1,417 Matching Annotations
  1. May 2018
    1. Fig. 7. The effect of elevated atmospheric CO2 concentration (550 ppm, 850 ppm and 950 ppm) on cumulative (A) NEE, (B) Reco and (G) GEE, at TS. The influence of rising temperatures (1°C, 2.7°C and 4.2°C) on cumulative (B) NEE, (E) Reco and (H) GEE and shifts in seasonal and annual precipitation patterns (−2%, +7% and +14%) on cumulative (C) NEE, (F) Reco and (I) GEE. Atmospheric convention is used here and positive numbers indicate a loss of C to the atmosphere. All simulations were compared to current weather and atmospheric CO2concentration (red line).

      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.

    2. Fig. 5. Observed versus modeled soil temperature at (A) TS and (B) SRS, and soil volumetric water content (VWC) at (C) TS and (D) SRS.

      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.

    3. ran the model for 100 years (1) under climate change projections,

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

    4. Fig. 4. Climate change scalars for (A) elevated atmospheric CO2 concentration, (B) air temperature, and (C) precipitation. The distributions for (D) minimum temperature, (E) maximum temperature and (F) precipitation were modified to match projected seasonal change.

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

  2. Apr 2018
    1. We computed anomaly fields using all data and compared these results with computed fields on the basis of data that did not include values exceeding 3 SDs.

      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.

    2. we used a 6-SD check to flag data as not being usable in this study as compared to the 3-SD check used earlier.

      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.

    1. biological, rather than physical, processes drove reach-scale rates (table S5)

      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.

    2. litterbag

      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.

    3. pools of benthic fine and coarse POC declined

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

    4. consideration of differences among litter species and potential divergence in rates due to the degree of biological processing

      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.

    5. Our results generally support the use of litterbags to measure larger-scale C dynamics

      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.

    6. Higher C loss rates at the litterbag scale than the reach scale are expected, because litterbags track distinct parcels of C, whereas reaches receive additional C inputs over time.

      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.

    7. We conducted two manipulative experiments at large spatial and temporal scales and focused our measurements on forest-derived leaf litter, because it is the most biologically active pool of terrestrial C in forest streams and is renewed annually (7).

      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.

    8. not been previously assessed in response to human-influenced stressors

      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.

    9. We measured the response of terrestrial C loss rates in whole 70- to 150-m stream reaches (tables S1 and S2).

      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.

    10. flow-proportional nitrogen (N) and phosphorus (P)

      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.

    1. using primers specific to the cDNA encoding each of these proteins, we performed RT-PCR on 7 tissues of the adult host, including those that are and those that are not dedicated to light modulation

      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.

    2. To determine whether they also co-localize in light-organ tissues, we applied 2 independent analyses of these 3 components: localization of message by PCR and of protein by immunocytochemistry.

      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.

    1. A GWAS analysis with linear mixed models, controlling for age, sex, and genetic relatedness (9), identified four regions with multiple significant associations

      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.

    2. using the Illumina Infinium Omni5 Genotyping array

      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.

    3. To estimate the proportion of pigmentation variance explained by the top eight candidate SNPs at SLC24A5, MFSD12, DDB1/TMEM138 and OCA2/HERC2, we used a linear mixed model with two genetic random effect terms, one based on the genome-wide kinship matrix, and the other based on the kinship matrix derived from the set of significant variants.

      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.

    4. We do not detect evidence for positive selection at MFSD12 using Tajima’s D

      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.

    5. luciferase expression assays

      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.

    6. CRISPR/Cas9 was used to generate a Mfsd12 null allele in a wild-type mouse background

      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.

    7. We silenced expression of the mouse ortholog of MFSD12 (Mfsd12) using small hairpin RNAs (shRNAs) in immortalized melan-Ink4a mouse melanocytes derived from C57BL/6J-Ink4a−/−mice

      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.

    8. using local imputation of high coverage sequencing data from a subset of 135 individuals and data from the Thousand Genomes Project (TGP)

      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.

    9. We then performed fine-mapping

      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.

    10. We genotyped 1,570 African individuals with quantified pigmentation levels

      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.

    11. To identify genes affecting skin pigmentation in Africa, we used a DSM II ColorMeter to quantify light reflectance from the inner arm as a proxy for melanin levels in 2,092 ethnically and genetically diverse Africans living in Ethiopia, Tanzania, and Botswana

      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.

    12. Exome sequencing of an archived gr/gr DNA sample, subsequently confirmed by Sanger sequencing in an independent colony,

      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.

    13. We targeted transmembrane domain 2 (TMD2) in the highly conserved zebrafish ortholog of mfsd12a with CRISPR/Cas9

      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.

    14. We assessed the localization of human MFSD12 isoform c (RefSeq NM_174983.4) tagged at the C terminus with the HA epitope (MFSD12-HA). By immunofluorescence microscopy,

      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.

    15. Analyses of gene expression using RNA-sequencing data from 106 primary melanocyte cultures

      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.

    16. We ranked potential causal variants within each locus using CAVIAR

      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.

    17. Association tests using a permutation approach indicated that, of the 35 protein-coding genes with a transcription start site within 1Mb of rs7948623, expression of DDB1 is most strongly associated with a SNP in an intron of DDB1, rs7120594, at marginal statistical significance after correction for ancestry and multiple testing (Padj = 0.06

      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.

    18. Allele-specific expression (ASE) analysis

      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.

    1. The resulting database contained 4140 individuals and over 2500 herbarium vouchers.

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

    2. We therefore stratified our study design such that each habitat was sampled once within each of the six combinations of two topographic positions (hilltop and slope) and three taxonomic blocks, for a total of 18 samples.

      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.

    3. Paracou experimental site (5°18′N, 52°55′W), a lowland tropical rain forest near Sinnamary, French Guiana (Gourlet-Fleury et al. 2004)

      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

    4. (i) How does logging disturbance affect tropical tree community structure, in terms of diversity, evenness and composition? (ii) How do the taxonomic and functional responses of tree communities to logging differ? (iii) What guidelines can we give to timber harvesters to improve biodiversity conservation in selectively logged forests?

      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.

    1. We performed a x2 test on the proportions of individuals with the A or B chloroplast haplotype per site (table 1) to verify that our type designations, which were classified according to the results of the Williams studies (Williams et al. 2005, 2007) and following their site locality sampling, were correct.

      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.

    1. homozygosity mapping provides an important approach to dissect this heterogeneity

      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.

    2. we sequenced NHE9 in other patients with autism and epilepsy

      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.

    3. binomial test

      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).

    4. neuronal membrane depolarization by elevated KCl

      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.
    5. hippocampal neurons

      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.

    6. microarray screens

      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.


    7. independently identified

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

    8. screens

      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.

    9. two sensitive methods for detecting them

      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.

    10. we reasoned that a prominent involvement of autosomal recessive genes in autism would be signaled by differences in the male-to-female (M/F) ratio of affected children in consanguineous (related) versus nonconsanguineous marriages (although recessive causes of autism may still retain some gender-specific difference in penetrance)

      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.

    11. The Homozygosity Mapping Collaborative for Autism (HMCA) (21) has recruited 104 families (79 simplex and 25 multiplex) from the Arabic Middle East, Turkey, and Pakistan (table S1 and fig. S1), of which 88 pedigrees (69 simplex and 19 multiplex) have cousin marriages (i.e., parental consanguinity).

      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.

    12. Reliability between clinician assessments was high

      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.

    13. homozygosity mapping

      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.

    14. de novo

      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).

    1. Table 4. Proboscis measurements (mean and standard error) for flower visitors to A. berteroi. Proboscis width and length with the same letters are not significantly different with Tukey comparisons.

      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.

    2. We then used monofilament nylon fishing line of four different diameters (4 lb, 0.20 mm diameter; 6 lb, 0.23 mm diameter; 8 lb, 0.28 mm diameter and 25 lb, 0.53 mm diameter) inserted into single flowers to simulate flower visits.

      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.

    3. Table 1. Flower visitors of A. berteroi observed in the study sites, and presence/absence of pollen on the proboscis.

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

    4. Angadenia berteroi bears large, showy, yellow, tubular flowers. They have the typical complex floral arrangement

      This species that will be studied shows complex floral arrangements.

    1. The Homozygosity Mapping Collaborative for Autism (HMCA) (21) has recruited 104 families (79 simplex and 25 multiplex) from the Arabic Middle East, Turkey, and Pakistan (table S1 and fig. S1), of which 88 pedigrees (69 simplex and 19 multiplex) have cousin marriages (i.e., parental consanguinity)

      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.

    1. we tested six sgRNAs targeting enhanced green fluorescent protein (EGFP)

      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.

  3. Mar 2018
    1. The two known populations of this species were included in our study, and we sampled 18–30 individuals per population (Table 1). All of the individuals (18) from the Dominican Republic population were included in the analyses. Leaf material was fast dried in the field using Drierite (W. A. Hammond Drierite Co. Ltd., Xenia, Ohio, USA), subsequently this material was used for DNA isolations using the DNeasy Mini Plant kit (QIAGEN, Venlo Limburg, The Netherlands).

      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

    2. The high levels of genetic differentiation detected within C. jimenezii raise questions whether these two populations can be treated as different varieties/subspecies

      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.

    3. Fig 2. Principal coordinate and STRUCTURE (K = 2) analyses of DNA microsatellite data for the two known populations of Coccothrinax jimenezii. The scatter diagram shows PCO values along the first two coordinates with their respective percentages of variance. Inset in upper right corner shows results yielded by STRUCTURE. Color and box sizes indicate the cluster type of each individual and the number of plants sampled per site. The vertical lines indicate the probability that each individual belongs to an inferred cluster. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

      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.

    4. The Bayesian clustering program STRUCTURE v.2.3.4

      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.

    5. A Monte Carlo Markov chain method was applied with 100,000 iterations, a burn-in of 10,000 and the significance level set at P < 0.001. Principal coordinate analysis (PCO) among all the individuals included in our study was computed with GenAlEx based on the algorithm developed by Orloci (1978) after conversion of the individual-by-individual genetic distance matrix, as defined by Smouse and Peakall (1999), to a covariance matrix and data standardization.

      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.

    6. Tests for Hardy–Weinberg Equilibrium (HWE) and the U test (Rousset and Raymond, 1995) for heterozygote excess or deficiency were run with GenePop v. 4.2 (Raymond and Rousset, 1995, 2008) using 10,000 Monte Carlo Markov chain iterations (Guo and Thompson, 1992).

      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.

    7. The program Micro-Checker v. 2.2.3 (Van Oosterhout et al., 2004) was used to evaluate the presence of null alleles and allelic dropouts, employing 3000 randomizations. Descriptive statistics

      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.

    8. PERL script program PAL_FINDER_v0.02.03 to identify potential 4 bp microsatellite repeat elements among the reads (Castoe et al., 2012; Slashdot Media, San Jose, California, USA). Among these SSR loci we selected six that cross-amplified with samples of C. jimenezii and that were polymorphic with different samples of this species.

      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.

    1. he peptide was a mixture of phosphorylated and unphosphorylated serine in position #357, so that antibodies might be generated to both the activated and non-activated forms of the molecule

      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.

    2. Using the cDNA sequences, we first used NCBI BLASTX analyses to identify the closest matches to the derived amino acid sequences

      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

    3. RACE primers (Table S2) were constructed from the EST sequences identified as having similarity to a transcript of interest.

      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.

    4. Retinal tissues of E. scolopes were used as a positive control for the cross reactivity of these antibodies in regions known to produce these proteins

      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.

    5. we used antibodies raised against cephalopod opsin, arrestin, and rhodopsin kinase (25, 26) to localize the protein in host tissues.

      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.

    6. we performed electroretinograms (ERGs) (21, 22), which extracellularly record photoreceptor membrane potential, of both eyes and light organs of juvenile E. scolopes.

      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.

    7. We identified 11 such cDNAs (Fig. 2; Table S1), including the gene encoding the visual pigment opsin itself, as well as molecules involved in subsequent activation and deactivation of the cascades.

      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.

    8. tissues that modulate the intensity and direction of symbiont light emission

      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.

    1. Much greater variation is associated with differences among species within a taxonomic group than between taxonomic groups (Fig. 2 and table S2)

      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.

    2. nearly as many studies of observed latitudinal changes fall above as below the observed = expected line in Fig. 1A

      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.

    3. To estimate the expected shifts, we calculated the distances in latitude (kilometers) and elevation (meters) that species in a given region would have been required to move to track temperature changes and thus to experience the same average temperature at the end of the recording period as encountered at the start (18) (table S1)

      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.

    4. mean latitudinal shift versus average temperature increase

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

    5. whereas the rates of range shift that we found were significantly greater [N = 22 species groups × regions, one-sample ttest versus 6.1 km decade−1, t = 3.99, P = 0.0007 for latitude; N = 30 groups × regions, one-sample t test versus 6.1 m decade−1, t = 3.49, P = 0.002 for elevation

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

    6. We considered N = 23 taxonomic group × geographic region combinations for latitude, incorporating 764 individual species responses, and N = 31 taxonomic group × region combinations for elevation, representing 1367 species responses. For the purpose of analysis, the mean shift across all species of a given taxonomic group, in a given region, was taken to represent a single value (for example, plants in Switzerland or birds in New York State; table S1)

      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.

    7. evidence has previously fallen short of demonstrating a direct link between temperature change and range shifts

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

    1. difference plots clearly show the distinct profiles obtained for the mixtures

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

    2. an alternative technique to rapidly and accurately genotype monotypic Symbiodinium populations.

      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.

    3. The touchdown protocol consisted of an initial denaturing step at 92 "C for 3 min, 21 cycles at 92 "C for 30 s, 62 "C for 40 s, and 72 "C for 30 s, decreasing each cycle 0.5 "C, followed by 15 cycles with a 52 "C annealing step and a final extension at 72 "C for 10 min.

      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.

    4. PCR amplification had the following conditions

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

    5. For each genotype, one of the samples was used as the reference genotype, while the other was treated as an ‘unknown.’

      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.

    6. To understand potential limitations of the HRM technique, three tests were conducted.

      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.
    7. The rest of the samples were assigned to a genotype based on the percentage of confidence

      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.

    8. DNA extractions were carried out using DNeasy# Plant Mini kit (Qiagen)

      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.

    9. Symbiodinium cultures of clades A–E were obtained from Dr Scott Santos

      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.

    1. Therefore, a considerable volume of the electric fish brain is devoted to electrosensory processing. For the computational algorithms proposed above to be involved in electrolocation, they must have a plausible neural implementation in the fish’s nervous system. We propose one such projection onto the neural networks in the electric fish brain.

      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.

    2. The scanning or probing movements have also been hypothesized to help recognize object features.

      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.

    3. To address these limitations and to simulate exploratory behaviors further, we built a complementary three-dimensional BEM electric fish model.

      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.

    4. This allows the fish to swim equally well forwards or backwards and to hold the body in an arc around objects (Bastian, 1986; Toerring and Belbenoit, 1979) while maintaining rigid control over the electroreceptive surfaces. Presumably, by keeping the detector array in a fixed orientation with respect to field generation, this controlled body motion reduces the number of variables that must be taken into account to interpret electrosensory information.

      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.

    5. To date we have mapped the EODs of three gymnotiform wave species and seven gymnotiform pulse species. These maps, for the first time, clearly illustrate the full spatiotemporal structure of the EOD (Fig. 1). In the majority of species, the EOD waveforms vary greatly with location, revealing considerably more complex patterns than were previously appreciated.
      • "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.
    6. We have developed a powerful system for mapping EOD potentials and electric field vectors in three dimensions.

      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.

    1. To determine whether observed trends in the timing of phenological events were associated with summer temperature trends, we tested the relationship between (βDOY_x_YEAR) with the summer temperature trend (βDOY_x_TAIRSUMMER) for each species at each subsite using linear mixed models, with site, subsite (nested within site) and species as random factors in JMP.

      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.

    2. Because site effects such as latitude, elevation and species traits have strong influences on the calendar date that a phenological event occurs, we did not use the DOY associated with a phenological event as a direct measure of phenological response. Instead, we used two types of measures that are largely independent of the site-specific properties (table 2). First, we calculated the TDD from snowmelt until the occurrence of the phenological event for each species-plot combination. This measure reflects the amount of heat accumulated from snowmelt until the phenological event was observed. Second, for each species-subsite combination, we calculated the slopes (β) of the relationships between the timing of the phenological event (represented as DOY or TDD) and the calendar year or site temperature (measured as air temperature of the spring or 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.

    3. To evaluate potential differences in species responses among locations, sites were categorized into climatic zones as in previous syntheses [11,22,23]: high Arctic, low Arctic or alpine. Subsites were categorized as dry, moist or wet, where dry refers to plant communities on well-drained, mineral soils typically located on ridges, moist refers to sites with some soil drainage, and wet refers to plant communities with water tables frequently near or above the surface.

      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.

    4. Consequently, we used mean temperatures of month combinations (spring = April–May and summer = June–August temperatures) as the basis of the temperature analysis.

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

    5. Mean monthly air temperatures for the months preceding the growing season and months of the growing season (April–August) were calculated for each study site each year for comparison with plant phenology.

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

    6. A cubic spline interpolation

      Used to show the most accurate average of the temperatures.

    7. The weather dataset was based on data collected at the sites

      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.

    8. A priority-ranking lumping scheme that accounted for differences in plant morphology was used to consolidate phenological variables, although for a given species at a subsite, the phenological definitions were consistent over time.

      The plants were ranked based on the way they looked.

    9. Flowering and leafing stages were compiled from most sites at an observation resolution of one to two times per week.

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

    10. Our approach was to use long-term trends and interannual variability across the ITEX control plots to evaluate change in plant phenology in relation to temperature.

      Plant phenology changes were measured using trends and interannual variations.

    1. Pollination success was quantified for these same flowers by recording the fruit production of visited flowers on the potted plants, maintained in the greenhouse. We placed at least 15 plants per day, each with one to three open flowers, over 20 days of observations, using a new set of plants each day. We recorded a total of 69 visits to over 400 flowers observed in this potted plant placement experiment. Pollination efficiency of each visitor group was assessed by comparing the percentage of visited flowers that produced fruit after a single visit.

      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.

    2. To determine the most effective pollinator, we placed 15 greenhouse-grown potted plants in the field to quantify pollination success at Site 3, the site with the highest visitation frequency (B. B. Roque, personal observations). On 20 different days during the flowering period, we compared the qualitative effectiveness of the different pollinator groups by allowing a single visit to individual flowers on the potted plants. Flowers that were ready to open prior to observation periods were bagged, while in bud, to exclude visitors. At the time of observation (from 9:00 am to 12:00 pm), bags were removed and flowers exposed to foraging insects. For a specific flower, pollinator visits were restricted to a single visit by one individual from one of the four groups of pollinators. After visitation, a flower was labelled (by pollinator group) and bagged to exclude subsequent visitors.

      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.

    3. To examine a possible relationship between line thickness and pollen deposition, we hand pollinated fresh flowers using fishing line of four different diameters. Each thickness was inserted into a fresh flower to the bottom of the corolla tube to collect pollen (as above); we then stained entire length of the fishing line with methylene blue to stain the adhering pollen grains and introduced the stained portion into another new fresh flower.

      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.

    4. To quantify the efficiency of each visitor group, we estimated pollen on the visitor mouthparts as the average number of pollen grains per individual visitor of each group.

      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.

    5. We haphazardly selected plants with open flowers for each of the intervals.

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

    6. The flowers have no notable fragrance, and offer viscous nectar as a pollinator reward, with the sugar concentration of the nectar ranging from 30 to 67 %

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

    1. individuals at the leading edge and back of the invasions were genotyped, and traits of all 14 genotypes were measured.

      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.

    2. separating individual pots of suitable habitat by gaps that were 0 (continuous landscapes), 4, 8, or 12 times the mean dispersal distance.

      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.

    3. In evolving populations, the resulting plants produced seeds, which dispersed across the array (assisted via a simulated rain event), constituting the next generation of the population (Fig.

      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.

    4. spreading through continuous and fragmented landscapes, each consisting of a linear array of rectangular pots

      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.

    1. To test whether neuronal responses to tickling are also modulated by such conditions, we tickled rats in both control (Fig. 3A, left) and anxiogenic settings, such as under bright illumination and on an elevated platform (Fig. 3A, right).

      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.

    2. (ventral tickling, 4.45 ± 0.28 Hz; ventral gentle touch, 2.58 ± 0.21 Hz; n = 16, P < 0.001; mean ± SEM, paired t test).

      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.

    3. rats rapidly approached the tickling hand, and tickling induced unsolicited jumps accompanied by 50-kHz USVs (Freudensprünge, “joy jumps”; movie S2), which can be seen in joyful subjects in various mammalian species (14–16). We visually categorized spectrograms of an extensive set of USVs (34,140 calls) into modulated, trill, combined, and miscellaneous call types (Fig. 1Band fig. S1).

      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.

    1. Hominin and non-hominin tracks were recognised in four test-pits at Site S, namely L8, M9, TP2 and M10.

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

    2. Consequently, we focused our interpretations on the more appropriate predictions inferred from the relationship between foot size and body dimensions in Australopithecus

      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)

    1. Fig. 4. Relative advantage of generalizing as a function of flower density and the proportion of deep flowers in the community. Outcomes with flight speed of 0.5 m s−1 are shown (15). The generalist is favored when its relative advantage is >1 (pink shading).

      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:


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


    2. Fig. 3. Change in flower abundance at landscape and local scales along a 400-m altitudinal gradient on Pennsylvania Mountain. (A) Map showing areas where PFD decreased (1.95 km2), is stable (1.29 km2), and increased (0.10 km2). Unshaded (excluded) areas contain cliff, talus, mining disturbance, and subalpine forest. (B) PFD (mean >± SE) for plots in krummholz (KRUM); tundra slopes (SLOPE); wet meadow (SWALE), false summit (FSUMMIT); and summit (SUMMIT) habitats (N = 6 species; F4,385 = 5.55, P = 0.0002). Asterisks indicate significant differences at P < 0.05. (C) Total flower production (in millions) is the product of total surface area for (A) each habitat (table S5) (15) and (B) mean PFD.

      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.

  4. Feb 2018
    1. In 2012–2014, we resurveyed bumble bee visitation on Mount Evans and Niwot Ridge in accordance with historical observations (18). Despite a 10-fold difference between past (n = 4099 visits observed) and present (n = 519 visits observed) collection effort, surveys indicate that resident bumble bees have broadened their diet. Resampling historical visitation data to match present collection effort reveals that foraging breadth (Levin’s niche breadth) (15) increased from 2.61 to 7.01 for B. balteatus [z score (Z) = 28.48, P < 0.0001] and 2.09 to 5.07 for B. sylvicola (Z = 19.78, P < 0.0001). Bumble bees have added flowers with shorter and more variable tube depth to their diet (B. balteatus: F1,1997 = 7554, P < 0.0001; B. sylvicola: F1,1997 = 64,851, P < 0.0001) (Fig. 2, E and F, and table S3).

      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.

    2. We measured the change in tongue length of B. balteatus and B. sylvicola using specimens collected from 1966–1980 and 2012–2014 in the central Rocky Mountains (15). These two species historically comprised 95 to 99% of bumble bees at our high-altitude field sites (16–18). B. balteatus workers were collected from three geographically isolated locations: Mount Evans (39°35.033′N, 105°38.307′W), Niwot Ridge (40°3.567′N, 105°37.000′W), and Pennsylvania Mountain (39°15.803′N, 106°8.564′W).

      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.

    3. Although the climate change impacts on phenological and spatial overlap of mutualists are well known, the role of climate change in generating functional discrepancies between them is less understood. Using historical data, we show that reduced flower abundance in bumble bee host-plants at the landscape scale has accompanied recent warming, leading to evolutionary shifts in foraging traits of two alpine bumble bee species

      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.

    1. we restricted this analysis to break periods.

      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.

    2. Our recordings revealed that USVs and neuronal activity in the trunk cortex are modulated in a similar way by tickling and anxiogenic conditions. We wondered whether tickling-evoked USVs and neuronal responses to tickling are causally linked. We therefore aligned neuronal firing to the onsets of USVs (Fig. 4, A and B).

      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?

    1. In this paper, we report a novel set of hominin tracks discovered at Laetoli in the new Site S, comparing it to a reappraisal of the original evidence. The new tracks can be referred to two different individuals moving in the same direction and on the same palaeosurface as those documented at Site G.

      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.

    1. climate protection

      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.

    2. Thus, for each of the two grassland experiments, we used data collected from each plot to estimate parameters for a model that projects soil C accumulation over a 50-year time frame

      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.

    3. E141, called BioCON, started in 1997 to explore how plant communities respond concurrently to three forms of environmental change: increasing nitrogen deposition, increasing atmospheric CO2, and decreasing biodiversity (45).

      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.

    4. represented C4 grasses, C3 grasses, legumes, and other forbs. The species composition of plots was chosen by separate random draws of 1, 2, 4, 8, or 16 plant species from a pool of 18 species, with each level replicated in 30 or more plots.

      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.

    5. Marginal carbon was computed for each of the 15 incremental steps in species richness described in the modeled data, from S = 1 to S = 2, S = 2 to S = 3, …, to S = 15 to S= 16, bounded by the actual data from the experiments where S varied from 1 to 16 in experimental plots.

      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.

    6. For each bootstrapped iteration for each year, the parameter values a and b were used to estimate total soil and ecosystem C content for plots ranging from 1 to 16 species

      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.

    7. In the end, the Metropolis-Hastings algorithm generates a distribution of accepted I and kvalues wherein their means coincide with the minimal value of J (that is, the best fit to the observed data). Soil C content for each plot was projected to 50 years using the mean parameter estimates I and k and measured C0 for both depths (that is, soil C at start of the experiment).

      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.

    8. For E141, soil C data were available for each plot at the beginning of the experiment (year 0) and after 5 and 10 years of experimental treatment (0- to 60-cm depth); we scaled soil C data to 0- to 100-cm depth for E141 using soil C depth distributions for E120 (20-cm increments to 1-m depth) to determine the proportion of C in the top meter of soil contained in the 60- to 100-cm depth, and then we used this proportion with observed soil C data for each plot to estimate total C to 1 m.

      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.

    9. To fit the model and obtain plot-level parameter estimates of I and k, we used all available soil C data from the Cedar Creek Ecosystem Science Reserve website (available publicly from www.cbs.umn.edu/explore/cedarcreek). For E120, surface soil data (0 to 20 cm) were available from years 0, 1, 5, 7, 9, and 11 for all plots, and from year 10 for some plots, and data for 0 to 100 cm were available for years 0 and 11.

      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.

    10. In both experiments, soils were treated before initiation of the manipulations. Before planting, methyl bromide was applied to soils in the BioCON experiment, and the uppermost layer of the soil (0 to 5 cm) was relocated off plot for BigBio, to reduce the influence of the seed bank on species composition of the experimental plots in both cases.

      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.

    11. These experiments—and our analyses of them—excluded large vertebrate grazers, which can influence grassland carbon storage (47) and, thus, its economic value; our assessment focused solely on species richness and did not consider grazing or other influences on grassland carbon accumulation

      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.

    12. Thus, any influence of functional groups on carbon accumulation (8, 46) are distributed across treatment levels in our analysis.

      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.

    13. Species richness was manipulated in subplots (2 m × 2 m) located within the three 20-m-diameter ambient CO2 plots, with 32 randomly assigned replicates for the 1-species treatments

      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.

    14. E120 contained 342 plots laid out as 13-m × 13-m squares with the central 9 m × 9 m actively maintained for the specified species and plant diversity (44).

      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.

    15. For plants, we used observed changes in plant carbon content. For soils, we used data on soil carbon and plant productivity to model carbon accumulation as a function of increasing species richness over a 50-year period.

      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.

    16. We utilized these data to assess the marginal increase in carbon content with increasing species richness and estimated the economic value of the carbon storage conferred

      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.

    17. We analyzed data from two experiments, performed in a North American grassland where species richness had been manipulated for over a decade periodic measurements of plant and soil carbon content in this site over time have suggested that both factors increase with species richness (8, 22),

      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.

    18. We calculated the marginal change in carbon content with increased richness next, we calculated the economic value of species richness for carbon storage in grasslands, using a wide range of estimates of the social cost of carbon compiled by the Interagency Working Group in a recent synthesis used by U.S. federal agencies when estimating the benefits of carbon reductions from application of federal rules and regulations [mid-range estimate, $137.26 per metric ton C (MT C−1), ranging from a low estimate of 41.94toahighestimateof41.94toahighestimateof41.94 to a high estimate of 400.33 MT C−1; see Materials and Methods] (25).

      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.

    1. Our methodology for identifying these pro-ISIS aggregates was as follows.

      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.
    2. Our data sets consist of detailed second-by-second longitudinal records of online support activity for ISIS from its 2014 development onward and, for comparison, online civil protestors across multiple countries within the past 3 years

      On a daily basis, experts looked for specific hashtags and keywords that indicated activities related to ISIS or to civil unrest. Then, at the same time each day, these experts logged into VK.com--an equivalent of Facebook that is popular in Europe--and searched for newly created aggregates, which were then inserted into a database.

    1. To determine the effect of starvation on lipid reserves, the total lipid contents of mosquitoes were quantified in either sugar-fed or starved females

      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.

    2. Here diet restriction, in vivo depletion of INSr and FOXO using RNA interference (RNAi) and insulin treatments were used to modify insulin signaling and study the cross-talk between insulin and JH in response to starvation.

      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.

    1. burst speed-length relationship

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

    2. Maximum swimming speed was measured following (Wardle, 1975):

      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.

    3. Pilot tests on euthanized rainbow trout (Oncorhynchus mykiss) (10°C) performed at the University of Copenhagen revealed no difference in peak contraction time with increasing stimulus voltage.

      This shows that having more or less voltage wouldn't affect the peak muscle contraction time, so having different fish be stimulated at different voltages wouldn't have affected the minimum contraction time that the authors were looking for during their experiment.

    4. We first applied 10V to a fish, doubling this amount in case of no contraction, using a maximum of 100V

      A small amount of voltage was used at first (10V), and this was then increased by doubling the initial voltage, until contraction occurred. However, a voltage above 100V was never used. To put this amount into perspective, the standard voltage for electrical outlets in the United States is 120V.

    5. post hoc Tukey test

      A statistical test used to confirm where the differences between groups occurred when it's known that there is a statistically significant difference between the means/averages of the groups.

    6. ANOVA

      A statistical method used to measure the variance in data between different groups.

    7. The body temperature at the stimulus location [15, 30, 45, 60, 75% along the fish fork length (Lf) with 0% representing the tip of the head and 100% the fork of the tail] was

      They also measured the muscle temperatures of each fish at the 5 different areas (along the length of the fish from head to tail) where they measured muscle contraction times. The temperature of the muscle would affect whether it contracts faster or slower (warmer is faster).

    8. Sea surface temperature

      The temperature at which fish live in also affects their swimming speed because warmer water generally enables them to propel through water more efficiently. That's why is it was especially important to record the temperatures of the waters from where the fish were collected.

    9. Estimates based on minimum muscle contraction times thus yield the theoretical maximum values attainable by fish

      Measuring the muscle contraction times of the fish after taking them out of the water enabled the researchers to know what the highest potential speed a fish can reach is without real-life factors of the fish's environment, like water current, affecting their data. Representative of data as if they had observed the fish in action with high-speed cameras.

    10. to measure their minimum muscle contraction times

      It's too difficult to observe maximum speed as it's happening in the wild so the best method would be to observe the physiology of the fish. The faster the muscle of an organism contracts, the faster it can move. As a result, the lower the time it takes for fish muscle to make one contraction, the faster the fish.

    11. predicts that such extreme speed is unlikely

      Using calculations, it should not be possible for sailfish and marlin to swim as fast as previously thought because swimming that fast would cause cavitation bubbles in the fish leading to death.

    1. see (6) for details

      In most scientific journals the Materials and Methods are part of the main text, but in Science they are part of the references and Supplementary Materials. For details on how the researchers developed their pathways and models, and information on the different ecosystem groupings, check out that link.

    1. Post hoc data presented here were generated by SPSS as standard outputs of the analysis, including the adjusted P-values reported throughout the manuscript.

      The authors of this experiment used the SPSS statistical software system to create the graphs presented in the article, showing the descriptive statistic analysis.

    2. The descriptive statistics function was used to analyze the distribution of the data.

      Author used descriptive statistics (mean, median, mode, etc) to compare data collected on the oocyte Wobalchia titer and those collected on oocyte size.

    3. For measurement of ovary volume, tissues were dissected from adult flies and imaged using an AmScope MD500 5.0 megapixel digital Camera mounted upon a Jenco ST-F803 dissection microscope set at 1× magnification.

      Using the AmScope digital camera, the authors were able to improve the visualization of the ovaries by having the field of view appear on a computer screen and analyze from there.

    4. Screen shots of these ovary fill diagrams were then imported into Fiji (Image J version 2.0.0-rc-43/1.51d, NIH) for conversion into 8-bit, thresholded black and white images. The area of the ovary fill diagrams was determined in terms of pixels2 by the Analyze Particles function in Fiji. A scale bar was also used to calculate a pixel2 to micron2ratio (9.3025:1) that was applied to all oocyte area data, for presentation and discussion purposes only. Statistical differences were determined through analysis of the primary data in terms of pixel2 units.

      In this experiment, the authors used the Fiji Image J processing software in order to calculate the size and area of the oocytes, providing more insight into how the oocytes were affected.

    5. Three or more experimental replicates were performed for all treatment conditions examined. Significance of differences between conditions was determined by ANOVA analysis of the raw data.

      The authors involved compared the oocyte titer raw data for each experimental replicate using the ANOVA analysis system by testing the differences of the means present.

    6. Images were manually processed in Photoshop to remove extraneous signal outside the oocyte, and remaining oocyte puncta were quantified using the Analyze Particles feature in Image J version 2.0.0-rc-43/1.51d (NIH).

      The authors used photoshop, an image editing software, in order to remove and unnecessary signaling outside the oocyte, making it easier to analyze and interpret the data.

      Full tutorial and introduction to processing scientific images in photoshop: https://www.youtube.com/watch?v=SbsDtPouggs

    7. confocal images

      The authors collected confocal images though confocal laser scanning microscopy which is an optical imaging technique to increase the optical resolution and contrast of a micrograph by using a spatial pinhole to block out-of-focus light during image formation.

    8. All replicates were imaged by laser scanning confocal microscopy on either Leica SP2 or an Olympus FV1200 confocal microscope at 63× magnification with 1.5× zoom.

      Laser scanning was used to magnify the cells and staining enhanced the detail of the structures, shown in black and white for differentiation purposes as well as measurement.

    9. This stock carries the wMel Wolbachia strain as confirmed previously (Christensen et al., 2016). 0−24-hour-old adult flies were selected at random and transferred into new bottles of standard food and aged for 2 days. Then flies were transferred to vials of nutrient-altered food and incubated for 3 days. Controls were run in parallel with all treatment conditions in all experiments.

      The authors of this experiment used flies this young in order to ensure the flies had not developed any Wolbachia yet, meaning it would be easier to extract the oocytes without shredding the tissue.

    10. All feeding experiments were done using flies of the genotype w; Sp/Cyo; Sb/Tm6B, reared on standard food and in a controlled, 25°C environment.

      Specific genotypes allowed for less error or genetic disruption of results.

    11. To ensure homogeneous suspensions of nutrient-altered diet preparations, all food vials were immediately transferred to an ice bucket to be cooled with additional stirring every 10 min until the food completely solidified. Kimwipe strips were inserted into the food to wick away excess moisture.

      The authors placed the vials in an ice bath (placed in bucket of ice) in order to ensure a homogenous suspension, meaning that the substances in the vials were equally suspended from each other.

    12. This standard food was used as a base for all nutrient-altered foods that were prepared in this study (Table S3). The sugar-enriched foods were prepared by first making a stock sugar solution of 20 g sugar in 10 ml ddH2O, solubilized with rounds of 15 s in the microwave and then stirring, repeated until the sugar dissolved. 1.5 ml amounts of these sugar solutions were immediately mixed with 3.5 ml of melted standard food. As aspartame, erythritol, saccharin, and xylitol were not uniformly soluble, the sweetener-enriched foods were generated through direct addition of powder equivalents directly into 5 ml of melted standard food to a final concentration of 1 M (Table S3). Yeast-enriched food was prepared by mixing 1.5 ml of heat-killed yeast paste into 3.5 ml melted standard food. Dually enriched food was prepared through addition of 1.5 ml sugar solution and 1.5 ml heat-killed yeast to 2 ml standard food. Desiccated food was prepared by addition of 2.5 g silica gel (roughly 2.5 ml volume) to vials containing 5 ml standard food (Table S3).

      The recipes for the substance-enriched foods given to the flies.

    13. The impact of diverse dietary sugars on insulin signaling has not been fully defined in D. melanogaster. From the perspective of Wolbachia endosymbiosis, this study suggests that dietary sugars induce different classes of mechanistic responses.

      The researcher's reasoning for executing this experiment was to uncover the frontier that is the mechanism that act in Wolbachia concentration, as there is very little information on it.

    14. To further investigate how oocyte Wolbachia titer is controlled, this study analyzed the response of wMel Wolbachia to diets enriched in an array of natural sugars and other sweet tastants. Confocal imaging of D. melanogaster oocytes showed that food enriched in dietary galactose, lactose, maltose and trehalose elevated Wolbachia titer.

      The paper attempts to find the mechanism responsible for Wolbachia concentration increase in germ line cells through tests of natural/artificial sugars and yeast.

    1. we illustrate through a series of analyses that the stationary gene partition is superior to the nonstationary partition

      Gene partitioning involves looking at the make up of complex traits. It involves computing heritability contributions from subsets of predictors to try and narrow down the search for causal variants.The reason why gene partitioning is so important is because if it is not done correctly the sister genomes results in aneuploidy. The consequences of these errors range from loss of normal cellular function to cell death. Stationary partitioning is superior to non-stationary because better results are given when trying to find these casual variants that are important for hereditary information.

    2. Herein, we demonstrate that these conclusions require substantial revision

      The main goal of this paper is to revise the previous work made on the construction of phylogenetic trees because according to previous studies by Rokas and Gee, those trees that have been created are fairly inaccurate. This research is being made to demonstrate how these phylogenetic trees are in fact accurate and correct the conclusions made by previous scientists.

    3. The authors then carried out a series of analyses

      In this experiment, the authors had to find out the lowest possible amount of data they needed to come up with a correct species tree. In other words, they want to discover the most efficient way possible to create an accurate phylogenetic tree.

    4. this approach is necessary because there are no identifiable parameters that predict the phylogenetic performance of genes (Gee, 2003; Rokas et al. 2003)

      It is hypothesized that no matter what, the accuracy of a tree is directly related to the number of genes used to create that tree. This means that the greater number of genes studied, the more accurate the tree, so with an infinite number of genes one can achieve an infinite amount of accuracy.

      The second part of the hypothesis states that the above statement should be true due to the fact that there is no set evidence that can "rank" a gene's ability to contribute to a phylogenetic tree. This is hypothesizing that all genes contribute an equal amount to a phylogenetic tree, with no gene being able to contribute any more or less than another gene.

    5. We investigated incongruence between stationary and nonstationary partitions further by examining partitioned Bremer support.

      Partitioned Bremer support is a method for assessing the similarity in joined data collections, although, there are some point of views that require some insight. When more than one similar parsimonious tree is found in the middle of varied ones, averaging Partitioned Bremen support for each set of data over these trees can avoid trouble, and it should ideally be analyzed for each unnatural tree. When numerous most parsimonious trees are examined due to joint data collection, Partitioned Bremen support is generally computed on the common tree. Be that as it may, extra information can be acquired on the off chance that Partitioned Bremen support is computed on each of the most parsimonious trees or less quality trees.

    6. We performed parsimony bootstrap analysis of individual genes across all positions to compare the phylogenetic performance of these partitions.

      "Bootstrapping" is a technology based practice for determining the accuracy or precision of many statistical results. For phylogenetic  trees, the bootstrap helps by exampling "confidence" in related organisms (common ancestor) in proportion with organisms from the same "family".

      During this procedure, the authors essentially performed an analysis to determine how divergent, or dissimilar, the genes had come to be.

  5. Jan 2018
    1. If Ir40a is required for the behavioral response to DEET, one must contemplate that both Ir40a and Orco are necessary for DEET sensation, but that neither pathway is sufficient for repellency on its own.

      The author of this paper is currently doing research on the olfactory receptors that mediate the mosquito’s human and plant host-seeking behavior and the genes that regulate their appetitive drives. This includes research on Ir40a.

    1. Figure 2 indicates reconstructed and estimated shifts in the distribution of major Mediterranean biomes

      These are some of the main general biomes found in the Mediterranean region. The BIOME4 model uses a longer list of specific biome types, and more than 20 were found in the Mediterranean region. For the analysis, this larger list was grouped into ten “aggregated biome types” which are presented in Figure 3. To see how the aggregated biomes were grouped, check out Table S1 in the Supplementary Materials.

    2. The colored areas illustrate the interquartile interval provided by the intermodel variability

      Each of the colored lines is generated from using multiple climate models as input to the BIOME4 model. The solid line indicates the average change ratio predicted from multiple runs of the model.The variation within each model is indicated by the shaded region, which encompasses the 25% of results above and below the average. As you can see, some models had higher variability than others, and the predicted changes within the first 50 years overlap between models.

    3. The limitations of a relatively simple ecosystem model are largely offset by two factors. First, this method directly relates the physical environment, including its seasonal variability, and atmospheric CO2 to plant processes and thereby avoids the strong assumptions made by niche models (18). Second, past observations are analyzed with the same process-based model that is used for the future projections, thus providing a more coherent framework for the assessment.

      Though the BIOME4 methods have limitations, there are two major advantages.

      First, the model is based on the underlying processes that connect climate and ecosystems, so it avoids the assumptions made by models that are based on correlating current ecosystem distributions and climate values. For example, these models often assume that the current ecosystem distributions are stable and at equilibrium, rather than in flux.

      Second, the researchers are able to use the same model for both the past reconstructions and for the future projections. This allows for more direct comparison between the two groups.

    4. For the Holocene, BIOME4 was inverted to generate gridded climate patterns by time steps of 100 years and associated ecosystems (“biomes”) from

      To reconstruct Holocene climate variables and biome types, the researchers "inverted" the BIOME4 model, flipping the input and output data. Rather than using climate data as the input, it uses plant data.

      The researchers started by converting the pollen core data for a given time and location into "plant functional type" scores, which BIOME4 uses to rank and select biome types based on the "best match." "Plant functional type" groups species together based on similar characteristics such as respiration rate, response to climate variation, and genetic makeup.

      The researchers then ran the BIOME4 model in "inverse" mode, testing a large number of randomized climate inputs for each time and location. The set of climate inputs that resulted in the best match to the pollen core data is used for the reconstruction.

    5. see table S2 and (6) for details

      In many scientific journals, the Materials and Methods are part of the main text, but in Science they are part of the references and Supplementary Materials. For details on how the researchers developed their pathways and models, and information on the different ecosystem groupings, check out the supplementary information.

    6. 25th, 50th, and 75th percentiles

      These boxes show a range of results from many model runs for each scenario. The dot indicates the 50th percentile (median) result for all runs. The box shows the range containing the middle 50% of the results.

    1. whole-mount in situ hybridization (WMISH) with species-specific probes, we show that crocodile, lizard, and snake placodes all exhibit spatial expression of Shh

      WMISH is a common technique for visualizing the location of expressed RNAs in embryos.

      In this study, the authors used WMISH to show that Shh was expressed in the placode.

    2. breeding experiments

      Individual lizards with different physical traits were bred together in order to observe how those traits were passed on to the offspring.

    3. each of these dermoepidermal elevations that generate scales in crocodiles, lizards, and snakes occurs at the location of a transient developmental unit that exhibits the characteristics (Fig. 1B) of the mammalian and avian anatomical placode

      The authors of this study expand on the findings of previous studies by showing that the elevations that result in scales correspond to the anatomical placode in mammals and birds, which gives rise to hair and feathers.

    4. skin developmental series (Fig. 1A) in crocodiles (Crocodylus niloticus), bearded dragon lizards (P. vitticeps), and corn snakes (Pantherophis guttatus)

      The authors took successive microscopic images of different body parts in both lizards and snakes, specifically focusing on the places that scales form.

    1. Here we present a framework to calculate the amount of mismanaged plastic waste generated annually by populations living within 50 km of a coast worldwide that can potentially enter the ocean as marine debris.

      The authors use population density data and waste accumulation rates to predict how much plastic might enter the ocean as marine debris.

  6. Dec 2017
    1. The most marked and derived macropatterning of skin in reptiles is observed in snakes

      Compared to other reptiles, snakes' scale development is unique.

    2. proliferating cell nuclear antigen (PCNA) analyses indicate a reduced proliferation rate of the placode epidermal cells

      PCNA is a protein involved in cell division, so it is used as a marker to locate cells that are actively dividing.

      This analysis showed that the cells of the placode were reproducing very slowly.