[Neurosciences/Junk Sciences] Autopsy of a flawed study of aluminum and brain inflammation (Li et al., J Inorg Biochem 2017)

Note: This is a special blog post coauthored by The Mad Virologist and The Blood-Brain Barrier Scientist (this article will be co-published on both our blogs). Another post has already been published on this paper, but we wanted to take a deeper look at everything that is wrong with this paper.

[UPDATE2] The study in question got retracted according to RetractionWatch:

[UPDATE] I would strongly recommend the reader to look at the comments on Pubpeer about this paper. It is terrifying to think how it percolated through peer-review.

A recent paper by ophthalmologist Chris Shaw was published and immediately touted as being proof positive that the aluminum adjuvants found in some vaccines are responsible for causing autism. Before we get into the paper, I have a few choice things to say about Chris Shaw. Despite not being an immunologist, Shaw has ventured into studying how vaccines and vaccine adjuvants cause neurological disorders such as autism. Shaw made headlines in 2016 when a paper he co-authored that claimed to show a link between the HPV vaccine and neurological disorders was retracted after being accepted by the journal Vaccine. It turns out that the statistics used in the paper were completely inappropriate and there were undisclosed conflicts of interests for some of the authors, including Shaw.These issues should have prevented the paper from being accepted in the first place, but mistakes do happen and science tends  to be self correcting. More surprising is that Shaw claimed that he didn’t know why the paper was retracted and that the science was of the highest quality. Shaw’s previous work has also been described by the WHO as deeply flawed and rejected by that body. This isn’t being brought up to dismiss the paper out of hand but to help illustrate why Shaw’s work is deserving of additional scrutiny. Hopefully by the end of this post, the logic behind the need for additional scrutiny of anything Shaw publishes is abundantly clear. We’ll begin by examining the methods used by Shaw’s research group and point out some of the issues.

Background for experimental design flaws: PK and species issues

One problem that is recurrent with Shaw is his “vaccination schedule” tries to consider rodents, such as mice and rats, as humans in miniature. It is wrong to assume that rodent and human primate species are alike, they’re not and there are notable physiological differences between rodents and non-rodents. For example, there are a couple of studies by Terasaki and colleagues (http://onlinelibrary.wiley.com/doi/10.1111/j.1471-4159.2011.07208.x/abstract) that have shown differences in the expression of solute carriers and drug transporters at the blood-brain barrier. We cannot exclude that such differences may bias the outcome observed in his studies, but this bias applies intrinsically to any in vivo studies based on a rodent model.
There is also the issue of brain development and mapping the vaccination schedule and the brain maturation. In this study (as well in the previous ones), Shaw and colleagues consider that applying vaccines from post-natal day (PND) 3 to 12 is representative of a human infant vaccine schedule. There is some differences in the literature, as previous studies from Clancy and colleagues mapped the PND12 to the 7th gestational months in humans (https://blogs.cornell.edu/bfinlay/files/2015/06/ClancyNeurosci01-17kkli7.pdf), some more recent publications map PND21 to 6th month post natal in humans, making the PND12 around the 3rd month infancy following full-term birth (http://www.sciencedirect.com/science/article/pii/S2352154615001096). You can easily appreciate that by following Shaw flawed experimental design, the total amount of Al administered during a 2 year period has been indeed administered within 90 days of birth, whereas the vaccination schedule according to the CDC does not start before the 2nd month of infancy if we exclude the two injections of Hepatitis B vaccines at birth and after the first month respectively (https://www.cdc.gov/vaccines/schedules/hcp/imz/child-adolescent.html).

In addition to a flaw in the experimental design, we cannot exclude some differences in the pharmacokinetic profile of Al adjuvants between mice and humans. The data available is fairly limited but a recent study from Kim and colleagues (https://www.ncbi.nlm.nih.gov/pubmed/26437923) failed to show a significant brain uptake of Al compared to controls following the single oral administration of different Al oxide nanoparticles at a concentration of 10mg/kg. Furthermore, the approximation of Shaw in terms of total burden of Al from vaccines (550 microg/kg) is not an accurate metric as we have a dynamic process involving absorption, distribution and elimination to occur simultaneously. A daily burden of Al from vaccines is a much more reliable parameter to consider. Yokel and McNamara (https://www.ncbi.nlm.nih.gov/pubmed/11322172) established it about 1.4-8 microg/day for based on 20 injections spanning over a 6-year period in a 20kgs individual.
If we consider Shaw calculation, then the total burden at age 6 would be 1650 microg/kg or 33’000 microg for a 20kgs 6-year old child. That’s about 15 microg/day of daily Al burden from vaccines, a value that is 2 to 10 folds higher than applied to humans. It makes therefore very difficult to compare apples to oranges, as Shaw experimental paradigm is flawed and not representative of a clinical scenario.

Selection of genes to measure:

Selecting which genes to measure is a crucial step in a study like this. If care is not given to ensure that the correct genes are selected, then the study will be a wasted effort. Shaw stated in the paper that they selected genes that were previously published. However, not all of the genes that they measured came from this paper. Only 14 of the genes were from this paper (KLK1, NFKBIB, NFKBIE, SFTPB, C2, CCL2, CEBPB, IFNG, LTB, MMP9, TNFα, SELE, SERPINE1, and STAT4). This leaves 17 genes the were measured but not found in the paper. Two of these can be explained. One gene, ACHE, was mentioned as having been selected because of other work, so it is sourced. The second gene, is the internal control gene beta-actin. This is a housekeeping gene that is often used as an internal control to provide a relative expression from. This leaves 15 genes unaccounted for. We suspect that these genes were selected because they are involved in the innate immune response, but no reason is stated in the paper.

The way these genes were selected is problematic. Because half of the genes seemed to be selected for uncited reasons, this study is what is known in science as a “fishing expedition.” There’s nothing inherently wrong with this type of research and indeed it can lead to new discoveries that expand our understanding of the natural world (this study that increased the number of sequenced viral genomes by nearly tenfold is a good example of this). But what fishing expeditions can show is limited. These types of studies can lead to other studies but they do not show causality. Shaw is claiming causality with his fishing expedition here.

There is also the problem that they used old literature to select their gene targets when much more recent research has been done. By happenstance, they did measure some of these same genes in their study. However, their results do not match has has been measured in children that have been diagnosed with autism. For example, RANTES was shown to be decreased in children with autism. In Shaw’s work there was no statistical difference in RANTES expression between mice given the aluminum treatment and those receiving saline. Likewise, MIP1alpha  was shown to be decreased in developmentally delayed children but was shown to be increased in the aluminum treated mice. This was also the case for ILIb which was found to be elevated in children with moderate autism yet there was no statistical difference between the mice receiving the aluminum treatment and those receiving saline. In fact IL-4 was the only gene to follow an expression pattern similar to what was found in children with severe autism (elevated in both cases). However, there is something odd with the gel in this case. This was the image for figure 4 that was included in the online version of the paper (we have not altered the image in any way). Look closely at the top right panel at the IL-4 samples and the IL-6 samples. You’ll notice that the bands for the control and the aluminum treated mice have different color backgrounds (We enlarged the image to help highlight this but did not adjust the contrast). If these came from the same gel, there would not be a shift in color like this where the treated bands have a lighter color encircling them. The only way this could happen is if the gel was assembled in photoshop. The differences could be real; however, since this image was modified we do not know for sure and this is scientific misconduct. Papers get retracted for this all the time and people have lost their degrees for doing this in their dissertations. These gel results cannot be trusted and the paper hinges on them. The Western blots and issues with them will be discussed below.


The unaltered figure 4.


A close up of the panel with the regions in question highlighted.

Semi-quantitative RT-PCR:

In order to quantify the gene expression levels of the genes that Shaw’s group selected, they used an older technique called semi-quantitative RT-PCR. This technique uses the exponential increase in PCR products in order to show differences between expression of a gene under different conditions. There’s nothing wrong with the technique provided one understands what the limitations are. Let’s say you have a large number of genes that you want to measure expression of, but you aren’t sure which genes are going to be responsive and you have limited funds. Semi-quantitative RT-PCR is a good method to screen for specific genes to be examined further by more precise techniques, such as Real-Time RT-PCR, but it’s not appropriate to use this technique and then make statements about precise quantification. Where semi-quantitative RT-PCR excels is with genes that are normally not expressed but can be expressed after some sort of stimulus, such as terpene biosynthesis genes that are induced by insect feeding.

To put it bluntly, semi-quantitative RT-PCR was not used properly in the paper by Shaw. The way that it was used implied that it would be quantitative when the technique is not that precise. Without verification by another method, ideally Real-Time PCR which can determine what the exact abundance of a given target is, these results should be taken with a grain of salt. This would still be the case if there weren’t irregularities in the gel images. With those irregularities, this is absolutely essential and should have prevented this paper from being accepted.

Western-blots and data manipulationPCR and Western-blots data: the owl is not what it seems
As The Mad Virologist mentioned, the semi-quantitative PCR is an old-fashioned RNA quantitation method, with the use of Real-Time quantitative PCR (that quantifies the amplification product at each cycle, using a fluorescent dye as an indicator) is a much more accepted method nowadays (see his section for more details). For Western-blots, the semi-quantitative approach is more accepted but it is important to show data that are consistent between what you show (qualitative) from what you count (quantitative). In Western-blot analysis, we measure the relative darkness of a protein band (the black lines that you see in papers) between treatments and controls. Because you cannot exclude some errors due to the amount of protein loading, we also measure the band intensity for proteins that are very abundant, usually referred as housekeeping proteins (because they play essential functions in cells). In this case, beta-actin (named ACT in the paper was used).
Once you normalize to beta-actin, you can compare the effect of a treatment by comparing the relative band intensity ratios. In both cases (semi-quantitative PCR and Western-blots), “what you see is what you measure” or you have to show a “representative Western-blot” alongside a quantitative data to demonstrate that your quantification matches with band densities. The common practice is the use of image acquisition software like ImageJ to determine band density. Showing Western-blot is nice, but not foolproof. Indeed, Western-blots data (with fluorescence images) is amongst the most common method by which some researchers can manipulate or even falsify data but also the most common type of data that spark a paper retraction. Someone notice something fuzzy on a Western-blot data, creating some questioning reaching to the editors and asking access to the full dataset (usually the X-ray film or the original full scan of the blot). Often, the author will use the excuse “the dog ate the flash drive” or “the hard drive containing the data crashed” if they cannot provide such data.
There are some methods to spot some image manipulation on Western-Blots and include playing with the brightness/contrast, requesting the presence of quantitative data in addition of a representative blot, samples must be coming from a same gel (you cannot use a cookie-cutter and build-your-own perfect gel). There is an excellent article that describe the pitfalls and cases of bad Western-blot data representation if not image manipulation. (https://www.elsevier.com/editors-update/story/publishing-ethics/the-art-of-detecting-data-and-image-manipulationThere are, at this time, different issues raised both in the Western-blots pictures and their subsequent analysis raising the reliability of the data presented in this study.

In this post, we have used the full-resolution pictures provided by the journal website (http://www.sciencedirect.com/science/article/pii/S0162013417300417), opened just pictures in ImageJ to convert such pictures into 8-bit format, invert the lookup tables (LUT) and adjusted the brightness and contrast. We have exported such pictures in Powerpoint to ease the annotation and comments. We recommend the reader to judge by himself/herself and download the full-resolution images as well.

The first concern is by looking at Figure 1C. First, this is the original Fig.1.


Then, this is the close-up analysis for Fig.1C


There are several issues. First there are some bands that appears as band splicings, in which the author create a custom blots by assembling different bands from different gels. This is a no-no in Western-blots: all bands showed in a blot should come from the same gel. This is why Western-blot is a torture for graduates students and postdocs, you need to show your best blot with all bands showing the same behavior for your quantitative analysis.
Second, the presence of a rectangular grey piece that was added on the top of control 3 TNF band. This is a possible data manipulation and fraud, as you are voluntary masking a band and hiding it. Thats a big red flag on the paper. The third issue of Fig.1C is the consistent feeling of seeing bands either cropped on a grey rectangle or what I call a “Photoshop brushing” in which you brush off using the brush function area of the gel you consider not looking good enough. You can clearly see it with actin as we have a clear line between the blurred blot and a sharp and uniform grey in the bottom half of the blot, compared to the wavy top of the blot. This a grey area that I am not familiar with Western-blot but this is a no-no for any immunofluorescence picture. Any image manipulation that goes beyond the brightness/contrast adjustment and involves alteration of the acquired picture is considered as data manipulation. If you analyze the data upon correcting for the inconsistency of Figure 1C, the graph looks much more different and failed to show any differences between Al-treated and control, when you restrict yourself in over-normalizing it and plot straight the protein/actin band density ratios.

What is also concerning and surprising is the conclusion from the authors that males, not females, showing an inflammatory response. Of course, the authors failed to show the same outcomes from female animals and expect us to trust them on this. The problem is that such conclusion is in direct contradiction with the literature. There is a solid literature supporting the presence of a sexual dimorphism in terms of inflammatory response, in particular in terms of neuroinflammation and autoimmune disorders such as multiple sclerosis (https://www.ncbi.nlm.nih.gov/pubmed/28647490; https://www.ncbi.nlm.nih.gov/pubmed/27870415). There is also a growing call to the scientific community to provide results for both sexes (males and females alike). Although Shaw reports the study was performed in both males and females, he gives us this explanation at the end of section 3.1: Taken together, a number of changes indicative of the activation of the immune-mediated NF-κB pathway were observed in both male and female mice brains as a result of Al-injection, although females seemed to be less susceptible than males as fewer genes were found altered in female brains.

Yet the interesting part comes when Shaw try to compare ikB phosphorylation between males and females following Al injection (Fig.3C). When you analyze the data, you are raising concerns very rapidly. First, we have a possible case of cookie-cutter band in which you just paste a band that seems nice enough in a blank space. This is a very suspicious activity as you can make up data as easy as this. Second, there is again this “Photoshopping brushing/erasing” taking place in that figure, in which I suspect a case of fraudulent activity. As you can see in female, it is as if someone tried to mask some bands that should not have been here. Remember when he said that males but not females showed an inflammatory response? Is it trying to dissimulate data that contradict his claims?


Again, lets bring up Figure 3 at its full resolution.

Finally, the same issues are persistent and even more obvious in Fig.5A. Again, we have a mixture of different Western-blots image manipulations including bands splicing, Photoshop brushing, cookie-cutter bands……

First, the unedited picture:

And below the close up of Fig.5A


These are some serious concerns that raise the credbility of this study and can only be addressed by providing a full-resolution (300dpi) of the original blots (X-ray films or the original picture file generated by the gel acquisition camera).  There has been a lot of chatter on PubPeer discussing this paper and many duplicated bands and other irregularities have been identified by the users there. If anyone is unsure of how accurate the results are, we strongly suggest looking at what has been identified on PubPeer as it suggests that the results are not entirely accurate and until the original gels and Western blots have been provided, it looks like the results were manufactured in Photoshop.


Long time followers know that I tend to go right to the statistics that are used in papers to see if what they are claiming is reasonable or not. Poor use of statistics has been the downfall of many scientists, even if they are making honest mistakes. It’s a common problem that scientists have to be wary of. One easy solution is to consult with a statistician before submitting a paper for publication. These experts can help point out if the statistical tests that were run are the correct or not. The Shaw paper could have benefited from this expertise. They used a Student’s T Test for all of their statistics comparing the control to the aluminum treated. This is problematic for a couple of reasons. These aren’t independent tests and the data likely does not have a normal distribution, so a T Test isn’t appropriate. Better statistical tests would have been either Hotelling’s T-squared distribution or Tukey’s HSD.  Another issue is how the authors used standard error (SE) instead of standard deviation (SD). To understand why this matters, it helps to understand what the SE and what the SD measure and what these statistics show. The SD measures the variation in samples and how far the measurements are from the mean of the measurements. A smaller SD means that there is low variability in the measurements. The SE measures the likelihood that a measurement varies from the mean of the measurements within a population. Both the SE and SD can be used; however, using the SE is not always appropriate, especially if you are trying to use it as a descriptive statistic (in other words if you are trying to summarize data). Simply put, the SE is an estimation and only shows the variation between the sample mean and the population mean. If you are trying to show descriptive statistics, then you need to use the SD. The misuse of SE when the SD needs to be shown is a common mistake in many research publications. In fact, this is what the GraphPad manual has to say about when to use the SD and when to use the SE:

If you want to create persuasive propaganda:
If your goal is to emphasize small and unimportant differences in your data, show your error bars as SEM,  and hope that your readers think they are SD. If our goal is to cover-up large differences, show the error bars as the standard deviations for the groups, and hope that your readers think they are a standard errors.” This approach was advocated by Steve Simon in his excellent weblog. Of course he meant it as a joke. If you don’t understand the joke, review  the differences between SD and SEM.” The bottom line is that there is an appropriate time to use the SE but not when you are trying to summarize data.

Another issue is the number of animals used in the study. A consensus in published study is to provide a minimal number of animals (usually n=8) needed to achieve statistical significance but also maintain to a minimum to ensure proper welfare and humane consideration for lab animals. In this study, such number is half (n=5). Also the authors are bringing some confusion by blurring the lines between biological replicates (n=5) and technical replicates (n=3). By definition, biological replicates are different organisms that are measured and are essential for statistical analysis as these replicates are independent from each other. Technical replicates are dependent on each other as they come from the same biological samples and are repeated measurements. By considering the latter as statistical relevant, you are biasing yourself to consider a fluke as a biological phenomenon.


Based on the methods that were used in this paper, Shaw et al. went too far in declaring that aluminum adjuvants cause autism. But there are six other key points that limit what conclusions can be drawn from this paper:
1) They selected genes based on old literature and ignored newer publications.
2) The method for PCR quantification is imprecise and cannot be used as an absolute quantification of expression of the selected genes.
3) They used inappropriate statistical tests that are more prone to giving significant results which is possibly why they were selected.
4) Their dosing regime for the mice makes assumptions on the development of mice that are not correct.
5) They gave the mice far more aluminum sooner than the vaccine schedule exposes children to.
6) There are irregularities in both the semi-quantitative RT-PCR and Western blot data that strongly suggests that these images were fabricated. This is probably the most damning thing about the paper. If the data were manipulated and images fabricated, then the paper needs to be retracted and UBC needs to do an investigation into research misconduct by the Shaw lab.

Maybe there’s a benign explanation for the irregularities that we’ve observed, but until these concerns are addressed this paper cannot be trusted.


[BBB/Junk Sciences] Polysorbate 80 and the BBB or how to put anti-vaxxers into a blowing cognitive dissonance

Here we go again, anti-vaxxers keeping on moving the goalpost to fit their belief instead to change to adjust it to the facts. First it was mercury, then it was formaldehyde, then aluminum, today the “ingredient du jour” is polysorbate 80 and tomorrow they will blame it to PBS saline solution.

The latest fad as I have seen is to blame polysorbate 80 as a source of “vaccine-injury” with the bold claim that it breaks down the blood-brain barrier (BBB). Lets put the fact straight and debunk this one for all. But what is even better is the “what if” counter-argument. What if polysorbate 80 was indeed a good ingredient? I will come to that later.

Polysorbate (aka Tween 80) is a amphiphile compound   as you can see the molecular structure below (source Wikipedia):

You can see the structure made of a lipophilic (loves fat) tail and a series of hydrophilic  (loves water) tails, loaded with oxygen and hydroxyl groups. This is a typical structure of a detergent: one side will mix well with water, the other will mix very well with fat and oils. The result? You can form microspheres that can dissolve well in water and dissolve fat into water. This is how a detergent works, it helps to breakdown fats into small spheres and dissolve them in the drain water.
Polysorbate 80, due to this property, is very good to dissolve drugs and medicines that under normal condition would barely dissolve into biological fluids. This is why we have it in vaccines, but we also have it in medicines. Thats the job of biopharmaceutics: finding formulations to dissolve drugs into the body and allow them to reach a concentration high enough to display their therapeutic activity.

The use of polysorbate 80 in drug delivery of anti-cancerous drug is probably the first and foremost main driving factor on investigating its effect on the BBB. Brain tumors (primary and metastatic alike) are up until now one of the most dreaded and deadliest form of cancer. For instance, the average expected lifespan upon diagnosis of a grade IV glioma (aka glioblastoma multiforme) is grim: 18-months, with less than 5% survival after 5 years. The major issue is being able to deliver drugs and chemotherapy across the BBB. As reported by Pr. William Partridge (UCLA) the BBB remains the bottleneck in drug development for the treating neurological disorders (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC539316/?fref=gc&dti=873247819461536)

The first report of the investigation of polysorbate 80 on the BBB is probably by Spiegelman and colleagues in 1984 (http://thejns.org/doi/pdf/10.3171/jns.1984.61.4.0674), investigating the effect of the solvent used in etoposide solution for treating cancer. According to their  result, they noted a statistical difference in the BBB permeability  (using Evans Blue and 99mTc as tracers) following the injection of 1.125ml/kg. According to their paper, 5mL solution contained 400mg of polysorbate 80 or a concentration of 80mg/mL. Based on this, we can assume that the BBB effect was observed for a dose of 90mg/kg. Thats a very huge dose.
If we go back to the manure anti-vaxxers say, the amount injected via vaccines is enough to cause a barrier opening. According to John Hopkins University Institute of Vaccine Safety (http://www.vaccinesafety.edu/components-DTaP.htm), the expected concentration of polysorbate is lesser or equal to 100mcg or micrograms. Thats 0.1mg per dose. If we assume such dose is injected to a newborn (average weight ~3 kgs), then the amount injected is about 0.033mg/kg. Thats 2700 times less than what has been reported to induce a BBB disruption. Also you have to factor the bioavailability of polysorbate (that is 100% upon IV route) making this number a very optimistic number.
Now, the interesting twist about polsyorbate 80 is its use to enhance some drug carriers and its widely used for finding novel formulation to enhance the delivery of anti-cancerous drugs across the BBB. You can find a list of publications on Pubmed about that aspect (https://www.ncbi.nlm.nih.gov/pubmed/?term=polysorbate+80+blood-brain+barrier). What if polysorbate 80 not only will not injure your brain, but actually may help deliver drugs to help your brain fight disease?


Keep in mind that polysorbate 80 is good at dissolving lipid in water solutions but it is not good to let charged molecules accross the BBB, just in case someone comes with the claims that it conjugates with aluminum. Thats some high-school chemistry level.



[Sciences/Neurosciences] International/European Society of Neurochemistry (ISN-ESN) Meeting 2017 – Paris (France). A summary

Today is the last day of the ISN-ESN biannual meeting taking place this year in Paris (France). The venue was taking place at the Palais Des Congres near Porte Maillot (right on the periphery of Paris). I thought it was a great place for the venue, first by its location (excentered from inner Paris, giving more affordable options for lodging), but also by hosting a shopping mall in the basement level (with affordable lunch options including a Galeries Gourmandes and a Paul Patisserie). Another special perk was the presence of complimentary coffee during the morning and afternoon session breaks.
The presence of vendors was fairly minimal but the welcome package provided by ISN was fairly nice. It included:

A mug of your choice (I took molecular basis of disease of course),

And a set of 10 RATP tickets allowing you to wander inside Paris when the urge of sightseeing overcomes your thirst of science:

This is a first time I am attending a ISN meeting, following the acceptance of my paper by the Journal of Neurochemistry. It is a small conference (maybe 500 attendees, this is a high estimate) but it does not mean the quality of science was small too. The conference was taking place on four full days (21-24 August) with morning plenary lectures including a senior keynote speaker and a junior keynote speaker, followed by two breakout sessions (one morning, one afternoon) covering different topics including development, gene and genetics, synapses and neurotransmission, molecular basis of diseases, neurodegeneration or cell energetics.

One of the nice thing was this huge crowd-sourced timeline in which attendees could fill it with stickers indicating their first publication in Journal of Neurochemistry, their first enrollment in one of the different societies.

Interesting fact, the first ISN took place in Strasbourg (my hometown) in 1967 and 50 years later, one attendee was still attending the same ISN meeting! Hail to the elders!


Senior keynote lectures were very instructive including a keynote lecture by Pr. Tamas Horvath (Yale University, USA) on the selective depletion of Agouti-gene related protein neurons and its impact on feeding behavior. These neurons are present are very few numbers (3000-6000) but play important role in feeding. The take home message? Resistance (to chocolate cake) is futile!
Another interesting keynote lecture was from Pr. Yoshi Hirabayashi (RIKEN, Japan) on glycolipids, their known impact on Gaucher’s disease and more interestingly their contribution into Parkinson’s disease. One slide to highlight the complexity of the topic is this one summarizing the different types of glycosphingolipids present in mammalian brains. Yes, this will be part of your next biochemistry quiz.

Finally, todays senior keynote lecture by Pr. Giovanna Malluci (Cambridge University, UK) on the importance of unfolded-protein response stress and its contribution to several neurodegenerative diseases (in particular on prion diseases), with the importance of elongation factor 2E (elF2E) as a rescue pathway in neurodegeneration. More interestingly was the description in the second part of the cold-shock response and the contribution of RBM3 as a neuroprotective agent. I was aware of the importance of cold in hypoxia tolerance (drowning in frigid water decreases the gravity of brain injury inflicted by hypoxia compared to warm water) but I was always skeptical on the use of cooling blanket on stroke patients to cool their body down. It seems there is some vestigial molecular pathways initially used in evolutionary adaptation in hibernating animals that maybe still present in non-hibernating animals via RBM3. It would be interesting to see how this pathway cross-talk with the HIF-1 pathway.

Other concurrent sessions were interesting including one on transporters in the CNS (especially one on glutathione handling in astrocytes through MRPs), the importance of TDP-43 in ALS and other diseases, SIRT6 and its importance in neurodegenerative (including the possible involvement of Wnt and HIF-1 pathways), mitochondria bioenergetics and the discussion and debate on mitochondria movements in astrocytes and neurons (with even the discussion on Eng Lo’s paper on mitochondria transfer following stroke injury) or novel aspects of neural development and neurogenesis.

The poster sessions were well designed with the exception of the manned poster sessions. Poster sessions were initially scheduled between the morning and afternoon concurrent sessions but the presence of poster authors was requested only during the evening socials after 6:00PM. By principle, I am done with science by 5:00PM if I have been bathing in since the morning, so I ended up seeing a lot of “empty” posters and wished I could have a chance to chat and talk to the poster authors. I think this is were SfN poster session is more adapted: you have half-day to showcase your poster and have a time period (2 hours) to stand next your poster. Maybe the organizers could take this into account for ISN2019 taking place in Montreal.

Finally, the ISN see themselves through the Neurochemistry consortium as funny people and hell yeah they know how to bring fun with a complimentary funny photomaton booth. Another opportunity for me to let the weird and funny coming out of me 🙂

See you in probably the ASN meeting 2018 in Riverside, CA and ISN2019 in Montreal (Quebec, Canada)!


[Sciences/Junk Sciences] Remember the deadly turmeric IV infusion done in a holistic clinic? Lessons from the FDA report

You have remember this story of this young woman that died shortly after recieving an IV infusion of turmeric acid (aka curcumin, a bioactive compound found in Curcuma) in a holistic clinic in California few months ago (http://www.10news.com/news/team-10/encinitas-woman-dead-after-i-v-infusion-of-turmeric).
This story baffled me for many reasons. First, it was really puzzling me on how quack medicine (rebranding itself as “holistic” and “integrative” to appear more sciencey) have been moving slowly but surely into medical procedures normally held by medical staff, with some dubious claims of “IV therapy” in which the onset of an IV line and pumping up vitamins straight into your systemic circulation will help you “detox” or “rejunevate”.
Second, how turmeric acid that have been bounced by some “health/food gurus” as superfood (move on kale and quinoa, you are so 2015!) quickly moved on as therapeutics without even having the right science to back it up (until now only preclinical studies done in cells grown on Petri dishes and in rodents), with the glittery “cures-it-all” sticker all over it.
You see, turmeric acid is way far from being the next wonder drug as sold by woo peddlers. Why? Lets see some of its features (https://pubchem.ncbi.nlm.nih.gov/compound/curcumin#section=Top).
First thing, turmeric acid has a problem. A huge problem. This problem is solubility. It has a calculated xLogP of 3.2, this is already telling us this compounds is lipophilic (likes fat). It will dissolve well in oil, but not well in water (less than 0.1mg/mL according to Santa Cruz Biotechnology data sheet). If you try to go beyond that value, you will have a saturated solution with turmeric acid precipitates. These precipitates can have serious effect if injected into an IV line, if these particles are big enough to clog some capillaries.
You can circumvent things around by tweaking nanoparticles carriers. Still, even from food intake, turmeric has a very low bioavailability. From 100g of pure turmeric acid swallowed, only 1g will effectively reach the circulation and circulate through your body.
The second problem with turmeric is its pharmacokinetic profile. According to the reference cited by the FDA report, turmeric is highly unstable at physiological pH (7.4). According to this review, the elimination half-life (t1/2) for turmeric is very low (1.7+/-0.5h). By 6 hours, most of the turmeric injected via IV route will be gone. Therefore, if turmeric was considering for therapeutic, it would require multiple dosing that are either ridiculous (Dosing interval of about ~2 hours, therefore swallowing a pill every two hours) or being on a constant IV infusion (that is not realistic for everyday life).
Third problem with turmeric? Its pharmacological activity. Two important parameters have to be accounted for a drug candidate: its selectivity (does the drug targets one or several proteins?) and IC50 (what is the concentration needed to achieve 50% inhibition).
The problem with turmeric is that it is considered as a “dirty” molecule because it hits a bit of everything, with many signaling pathways affected by it. The second problem is its very high IC50. Anti-cancerous activity of turmeric swings around 10microM in various cancer cell lines in a Petri dish and have other targets at higher doses. This is not a horrible value, not a good value either. Usually we want to reach an IC50 in the nanoM range (10’000 less concentration than 10µM). Thats not the case for turmeric. Maybe by tweaking the chemical structure we may improve its IC50, but since the compound itself has so many targets trying to optimize it for therapeutic purposes maybe simply a waste of time.
If we stick to the 10µM concentration and an average molecular weight of 328g.mol-1 for turmeric, we need a concentration of 3mg/L or (0.003mg/mL) to expect some biological activity. Now the problems come in with the FDA report. There are two reported cases of adverse events, including the fatal cases. In both cases, patient had an IV line of turmeric acid. In both cases, both patients were mentioned an IV infusion of turmeric acid at 10mg/mL. First, this concentration would have made no sense. It is 300 times higher than the hypothetical dose needed to achieve a biological activity in vivo. Second, the final concentration in the IV bag was much less than this concentration, as the FDA reported only 1% of the prescribed concentration was found in the IV bag (0.00235mg/mL).
Someone has been not only been deceiving their customers by selling you less product than advertised (1% net content is honestly a huge rip-off) but also had absolutely no clues on what they were injecting. So we can blame two actors: either the compounding company that prepared the turmeric or the holistic clinic (I guess you can point who is the crook in the story).
Both cases involved ImprimisRX, a compounding pharmacy. These are laboratories under the responsibility of a pharmacist holding a specialization in compounding. He or she has to follow established rules and protocols, adhere to good manufacturing procedures in compliance with the FDA. It seems there is no wrongdoing from the compounding. The compounding produced an emulsified form of turmeric (to increase its solubility). Yet, the final concentration in the vial was about 0.205mg/mL or about 2% of the amount put on the label. Since turmeric is highly unstable under aqueous solution (even in its emulsified form) we cannot exclude a degradation of the product from the time it got compounded to the time it was administered. In aqueous protein-free solution, 90% of turmeric acid is degraded within 30 minutes (https://www.fda.gov/downloads/AdvisoryCommittees/CommitteesMeetingMaterials/Drugs/PharmacyCompoundingAdvisoryCommittee/UCM466380.pdf).
Now comes an another problem: was there any deception between ImprimisRX and the holistic clinic? One of the reason is the use of polyethylene glycol 40 (PEG40) castor oil in the compounding process. PEG40 may contain traces of diethylene glycol (DEG), a very well known toxic compound if ingested, with a toxicity of about 1mg/kg. DEG is a byproduct of PEG production, therefore the FDA has different quality grades of PEG whether it is destined for non-medical usage or for human consumption. DEG was found at a concentration of 0.21% (0.21g pure DEG in 100g of PEG40). The PEG40 used for the compounding was 1.25% with the clear label “CAUTION: For manufacturing or laboratory use only.” Why the compounding pharmacy used that ungraded PEG40? We don’t know yet.
PEG40 oils are used for cosmetics and considered safe for cosmetics usage  because the bioavailability of this compound is small and suited for topical application (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4505343/). But you have to remember that a product that is considered safe in an administration mode is not in another administration route. This is probably explaining the adverse effect observed.
The second possible issues is a possible allergic reaction to PEG40, as the FDA cited previous reports of allergic reactions of patients exposed to PEG formulations following IV infusion of anti-cancerous agents.
By now, your enthusiasm for cur turmeric should (rightly) wind down. Turmeric is certainly great for spicing your food, not much for your health. But most of all, don’t let a “holistic clinic” perform any type of IV infusion.
IV infusion is a very delicate procedure, used for restricted applications (chemotherapy, anesthesia, infectious disease……) by a trained personnel in a medical environment (hospital or medical clinic).

[Sciences/Junk Sciences] How the recent AHA recommendation on coconut oil is making many getting nuts (and why coconut oil is not an healthy choice)!

Coconut oil. Coconut oil. Yep, that same coconut oil that (almost) nobody knew about a couple of years ago and suddenly became the next big thing in fad diets. Some claimed it is healthier than vegetable oil (http://pilatesnutritionist.com/why-coconut-oil-is-better-than-vegetable-oil/; which turned out is not true), other claimed it can help you loose weight (https://authoritynutrition.com/coconut-oil-and-weight-loss/; that is also hard to imagine how to loose fat by keeping an high-fat diet) or even use it as a natural sunscreen (http://thecoconutmama.com/coconut-oil-sunscreen/; which of course will more likely help you roast like a rotisserie chicken).
You see the fad went a bit crazy with the habitual “wellness” bloggers making miraculous claim. The fact is coconut oil is no better than any oil and indeed maybe as bad as any saturated fats.
The only thing that I would say coconut oil is good, is giving you some tasty and crunchy fries that are not too greasy. Any French household know the “Vegetaline” brand (basically solid coconut oil that you mix with half sunflower oil to get a frying oil).

What is (in terms of chemical composition) coconut oil?

Coconut oil is extracted from the inner side of the coconut. It is also called copra oil. Some coconut oil are referred as “organic coconut oil” and even some referring as GMO-free coconut oil (you know the GMO-free project sticker that have no sense except operating as a form of racketeering? There are been never any GM-coconuts that hit the market. http://www.zebraorganics.com/organic-virgin-raw-coconut-oil-1-gallon-tub-zebra-organics.html?gclid=Cj0KEQjwyZjKBRDu–WG9ayT_ZEBEiQApZBFuK3KbEfSPhyNyx9z9eNUIwAmd6OwcxTWJUYKADA_fhEaAnvd8P8HAQ). Therefore, we consider all coconut oil equals (maybe slight variations between cultivars but this should not affect much the overall composition to be considered significant).

Before we discuss about the composition of coconut oil, it is important to know what a fatty acid is. Fatty acids (FA) are hydrocarbon chains (made of carbons and hydrogens) that are very similar to molecules belonging to alkanes (these are the molecules such as propane, butane and octane that are present in your propane gas tank right now fueling your grill, fueling your gas stove or fueling your SUV).
In contrast to alkanes, FA have a carboxyl (-COOH) “head” denominated and seen below:

We have two type of FA: saturated FAs (fully loaded with hydrogens) and unsaturated FAs (that have one or several C=C double bounds). Saturated FAs are usually found in fat products from animal origin (lard, butter, ghee…) whereas unsaturated FAs are usually found in plants (olive, rapseed/canola, corn, sunflower…) and in fish and seafood (usually polyunsaturated fatty acids or PUFAs aka omega- fatty acids). Unsaturated FAs either show a cis-form (like the oleic acid depicted, in which the two carbon branches are in the same side) or a trans-form (in which the two pieces of the carbon branches are opposing each other). Trans unsaturated FAs (aka trans-fats) have been already a bad rep because of their detrimental effects on the cardiovascular system (they are suspected to increase LDL levels which are known to contribute in the atherosclerotic plaques formation). Saturated FAs are also having a bad rep because they are also associated with increased risk of cardiovascular diseases, whereas unsaturated FAs (commonly found in “the Mediterranean diet”) are considered healthier.
FAs composition are usually denominated as the following: Cn:m with n referring to the number of carbons (usually an even number), m referring to the number of C=C. In our cases, stearic and oleic acid share the same number of carbon (C18) but the former has no C=C bounds (C18:0) and the latter has a C=C bound (C18:1).
Based on this table, you can see how coconut oil fares to other oils (https://www.chempro.in/fattyacid.htm)
It contains 90% of saturated FAs and 10% unsaturated FAs, whereas most of other oils commonly used in Western countries have at least 50% or more of unsaturated FAs. To give you an idea lard, tallow (beef) and butter contains 40%, 37% and 41% respectively.  You can see how coconut oil is exploding the chart.

But, but this is coming from one study and science has been wrong all the time

If you stick to mainstream media, you will get this impression right. News outlets like to sell single studies as sold and irrefutable evidence and often oversell the claims of that study. Science is never settled, especially on a single study. Many things can go wrong that result in bias. Sometimes, scientists even cut the corners and publish fraudulent data to support their claims (thats what you see a lot with anti-vaccines, anti-GMO papers, climate-deniers, creationism……).
Science build a consensus on the amount of publications and their robustness in their experimental design. When you have an overwhelming majority of papers show you a same trend, arrive to same conclusion on a phenomenon using different approaches and different observations by different groups, you reach a conclusion and set a consensus.
A consensus is only broken once you have new studies that refute the existing claims with more robust and more precise data than the existing literature. This happens very rarely as you have to being in a weight of evidence bigger than the existing literature.

The science on FAs and their effect on cardiovascular diseases is not new, this have been known for over 50 years and keep refining. This consensus built on the detrimental effects of high-fat diet is well-known and served to establish guidelines and public health recommendations. The American Heart Association, the leading association worldwide gathering both basic and clinical scientists as well as any healthcare actors establish guidelines.

The AHA has a clear statement, visible here:
Replacing saturated fats may help to reduce your risk of cardiovascular events, in addition to an healthy (balanced) diet and physical activity.

The study that made the uproar is available here and comes from the scientific board of the AHA. You can download it for free and you can see another fat composition of different oils:

As you can see, coconut oil tops the list of saturated oils and fats, followed by butter and lard. Saturated fats consumption are clearly associated with increased risk of coronary heart diseases (CHD, aka heart attack), replacement with unsaturated fats reduce such risks. Replacement with PUFAs appears even more beneficial. Such effects is not limited to CHDs, but appears involved in other diseases as well (see Figure 4).

In conclusion, dont ditch your coconut oil yet. As small amount, coconut oil is fine. What is not fine was the fad diet that was basically pushing you to switch everything to coconut oil. In my personal opinion, I would say that butter (real unsalted butter like the French “President”, Irish “Kerrygold” or Danish “Lupak” butters; not the things called margarines that were at the basis of the trans-fat problem),  was even a better alternative  than coconut oil.

In conclusion, keep your peanut oil for your deep-frying cooking, keep your canola oil for your dressings and use olive oil for cooking instead of lard and coconut oil. If the taste of coconut oil is good, just add the minimal amount needed to taste.


[Sciences/BBB] Endothelial TLR4 and the microbiome drive cerebral cavernous malformations (Tang et al., Nature 2017)

You may have heard about this study that showed how your gut bacteria were responsible for stroke. Of course headline news always love to stretch scientific findings as much as I use to stretch my Stretch Armstrong when I was a kid. However, the paper cited was indeed published in Nature and can be found here:

It is a very interesting paper to read, because a lot of it sounds like a serendipity and lucky strikes. This paper investigated changes in two mouse models of cerebral cavernoma (Ccms). Ccms are a particular type of hemorrhagic stroke because they are mostly genetics (there are three Ccm genes described, in this study they focused on Krit1 and Ccm2) and most of the time go unnoticed. Mutations in those genes result in some alterations in brain microvessels, making some tiny anatomical abnormalities resulting in a higher susceptibility in some of these micro vessels to spontaneously burst and bleed.

The authors of this study have been developing Cre/Lox mice colonies for Ccm2 and Krit1 to better understand the pathology of this disease. The advantage of Cre/Lox is you can knockout a gene in a specific place at a specific time, just by injecting or providing a molecule (usually tamoxifen) that will induce it.

They have been breeding mice that were deficient in Ccm2 or Krit1 and were as expected developing brain micro bleeds (usually around their first two weeks of postnatal age). Following some changes in the animal facility, they observed that a small fraction of their mice colonies suddenly became resistant to cerebral micro bleeds: they still carried the mutations but they fail to develop these microbleeds. Therefore some non-genetic factors were influencing this resistance pattern.
Things became even more interesting as they found that among some of these resistant mice, some developed again the microbleeds within a same littler. The only difference between those developing the microbleeds and those which did not were apparently related to the intraperitoneal (i.p.) injection of tamoxifen. Have the authors provided the tamoxifen through the drinking water, that would have ended the story here.
The authors indeed found that those who reversed their phenotype from resistant to susceptible developed a bacterial infection at the site of the i.p. injection suggesting that such micro bleed was driven by some bacterial factor. They showed that similar results were obtained if they injected LPS (a common Gram-negative antigen) to these mice.

They identified two receptors known to play a role in cellular response to pathogens (we refer such signaling pathways as Pathogen Associated Molecular Patterns or PAMPs): TLR4 (toll-like receptor 4) and CD14 (TLR4 co-receptor). By knocking down these receptors in their Ccm-resistant animals, they were capable to block such bacteria-induced response. The possible interactions of Gram-negative bacteria with these two receptors at the blood-brain barrier maybe enough to trigger the cerebral micro bleeds.

What is also interesting is that mutations in these two genes (some single nucleotide polymorphism or SNP) in patients known to have an history of Ccm also resulted in a higher probability to have brain microbleeds.

I will not spoil the rest of the story but it confirms the presence of a brain-gut axis in Ccm, suggesting the possible effect of the gut microbiota as a risk factor to increased microbleeds in Ccm patients. Let it be clear, these bacteria WILL NOT induce Ccm in normal invididuals. It increase the risk of bleeds in patients already at risk of Ccm.

Another limitation is that in vitro data to confirm the presence of TLR4/CD14 at the BBB and fails to explain how these receptors are triggered by the gut microbiota. The authors suggested a bacteremia (circulating bacteria from gut to the brain via bloodstream) but I remain skeptical about it.

Nevertheless it is a very good paper that worth being read.


[Science/Neurosciences] Mole rats running on…..fructose!

You may have heard about this paper from Park TJ and colleagues (Park TJ et al., Science 2017) on how mole rats were showing extreme compliance to anoxic (0% oxygen) level, no? It made the news these last couple of weeks and finally was able to put my hand on. You can access to it here (need to have a Science subscription though) but I read it and it is really interesting for many reasons, especially because I try to think how can we translate it as a therapeutical strategies for hypoxemic pre-terms babies or even as a stroke fighting-drug.

First, mole rats. Oh mole rats! Not the prettiest mammals out there. They are naked, they have long teeth and look all wrinkled. But they are underground dwelling animals like moles. Underneath, oxygenation is scarce and these animals have developed formidable adaption to hypoxia. We as humans can barely survive 8% oxygen (thats about the Mount Everest). At 6% oxygen (thats what would happen if a aircraft cabin undergo a depressurization), you die within minutes.

In this experiment, they went fairly extreme, they put the animals into anoxia (0% O2) and looked how long the animals would survive. They used a common mouse strain as a control. Mice rapidly died at 100% rate at 5% O2 and died twice faster (based on the number of breaths) at 0% O2. In opposite, mole rats went 30 times longer than mice and still were doing fine (0% deaths). Were mice died within 60 seconds, molerats died over 1000 seconds of anoxia. One possible reason is their ability of their heart to beat much longer than mice.

Now what is interesting is how the authors came to fructose. Mammalian cells run on glucose through the following biochemical pathway (see below):


I will spare you the Krebs cycle but this is what every since healthcare and life scientist have to learn. Glucose is broken down into many intermediates and at the end becomes pyruvate. From pyruvate, you can enter the Krebs Cycle and produce a significant amount of ATP (the fuel cell of every living organism) needed to provide energy for any biological process. Krebs cycle is very good at it and provides an ATP yield of 36ATP/glucose consumed. However, the Krebs cycle stall under hypoxia and forces the cell to adapt. In particular, it needs to regenerate NAD+ (from NADH) in order to keep the system flowing and producing energy. One way mammalian cells solved it is by converting pyruvate into lactate. Thats allow cells to produce some energy (2ATP/glucose) and regenerate its NAD+. However lactate has tendency to accumulate and develop adverse effect (the famous muscle cramps any runners have experienced).

Fructose is not much different from glucose, it has the same composition but just a little difference in the molecular structure.  We get fructose from our daily diet made of fruits and vegetables, but also from refined sugar (sucrose or HFCS, same deal).


Now fructose can bypass and feed the glycolysis at different steps:

Fructose can produce glyceraldehyde-3-P (GA3P) and dihydroxyacetone-P (DHAP) and enter the rest of the glycolysis. Now like glucose, fructose needs a transporter to enter inside the cells. Glucose has a myriad of glucose transporters (GLUTs and SGLTs) that can provide glucose inside the cells. But not fructose. These transporters have very poor affinity for fructose. In that case, fructose has one transporter called GLUT5 that prefers fructose over glucose.
Now this is where it becomes interesting, mole rats show much higher levels of fructose than mice during anoxia in many organs and in blood. Now the interesting fact is the high prevalence of it as fructose-1-P in the brain, only this form. How it goes in? I don’t know but mole rat brains have a higher GLUT5 expression than mice. Where this transporter is expressed? I don’t know either but it would interesting to look at this transporter at the BBB.

What is interesting is the difference in how mole rats  brain and heart differ from mice in terms of fructose activity. When administered fructose over glucose, mole rats organs know to switch between the two sugars to gets its energy. In the other hand, mice organs fail to switch and result in decrease their activity.

Now the question I have (since I am working on glucose transport across the BBB and its impact in kids suffering from GLUT1 deficiency) is: does human express GLUT5? If yes, which brain cells express it and if these cells can adopt fructose as a source of energy?