Cats and uncontrollable bursts of rage in humans

 

That many domestic cats carry the parasite Toxoplasma gondii is no news. Nor is the fact that 30-50% of the global population is infected with it, mainly as a result of contact with cat feces.

The news is that individuals with toxoplasmosis are a lot more likely to have episodes of uncontrollable rage. It was previously known that toxoplasmosis is associated with some psychological disturbances, like personality changes or cognitive impairments. In this new longitudinal study (that means a study that spanned more than a decade) published three days ago, Coccaro et al. (2016) tested 358 adults with or without psychiatric disorders for toxoplasmosis. They also submitted the subjects to a battery of psychological tests for anxiety, impulsivity, aggression, depression, and suicidal behavior.

The results showed that the all the subjects who were infected with T. gondii had higher scores on aggression, regardless of their mental status. Among the people with toxoplasmosis, the aggression scores were highest in the patients previously diagnosed with intermittent explosive disorder,

 

a little lower in patients with non-aggressive psychiatric disorders, and finally lower (but still significantly higher than non-infected people) in healthy people.

The authors are adamant in pointing out that this is a correlational study, therefore no causality direction can be inferred. So don’t kick out you felines just yet. However, as CDC points out, a little more care when changing the cat litter or a little more vigorous washing of the kitchen counters would not hurt anybody and may protect against T. gondii infection.

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Reference: Coccaro EF, Lee R, Groer MW, Can A, Coussons-Read M, & Postolache TT (23 march 2016). Toxoplasma gondii Infection: Relationship With Aggression in Psychiatric Subjects. The Journal of Clinical Psychiatry, 77(3): 334-341. doi: 10.4088/JCP.14m09621. Article Abstract | FREE Full Text | The Guardian cover

By Neuronicus, 26 March 2016

Intracranial recordings in human orbitofrontal cortex

How is reward processed in the brain has been of great interest to neuroscience because of the relevance of pleasure (or lack of it) to a plethora of disorders, from addiction to depression. Among the cortical areas (that is the surface of the brain), the most involved structure in reward processing is the orbitofrontal cortex (OFC). Most of the knowledge about the human OFC comes from patients with lesions or from imaging studies. Now, for the first time, we have insights about how and when the OFC processes reward from a group of scientists that studied it up close and personal, by recording directly from those neurons in the living, awake, behaving human.

Li et al. (2016) gained access to six patients who had implanted electrodes to monitor their brain activity before they went into surgery for epilepsy. All patients’ epilepsy foci were elsewhere in the brain, so the authors figured the overall function of OFC is relatively intact.

While recording directly form the OFC the patients performed a probabilistic monetary reward task: on a screen, 5 visually different slot machine appeared and each machine had a different probability of winning 20 Euros (0% chances, 25%, 50%, 75% and 100%), fact that has not been told to the patients. The patients were asked to press a button if a particular slot machine is more likely to give money. Then they would use the slot machine and the outcome (win 20 or 0 Euros) would appear on the screen. The patients figured out quickly which slot machine is which, meaning they ‘guessed’ correctly the probability of being rewarded or not after only 1 to 4 trails (generally, learning is defined in behavioral studies as > 80% correct responses). The researchers also timed the patients during every part of the task.

Not surprisingly, the subjects spent more time deciding whether or not the 50% chance of winning slot machine was a winner or not than in all other 4 possibilities. In other words, the more riskier the choice, the slower the time reaction to make that choice.

The design of the task allowed the researchers to observe three 3 phases which were linked with 3 different signals in the OFC:

1) the expected value phase where the subjects saw the slot machine and made their judgement. The corresponding signal showed an increase in the neurons’ firing about 400 ms after the slot machine appeared on the screen in moth medial and lateral OFC.

2) the risk or uncertainty phase, when subjects where waiting for the slot machine to stop its spinners and show whether they won or not (1000-1500 ms). They called the risk phase because both medial and lateral OFC had the higher responses when there was presented the riskiest probability, i.e. 50% chance. Unexpectedly, the OFC did not distinguish between the winning and the non-wining outcomes at this phase.

3) the experienced value or outcome phase when the subjects found out whether they won or not. Only the lateral OFC responded during this phase, that is immediately upon finding if the action was rewarded or not.

For the professional interested in precise anatomy, the article provides a nicely detailed diagram with the locations of the electrodes in Fig. 6.

The paper is also covered for the neuroscientists’ interest (that is, is full of scientific jargon) by Kringelbach in the same Journal, a prominent neuroscientist mostly known for his work in affective neuroscience and OFC. One of the reasons I also covered this paper is that both its full text and Kringelbach’s commentary are behind a paywall, so I am giving you a preview of the paper in case you don’t have access to it.

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Reference: Li Y, Vanni-Mercier G, Isnard J, Mauguière F & Dreher J-C (1 Apr 2016, Epub 25 Jan 2016). The neural dynamics of reward value and risk coding in the human orbitofrontal cortex. Brain, 139(4):1295-1309. DOI: http://dx.doi.org/10.1093/brain/awv409. Article

By Neuronicus, 25 March 2016

Pic of the day: The most prevalent infection

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Reference: Flegr J, Prandota J, Sovickova M, Israili ZH (2014). Toxoplasmosis – A Global Threat. Correlation of Latent Toxoplasmosis with Specific Disease Burden in a Set of 88 Countries. PLoS ONE, 9(3): e90203. doi:10.1371/journal.pone.0090203. Article | FREE fulltext PDF

By Neuronicus, 22 March 2016

Now, isn’t that sweet?

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When I opened one of my social media pages today, I saw a message from a friend of mine which was urging people to not believe everything they read, particularly when it comes to issues like safety and health. Instead, one should go directly at the original research articles on a particular issue. In case the reader is not familiar with the scientific jargon, the message was accompanied by one of the many very useful links to blogs that teach a non-scientist how to cleverly read a scientific paper without any specific science training.

Needless to say, I had to spread the message, as I believe in it wholeheartedly. All good and well, but what happens when you encounter two research papers with drastically opposite views on the same topic? What do you do then? Who do you believe?

So I thought pertinent to tell you my short experience with one of these issues and see if we can find a way out of this conundrum. A few days ago, the British Chancellor of the Exchequer (the rough equivalent of a Secretary of the Treasury or Minister of Finance in other countries) announced the introduction of a new tax on sugary drinks: the more sugar a company puts in its drinks, the more taxes it would pay. In his speech announcing the law, Mr. George Osborne was saying that the reason for this law is that there is a positive association between sugar consumption and obesity, meaning the more sugar you eat, the fatter you get. Naturally, he did not cite any studies (he would be a really odd politician if he did so).

Therefore, I started looking for these studies. As a scientist, but not a specialist in nutrition, the first thing I did was searching for reviews on the association between sugar consumption and obesity on peer-reviewed databases (like the Nature journals, the US NIH Library of Medicine, and the Stanford Search Engine). My next step would have been skimming a handful of reviews and then look at their references and select some dozens or so of research papers and read those. But I didn’t get that far and here is why.

At first glance (that is, skimming about a hundred abstracts or so), it seems there are overwhelmingly more papers out there that say there is a positive correlation between sugar intake and obesity in both children and adults. But, when looking at reviews, there are plenty of reviews on both sides of the issue! Usually, the reviews tend to reflect the compounded data, that’s what they are for and that’s why is a good idea to start with a review on a subject, if one knows nothing about it. So this dissociation between research data and reviews seemed suspicious. Among the reviews in question, the ones that seemed more systematic than others are this one and this one, with obvious opposite conclusions.

And then, instead of going for the original research and leave the reviews alone, I did something I am trying like hell not to do: I looked the authors and their affiliations up. Those who follow my blog might have noticed that very rarely do I mention where the research has taken place and, except in the Reference section, I almost never mention the name of the journal where the research was published in the main body of the text. And I do this quite intentionally as I am trying – and urge the readers to do the same thing – to not judge the book by the cover. That is, not forming a priori expectations based on the fame/prestige (or lack thereof) of the institution or journal in which the research was conducted and published, respectively. Judge the work by its value, not by its authors; and this paid off many times during my career, as I have seen crappy-crappity-crap papers published in Nature or Science, bloopers of cosmic proportions coming from NASA (see arsenic-DNA incorporation), or really big names screwing up big time. On the other hand, I have seen some quite interesting work, admittedly rare, done in Thailand, Morocco or other countries not known for their expensive research facilities.

But even in research the old dictum “follow the money” is, unfortunately, valid. Because a quick search showed that most of the nay-sayers (i.e. sugar does not cause weight gain) were 1) from USA and 2) had been funded by the food and beverage industry. Luckily for everybody, enter the scene: Canada. Leave it for the Canadians to set things straight. In other words, a true rara avis poked its head amidst this controversy: a meta-review. Lo and behold – a review of reviews! Massougbodji et al. (2014) found all sorts of things, from the lack of consensus on the strength of the evidence on causality to the quality of these reviews. But the one finding that was interesting to me was:

“reviews funded by the industry were less likely to conclude that there was a strong association between sugar-sweetened beverages consumption and obesity/weight gain” (p. 1103).

In conclusion, I would add a morsel of advice to my friend’s message: in addition to looking up the original research on a topic, also look where the money funding that research is coming from. Money with no strings attached usually comes only from governments. Usually is the word, there may be exceptions, I am sure I am not well-versed in the behind-the-scenes money politics. But if you see Marlboro paying for “research” that says smoking is not causing lung cancer or the American Beverage Association funding studies to establish daily intake limits for high-fructose corn syrup, for sure you should cock an eyebrow before reading further.

Reference: Massougbodji J, Le Bodo Y, Fratu R, & De Wals P (2014). Reviews examining sugar-sweetened beverages and body weight: correlates of their quality and conclusions. The American Journal of Clinical Nutrition, 99:1096–1104. doi: 10.3945/ajcn.113.063776. Article | FREE PDF

By Neuronicus, 20 March 2016

Younger children in a grade are more likely to be diagnosed with ADHD

AHDH immaturity - Copy.jpgA few weeks ago I was drawing attention to the fact that some children diagnosed with ADHD do not have attention deficits. Instead, a natural propensity for seeking more stimulation may have led to overdiagnosing and overmedicating these kids.

Another reason for the dramatic increase in ADHD diagnosis over the past couple of decades may stem in the increasingly age-inappropriate demands that we place on children. Namely, children in the same grade can be as much as 1 year apart in chronological age, but at these young ages 1 year means quite a lot in terms of cognitive and behavioral development. So if we put a standard of expectations based on how the older children behave, then the younger children in the same grade would fall short of these standards simply because they are too immature to live up to them.

So what does the data say? Two studies, Morrow et al. (2012) and Chen et al. (2016) checked to see if the younger children in a given grade are more likely to be diagnosed with ADHD and/or medicated. The first study was conducted in almost 1 million Canadian children, aged 6-12 years and the second investigated almost 400,000 Taiwanese children, aged 4-17 years.

In Canada, the cut-off for starting school in Dec. 31. Which means that in the first grade, a child born in January is almost a year older that a child born in December. Morrow et al. (2012) concluded that the children born in December were significantly more likely to receive a diagnosis of ADHD than those born in January (30% more likely for boys and 70% for girls). Moreover, the children born in December were more likely to be given an ADHD medication prescription (41% more likely for boys and 77% for girls).

In Taiwan, the cut-off date for starting school in August 31. Similar to the Canadian study, Chen et al. (2016) found that the children born in August were more likely to be diagnosed with ADHD and receive ADHD medication than the children born in September.

Now let’s be clear on one thing: ADHD is no trivial matter. It is a real disorder. It’s an incredibly debilitating disease for both children and their parents. Impulsivity, inattention and hyperactivity are the hallmarks of almost every activity the child engages in, leading to very poor school performance (the majority cannot get a college degree) and hard family life, plus a lifetime of stigma that brings its own “gifts” such as marginalization, loneliness, depression, anxiety, poor eating habits, etc.

The data presented above favors the “immaturity hypothesis” which posits that the behaviors expected out of some children cannot be performed not because something is wrong with them, but because they are simply too immature to be able to perform those behaviors. That does not mean that every child diagnosed with ADHD will just grow out of it; the researchers just point to the fact that ignoring the chronological age of the child coupled with prematurely entering a highly stressful and demanding system as school might lead to ADHD overdiagnosis.

Bottom line: ignoring the chronological age of the child might explain some of increase in prevalence of ADHD by overdiagnostication (in US alone, the rise is from 6% of children diagnosed with ADHD in 2000 to 11-15% in 2015).

References:

  1. Morrow RL, Garland EJ, Wright JM, Maclure M, Taylor S, & Dormuth CR. (17 Apr 2012, Epub 5 Mar 2012). Influence of relative age on diagnosis and treatment of attention-deficit/hyperactivity disorder in children. Canadian Medical Association Journal, 184 (7), 755-762, doi: 10.1503/cmaj.111619. Article | FREE PDF 
  1. Chen M-H, Lan W-H, Bai Y-M, Huang K-L, Su T-P, Tsai S-J, Li C-T, Lin W-C, Chang W-H, & Pan T-L, Chen T-J, & Hsu J-W. (10 Mar 2016). Influence of Relative Age on Diagnosis and Treatment of Attention-Deficit Hyperactivity Disorder in Taiwanese Children. The Journal of Pediatrics [Epub ahead print]. DOI: http://dx.doi.org/10.1016/j.jpeds.2016.02.012 Article | FREE PDF

By Neuronicus, 14 March 2016

Inhaling a bitter tasting solution may help with asthma (don’t try this at home, yet)

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Asthma is an inflammatory disease of the lungs’ airways. The airway smooth muscle (ASM) expresses a large number of G protein-coupled receptors (GPCRs). The GPCRs are proteins bound to the cell membrane that sense what happens outside the cell and thus signal the cell to engage in appropriate responses. There are many, many types of GPCRs (in the upper hundreds) all over the body. Furthermore, alternative splicing (that is reshuffling parts of the gene that codes for a protein in such a way that you can get several different proteins from the same gene) may produce new types.

In an a effort to characterize the GPCRs in the ASM in the hope of finding an asthma pharmacological target, Einstein et al. (2008) found many more types of these receptors than previously thought, produced mainly by alternative splicing. In a subsequent study, the same group found out that some of these GPCRs are the same GPCRs that are expressed by your tongue in order to taste bitterness (Desphande et al., 2010)! The researchers were not expecting this.

Moreover, the bitter receptors (called TAS2Rs) in the lungs are fully functional, that is they respond to bitter substances like quinine. The response is, surprisingly, that of relaxation of the airways. It’s surprising because the role of bitter receptors in the tongue is to signal avoidance of bitter foods, because they usually contain toxins. So Desphande et al. (2010) (and anyone else in their shoes) would have expected a similar role for the bitter receptors in the lungs: that is, upon smelling something bitter the airways would close to prevent further poisoning. The data proved this expectation to be wrong.

The work so far has been done in isolated human cells. If quinine relaxes the ASM in an Petri dish, would it do so also when the ASM is still attached to its owner? So the researchers gave some bitter inhalants to some mice who had asthma and this treatment DECREASED the airway obstruction in a dose-dependent manner.

Asthma hits 300 million people worldwide and more than a quarter million die of it per year. So this research sparks great hopes for a new treatment direction.

References:

  1. Einstein R, Jordan H, Zhou W, Brenner M, Moses EG, & Liggett SB (1 Apr 2008, Epub 24 Mar 2008). Alternative splicing of the G protein-coupled receptor superfamily in human airway smooth muscle diversifies the complement of receptors. Proceedings of the National Academy of Sciences of the United States of America, 105(13):5230-5. doi: 10.1073/pnas.0801319105. Article | FREE FULLTEXT PDF
  1. Deshpande DA, Wang WC, McIlmoyle EL, Robinett KS, Schillinger RM, An SS, Sham JS, & Liggett SB. (Nov 2010, Epub 24 Oct 2010). Bitter taste receptors on airway smooth muscle bronchodilate by localized calcium signaling and reverse obstruction. Nature Medicine, 16(11):1299-304. doi: 10.1038/nm.2237. Article | FREE FULLTEXT PDF 

By Neuronicus, 10 March 2016

Pic of the day: Lungs’ taste receptors

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Reference: Deshpande DA, Wang WC, McIlmoyle EL, Robinett KS, Schillinger RM, An SS, Sham JS, & Liggett SB. (Nov 2010, Epub 24 Oct 2010). Bitter taste receptors on airway smooth muscle bronchodilate by localized calcium signaling and reverse obstruction. Nature Medicine, 16(11):1299-304. PMID: 20972434, PMCID: PMC3066567, DOI: 10.1038/nm.2237. Article | FREE FULLTEXT PDF

All mammals bigger than 3 Kg pee in 21 seconds

The Ig Nobel is a prize awarded for “research that makes people LAUGH, then THINK — real research, about anything and everything, from everywhere”. Although it started as a parody of the real Nobel prize, over the past two decades it gained much respect and is coveted by many researchers, almost – but not quite – like the real Nobels.

The 2015 Ig Nobel Prize in Physics went to a group of researchers who established, once and for all, how long it takes for a mammal to pee. That’s right, pee.

Sometimes, the time spent procrastinating on YouTube, where you start by looking for something specific and end up 3 hours later watching funny cat video compilations, may not be a complete waste. For example, Yang et al. (2015) gathered 28 YouTube videos of various animals peeing. They also went to the local zoo and videotaped 16 more animals at the Atlanta Zoo emptying their bladders and collected their urine.

Their analysis showed that any mammal larger than 3 Kg pees in an amazing constant amount of time: 21 ± 13 s. That’s right: the cat and the elephant, the dog and the zebra, all pee in about 21 seconds. Too bad they didn’t include the humans in this experiment. I guess there would have been serious questions regarding the videotaping of a man or a woman’s privates…(but they could have sent their students to the toilet with a stopwatch…) Nevertheless, the knowledge about human urethra diameter, bladder size and flow rate (mL/s) can give an estimate of human urination duration, which is about the same as other mammals.

So…. why is that? After all, you would expect that emptying the 160 L of urine (that’s the capacity of an elephant bladder ) will to take longer than 1.4 L (the dog’s bladder capacity). The answer lies in the specifications of the urethra. The longer and wider the urethra is, the faster the urine flow. As the researchers put it, “the urethra is analogous to Pascal’s Barrel: by providing a water-tight pipe to direct urine downward, the urethra increases the gravitational force acting on urine and therefore, the rate at which urine is expelled from the body” (p. 11936). Therefore, the urethra is not just a tube between bladder and genitals, as the medical textbooks define it, but is and amazingly adaptive, robust and efficient system. Contrary to previous thinking, the peeing time is not dictated by muscular contraction resulting in bladder pressure, but by the length and width of the emptying tube.

Of important note, animals smaller than 1 Kg do not follow the what is probably called by now the Hu Constant Urination Law (Hu is the Principal Investigator of the lab and last author of the paper). Why? Because their urethrae are so small that gravity may not help them much. In other words, capillary and viscous forces force them to expel urine in drops in less than 2 seconds. (So astronauts in space pee in drops?)

The researchers also produced a mathematical model of their data (of course). Such model can be used for studying urological disorders in humans. Until now, these studies have been conducted in rodents, which turns out that may not be as good models after all. Another application is in engineering, when designing draining that does not depend on the size of the system.

Overall, a funny, very graphic (has videos attached), highly mathematical and interesting paper to read. The prize is well-deserved.

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Reference: Yang PJ, Pham J, Choo J, & Hu, DL (19 Aug 2014, Epub 26 Jun 2014). Duration of urination does not change with body size. Proceedings of the National Academy of Sciences of the United States of America, 111(33): 11932–11937, doi: 10.1073/pnas.1402289111 Article | FREE FULLTEXT PDF

By Neuronicus, 9 March 2016