bluuebunny/crossref_metadata_2025 huggingface dataset:
Distribution of prophages in the Streptococcus bacteria genus and their role in increasing host pathogenicity
Authors: Ge Carol , Mathur Vinayak
Published: September 2023

Bacteriophages are a category of viruses that only infect bacteria. Virulent phages cause the cell to produce new phages and lyse, while temperate phages remain in a latent state following phage lysogeny and integration of genetic material into the host genome as prophages. This integration enhances the genetic diversity of the host species, and the new genetic material may offer advantageous traits to aid the host’s survival and adaptation to new environments. Streptococcus bacteria are pathogens that infect both humans and animals, causing invasive infections and a diverse set of diseases. We hypothesized that strains of Streptococcus that have prophages present in their genome are linked to increased pathogenicity or antibiotic resistance. We used PhageWeb to identify prophages found within the 819 strains of Streptococcus genus from GenBank and the distribution of prophages across different species within the genus. With the Progressive Mauve software, we compared the sequences of identified prophages to determine similarities and relationships between the different prophages. Ultimately, based on information from gene ontology databases, we found that different prophages were associated with various virulence factors, adherence factors, and antibiotic resistance genes in their respective bacteria. Bacterial strains containing these prophages may have increased pathogenicity and the embedded genes could have a role in bacterial survivability in different environments. This genetic variation and these prophage characteristics shed light on the evolutionary dynamics of these bacteria species and can be applied to phage therapy.
Autologous transplantation of fresh ovarian tissue in the ICR mice model
Authors: Wang Yuanxi , Zhao Zihan , Xia Guoliang
Published: September 2023

SUMMARY

During the past 20 years, autologous transplantation of either frozen ovarian tissue for cancer patients or ovarian tissue pretreated with curative medications for premature ovarian insufficiency (POI) patients have been achieved worldwide. POI is characterized by amenorrhea before 40 years of age. As a result, juvenile cancer patients and POI patients have increased chances to give healthy birth based on this achievement. It also indicates that mastering the skills of ovarian auto-transplantation is required for researchers and doctors. In this study, we performed orthotopic auto-transplantation of fresh ovarian tissues by transplanting unilateral half ovarian tissue to the contralateral ovary in the ICR (Institute of Cancer Research) strain of outbred, heterogeneous mice to determine if the transplanted tissue could be functional. The transplantation surgery entailed taking partial ovarian tissue from the unilateral ovary of the adult ICR female mouse and then transplanting into the ovarian sac of the contralateral ovary, in which part of the ovarian tissue had been removed in advance. One week after surgery, we found that the freshly transplanted mouse ovarian tissue survived and functional, as histochemical and immunofluorescence assays have shown that not only both follicles at different developing stages and corpus luteum are available, but the morphology of them are properly maintained within the transplanted tissue. This study approved that for those who are interested in ovarian transplantation study, applying mouse model to practice ovarian tissue auto-transplantation is reliable and easy handled.
siRNA-dependent KCNMB2 silencing inhibits lung cancer cell proliferation and promotes cell death
Authors: Jeong Eunice , Rin Lee Woo
Published: September 2023

Non-small cell lung cancer (NSCLC) is one of the most common causes of premature death worldwide. Since NSCLC patients have a high rate of mutation in EGFR and KRAS, a better understanding of the genetic association underlying NSCLC progression is needed. Recent technological advances in gene expression profiling in cancer cells have provided the expression data of thousands of genes. Therefore, we screened hundreds of genes through the Kaplan Meier plotter database to find a novel gene expression pattern associated with lung cancer patient survival. First, we analyzed 3,019 lung cancer patients’ data and performed a Kaplan-Meier survival analysis. We found that KCNMB2 upregulation was significantly correlated with poor prognosis in lung cancer patients. Therefore, we hypothesized that KCNMB2 downregulation would inhibit lung cancer cell proliferation. Next, we found that KCNMB2 silencing by small interfering RNA (siRNA) inhibits cell proliferation and promotes apoptosis, suggesting that targeting KCNMB2 may be an effective therapeutic strategy for NSCLC patients.
Using machine learning to develop a global coral bleaching predictor
Authors: Madireddy Indeever , Bosch Rachel , McCalla Serena
Published: September 2023

Coral bleaching is a fatal process that reduces coral diversity, leads to habitat loss for marine organisms, and is a symptom of climate change. This process occurs when corals expel their symbiotic dinoflagellates, algae that photosynthesize within coral tissue providing corals with glucose. Restoration efforts have attempted to repair damaged reefs; however, there are over 360,000 square miles of coral reefs worldwide, making it challenging to target conservation efforts. Thus, predicting the likelihood of bleaching in a certain region would make it easier to allocate resources for conservation efforts. We developed a machine learning model to predict global locations at risk for coral bleaching. Data obtained from the Biological and Chemical Oceanography Data Management Office consisted of various coral bleaching events and the parameters under which the bleaching occurred. Sea surface temperature, sea surface temperature anomalies, longitude, latitude, and coral depth below the surface were the features found to be most correlated to coral bleaching. Thirty-nine machine learning models were tested to determine which one most accurately used the parameters of interest to predict the percentage of corals that would be bleached. A random forest regressor model with an R-squared value of 0.25 and a root mean squared error value of 7.91 was determined to be the best model for predicting coral bleaching. In the end, the random model had a 96% accuracy in predicting the percentage of corals that would be bleached. This prediction system can make it easier for researchers and conservationists to identify coral bleaching hotspots and properly allocate resources to prevent or mitigate bleaching events.
The effect of COVID-19 on the USA house market
Authors: Xiao William G , Gong Linying
Published: September 2023

The purpose of this study was to understand the varying effects of COVID-19 on the median house price in metropolitan areas in the USA. Recently, the demand for houses has increased due to the COVID-19 pandemic. The pandemic increased the desire to stay indoors and introduced working from home. Four different factors were tested for their impact on the housing market: number of COVID-19 deaths, number of available houses for sale, unemployment rate, and mortgage interest rates. The control in this study was 2018-2019 house price data. We hypothesized that the house supply would cause the greatest change in house prices. Ckmean clustering method was applied to separate 93 metropolitan areas of the USA into three groups with different median house price levels. We then conducted linear regression modeling for each group to determine the varying level of effect each of the variables had. The results suggested that unemployment rate had the largest correlation with house prices, especially for metropolitan areas with extremely high house prices. This result did not support the research hypothesis. Further research could clarify the findings of our study by using fine-turned modeling techniques and including more economic factors like immigration or tourism. Additionally, we can research the effect of COVID-19 on house prices globally.
Effect of hypervitaminosis A in regenerating planaria: A potential model for teratogenicity testing
Authors: Bennet Eva , Murphy Kristen , Bennet Amrith
Published: September 2023

According to the Centers for Disease Control and Prevention, a child with birth defects is born approximately every 4.5 minutes. The currently accepted method to determine the potential of new medicines and chemicals to cause birth defects (teratogenicity) involves testing in pregnant animals. Millions of mammalian animals are sacrificed annually for research, and scientists are searching for alternative models to reduce mammal use in research. This unique research study evaluated the potential use of the flatworm, brown planaria (Dugesia tigrine), as an alternative model for teratogenicity testing. There are similarities between mammalian embryonic development and regeneration of planaria during the early stages of development of the nervous system, including the eyes. In this study, we exposed amputated planaria to varying concentrations of a known teratogen, vitamin A (retinol), for approximately 2 weeks, and evaluated multiple parameters including the formation of blastema and eyes. Retinol delayed the formation of blastema and eyes in regenerating planaria in a concentration-dependent manner. At high concentrations of retinol, regenerating planaria also developed cyclopia, a well-known birth defect in humans, which has been linked to high levels of vitamin A in mammalian studies. The results from this study demonstrated that high concentrations of retinol caused defects in head and eye formation in regenerating planaria, with similarities to vitamin A related teratogenicity findings in mammals. Based on these results, regenerating brown planaria are a promising alternative model for teratogenicity testing, which can potentially be paradigm shifting as it can reduce cost, time, and pregnant animal use in research.
Linearity of piezoelectric response of electrospun polymer-based (PVDF) fibers with barium titanate nanoparticles
Authors: Nichitiu Marc D , Winston Stan
Published: September 2023

Piezoelectric sensors respond to applied force by generating voltage between their surfaces, measurable with contact electrodes. Flexible piezoelectric polymers with nanoparticles are novel materials allowing building wearable-textile sensors with applications including helping people better adapt to prosthetic devices or providing extra sensorial input. These materials can also be embedded into constructions, such as bridges or buildings, to continuously monitor their structural health. Moreover, when the sensors’ response varies linearly with their input, they can be mathematically modeled with linear systems of equations. These are much easier to solve or further adjust, as opposed to quadratic or higher degrees, exponential, or other functions. Here, we investigated whether flexible, polymer-based piezoelectric materials produced through electro-spinning a Polyvinyledene Fluoride (PVDF) solution containing a specific amount of BaTiO3 nanoparticles respond linearly to applied force by producing a corresponding voltage. We applied forces up to 3.4N on electrospun fibers and on the sides of electrospun meshes and measured the voltage along them. Our results revealed that the generated voltage depends piecewise-linearly with applied force. We carried out these measurements at 20 oC, 5 oC and 40 oC, and the resulting slope dependency demonstrated that the overall piecewise linear behavior was conserved. These results greatly increase the practical interest of such materials. They can be produced relatively easily, appear to be usable outdoors in a variety of climates and can be modeled with linear systems of equations, simplifying integration in complex devices. Our results show that more in-depth studies remain of interest.
Spectrophotometric comparison of 4-Nitrophenyl carbonates & carbamates as base-labile protecting groups
Authors: Kocalar Selin , Zhou Alice , Salahifar Aylin , Njoo Edward
Published: September 2023

In organic synthesis, protecting groups are derivatives of reactive functionalities that play a key role in ensuring chemoselectivity of chemical transformations. To protect alcohols and amines, acid-labile tert-butyloxycarbonyl protecting groups are often employed but are avoided when the substrate is acid-sensitive. Thus, orthogonal base-labile protecting groups have been in demand to enable selective deprotection and to preserve the reactivity of acid-sensitive substrates. To meet this demand, we present 4-nitrophenyl carbonates and carbamates as orthogonal base-labile protecting group strategies. These protecting groups are relatively stable in aqueous and acidic solution yet cleaved and irreversibly decarboxylated in mild basic conditions. We showed that deprotection can be monitored spectroscopically, as hydrolysis yields 4-nitrophenol, a bright yellow compound with an optical readout at 413 nm. Finally, we demonstrated that the use of 4-nitrophenol as an effective leaving group allows for deprotection to be carried out in mild conditions. We protected benzyl alcohol and benzylamine via acylation by 4-nitrophenyl chloroformate, yielding substrates that were subsequently subjected to hydrolysis in various pH conditions. The release of 4-nitrophenol was monitored spectroscopically and the reaction kinetics were derived from absorbance data, yielding that hydrolysis was accelerated only in basic conditions and was most effective in pH 12 and above. These results inform the feasibility of our protecting group in organic synthesis and open avenues toward new synthetic routes by broadening the spectrum of effective protecting group strategies.
Singlet oxygen production analysis of reduced berberine analogs via NMR spectroscopy
Authors: Su Sarah , Le Emma , Singh Pratyush , Sri Indran Karthikha , Pal Sohie , Regan Anika , Jain Meher , Shah Aashi , Njoo Edward
Published: September 2023

Berberine is a natural product isoquinoline alkaloid derived from plants of the genus Berberis. When exposed to photoirradiation, it produces singlet oxygen through photosensitization of triplet oxygen. The production of singlet oxygen grants Berberine its biological activity, as singlet oxygen forms an activated complex with DNA, oxidizing its guanine residues, halting cell replication and leading to cell death, which can be applied in photodynamic therapy of cancer. Through qNMR analysis of 1H NMR spectra gathered through kinetic experiments, we were able to track the generation of a product between singlet oxygen and alpha terpinene, allowing us to quantitatively measure the photosensitizing properties of our scaffolds. Moreover, we implemented 7,8-dihydroberberine and tetrahydroberberine, the reduced and over-reduced forms of berberine, respectively, in the studies to test the effect of the reduction of a compound on its singlet oxygen production.
Failure of colony growth in probiotic Lactobacillus casei Shirota as result of preservative sorbic acid
Authors: Raymond Mason D , Raymond III Charles
Published: September 2023

Preservatives have been a part of the food industry for years. Even before the days of bacterial pesticides and other antimicrobial technology, people used items like salt to prevent bacteria from growing. However, questionable claims on the negative effects of preservatives have been made, starting a new wave of “clean eating.” In this study, we tested the proficiency of different concentrations of the antimicrobial sorbic acid to inhibit the probiotic Lactobacillus casei Shirota. We hypothesized that sorbic acid’s use as a bacterial deterrent would also target this bacterial strain of Lactobacillus. We inoculated petri dishes in trials of 0%, 0.03%, and 0.1% sorbic acid concentrations and examined them over the 36-hour study. The results supported our hypothesis, with the colony count of L. casei Shirota having significant decreases at all concentrations of sorbic acid. These results additionally suggest that even under the FDA sorbic acid restrictions of 0.03% concentration, damaging effects could be seen in L. casei Shirota.
Blockchain databases: Encrypted for efficient and secure NoSQL key-store
Authors: Mehrota Ayushi , Kim David
Published: September 2023

Databases have revealed many vulnerabilities in which hackers can penetrate and gain access to the data. Blockchains have been proven useful to protect against fraud and data miners, exemplified in cryptocurrencies. In this paper, we propose a blockchain database framework as a non-relational database structure that integrates the properties of blockchains and databases. The independent variables when testing this database were the Append, Delete, Query, and Update functions in the database framework. We predicted that the Append, Query, and Update functions would have a logarithmic runtime and linear throughput; while the Delete function would have a constant runtime and throughput. The database was tested with about 150,000 operations with the server and client locally running. We observed the runtime was slightly positively correlated while the Delete was not positively correlated with the number of operations in the Append, Query, and Update functions. The throughput of the Append, Query, and Update functions were significantly negatively correlated with the number of operations. The blockchain database framework displayed end-to-end encryption and feasibility with this experiment. One possible application of the database framework is in the financial industry, as there is a one-to-one correspondence with user and transaction.
An analysis of the feasibility of SARIMAX-GARCH through load forecasting
Authors: Satheesh Anirudh , Sundararagan Sateesh
Published: September 2023

Load forecasting is critical for energy sector planners and generation companies to predict the level of energy that should be generated to maximize energy security. Accurate predictions of future energy consumption and supply capacity increase public confidence in energy sector planners, and help make informed decisions on power generation infrastructure to reduce capital costs. To forecast load, energy sector planners have used variations of the AutoRegressive Integrated Moving Average (ARIMA) model, such as Seasonal AutoRegressive Integrated Moving Average with eXogenous factors (SARIMAX). However, the accuracy of these models is limited due to heteroskedasticity, where the variance of data is not constant. Consequently, ARIMA can be combined with General AutoRegressive Conditional Heteroskedasticity (GARCH), a model that forecasts variance, in the SARIMAX-GARCH model. We hypothesized that SARIMAX-GARCH will be more accurate in predicting load than SARIMAX, a variant of ARIMA. We trained SARIMAX-GARCH and SARIMAX and selected the best models using Akaike Information Criterion (AIC) and Bayes Information Criterion (BIC), resulting in a Mean Absolute Percentage Error (MAPE) of 13.2% for SARIMAX and 11.0% for SARIMAX-GARCH. This shows that SARIMAX-GARCH is more accurate than SARIMAX for load forecasting data. The results indicate that SARIMAX-GARCH could potentially be improved through ensemble techniques and other exogenous variables. The results of our study will help energy sector planners and generation companies in forecasting energy consumption with more accurate predictions.
An accessible experiment to assess the impact of shapes of buildings and roofs on wind resistance
Authors: Tao Lee , Wu Wei
Published: September 2023

Hurricanes cause extensive amounts of damage in coastal communities each year. Rebuilding is costly, and the impact of hurricanes can be alleviated by mitigating the destruction to buildings. As such, buildings that are resistant to high winds are the key to increasing the resilience of communities to hurricanes. Here, we designed an accessible experiment to evaluate the effects of house and roof shape on wind resistance. We built four types of house models: box-shaped houses with pyramid hip roofs, box-shaped houses with flat roofs, round houses with pyramid hip roofs, and round houses with flat roofs. To evaluate the stability of these house models, we applied strong winds using a leaf blower. We determined stability by measuring the distance between the leaf blower and the house models when they were blown away, and the time it took for the houses to be blown away if the distance was 0 cm. The smaller the distance and the longer the time, the more resistant the houses are to strong winds. We found round houses were more resistant to strong winds than box-shaped houses, and houses with pyramid hip roofs were more resistant to strong winds than houses with flat roofs if other attributes of the houses were kept the same. Furthermore, we found roof shape was more important than house shape among the different combinations of house shapes and roof shapes we studied. Our study provides scientific data to facilitate policy making in improving coastal resilience, particularly through updating building codes that account for house and roof shape.
The effects of Helianthus Annuus on Amyotrophic Lateral Sclerosis using Drosophila Melanogaster
Authors: Srinivasan Shridhula , Srinivasan Mridula , Fallon Renne
Published: September 2023

Amyotrophic lateral sclerosis (ALS) affects nearly 200,000 people worldwide. The main cause of ALS is unknown as 90% of people diagnosed do not have genetic mutations or a family history of ALS. Currently, there is no cure for patients with ALS, and doctors recommend that patients do physical therapy to retain muscle strength and control. The purpose of the study was to determine if Helianthus annuus seeds helped reduce nerve degeneration and increase locomotion. H. annuus, also known as the sunflower, has antioxidant properties which can help to protect the nerves. H. annuus is also rich in magnesium, which helps regulate muscle and nerve conduction. In this experiment, we used Drosophila melanogaster as the model organism. We hypothesized that incorporating H. annuus into the diet of D. melanogaster would decrease nerve degeneration, leading to an increase in locomotion and a decrease in the disorderliness of the ommatidia in the eye. Through this experiment, we found a general trend suggesting that H. annuus helped increase the mobility of the D. melanogaster. Thus, with further experimentation, H. annuus could become a viable supplement for patients with ALS to help with the control of muscles and prevent the progression of the disease.
Comparing the performance of lateral control algorithms on long rigid vehicles in urban environments
Authors: Boyarov Artyom , Shannon Eoin
Published: September 2023

Existing research on autonomous vehicle control is largely focused on how control algorithms perform on cars; long vehicles or buses have not been significantly investigated. Existing studies indicate that people display positive attitudes to using autonomous buses, indicating the value of researching control algorithms for autonomous buses. To provide insight on the performance of control algorithms on autonomous buses, we compared multiple lateral control algorithms on how well they maneuver a long vehicle around three courses resembling urban environments. We compared the Stanley and pure pursuit control algorithms and two new control algorithms which were improved versions of the Stanley and pure pursuit controllers. We compared the control algorithms in a kinematic simulation which recorded the steering angle and cross track error from the front axle for each controller driving the vehicle at 50 km/h around the course. We hypothesized that the Stanley control algorithm would perform the best due to its success in navigating existing vehicles. The Stanley control algorithm had a low cross track error, but it had a large steering angle and large changes in steering angle. The pure pursuit controller had smoother changes in steering angle, but the cross track error was larger than the Stanley controller. Our results suggest that none of the algorithms we tested were optimal, and that an algorithm which can utilize the ability of the Stanley controller to maintain a low cross track error while also keeping a low steering angle change will perform the best for long vehicles.
Deciphering correlation and causation in risk factors for heart disease with Mendelian randomization
Authors: Singh Aryamann , Akbari Parsa
Published: September 2023

In this analysis, we studied the use of Mendelian randomization to identify the risk factors of coronary artery disease (CAD), a major cause of cardiovascular disease. Identifying risk factors of CAD are critical to understanding and managing the disease. Our analysis combined results from 28 genetic analyses from 12 unique studies. For each genetic variation, we obtained the variant ID, chromosome, base-pair position, reference and alternative alleles of the genetic variation, and estimated effect and p-value of the genetic variation on the outcome. We hypothesized that traits which are correlated with CAD outcomes will be causally associated with CAD risk in a genetic Mendelian randomization analysis. Our analysis showed that several traits such as blood pressure readings (systolic, OR 0.51 (95% CI: 0.34-0.69), p-value = 5.4x10-9) and (diastolic, OR 0.56 (95% CI: 0.41-0.71), p-value = 7.6x10-14), LDL cholesterol levels (OR 0.54 (95% CI: 0.47-0.60), p-value = 4.4x10-56), and BMI (OR 0.41 (95% I: 0.35-0.48), p-value = 6.30x10-33) were significant risk factors for CAD. C-reactive protein (OR -0.09 (95% CI: -0.18–0.00), p-value = 0.05) was a protective risk factor of CAD due to its negative odds ratio. In contrast, eosinophil count (OR -0.007 (95% CI: -0.06-0.04), p-value = 0.79) had no statistically significant association. Blood cells had weak associations with CAD, and uric acid’s role as a causal or reversible risk factor of CAD was inconclusive, requiring further study.
The velocity of white dwarf stars relates to their magnitude
Authors: Glazer Jai , Joiner Jessica
Published: September 2023

The relationship between the velocity of a white dwarf star and its absolute magnitude is unknown, posing unresolved questions about what characteristics a fast-moving white dwarf has compared to its slower counterparts. Using the European Space Agency’s Gaia dataset, we analyzed the relationship between white dwarfs’ magnitudes and proper motions. We hypothesized that older white dwarf stars may have different velocities than younger ones, possibly that stars slow down as they age. After filtering down the Gaia dataset to a set of roughly 65,000 white dwarfs, we selected the ones that had the highest proper motions. When we further filtered the high proper motion dataset to not include white dwarfs with outlier parallaxes, we were left with a dataset that was theoretically the fastest white dwarf stars in the Gaia dataset. Comparing these fast white dwarfs to the candidate dataset, we found that the white dwarfs in our filtered dataset were substantially redder and higher magnitude (traits traditionally associated with older stars) as compared to their non-fast counterparts.
Analysis of ultraviolet light as a bactericide of gram-negative bacteria in Cladophora macroalgae extracts
Authors: Newell Leisya , Rasmus Joseph
Published: September 2023

In recent years, antibiotic resistance has increased in pathogenic bacteria, posing a growing threat to both patients and the pharmaceutical industry. This has resulted in inflated medical expenses and higher mortality rates for individuals diagnosed with bacterial infections. A potential alternative to synthetic medications involves the use of marine algae as natural antibacterial agents. Prior research suggests that the Cladophora macroalgae genus may be one option, as it has high polyphenolic content that has previously exhibited antibacterial properties. However, obtaining organic samples from bacteria-ridden environments poses complications concerning microbial contamination of medicinal plants. During initial trials of antibacterial testing, the Cladophora algae extract was found to be greatly contaminated with gram-negative bacteria. The study was then adapted to explore ultraviolet (UV) light as a possible bactericide of this microbial growth. The experiment utilized a control with no UV light treatment along with four experimental samples exposed to UV light for durations of 15, 30, 45, and 60 minutes. We found that there was a statistically significant difference between the control mean and the means of the 30, 45, and 60-minute treatment groups. The overall data trend displays a negative correlation between the ZOF diameter and UV exposure time, supporting the hypothesis that longer durations of UV light treatment have a greater degree of antibacterial effectiveness.
Analysis of biofertilization impacts on Pisum sativum
Authors: Holden Isabelle , Rasmus Joeseph
Published: September 2023

Nutrient degradation in soil is becoming a prominent agricultural issue due to widespread unsustainable farming practices such as overgrazing and over-cultivation. As agriculture is such an integral aspect of society, developing methods to increase crop yield is imperative for feeding the future generations of humankind. The United States spends billions of dollars each year to combat nutrient loss in soil, but soil productivity and crop yields are still decreasing. In this study, we explored the various effects of three different produce-based biofertilizers on pea plant growth, using red apple, pear, strawberry, and control treatments. To apply the fruit biomatter, we peeled, powdered, and mixed the fruit with distilled water to form a solution. We watered the pea plants, Pisum sativum, with the different solutions for the duration of the 18-week experiment. We hypothesized that the application of fruit biomatter would increase the growth of pea plants, with the application of strawberry biomatter having the most significant effect due to strawberries containing a higher nutrient content compared to pears and apples. Upon analysis, we observed that the fruit biomatter with strawberry peels significantly increased the growth of the pea plants, while the application of red apple biomatter and pear peel biomatter had no significant effect. The application of strawberry biomatter could prove to be an effective way to increase plant growth in commercial agriculture. Further research is needed to determine if the application of apple and pear biofertilizers increases the plant growth of Pisum sativum.
Cell cytotoxicity and pro-apoptosis on MCF-7 cells using polyherbal formulation, MAT20
Authors: Tarigopula Sohan , Narayan Aadi , Vijaykumar Kasture Pooja , N V Bhavana , Rao Jyothsna , Rao Gururaj
Published: September 2023

Today, standard of care cancer treatment includes chemotherapy, radiation, and surgery, which have serious side effects. A different option for medication could be using standard of care treatments in conjunction with herbal adjuvants. This integrated approach reduces the dosage, and the side effects of chemotherapy could lead to a better prognosis. The purpose of this study was to test the anti-cancer properties and pro-apoptotic effects of the polyherbal formulation MAT20 as a complementary treatment. Moringa oleifera (Moringa), Phyllanthus emblica (Amla) and Ocimum sanctum (Tulsi), these 3 herbs were used to formulate MAT20, which contain phytochemicals that are known to display anti-cancer properties. In this study, we hypothesized that MCF-7 breast cancer cells treated with MAT20 would show increased cytotoxicity compared to its individual plant extracts. MAT20 showed significantly lower IC50 values were found for both 24-hour (33.01µg/mL) and 48-hour (21.09 µg/mL) exposure compared to any of the other individual extracts for the given exposure duration. MAT20 did not show a significantly lower IC50 value compared to the chemotherapeutic drug Paclitaxel. Additionally, staining methods (DAPI, Hoechst, Dual staining) showed that MAT20 treated cells caused 49.6% cell death after 24 hours and 51% cell death after 48 hours of exposure, indicating successful drug activity in inducing apoptosis.
Association between nonpharmacological interventions and dementia: A retrospective cohort study
Authors: Yerabandi Nitya , Zhu Shannon , Cersonsky Tess EK
Published: September 2023

One of the most common forms of dementia is Alzheimer’s Disease (AD), a neurodegenerative disease in which amyloid plaques and neurofibrillary tangles accumulate within the brain, disrupting neuronal function. This commonly results in changes to one’s cognition, mood, and behavior. Nonpharmacological interventions, such as cognitive training, physical exercise, reminiscence, music, muscle relaxation, support groups, therapeutic writing, and discussions, have been studied as preventative measures that may delay cognitive impairment in individuals with or without dementia. In this study, we investigated the correlation between physical activity (e.g., sports, recreational activities, traveling), socialization (e.g., family gatherings, clubs/organizations, volunteer work), intellectual stimulation (e.g., occupation, education, reading), and the presence of dementia. We hypothesized that individuals without cognitive impairment would participate in these activities more throughout their lives compared to those with cognitive impairment. This is a retrospective case-control study in which 22 participants from two senior centers in San Diego were interviewed about their lifestyle history. The results of this study showed that there were no statistically significant differences in self-reported activities between individuals with and without dementia. While we intended to measure subject participation in physical, social, and intellectual activities, the results reflected activity recall rather than the activity itself. This points to the need for further research on the deficits in activity recall in individuals with cognitive impairment.
Elevated levels of IL-8, TGF-β, and TNF-α associated with pneumoconiosis: A meta-analysis
Authors: Chen Shenghong , Syed Ali Alamdar Sher
Published: September 2023

There have been multiple studies over the years looking into the role of cytokines, which are regulators of inflammation in the development of pneumoconiosis. The aim of this study to determine whether serum levels of certain cytokines can be useful as biomarkers for pneumoconiosis. To date, the most investigated cytokines have been Interleukin 8 (IL-8), transforming growth factor beta 1 (TGF-β1), and tumor necrosis factor alpha (TNF-α). Results from previous studies generally show that the serum levels of these cytokines are altered in pneumoconiosis, however not all of these deviations are statistically significant. Here we attempt to determine whether levels of IL-8, TGF-β1, and TNF-α are significantly related to pneumoconiosis, by conducting a meta-analysis of 11 studies on the serum levels of three cytokines: IL-8, TGF-β1, and TNF-α. The meta-analysis concluded that pneumoconiosis patients display significantly elevated levels of IL-8 and TNF-α. The meta-analysis for serum TGF-β1 in pneumoconiosis patients failed to reach statistical significance. The results of the meta-analysis suggest that serum levels of IL-8 and TNF-α could be utilized in the diagnosis of pneumoconiosis, and further studies should be conducted to investigate the correlation strength of these two cytokines with pneumoconiosis.
Evaluating machine learning algorithms to classify forest tree species through satellite imagery
Authors: Gupta Neiv , Li Wen Jeff
Published: September 2023

Recent events indicate an uptick in forest fires in the western United States, prompting cities and organizations to develop a better understanding of forests and how to manage them. Tree species classification is important for forest management and carbon sequestration analysis. Currently, remote sensing stands as the prevalent method for the classification of tree species, land cover, etc. Researchers often use machine learning techniques for classification and general remote sensing. We hypothesized that it is possible to classify forest tree species with high classification accuracy using solely RGB values as the inputs for the machine learning models. We experimented with different machine learning algorithms such as Random Forest (RF), k-Nearest Neighbors (kNN), Gradient Boosting (GB), and Linear Discriminant Analysis (LDA) to classify forest tree species, specifically through multispectral Landsat 8 satellite imagery. Each algorithm was trained and validated using the same dataset and satellite imagery of the same region. Our findings indicated RF had the highest classification accuracy of 95.4% for validation on the same general region it trained on. kNN, GB, and LDA had classification accuracies of 81.6%, 76.4%, and 64.6%, respectively. Based on these results, we concluded that RF is the more accurate algorithm for classifying tree species through RGB satellite imagery. Our findings also indicate that model training and inference on the same general region result in higher classification accuracy. However, as the inference region changes, the classification accuracy reduces. In such cases, additional predictor variables, including trunk diameter, crown shape, and vegetation indices, could be introduced to improve classification accuracy.
Toxicity of aminomethylphosphonic acid via the Wnt signaling pathway as a novel mechanism
Authors: Zhuang Richard , Spinelli Nicole
Published: September 2023

Glyphosate is one of the most ubiquitous herbicides in the world due to its effective plant removal. However, even though glyphosate and its main metabolite, aminomethylphosphonic acid (AMPA), contaminate the environment and pose threats to humans, their mechanism of toxicity is not well-elucidated. One possible mechanism of action is through the canonical Wnt pathway. This pathway regulates many cellular processes, such as cell fate determination and organogenesis, but its dysfunction can result in cancer. The goal of this study was to assess the toxicity of AMPA and elucidate its effects on Wnt signaling by using planarian regeneration models and molecular docking simulations. To evaluate the toxicity of AMPA, planaria were exposed to environmental concentrations of AMPA and they generally exhibited significantly reduced locomotion, delayed regeneration, and smaller blastema areas. AMPA displayed comparable toxicity to glyphosate and was harmful at low concentrations. To probe the mechanism of action of AMPA and glyphosate, we conducted in silico molecular docking in PyRx to predict its binding to canonical Wnt targets. Both AMPA and glyphosate had moderate simulated binding affinities for proteins in the Wnt pathway, with glyphosate exhibiting stronger affinities than those of AMPA. According to our molecular docking results, AMPA may be capable of binding to Wnt targets. However, it is unclear whether AMPA inhibited or activated Wnt proteins, so it cannot be ascertained that AMPA is definitively carcinogenic. Regardless, AMPA was toxic to planaria, and herbicide application should be more closely regulated to avoid environmental deposition of glyphosate and AMPA.
In vitro characterization of umilical cord-dervied MSC's supplemented with PLAY®:A potential FBS substitute
Authors: Lakkhundi Vedant , Thomas Teena Mary , Sreenivas Archana , Pramod Mercy Jennis , Prasad Shambhavi , Rao Jyothsna , Rao Gururaj
Published: September 2023

Recent interest in the wound healing and regenerative properties of mesenchymal stem cells (MSCs) has prompted further investigation to elucidate their regenerative properties. Characterized by their ability to differentiate into various cell lineages, such as osteocytes, chondrocytes, and adipocytes, alongside promoting local angiogenesis and chemotaxis at the wound site, MSCs have proven to reduce the stipulated healing time. The myriad sources they originate from, including bone marrow and umbilical cord, underscore their wide range of clinical applicability. Extending the time for MSC senescence by using alternative media in a manner that preserves their stem-cell-like nature may be a viable option of achieving optimum cell numbers required for clinical protocols. Furthermore, various culture conditions have varied effects on MSCs, therefore, standardizing MSC growth conditions may help to produce MSCs with verified potency, which could be then extrapolated to clinical conditions. The presence of potential contaminants within commonly used cell culture media such as fetal bovine serum (FBS) curbs the scope of MSC implementation in tissue regeneration. Our current study aimed to continue to investigate the effects of blood derivative PLAY® on trends in MSC culture across various experimental parameters in comparison to FBS. Our results demonstrated that PLAY® consistently outperformed FBS across all the experimental metrics studied.
Rhythmic lyrics translation: Customizing a pre-trained language model using stacked fine-tuning
Authors: Chong Jiwon , Chong Jaehyok
Published: September 2023

Neural machine translation (NMT) is a software that uses neural network techniques to translate text from one language to another. As NMT models are on the rise, the focus is on translating everyday mundane sentences. However, it is also necessary to start paying attention to the translation of domain-specific text, such as lyrics or poetry. For example, even one of the most famous NMT models—Google Translate—failed to give an accurate English translation of a famous Korean nursery rhyme, "Airplane" (비행기). To teach the model to retain specific information other than semantics, we need specific data which contains the exact information that we are attempting to teach. In the case of rhythmically accurate lyrics translation—translated lyrics that can be used to sing along to the original melody—we need corresponding data, containing lyrical and rhythmical properties, all the while being semantically accurate. However, as there is not enough data that fits our criteria, we propose a novel method we call 'stacked fine-tuning'. We fine-tuned a pre-trained model first with a dataset from the lyrics domain, and then with a smaller dataset containing the rhythmical properties, to teach the model to translate rhythmically accurate lyrics. To evaluate the effectiveness of our approach, we translated two famous Korean nursery rhymes to English and matched them to the original melody. Our stacked fine-tuning method resulted in an NMT model that could maintain the rhythmical characteristics of lyrics during translation while single fine-tuned models failed to do so.
Reduce the harm of acid rain to plants by producing nitrogen fertilizer through neutralization
Authors: Xu Feier , Pfund Steve
Published: September 2023

The phenomenon of dying trees and plants in areas affected by acid rain has become increasingly problematic in recent times. Is there any method to efficiently utilize the rainwater and reduce the harmfulness of acid rain or make it beneficial to plants? This study aimed to investigate the potential of neutralizing acid rainwater infiltrating the soil to increase soil pH, produce beneficial salts for plants, and support better plant growth. To test this hypothesis, precipitation samples were collected from six states in the U.S. in 2022, and the pH of the acid rain was measured to obtain a representative pH value for the country. Experiments were then conducted to simulate the neutralization of acid rain and the subsequent change in soil pH levels. To evaluate the effectiveness and feasibility of this method, cat grass was planted in pots of soil soaked with solutions mimicking acid rain, with control and experimental groups receiving neutralizing agents (ammonium hydroxide) or not. Plant growth was measured by analyzing the height of the plants. Results demonstrated that neutralizing agents were effective in improving soil pH levels and that the resulting salts produced were beneficial to the growth of the grass. The findings suggest that this method could be applied on a larger agricultural scale to reduce the harmful effects of acid rain and increase agricultural efficiency.
Analyzing resilience in a sample population as a novel qualifier for triage in psychological first aid
Authors: Ramesh Ranjana , LaBrie Jessica
Published: September 2023

The human capability to adapt in response to disaster is remarkable. Psychological first aid (PFA) is a method to preserve and nurture resilience after a disaster or traumatic experience and is a comparable first response strategy to medical first aid. Contrary to medical first aid, however, studies suggest that Rapport/Reflective listening, Assessment, Prioritization, Intervention, and Disposition-based PFA, or RAPID-PFA, the most prominent method of PFA today, does not utilize a system of triage, where degrees of urgency are assigned to victims during care. Understanding whether different people experience resilience differently is necessary in understanding whether triage could benefit PFA’s application in the field. Using data from 281 participants, we calculated resilience using a novel quantitative method of resilience analysis: a formula-based resilience index. We hypothesized that 1) younger individuals would be less resilient than older ones, 2) women would be more resilient than men, and 3) individuals of different races would be equally resilient. Our results showed that, while race did not affect resilience, people of different ages and different legal sexes do exhibit different levels of resilience. Children and adolescents scored lowest of all age subcategories and – contrary to our hypothesis - women scored lower on the resilience index than men. These findings suggest that age and sex may act as predictors of vulnerability for use in PFA triage. To supplement these findings before applications in the field, we should conduct further longitudinal studies with larger sample populations using the same methodology.
Modeling the heart’s reaction to narrow blood vessels
Authors: Athulathmudali Yasmin , Araujo Fernanda
Published: September 2023

Cardiovascular diseases are the largest cause of death globally, making it a critical area of focus. The circulatory system is required to make the heart function. One component of this system is blood vessels, which is the focus of our study. Whether due to low temperatures or a medical condition, blood vessels can constrict, occasionally to a dangerous degree. Despite the serious consequences narrow blood vessels can have on one’s body, due to their complexity and size, there is little information pertaining to how their constriction relates to the heart’s ability to pump blood. Therefore, our work aims to demonstrate the numeric relationship between a blood vessel's diameter and the number of pumps needed to transport blood. We explored this concept using a water bottle model to represent the heart, and straws of varying diameters to represent the blood vessels. The experiment recorded the number of pumps necessary to transport 200 mL of red-dyed water to a second bottle using straws. We hypothesized that the number of pumps would increase as the diameter decreased, and that there would be a linear relationship between these variables. The data supported the numeric relationship we hypothesized, in which the largest diameter straw, 1 cm, required the least pumps and the smallest diameter, 0.4 cm, required the most. Our results depict how the heart must overcompensate to transport blood through narrow vessels, providing a better understanding of how the heart behaves when vessels constrict.