Fight Fire with…(Why it’s good you’re already finishing this title)

The elderly woman exhaled loudly as she pushed up from sitting at the kitchen table. She’d heard a knocking from the front porch and wondered if her son had forgotten something earlier. She walked to the kitchen door and looked out across the porch, only to see giant orange flames licking up the siding of the house. Her breath caught in her throat. She fumbled pulling her phone from her pocket and her fingers shook as she punched in 9-1-1. Her voice trembled as she almost screamed at the operator – “There’s a fire on the front porch!” Then, in her hurry to leave, she put the phone down as she picked up her purse and rushed towards the side door. Just as she made it out into the yard, she saw that the flames had already come around the porch and soon the entire side of the house was on fire. Now safely outside the burning house, she suddenly wondered why the operator had said they were sending the police. Why weren’t they sending the firetrucks? I need firefighters!  

Minutes later a neighbor drove by, saw the flames and stopped to help. The woman had the presence of mind to borrow his phone to call 911 back and clarify that her house was on fire and that she needed firefighters to be sent. But in those critical moments, the fire had grown in intensity and the house seemed already engulfed. Somehow, the first 911 operator had heard “there’s a fight” instead of “there’s a fire”.

The old adage, learn from your mistakes, applies not just to trying to improve yourself, but to how the different kinds of mistakes we make can teach us about how the world works. For example, understanding communication mistakes like the one above can help us to better understand human cognition and the mechanisms behind how our minds comprehend language, and these lessons can then be broadly applied in everything from improving education to making your Google/Amazon/Apple AI assistant work better. So, what might have led to the mistake in our story?

You might be thinking, well, “fight” and “fire” sound somewhat alike. The distinction between the two may be even less obvious depending on the speaker’s accent, rate of speech, and degrees of emphasis and articulation. Additionally, maybe the clarity of the audio was degraded over the cellular signal or through the phone’s speaker, and all of this may have been affected or exasperated by the stress and intensity of the emergency situation. Perhaps what the 911 operator heard simply sounded more like “fight” than “fire.”

A maybe less obvious possibility is that the 911 operator’s mind made a sort-of calculated guess – a prediction – about the word or words it might hear, given the context of an emergency call and the phrase “There’s a…”, and that this prediction influenced what they thought they heard. It might seem strange to think that our minds make predictions about what we’re about to hear or read, because if we waited just a few moments there probably wouldn’t be a need to predict at all. However, we know that human minds make lots of other generally beneficial predictions. You may try to predict how your opponent will move when playing basketball, where the ball will land in a game of catch, or how the drivers around you will behave to better plan your own movements. You probably aren’t even fully aware that you’re doing it. If you think of language use like these other joint activities, predictions of what a speaker might say next could allow better coordination of turn-taking, faster comprehension, and better planning of your own responses. When you add in the additional ambiguity of spoken language, from all the words that sound alike to all the different ways the same word can be articulated to just how unintelligible speech can sometimes be, making calculated guesses – when you’re right – could be very beneficial for efficient comprehension.

If our minds are really making predictions during language comprehension, what specifically is being predicted and what information is used to make those predictions? These are questions that are still being actively investigated and debated across the levels of language. There is evidence that one source of information that people can use to make predictions is knowledge about the world, and specifically about what is likely to happen in a given context, to make predictions about upcoming language. For example, how would you complete the following sentences?

Getting himself and his car to work on the neighboring island was time consuming.

Every morning he drove for a few minutes, and then boarded the…

If you said ferry you agreed with most people in the classic study by Federmeier & Kutas where people were able to use knowledge about what can be boarded (not a bridge) and how you can travel to islands with a car (not on just a regular boat) in order to predict the next word in sentence pairs like these.  

           But asking people to complete sentences isn’t necessarily the same as predicting language in real time as it’s being produced. How do we know that people are making predictions early and throughout language comprehension? One way is to follow their eyes. People are attending to what they are looking at, and thus following their gaze (or eye-tracking) as they comprehend sentences can allow you to determine how people are processing information in real time, and specifically what they are thinking about. This is often done using the visual world paradigm, developed by Michael Tanenhaus and colleagues. People are asked to look at objects (or pictures of objects) while their eye movements are measured with a special eye-tracking device. In a seminal study using this paradigm, Altmann & Kamide found that people looked more at a picture of a cake than a train or ball while hearing the sentence “The boy ate the cake” after the verb ate but importantly before they even heard the word cake. Thus people were using their knowledge of what can be eaten to restrict and predict what could be talked about before it was even mentioned.

Another way language prediction can be seen is by measuring how the brain responds to specific linguistic stimuli like words, using non-invasive EEG (those fun head caps with all the wires sticking out everywhere!). A neural response to a specific stimuli, or event, is called an Event Related Potential (ERP).

A centro-parietal, negative-going event-related brain potential that occurs about 300-500 ms after a word is encountered is commonly referred to as the N400 (because it is negative and occurs around 400 ms). A large amplitude of the N400 seems to be the “default” response of the brain to words, with reductions occurring for words that are easier to access because of the prior context or because they are semantically related or part of a predictable continuation. So you might have a smaller N400 to “fire” after hearing “Harry Potter and the Goblet of…” and a larger N400 to “fire” after hearing “Harry went to the circus and ate…” In both cases, it seems your mind uses your own real world knowledge (about what is typically eaten) and experiences (enjoying the Harry Potter series) to make predictions about what the next word might be. (See Kutas & Hillyard, 1980 for foundational N400 work or Troyer& Kutas, 2018 for a more recent example of work in this area.)

       The same might be true of our 911 operator. Perhaps they typically have more calls for fights than fires, or perhaps they had just had another similar call that was about a fight. Perhaps, over the course of the operator’s experiences with the language that people use in emergency calls, people tended to say “My _____ is on fire”, whereas they tended to end phrases like “There’s a…” with words like fight or car accident. (In fact, a quick check of the Google Ngram corpus of literature and periodicals finds that “there’s a fire” is less frequently used compared with “is on fire.”) It would take more research to understand exactly why our operator heard “fight” over “fire,” but this example illustrates the importance of understanding the cognitive mechanisms behind language prediction and comprehension in general. In the majority of cases, predictions like this might not even lead to mistakes, and in fact could lead to better, more efficient responses to a variety of communicative situations. However, understanding more about how the mind makes predictions in language comprehension, both in the mistakes and the successes, can help us to have a greater understanding of the human cognition of language and could be vital to improving any human endeavor that depends on successful communication.

Girls Talk Math – Engaging Girls through Math Media

Girls Talk Math is a non-traditional math camp in that students not only learn challenging Mathematics usually not encountered until college, but also research the life of female mathematicians who have worked on related topics. Campers share what they learned during the two-week day camp by writing a blog post about their Math topic and writing and recording a podcast about the mathematician they researched. Media created by the campers can be found on our website at www.girlstalkmath.web.unc.edu.

Girls Talk Math was founded in 2016 by Francesca Bernardi and Katrina Morgan, then Ph.D. candidates in Mathematics at UNC Chapel Hill. It was born of a desire to create a space for high-school students identifying as female or from an underrepresented gender who are interested in Mathematics. This summer, a sister camp at the University of Maryland at College Park had its first run thanks to Sarah Burnett and Cara Peters, Ph.D. candidates in Mathematics at UMD (www.gtm.math.umd.edu).

During two weeks of July 2018, 39 high schoolers came to the UNC Mathematics Department to participate in the 3rd year of Girls Talk Math. They were divided into groups of 4-5 campers, and each group completed a problem set focused on a different Math topic:

-Number Systems
-Network Science
-RSA Encryption Cryptography
-Elliptic Curve Cryptography
-Mathematical Epidemiology
-Quantum Mechanics
-Knot Theory
-Classification of Surfaces

Each group then wrote a blog post to share what they learned about their topic. Below are excerpts from each post written by the campers, and you can read the full blog posts here. 

 

Number Systems
Miranda Copenhaver, Nancy Hindman, Efiotu Jagun, and Gloria Su

The Number Systems problem set focuses on learning about number bases (in particular, base 2 and 16) to understand how data is stored in computers and how to translate information into a language readable by machines. This problem set included coding in Python.

“[…]  We count in the decimal – or base 10 – system. This means that we count using 10 basic numbers: 0, 1, 2, 3, 4, 5, 6, 7, 8, and 9. In base 10, each place value represents a power of 10.”

“[…]  The two most important bases in coding are binary (base two) and hexadecimal (base sixteen). Binary is quite simple to think about because it only has two numbers that you could possibly use: 1 and 0.”

“[…]  If we had the number 1101010, we would start by labeling each place value with what power of two it represents. Next, we would multiply each digit by its power of two and simplify:                           

                       1101010 = 1*26 + 1*25 + 0*24 + 1*23 + 0*22 + 1*21 + 0*20

                                       = 26 + 25 + 23 + 21

                                       = 64 + 32 + 8 + 2

                                       = 106

We see that the binary number 1101010 is the decimal number 106.”

 

Network Science
Myla James, Shania Johnson, Maya Mukerjee, and Savitha Saminathan

The Network Science problem set focuses on graph theory and how it is utilized for large data sets. Students learned about data storage in networks and how to analyze and study different data sets. This problem set included coding in Python.

“[…]  We were given a map of the city of Königsberg, Prussia that helped us learn about paths and circuits. Euler Paths and Circuits were named after Leonhard Euler, who asked the question: “Is there some route in this city wherein one would cross each of the seven bridges once and only once?”

“An Euler path must include two or less odd degree vertices. […]  In simplest form, an Euler path is a set of edges that is connected, and an Euler circuit is a set of edges that is connected and begins and ends at the same node. An analogy would be an electrical circuit. Electricity can flow in a closed circuit, but not an open path.”

 

RSA Encryption Cryptography
Camille Clark, Layke Jones, Isabella Lane, Aza McFadden, and Lizbeth Otero

The RSA Cryptography problem set introduces the field of Number Theory through modular arithmetic, prime numbers, and prime factorization. RSA cryptography is one of the most widespread methods to transmit codified information and has several applications in everyday technology.

“[…]  A common divisor is an integer that all the numbers in a given set can be divided into without a remainder. To calculate the of 2 numbers, you need to write out the prime factorization. (Camp directors’ note: the greatest common divisor (gcd) of two or more integers, not all zero, is the largest positive integer that divides each of the integers without a remainder.)

For example, let’s consider 8 and 12. The prime factorization of 8 is 23, while the prime factorization of 12 is 3*(22). Then, take the largest factor that overlaps in the two factorizations. Here, 22 is the largest factor in common between the prime factorizations of 8 and 12; then, 4 = gcd(8,12).

We say that two integers a and b are if gcd(a,b) = 1, where a and b don’t need to be prime themselves. For example, if a = 35 and b = 8, then gcd(a,b) = 1, but neither is a prime.”

 

Elliptic Curve Cryptography
Mukta Dharmapurikar, Anagha Jandhyala, Savanna Jones, and Ciara Renaud

In the Elliptic Curve Cryptography (ECC) problem set students learn how to apply this fascinating method of encoding, transmitting, and deciphering information. Elliptic Curve Cryptography is an interesting application of very theoretical concepts from Algebraic Geometry and Abstract Algebra.

“[…]  While the road to understanding Elliptic Curve cryptography was interesting and exciting, there were many twists and turns along the way. Our greatest challenge was that ECC is extremely hard to conceptualize as most of the math differed from our previous understandings and was often very theoretical or abstract.

However, we thoroughly enjoyed learning about topics in math, typically not discussed in school. For example, on the first day, we were learning about modular arithmetic. It was a difficult concept to grasp because it was fundamentally different than what we had learned before. Over time, just by working through the problem set, we became more and more comfortable with the topic, even going as far as being able to explain how it works to other people.

This goes to show, that even when faced with a very difficult problem set, if you keep persevering, eventually you will understand the math. Girls Talk Math has really taught us to never give up, and increased our confidence in learning higher level math.”

 

Mathematical Epidemiology
Camilla Fratta, Ananya Jain, Sydney Mason, Gabby Matejowsky, and Nevaeh Pinkney

The Mathematical Epidemiology problem set introduces the concept of modeling as a whole and in particular focuses on modeling disease spreading in populations. In this problem set campers have used an applet in Python.

“[…]  A mathematical model is an equation used to predict or model the most likely results to occur in a real-world situation. We used these types of equations to model the spread of a disease in a population, tracking the flow of populations from susceptible to infected to recovered. In real life scenarios, there are too many variables to fully account for, so we only were able to place a few in our equations. This made the models less accurate, but at the same time very useful to us in our problem set. They gave us a good idea of how things worked in an actual epidemic and helped us to understand what mathematical modeling really is.”

 

Quantum Mechanics
Izzy Cox, Divya Iyer, Wgoud Mansour, Ashleigh Sico, and Elizabeth Whetzel

The Quantum Mechanics problem set starts by explaining why classical mechanics does not describe properly the behavior of subatomic particles. It then introduces the main concepts of quantum mechanics, in particular focusing on the wave-particle duality, i.e. the fact that mass can be described as both a particle and a wave. As part of their problem set, campers ran a physical experiment to measure Planck’s Constant.

“[…] Quantum Mechanics is the physics of molecular and microscopic particles. However, it has applications in everyday life as well. If someone asked you if a human was a particle or a wave, what would you think? What about a ball? What about light? Not so easy now, is it? It turns out that all of those things, and in fact, everything around us, can be expressed in physics as both a particle and a wave.”

“[…] The realm of physics gets much stranger when it gets smaller! […]  [Quantum mechanics] is arguably one of the most complicated fields of physics, where all traditional rules are wrong. There is much still being added, and so much more to be discovered.”

 

Knot Theory
Jillian Byrnes, Monique Dacanay, Kaycee DeArmey, Alana Drumgold, Ariyana Smith, and Wisdom Talley

The Knot Theory problem set discusses the fascinating field of Abstract Geometry that deals with knots. Maybe surprisingly, there is a Mathematical theory behind tying and untying knots which can be described formally with algebraic symbols. This problem set is a Mathematical approach to knots and how to study and classify them.

“[…]  The Reidemeister moves are the three possible manipulations of knots that are used to find out if two diagrams represent equivalent knots. None of them physically change the knot, because they don’t make any cuts or make the knot intersect itself, so if the two diagrams are equivalent, they are related through a sequence of these three moves:”

Three examples of Reidemeister moves: I, II, III

 

Classification of Surfaces
Ayanna Blake, Lisa Oommen, Myla Marve, Tamarr Moore, Caylah Vickers, and Lily Zeng

The Classification of Surfaces problem set deals with questions of shape, size, and the properties of space. Starting from a Mathematical definition of surfaces, students learn about aspects of a number of shapes, some of which they are already familiar with and some that do not exist in 3-dimensional space, with the aim of classifying them.

“[…]  Before we start off with explaining the basics, we give the definition of a surface, which is an example of a two-dimensional object. When talking about dimensions, basically it’s a way of classifying how many directions of travel an object has.

For example, a line on a piece of paper would be one dimensional because you can only go up or down on that line. A sheet of paper would be two dimensional because you can draw up or down and side to side. A room would be three dimensional because if you imagine throwing a ball in the air, it can move up or down, side to side, and forwards or backwards.”

 

* Girls Talk Math has been funded through the Mathematical Association of America Tensor Women and Mathematics grant which has supported the camp for the past three years. *

 

Peer edited by Rachel Cherney.

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Putting the Brakes on CRISPR

CRISPR-Cas9, more commonly referred to as CRISPR, has been one of the hottest terms in science over the last few years. For goodness sake, Jennifer Lopez is the executive producer of the prospective NBC bio-terror drama CRISPR, which is centered around the gene-editing technique. Starting in 2012, CRISPR began its rise to becoming the newest and most promising gene-editing tool. It has since transformed the way many labs conduct research and has turned into a multi-billion dollar industry. Even though CRISPR has become more mainstream with seemingly limitless applications, recent research has shown we must move forward cautiously and be patient as this technology matures. 

 

CRISPR Therapeutics currently is the largest biotechnology company that specializes in gene editing via CRISPR. After initially opening at $15 per share on October 19, 2016, CRISPR Therapeutics climbed to $74 per share and had a market cap of $3.47 billion on May 30, 2018. The company’s surge was in response to their announcement in April 2018 that they were moving forward with an Investigational New Drug (IND) application with their partner Vertex Pharmaceuticals Inc. The two companies also had plans to start a Phase 1/2 clinical trial to treat adults with sickle cell disease using CRISPR gene-editing technology in both the United States and Europe. On May 30, 2018, CRISPR Therapeutics announced that the FDA put a clinical hold on its IND application pending the resolution of certain questions by the FDA. The announcement offers no insight into the questions or concerns of the FDA, but this news was enough to spook investors. CRISPR Therapeutics’ stock fell 20.2% in June and 19.1% in July. Currently, it is trading about $48 per share and its market cap is valued at $2.295 billion.

Only part of the CRISPR Therapeutics decline can be attributed to the FDA’s announcement. Three separate studies published this summer negatively influenced investors outlook on CRISPR Therapeutics, as well as the two other major biotechs specializing in CRISPR, Editas Medicine and Intellia Therapeutics. The first study, which was published June 11 in Nature Medicine, highlights how double stranded breaks in DNA caused by Cas9, the molecular scissors of the CRISPR-Cas9 system, are toxic to human pluripotent stem cells (hPSCs). hPSCs, cell lines similar to an early embryo that are capable of differentiating into other cell types, depend on the tumor suppressor protein p53 for its toxic response to prevent growth of aberrant cells. Given that p53 mutations are prevalent in hPSCS, there is also a concern that hPSCs engineered using CRISPR-Cas9 could cause cancer. A second study, published in the same issue of Nature Medicine on June 11, used human retinal pigment epithelial cells and reached a conclusion similar to the previous study, CRISPR-Cas9 induces a p53-dependent DNA damage response. In addition, this group also found CRISPR-Cas9 causes cell cycle arrest. Both studies clearly indicate that it is crucial to monitor p53 function when developing cell-based therapies using CRISPR-Cas9.

A third study, published July 16 in Nature Biotechnology, further casts a cloud of uncertainty over CRISPR. This study revealed that CRISPR-Cas9 causes “significant on-target mutagenesis, such as large deletions and more complex genomic rearrangements at the targeted sites in mouse embryonic stem cells, mouse hematopoietic progenitor and a human differentiated cell line.” Even though these three articles were all released in the last two months and were the primary reason investors in CRISPR-based companies have been more reluctant to invest, two other studies also show negative effects of CRISPR. One shows an adaptive immune response to Cas9 and the other shows major genomic rearrangements from in a mouse model following the use of CRISPR-Cas9 also show negative effects of CRISPR.

Even though it has been a disappointing summer for companies specializing in CRISPR, CRISPR Therapeutics, Editas Medicine, and Intellia Therapeutics remain adamant that the future looks bright. For many people, these studies might be more a speed bump rather than a road block.

Peer edited by Justine Grabiec.

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Science communication drives away my graduate anxiety

I did not know graduate depression was a thing almost a decade ago when I studied for my Master’s degree. I experienced a period of depression symptoms but I did not confide in or consult with anyone. I felt ashamed to talk about my problems. “Didn’t everyone survive and eventually graduate?” I thought to myself; it must be my poor ability that stopped me from making progress. Now I am halfway into my Ph.D program and I realize an essential element to motivate myself: the exercise in science communication.

When I finished my undergraduate, the transition to advanced research did not come easily despite continuing in the same research lab. At the beginning of the first year, I started to suffer from insomnia. Every night in bed, my brain would not stop emulating the worst scenario. I could get humiliated in public or get kicked out of the program for poor performance. Often I felt my anxiety so intensely that I jumped out of bed in the middle of the night. I screamed, silently, so that I would not perturb my roommates. I cried to myself, declaring my desire to quit. However, I did not dare to talk about it and acted normal the next day. I also avoided contact with my advisor. I would sneak out of the office when he came in, pretending to go for a walk so I wouldn’t have to talk about my research progress which was nonexistent.

My lack of motivation continued for a semester until I returned from a week-long holiday. During the break, I revisited a couple of critical journals relevant to my research which I had a hard time fathoming. I tried turning numbers into schematics and summarizing their work with my own words. My advisor was impressed that I was able to convey the project after a short period. He did not know what happened to me during the break, and neither did I. Without knowing it, I was learning to communicate science to a broad audience. Only, at first, that audience was me. With better communication with my advisor, my anxiety disappeared. I graduated in the expected period and began to climb the career ladder in my field.

Looking back, I did not know I was experiencing mental depression. I was not even aware that I fixed my crisis through science communication practice. Years later, I decided to accomplish a bigger goal: to earn a doctoral degree. What I have feared the most, is that the graduate anxiety which once hit me would not just resolve itself, even though I now felt more mentally mature. Doing my graduate work and living in a new country, the social and language barriers frustrate me in many ways. I felt the need to find a community where I can get support and also advocate for myself and others in my situation. I wanted to have a supporting network to protect me before the graduate depression had its chance to strike me again. I started searching for an opportunity to reach out, and that was when I met the Pipettepen and began my journey of science communication training.

To get my feet wet, I made a start on editing work. And then my first article discussing the effects of the nanomaterials on our daily life was published, a topic inspired by my research project. I remember I worried about failing to meet the expectations and any tough judgment. Thanks to the good and helpful suggestions from the Pipettepen editors along the way, my confidence in writing built up since the first attempt.

I am particularly fond of writing regarding effective communication. Science writing fuels me with the energy to keep on the track of graduate life. Not only is writing an independent activity which suits my personality, but the process also provides me with a safe place to develop my voice. The process of organizing an article also helps my professional work. It makes me less fearful of starting a longer and denser manuscript. More than that, I have begun to explore science and science communication in many aspects. I attended the regional ComSciCon workshop in Triangle this spring, an event that I would have been afraid to even think about if not with writing experiences in the Pipettepen. I set up my Twitter account and get to glimpse another side of scientific expression and events that I did not even know existed!

https://www.pexels.com/photo/alone-anime-art-artistic-262272/

Graduate life has its ups and downs. We all have our very own struggles. Keep looking for a place to develop your voice.

 

Graduate life can be very stressful. Sometimes I am in limbo and doubt my decision to earn a Ph.D., and still don’t know what I want. The truth is, I always know what I want, and that is to be happy and live my life to the fullest. Pursuing a Ph.D. degree is one of the life goals set in my early research years. I am approaching this goal while acknowledging the mental health crisis among graduates. By doing things I am good at and enjoy, along with the main work of research, the wheels of my graduate life can keep turning.

You might not find writing as enjoyable but remember, there are many channels to reach out and express your voices. Most importantly, it is to build a supportive network where you can transform your frustration or anxiety into something positive.

Peer edited by Gabrielle Budziszewski.

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Are female túngara frogs better at learning than males because of how they breed?

Image from Alexander T. Baugh (Encyclopedia of Life)

A female (above) túngara frog chooses a male (below) to mate with based on his call. Although it is difficult to tell, these frogs are small enough to fit on a quarter!

 

 

 

 

 

 

 

 

 

As Charles Darwin was the first to document, the behavior, physical features and sexual activities of species. These observations can frequently be understood through the lens of thousands or even millions of years of natural selection. Random genetic changes arise and organisms become “mutated,” so to speak. In turn, organisms with the best-suited characteristics for their environment (which of course, can also change and set things back to square one!) are more likely to survive and continue to reproduce and populate their current environment.

Most people tend to associate these adapted characteristics with the famous beaks of Darwin’s finches, or maybe the hilariously long necks of giraffes. But one often overlooked feature is the brain. The control center of behavior, albeit quite enigmatic in how it operates, functions due to the coordinated firing of many small units known as neurons. The characteristics of the brain that are most interesting to me are cognitive abilities, specifically, the abilities of learning and memory. Superior learning and memory abilities may be selected for within a species for various reasons. For instance, the black-capped chickadee (Poecile atricapilla) can be found all over North America, from Alaska to Colorado. When birds from these areas were behaviorally assessed and their brains were compared, it turned out that birds from Alaska were more efficient at hiding and finding food, in addition to having larger hippocampi – the area of the brain responsible for long-term memory (Pravosudov & Clayton, 2002, Croston et al. 2015). What’s the proposed reason for this? Alaskan birds needed to be better than Coloradan birds at saving food during the summers then finding it later to survive their longer winters (Pravosudov & Clayton, 2002, Croston et al. 2015).

These differences in brainpower aren’t just explained by food hoarding habits though! They can also be observed in the polygamous meadow voles (Microtus pennsylvanicus). Males exhibit an increased ability for spatial memory over females likely due to their breeding behavior. The promiscuous males greatly expand their home ranges in order to seek out and breed with a multitude of females (Gaulin & FitzGerald, 1989). As expected, male voles have comparatively larger hippocampi than female voles (Jacobs et al., 1990) and perform better on spatial memory tasks (Gaulin, FitzGerald & Wartell, 1990).

As these natural ecological differences within species are recognized, it continues to provide credence to the idea that learning and memory skills can adapt within species while most other characteristics remain the same. This idea led to the túngara frog (Physalaemus pustulosus), whose mating behaviors rely solely on the female’s assessment and choice of males. While males remain stationary in a breeding pond and produce breeding calls, females visit multiple males before ultimately deciding on a mate (Ryan, 1985). In turn, females that are able to better recall the locations of particular males in a pond will be more successful in finding the best possible male (Ryan, Akre, & Kirkpatrick, 2009). These frogs have had to mate for millions of years and certain characteristics have become selected for within the species. It makes sense that female túngara frogs have adapted to have greater spatial memory and cognitive abilities than males. But do carefully controlled learning experiments justify this claim?

Since we can’t go back and observe this process happening over the many millions of years, the next best option is to attempt to gauge for ourselves whether or not this theory may be valid. Unsurprisingly, it is not a simple task to assess memory and cognitive abilities in animals with brains that are smaller than a pea. The first experiments done to test this utilized the simplest possible method in order to see if frogs could distinguish between two colors to learn how to escape a two-arm maze (Liu & Burmeister, 2017).

The purpose of this experiment was to train frogs to associate the reward of exiting a bright and arid maze (not an idea environment for a nocturnal rainforest habitat!) with the red door that allowed them to exit the maze and return to their shaded enclosure. Results showed that although female frogs learned to exit the maze using the red door, male frogs didn’t respond to the color of the door at all, instead preferring to rely on turning either right or left, and performing as well as females when they were able to use these turning cues to turn the same direction in consecutive trials.

Image from Liu & Burmeister, 2017.

A schematic diagram of the two-choice maze used in these experiments.

 

That’s confusing – males can only remember how to turn left or right but ignore colors? Does this mean that females can learn better after all? Seeking to explain that question, I replicated this original experiment for my thesis research, using twice as many frogs and removing the ability to use turn cues at all. Instead, frogs were released in a random orientation for every single trial. As expected, the frogs learned to exit the maze, but unexpectedly, both males and females alike learned the maze at the same rate of success. It seemed that male frogs were in fact not ignoring the colors at all, but perhaps simply reluctant to pay attention to colors if they were able to simply turn left or right and remember their last turn direction.

Although I saw that males and females could demonstrate their ability to learn a simple color association, a strange pattern emerged in my experiment. In training half of my frogs to use the red door and the other half to use the yellow door, it seemed that the frogs trained to the red door were more successful than their yellow door brethren. I sought to address this bias in a follow up experiment by removing colors entirely and instead utilizing monochromatic patterns. Although frogs are known to be able to see black and white, it seemed that the chosen patterns were not distinct enough for the frogs, and they failed to show evidence of learning.

Something that a lot of people don’t realize about science is how many failures could possibly be hiding behind the triumphant headline of a successful result. Despite the questions of whether or not there is a sex difference in the ability to learn in túngara frogs, it is clear at this point that the distinction is not as cut and dry as it was once thought to be. Follow up experiments will aim to elucidate the differences between male and female túngara frogs, by continuing to seek possible answers (or maybe produce more questions…) using improved black and white cues, auditory cues, and removing all cues but turning cues. Although our understanding of how evolutionary mechanisms can alter the attributes and abilities of the brain is still in need of significant contributions, these experiments show that even without access to a DeLorean, it is still possible to work towards elucidating our evolutionary past.

Peer edited by Emma Hinkle.

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A Blood Test to Diagnose Autism Spectrum Disorder

When it comes to diagnosing children with autism spectrum disorder (ASD), earlier is better. The American Academy of Pediatrics recommends screening children for ASD between 1.5 – 2 years of age. However up until now, diagnosis of ASD has been driven by clinical observations, often behaviors not yet formed in children this young, and consequently most children are diagnosed around 4 or 5 years.

Earlier diagnosis allows for specialized interventions that capitalize on the plasticity of toddler’s brains while implementing proven behavioral therapies like applied behavioral analysis and developmental relationship-based approaches to promote communication and social interaction.

One of the challenges in diagnosing ASD is the variability in symptoms along the spectrum, and the change in developmental standards with age. Some symptoms common to ASD are common to other disorders as well and therefore do not aid in diagnosis. With 1 in 59 children identified with ASD and median diagnosis age ranging from 3 to 5 years, research in the field has been two-pronged: characterizing the variability in the disorder and improving diagnostic tests.

Depiction of ASD aspects at each part of the spectrum courtesy of Rebecca Burgess

Depiction of ASD aspects at each part of the spectrum (image courtesy of Rebecca Burgess).

A blood test to diagnose ASD has been nothing but a pipe dream…until now. Last month, the first blood test for autism was confirmed as highly accurate in a secondary trial. Blood tests for other diseases often test for a single marker, such as carcinoembryonic antigen for colon, lung, and liver cancer, or TRU-QUANT (CA27.29) for breast cancer. Efforts to identify a single metabolic marker for ASD has fallen short. So what was the reason for success in this new endeavor? Instead of exploring for a single metabolite that predicts ASD diagnosis, researchers from the Rensselaer Polytechnic Institute (RPI) utilized big data methods to find patterns in metabolites involved in metabolic pathways implicated in ASD physiology. Both pathways have been implicated in ASD physiology, and by using information on 24 metabolites instead of just one, the predictive algorithm had 88% accuracy rate when applied to a new data set. The RPI lab, led by Juergen Hahn, is not an autism-focused lab. Instead, the Hahn research group focuses on new techniques for systems engineering and analysis and the application of those analyses to biochemical systems – like the methionine and transsulfuration pathways for ASD. Unlike behavioral symptoms that do not emerge until later in development, a blood test can be administered at younger ages allowing for earlier diagnosis and intervention.

There are several things to consider moving forward with a diagnostic test for ASD, including:

  1. Will the algorithm be validated in additional data sets?
  2. Are the metabolites readily measured in ASD diagnostic settings?
  3. Does the algorithm perform similarly across the autism spectrum?

Will this test change the face of ASD diagnosis and treatment – what do you think?

Note: This article refers to the autism spectrum as “Autism Spectrum Disorder (ASD)” parallel with current research areas. However, many involved in autism spectrum advocacy and collaboration argue to drop the term “disorder” as well as labels such as “high functioning” and “low functioning”. You can learn more here from the Art of Autism.

Peer edited by Rachel Haake.

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Metabolic Therapies with Dr. Dominic D’Agostino

Dr. Dominic D’Agostino, University of South Florida

I had the pleasure of interviewing Dr. Dominic D’Agostino, a scientist with an interesting and diverse research portfolio that includes collaborations with NASA and the US Navy. Dr. D’Agostino majored in Biology and Nutrition Science at Rutgers University where he developed a fascination with Neuroscience. Dr. D’Agostino then obtained his PhD in Neuroscience and Physiology from Rutgers studying neural control of autonomic regulation, specifically brainstem mechanisms that control cardiovascular/respiratory function. His graduate work within the central nervous system led Dr. D’Agostino to Wright State University for a  postdoctoral fellowship where he developed a system to mitigate central nervous system oxygen toxicity in Navy Seal War Fighters. Specifically, D’ Agostino leveraged the neuroprotective character of the ketogenic diet to reduce oxidative stress in the undersea divers. This research exposed D’Agostino to the influence of metabolism, especially within the CNS, and how it may be leveraged to mitigate debilitating disease. Since then, Dr. D’Agostino has emerged as the leading expert on the ketogenic diet. His work has demonstrated the therapeutic potential of the ketogenic diet in the treatment of cancer, its ability to mitigate the physiological impairments associated with extreme environments, and propelled metabolic therapy research forward as we begin to understand just how powerful nutrition can be.

The Ketogenic Diet is comprised primarily of fatty foods such as fish, red meats, and nuts.

The Ketogenic Diet is comprised of primarily fat-rich foods such as fish, red meats, and nuts.

What is a Metabolic Therapy?

Metabolic therapies utilize macronutrients, vitamins, or minerals obtained through a specified nutritional profile to treat disease. Moreover, these treatments often aim to alter a metabolic abnormality that results from disease. For example, to treat phenylketonuria, a rare metabolic disorder, a plethora of metabolic therapies are employed including supplementing a variety of amino acids and enzyme cofactors. Additionally, and most relevant to this article, treatment of cancers such as glioma can consist of traditional chemotherapy and metabolic intervention including increasing fat consumption while decreasing carbohydrate consumption; this is the basic principle of the ketogenic diet.

The ketogenic diet is a high fat, low protein, and very low carbohydrate regimen that aims to achieve nutritional ketosis, a metabolic state in which fats are utilized as the primary source of energy through a metabolic process called beta oxidation. Interestingly, beta oxidation is not the cell’s preferred source of energy production. Rather, the cell would prefer to utilize carbohydrates as the primary source of energy through another metabolic process termed glycolysis, only breaking down fats when energy requirements are high and cannot be met through glycolysis alone. Thus, achieving ketosis is quite difficult as it requires a fundamental alteration in the way our bodies break down food to make energy.

Both beta oxidation and glycolysis feed into oxidative phosphorylation (our main source of energy production), so put simply, our bodies will utilize whatever is available for energy and in this case, we want it to utilize fats to achieve ketosis. Nutritional ketosis is achieved when blood ketone levels (ketones are byproducts of fat metabolism) exceed 0.5 mmol; this is achieved through a diet comprised of approximately 85% fats. But, how does this contribute to the treatment of diseases such as epilepsy and cancer?

First, it is important to realize that carbohydrate restriction in combination with a high fat diet will effectively maintain low blood glucose levels and suppress insulin signaling. Studies suggest that hyperglycemia, high levels of glucose in the blood, increases hyperexcitation of neurons in epilepsy and tumor cell proliferation in cancer. By following a strict ketogenic diet, it is possible to deprive the cancer cells of glucose (their primary source of energy) while normal cells can maintain function by simply using fats as energy.

Ketosis has also been shown to be protective against damaging metabolites. Specifically, ketone bodies can mitigate oxidative stress. Oxygen free radicals are highly reactive oxygen atoms that can catalyze unfavorable chemical reactions and are a normal byproducts of aerobic (oxygen-requiring) metabolism. Some research has indicated that metabolites of the ketogenic diet, particularly β-hydroxybutyrate, can effectively reduce oxidative stress by inhibiting highly influential signaling pathways, further strengthening the therapeutic properties of the diet.

Lastly, the ketogenic diet is neuroprotective by a plethora of different mechanisms including mitigating oxidative stress, preventing apoptosis, decreasing excitotoxicity by altering glutamate release and increasing autophagy (recycling and degradation processes) via mTOR inhibition. For example, increases in autophagy have propelled ketogenic diet research into realm of neurodegenerative disease treatment where ketone body inhibition of mTOR may allow for the clearance of problematic protein aggregates in diseases such as Alzheimer’s, Parkinson’s and Huntington’s.

The Ketogenic Diet Outside the Clinic

When the ketogenic diet is used to treat disease, it is a very strict nutritional regimen with a therapeutic purpose. Unfortunately, the diet initially gained traction within the public sphere as a low-carbohydrate weight loss diet. This is demonstrated with fad diets such as the Atkins or South Beach diets which market carbohydrate restriction as the key to weight loss, unfortunately overlooking the basic metabolic principle that an overall restriction of calories, not carbohydrates, will result in weight loss. This unrightfully demonized carbohydrates as the source of fat gain, placed the ketogenic diet in a group with other, non-science based low-carbohydrate diets, and stripped the proven metabolic therapy of its scientific integrity.

Yet, thanks to the research and communication of scientists like Dr. D’Agostino, more people have begun to realize the evidence-based benefits of the KD, how it differs from other low-carbohydrate diets, and have incorporated a more sustainable version (compared to the clinical ketogenic diet) into their every day diet. Often, this macronutrient profile is more liberal in protein, but still high in fat and low in carbohydrates. A keto athlete will consume 1.2-2.0 grams of protein per kilogram of lean body mass (optimal for muscle anabolism), no more than 50 grams of carbohydrates, and the rest of his/her calories will come from fats with caloric consumption dependent on the athletes’ physique and performance goals. In addition to reaping some of the anti-inflammatory and neuroprotective benefits of the diet, some research has shown that athletes are better able to maintain lean body mass and overall performance while on  a fat-centric diet.

From assisting Navy Seals in their underwater missions to treating terminal brain cancer, the ketogenic diet has proven to be beneficial in and outside the clinic. The ketogenic diet currently stands as a first/second-line treatment for various forms of epilepsy, and there is still much research to be performed regarding the its’ role as a metabolic therapy. With time, scientists will begin to uncover the limitless therapeutic targets for this powerful nutritional regimen.

Who would have thought a diet could be so powerful?

 

Peer edited by Tamara Vital.

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My Experience Writing for a Trade Magazine

During my last year of graduate study in physics, I attended the 2015 ComSciCon Triangle workshop and learned that I could make a career out of science writing. So I began writing for the Pipettepen and applied for the AAAS Mass Media Fellowship in 2016 as I finished writing my dissertation. I was accepted and ended up at Voice of America in Washington, D.C. for 10 weeks. I had three really great editors who not only showed me the ropes of being a science journalist, they also worked with me on producing radio and TV pieces. It was fun and I learned a lot, but I still didn’t feel ready to put all my eggs in the science writer basket.

I worked as a part-time adjunct faculty and applied for full time jobs. I applied to a few writing jobs here and there but didn’t have much luck for a year and a half. Then one day a job popped up in one of my many email alerts. It was for an associate editor position at a magazine that had something to do with the healthcare industry. The job description was pretty vague, and they just wanted writing experience so I applied.

The next morning, after I dropped my kids off at daycare, I received a phone call from the Editor in Chief of the magazine. After we spoke for a while he said he was intrigued and wanted me to come in for an interview. When I arrived at the office a few days later it was eerily quiet except for a single pair of hands typing on a keyboard. The office had eight cubicles in the middle of the room with high walls so you couldn’t see over them, but I could tell 7 out of 8 of them weren’t occupied. Around the perimeter were offices that were all occupied. I chatted with the Editor in Chief and he told me about what they did there. They were a trade magazine aimed at administrators of outpatient surgery centers. If you’re not familiar (I wasn’t) these are places where people go to have surgical procedures in under 24 hours. Cataract surgery, total knee and hip replacements, and many ENT (ears, nose and throat) procedures are all done in under 24 hours.

The job entailed interviewing nurses, surgeons and administrators that worked at outpatient facilities each month about topics such as multimodal pain management and how to pass an accreditation survey. Articles with a single source were ghostwritten by the editors, meaning that the editor wrote the piece but the source would be the author when the article went to print. Articles with two or more sources would be authored by the editor. Sounded fun and easy enough. After doing a test write, where I interviewed an administrator and wrote up a short essay about a space-saving idea she implemented at her facility, they hired me. They also gave me the salary I asked for. I totally low-balled myself but I didn’t care. I finally had full-time work writing!

This magazine put out new issues monthly and editors were assigned their topics the first Monday of each month. Usually assignments consisted of 2 to 3 feature articles and 2 departments. Departments are two-page articles that run every month covering current issues affecting anesthesia providers or infection preventionists for example. Feature topics varied month to month and were actually decided well in advance so the publication could solicit advertisers to buy ad space. Some months we were assigned 2 additional features for a supplement issue. It wasn’t unheard of for an editor to have 4 to 5 features and 2 or 3 departments during months when a supplement issue ran.

It sounds like a lot. But it’s not all. Every Tuesday we had to write up short summaries of current news we found that affected outpatient surgery centers to send out to our readers in a weekly email blast. I was also put in charge of our daily emails. Every weekday we sent out the feature articles from the previous month reimagined as a “Tip of the Day”. The headlines and email subjects had to be catchy and clickbaity. This was probably my least favorite thing to do. I did my best to be as truthful as possible and still make them interesting enough to click on.

This brings me to the editing process. The other two associate editors I worked with were seasoned journalists. At both the Pipettepen and Voice of America, my editors usually helped me reword things if they weren’t clear and maybe changed the lede of my article if it wasn’t engaging enough. If things were really unacceptable, they’d ask me to rewrite. For the most part they left my voice and my stories alone though. My co-workers said that had been their experiences too.

This magazine, however, had established a certain voice. The magazine wanted their readers to feel like they were having a candid conversation with another professional. So the more senior editors took a very heavy hand when editing anything we submitted. No matter how early we turned in our pieces, we usually didn’t see the articles again until they were posted to the website or we proofed them before going to print in the magazine. So we didn’t have much of a say in the final published article. It took me a while to get used to the process. Actually, I’m not sure I ever fully accepted it.

Proofing was another interesting experience that differed from other experiences I had. At both the Pipettepen and Voice of America, only one or two additional eyes would look over my pieces before they were published. Since this was a print publication, mistakes can’t be corrected, so every piece had at least four sets of eyes that looked over it. As described above, after an editor submitted their piece, the senior editors made their changes. Then the senior editors copied and pasted the article into the magazine layout and adjusted it to fit between the images and ads. Once it looked right, I had to print out the article and proof it. Then I passed my corrections to the Executive Editor. He updated the piece and proofed it again. Then the other associate editor proofed it and gave it to the Editor in Chief to do one final proofing. Now when I say proofing I mean grammatical corrections or checking the numbering in lists. We rarely pointed out issues that would need significant re-writes due to time constraints.

Since we were only assigned our pieces at the beginning of the month, the last week of the month seemed hectic and stressful for the more senior editors. They not only had to write their own pieces but also edit ours. The tensions and nerves of the more senior editors were usually high that last week of the month and it made for a very unpleasant work environment.

And then, after we went to print, a new month would begin and everything would be calm and pleasant. I started to realize why there was only one set of hands typing on the keyboard that day I interviewed. Most associate editors quit after a few months of the crazy schedule and tense, unpredictable atmosphere. When I started, there was one other associate editor who had been there for three months. She left a month and a half after I started. A new associate editor started right after she left. But he left after two and a half months. After watching two friends quit in 5 months, I decided to leave too.

Despite the end of the month craziness, I absolutely loved the writing. Being assigned topics I knew nothing about was exciting for me. Everyone I interviewed was friendly and more than happy to explain things I didn’t know. I really enjoyed the process up until I had to turn in my work. Would I do it again? For another outlet, absolutely! The only reason I left was because of an unwelcoming environment that made it difficult for me to write. So I’ll leave you with a list of things you should be aware of if you’re going into the magazine business that I’m definitely keeping in mind going forward.

  • Read the room – How many other editors/writers are working there currently? Ask how long people stay. I asked during my interview and got a carefully worded answer. Something along the lines of: “It varies. Some stay for 15 years others stay for a few months.” The truth was that only the more senior staff had been there that long. I heard from other employees that the longest anyone else stayed was 5 years.
  • Editor style – It might be a good idea to ask what the editing process is like before you start. Some editors may heavily rewrite your work and not give chances for rewrites while others may send your pieces back to you with comments and suggestions.
  • Know your worth – Ask for a range in salary, not a single number. Glassdoor will give you an average salary range for any position. Use that as a starting point. If you have an advanced degree, you can use that to justify a higher range.
  • Alerts – Set up Google Alerts for topics. Google alerts are actually a great way to find topics to write about if you don’t have access to the AAAS website for embargoed journal articles — EurekAlert. It also lets you see how authors are approaching a story, so you can come up with a different angle. You can even set the time of day you get the alerts. I always found that mornings allowed me to get the freshest news.
  • Forums – Join the forums of the professional societies where your readers are members. You’ll be able to keep up with current topics of interest and find sources to interview for those topics.
  • Passive voice – Academia often overlooks the use of passive voice. So just be aware of this and know that your editors will call you out on it. I found this article helpful in identifying passive voice in my writing.
  • Start early – Research and reach out to sources as soon as you get your assignments. Potential sources are very busy but most likely want to talk to you. The earlier you contact them the more time and flexibility you have to schedule interviews.
  • Keep track – Have a running to-do list of what your next goal is for each article. I always updated mine at the end of the day so the next morning I knew exactly where I was with each feature. The different stages usually looked like
    • Find sources – If you don’t hear from them after one or two days, follow-up
    • Interview source
    • Outline article – Ask source follow-up questions
    • Write article – Ask source follow-up questions
    • Send draft to source for review

    It always helped me to have the process written out so I could see each task I had to accomplish and how long I had to do it.

As a graduate student who made the leap into science writing, I had a ton of skills that made me a successful trade magazine editor. My ability to research topics thoroughly and quickly allowed me to get up to speed on the topics I had to write about. There are also lots of similarities between earning a Ph.D and earning a certification in healthcare or a medical degree! So it was easy for me to make connections with sources. Writing for the Pipettepen allowed me to hone my writing skills and amass a library of writing samples (a.k.a. clips) to use for any job or fellowship applications. The AAAS Mass Media Fellowship threw me into science journalism and forced me to learn how to find and interview sources on a deadline.

Reflecting on my experience working at a trade magazine, I learned that the time I spent in graduate school and science writing made me a successful editor. But I also learned the signs of a tense, unpredictable work environment and that I’m not comfortable with certain editing styles. Trade magazines, especially in an unfamiliar field, can be a great way for non-journalism students to get their feet wet in the sea of journalism, as long as the editors provide a supportive and respectful space. If you have the clips go for it!

Peer edited by Amanda Tapia.

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Pharmacies of the Future: Chemical Lego Towers

Chemists and engineers are in the process of making on-demand production of pharmaceuticals less of an idea from a movie, and potentially a viable option for situations where medicines may not be easily accessible.

Imagine taking a vacation to an isolated rainforest resort.  You explored your adventurous side, hiking through the lush vegetation with a knowledgeable tour. Less than 10 minutes after arriving back at the hotel, an uncontrollable itch began on your forearms. It traveled up your arms, across your chest, and began rising up your neck. Was it from a bug or a plant you encountered during the hike? At this point, you are unconcerned about the cause, and just want a solution. The closest drug store is hours away; when booking the trip, it seemed like a great idea to pick the most isolated resort for your dream vacation. Even if the drug store was closer, it was not a guarantee that they would even have anything to help you. In the US, there were over 200 instances of drugs shortages from the years 2011-2014. There was no telling how difficult it would be to get medicine to this remote location.

You head to the front desk of the hotel, hoping they have something to give you for relief. They lead you down the hall and into a small room. There are a few chairs and an appliance that is similar in size and shape to a refrigerator. The employee enters a few commands into a keyboard and the machine starts working. In fifteen minutes, the employee hands you two tablets- diphenhydramine hydrochloride, more commonly known as Benadryl®.  

https://www.flickr.com/photos/mindonfire/3249070405

Diphenhydramine, better known by the brand name Benadryl, is one of the four medications that can be synthesized by the original compact, reconfigurable pharmaceutical production system.

While this scenario is not plausible in the current day, it will be in the near future. In a 2016 Science article, researchers from around the world introduced a refrigerator-sized machine that could make four common medicines. More recently, a 2nd generation prototype was released; the new model is 25% smaller and contains enhanced features necessary for the synthesis of four additional drugs that meet US Pharmacopeia standards. This is possible by technology known as flow chemistry. Flow chemistry is a development where chemicals are pumped through tiny tubes. When two tubes merge, a reaction between the two chemicals occurs, resulting in a new molecule. Compared to traditional chemical reactions (stirring two chemicals together in a flask), flow reactions are generally safer and happen faster.

In this new machine, there are different “synthesis modules,” or small boxes that contain the equipment to do a single chemical reaction. Much like an assembly line to build a car, pharmaceutical molecules are made by starting with something very simple, and pieces are added on and manipulated until it is something useful. In the case of pharmaceuticals, the assembly line consists of molecules and reactions. The modules, or boxes, can be rearranged to do the chemical reactions in the order needed to make the desired medicine. To make a different medicine, the modules must simply be rearranged. Researchers can use the original prototype to make Benadryl, Lidocaine (local anesthetic), Valium (anti-anxiety), and Prozac (anti-depressant), using different combinations of the exact same modules. As of July 2018, the FDA reported that both diazepam (Valium) and lidocaine were currently in a shortage, due to manufacturing delays.

http://www.columbus.af.mil/News/Photos/igphoto/2000125986/

On demand pharmaceutical production would allow access to medicines in rural locations and war zones.

The future of this technology would allow anyone to use it. A user could simply input the medicine they want, and computers would rearrange the modules and use the correct starting chemicals, and in about 15 minutes, you could receive the desired medicine. This technology has vast applications. It could help alleviate the aforementioned drug shortages. Additionally, it could allow access to medicine in locations where it may be difficult to ship to, including rural locations or war zones, often places that need medicines most. In these places, delivery may be difficult, and some medicines go bad quickly. With this technology, it would not be necessary to store medicines that could go bad; it could simply be made as soon as it is needed. This could also prevent waste from medicines that are not used before they go out of date. These developments could revolutionize the pharmaceutical industry and I look forward to seeing the good that these technology advances can lead to. 

Peer edited by Nicholas Martinez

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