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Congratulations to our 2019 CJSJ Finalists!
Jake azrolan- The Effects of Resveratrol and Nicotinamide Riboside on the Lifespan of Drosophila melanogaster
Resveratrol (RSV) is a widely marketed longevity supplement that is a naturally occurring polyphenolic compound found in many fruits including grapes, peanuts, and berries. The mechanism of action of RSV is dependent on the presence of a surplus of NAD+. Therefore, it is unclear how RSV might aid in longevity if not supplemented with NAD+. Drosophila melanogaster wild type were exposed to RSV and Nicotinamide Riboside (NR), a precursor to NAD+, either independently or in combination (RSV+NR) and compared to the control group.
About the author: Jake Azrolan is in 10th grade at Roslyn High School and enrolled in his school’s Independent Study Natural Science Research Program. This past summer he attended Columbia University School of Professional Studies and completed Introduction to the Physical Sciences, a 3 week summer program for high school students. Recently, he completed a study in the Roslyn High School laboratory that he designed on The Effects of Resveratrol and Nicotinamide riboside on the lifespan of Drosophila melanogaster. This research area was of interest because of numerous advertisements for resveratrol and NR supplements that claim anti-oxidative therapeutic effects and also claim to increase life span. He designed his experiment to test these claims and their effects on life extension in a model organism D. melanogaster.
Ross bernstein- Catecholamine Inhibition of IL-4 Induced B-Cell Activation
Though seemingly separate, the nervous system plays a major part in modulation of the immune system. The Vagus Nerve transmits signals throughout the human body to control essential bodily functions. A branch of the Vagus Nerve innervates the spleen, where acetylcholine, adrenaline, and noradrenaline modulate TNFɑ release, by targeting T-cells and macrophages. However, it has not been investigated how the release of these neurotransmitters affect B-cells, immune cells that secrete antibodies (IgG). B-cells and T-cells were isolated from WT-Black 6 mice and treated with varying neurotransmitters to compare the effects. After treatment, the cells were stained and examined through flow cytometry to compare the percentage of T-cells, B-cells, and activated B-cells present in the population of lymphocytes. Our analysis indicated that epinephrine and norepinephrine increased B-cell activation, but more surprisingly they inhibited B-cell activation by IL-4.
About the author: Ross Bernstein is a high school senior at Plainview-Old Bethpage John F. Kennedy High School. In his free time, he tutors Algebra and Life Sciences as well as plays guitar and reads books. He is heavily involved in his scholastic research program and is the President of his school's Mathletes Club. Over the past two summers, he has conducted biomedical research and performed clinical observations of physicians. He plans to pursue a career in medicine.
Catherine Buren- Analyzing the Effects of FXR and SP-C on Macrophage Inflammatory Response to Nitrogen Mustard and Ozone
This paper has been retracted as of May 2020.
About the author: Catherine Buren is a junior at Scotch Plains-Fanwood High School. She was fortunate to be selected for a competitive research internship program this past summer through the LSC Partners in Science program. Through this program, she was paired with a mentor from Rutgers University, Dr. Debra Laskin, and given the opportunity to conduct meaningful research in a state-of-the-art inflammation research laboratory. She is grateful for all those who supported her endeavors in the lab last summer.
Alan chen- A Taxonomic Morphometric Analyses between Extinct Dominican Amber Fossilized Formicidae from the Miocene and Extant Dominican Formicidae
This study analyzes Dominican fossil-ants from the Miocene epoch (20 MYA). The objective is to infer ecosystem changes from the evolutionary change over 20 million years by comparing Miocene Formicidae fossils to modern Holocene specimens. Morphometric data, consisting of body measurements, were gathered from fossil ants and compared to those of modern ants. The comparison showed an overall decrease of Formicidae diversity. There are also some traits that collectively exhibited evolution over time. Many traits, however, remained static. The evolutionary changes observed indicate some driving environmental change which exerted selective pressures—forcing adaptation. The fact that many phenotypes remained static suggests that traits remain favorable and that environmental changes over 20 million years were not dramatic.
About the author: Alan Chen is a Senior at Livingston High School, NJ. He is currently a high school researcher at the Barden Lab of NJIT, where he works to understand the relationship between living and fossil ant communities through morphometrics. He started to join the lab in December 2017, and he drew towards the morphometric analyses involved in paleomyrmecology. This research has garnered Alan several awards, most notably being named a Regeneron Science Talent Search Scholar in 2019. Outside of science, Alan is a Varsity Captain of his football team, as well as the principal cellist in his orchestra. Alan plans to pursue a career in biology and medicine, where he plans to continue research throughout his life and pursue medicine beyond college. He will study biology and finance at Washington University in St. Louis, while also planning to play football for the WashU Bears.
EMILY choe- Change in Drosophila Receptor Activity and Contraceptive Pill Efficiency Due to Antibiotics
The increase in the use of contraceptive pills is raising the question of the effect of antibiotics. Although some warning messages inform the public about the effect of antibiotics on birth control, uncertainties regarding the specificity, magnitude, and lasting consequences of the effect on contraceptives prevail. This study tested the effect of antibiotics on the contraceptive pill Minulet, consisting of estrogen and gestodene. Penicillin, Cephalosporin, Macrolide, and Non-steroidal anti-inflammatory antibiotics were used. These selected antibiotics are some of the most commonly used drugs for multiple widespread illnesses. Drosophila (fruit flies) were utilized as estrogen and Drosophila Estrogen-Related Receptor (dERR) are essential to Drosophila growth after the pupa stage [5]. This study examined whether the antibiotics affect the Drosophila by disassembling estrogen or hindering the development of dERR itself, as well as whether there are lasting effects. The results revealed that regardless of the order of exposure, there are negative effects on the birth control pill when taken with antibiotics. However, while the estrogen could be affected by the antibiotics, the dERR had not been affected. Therefore, the antibiotics decrease the effectiveness of the contraceptive pills when taken together but there are no lasting consequences.
About the author: Emily Choe is a passionate scholar in STEM, psychology, and human rights. She has been an intern at Cha Bio Company, one of the largest biotechnology companies in Korea. She also works as an arts editor for the Spectrum magazine for women’s rights and as the chief editor of the Yearbook club. In her free time, she immerses herself in yoga, creating art, teaching math, science, and Chinese as a peer tutor, and participating in Brooks School’s drama productions. Influenced by her mother who is a pediatrician, she has dreams to reach out to those in need through medical and psychological care in the future. Her goal is to be constantly learning and making positive change through her passionate fields, and hopes to keep on improving the world for those who need help.
vasu kaker- Facile Synthesis, Characterization and Electrochemical Testing of Lithium-ion battery cathode material
Lithium ion batteries (LIBs) are widely used in electronic devices such as mobile phones and laptops as well as electric vehicles. LIBs have the highest specific energy (amount of energy stored per kilogram of battery or electric material) out of all commercialized battery options. The cathode material used in LIBs is typically Lithium Cobalt Oxide (LiCoO2) of which the major chemical constituent is cobalt: a toxic, expensive, unsustainably sourced metal. In this study, we synthesised and evaluated the performance of an alternative, cobalt free cathode material, Lithium Nickel Manganese Oxide (LiNi0.5Mn1.5O4). It is much cheaper, less toxic, and has the potential to match the specific energy of Lithium Cobalt Oxide (LiCoO2) cathodes. LiNi0.5Mn1.5O4 was successfully synthesized through a new molten salt synthesis where precursors of LiOH, LiCl, Ni(OH)2 and either Mn2O3 (Mn3+) or MnSO4 (Mn2+) were mixed in a crucible and heated in a furnace. The sample was later characterized via X-Ray Diffraction and Scanning Electron Microscopy imaging. Battery cells were then assembled and subjected to electrochemical testing at room temperature. Our results showed a reversible capacity of 120 milliampere hours per gram (mAh/g) at 0.1 Coulombs (C) rate, and a discharge voltage of 4.6 Volts. The synthesized material exhibited a comparable specific energy to LiCoO2.
About the author: Vasu Kaker is a U.S. citizen currently in his sophomore year at the United World College of South East Asia in Singapore. He is passionate about scientific research with a specific interest in chemistry, material science, and its applications in energy storage technologies. He conducted his research at the Advanced Batteries Lab, National University of Singapore under the mentorship of Principal Investigator Dr. M.V. Reddy. He is also an avid juggler and a performing artist at the Bornfire Circus Troupe in Singapore.
Min Jae Kim- Fractal Analysis of Enzyme Active Site
Enzymes can only react with specific substrates that enter their active sites. However, daily observations lead us to conclude that substrates find their target enzymes in a matter of minutes upon being accepted into the body. To explain how substrates are able to find enzymatic active sites in such an efficient manner, it was hypothesized that enzymes would have higher fractal dimensions in regions adjacent or leading to their active sites. This followed from the conjecture that high-fractal surfaces would have higher interactivity with surrounding solvent. Three PDB files were extracted from the RSCB Protein Data Bank and each was divided into 1,000 cuboid regions. The fractal dimensions of each of these regions were calculated and visualized. The visualizations illustrated that enzymatic regions leading into the active site had high fractal dimensions, while regions adjacent to the active site were observed to not necessarily have high fractal values.
About the author: Min Jae Kim was inspired by the realization of how efficient our enzymes are. Aspirin reduces head pains by inhibiting the enzyme COX-2. However, after consuming merely a few hundred milligrams of aspirin the inhibitor finds it target enzyme in a matter of minutes. Min Jae would also like to acknowledge the mentor and high school chemistry teacher Dr. Mark Zottola for his invaluable advice along the development of this project.
sruthi kurada- A Customized Machine Learning Pipeline to Build State-of-the-Art Audio Classifiers
Audio classifiers have many real-world applications, from informing medical diagnoses to revealing automobile malfunctions. In this study, I have explored strategies to build an accurate classifier to categorize environmental sounds from the UrbanSound8K dataset. Published classifiers on this ten-class dataset only have 50-79% accuracy. Through engineering a machine learning pipeline, I have built a state-of-the-art classifier with a 99% test-set accuracy on this dataset. In order to examine the general applicability of this pipeline to build reliable classifiers on other audio datasets, I have examined its performance in differentiating four unique heart sounds and found it to be equally effective. The final heart sound classifier achieved a 98% test set accuracy.
About the author: Sruthi Kurada is a 9th grader from Littleton, MA. She is a passionate engineer and programmer. Over the last few years, she has learned several programming languages, including Python, Java, Swift, HTML, and CSS. She utilized these skills to lead teams in the creation of several apps which have gained national level acclaim including HiveSwarm, a cloud-based solution which enables beekeepers to take better care of their hives. Over the summer of 2018, she interned at the WPI Data Science Institute and worked on a machine learning project to identify new strategies to handle missing data in multivariate time series to improve predictive outcomes. The paper was accepted to the MIT IEEE Conference, where she presented the research in October. She undertook this audio classification project at home to further her understanding of machine learning. Through the research process, she enjoyed learning the practical aspects of machine learning in addition to the underlying theory.
Mrunali Manjrekar- A Rule-Based Natural Language Processing Pipeline for Anesthesia Classification from Unstructured Operative Notes
Previous studies have shown anesthesia type administered during operations can influence postoperative pain outcomes. However, researchers cannot quickly analyze anesthesia type in large studies from electronic health records because of their unstructured data format. In this study, we show the development, implementation, and evaluation of a natural language processing (NLP) pipeline, a series of Python-programmed rules built to classify different types of anesthesia type based on textual features within the free text of operative notes. The first pipeline attained a precision score of 1 out of 1 and recall score of 0.96 out of 1 on 100 post-operative notes annotated by a clinician. After initial revision and testing on independent data, the second pipeline’s overall precision score of 0.88 and recall score of 0.77 suggests a need for more robust dictionaries to match additional textual features and improved intuitive context extraction to increase accuracy.
About the author: Mrunali Manjrekar is a senior at Leigh High School who found the interface of computer science and biology a mesmerizing combination with great potential for the future of personalized healthcare. After coming across the Boussard Lab in the Stanford School of Medicine’s Center for Biomedical Informatics Research, Mrunali chose to join the lab for the summer as an intern to find a channel for her excitement through a bioinformatics project. Mrunali enjoys applying computer science to other branches of science, exploring STEM with as her school’s Science Olympiad team, and advocating for women in science and technology as a self-proclaimed STEMinist.
Ethan mcfarlin- Ultrasensitive volumetric imaging through optical coherence tomography
This paper was retracted by the author as of May 2020.
Riya patel- Fluorescence Quenching by 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES) Buffer
Quenching in fluorescence spectroscopy is crucial in numerous applications and can reveal important information about biochemical systems. The purpose of this study was to investigate if the 4-(2-hydroxyethyl)-1- piperazineethanesulfonic acid (HEPES) has a quenching effect and draw a correlation between reduction potential and quenching. Although for C343 the quenching effect was negligible, HEPES decreased the fluorescence responses of the BODIPY dyes significantly. A direct correlation between quenching rate and reduction potential was established.
ethan reiter- Stabilization of Amorphous DDT in Polymers to Increase Lethality
Dichloro-diphenyl-trichloroethane (DDT) is a toxic contact insecticide used in disease-stricken regions for vector control, which is the management of disease-transmitting organisms’ populations. This paper investigates the capacity of various polymers to stabilize DDT’s amorphous state, its most lethal form to insects, and thereby increase its insecticidal efficacy. Improved stabilization of DDT’s most lethal form would more effectively neutralize mosquitos, the arguably deadliest disease transmitters, therefore minimizing the DDT usage required for vector control.
About the author: Ethan Reiter is a junior at Livingston High School and a research intern at the Materials Research Science and Engineering Center (MRSEC) under the New York University (NYU) Department of Chemistry. He is most passionate about solid-state chemistry and X-ray crystallography, and he is currently researching the potential of novel nanoformulations of insecticides with the Kahr Lab Group. His research has inspired him to use science to give back to society through environmental sustainability efforts and community outreach as president of his school's Science National Honor Society. Outside of his research, Ethan is also fascinated by philosophy, public policy, and creative writing. He has taken myriad university classes in these fields online, and he has received national recognition for his performances in public forum debate and his critical essays on issues of social science. Ethan is excited to turn his love for scientific discovery into real world improvements, whether they be through chemistry or politics.
nikhiya shamsher- QuitPuff: A Simple, Home-based, Salivary Diagnostic Test to assess Risk of Oral Pre-cancer and Cancer in Chronic Smokers
High mortality rate in oral cancer is mainly due to late diagnosis. Current methods involve complex laboratory procedures and are unavailable in rural areas. In this study, a simple, home-based salivary diagnostic test for smokers is devised for early detection of oral pre-cancer and cancer.
About the author: Nikhiya Shamsher is very passionate about science. She has been promoting STEM education for 4 years. Her non-profit, Yearn to Learn, has so far set up 130 laboratories of Science and Math in 30 Schools for nearly 15,000 underprivileged children. These labs have inspired students as young as 12 to invent low-cost vacuum cleaners (costing a mere $5), blenders, hydraulic lifts, and manual generators. Her oral cancer diagnostic project has won many national and international awards including a Grand Award at Intel ISEF 2019, a grand award at IRIS 2018 and a gold medal at INSEF 2018. Overall, her career goal is to pursue theoretical physics, as she has always been fascinated about the origin of the universe and wants to figure out how it all started.