bluuebunny/crossref_metadata_2025 huggingface dataset:
Zinc-related Treatments Combined with Chloroquine and Gemcitabine for Treating Pancreatic Cancer
Authors: Ma Larissa , Joykutty Leya
Published: September 2023

Pancreatic cancer is one of the deadliest cancers, with a 10% 5-year survival rate. A prominent issue with the treatment mainly used today, gemcitabine, is that it is unable to penetrate the stroma around the pancreatic cancer tumor. The stroma is a dense network of cells that promotes cancer development and metastasis and creates difficulty for chemotherapy treatments to be delivered effectively to the tumor. Targeting the pathways responsible for both the stroma (namely the Hedgehog signaling pathway) and the tumor (the Ras/MAPK pathway) could potentially lead to more effective treatments. The dysregulation of zinc has been implicated in disease progression through these pathways, however its exact effect is unclear. TPEN is a metal ion chelator that is able to induce zinc deficiency. We hypothesized that if various dosages of TPEN and zinc are used in combination with Chloroquine and Gemcitabine, then combinations of medium to high doses of zinc, Chloroquine, and Gemcitabine will be the most effective at reducing cell proliferation. Several treatment combinations were created in a drug matrix and tested using a cell proliferation assay. To mimic the stroma-tumor interaction that would occur in vivo, we took the conditioned medium from pancreatic cancer associated fibroblasts (mCAF) and cultured pancreatic cancer cells (PANC-1). The results showed that while TPEN was able to significantly lower cell proliferation, it was not more effective than the current treatment. However, when combined with Chloroquine and Gemcitabine, zinc and TPEN both significantly lowered cell proliferation compared to Gemcitabine, suggesting a synergistic effect that resulted in a more cytotoxic treatment. Further research and clinical trials on this topic are needed to determine whether this could be a viable treatment for pancreatic cancer. This repurposed treatment could potentially increase survival rates and become a more affordable alternative to novel drug development.
Building a video classifier to improve the accuracy of depth-aware frame interpolation
Authors: Jasper Surya , Tu Carol , Kozerawski Jedrzej
Published: September 2023

With the current growth in video technology, 4K resolution and sixty frames per second are becoming the industry standards for live, pre-recorded, and animated footage. Although many old movies have a lower frame rate because of insufficient technology, the larger issue lies in the processing of videos. As videos are streamed online, the frame rate can be significantly impaired. So, if we can computationally increase the frame rate, we can dramatically reduce the amount of data being sent to the user. With the recent rising popularity, efficiency, and effectiveness of artificial intelligence, deep learning is undoubtedly the most plausible solution to this problem. Multiple projects have used neural networks to interpolate videos and improve their frame rate. However, since different categories of videos, such as two-dimensional and three-dimensional, can have drastically different color schemes and motion paths, training a single model to handle all of them leads to overfitting, which can be seen in current interpolation algorithms that are specialized to interpolate certain categories of videos. To combat this issue, we researched whether it would be possible to find a single method to perform frame interpolation invariant to the type of video inputted. In this process, we found several pre-existing models that performed well with either 2D or 3D footage, but not both; therefore, we hypothesized that building a video classifier to categorize the input video’s dimensionality would thus improve their accuracy. After integrating the classifier with two depth-aware frame interpolation models, we improved the average accuracy to 97.2%.
The relationship between macroinvertebrates, water quality, and the health of Stevens Creek
Authors: Li Ryan , Dudek David
Published: September 2023

Stevens Creek, which flows through Santa Clara County in California, provides a crucial habitat for federally designated threatened steelhead trout, with a portion of the trout’s diet being dependent on the presence and abundance of macroinvertebrates that inhabit the creek. This led to the formation of our research question: how the water chemistry within the creek was associated with the abundance and diversity of macroinvertebrates, and subsequently the creek’s health. We hypothesized that if the conditions within the creek were optimal for macroinvertebrate survival (specifically the pH range of 6.5-8.5), then there would be a higher abundance and diversity of macroinvertebrates found compared to areas of the creek with pHs outside of the aforementioned range. We conducted a qualitative analysis of macroinvertebrates and water quality to obtain a general understanding of the health of Stevens Creek. Macroinvertebrate sampling and water quality testing, including pH measurements, were carried out in two locations within Stevens Creek, with seven trials in each location. The overall total dissolved solids (TDS), as well as abundance and diversity of macroinvertebrates, between the two locations were found to be similar (not statistically significant), with pollution intolerant macroinvertebrates (Orders Ephemeroptera and Plecoptera) found within the 14 total trials, even though the pH was in the upper limit (8.4). These observations indicate that the portion of Stevens Creek sampled is likely to be healthy and relatively free from nonpoint source (NPS) pollution from the surrounding suburban area, boding well for the steelhead trout residing within it.
Effects of vascular normalizing agents on immune marker expression in T cells, dendritic cells, and melanoma cells
Authors: Yaskolko Maxim , Filderman Jessica
Published: September 2023

Tertiary lymphoid structures (TLS) are lymph node-like structures that form at sites of inflammation, and their presence in cancer patients is predictive of a better clinical outcome. One significant obstacle to TLS formation is reduced immune cell infiltration into the tumor microenvironment (TME), resulting from aberrant vasculature within the TME. Recent studies have shown that low doses of vasculature normalizing (VN) agents may override this defect, leading to improved tissue perfusion and increased immune cell entry into the TME. While the effect of VN agents on vascular endothelial cells has been well documented, their effects on immune cell and tumor cell phenotype remain understudied. We hypothesized that treating immune cells with VN agents would induce a pro-inflammatory phenotype in T cells and dendritic cells (DCs), while treating tumor cells would reduce their immunosuppressive phenotype and promote production of chemokines that recruit immune cells and foster TLS formation. To test this, a mouse melanoma cell line, primary murine T cells, and DCs were treated overnight with VN agents. The next day, treated and control cells were harvested for analyses to measure transcript levels of target genes as well as levels of surface markers. Overall, VN agents were observed to have differential but predominantly immune-supportive effects on immune and tumor cell phenotypes. These findings will guide future experiments which may result in an effective clinical treatment.
Can the Growth Mindset Encourage Girls to Pursue “Male” Careers?
Authors: Lateef Rania , Peterman Debra
Published: September 2023

Despite major advances in gender equality, men still far outnumber women in science, technology, engineering and math (STEM) professions. The purpose of this project was to determine whether mindset could affect a student’s future career choices and whether this effect differed based on gender. In a growth mindset, people believe that their most basic abilities can be developed through dedication and hard work, while a fixed mindset assumes that our character, intelligence, and creative ability are static givens. We hypothesized that girls with a growth mindset would be more likely to consider pursuing careers typically chosen by males, in the future, compared to girls with a fixed mindset. Using the Dweck mindset quiz, each subject was assigned either a growth or fixed mindset. Subjects were then shown gendered, workplace pictures and asked to identify careers they would like to pursue Males picked more potential careers, in general, compared to females (7 vs. 5, out of 10 options). When looking within the gender groups, 86% of females who had a growth mindset were likely to consider a “male” career, whereas only 16% of females with fixed mindset would likely to consider a “male” career. Especially for girls, cultivating a growth mindset may be a great strategy to address the problem of fewer girls picking STEM careers. The more we believe we can, the more we can accomplish!
Genomic Signature Analysis for the Strategic Bioremediation of Polycyclic Aromatic Hydrocarbons in Mangrove Ecosystems in the Gulf of Tonkin
Authors: Dao Nam H , Le Quan M , Dao Thang X
Published: September 2023

Current oil spill cleanup methods can be inefficient, costly, and have many more downsides. In an effort to create an efficient, cost-effective, and environmentally-friendly solution to cleaning oil spills, there has been a flurry of advancements in microbiological vectors. These plasmids confer oil-degrading genes that can be implemented into the native microbial population. For this strategy to work, it is critical that an appropriate naturally-found plasmid be picked as a base to ensure long-term plasmid survival and activation of its genes. To help realize this goal, this study relies on emerging computational technologies to measure genetic similarity between the host chromosome and the potential plasmid vector, utilizing an algorithm for 3-mer genomic signature analysis to determine the best naturally-found plasmids for later use as vectors, as well as detect local species or genera that are most compatible with these plasmids. Our hypothesis is that the resulting plasmid-species combinations will reflect existing literature regarding historical host-species interactions, further supporting genomic signature analysis as a tool to find historical plasmid-host interactions and thus predict plasmid compatibility. The plasmids we identify can then be chosen as a base vector to be equipped with hydrocarbon-degrading genes in future studies. Based on our results, for mangrove forests located in the Gulf of Tonkin, the combinations IncP-9 (Pseudomonas lurida, Pseudomonas pelagia, Pseudomonas alkylphenolica, Pseudomonas antarctica), IncA/C (Marinobacter salinus), Ri/Ti (Erythrobacter atlanticus) or Ri/Ti (Pseudorhodoplanes sinuspersici) should be the targets of future oil-degrading bioremediation strategies.
Machine learning for the diagnosis of malaria: a pilot study of transfer learning techniques
Authors: Stolker Jacob , Assaf Rida
Published: September 2023

Despite being treatable and preventable, malaria continues to affect millions of people worldwide. A major hindrance to the disease’s eradication is difficulty with testing, and attempts have already been made to shift towards more automated testing methods rather than older testing technologies such as light microscopy and rapid diagnostic tests. Machine learning models have shown promise in diagnosing malaria, but prior machine learning algorithms have been contingent upon the availability of clean and relevant data. Furthermore, there are multiple species of malaria that may require different treatments, often resulting in fewer comparative images of individual malarial subtypes on blood slides of a given patient population. In this pilot study, we tested a machine learning technique called transfer learning to reduce the error caused by lesser amounts of available data. By training the algorithm on a known (but not necessarily related) dataset and then re-training on malaria datasets, we were able to significantly increase diagnostic accuracy. Specifically, using transfer learning to prepare the algorithm on a completely unrelated database before applying to malaria slide interpretation, our diagnostic accuracy improved from 65.5% to 80.7% in a small dataset of malaria blood slides, and from 95.5% to 98.0% in a much larger malarial dataset. Moving forward, these types of experiments will help develop a smartphone application to increase the opportunity to diagnose malaria in places where resources are too limited to permit standard diagnostic techniques.
Determining the best convolutional neural network for identifying tuberculosis and pneumonia in chest x-rays
Authors: Kudum Sunny , Shah Dristi , Vaish Ishita , Tirumala Padmavati
Published: September 2023

Tuberculosis (TB) and pneumonia are commonly misdiagnosed respiratory conditions associated with high rates of mortality. Chest X-rays (CXRs) are an inexpensive method to identify respiratory conditions. Thus, a model used to distinguish between CXRs depicting lungs classified as normal, pneumonia, and tuberculosis would lead to accurate diagnoses of these respiratory conditions. This need is fulfilled by the recent explosion in deep learning, and new models with robust performance are constantly developed. However, these models have varying strengths and weaknesses which allow them to excel at certain tasks and struggle with others. Therefore, testing these models is essential to find the most suited model. In this study, we trained and applied six convolutional neural networks, the InceptionV3, ResNet50, ResNet152, InceptionResNetV2, DenseNet121, and AlexNet, to the diagnosis of TB and pneumonia. We hypothesized that InceptionResNetV2 would perform best for this task due to its combination of inception blocks that reduce the dimensionality of the CXR images and residual blocks that allow for deeper models by eliminating vanishing gradient. After training on a combination of five datasets from the Guangzhou Women and Children’s Medical Center, Shenzhen, Montgomery County, Belarus, and ChestX-ray8, it was found that various models excelled in predicting different diseases shown in the datasets. The results displayed that there was no clear superior model but instead significant superiority within certain diseases.
The effects of food type on mediator-less microbial fuel cell electricity output
Authors: Hung Aaron , Lin Jonathan , Ponnampalam Dino
Published: September 2023

Clean power production is a heavily investigated topic in science today. The journey to find a clean, sustainable power source capable of producing enough energy to power an entire city is still in progress. Among the developments of different methods, the microbial fuel cell (MFC) is a promising idea, harnessing microbes to generate power through consumption of organic substances. In this investigation, we compared the different power outputs from using various foods as fuel sources, including sugar, cheese, and grapes. We hypothesized that different types of food, when placed inside the MFC, will produce different amounts of power. From the experiment, we observed a higher energy output for the sugar solution which suggests the potential energy output generated by the MFC of Shewanella putrefaciens is indeed affected by the fuel source used. From this study we have shown that the type of fuel used to power an MFC plays an instrumental role in the efficiency of the MFC and should be of the utmost importance when developing MFCs in the future.
Impact of Population Density and Elevation on Tuberculosis Spread and Transmission in Maharashtra, India
Authors: Rao Melosa , Johnson Ann
Published: September 2023

The causative agent of Tuberculosis (TB) in humans is Mycobacterium tuberculosis. When lung TB patients cough, sneeze, or spit, TB spreads through the air. India accounts for over 2.4 million recorded cases of TB, about 26% of the world’s TB cases. This research ascertained the bearing of both the population density and the average elevation above mean sea level (MSL) on the number of cases of TB recorded by the districts in Maharashtra, India. Using multiple regression analysis, we demonstrated that about 75% of the variance in the reported cases of TB per thousand people can be attributed to the average elevation above MSL and the population density. We found a strong positive correlation between the number of TB cases per thousand people and the population density and a strong negative correlation between the number of TB cases per thousand people and the average elevation above MSL.
Homology modeling of clinically-relevant rilpivirine-resistant HIV-RT variants identifies novel rilpivirine analogs with retained binding affinity against NNRTI-resistant HIV mutations
Authors: Luk Charissa , Wu Jeslyn , Njoo Edward
Published: September 2023

Human immunodeficiency virus (HIV), which affects tens of millions of individuals worldwide, can lead to acquired immunodeficiency syndrome (AIDS). Though there is currently no cure for HIV, the development of small molecule antiretroviral agents has greatly improved the prognosis of infected individuals, especially in developed countries. In particular, compounds such as rilpivirine have been developed as non-nucleoside reverse transcriptase inhibitors (NNRTIs), which allosterically target the reverse transcriptase enzyme in the retrovirus. However, mutations to the reverse transcriptase enzyme threaten to undermine the efficacy of this class of antivirals. Recent advances in computational biophysical modeling enable the structural analyses of such variants without the complications of obtaining crystal structures. Here, we employ homology modeling and molecular docking towards the identification of novel rilpivirine analogs that retain high binding affinity to clinically relevant rilpivirine-resistant mutations of the HIV reverse transcriptase enzyme.
The role of xpa-1 and him-1 in UV protection of Caenorhabditis elegans
Authors: Tung Kelly , Fallon Renee
Published: September 2023

Caenorhabditis elegans xpa-1 and him-1 are orthologs of human XPA (xeroderma pigmentosum group A) and human SMC1A (Structural maintenance of chromosomes 1A), respectively. Mutations in the XPA are correlated with Xeroderma pigmentosum, a condition that induces hypersensitivity to ultraviolet (UV) radiation. Alternatively, SMC1A mutations may lead to Cornelia de Lange Syndrome, a multi-organ disorder that makes patients more sensitive to UVinduced DNA damage. Both C. elegans genes have been found to be involved in protection against UV radiation, but their combined effects have not been tested when they are both knocked down. We hypothesized that because these genes are involved in separate pathways, the simultaneous knockdown of both of these genes using RNA interference (RNAi) in C. elegans will cause them to become more sensitive to UV radiation than either of them knocked down individually. UV protection was measured via the percent survival of C. elegans post 365 nm and 5.4x10-19 joules of UV radiation. The double xpa-1/him-1 RNAi knockdown showed a significantly reduced percent survival after 15 and 30 minutes of UV radiation relative to wild-type and xpa-1 and him-1 single knockdowns. These measurements were consistent with our hypothesis and demonstrated that xpa-1 and him-1 genes play distinct roles in resistance against UV stress in C. elegans. This result raises the possibility that the xpa-1/him-1 double knockdown could be useful as an animal model for studying the human disease Xeroderma pigmentosum and Cornelia de Lange Syndrome.
The influence of implicit social pressure on prosocial behavior of adolescents
Authors: Carroll Kieran , Mullers Sacha , Tulleners Elsefien , van der Woude Amber , W te Brinke Lysanne
Published: September 2023

Adolescents are easily influenced by their peers, resulting in a phenomenon known as social pressure, which can have both positive and negative effects on the teens. This study addresses the influence of implicit social pressure on prosocial behavior (e.g., voluntary acts that benefit someone else) in adolescents aged 12–19. Specifically, this experiment measured the influence of prosocial, neutral, and antisocial pressure on sharing. This study consisted of 2 parts, part 1 (N = 101) and part 2 (N = 16). In a game similar to a dictator game, participants divided money between themselves and four teammates with whom they did a school project. Participants received manipulated social pressure by showing an example of how the money can be divided. We hypothesized that participants would share more after receiving implicit prosocial pressure, and that girls would share more than boys. Our results indicate that there was no difference in the way participants divided the money in the prosocial, neutral, and antisocial condition. In addition, there was also no statistically significant difference between boys and girls. These findings may implicate that implicit social pressure has no influence on adolescents’ behavior. However, methodological and contextual factors like the COVID-19 pandemic need to be considered.
A study of South Korean international school students: Impact of COVID-19 on anxiety and learning habits
Authors: Kim Grace Jisoo , Kim Jinsup
Published: September 2023

The COVID-19 pandemic has impacted students worldwide on their social, mental, and physical health, as well as their academics. Many studies have shown how COVID-19 has affected different groups of students. The purpose of our research was to study the effect of COVID-19 on international high school students in South Korea. South Korea was lauded for its response to the COVID-19 outbreak, so we further investigated how the online school environment has affected this demographic in particular. We used a survey-based study to gather data on academics, mental, social, and physical health and well-being from 100 high school students attending numerous international schools in Korea. We split up our survey participants by gender and socioeconomic status and compared the averages of their answers using t-tests. Our study confirmed that female students study more than male students and feel they are doing better academically. Furthermore, more of the female students perceived COVID-19 to be dangerous compared to their male counterparts. Seventy-five percent of students also saw a change in their grades based on how their study habits had changed during online school. In addition, most students felt more depressed and anxious during the pandemic, feeling the "COVID blues." The findings from our study can be used to further improve school systems and student management, especially during a time of crisis in the future.
DNA-SEnet: A convolutional neural network for classifying DNA-asthma associations
Authors: Bubby Siva , Chrisman Brianna
Published: September 2023

Asthma is a complex disease with a growing global prevalence whose genetic causes remain largely unexplored. The rise of next-generation sequencing has significantly augmented genetic studies in identifying asthma-associated mutations, the most common of which are single nucleotide polymorphisms (SNPs). Population-based and biochemical analyses have been used to identify novel disease-associated loci and their biological consequences; however, SNPs alone do not explain the mechanisms of asthma nor do they offer a context to evaluate candidate SNP-asthma associations. To this end, we developed a model named DNA Sequence Embedding Network (DNA-SEnet) to classify DNA-asthma associations using their genomic patterns. The hypotheses of this study are that DNA-asthma associations can be discerned through high-dimensional vector representations of DNA sequences around SNPs, that these features can be applied to determine novel SNP-asthma associations, and that this model can be generalized to predict SNP-disease associations for other complex traits. On average, this model achieved an Area Under the Curve (AUC) equaling 0.81 when learning and classifying DNA-asthma associations. Additionally, DNA-SEnet corroborated previous studies’ SNP-asthma connections and proposed two novel asthma-linked loci based on their surrounding semantic properties. Moreover, DNA-SEnet effectively learned DNA-disease associations when applied to sequence data regarding coronary heart disease, type 2 diabetes mellitus, and rheumatoid arthritis. Therefore, this model can be used to identify novel disease-associated sequences across various disease types.
Idotea balthica comparison: Anatomy, locomotion, and seaweed preference of Massachusetts isopods
Authors: Yee Esther , Elliston Judith
Published: September 2023

We investigated a select population of Massachusetts marine isopods to determine if they are of the species Idotea balthica by comparing their features to those of ,em>I. balthica living in the Baltic Sea. We hypothesized that the Massachusetts isopods belonged to the species, despite the large geographical distance between the two populations. For this study, a group of 12-18 isopods were captured in Plymouth, Massachusetts in October 2020 and observed in captivity. After examination, they were then compared in three areas (morphology, movement, and seaweed preference) using previous studies on the Baltic Sea isopods as references for comparison. Results indicated that the Massachusetts isopods resembled the Baltic Sea isopods in most areas, with the few key exceptions of smaller female length, slightly darker coloration of males, and greater seaweed preference for Chondrus crispus with no inclination toward Pilayella littoralis. This knowledge could be useful for future examination of the two groups, such as when measuring their responses to climate change, especially given the physical and ecological differences between the Massachusetts Bay and Baltic Sea marine environments.
A study on the stretching behavior of rubber bands
Authors: Davuluri Sravya , Ravipati Aruna
Published: September 2023

Rubber bands are simple and familiar household items whose properties are worth researching to determine their utility and value. They are used ubiquitously, as toys, binders for objects and as equipment in the fitness industry, which necessitates study of their properties and manufacturing and labelling them based on standard extensibility and strength, specific to utility. Our study aimed to investigate the applicability of Hooke’s law to rubber bands. We hypothesized that rubber bands are ideal elastic materials, exhibiting stretch in direct proportion to loads and that bands of any length respond equally to pulling forces. We exposed a few rubber bands to a step-wise longitudinal loading process, and the stretch response after each step of the load was measured. While the initial loading steps removed only the slack of bands, a marked stretch behavior was observed soon. A linear relationship between stretch and applied force, noted in a few intermediate steps, was lost eventually. When we compared the bands of different lengths, it was obvious that the shorter bands stretched less than the longer ones for similar loading. Finally, we rejected the hypothesis since the findings supported that rubber bands do not follow Hooke's law and that their initial lengths affect the stretch response for loading. This study can be used in further research of the properties and molecular structure of rubber bands and to compare them with some visco-elastic structures.
Protein concentrations in cows’ milk during the four stages of lactation
Authors: Wilson Madeleine , Vaughn Robin
Published: September 2023

Proteins play an essential role in the growth and development of young calves, and changes in the nutritional needs of these calves may be responsible for changes in milk protein concentrations across the four stages of bovine lactation. The purpose of this research was to analyze the fluctuations in the concentrations of casein and whey, which are the two primary sources of protein in cows’ milk. Milk proteins provide essential nourishment for young calves, so we hypothesized that the total protein concentration of the milk would decline from the first stage of lactation to the fourth stage of lactation. Absorption spectroscopy was used to determine the concentration of the proteins in the milk, and five trials were conducted for each stage of lactation. A spectrometer was used to collect absorbance data for the whole milk, casein, and whey samples, and a standard curve was used to convert those absorbance readings into concentration values. The hypothesis for this research was supported in that the total protein concentration of the milk declined from the first stage of lactation to the fourth stage of lactation. More specifically, the concentration of casein proteins decreased as the concentration of whey proteins increased. These trends are important because they provide a foundation for future research to determine whether the observed fluctuations in the protein concentrations are significant enough to pose implications for individuals suffering from lactose intolerance.
Effects of Temperature on Hand Sanitizer Efficiency
Authors: Molom-Ochir Sanchir Sam , Davis Kimberly M
Published: September 2023

In times of pandemic, hand sanitizers are one of the things that slow the spread of contagious disease. As they are readily available, they are stored at different temperatures because they might be used in different environments. It is important to understand what effects storage temperature has on hand sanitizer effectiveness in order to maximize its effectiveness. This research addresses the effect of varying temperatures on hand sanitizer effectiveness. In four separate trials, we applied hand sanitizer before and after touching a cell phone to expose our hands to microbes, then applied our hands to pre-poured sterile LB-agar plates. After 75 hours, we compared the number of surviving bacteria from before and after plates and generated a killing effectiveness value. This study was successful in finding the most effective temperature for 70% ethyl-alcohol-based sanitizers. Our results show that hand sanitizers are the least effective at temperatures above 107.27 °F and the most effective at 96.17 °F. Knowing the temperature range at which sanitizers are the most effective will help us better store the sanitizers to achieve their maximum effectiveness.
Racemic serine is less soluble than pure enantiomers due to stronger intermolecular hydrogen bonds
Authors: Ranka Samvi , Deamer David
Published: September 2023

The chemical and physical properties of amino acids determine the properties of the proteins they compose. Two of these properties include solubility and chirality. It is known that pure D- and L-serine are approximately eight times more soluble than DL- serine, their racemic mixture, but the reason is not clear. Our hypothesis is that the difference is related to the types of H-bonds that stabilize crystals of the pure serine enantiomers compared to their DL-racemic mixture. We tested the hypothesis by examining the structures of microscopic crystals and observed that the D- and L-serine formed platelets while the DL- serine formed prisms. We also discovered that when saturated solutions of D- and L-serine are mixed, DL- serine crystals form within seconds, accompanied by release of heat energy corresponding to -2.7 kcal/mol. This exothermic heat can be accounted for if a new type of hydrogen bond can form between the D- and L-serine enantiomers during crystallization that is absent in crystals of pure enantiomers. We confirmed this conclusion by examining crystal structures previously reported in X-ray diffraction studies of serine crystals. The significance of our observation is that release of heat energy during crystallization of a mixture of pure D and L enantiomers has not been previously reported and may be unique to the amino acid serine.
Taft linear free-energy relationships in the biocatalytic hydrolysis of sterically hindered nitrophenyl ester substrates
Authors: Kocalar Selin , Njoo Edward
Published: September 2023

Linear free-energy relationships (LFERs) have been commonly used to uncover reaction mechanisms in organic chemistry by correlating trends in reactivity to reactant properties. However, the applications of LFERs have largely been limited to traditional organic synthesis and have much less frequently been applied toward enzyme-catalyzed reactions. In this study, we used the Taft LFER, which correlates reaction rates with steric properties of reactants, to study kinetic trends in the enzymatic hydrolysis of sterically hindered substrates. We synthesized 4-nitrophenyl ester compounds with substituents of varying degrees of steric hindrance, and then subjected these compounds to hydrolysis by the enzymes lipase, trypsin, and nattokinase. Kinetic data was obtained by using a spectrophotometer to monitor the formation of 4-nitrophenol, a bright yellow product of the ester hydrolysis with an optical readout at 413 nm. Contrary to initial hypotheses, Taft plots did not exhibit linear relationships and further analysis yielded mechanistic insight into the nature of the Taft steric parameter, the relative sensitivity of each enzyme to steric effects, and potential enzyme-substrate binding interactions. This analysis was paralleled with computational calculations to determine local charge density of the reaction center, which supported that the unexpected trends were largely a function of the aforementioned factors rather than electronic effects. Ultimately, we demonstrate the unconventional application of the Taft LFER toward biocatalytic transformations and open avenues toward the broader use of biocatalysts in synthetic organic chemistry.
Impact of salinity and phosphorus on growth of Phaseolus Vulgaris inoculated with Arbuscular Mycorrhizal Fungi
Authors: Matanachai Karit , Rinehart Jennifer
Published: September 2023

As the supply of rock phosphate decreases, it is essential that the agriculture industry reduces wasteful phosphorus (P) fertilizer application by improving crop acquisition of P. Arbuscular mycorrhizal fungi (AMF), a fungus that forms a beneficial relationship with many crops, is one potential solution to this problem. Numerous studies show that crops inoculated with AMF have many benefits such as increased P uptake, resulting in higher yield and resistance to abiotic stresses. The objective of this study was to understand the impact of mycorrhizal symbiosis on bean growth under varying soil conditions of P and salinity. We tested several P concentrations and salinity levels and found that beans planted in soil conditions containing the highest levels of P and salinity exhibited significantly lower root-to-shoot ratios than any other trials while still maintaining similar biomass weight. This suggests that AMF hyphae increased the affinity of the plant for absorbing nutrients, allowing it to focus on shoot growth instead of root growth. We also observed that adding more P fertilizer to the AMF-inoculated bean plants both under salt and non-salt conditions led to diminishing returns in terms of plant height and dry weight. Hence, adding more P fertilizer to compensate for high soil salinity in AMF-inoculated soil could be inefficient and lead to fertilizer run-off that would negatively impact surrounding ecosystems.
Post-Traumatic Stress Disorder (PTSD) biomarker identification using a deep learning model
Authors: Banerjee Sohini , Istanbouli Mazen , Daigle Bernie J
Published: September 2023

Post-traumatic stress disorder (PTSD) is a neuropsychological disorder in which individuals struggle to recover from a traumatizing event. It affects a significant population, including COVID-19 patients, frontline health workers, and war veterans. Given biases associated with self-assessment and diagnosis of PTSD, researchers are actively searching for unbiased biological markers (biomarkers) for predicting PTSD status. The Systems Biology of PTSD Consortium has collected candidate biomarkers for PTSD using molecular and clinical measurements of male war veterans between the ages of 20 and 60. PTSD-positive and negative subjects were separated based on the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) Clinician Administered PTSD Scale (CAPS) scores, derived from structured interviews to measure an individual’s abundance of symptoms, such as re-experiencing, flashbacks, and hyperarousal. CAPS scores higher than 40 were considered PTSD-positive and below 20 were considered negative. We created artificial neural network models to classify PTSD-positive and negative individuals based on metabolomics, micro-RNA (miRNA), protein expression, endocrine markers, and DNA methylation datasets. Model training involved 64 iterations of a Bayesian Hyperparameter Optimization algorithm with 5-fold cross-validation. Each model was calibrated based on cross-validation performance and variance across iterations and then fit to the entire respective dataset (76 PTSD-positive, 76 PTSD-negative). We applied the trained models to an independent validation cohort to assess accuracy on unseen datasets. The top performing datasets from the validation cohort based on classification accuracy were metabolomics (65.2%) and protein expression (61.8%). We anticipate the candidate biomarkers identified in this and future studies will assist with the diagnosis of PTSD.
The effects of the cancer metastasis promoting gene CD151 in E. coli
Authors: Burgess Cara , Yuwanita Inez , Pennycook Louise , Ismail Youssef
Published: September 2023

The most feared and most deadly stage of cancer is stage 4, or metastasis. Metastasis is the ability of cancer cells to spread throughout the body. CD151 is a known metastasis-promoting gene in humans. However, the independent effects of CD151 in the process of metastasis are not known. We wanted to isolate CD151 to discover what its role in metastasis would be on its own and uninfluenced by potential interactions with other components and pathways in human cells. To determine the independent effects of CD151 on cellular motility and adhesion, we expressed CD151 in bacteria and then performed several assays. Our results showed that CD151 significantly increased the adhesion of the cells and decreased their motility. From this, we conjecture that CD151 is upregulated in cancer cells for the last step of metastasis, and it increases the chances of success of metastasis by aiding in implantation of the cancer cells. Targeting CD151 in chemotherapeutic modalities could therefore potentially slow or prevent metastasis.
Myrtaceaes as antimicrobial agents against Staphylococcus aureus and Pseudomonas aeruginosa
Authors: Kottasha Vidhanelage Gihansa , Mitchell Melissa
Published: September 2023

Anti-microbial resistance causes more than 700,000 deaths annually, a figure that is predicted to grow to 10 million by 2050 and is one of the leading contributors to the Global Burden of Disease. The six leading contributors to the surge of antimicrobial resistance are named the ESKAPE pathogens. Staphylococcus aureus and Pseudomonas aeruginosa are two of these bacteria. More than 80% of the active ingredients in antimicrobial drugs are based on natural products. Botanical species are the largest contributors of these active ingredients, yet they remain largely unstudied. Our research aimed to explore the antimicrobial properties of the Myrtaceae family. We collected, dried, and extracted the flowers of six native Australian Myrtaceae species. We tested these crude extracts at ten different concentrations on S. aureus and P. aeruginosa, to determine percentage inhibition, which was used as an indicator of the efficiency of the crude extract in causing bacterial death. The minimum inhibitory concentration (MIC) determines the viability of an extract for further drug development. For S. aureus, all six tested Myrtaceae species exceeded MIC80 (concentration needed for 80% inhibition), with Corymbia ficifolia being the most potent, exceeding MIC80 at 0.04 mg/mL. For P. aeruginosa four out of the six tested Myrtaceae species reached MIC80. Xanthostemon chrysanthus was most effective against P. aeruginosa with a MIC80 of 5.00 mg/mL. Myrtaceae species were shown to be highly effective against S. aureus and even P. aeruginosa, suggesting that further investigation into Myrtaceae species, could be revolutionary in drug development for newer, more effective antimicrobial drugs.
Does technology help or hurt learning? Evidence from middle school and high school students
Authors: Lu Marco , Mo Davis , Du Fei
Published: September 2023

In this study, we examined the effect of technology use on middle and high school students’ learning effectiveness. Based on prior literature, we hypothesized that device use at school would increase students’ learning effectiveness (H1), but that device use at home would decrease learning effectiveness (H2). To test our hypotheses, we conducted a survey of middle and high school students across different states in the United States. We measured the device use and learning effectiveness by asking participants to report their actual device use time both at school and at home and to rate the extent to which their learning met their expectations on a 7-point Likert-type scale. We found partial support for H1. While we did not find an overall positive relation between technology use at school and learning effectiveness, we found such effects among male students and middle school students. Consistent with H2, we found strong support for a negative effect of technology use at home on learning effectiveness. Further, this negative effect was exacerbated for female students and middle school students. Taken together, these results provide evidence suggesting that the effect of technology use on learning depends on where the device is used, the gender of students, and the grade in which students are in. Furthermore, we conducted additional analyses to shed light on how technology use benefits learning. Our results suggest that technology use improves learning mainly by facilitating collaboration, enabling more personalized learning, improving organization, allowing teachers to provide more timely feedback, and making learning more effective.
Health services in Iraq - A cross-sectional survey of adolescents in Basra
Authors: Al Saeedi Ahmed M , Al Saeedi Sara M , Mahmoud Janaen Y
Published: September 2023

Adolescence is a transition phase from a child into an adult. Adolescents face many problems, including psychological, health, and economic problems. In some developing countries such as Iraq, adolescents face several barriers to obtaining the health services they need. We performed a cross-sectional survey of adolescents in Basra, the second-largest city in Iraq, from November 2020 to March 2021 to collect data from respondents to obtain information about the types of adolescent problems, the individuals and institutions adolescents turn to, and the role of public health centers in dealing with their problems. We randomly selected study participants from high school students and non-students between the ages of 12 and 18 years of both sexes. The sample size was 100 people, who were divided according to gender and educational level into 4 groups. We found through the study that psychological problems represent the largest proportion of health problems, and most adolescents turn to their parents to discuss their problems. Our study revealed that the number of working non-students is more than double the number of working students in this survey, and poverty was the main reason for work. Our results also showed that a quarter of the participants were below average, most of them non-students, and 28% of adolescents were dissatisfied with the efficiency and adequacy of the health services provided (half of them are non-students). Our study indicated that there is an urgent need to pay attention to public health centers and provide health and psychological support to adolescents.
A computational quantum chemical study of fluorinated Allopurinol
Authors: Khan MD Mostakim , Tuly Rafia Akter
Published: September 2023

Allopurinol is a two-ring heterocyclic drug. Allopurinol has several conveniences for medicinal chemistry, including easy preparation methods and low toxicity, which make it a preferable choice for researchers and scientists. However, it has some limitations such as a short half-life and low stability. Fluorination is one of the most effective ways to enhance a number of chemical properties and applications of a compound. The small and highly electronegative features of fluorine have thus made it a profitable choice to optimize a compound. The inclusion of fluorine atoms can improve the effectiveness and reduce the limitations of allopurinol was the presumption of this study. From that context, this research deals with an examination of the effect of fluorine atoms on allopurinol. We investigated several chemical properties of allopurinol with quantum chemistry calculations using Hartree-Fock theory. We evaluated the molecular geometry, Mulliken charge analysis, and frontier molecular orbitals calculations. We conducted a comparison of our calculated properties to determine the advantages and disadvantages of allopurinol and two simulated, fluorinated, hybrid compounds. We found higher chemical stability in the hybrid compounds. The first hybrid compound was more organic agent-friendly, whereas the second one was more ionic and polar agent-friendly. The fluorinated compounds showed their potential to prevent metabolic attacks and improve reactivity with different chemical agents.
Impacts of COVID-19 on daily water use: Have people started using more water?
Authors: Araujo dos Santos Silva Jenifer , Soares Marilia
Published: September 2023

In São Paulo, as well as every other city around the world, water is an invaluable natural resource. More than a necessary input for production and a strategic resource for economic development, it is vital for the maintenance of biological, geological, and chemical cycles, which keep ecosystems in balance. There is a shortage of water in the world, and this situation is aggravated by social inequality, the lack of sustainable management, and use of natural resources. The purpose of this research was to discover if, during the quarantine of COVID-19, there was an increase in the daily use of water in the city of São Paulo and, if this happened, to understand why and to investigate its impact on reservoirs. We hypothesized that, during the COVID-19 quarantine, water consumption increased exponentially due to virus precautions. Based on our hypothesis, we carried out a survey where we interviewed 100 people in the São Paulo capital. Most reported that water consumption in their homes increased, according to our research; for example, we discovered that individuals who took an average of five-minute showers increased their time to sixteen-minute showers. This phenomena worsened the water shortage situation in many reservoirs in São Paulo. The findings from our study can be used to further help solve water waste problems.