Jul
21
2011
0

Alcohol policy and STDs

From Chesson et al, Journal of Law and Economics (2000):

Reduced-form regressions of STD rates on state alcohol taxes for the years 1981–95 (with controls for state and year) indicate that a $1 increase in the per-gallon liquor tax reduces gonorrhea rates by 2.1 percent, and a beer tax increase of $.20 per six-pack reduces gonorrhea rates by 8.9 percent, with similar though more pronounced effects on syphilis rates.

Full text link: http://dinhvutrangngan.com/teaching/Social_Economics/Sexual_Behaviors/Chesson%20et%20al_2000.pdf

Written by Elliott in: Uncategorized |
Jul
20
2011
0

Economic consequences of the Black Death

From Haddock and Kiesling, Journal of Legal Studies (2002):

The Black Death visited unprecedented mortality rates on Europe, realigning relative values of factors of production, and in consequence the costs and benefits of defining and enforcing property rights. . . . [T]he marginal value of labor and human capital rose, which placed insupportable stress on feudal institutions. The predictable evolution of workers’ rights to their own labor accelerated the erosion of serfdom.

Full text available here.

Written by Elliott in: Uncategorized |
Feb
07
2011
0

Oxytocin Promotes Ethnocentrism

De Dreu et al (2011) report preliminary evidence of oxytocin’s role in ethnic conflict in Proceedings of the National Academy of Sciences of America:

Human ethnocentrism—the tendency to view one’s group as centrally important and superior to other groups—creates intergroup bias that fuels prejudice, xenophobia, and intergroup violence. Grounded in the idea that ethnocentrism also facilitates within-group trust, cooperation, and coordination, we conjecture that ethnocentrism may be modulated by brain oxytocin, a peptide shown to promote cooperation among in-group members. In double-blind, placebo-controlled designs, males self-administered oxytocin or placebo and privately performed computer-guided tasks to gauge different manifestations of ethnocentric in-group favoritism as well as out-group derogation. Experiments 1 and 2 used the Implicit Association Test to assess in-group favoritism and out-group derogation. Experiment 3 used the infrahumanization task to assess the extent to which humans ascribe secondary, uniquely human emotions to their in-group and to an out-group. Experiments 4 and 5 confronted participants with the option to save the life of a larger collective by sacrificing one individual, nominated as in-group or as out-group. Results show that oxytocin creates intergroup bias because oxytocin motivates in-group favoritism and, to a lesser extent, out-group derogation. These findings call into question the view of oxytocin as an indiscriminate “love drug” or “cuddle chemical” and suggest that oxytocin has a role in the emergence of intergroup conflict and violence.

Link: http://www.pnas.org/content/early/2011/01/06/1015316108.abstract

Written by Elliott in: Uncategorized |
Feb
06
2011
0

Evidence that Cell Phone Use Reduces Smoking

From Labonne and Chase in Applied Economics Letters:

Using spatially coded data on mobile phone coverage and panel data from 2100 households in 135 communities of the Philippines, we estimate the impact of mobile phone ownership on tobacco consumption. Purchasing a mobile phone leads to a 17.1% decrease in tobacco consumption per adult over the age of 15.

Link: http://www.informaworld.com/smpp/content~content=a927137877~db=all

Written by Elliott in: Uncategorized |
Jan
08
2011
1

Fractal-Like Scaling in Hunter-Gatherer Groups

Hamilton et al (2007) use an ethnographic dataset with information for over a thousand hunter-gatherer groups to show that all primitive human societies are organized according to a branching, fractal-like system in which individuals are subsumed into successively larger hierarchies. Groups of approximately 3.7 individuals form one unit in the next level of the hierarchy (e.g., 4 individuals in a family, 14 individuals in an extended family, 51 individuals in a village, etc.). Following I excerpt part of the discussion section:

The hierarchical fractal-like organization of hunter-gatherer social systems is similar to the self-organized structures of other complex systems in nature (Arenas et al. 2001, 2004; Oltvai & Barabasi 2002; Sole & Bascompte 2006). We suggest that these complex social systems have been shaped by similar optimization processes operating to maximize whole-system performance. In the present case, these human social systems are hypothesized to reflect optimized networks of flows of essential commodities: food, other material resources, genes and culturally transmitted information. . . .

Yet, how do we account quantitatively for the branching ratio? We offer the following hypothesis. Recall . . . that the branching ratio is simply the ratio of the frequency of group sizes between successive levels, Graphic. This can be rearranged to be Graphic or more generally Graphic, and as Graphic, we haveFormula Further, as N(g1) = population size, gΩ, we then have gΩ=BΩ−1 or gΩ=B5 in this case as Ω=6. [I]t follows that the number of families in a population scales with the branching ratio as N(g2)=BΩ−2. As N(g2)=gΩ/g2, we can write the branching ratio as B=(gΩ/g2)1/Ω−2 where family size, g2, can be expressed in terms of the net reproductive rate, R, thus g2=2(R+1). Substituting this expression into the preceding equation, we then have

Formula

and rearranging, the net reproductive rate is then

Formula

Hence, as population size, gΩ, approaches BΩ−1, the net reproductive rate goes to 1 (i.e. reproductive replacement rates) as this equation reduces to R=B/2−1=1. Therefore, at replacement rates, independent of population size or the number of levels in the network, the branching ratio reaches an equilibrium of 4 and follows the replacement family size of 4 (two parents and two offspring). It follows that in growing populations where the net reproductive rate R>1, the branching ratio should be less than the mean family size, and family size will be greater than 4. Our results show that the mean branching ratio in our sample is approximately 3.8, suggesting that hunter-gatherer populations are, on average, growing, predicting that mean family size should be greater than 4. Indeed, mean family size is significantly greater than 4, F=4.48 (4.30–4.67), giving a mean net reproductive rate R=1.28 (1.15–1.33), and a mean population growth rate r=0.011 (0.007–0.015) or approximately 1%, where r=ln R/τ, and τ is generation time, approximately 20 years for traditional human populations under natural fertility conditions (Walker et al. 2006). . . .

[G]roup dynamics are governed by two basic kinds of forces: (i) cohesive forces that tend to draw and hold individuals together and (ii) disruptive forces that tend to pull individuals apart and to create barriers to exchanges between them (see Chagnon 1975). Cohesive forces in hunter-gatherer groups include kin selection due to genetic relatedness, sharing of non-genetic information and exchange of material resources. There are clear cohesive forces within families and wider kin relations, but there are also cohesive forces that extend to larger groups at higher levels of the societal hierarchy. These include exchange of marriage partners so as to avoid inbreeding, communication of information about social and environmental conditions, and exchange of material resources through trade and commerce. Disruptive or antagonistic forces include competition for material resources and for mates, inter-personal conflict and disease epidemics. The intensity of competition, the balance between mutualistic and antagonistic interactions, and the probability of disease outbreak all increase with increasing group size, with the result that individuals aggregate into successively larger groups with successively decreasing frequencies and only for specific purposes, such as exchange of marriage partners, trade in goods that are not available locally, and defence against or competitive aggression (e.g. warfare) towards other higher-level groups.

Written by Elliott in: Uncategorized |
Jan
06
2011
0

Web Size and Cooperation in a Eusocial Spider

Yip, Powers, and Aviles (2008) find that web size in a colony of eusocial spiders reflects an optimal tradeoff between having to feed a larger population and consuming larger prey through cooperative hunting. The following excerpt summarizes the findings:

Here, we demonstrate the major role that cooperation plays in solving the problem of a declining surface area to volume ratio in this social spider. Anelosimus eximius is notable among cooperative spiders—also known as nonterritorial, permanent social, or simply social—for building the largest webs and colonies among species of this social system (18). Cooperative social spiders build and maintain communal webs in which members of a colony cooperate in the capture of prey, feeding, and brood care. Colony members are totipotent and mate with each other to produce new generations of spiders that continue to occupy and expand the natal nest. Colonies grow through this process of internal recruitment until, in species such as A. eximius, a single colony’s population may on occasion reach into the tens of thousands (18). Here, we show that cooperative foraging in A. eximius allows the capture of increasingly large insects as colony size increases and that this effect is sufficient to overcome the decline in the number of insects caught per capita that results from the scaling of prey capture area per spider with increasing colony size. As a result, prey biomass intake per capita is maximized in colonies of intermediate size, thus explaining both sociality and colony size range in this social spider. This is an intriguing solution to a universal scaling problem, made possible because the “organism” in this case is a collective of units capable of cooperation.

 

Written by Elliott in: Uncategorized |
Nov
30
2010
0

American Media and Servility

George Orwell on the mentality of waiters:

The waiter’s outlook is quite different. He too is proud in a way of his skill, but his skill is chiefly in being servile. His work gives him the mentality, not of a workman, but of a snob. He lives perpetually in sight of rich people, stands at their tables, listens to their conversation, sucks up to them with smiles and discreet little jokes. He has the pleasure of spending money by proxy. Moreover, there is always the chance that he may become rich himself, for, though most waiters die poor, they have long runs of luck occasionally. At some cafes on the Grand Boulevard there is so much money to be made that the waiters actually pay the PATRON for their employment. The result is that between constantly seeing money, and hoping to get it, the waiter comes to identify himself to some extent with his employers. He will take pains to serve a meal in style, because he feels that he is participating in the meal himself.

Glenn Greenwald on the New York Times’ response to the newest WikiLeaks disclosure:

Most political journalists rely on their relationships with government officials and come to like them and both identify and empathize with them.  By contrast, WikiLeaks is truly adversarial to those powerful factions in exactly the way that these media figures are not:  hence, the widespread media hatred and contempt for what WikiLeaks does.  Just look at how important it was for Bill Keller to emphasize that the Government is criticizing WikiLeaks but not The New York Times; having the Government pleased with his behavior is his metric for assessing how good his “journalism” is.  If the Government is patting him on the head, then it’s proof that he acted “responsibly.”  That servile-to-power mentality is what gets exposed by the contrast Wikileaks provides.

Written by Elliott in: Uncategorized |
Oct
26
2010
0

No effect of Adderall on normal subjects

Adderall, the treatment for Attention Deficit Hyperactive Disorder (ADHD), is one of the most effective psychiatric drugs in current use, improving attention and behavior in over 70% of ADHD patients. Compare this to serotonin reuptake inhibitors (SSRIs) like Prozac or Zoloft, each of which are effective in about 30% of people with depression.

In a poster abstract at this year’s SfN, Ilieva from the Farah lab at UPenn report on a placebo-controlled double-blind clinical trial with Adderall using cognitively normal subjects. They found no objective effect on working memory and cognitive control. Subjects, interestingly, subjectively reported improved performance in these tasks. Here is the abstract:

A growing number of cognitively normal adults use stimulant medications in order to enhance their cognitive abilities. We investigated whether such medications enhance executive function, which is closely associated with intelligence and is dependent on the catecholaminergic targets of stimulant drugs. The literature to date yields inconsistent results, with as many null results as findings of enhancement. In a double-blind placebo controlled cross-over study using 20 mg of mixed amphetamine salts administered to 48 healthy adults aged 21-30, we assessed working memory and cognitive control with two tasks each (Digit Span, Object-2-Back, Go/No-go and Flanker). Although the study was adequately powered to detect an effect of moderate or greater size, we failed to find an overall effect of the drug, nor did we find enhancement in any individual task. The lack of effect held for both higher and lower performers. In contrast, participants reported more perceived cognitive benefit with amphetamine. We conclude that the objective effects of amphetamine on executive function are at best subtle, whereas the subjective effects of amphetamine are sufficiently salient to measurably affect self-perceived performance in this study. This is consistent with the existing literature on stimulant effects in specific executive function tasks, especially in view of the higher barrier to publishing null results, and also suggests a reason for the popularity of these drugs as cognitive enhancers. It must be added that cognitive abilities other than those tested by us may well have been substantially enhanced.

Adderall doesn’t improve your study abilities, but by associating studying with positive feelings (a side effect of the amphetamine), it makes studying more fun. Pairing studying with an enjoyable drug allows homework to compete with all of the other fun things you could be doing, like video games, facebook, or beer pong.

Written by Ryan in: Uncategorized |
Sep
16
2010
0

Mouse genetic background issues in my grad school lab

I just had my first major set-back in grad school. For the past 4 months, I have been breeding transgenic mice to study the neurobiology of autism. I realized yesterday that I’ve been going about the breeding all wrong, and now I have to start over. It’s a subtle issue, so let me try to explain.

The issue is the genetic background of the mice. The mice generally used in biology experiments are completely inbred. For a given strain of mouse, every member of the strain has essentially the same DNA.There are many strains that people commonly use – one is C57 Black 6, another is FVB, another is 129; The names come from a random fact about the mouse when it was originally inbred. The name FVB, for example, comes from the fact that a mouse was found to be susceptible to Friend leukemia Virus strain B. All of these mice have been inbred with litter mates over dozens of generations until, statistically, they are homozygous at both alleles of each gene.

For the major inbred mouse lines, there are master strains managed by Jackson Labs, a huge government-funded mouse factory in Bar Harbor, Maine (If you want a mouse of a given strain, you can order it for $15-20 and have it shipped to your laboratory in 3 days).

When mice are mutated in some way (It used to be that mutant mice were generated by feeding mice mutagens and observing their offspring for strange traits and behaviors. The two most common approaches used these days are “knock out” by homologous recombination or gene insertion by classical transgenesis), a specific mouse strain must be chosen to make the mutation. FVB or 129 are good for classical transgenesis because they have large embryos, so it is easy to inject the exogenous mutant DNA into the embryo (which will then mysteriously integrate into the embryo’s genome and create a transgenic mouse). C57 is good because it’s behavior is well characterized and it has been used for lots of experiments for several decades, so you can directly compare your results to previous results.

There are significant differences in phenotype between different inbred mouse strains. Recessive alleles become homozygous during the inbreeding process and are a permanent trait of the mouse.FVB mice, for example, have an abnormal photoreceptor gene which causes retinal degeneration. C57 mice have good memory (for mice). 129 mice have large litters. And so on. If you mutate a specific gene, it may have different effects on different mouse lines, but this is unpredictable. So the important thing is to be internally consistent – to be sure that you’re doing all your work on one genetic background, or on one combination of backgrounds. That way it can be reproducible.

We have two major transgenic mouse lines in the lab that we use. The thy1-GFP mice express the Green Fluorescent Protein (GFP – a protein from jellyfish that glows in the dark) randomly in neurons. How they made the mouse: they took the promoter for thy1 (thy1=thymus cell antigen – a protein of unknown function which is expressed in neurons and the thymus), altered the promoter so that it would only cause expression in neurons, and placed GFP behind the promoter. They then injected this DNA fragment they made into C57 mouse embryos, which inserted into DNA at random spots.

Which cells in the body express the trangene depends on where the transgene  inserts into the genome, and on the promoter.  A gene’s promoter (aka enhancing sequence) determines which cells will express the protein, because it has binding sites for specific transcription factors (gene expression-regulating proteins). If a cell has the right combination of transcription factors, the gene will be expressed.

Because of thy1-GFP’s altered thy1 promoter, and because of where it inserted into the genome in the mouse line we use, a small subset of the mouse’s neurons glow in the dark. So if we make a hole in the mouse’s skull and put the brain under a microscope, we can see the mouse’s neurons (Actually, the fluorescent proteins only glow when excited – a laser must be scanned through the mouse’s brain to induce the neurons to glow.).By placing a glass coverslip into the hole in the skull, we can image the same neurons over several days, and see how they grow, respond to different experimental interventions, and form synapses with other cells.

The other mouse line we use is the mecp2-Tg1 mouse. This mouse overexpresses the gene methyl CpG binding Protein 2 (MECP2) at double normal levels. This same genetic defect causes a severe developmental syndrome in humans which most notably includes autism. The mecp2-Tg1 mouse also has weird behavior

If we cross this mecp2-tg1 mouse with the thy1-gfp mice, we can see the genetically-mutated neurons in the living animal, and they are structurally abnormal. Their dendrites are much more intricately branched than normal neurons, and they form fewer excitatory synapses, among other things. It’s interesting to characterize these mice because they may tell us something about the pathophysiology of autism

Okay, that was just context for the set back I had today.

The thy1-GFP mice were generated on a C57 background. The mecp2-Tg1 mice were generated on an FVB background. So when we cross these two mice (to allow us to visualize the neurons in the ‘autistic’ mouse [Saying a mouse has autism, or is autistic, or demosntrates autism-like behaviors, is ill-advised in science. Autism is a complex human disorder of unknown etiology, and its symptom presentation depends on uniquely human characteristics like social behavior and language. Although mice with these genetic abnormalities demonstrate changes in social behavior, and some even change the way they communicate with sound, it's a grand leap to label these phenotypic changes autistic.]), half of the offspring’s chromosomes are C57  and half are FVB. It’s not as ideal as a pure background, but at least it’s reproducible – you know that for every gene, one allele is C57 and one allele is FVB. This sort of cross generates F1 heterozygotes for experimental use.

(Random facts: Mice give birth 3 weeks after conception, are weaned at 3 weeks of age, and are fertile at 5 weeks of age. The standard breeding scheme is 1 male and 2 females. Females are fertile the day they give birth. Litter size is about 8-12 pups on average. So 1 mating cage (1 male + 2 females) can easily pump out 200 mice in a year. The American scientific enterprise ‘uses’ in excess of 6 million mice per year).

The problem in our lab is that when choosing the parents for the past year’s breedings, we only took transgene into account, not the background. So we crossed  mice which already had a mixed C57xFVB background. In these crosses, the offspring all have different combinations of genes from each background. It may not have any effect on our measurements, but this can’t be proven (barring doing the experiments on many different backgrounds, which would be tedious and very time consuming).It is known that different mouse strains have different behavioral phenotypes, but traits like neuron structure are probably unchanged. It’s still a better practice where possible to stick to crossing pure C57 to pure FVB.

So we will have to reorganize the breedings for these mecp2-Tg1 x thy1-GFP mice. A major delay.

But I am not using these mice for my thesis project. My thesis in brief: Given that mecp2 overexpression causes autism in humans, and causes these structural changes in neurons in the brain, an important question is whether the neuron abnormalities are due to overexpression of mecp2 during development or during adolescence. It is also important to determine if resolving the genetic defect (returning mecp2 expression levels to normal) would resolve the abnormal neuron structure and behavioral changes caused by the defect.

To address these questions, I plan to use the tetracycline-inducible gene expression system (this is complicated, bear with me). This system, called “Tet-Off” for short, allows you to control the expression level of a mutant transgene by giving the mouse different doses of the antibiotic tetracycline. How it works is that you mutate the mouse to carry two new transgenes: One is a transcription factor from bacteria which drives the expression at a specific promoter (called the tetracycline-responsive element [TRE]) when not bound to tetracycline; the other is the gene whose expression you want to control placed behind a TRE promoter. For my project, the first gene is called tetracycline trans-activator (tTA); the second is called tetO-mecp2. If  two transgenic mice, once carrying tTA and the other tetO-mecp2, are crossed together, their offspring will carry both transgenes, and they will overexpress mecp2 unless given tetracycline (in the food or water).

I also want to image the neurons of these mice, so I need to get thy1-GFP in addition to tTA and tetO-mecp2 on the same mouse, which takes multiple breeding crosses. tTA and thy1-GFP are on a C57 background; tetO-mecp2 is on FVB. My original plan was to breed both the thy1-GFP and tetO-mecp2 to homozygosity, then to cross the double homozygotes with a tTA mouse to generate experiment-ready offspring, half with all 3 alleles (thy1-GFP, tTA, & tetO-mecp2), half with 2 (thy1-GFP & tetO-mecp2 – without tTA, mecp2 will not express, making these mice littermate controls). Unfortunately, this strategy includes breeding steps in which I self-cross mixed C57xFVB mice, leading to random variability in allele distribution in the offspring. A better breeding strategy as far as genetic background goes would be to first homozygose the C57 thy1-GFP and tTA transgenes, and then cross this double homozygote (which is still C57) to the pure FVB biTetO-mecp2. This strategy would produce mice which are of determinate genetic background.

After meeting with a mouse breeding expert today, I decided that, instead, I’m going to cross heterozygous thy1-GFP/+;tTA/+ mice (which are on a pure C57 background) to tetO-mecp2/+ mice (which are on a pure FVB background). This strategy saves the cross to the FVB mouse for last and allows all experiments to be performed on F1 heterozygotes. The new strategy will generate a lot of extra mice which must be culled, but this is common according to the mouse expert I spoke with. Worst, it will add a month or two to my predicted breeding period. Best, it will deal with any problem of genetic background. and it will allow me to avoid having to homozygose the two transgenes (an arduous task which requires the technically-demanding  quantitative polymerase chain reaction (qPCR – a method to quantify the number of copes if a specific gene) for genotyping (=determining if an individual harbors a specific gene or mutation).

To make matters worse, I found out that my tetO-mecp2 mice are not actually on a pure FVB background. After the above decision-making, I e-mailed the collaborator who provided the tetO-mecp2 mice to confirm that they are on a pure FVB background (as described in the paper which originally used the mouse).

“Should be FVB. Is their fur white?” She replied (FVB mice are white; C57 are black).

“No, two are black and one is brown,” I e-mailed.

“That means they are mixed galore. I recommend back-crossing to C57,” She said.

So I won’t be able to completely elucidate the genetic background of my mice unless I perform a back-cross, in which a transgenic mouse is iteratively crossed to a pure inbred strain over several generations. A speed back-cross to C57, using single-nucleotide polymorphism analysis kits developed by Rich Paylor here at BCM, will take 1 year, but is not too difficult. It uses PCR to pick out the mice that are most “C57-like” in each generation and cross those again to C57. It cuts the time to attain congenic status (Congenic means approximately inbred) from 2 years to 1 year.

The most reasonable plan I’ve come across so far is to use my mixed-background mice for the imaging experiments, as it is very unlikely that reviewers will think background is important for these measurements. In the background, proceed with the back cross, and in a year perform the behavioral tests on the mice after they are congenic for C57 (reviewers for behavioral experiments care much more about background).

This is the biggest setback I’ve had in graduate school thus far (I’m a bit over a year in). It could be much worse – a student in the class ahead of me had to change her experimental model from mouse to rat after doing 2 years of experiments on mice – the department of defense was funding her research on traumatic brain injury (TBI), and they decided that only the rat was a legitimate animal model for TBI.

The strange thing is that my biggest success in graduate school also occurred today. I was awarded the grant fellowship I applied to last summer (in which I proposed the above project). I hope they don’t read this, find out about all of these problems with the proposal I submitted, and change their mind.

Written by Ryan in: Uncategorized |
Sep
10
2010
0

Some Health Care Economics

Courtesy of Mark Duggan from the University of Maryland, I share two important empirical findings on health care (emphases added):

Duggan and Morton (2005):

To determine the price that it will pay for each drug, Medicaid uses the average private sector price. When Medicaid is a large part of the demand for a drug, this creates an incentive for its maker to increase prices for other health care consumers. Using drug utilization and expenditure data for the top 200 drugs in 1997 and in 2002, we investigate the relationship between the Medicaid market share (MMS) and the average price of a prescription. Our estimates imply that a 10 percentage-point increase in the MMS is associated with a 7 to 10 percent increase in the average price of a prescription.

Duggan (2004):

Recent research has suggested that the shift to new drugs may lower health care spending by reducing the demand for hospitalizations and other health care services. Using a 20% sample of Medicaid recipients from the state of California for the 1993-2001 period, I investigate this hypothesis for antipsychotic drugs – the therapeutic category that has accounted for more government spending than any other during the past decade. Using three different identification strategies, my findings demonstrate that the 610% increase in Medicaid spending on antipsychotic drugs during the study period caused by the shift to three new treatments has not reduced spending on other types of medical care, thus undermining the hypothesis that the drugs have “paid for themselves.” Because of data limitations the findings for health outcomes are necessarily more speculative but suggest that the new medications have increased the prevalence of diabetes while reducing the prevalence of extrapyramidal symptoms among the mentally ill.

Written by Elliott in: Uncategorized |

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