directly test whether the unique 28S rRNA structure contributes to the increased fidelity of translation, we speculate that it may change the folding or dynamics of the large ribosomal subunit, altering the rate of GTP hydrolysis and/or interaction of the large subunit with tRNA during accommodation, thus affecting the fidelity of protein synthesis."

it's a strong suggestion that the authors are searchng for impact- that is, they found some mildly interesting data from an experiment that is replicable. The rest of it- the speculation- can just be tossed out. Their data is not strong enough to support it, so it's just speculation.

I once had a prof who seemed really arrogant to me. He said, "when I read a paper, I skip to the methods. if the methods make sense (IE, they actually know how to run a basic experiment) then I look at the results. That's all."

I thought that was arrogant, but in retrospect he was giving sage advice: the only content in most papers is in their data sections, not in the introduction, conclusion or discussion. Spend your time looking at the data, not what the authors think the data means, and make up your own mind.

That's fine if you happen to only read papers that are dealing with data you understand. In short, only papers in your own field.

You can't understand the statistics, and therefore the conclusions, if you don't understand the data. Your Professor was certainly arrogant (and foolish) if he didn't comprehend that.

Disagree completely. I can easily read papers well outside of my area (biophysics), such as climate research, and follow most if not all of the analysis. my field along includes hundreds of subspecialities, and I must frequently read and follow papers in another specialty.

Statistics itself is indepedent of the study details; it's just the application of probability to hypothesis testing and I know of no science which cannot express its models in the form of probabilistic analysis. That's why people who are physicists can move to medicine and produce useful criticisms of study design (cf Stan Glantz).

The one big issue with studies outside of my domain is that it takes more time and attention to read because I have to refer to citations or online resources to understand the technical details of their domain.

A while back, I picked up an old introduction to statistics book from the 1950s, just out of interest to see how things were done before computers, and I remember that near the beginning, there was a cautionary tale.

It started out with a simple bimodal distribution and explained that it was the results of some student tests. The reason it was bimodal was simply that it was the results from two different classes, the "smart" class and the "others". And talked about how this is a classic way to spot that you are dealing with two populations.

Then it related the tale of First World War marksmen. It turns out that when they were training their sharpshooters, the results, when plotted, had a bimodal distribution where they were expecting a normal one. They took this to mean that there were such things as "natural shots": men with a natural ability for shooting. If they could identify early which ones were the natural shots, they could concentrate their training much more effectively.

But it didn't work. After they separated the groups, it turns out that not only did the "natural" group also have a bimodal distribution, but they actually didn't perform any better than the "bad shots". To cut a long story short, they discovered that the bimodal distribution was actually an artifact of the scoring system they were using. When they recalculated the data with a different scoring system, they had a regular normal distribution.

It's a simple story with a simple moral: you can't interpret your results if you don't understand your data. Maybe I'm wrong though; it's been a while since I did stats and I've driven most of it from my memory. :-)

Oh, and it's not at all sad that I buy second-hand statistics books for fun reading. It's just not.

The scoring system would be described in the methods section and anybody with a decent data analysis and experimental design background would ferret that out.

Amazing how building a diagnostic protein, the biological equivalent of a `printf` statement, is being used here.

It's also exciting that this is no big deal for the researchers.

I like how the debunkers have already appeared, stoping scientific progress at every opportunity

it's not scientific progress if we falsely accept incorrect hypotheses. Debunkers play an important role of casting doubt on improbably claims.

Like how the sun is the center of the universe and burn all the heretics?

Looking like a naked mole rat is quite the price to pay for cancer immunity. But I guess every species is subject to evolutionary trade-offs. :p

"A number of studies have hinted..."

"The scientists were unable to directly examine the 28S RNA fragments in action, so they can’t say for sure that splitting 28S in two is the reason for the accuracy of naked mole rat proteins."

Right. So the entie article is nothing more than bs. Thank you for the book-tip, HN: "Bad Science", Chapter 11: How the Media Promote the Public Misunderstanding of Science "The dumbing-down of science to produce easily assimilated wacky, breakthrough or scare stories... The relative scarcity of sensational medical breakthroughs since a golden age of discovery between 1935 and 1975, is seen as motivating the production of dumbed-down stories which trumpet unpublished research and ill-founded speculation. "

I used to get upset about these things, but nowadays if a writeup of a paper bothers me or sounds weird, i just go to the original publication. This might be hard if you're not at a university or otherwise have access to the journals.

In this case i don't see anything particularly wrong. Just reading the abstract would tell you enough (linked from the article):

http://www.pnas.org/content/early/2013/09/25/1313473110

The paper reports that the 28S RNA is split and that the ribosomes seem to be better at avoiding mistakes whilst keeping the same translation speed, and the authors speculate if these two things could be linked. And that's the gist from the Nat. Geo. article, too.

Thank's for the reply. I'm currently reading 'Bad Science', After someone mentioned it here on HN. Perhaps I'm now in a 'too sceptical' mood. My apolegies to the author ;-)

As mohawk says, the content of the summary article fairly clearly reflects the gist of the publication. It was exploratory work, they think that that's the key factor but aren't sure.

I'd rather have public misunderstanding of aspects of science than have a deep public mistrust of science, which is the only thing that comments like yours create.

We need more of the public engaged with science and we need a wider appreciation of its value. Misunderstandings can be corrected over time.

Pleger read my comment "The dumbing-down of science to produce easily assimilated wacky, breakthrough or scare stories.."

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