A picture is worth a thousand words

I chose the 4 May 2007 edition of the journal called ‘Science’. On page 709 of this journal, I found an article with the title, “Recent Climate Observations Compared to Projections” that, much like the title, compared observations based on the climate from recent research to those based on projections.

The graph displayed on this article lists the sea level change (cm), temperature change (degrees Celsius), and carbon dioxide concentration (ppm) due to climate change over a range of years starting as early as around 1973. The graph plots a representation of the projected increase in each of the conditions as well as the actual change recorded over the respective years. The relative simplicity of the graph made it simple to understand its content and the trend of the increase in sea level, temperature, and carbon dioxide concentration due to climate change. As a result, it did not take me very long to decipher the point of the graph. I learned that the temperature increase is in the upper part of the range projected by the Intergovernmental Panel on Climate Change (IPCC). Similarly, sea level has been on the rise faster than the rise projected by models since 1990. Carbon dioxide concentration has been following the projections very closely, though the projections themselves are implying a relatively rapid increase. Because the graph was very precise and well presented, I did not have to rely very much on the text to help me put together the information provided by the graph. Overall, the data collected from this study really serves to emphasize the gravity of climate change.

I choose the article “Ocean Warming Slows Coral Growth in the Central Red Sea” on page 322 in the Magazine Science (Vol. 329, 16 July 2010). The graph recorded how varying temperatures in the summer affects the growth (mm/year) of Coral in the Red Sea.
The graph is in the form of a plot graph, with confidence bars provided. It tallied coral growth in mm/year under different temperature conditions in the summer (29.6-31C, in 0.2C intervals). It took me about 10 seconds to scan the graph and decipher what it was trying to represent. The form of the graph is a common one that many people have seen, plot graphs are very straight forward and easy to understand.
From the graph, I learned that coral growth decreases slightly between the temperature ranges 29.6-30.2C. However, as you go above 30.2C, the growth rate decreases more dramatically between the 0.2C intervals. Therefore, I concluded that optimum coral growth can only occur between specific temperature ranges, and that the ocean warming will slow the coral growth.
Due to the fact that the graph I choose was fairly straight forward and specific, I did not have to rely on the text at all when I first looked at it. However, I did read over the text when I observed the graph the second time to deepen my understanding.

The graph I choose is in “Youth Bulge” on page 923 in Science (Vol.325, 21 August 2009). This graph shows the population of youth from developed courtiers, Africa, Latin America/ Caribbean and Asia/ Pacific in 1950 and predicts the population in each group in 2050. This graph is easy to understand because Constance Holden, the writer, uses different colors to represent different location and includes all the data, from the same year, into a circle, which can make it easier for the reader to compare the population. In 1959, there were 461 million youth in the world, and Asia/ Pacific group occupies more than 50% of the whole population. After 100 years, the population, as Holden predicts, will triple. What surprises me is that the Africa group will grow from 43 million to 348 million (this means that they increases form 10% of the whole population to 25%). This pie graph implies that the African people have a huge demand of young adults to do the labor. Also, this data proves the statement that Population Reference Bureau made before: “twenty percent of the worlds’ population is between the ages of 18 and 24”. I’m also surprised by the dramatic decrease in population from the developed countries group; they used to be 20% of the whole population, but in 2050, they will shrink to 10%. To my opinion, this is caused by the phenomenon of which couples avoid having children because they cannot afford them. The article just briefly explains some background knowledge about the youth population. The main part is the graph. This is why I don’t have to read the article before reading the graph.

The article I chose is from the May 4, 2007 edition of the journal, “Science.” The article begins on page 705 and the title of the article is “Ultracold Neutral Plasmas,” which are slowly moving charged particles that display unusual behaviour in their oscillation of kinetic energy compared to other contemporary plasmas. The graph showing the related data is found on page 706.

The graph portrays the relationship between the average temperature of the ultracold neutral plasma in kelvins and the time after formation of the plasma via photoionization in nanoseconds. The purpose of the graph is to illustrate that the average temperature increases in the first 200 ns as the ions in the plasma reach equilibrium. However, the more important information implied in the graph is that the ultracold neutral plasma equilibrates towards an average temperature of 1K! Compared to other conventional plasmas such as candel light, which has an average temperature of around 1000K (even this is considered cold), ultracold neutral plasmas have super-low temperature, which gives rise to their surprising dynamics due to the ions’ slow movement.

It took me quite a while to understand the key points of the graph because a lot of specific scientific terminologies were used in describing what the graph was about. I also repeatedly read over the abstract and the introduction to understand how this graph correlates to the main idea of the article. Without the text, I would have probably had no idea how to decipher this graph.

The article “The Developmental Role of Agouti in Color Pattern Evolution” by Marie Manceau, et al. in Science journal (Volume 331 / February 25, 2011) intrigued me in a number of ways. Besides the adorable deer mouse featured on the cover, its fascinating aspect lays on the investigation on how genotypes affect phenotypical attributes; in this case, the causal gene Agouti for color pattern is targeted. As a negative regulator for adult pigmentation, the ventral-specific Agouti delays terminal differentiation of ventral melanocytes, as “preplanned” in embryonic expression. To demonstrate such, two populations of Peromyscus, Mainland and Beach, with different colour formations due to local adaptation are studies along with their hybrids. One of the results is shown in Figure 2, a fine-scale gene mapping of the Agouti locus LG7 presented with its variation from crossing over through recombinant breakpoint analysis of the F1 hybrids. It is shown that genes up from Napb to Top1 are often dislocated during gamete formation. The hybrid Agouti LL also demonstrates in part B to have a lower relative expression of the light skin allele, resulting a boundary between dark and light coloration between that of Mainland and Beach.

This visually oriented information took me less than 10 minutes to decipher the peripheral message of the figure without reading the caption and text, but as I dig deeper into it, I spent more than an hour trying to pinpoint the details such as the meaning of LOD (level of deviation? Dislocation?) and 2^ct. Generally, I did not rely much on the text. In this figure, I see the real-life scenario of crossing over, whose breakpoints are not always concrete but a gradient towards the gene of interest; in this case, Agouti (30.3) is chosen. Also, hybrids do not simply have an equal blend of their parents’ phenotypes. As shown in part B to E of the figure, on the surface, the light allele being expressed more than the dark allele; however, the white allele experienced major decrease in expression compared to the P1 generation.

I found a geographical representation of the distribution of the areas that are at risk for Plasmodium vivax transmission in the August 6th 2010 edition of Science Magazine. It took me a very short amount of time to interpret what the picture was trying to portray– at first, upon glancing at only the picture, I could tell it was some type of distribution data. Where the colours were darker, there was a higher concentration of something. However, it was not until I read the title of the figure that I could tell what they were exactly trying to map– “Areas at Risk of Plasmodium vivax Transmission”. With this single line, I was more or less able to interpret what the map meant. Intuitively, I guess that the darker red areas meant a higher risk, whereas the pinker-coloured areas inferred less risk of infection. This was found to be true when I looked at the legend.
The colourful schematic of the map visually helped me to infer many things about the spread of the disease– it clearly shows that the risk of transmission is significantly higher in the southern parts of the world, particularly, as it seems, where it is very warm. Also, it seems as though transmission is also increased in places where there are countries notorious for its lower standard of living. By mapping out the risk of transmission instead of listing number and countries, it helps the reader visualize what the trends are in the transmission, which is greatly helpful in being able to synthesize information about the figure.

My diagram comes from the 15th of February 2007 edition of the International Weekly Journal of Science called “Nature”. My article is on page 724, the title of the article is “Cell fate in the mammary gland” and the figure is on page 725. The figure shows a simplified step-by-step diagram on how a gene-regulatory factor, GATA-3, affects the development of immature breast cells. The GATA-3 binds to a regulatory region, the promoter, of the gene encoding FoxA1. If FoxA1 is activated is activated, it will interact with ERα and the FoxA1 may bind to the ERα gene promoter to turn on the transcription of the ERα target genes that include FoxA1 and ERα. It took around 10 minutes in order to understand what the diagram; it was somewhat difficult to understand what kind of promoter the GATA-3 was attaching itself to because it did not explicitly say that it was a FoxA1 promoter and it was only showed to be on the left hand side of the FoxA1 gene. After I understood the first step of the figure, the rest of the diagram was straightforward. I learnt in this diagram that the binding GATA-3 is a crucial first step in setting off a chain of reactions to cause mammary gland progenitor cells to become luminal epithelial cells. Luminal epithelial cells then develop into lobuloalveolar cells that can secrete milk for mammary glands. There was some reliance in the text in order to understand the different roles of each protein and gene mentioned in the passage. After each of the protein and gene roles were defined by the article, it was clear how each of the genes and proteins related to each other.

The 12 March 2010 edition of Science (Volume 327 Issue 5971) contains an interesting article, “Plumage Color Patterns of an Extinct Dinosaur.” Figure 1 shows the SEMs (scanning electron micrographs) samples of feathers of A. huxleyi. Part A shows a clear, detailed image of the right hindlimb, and right and left forelimb. Based on Part A, Part B illustrates the main bone composition where the numbered red dots represents sample number and the blue dots represent its counterpart. Parts C to H show magnified versions of the SEMs samples of melanosomes and melanosome impressions at various parts of the limbs, including the left scapula, right ulna, left humerus, and left pes. Melanosomes, organelles that contain melanin, determine the plumage color. By analyzing melanosome size, shape, density and distribution, the plumage pattern of A. huxleyi can be identified.

This took me around 40 minutes as I had to read through the article and analyzed other figures to gain a better understanding on the topic. Although Figure 1 provides a clear image of SEMs samples, I found it difficult to understand the significance of the image solely by reading the caption. I spent nearly 15 minutes to understand Figure 1 and roughly 30 minutes to read and understand this topic. I learned that it is possible to determine the plumage color patterns of a the Jurassic troodontid A. huxleyi by analyzing the characteristics of melanosome, that was well preserved in fossil fuels for many years.

The Figure 2 from the article “Mantle Flow Drives the Subsidence of Oceanic Plates” (Science, Volume 328 Page 83-85) describes the age of the sea floor along the Pacific plate. It colour codes different ages on the map of the Pacific plate. The graph also represents the shift in the sediments by the Pacific plate with a black line. The graph portrays. Also, there are two depth vs sea-floor-age linearized graphs of the data collected from two different water flow lines.

I think the figure is supposed to portray how the movement of the Pacific plate shifts the old sediments of the sea floor and create a variation in the age of the sea floor. It also shows that the sea floor age depends on the depth of the ocean, and I think this shows how the sediments get transported along the movement of the plate and deposited where the ocean is deeper.

It took me about 3 minutes to figure out what the graph and the different colours of the map meant, and to understand what the caption was saying. I learned that the captions used in scientific articles are supposed to be thorough enough so that the captions are sufficient to understand what the author(s) try to represent through graphs. Although the axis gave me an idea what the graphs were about, I did not have a clue what the map was suppose to represent until I read the word “Pacific plate.” Then I went back to the title of this article, and everything started to come together.

Page 891 of the 13th February 2009 edition of Science (volume 323) shows an image of the brain. One part of the image shows the pain network, while the other shows the reward network. The image shows that pain network consists of the dorsal anterior cingulate cortex, insula, somatosensory cortex, thalamus, and periaqueductal gray. This network detects pain both physically and emotionally. These pains include physical pains, social exclusion, bereavement, being treated unfairly, and negative social comparison. The reward network consists of the ventral tegmental area, ventral striatum, ventromedial predrontal cortex, and the amygdala. Like the pain network, the reward network includes both physical and social rewards (such as physical pleasures, having a good reputation, being treated fairly, cooperating, giving to charity, and schadenfreude).
The two images of the brain shows that the pain and reward network are located close to each other. This implies that there might be a connection between social and physical pains and pleasure. Even though the image depicts clearly the different parts of the brain involved in these networks, we will have to reply on the text for information on how these two networks are actually connected. I learnt that even though being excluded is painful and giving to charity is pleasurable, they activate the same brain regions. This shows that the brain might treat social experiences and concrete physical experiences as more similar than is generally assumed.

I found a map-like image in the July 2010 issue of the Nature magazine (page S10) that portrayed where different HIV preventative studies where being tested. The image was clear enough that it did not take me very long to decipher it. I learned a new technique of presenting information—that of a world map. You are able to use symbols representing different “prevention techniques” being tested and plot them on countries on the map to indicate where certain types of studies are held. This kind of data representation is very clear, concise and effective because it did not take me long to figure out what the image was representing. I mostly relied on the legend of the symbols on the bottom as well as the title and subtitle of the image to figure out what the image was saying. Reading the title of the article the image came from also helped understand the image.
From the image, I learned about the existence of different HIV prevention options that are being tested world wide, such as vaccines, microbicides and partner treatment. I had to rely more on the text to understand what these preventative options were. From the map, I was able to discern that most of the tests of various preventative options were conducted in southern Africa, the US, and Thailand. Canada is testing the effectiveness of vaccines against HIV.

I chose the article “Anthrax toxins cooperatively inhibit endocytic recycling by the Rab11/Sec15 exocyst” from page 854 of the October 14, 2010 Nature magazine.
The image in this article showed pictures of fly wings, in varying diseased states. It took me some time to determine what the figure was representing, and I had to look up information regarding the anthrax disease, as this was what the article was researching. Researchers were trying to identify pathways involved in anthrax pathogenesis, and were utilizing flies in these experiments. It was determined that when two enzymatic moieties (LF and EF) were expressed in the larval wings of flies, new phenotypes were produced. These phenotypes were illustrated in the figure. The caption underneath the image described the traits in each phenotype, such as notched wings, and thickened veins.
It did not take me long to interpret that the figure was representing various phenotypes but did take some time to decipher what these phenotypes were representative of. I relied mostly on the text from the article, and not from the figure itself. More reading was required to understand what the research was about, as the image did not provide this information. I learned what anthrax disease is, and how it is transmitted. Additionally, I learned that the aetiological agent in anthrax, B. anthracis, secretes three factors that, when expressed within a cell, result in many different phenotypes.

The article titled “Historical Warnings of Future Food Insecurity with Unprecedented Seasonal Heat” was published in volume 323 of the 9 January 2009 edition of “Science”. The figure I chose to decipher was Figure 1, located on page 241. It displayed hypothetical distributions of summer season temperatures form 1900-2000 and 2080-2100 with x axis indicating seasonal temperature and y axis representing probability of occurrence.

Figure 1 consists two parts, with (A) showing that the highest growing season temperature of the 20th century represents the median seasonal temperature by the end of the 21st century. This data is then compared with that from part (B) with future temperatures that are-out-bounds hot. That is, the growing season temperature at the end of the 21st century will exceed the hottest growing season ever observed.The graph was fairly simple to decipher by carefully relating the graphs with the caption underneath them. As I could see straightly from the graph that there was no overlap between mean temperature graph of 1900-2000 and that of 2080-2100 in part (B) whereas the two graphs overlapped in part (A). Initially, it seemed no need for me to read the journal article to understand the graphs. However, it still took me 30 minutes to interpret the significance of the graphs. By further extracting the information from the abstract and related paragraphs surrounding the figure for a deeper level of understanding, I learned that if the average future seasonal temperature were to exceed the hottest seasons on record, there would be widespread risks of food insecurity around the globe as crops will likely suffer at very high temperatures in the absence of adaptation.

The research article, “Role of Secondary Sensory Cortices in Emotional Memory Storage and Retrieval in Rats,” in the journal, “Science,” (Vol 329, 6 August 2010) describes experiments involving the investigation of the mechanisms and areas in the brain in which emotional memories are stored, by testing the reactions to stimuli of mice trained to associate acoustic stimuli with conditioned stimuli before and after varying parts of the brains were lesioned (Te1, Te2, Te3, Oc2L). The graph I chose was Figure 5D, found on page 653 of the journal.
The bar graph compares the relative mean startle amplitudes of control mice, of Te2 lesioned mice trained to recognize the stimuli, and Te2 lesioned untrained mice on the first day of training prior to lesioning, after lesioning (retention test) and when they were subjected to a new acoustic stimulus. The trained and control mice groups both displayed significant decrease in startle amplitude in the retention test. The confidence intervals for the untrained, Te2 lesioned mice overlapped for the trials carried out before and after lesioning, which signifies that Te2 lesions do not affect startle reactions of mice. When subjected to a new acoustic stimulus, all three groups of mice displayed significantly greater startle amplitudes.
It took me a while to understand the graph because it was in the middle of the article and the labels were condensed and consisted mostly of scientific terms. I had to skim the beginning of the article and read the text above the figure to understand the purpose and meaning of the graph. I learned a few new terms from the graph, as well as the fact that the Te2 region was found to not play a significant role in emotional memory storage.

I chose the article “A chronological framework for the British Quaternary based on Bithynia opercula” from Nature (Issue 7361, August 25, 2011).
Figure 2 of this article is a graph that shows the percentage of racemization of various amino acids in the opercula of the gastropod species Bithynia tentaculata over the span of 3 000 000 years. Racemization is a process occurring in a dead organism where the enantiomer of its amino acid (L form) spontaneously converts to its other form (D form) over time. By analyzing the percentage of racemization in various amino acids from this graph, the researchers can determine the geological period of the Bithynia.
There were specific terminologies in this graph that I had to refer back to previous texts and do some additional research to understand. However, once I understood these terms, I found the graph easy to understand because it shows obvious trends in the percentage of racemization and clearly distinguished the different amino acids. I was able to learn from this graph a new method of using amino acids to date the age of organisms.

In the research article, “Oil Cruise Finds Deep-Sea-plume,” in the journal “Nature,” (Vol 465 page 274-275) there is a picture of a map showing an area in the ocean where a giant oil plume is located. The plume of oil seems to be spreading southwest. The oil density in the water is higher in the centre of the plume as expected and lower on the outer edges of the plume. It did not take long to decipher this image as it is very clear. The title also helps in understanding the image.

The journal I chose was the July 22, 2011 edition of Science and the article was “Identity: Key to Children’s Understanding of Belief”. One of the graphs in this article portrayed the mean proportion of children in different age groups that passed various tests. The point the graph was trying to show was quite simple, and that was that the number of children that passed these tests increased with age. This could be seen just from looking at the graph, the text was not necessary. However, the part of the graph that was complicated was what these tests were actually testing and whether passing these tests was a good or bad thing. The three tests are called the dual function test, identity test, and false belief test, but that was all I knew from the graph. The caption helped my understanding slightly by explaining what the tests consisted of and how children passed these tests. The information given in the caption also gave me the impression that passing these tests was good, and that the increase in proportion of children that passed showed heightened intelligence in critical thinking and problem-solving. However, even after reading the article, I still did not fully understand what the three tests were actually testing for.

The graph that I chose was from “Does ‘Junk Food’ Threaten Marine Predators in Northern Seas?” published in the December 19th, 2008 edition of Science. The title of the graph is “Abundance of Breeding Seabirds in Scotland (1986-2004)”, and the axes are “Index of Abundance (% relative to 1986)” versus “Year”. It has a general downward trend in terms of the index of abundance as time went on. The point of the graph was not hard to decipher at all, as it merely showed that there was a steady decline in the abundance of breeding seabirds in Scotland, from an index of 100 in 1986 to an index of about 40 in 2004. However, since the article did not explicit refer to this graph and did not explain what the “index of abundance” really meant, I could not decipher the exact numerical meaning of the graph. The graph itself did not need any text to help me figure out what it meant in general, despite the lack of explanation of the meaning of the index of abundance, but I needed to read the article to find out what “junk food” meant in terms of seabird diet and what the reason was behind the decline in the abundance of breeding seabirds in Scotland, leading to how this decline threatens marine predators in Northern Seas.

I learned that the term “junk food” used in the article was from a “junk-food hypothesis” that was coined by John Piatt, a seabird ecologist at the U.S. Geological Survey Alaska Science Center in Anchorage. He was doing research on colonies of common murres (the American name for guillemots) in the Gulf of Alaska, and he noticed that they had not recovered as expected from the 1989 Exxon Valdez oil spill. He examined the gut content data of the murres from the early 1970s, and he found that they had mostly been eating capelin, in which one gram of capelin can contain up to twice as many calories as a gram of pollock. Thus, captive seabirds fed oily fish like capelin gained weight much more quickly than those fed pollock. And so, Piatt thought that this “dietary shift” might explain the murre’s decline. The term “junk food” was later explained in the article to be a bit misleading as this term used in the human world meant fatty foods, while in terms of the seabird diet in this article meant something like a diet of celery – a lean cuisine that is leading to the decline of seabirds as they are starving from these low-calorie diets. The point of this article was to examine the reason behind the decline of marine predators such as the endangered Steller sea lion, whether it is the “junk food” fish they are eating or overfishing. It was concluded in this article that to work out how much the problems are a junk-food issue and how much is lack of food is difficult.

I chose one of the graphs presented in the Research Article “Atomic-Level Characterization of the Structural Dynamics of Proteins” published in the 15 October 15 2010 issue (Volume 330) of the ‘Science’ magazine.
The two side-by-side graphs show the sequence of steps and the amount of time (in microseconds) in takes for a protein to fold and refold – shown on the x-axis. There are four different lines on each graph each of which represents a different region of the protein: (e.g. the blue line represents the sequence of events from residue 12 to 18 etc.). The y-axis represents the ‘RMSD to native’ in Angstroms. I had to refer to the article to understand that RMSD (which stands for root-mean-squared deviation), is a measure of how close the experimental value is to the native value (which is the original crystal structure). According to the graph and its caption, RMSD is higher for regions of protein with greater number of residues. So for example, the RMSD to native for the region from residues 2 to 33 (full protein) was highest whereas the RMSD was lowest for the blue region mentioned above.
It took me about 10 minutes to find out what the graph was trying to report. I used mostly the captions to figure the graphs out, as well as the article itself. This was because there was no indication on the graph itself as of what each of the red, blue, orange and green lines represented. Moreover, I had no idea what RMSD stands for and I had no idea what they meant by ‘native’ for which I had to refer to the article.
An interesting fact I learned was the specific steps of folding process where at first, tip of hairpin 1 forms, followed by hairpin1, followed by hairpin 2, followed by the rest of the protein. This information was consistent with what we learned in class about protein structure and folding, so it did not take me too long to comprehend some of the new information.