How can we know?

A recent paper in Nature reported

Tissue samples were obtained from one of the following sources: Asterand, Pathlore, Tissue Transformation Technologies, Northwest Andrology, National Disease Research Interchange and Biocat. Only anonymized samples were used, and ethical approval was obtained for the study from Ärztekammer Berlin and the Cambridge Local Research Ethics Committee. […] Human primary cells were obtained from Cascade Biologics, Cell Applications, Analytical Biological Services, Cambrex Bio Science and the Deutsches Institut für Zell- und Gewebeersatz.

How did “Ärztekammer Berlin” or “Cambridge LREC” evaluate ethical performance of these companies? Or did anonymity automatically guarantee ethical research? Or is it just a formal requirement to mention ethics? Or …?


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Open culture podcasts

As a frequent traveller I like podcasts. Here is a quick link to Open culture that have a huge university podcast collection including many foreign language selections (Boston College, Bowdoin College, Collège de France, Duke University Law School, Harvard University, Haverford College – Classic Texts, Johns Hopkins, Northwestern University, Ohio State, Princeton University, Stanford University, Swathmore College, University of California (the best collection), The University of Chicago, The University of Glasgow, The University of Pennsylvania, The University of Virginia, The University of Wisconsin-Madison, Vanderbilt University, Yale University and Ecole normale supérieure). If you don´t like proprietary formats you need to find the good and the bad apples.


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Evolution in fast motion

Nature genetics as an advance online publication about comparative genome sequencing of E. coli where 13 de novo mutations in 5 strains were monitored over 44 d (or ~660 generations). It is a great study – not only because the author list includes one of my previous coauthors – but for giving a first insight about development of a mutation and fixing its allele frequency. Unfortunately, there is no flowchart and the methods are somewhat vague, what has been sequenced (or resequenced) in which strain at what time . In other words who are the winners? Did they manage that by their own strength or with a little help of some friends? Why rises the allele frequency always to 100% and what about some discrepancy of allele frequency and fitness? We will hopefully see more of these studies, yea, yea.


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Dr. med. Sigmund Rascher, KL Dachau

On my way to work I am crossing every morning in Dachau East the former Nazi concentration camp/Konzentrationslager (KL). Its a monument of inhumanity and the deepest point in the history of “science”. A large number of prisoners were abused by SS doctors for medical experiments; an unknown number of prisoners suffered agonizing deaths in the course of atmospheric pressure, hypothermia, malaria and other experiments.

photo by 11 Dec 06
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Having a longstanding interest in history (and even published on the 50th anniversary of the Nuremberg trials) I have now been very interested in a new book by Sigfried Bär, one of the outstanding German science writers “Der Untergang des Hauses Rascher”, a history of the life of Dr. Sigmund Rascher, anthroposophic scholar, medical student, DFG-scholar, minion of of Heinrich Himmlers, air pressure and hypothermia researcher at KL Dachau and finally prisoner who died by being shot in the neck.

Dr. Bär spent several years researching the life of this mass murderer. He contacted relatives of Rascher, looked at family photos, talked to people who knew Rascher and went to archives. This is a unique document showing the avidity of a researcher for recognition by scientific colleagues. Other books from my own library that I recommend:

pb300004.JPG


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Pathway to nowhere

I love pathway diagrams since I mounted the famous Biochemical Pathways of Boehringer in my bachelor flat. As far as complex disease genetics is concerned with many disease genes, an integration into a pathway context becomes critical. There are many attempts to extract this information from the literature and many companies that offer highly curated information (Biomax, Ariadne Genomics, Genomatix to name a few). Academia relies mainly on KEGG, the Kyoto encyclopedia of genes and genomes or Biocarta. Last week another pathway server appeared that is curated by the NCI and Nature magazine. Let’s have a look – I am currently working on Affymetrix 500K SNP annotation, yea, yea.


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How to detect your own CNVs

How to detect copy number variation (CNV) in your own genotype chip data, can be found in a companion paper of the recent Nature publication.
In the previous Nature paper the authors explained their algorithm to be based on k-means and PAM (partitioning around medoid) clustering, but it seems quite different. They call genotypes with DM (which seems to be already obsolete by the BRLMM, see a comparison at Broad and the AFFX whitepaper), then adjust heterocygote ratios by Gaussian mixture clustering, normalize and reduce noise before! merging NspI and StyI arrays. The software is at Genome Science, Tokyo. Yea, yea.


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On mice and men with asthma

A new series of pro- and con editorials in the Am J Res Crit Care Med discusses the question why in some instances mouse models have “misdirected resources and thinking”. You may have noticed that I have only rarely used animals for research; the authors of this editorial have collected empirical data on the exploding use of murine models. Despite their attractiveness from a technological point, they are often useless because

  • mice do not have asthma as even the most hyperresponsive strain does not show spontaneous symptoms
  • mice do not have allergy – although sensitization can be manipulated by high intraperitoneal allergen/adjuvant injection, this does not involve immediate and late airway obstruction.
  • immune reaction in mice is quite different – the interfering of some substances like vitamin D cannot be reliable tested, there is no pure Th1 and Th2 reaction in human and less stronger IL-13 response
  • mice typically can not be challenged with the complex (and interacting) human exposure – oxidant stress, viral infection, obesity, diet, smoke, pollutants, ….
  • time course is difficult to mimicking in the mouse, there is no longterm model
  • structure of mouse airways is different – there are fewer airway generations, much less hypertrophy of smooth muscle
  • inflammation in mouse is parenchymal rather than restricted
  • humans are outbred, mice are inbred
  • early microbial environment is different
  • many promising interventions of mice pathways failed in humans (VLA-4, IL4, IL5, bradykinine, PAF,…)

I am sure there are even more arguments – I suggest that the authors deserve the Felix-Wankel price.

Addendum

15 Dec 2006: The BMJ has 6 more examples about the discordance between animal and human studies: steroids in acute head injury, antifibrinolytics in haemorrhage, thrombolysis or tirilazad treatment in acure ischaemic stroke, antenatal steroids to prevent RDS and biphosphonate to treat osteoporosis.

19 Dec 2006: Another pitfall paper

31 Dec 2006: A blog on animal welfare

25 Apr 2007: Call for better mouse models

15 Jul 2018: Of Mice, Dirty Mice, and Men: Using Mice to Understand Human Immunology

16 Oct 2019 Allergy protection on farms – why also studies in mice could have failed

18 Feb 2023 The case for free running lab mice, see
Cell and Science paper

7 Jan  2023: A review concluding that  The vitamin D system in humans and mice: Similar but not the same

12 March 2024: Limitations of the mouse model

  • Lack of clinical relevance – The OVA model often fails to accurately replicate human asthma and allergic diseases. OVA is not a common human allergen, unlike house dust mites, pollen, and pet dander.
  • Artificial sensitization – The model requires sensitization with alum, a strong Th2-skewing adjuvant, which does not reflect natural allergen exposure in humans.
  • Simplistic immune response – OVA exposure leads to a predominantly Th2 immune response, whereas human asthma involves a complex interplay of Th1, Th2, Th17, and innate immune responses.
  • Limited chronicity – Most OVA models induce short-term allergic inflammation but fail to reproduce the chronic airway remodeling, fibrosis, and structural changes seen in human asthma.
  • Non-physiological exposure – OVA is often administered at high doses via intraperitoneal injection or repeated aerosol exposure, which does not mimic real-life human allergen exposure.
  • Strain-specific bias – Different mouse strains respond variably to OVA, making it difficult to generalize findings.
  • Lack of environmental and genetic factors – The model does not account for genetic predisposition, pollution, infections, or microbiome variations that influence human allergic disease development.
  • Poor translational value – Many drugs that show promise in OVA models fail in human clinical trials, highlighting the model’s limited predictive power.

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Why dog and cat can’t marry

or in more scientific terms: Why are F1 hybrids so often sterile or lethal?

The Dobzhansky-Muller theory says that there is an incompatibility between genes with reduced fitness that have diverged between species. So far nobody has ever observed a D-M gene but a new Science paper describes two genes that separate D. simulans and D. melanogaster: lhr (lethal hybrid rescue) and hmr (hybrid male rescue).

Well, dogs have 78 chromosomes, arranged in 39 pairs, while cats have 38 chromosomes, in 19 pairs – so no viable embryo can be produced.

 

Yea, Yea.


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For the first time two human genomes compared

Another “first discovery” in this nature genetics preprint although the analysis could have already been done some years earlier. The CNV specialists from Toronto now compare the Human Genome Project sequence with the Celera sequence – the gap between the two compilations was obviously bigger than the intra-sequence gaps. Of course both sequences are still mosaics from several individuals but the analysis nicely exemplifies how difficult it will be to compare the genome of two different human beings.
The authors employ a whole battery of alignment tools BLAT, MEGABLAST, GCA and A2Amapper. Of course results depend on the strategy, definition and implementation. As show by FISH analysis most of the discrepancies are true and can be classified into a few categories – insertions or deletions if seen from the second genome (has somebody ever thought about a minimal human genome?), mismatches and inversions. We are getting here a preview of the diagnostic workup in a patient in 2026. This blog contains forward looking statements while the responsibility rests solely with the reader. Yea, yea.


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The mind has a thousand eyes

The night has a thousand eyes,
And the day but one:
Yet the light of the bright world dies
With the dying sun.

The mind has a thousand eyes,
And the heart but one.
Yet the light of a whole life dies
When love is done.

Francis William Bourdillon

(found 7/12/06 on the inside cover of an old book with title “Perdita” in the patient library of a university clinic)


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Assets minus debts

Slashdot reports a United Nations study that

the richest 2% of adults in the world own more than half of all household wealth… Most previous studies of economic disparity have looked at income, whereas this one looks at wealth – assets minus debts.

Looks similar to science budgets, yea, yea.

Addendum

An interview with Richard Münch in Laborjournal 12/2006, p.23 confirms this: 17 out of 100 German universities consume 50% of all funds provided by DFG. He furthermore believes that SFBs and research networks are a kind of ideological framework; projects are not assessed retrospectively; there is an overkill of management costs where a considerable part of third-party funding is used to get more third-party funding.


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Headline: For the first time 2 human genomes compared

What sounds brand new in a current nature genetics preprint, could have even been done already a couple of years before. The CNV specialists from Toronto compare now the Human Genome Project sequence with the Celera sequence. Was the gap between these two compilations bigger than the intra sequence holes? Both sequences are of course mosaics from several individuals but the analysis nevertheless exemplifies how difficult it may be to compare even the genome of two related individuals. The authors employ a whole battery of alignment tools BLAT, MEGABLAST, A2Axxx, GCA. Of course results are different depending on strategy, definition and implementation used. As show nicely by FISH analysis most of the discrepancies are true and can be classified into a few categories – insertions with and without corresponding fragment or deletions if seen from the second genome (has somebody ever thought about a minimal human genome?), mismatches and inversions. We are getting here a preview of the diagnostic workup in a patient in 2026. This blog contains forward looking statements while the responsibility rests solely with the reader. Yea, yea.


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New LD measure

There is a new way to calculate LD that may overcome the limitations of D’ and R^2 that are not easily generalizable to multiallelic markers (or haplotypes) and depend on the distribution of SNPs (or haplotypes).
The paper is at BMC, the sources at the authors’ website. I have slightly modified the program to allow input and output file names on the command line before compiling it. Use at your own risk, yea, yea.


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New R packages for SNP studies

The December R newsletter reports several brandnew bioconductor packages useful for SNP studies:

more


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