A lab technique that isolates a single species of bacteria from a sample with more than one species of bacteria.

Many experiments from other researchers are utilized in this study to compare model calculations with experimental data.

The authors in this study utilize all of these different sources of information to build a better understanding of the sources of air pollution.

Here, in situ means "in place." Measurements were made of the actual footprint contours left by the individuals striding along the trackway.

For each test-pit, the authors analyzed the soil profile.This established how the different areas were related geologically and provided information about how to proceed with the analysis of hominin and wildlife print present.

The degree of fossilization of the footprints varied in different locations. In order to study the shape and structure of a footprint, soil had to be carefully removed from the depression.

The trackway footprints are extremely fragile. Clearing and preserving them had to be done with the utmost care. Unlike fossil bones that are solid, the footprints are only empty spaces. Depending on the substrate, an incorrect move could cause the soil to crumble and the footprint to be destroyed. The author had to do a careful analysis of the trackway soils to be able to know how to best preserve and analyze each footprint.

Site G is the code used by Leakey to identify the trackway her group discovered. The three individuals leaving the footprints are referred to as G-1, G-2, and G-2. Keeping with this code system, the authors identified the new trackway area as Site S. The footprints are attributed to individuals S-1 leaving foot prints numbered S-1-1 through S-1-7 in location L8. Individual S-1 also traveled through locations M9 and TP2.

It is only by embracing Newton's ideas that physicists such as Einstein were able to consider exceptions and, in doing so, build on them.

Although we don't often think about it, scientists improve on each others' ideas all the time and revise theories in light of new evidence generated by new technologies and methodologies.

Einstein introduces the need for a concept of general relativity, which describes motion with respect to any two coordinate systems, not just inertial coordinate systems.

Einstein's question points out that coordinate systems are not a product of nature, but a way of understanding nature. It is because of this that physicists are able to revise the tools and methodologies they use in light of new evidence.

After determining that neither the SM tag nor Fab would disrupt cellular processes, the authors wanted to determine how soon Fab would mark KDM5B. To do this, the authors repeated their first trial but imaged at 6 hours instead of 24.

Preliminary testing was conducted twenty-four hours after the plasmid was transiently transferred to ensure that the methods of coupling the FLAG SM tag (that can be labeled with the anti-fluorescein antibody, anti-FLAG Fab) and the MS2 stem-loop (that can be identified with a MS2 coat protein) would not inhibit transcription, translation, or the movement of SM-KDM5B mRNAs throughout the cell.

The results are highlighted in Fig. 1C with the SM-KDM5B protein in green and the MCP-labeled mRNAs in red.

JF646 produces a brighter fluorescence than other proteins.

MS2 is a protein from the coat of bacteriophages. It has a high affinity for "stem-loop" structures, which are hairpin-like shapes formed by DNA. The authors took advantage of this high affinity by using labeled MS2 to detect certain sequences.

Scientists are always working to improve existing techniques to be more precise and versatile.

The final map, 3H, uses a different color coding key, and shows the grid points that are different between the past, present, and future scenarios. Grid points that differ between the 4700 B.P. scenario and the present scenario are marked with blue circles. The filled dots all indicate differences in the biomes between the present and certain future scenarios. Yellow dots are grid points that are only different in the 4.0°C scenario, RCP8.5. The orange dots are different in both the RCP4.5 and RCP8.8 scenarios, and the red dots are different in the RCP2.6, RCP4.5, and RCP7.5 scenarios.

The third map, 3C, was generated by putting the current climate data into the BIOME4 model, running in "forward" mode. This does differ from the first map, based on pollen core samples. The biggest difference is that the first map shows warm mixed forest whereas the third map shows Temperate Deciduous Forest; this is likely caused by pine pollen being over-represented in the pollen core data.

The second map, 3B, comes from putting the 4700 B.P. pollen core data (covering the years 4650–4750 B.P.) into the BIOME4 model. This time slice was picked to represent the past Holocene because it had the highest variation from the present distribution - this is the bar that extends above the 99th percentile line in Figure 2.

These lines, marked below in purple, provide information about the distribution of the black bars, which show the proportional biome change in past Holocene compared to the current period. Half of the values are at or below the lowest line, whereas all but 1% of the past values fall at or below the top line.

Here's the figure with the lines more prominently marked:

To calculate future values, BIOME4 was run in its normal mode—using climate inputs to generate biome predictions. The climate inputs come from the models and time-series data found in the Coupled Model Intercomparison Project (CMIP5), which "promotes a standard set of model simulations." This way, research is done using the same underlying models, which allows for better comparisons across projects. Researchers update these models approximately every 5 years, incorporating new information.

The researchers use two main methods to generate the information about the Mediterranean Basin in this paper—for the past, the model uses data from pollen cores to generate information about the climate and ecosystems found over the past 10,000 years. For the future, the model uses different CO₂ emissions pathways to generate projections about the ecosystems and climate.

The error bars for the Holocene and 1901–2009 data points are based on standard deviations. This is a different method from what the researchers used to calculate the future predicted values.

Authors found that this species of ants are more efficient at being predators.

The ant species C. floridanus death rate is at 56.3% during this experiment. They have forced some or all instar caterpillars to leave their habitat.

The instar caterpillars were vulnerable to be eaten, or killed by other predators.

Each species was investigated to determine and compare each tree group.

The experiment was conducted at Biscayne National Park and was split into three parts. The first part was using pitfall traps to collect ants at Biscayne Park near the host plants. Secondly, the host plants with known caterpillars were protected with various combinations of cages and tanglefoots. Concluding the author was keeping track of how long it take for certain species of ants to first find the caterpillars. Authors assumed that the ants would interact with caterpillars more frequently than other predators.

All of the ants found in pitfall traps that were placed all around the canopy in the keys. 11 out of 25 species were found to be exotic and 735 out of 1418 of the total amount of ants were exotic.

After the experiment was finished, they have found that the Pseudomyrmex gracilis and C. floridanus interacted more aggressively toward the subject compared to another species.

A learned association between a stimulus and negative outcomes, in this case represented by pictures associated with an electric shock.

Learn more about fear conditioning (animal study): https://www.youtube.com/watch?v=ozkpK-nhz04

Reinforcement that allows the association of a symbol with a positive outcome, in this case money. After trials, the objective was to teach participants to respond to the animal pictures associated with a reward.

This task establishes an association between a neutral stimulus and a negative outcome with the hope that the repetitive task will teach participants to avoid the stimulus.

In this study, the negative stimulus was an electric shock over four stages of learning.

The determination of the correlation coefficient.

In this study, the authors used both Pearson (r) and Spearman (rho) correlations. Pearson correlation is used when there is an assumed normal distribution (distribution that shows symmetry around the mean), while Spearman is used when it is assumed the distribution will not be normal.

Learn more about coefficient determination:

http://blog.uwgb.edu/bansalg/statistics-data-analytics/linear-regression/what-does-coefficient-of-determination-explain-in-terms-of-variation/

The eight blocks (96 trials) where participants were tested and learned from the feedback that they received after their response to the presentation of the pictures.

A urine screen is performed to rule out medical conditions and/or drug use. In this case, the authors used it to determine if the volunteers were appropriate for their study and to see if they tested positive for drug use for the different types of drugs involved.

A test that makes it easier to analyze data that aren’t normally distributed. The authors performed this analysis to reduce skewness (effects due to asymmetry in a probability distribution) and stabilize variance from the questionnaires and demographic responses.

To learn more about transformation: http://fmwww.bc.edu/repec/bocode/t/transint.html

In this experiment, skin from a human was grafted onto mice with depressed immune systems. This means a piece of human skin was transplanted onto mice whose immune systems could not protect them from diseases.

In this study, the cells from the neural crest of mice that carried the specific mutation Kitl were treated with endothelin 3.

The study described here consisted of treating quail (type of bird) neural crest cultures with Edn3. This study was in vitro, meaning the embryonic neural crest was removed and treated outside of the organism. This study showed the role that Edn3 plays in development as stated in the paper.

Exact numbers are not available for the mass of plastic waste entering the ocean, so the authors used a series of estimates in their calculations.

For the reconstructions of the past Holocene ecosystems based on the pollen cores, the initial model outputs are at a lower resolution than the 0.5° by 0.5° resolution of the future projected biomes. The resolution of the reconstructions was a grid of 2° latitude and 4° longitude.

To allow more direct comparisons between past and future, the researchers interpolated the reconstruction data to fill in a 0.5° by 0.5° grid. However, this may miss some features at scales smaller than the original gird.

How the authors obtained AGB and tree biodiversity, evaluated trade off among tree diversity and aboveground biomass

Table 1 shows the different types of plots used and how they differed in size, area covered, areas inventories, shape, and number of days used.

Fundamental paper which shows how plants will uptake more CO2 when it is present in higher and higher quantities.

At 600 parts CO2 per million parts air, plant carbon uptake is limited due to low levels of CO2 present in atmosphere.

The solid bars show the actual data gathered. They measure the different rates of carbon exchange.

Figures displays projections for the effect of three climate-induced environmental changes on ecosystem processes (NEE, Reco, GEE).

As CO2 levels and temperature increase, the ecosystem will uptake more and more CO2, and will retain more carbon.

The figures show what happened to the actual data vs the data from the model. They are very close and show that the model is reliable, in other words, the data is precise.

Remember, this is a simulation! It was done on the DAYCENT simulation model.

These charts show the different magnitudes, at differing scales of CO2, temperature, and rainfall, respectively, projected out to the year 2076.

By comparing a modeled map using every data point available and comparing that map to one that excludes outliers exceeding 3 standard deviations, the authors realized they were actually excluding some ocean temperature features that occurred. Thus by changing the data cut-off to 6 standard deviations it was possible to more accurately model ocean conditions.

By broadening the cutoff criteria the authors of this study were able to distinguish real-life changes in ocean temperatures. Their previous data cutoff of 3 standard deviations (which are a measure of variance around a mean), was too strict and deleting real data points.

Broadening the pool of what was considered "good" or "realistic" data to 6 standard deviations was necessary in order to properly document temperatures that actually occurred in the oceans.

Biological factors that drive the decomposition of carbon include the consumption and respiration from microbes, vertebrates, and in-vertebrates.

Physical factors include temperature, flow of water, and sediment.

The alignment of the reach-litterbag scale rates show that the bags represent the actual rates, and that the bags were not simply filtered by increased water flow or torn apart because of temperature.

The litterbag technique can be used to measure the density lost due to composition by microbes and fungi.

A known type and amount of litter is stuffed in the bag and is left for a certain amount of time in the stream. The bag is then later taken out and weighed while wet. The bag is allowed to dry and then the dry weight is taken.

Benthic fine and coarse particulate organic carbon can be used as a measurement when observing loss of carbon caused by detrivores.

In this experiment, leaf litter from different types of trees were used. The results are in Figure 3.

The structure and chemistry of leaves are different and this determines how fast they may decompose.

For example, tulip poplar decomposes the quickest and has a low carbon to nitrogen ratio. Comparatively, oak decomposes slowly and has a higher carbon to nitrogen ratio.

It is often necessary to use a simpler model version of a larger system because it is easier to observe.

It is difficult to observe the effects on a whole stream, but the litter bags are observed and represent the carbon loss in streams.

Litter in the litter bags have a higher concentration of carbon than the stream, which has carbon more spread out. The litter will have higher loss of carbon but generally represents reach-scales.

Two experiments were done separately to test the effects of nitrogen to phosphorus ratios on streams.

Pre-treatment of streams include recording the levels of nutrients and typical conditions throughout a year.

The first experiment had two watersheds with one being the control and the other having an addition of nitrogen and phosphorus to match a ratio that was decided by the scientists.

The second experiment was done on five streams with different combinations of the nitrogen and phosphorus ratio.

Although this experiment focuses on microbial and fungal effects on streams, humans sometimes also have an impact.

These effects may include the leaking of septic tanks into bodies of water that increase human waste and phosphorus levels. Fishing and polluting also affect stream ecosystems.

The experiments were conducted on streams in the Appalachian Mountains of North Carolina.

Because of the elevation, there are little to no fish influencing the data. Mainly microbes and fungi influence the nutrient levels of the streams.

An irrigation line was used along the 70-150 meter streams to pump in liquid nutrients. The nutrients were pumped proportional to the flow of the water.

Using reverse transcription polymerase chain reaction (RT-PCR), the authors amplified sequences for the genes coding for opsin, arrestin, and rhodopsin kinase (RK). Transcripts were extracted from the tissues of the light organ, eye, gills, mantle, tentacle, and arm.

The authors used two methods to discover if opsin, arrestin, and rhodopsin kinase also occur in the light organ.

In the first method (message expression), the authors looked for the molecular signals of these proteins in tissues from the light organ, eye, gills, mantle, tentacle, and arm.

In the second method (immunocytochemistry), the authors looked for evidence of protein production in the tissues of the light organ using confocal microscopy.

The authors do a Genome-Wide Association Study (GWAS) analysis, which is a study of whether any particular loci in the genome are associated with a particular phenotype (in this case, skin pigmentation levels).

GWAS analyses look at variants (alleles) across the whole genome, rather than focusing only on regions that are thought to be associated with a phenotype. This way, new regions of the genome can be discovered as being involved in the genetic architecture of a trait.

The authors control for age, sex, and genetic relatedness, because these are variables that could confound (confuse) the results by affecting the phenotype of interest, in this case skin pigmentation. To avoid confusion, the authors take these variables into account when they look for associations between SNPs and skin pigmentation.

The authors used the Illumina Infinium Omni5 Genotyping array, a specific type of SNP array.

The array has a set of oligos (short stretches of single-stranded DNA) on a chip that is complementary to the DNA right next to the SNP of interest. DNA taken from the person being genotyped gets broken up into small pieces and put on the chip, where it will stick to the complementary oligo.

Next, nucleotides (A, C, G, T) labeled with different color dyes get put on the chip and will bind to the DNA that is attached to the oligos. A scanner reads what color is found at each spot on the chip, which tells the investigator what nucleotide the person has at that locus—which is also known as what allele the person has.

The authors estimate how much pigmentation variation can be explained by their top predicted variants.

A mixed model has both fixed effects and random effects. In this case the authors looked at random effect terms based on looking at the whole genome as well as looking at only variants that were identified as significant. The mixed model gives an estimation of how much each of the variants contributes to skin pigmentation in their study.

Directional selection occurs when one trait is favored over others, leading to a shift in allele frequency toward the allele associated with the favored trait. This also leads to an excess of low-frequency alleles, and a negative value of Tajima's D.

Balancing selection is a process by which multiple alleles are maintained in the population, for example when heterozygotes are at an advantage (which keeps both of their alleles at a relatively high frequency). This leads to a lack of rare alleles, and a positive Tajima's D.

Tajima's D statistic of approximately zero indicates that the population is evolving with little or no selection.

The luciferase expression assay is also known as the luciferase reporter assay, and is a method to detect how much expression can be driven by a particular enhancer.

The assay is described in detail here: https://bitesizebio.com/10774/the-luciferase-reporter-assay-how-it-works/. Briefly, the authors put DNA that corresponds to the predicted, potentially causal regulatory regions into a vector that also has the luciferase gene, and then put this vector into cells. In this experiment, the authors use WM88 melanoma cells, which are a cell line grown from a patient who had melanoma.

The luciferase gene will only get expressed (and the luciferase protein made) if the regulatory region ahead of it gets expressed in these cells. To detect whether there is luciferase in the cells, the authors break open the cells to release their proteins, add additional reagents that interact with luciferase (if it is present), and use a detector to see how much light gets emitted. More light emitted means more luciferase was present, which means that there was more expression being driven by the regulatory region.

The authors extend their previous experiments in mouse cells to make mice that are missing Mfsd12 in all of their cells.

They use CRISPR/Cas9 to make a null allele of the gene, which is a nonfunctional copy of a gene due to genetic mutation. They do this in mice that are otherwise wild-type, or have typical genetic and phenotypic characteristics.

In this experiment, the authors use a genetic tool called shRNA (small hairpin RNAs) to turn off expression of the gene in mice that is homologous to one of the genes they identified in the previous section as being associated with skin pigmentation. An ortholog is a homologous gene from a different species.

An shRNA is an artificial RNA molecule that is shaped like a hairpin—a strand with a tight turn as it folds back on itself. shRNAs are processed by mammalian cells into small interfering RNAs (siRNAs), which suppress gene expression of a particular gene that it is complementary to—in this case, the authors use shRNA that will silence the gene Mfsd12.

To perform fine-mapping, the authors need more data than they have from their SNP arrays. To get more precise data, they performed full-coverage sequencing of a small subset of people from their original populations, sequencing only the regions of the genome they identified with the GWAS. Sequencing allows researchers to discover the order of nucleotides across a given region of the genome.

The authors also used previously published work from a data set called the Thousand Genomes Project, which looked at the sequences of the whole genome for over 1000 people.

Local imputation uses patterns of association between SNPs in the data sets with higher coverage, as well as known patterns of linkage disequilibrium (nonrandom association of alleles in a particular population) between SNPs, to predict what alleles a person has at those regions. This means that it is possible to confidently predict the alleles for each of the >1500 people in the current study, even for loci with SNPs that aren't included in the original genotyping array.

The authors use fine-mapping to narrow down the larger regions identified in their GWAS results, allowing them to identify specific SNPs that are likely to be causal, so they can study these SNPs further. Fine-mapping uses a variety of methods to pinpoint the precise location of a gene or regulatory region that is associated with variation in a phenotype.

The authors determined the genotypes (the set of alleles in an organism's genome) of the people for whom they had quantified skin pigmentation.

They use a SNP array for genotyping, which is a tool that allows researchers to study small differences between genomes. A SNP (pronounced "snip") is a single nucleotide polymorphism, or a change to a single base (nucleotide) at a particular DNA locus.

The authors wanted to study a wide variety of Africans, and used a handheld battery operated tool called the DSM II ColorMeter to get a quantification of how much pigment was in each person's skin.

The DSM II ColorMeter works by shining light at skin and detecting how much light reflects back, and at what wavelengths. They used a particular wavelength to determine how much melanin was present in the skin.

The authors look at the exome (all of the protein coding parts of the genome) by gene sequencing, to see what differences exist between gr/gr mice that are gray and wild-type mice with the usual agouti color.

They sequence a saved sample they had, and confirm that they can find the same mutation in a gr/gr mouse from a different colony, to be sure that the mutation they found in Mfsd12 wasn't a random mutation that arose in their colony.

For confirmation of the mutation, they use Sanger sequencing of the specific region around the mutation. Sanger sequencing is a method of sequencing shorter pieces of DNA, instead of the whole exome.

Here, the authors investigate the effect of losing the zebrafish ortholog of MFSD12 by using a technique called CRISPR/Cas9.

Cas9 is an enzyme that cuts DNA, and is guided to particular DNA sequences by a guide RNA (gRNA). Researchers can use different gRNAs to make cuts to particular DNA regions in order to disrupt expression of genes.

The authors use CRISPR/Cas9 with gRNAs targeting the part of the zebrafish ortholog mfsd12a that spans the cell membrane so that the protein will no longer function properly. They then examined the zebrafish for what impact the knockdown of the gene has had, if any.

The authors look for what part of the cell the MFSD12 protein they're interested in is located. To find the protein, they first "tag" it at the C terminus with an HA epitope.

The C terminus is the end of the protein. Tags are often put on the end of the protein because in some cases they are less likely to interfere with expression or function if they're at the end.

HA stands for human influenza hemagglutinin, which is a protein on the surface of human cells. A particular part of it, the HA epitope, can be used to tag proteins in cells because it's small, so it's unlikely to interfere with protein function or location.

An epitope is a part of a protein that is recognized by an antibody, which can be bound to fluorescent molecules so it can be visualized by a technique called immunofluorescence microscopy.

RNA-sequencing, or RNA-seq for short, is a method to quantify the amount of specific sequences of RNA in a sample.

To perform RNA-seq, the authors extracted the RNA from primary melanocyte cultures (melanocytes growing in a dish after being taken from human skin). Next they made complementary DNA, or cDNA, that corresponds to each RNA fragment from the cells. The more RNA there is for a particular gene, the more cDNA there will be.

Then, the authors sequence the cDNA, and determine how many times they detect each molecule of cDNA. The number of times they see each cDNA (the number of reads) corresponds to how much RNA for that gene was in the sample, and the authors compare the amount of RNA for different genes in different groups of people from whom they collected melanocytes.

Next, the authors ranked the known and predicted variants using a method called CAVIAR (CAusal Variants Identification in Associated Regions). CAVIAR is a statistical method used to determine the likely DNA variants causing differences in a trait. This method is better than previous methods used to determine causal variants, because it allows for the idea that there may be multiple causal variants in a region. This is likely to be the case for many traits, possibly including skin pigmentation.

The authors use a statistical approach to determine which gene within 1 Mb (1 million basepairs) of a variant of interest, rs7948623, has expression levels most strongly associated with the variant.

1 Mb is used as the distance to look for genes within because most regulatory regions act on genes that start within 1 Mb.

The authors use allele-specific expression (ASE) analysis, a method to determine how much expression occurs from each allele at a particular locus in an individual.

ASE looks at the amount of RNA that gets transcribed from each copy of a gene (the copy inherited from the mother and the copy inherited from the father).

The authors use this analysis to determine whether people who are heterozygous for the allele of interest (people who have different variants in their two copies of the allele) have different levels of expression from the two copies of the gene, which would indicate that this particular variant could affect the expression level directly.

These numbers refer to the total sample size in the experiment.

In statistics, stratification allows a researcher to divide entire populations in to subgroups.

The authors divide the data set into hilltop and slope, and 3 differently identified groups.

The Paracou experimental site is located near the Paracou Field Station in French Guiana.

Read more about the field station at: https://paracou.cirad.fr/station/overview

The objective of the study is to address whether logging affects the forest species; is there a difference between what types of species and what each species contributes to the community when logged; and how this information can be used to improve how the forest is logged.

Geiger et al. utilized the Pearson's chi-squared test (χ2), a statistical test applied to sets of categorical data to evaluate how likely it is that any observed difference between the sets arose by chance, to conclude the accuracy of the type designations given.

Families that share a larger part of their genome are more likely to be homozygous for certain genes. Studying these families can make it easier to identify and isolate the effects of certain genes.

The authors compared the genotypes of patients who have both autism and epilepsy to determine if these patients had similar mutations to NHE9 and surrounding genes.

A statistical measure of the probability that experimental results are due to chance. It is calculated by looking at the difference between the observed (experimental) results and the expected results (i.e. the results that would be expected if only chance were involved).

The results of the test are reported as a P value, which is a probability. In general, a P of less than 0.05 means that the results of an experiment are statistically significant (and not a result of chance).

This technique is used to study enhanced neuronal activity that may result from changes in gene expression.

Elevated KCl (an increase in potassium outside the cell) results in a sustained depolarized state in three ways:

1. Normally, potassium ions flow out of the cell, resulting in hyperpolarization. Elevated KCl outside the cell disrupts this gradient and slows the outward flow of potassium. At the same time potassium ions are flowing out of the cell, sodium ions are flowing into the cell. The flow of sodium ions into the cell does not slow down.
2. The increase in the cell's membrane potential (the difference in charge on one side of the membrane versus the other) causes sodium channels to open. This allows more sodium ions into the cell and results in further depolarization.
3. Partial activation of sodium ion channels prevents the neuron from triggering a full action potential.

The hippocampus is a major component of the human brain and those of other vertebrates. It is part of the limbic system and has a crucial role in the consolidation of information, including short- and long-term memory and spatial navigation.

Rat and mouse hippocampal neurons are widely used in neurobiological studies. By isolating and growing individual neurons, researchers are able to analyze properties related to cellular trafficking, cellular structure, and individual protein localization.

An array is a grid of DNA samples that is used to identify and map genes.

In this experimental setup, the cDNA derived from the mRNA of known genes is immobilized. The expression pattern is then compared to the expression pattern of a gene responsible for a disease.

https://www.youtube.com/watch?v=pWk_zBpKt_w

Because the three genes were identified by independent screens, it increases the reliability of the authors' conclusions.

A technique used to detect a mutation or abnormality and provide important information on its function. In this case, the authors screened for genes associated with autism.

There are many different types of screens depending on a researcher's needs, and they are widely used in scientific research.

Both the single nucleotide polymorphism array and BAC Comparative Genomic Hybridization arrays are used to detect the number of copies of a specific locus in a subject's DNA. This allows us to find out whether the locus is present on one or both chromosomes of a subject.

To do this, control DNA and experimental DNA are labeled with different fluorescent molecules of different colors (in the picture below, the control is red and the experimental is green).

If the experimental DNA and the control DNA are identical (i.e. the target variant is present on both chromosomes), the sample will appear orange. If the control DNA has deletions, the solution will appear red. It it has insertions, it will appear green.

Based on studies of other neurological birth defects, the authors hypothesized that differences between consanguineous and non-consanguineous families in the M/F ratio of affected children would suggest that autosomal recessive genes play a large part in incidence.

The authors selected families with one or more individuals affected by autism.

Among those families, about half have cousin marriages, which are referred to as consanguineous pedigrees.

A simplex family is one in which there is only one person with autism. A multiplex family has multiple people with autism.

In order to ensure that the results obtained from this study are reliable, the authors ensured that all of the teams were using the same clinical protocol in the same way.

To improve the quality of results, the authors chose consanguineous families (families that share a very recent ancestor), because of their high risk of having autistic children.

Researchers at Johns Hopkins University reasoned that families with multiple females with autism must have special genetic variants for autism that can be more easily identified than when comparing other groups.

For more information, see the Hub at Johns Hopkins.

In this article, the authors focus on patients who inherited long deletions or additions from their parents.

However, this is not the only approach to understanding the genetics of autism. Some look directly at the appearance of de novo single nucleotide polymorphisms (mutations to a single base).

In this table, the author describes how the width and length of the insects proboscis play a role in pollination.

This chart was made to determine the differences in proboscis.

Fishing line was used to simulate repeatedly the collecting of nectar. This could then be used to see which line (stand-in for proboscis) collected the most pollen, and if it correlated with thickness.

In this table, the author describes various interactions the visitor encountered with plants.

This species that will be studied shows complex floral arrangements.

The authors selected families with one or more individuals affected by autism.

Among those families, about half have cousin marriages, which are referred to as consanguineous pedigrees.

A simplex family is one in which there is only one person with autism. A multiplex family has multiple people with autism.

The authors used sgRNAs to target enhanced green fluorescent protein (EGFP) cells.

The EGFP cells allow the cell to express fluorescent color. sgRNAs target these cells and destroy them. In cells where the sgRNA removed the EGFP gene, there is no fluorescent color.

For the first part of their experiment, the authors gathered samples of 18-30 plants from two known populations of C. jimenezii. They then dried the leaf material of the Dominican Republic sample, using Drierite (an all-purpose drying agent most commonly used in storage spaces as it dries the air in the atmosphere). The DNA from these populations was isolated from the dried material using the DNeasy Mini Plant kit; the procedure was similar to the one described in the following video https://www.youtube.com/watch?v=rY-Qbrw9KMc

In this study, the researchers found some questions as to whether the two species of C. jimenezii could be grouped with the same taxa.

The authors used molecular tools which have found a large amount of differentiation. This was not what the authors hoped and in turn it was concluded that they were to remain in separate taxa.

This figure describes the 2 populations of Coccothrinax Jimenezii and it shows the results that are yielded by the processing computer software called STRUCTURE that is used for analysis of microsattelites.

In this experiment the authors used The Bayesian clustering program STRUCTURE v.2.3.4 as a way to estimate the underlying genetic structure among populations.

This experiment was conducted with the purpose of producing a scatter diagram that summarized the original multidimensional data set and revealed the presence of groups. They also used GenAIEx to analyze the principal coordinate among all individuals in the study. This experiment also allowed them to detect the genetic structure of populations projected in a continuous space.

This experiment was done with GenePop v. 4.2 using 10,000 Monte Carlo Markov chain interactions. Throughout this experiment the researcher tested for Hardy–Weinberg Equilibrium, which says that the genotype frequencies in a population tend to remain constant throughout generations if no evolutionary influences are present. They also used GenePop v.4.2. to do a U test and to look for heterozygote excess or deficiency.

This experiment was carried out with the purpose of identifying null alleles which are those that express the same trait whether they are homozygous or heterozygous, and allelic dropouts which are copies of a locus that are not amplified by the primer. This part of the experiment was completed through the use of Micro-Checker v. 2.2.3.

This experiment was conducted using the PERL script program PAL_FINDER v0.02.03 and the 100bp Illumina sequences from the previous experiment. This experiment resulted in the identification of potential 4bp microsatellite repeat elements. Of these microsatellite repeats, only six were selected which had different phenotypes than C.jimenezii.

Proteins in the phototransduction cascade can be in either an "on" (activated) or "off" (inactivated) state. The authors created antibodies to bind to either state to ensure that they would be able to detect the protein regardless of what form it was in.

Basic Local Alignment Search Tool (BLASTX) is a search algorithm developed by the National Center for Biotechnology Information (NCBI)

For more information about BLASTX, go to: NCBI: BLAST

Primers are short, single-stranded sequences of DNA used to amplify RNA sequences of interest using polymerase chain reaction (PCR). Amplifying a sequence means exponentially increasing the number of copies.

A positive control is used to verify that your experiment is working the way you want.

In this study, the authors tested their immunocytochemical test by using it on tissues that they already knew contained the three proteins.

The authors created antibodies against the three proteins so they could detect them in specific tissues using immunocytochemistry.

They incubated squid eyes and light organs with the antibodies and stained with secondary antibodies that were tagged with a fluorescent molecule.

The stained eyes and light-organs were mounted on microscope slides and viewed with a confocal microscope. A fluorescent signal identified the presence of the proteins.

Electroretinograms (ERGs) measure the change in voltage across cells when exposed to a light stimulus. The authors compared the response of photoreceptive tissues in both the eyes and light organs of juvenile Euprymna.

Electrical signals of rhabdomeric photoreceptors typically respond by depolarizing, that is, becoming more negative.

Electrical signals of ciliary photoreceptors typically respond by hyperpolarizing, that is becoming less negative.

The authors looked for evidence that the light organ produces proteins similar to those found in the eye that could generate a phototransduction cascade.

The authors identified 11 sequences that code for proteins similar to those responsible for phototransduction in the eye.

The authors determined that light organs have tissues that are similar to the eye: a lens that is able to focus light, reflective tissue that is able to reflect light, and an iris that can control the amount of light entering or leaving the light organ.

The latitudinal range shift variation among species within four typical taxonomic groups was evaluated in Figure 2. This was compared to the overall variation among all the latitude taxonomic groups in the meta-analysis.

The authors also calculated the percentage of species in each taxonomic group which moved in a direction opposite to that expected based on temperature change.

If species are tracking climate change, then the observed range shifts should equal the expected range shifts. The authors did a chi-square (goodness-of-fit) statistical test to measure how well this 1:1 relationship describes the data.

This correlation test examined the relationship between observed range shifts and expected range shifts (based on temperature change patterns).

For an explanation of how the expected range shifts were calculated, please see the notes for Table S1.

The authors conducted a statistical correlation test to determine if there is a linear correlation (relationship) between range shifts and temperature changes.

The authors did a one-sample t test to compare their range shift rates to those in Reference 14.

The authors conducted the current study to determine if there is a positive trend between observed range shifts and climate warming. They performed a meta-analysis of a very large set of data for diverse species and geographic regions.

The data used in the meta-analysis are summarized in Tables S1a and S1b. Rates of range shift and statistical analyses were calculated as described in the notes for Table S1.

One goal of this meta-analysis was to demonstrate this direct link between temperature change and range shifts.

Fluorescence is used to determine the profiles of the DNA mixtures between the Symbiodinium types.

In this experiment, a faster and alternative method was used in order to accurately genotype the monotypic (one type) Symbiodinium populations. This method was compared to those with DGGE profiles, where they extracted the gel bands and sequenced them based on region 2 of the ribosomal DNA transcribed spacer.

One PCR cycle consists of denaturing, annealing, and extension steps. Denaturing means that the double-stranded DNA is separating into single-stranded DNA. Annealing refers to primers being added to the DNA strand. The extension step is when Taq polymerase adds dNTPs to the annealed primer.

The PCR amplifications exhibited a set of conditions in order to compare the cultures of a HRM analysis to that of a DGGE analysis.

In order to determine if HRM is accurate, onr of the genotypes was used as the sample and the other was used as an unknown to identify if the template concentration affects accuracy of genotyping.

Three different tests were conducted for HRM:

1. Tested out if the template concentration affected the accuracy.
2. DNA from Symbiodinium types of the same clade were combined to identify if it will change melting profiles.
3. DNA from Symbiodinium types of the all clades were combined to identify if it will change melting profiles.

The amplifications were compared based on the best percentage confidence (accuracy) of the specific culture ( HRM vs. DGGE). This was done through a software. In order to calculate the error, the square of the difference was taken between the fluorescence of each reading sample and reference genotype.

A standardized kit was used to extract each culture's DNA, where two replications of the DNA were obtained.

The ITS2 (a specific gene in a ribosome) was then amplified.

The experiment consisted of cultures of the Symbiodinium clades A-E for growing marine algae; the media was replaced (only half of it) with fresh medium every month. They were set at a constant temperature of 25˚C and were exposed under a constant light intensity for 12 hours light and a 12 hour dark period.

Electric fish are able to receive signals and information from emission of electroreceptors in their environment passing through their skin. After the contact of the electroreceptors and the external stimuli, information is relayed in a pattern to the electro-receptory organs of the fish. Since this is an essential part of their way of life, the authors know a large amount of neurons and brain matter are involved in this process. Therefore, scientists hypothesized that in order to ensure this sensory information is relayed efficiently and quickly to the brain of the electric fish, there must be an algorithm used by the neural networks in the fish in order for this process to occur.

The movements that these electric fish use allows for the recognition of an object's features. Evidence from Heiligenberg's stimulation show that when electric fish bend their tails it increases the spatial contrast and makes it easier to distinguish an object's features. While Bacher's 3-D model showed that fish's tail bending help show a clear difference between the object's location and its shape. The BEM stimulation showed that electric fish control their movement in order to regulate their electrosensory system input by demonstrating a stable image of the rostral body which is thought to help the fish to distinguish features.

The boundary element numerical method (BEM) simulator was built by the authors to remedy an issue presented by their standard three-dimensional simulator (color-coded mapping of a stationary fish): only the proximal (close to the center/point of origin) side of the fish's body could be digitized since secondary effects of the body could not be accounted for on the EOD. The BEM simulator addressed this problem by allowing objects under analysis to be bent or randomly shaped via nodes placed on their surfaces, thus giving the BEM simulator the ability to analyze secondary effects and other regions of the fish's body.

The author is explaining here that the fish have a certain mechanism in their body that allows them to move much more fluently, whether forwards or backwards, and allows them to wrap around objects while not compromising the information they get from their electroreceptors. The mechanism that allows them to do this is done by keeping their bodies rigid and only moving their dorsal or ventral fin.

• "Wave" fish have longer discharges when it comes to EOD's and continuous charges, "pulse" fish however have silent intervals between discharges.
• This experiment, as the author illustrated above, allows for the statistical analysis of the EOD discharges rather than the collective qualitative data that stood in its place.
• With this experiment, the waveforms created by the EOD's are affected by their location and proximity to other objects, and although in the charts both fish have many similarities, it seems the further the fish, the easier it becomes to tell the wavelength between both fish apart.
• Thanks to this study, it is no longer difficult to explain the results of this experiment, previously there were no numbers to support claims, but now the authors have helped to provide some numerical values to this type of research.

Electric organ discharge (EOD) potentials, which are generated by electrodes located near the head and tail of an electric fish, are typically difficult to analyze due to variations among different species and the inconsistent geometry of the EOD spatial patterns. Thus, to overcome this obstacle, the authors devised a system for the visual representation of EOD potentials to facilitate analysis. This was achieved by the creation of a robotic arm that recorded the EOD of an immobile electric fish at multiple positions around its body. The motionless state of the fish also enabled the authors to capture the exact times of numerous EODs. Each EOD measurement collected from the arm was then digitally processed and converted into a color-coded map overlaid on a diagram of the fish's body for further research/analysis in the phenomenon known as electrolocation.

Statistical analysis such as linear mixed models were used to demonstrate if the trends in the timing of phenological events were associated with the temperature during the summer.

Two types of measures were used to calculate the time of phenological events. One of them was thaw degree days (TDD) which was able to show how much heat was produced from snowmelt until the phenological response occurred. The other measure was done by comparing the slopes of each species-subsite. The slopes represented the time of the phenological event and the year or temperature it took place. One of the advantages of this measure is that it shows the comparison between species and sites.

The different locations used was categorized based on climate zones which were high Arctic, low Arctic, and alpine. They were also categorized as dry, moist, or wet.

The average temperature for spring and summer times within a year were used to analyze temperature change throughout the experiment.

The plant phenology was compared with the mean monthly air temperatures.

Used to show the most accurate average of the temperatures.

The data used for the weather was gathered from the specific site. However, in some places such as Finse, Norway, where the weather data was not available for a period of time, the averages from previous years was used.

The plants were ranked based on the way they looked.

The plants' flowers and leafs were measured once or twice a week.

Plant phenology changes were measured using trends and interannual variations.

The success rate of the pollination was determined by recording the fruit produced by visited flowers. 15 potted plants having 1-3 open flowers were studied over 20 days, and a new set of plants was used every day. 69 total visits to over 400 flowers were observed throughout the course of the experiment.

For this experiment, the authors wanted to determine which was the best pollinator in relation to effectiveness. They grew 15 plants in the greenhouse and then placed them at the site with the highest number of visitors. Over 20 days, a single visit by pollinators was allowed for each individual flower. Bags were placed on the flowers whenever they were not being studied so as to avoid pollinator visits.

In this experiment, fresh flowers were pollinated using four fishing lines of different diameters to simulate different proboscis diameters. The fishing lines were inserted into the floral tube in order to collect pollen. Then, the length of the fishing lines were stained blue. The fishing lines were re-inserted and the pollen that attached were stained blue. The same fishing lines were then inserted into other fresh flowers.

The authors counted average number of pollen grains per group, as well as time spent at each flower, and the behavior of the pollinator after leaving the flower.

All of these metrics are important to pollination efficiency.

The authors use the word 'haphazardly' to indicate randomness in the sampling of the flowers. It is important to have randomness to avoid bias.

This species has no fragrance and uses nectar as a reward with 30-67% sugar concentration as the reward.

The authors aimed to determine both the genotype and the phenotype of the plants to determine which traits (phenotype) contributed to successful invasion, and how the diversity of the plants at the leading edge changes with gap size (determined by number of genotypes present). Comparing the leading edge and the back allows for determining the effect of invasion on population evolution.

The question of how evolution occurs in patchy landscapes was addressed by testing both evolving and non-evolving populations in environments in which there was space between the habitable spaces in order to grow. Gaps simulated barriers in landscape which may require certain traits to overcome.

One of the questions addressed in the study is how evolution affects the spreading of plants. To test this, plants in the evolving condition were allowed to spread seeds, and then the seeds grew into the next generation. In the non-evolving condition, the new seedlings were replaced with seeds randomly drawn from the source population. This difference allows for determining if the traits the seeds carry with them are important for how fast they spread.

The experiments were designed to mimic real-life invasion using a one dimensional (linear) model. Pots filled with soil are places where seeds can grow, while empty pots act as barriers to invasion, resembling a fragmented landscape. The setup allows for the researchers to have precise control over as many variables as possible, and the linear array makes tracking of invasion progress simpler.

The authors wanted to test whether ticklishness in rats is mood dependent, as it is in humans.

To do this, they used bright lights and height to trigger anxiety in the rats. They then recorded USVs and the neuron firing rate while tickling the rats under these conditions.

SEM is the standard error of the mean. It is related to standard deviation and provides information about the likelihood that the studied sample represents the whole population.

A paired t-test is used to compare two measurements (in this case ventral gentle touch vs. ventral tickling) to see if they are significantly different. A P-value of 0.05 or less is an indicator of statistical significance.

The authors tickled rats while recording their behaviors and vocalizations.

A spectrogram is a visual representation of sound waves. It provides quantitative information about the pitch and volume of the rat calls.

By looking at spectrograms the researchers sorted the vocalizations into three categories.

The authors made a series of test-pits in order to follow the predicted direction of the footprints.

The authors used the size and shape of the footprints to infer body mass, stature, and walking speed for four of the individuals (S1, G1,G2, and G3)

The influences of floral density and the abundance of flowers featuring deep corollas are used to identify the advantage that a generalist (short-tongued) bumble bee would have over a specialist (long-tongued) bumble bee where bees have the same flight speed. Pink areas denote conditions that favor generalists.

This model was adapted from a model that explained the effects of floral density on the composition of pollinators. The means by which the model that was adapted from to produce this model can be found at:

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3825104/

A list of materials and methods used to produce this figure is found at:

http://science.sciencemag.org/content/sci/suppl/2015/09/23/349.6255.1541.DC1/Miller-Struttmann-SM.pdf

These results show that the peak flower density of the habitat of the bumble bees is mostly decreasing, causing more competition for available nectar to ensue among the bees.

The researchers analyzed differences in bumble bee diets on Mount Evans and Niwot Ridge, between the 1960s and presently around 2011. Fewer bee visits were recorded during the more recent survey, but it appears that the bees have an expanded range of plants in their diet. This diet includes flowers that have shorter and more varied depths.

B. balteatus and B. sylvicola are the most common bumble bee species at the three research sites in the central Rocky Mountains. The sites are Mount Evans, Niwot Range, and Pennsylvania Mountain. To analyze the change in tongue length over time of both species at the sites, recent specimens from 2012-2014 were compared to older specimens from 1966-1980.

It is known that climate change is impacting compatibility of mutualistic species. However, it is unknown which specific mechanisms of the mutualistic relationship are being affected. Using historical data the authors measured flower abundance shifts due to climate change and their effects on foraging behaviors by the bees studied.

The authors wanted to look at the relationship between neural activity and USV production. However, they needed to remove the possibility that both of these things are independent responses to tickling.

For this reason, they carried out the experiments during breaks, when USVs and increased neuronal activity were occurring, but tickling was not a factor.

The authors observed that USV production and neuron firing change in the same ways in response to tickling.

In this set of experiments they wanted to see if there was also a causal relationship. In other words, is the neuronal activity triggering the production of sounds or do they just happen to occur at the same time?

The authors of this study analyzed the new set of footprints found at the Laetoli site. Their goal was to compare their results with earlier work in determining stature, morphology, and degree of sexual dimorphism of the individuals leaving the tracks.

This paper investigates a means to optimize carbon storage by understanding the diversity of the mechanics and use of plant life as carbon sinks in order to lower atmospheric CO2.

The author used data collected from each plot to produce a fraction to estimate the carbon accumulation in the soil, on the surface (0 to 20 cm) and at a deeper level ranging from 20 to 100 cm, over time. Using that fraction, the author created an equation that would estimate the amount of carbon accumulating in the soil over a 50-year period.

In an experiment conducted by P. B. Reich and others in 1997, the effect of increased nitrogen deposits, increased atmospheric CO2 levels, and decreased species richness on plant communities was observed. The author used only the data from the CO2 concentrations and Nitrogen treatments for this research study. With this data the author was able to calculate carbon storage in the BioCON plots because plants store carbon through the accumulation of biomass. CO2 and nitrogen are vital components in the chemical pathways plants use to add on biomass.

The author used C4 grasses, C3 grasses, legumes, and other forbs, in this experiment, as a common variable between all experimental plots. The author mixed the native species, to the American grassland, and a variety of 18 other plant species. The author randomly selected varying levels of species richness, for each plot, by introducing 1, 2, 4, 8, or 16 different plant species. Each mixture of species richness was replicated in 30 or more plots to produce multiple trials of the same level of species richness to produce an average.

The marginal increase of carbon was estimated for each increasing level of species richness. The model data calculated from equation (2) was bounded by the actual data collected from the experiment in each plot.

The equation above was used by the author to calculate the total amount of carbon, in the soil and ecosystem, between the varying species richness in each plot. The a and b values were parameters calculated, by equation 1, to measure the amount of carbon in the plants and the soil for a 50-year simulation. Using the parameters of a and b and the different amount of specie richness (ranging from 1 to 16), in each plot, the total amount of carbon in the ecosystem was determined.

The author used the equation above, the Metropolis-Hastings algorithm, to calculate the difference between the observed and modeled data of carbon accumulation in the soil for each year the carbon soil data was provided. The equation generated a variety of accepted i and k values. The author then calculated the average i and k values with the smallest J value (best fit for observed data). Using the average i and k values that were calculated, the author was able to find the amount of carbon accumulated, at both the surface and deeper level of the soil, over a 50-year period. The author assumes the calculations to be within a 30% accuracy of the actual amount of carbon in the soil.

For the BioCON experiment, the author used soil carbon data collected from each plot at the beginning of the experiment and the 5 and 10 years after the introduction of varying species richness (from a 0 to 60 cm depth). The author then estimated the amount of carbon in the soil, from 0 to 100 cm depth, by using carbon soil depth distribution data, for 20 cm increments up to a 1 meter depth. Using the data from the BigBio experiment, the author developed a proportion that helped determine the amount of carbon in the soil up to a meter depth for the BiCON plots.

The author used data collected on carbon accumulation in the soil from the Cedar Creek Ecosystem Science Reserve website to obtain estimated parameters for: i) the constant rate of decomposition of plants, per year (k) and ii) the annual input of carbon into the soil. In the BigBio experiment, the author used data, on carbon content in the surface of the soil, from years 0, 1, 5, 7, 9, 11 for all plots, and year 10 for some plots. The author also collected data, of deeper soil carbon content, from years 0 and 11.

The soil in all plots was treated before the experiment was conducted. Methyl bromide was applied to the BioCON plots and the first 0 to 5 centimeters of soil was relocated in the BigBio plots. The author either treated the soil or relocated it to make sure any previously existing seeds would not change the species richness of each plot. The addition of plant species not recorded in the experiment would influence the amount of carbon storage occurring in each plot. This could possibly skew the data collected over the duration of the experiment. The difference in pretreatments between BioCON and BigBio could have contributed to the different rates of carbon accumulation between the two experiments.

A previous research study, wrote by D. P. Xiong, suggested that the presence of grazing animals influences grassland carbon storage. By consuming plants, grazing animals decrease the total amount of biomass in the American grasslands thereby decreasing the amount of carbon storage in an environment. The author decided not to take into account the effect grazing animals had on carbon storage and only looked at the effects of plant diversity on carbon accumulation.

The idea of using C4 grasses, C3 grasses, legumes, and other forbs across all plots in this study was inspired by the works of leading scientists D. A. Fornara and D. A. Wedin. By using the native species in all plots, the author was able to concluded that any disturbances, when considering carbon storage, across the plots was due to the varying levels of species richness. The author used the differences in carbon storage as data during the experiment's analysis, to find out the correlation between increased species richness and its effect on carbon storage.

For BioCON, the author used 2 m x 2 m subplots to see the effects of increased species richness on carbon storage. The author randomly chose 32 identical species mixtures from the experimental plots in E120 with varying levels of species richness. 15 plots were given a mixture of 4 different species and 12 plots were given a mixture of 16 different plant species.

A previous work, drafted by D. Tilman and coworkers, suggested the experimental outlay of this research study. By using 342 plots, in Cedar Creek Ecosystem Reserve in Minnesota, United States, the author was able to see the relationship between increased species richness and its effect on carbon storage in the American grassland. The author started in 1994 and used the 13 m x 13 m plots as the experimental group in this experiment. These plots were subjected to varying levels of species richness and observed the carbon uptake response. The central 9 m x 9 m plots were used as a control group because the species inhabiting the plots and plant diversity were constantly maintained.

The author used the observation of increased plant growth to measure the amount of carbon being sequestered by the plants.

For soil, the author used data collected over a 50-year period, on soil carbon levels and plant productivity, to measure to total amount of carbon accumulated when introduced to increased species richness. The author was then able to create a fraction, used in later equation (1), of carbon content to estimate the amount of carbon in the soil during the experiment.

The author used data collected from the American grasslands, with increased plant diversity, to see if there was an increase in carbon uptake, in the environment, compared to the control group's carbon content.

Using the valuation of carbon the author then estimated the economical worth of the carbon storage in the experimental fields in order to graph the results to show a correlation.

The author collected data, from two different American grassland fields with varying levels of plant species diversity for over ten years, on the amount of carbon in both the plants and the soil.

In multiple research papers, written by leading scientists D. A. Fornara and P. B. Reich, the results show that increased plant diversity, in grassland environments, increased the carbon content in both plants and soil. The data in this research paper correlates with the past findings that an increase in species richness, in American grasslands, increases carbon storage in an ecosystem over time.

The author used the data collected to find the change in the amount of carbon, in the American grassland fields, when exposed to increased plant diversity. The author then used data on the cost of carbon, by the Interagency Working Group and a previous research study conducted by the United States Government, to calculate the economical worth of the carbon stored in the American grassland fields.The previous research study gave the author insight into the how to assign a dollar total amount to carbon in the American grassland fields.

As from the Supplementary Material, the manual analysis described here can be broken down into the following steps:

• Experts search websites such as VK.com for common hashtags and keywords on a daily basis.
• A manual list of aggregates, which was updated daily, was assembled by the experts to include only those aggregates appearing to express a strong allegiance to ISIS.
• To find newly created aggregates, the experts analyze posts and reposts among known aggregates, as well as follow selected profiles that actively publish ISIS news.
• Newly found aggregates were included in the authors' database.
• The database of aggregates was analyzed on a daily basis to determine which aggregates were still active and which were shut down.

Starvation is a state in which the body responds to long periods of fasting. The body then burns fatty acids and lipid reserves, along with small amounts of muscle tissue to provide the brain with an energy source of glucose.

INSr is a gene that encodes for a cell surface receptor, also known as tyrosine kinase. Binding of insulin initiates the insulin signaling pathway, which regulates how glucose is absorbed by muscle and fat cells. FOXO is a series of transcription factors, which are proteins that control transcription of genetic information from DNA to messenger RNA. FOXO transcription factors are responsible for regulating which genes are expressed, and these transcription factors are also responsible for signaling apoptosis, or cellular suicide, when a cell is damaged beyond repair.

To account for an initial burst of energy, that gives an initial burst of speed.

The following formula was used to determine the maximum swimming speed for each of the fish. The measurements needed are the fork length of a fish, its stride length, and its tail-beat frequency.