World sensation: Increase in life expectancy by more than 10 years!

Anyone who follows this blog must get the impression that I am a nag and misanthropist. Nothing and nobody seems to please me. I alway find the sample sizes too small, the statistics too lazy, the data hand-picked, or the results too positive and the conclusions drawn from them too exaggerated. Also, I find the peer review system unreliable, not to mention support of mainstream research and giving to those who already have (‘Matthew effec’)  by the funding agencies. I even dared to critsize the Nobel Prize an atavistic instrument celebrating the lonely, white male reseacher and genius. Artificial intelligence I find stupid, and the academic career system the core of all these evils. To name but just a few examples.

But that is far from the truth! I am a science enthusiast! I am convinced that science is the best that the 1500 grams of protein and fat encapsulated in our skull have ever produced. Yes, I am a science nut. So with this entry, at the beginning of the new decade, let’s start with a proper hymn to biomedical science. Continue reading

Diet: Is nutrition science a more reliable source of advice than your grandmother?

Meat consumption is bad for your health. It gives you cancer, heart attacks, stroke, you name it. Says nutrition science. And they must know. After all, it’s a science. Is it, really?

A few years ago, Jonathan Schoenfeld and John Ioannidis took a standard cookbook and randomly selected 50 frequently occurring ingredients (sugar, coffee, salt, etc.). They then carried out a systematic literature search, asking whether there were epidemiologicial studies that had investigated the cancer risk of these ingredients. And they found what they were looking for. For 80% of the ingredients at least one study existed, for many even several. Of 264 of these studies, 103 found that the ingredient investigated increased the risk of cancer, while 88 reduced the risk! So  after all Joe Jackson was right: ‘Everything gives you cancer’! But wait a minute: Milk? Veal? Orange juice? Continue reading

Why do WE trust the Intergovernmental Panel on Climate Change, but not the climate skeptics?

The societal acceptance of the results of our daily work as scientists is dire. The majority of the US population does not explain evolution with Darwin, but with Holy Scripture. Measles is on the rise again worldwide, because vaccination opponents smell a conspiracy by the pharmaceutical industry to make children autistic. A substantial proportion of the population does not believe that climate change is man-made. They believe that if you fear climate change you are hysterical, and manipulated  by interested scientists competing for funding and fame. Homeopaths treat disease with sugar pills, while the health insurers, with our money, foot the bill.

A popular recipe against this increasing rejection of relevant scientific findings is to provide more and better science education in schools and the media. Inspired by a lecture of the American sociologist and historian of science Steven Shapin, I respectfully disagree.

Continue reading

Podcast mania

In letzter Zeit war ich zu Gast in einigen Podcasts und längeren Interviews, für Audiophile hier die links:

 

 

 

Spektrum der Wissenschaft

AUS FORSCHUNG WIRD GESUNDHEIT
Wie gut ist die biomedizinische Forschung?
Stefanie Seltmann

Heute stellen wir die Frage: Wie gut ist die biomedizinische Forschung? Stimmt es, was John Ioannidis von der amerikanischen Universität Stanford behauptet hat, dass die Hälfte aller wissenschaftlichen Artikel falsch sind? Beantworten kann mir diese Frage Professor Ulrich Dirnagl. Er leitet am Berlin Institute of Health das BIH Quest Center, das die Qualität und Ethik in der Wissenschaft erforscht. Er hat John Ioannidis ans BIH eingeladen, um als Einstein BIH Visiting Fellow mit ihm zusammen zu arbeiten.

https://www.spektrum.de/podcast/wie-gut-ist-die-biomedizinische-forschung/1702044

14 min


Inforadio Berlin

Dichtung und Wahrheit in der Forschung

Ulrich Dirnagl ist Professor für Neurologie an der Charité – und “Wissenschaftsnarr”, als der er regelmäßig eine Kolumne im “Laborjournal” schreibt. Mit Thomas Prinzler spricht er über Qualität und Ethik in der biomedizinischen Forschung. Denn zu oft würden Ergebnisse weggelassen oder auch gefälscht.

https://www.inforadio.de/programm/schema/sendungen/wissenswerte/202002/09/wissenschaft-forschung-medizin-ethik-faelschung-betrug.html

15 min


Deutschlandfunk Kultur

Wo Professor Zufall regiert  

Zu wenige Versuchspersonen, unsauber geplante Experimente, keine Replikation der Untersuchung: viele biomedizinische Studien haben Schwächen. So große, dass man stattdessen genauso gut eine Münze werfen könnte, meint der Neurologe Ulrich Dirnagl.

https://www.deutschlandfunkkultur.de/biomedizinische-studien-wo-professor-zufall-regiert.976.de.html?dram:article_id=458680#

7 min


Podcast Spektrum – Wirkstoffradio (André Lampe und Bernd Rupp)

WSR019 Schlaganfall, Stroke Units und die Verantwortung der Forschung 

150 min!


Podcast Kritisches Denken (Philip Barth, Andreas Blessing)

Episode 25 – Qualität in der Forschung

Im ersten Teil des Gesprächs mit Prof. Ulrich Dirnagl von der Charité Berlin sprechen wir über strukturelle Probleme in der Forschungslandschaft, die Reproduzierbarkeitskrise und den p-Wert. Details zur Episode

https://kritisches-denken-podcast.de/episode-25-qualitaet-in-der-forschung/

40 min


Podcast Kritisches Denken (Philip Barth, Andreas Blessing)

Episode 26 – Mikrobiomforschung und andere Hype-Zyklen

In Teil 2 des Gesprächs mit Prof. Ulrich Dirnagl unterhalten wir uns über die Mikrobiomforschung und wie Hype-Zyklen in der Wissenschaft verlaufen.

https://kritisches-denken-podcast.de/episode-26-mikrobiomforschung-und-andere-hype-zyklen/

60 min


Podcast Gesundheit Macht Politik

Ulrich Dirnagl | Forschung: This is an intergalactic emergency

https://gmp-podcast.de/blog/gmp053/


And here’s a video cast from the European Academy of Neurology

EAN 2019: Charles Edouard Brown-Séquard Lecture – Interview with Prof. Ulrich Dirnagl

When carmakers hack brains

You got to see this youtube video! Hectically cut sequences of busy young scientists in high-tech laboratories wearing lab coats, nerdy looking guys are soldering electronic circuits and stare into oscilloscopes, we are taken on a roller coaster ride through an animated brain chockful of tangled nerve cells. And in between all this, on stage at the California Academy of Sciences,  car and rocket manufacturer Elon Musk announces his latest vision in a messianic pose: The symbiosis of the human brain with artificial intelligence (AI)!  This time his plan to save mankind does not involve mass evacuation to Mars, but will be realized by a revolutionary Brain Machine Interface (BMI), designed and manufactured by his company Neuralink. You may have guessed it, this has caused a tremendous media hype all over the world. The verdict in the press and on the net was: “Musk at his best, a bit over the edge, but if HE announces a breakthrough like that there must be something to it”. The more cautious asked: “But couldn’t this be dangerous for mankind? Do we need a new ethic for stuff like this?” Continue reading

Love thy NULL result as thy statistically most significant!

Damn! What an effort: Generation of a knockout mouse line, back crossing in background strain and litermates, all the genotyping. Followed by a plethora of experiments in a disease model: surgery, magnetic resonance imaging, histology, behavioral studies, and so on. Finally the result: No phenotype! The knockout mouse appears to be a mouse like any other. Not different from the wild type background strain. But wait, we rather need to phrase it like this: We did not find a statistically significant difference between knockout and wild type. So we cannot even conclude that wild type are like knowout mice, but rather: If there is a difference, it might be smaller than the detectable effect size, depended on sample size, error level (alpha and beta) and the variance of our results. But we had planned our experiments well:  The sample size was determined a priori, and chosen so that we would have been able to detect a difference on the order of one standard deviation. This is what statisticians call a Cohen’s d of 1, which is considered a substantial effect. We could not have done more animals than the  (34!), because of limited ressources, the duration of the PhD thesis, and the timing of the grant. But what now? Write a paper? Reporting a NULL result? How would this look like in a resume, besides, who cares about NULL results, and which reputable journal would publish them at all? Continue reading