| 1 |
Author(s):
Sri Sahasra Bikumala.
Page No : 1-6
|
The Fundamental Role of Dietary Habit, Physical Activity, and Sleep Pattern on Amyloid-Beta and Tau Pathology.
Abstract
Alzheimer’s disease (AD) is a debilitating neurodegenerative disease that affects an estimated 24 million adults over the age of 65 worldwide, with symptoms including memory loss, cognitive decline, and behavioral changes. Currently, there is no cure, although there is a 100% mortality rate once the disease has progressed. Age is the most significant risk factor for developing AD; however, diet, physical activity, and disrupted sleep patterns contribute to disease progression. An improper diet in particular can contribute to inflammation and increase reactive oxygen species leading to AD progression. Physical activity has many benefits on overall health but has a unique positive impact on AD through improved cognitive outcomes. Sleep disturbances are regularly reported by AD patients. There is now evidence to support sleep disruption as an early marker of AD while also significantly contributing to the progression of AD. Improving diet, physical activity, and sleep patterns may have positive outcomes for AD patients and reduce the burden on their families and caretakers, promoting a healthier family environment. In this review, we will explore how diet, physical activity, and sleep patterns contribute to AD progression and highlight how changes in these areas can improve the quality of life of AD patients.
| 2 |
Author(s):
Pranav Kalidindi.
Page No : 7-16
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The Effects of Stress on Alzheimer’s Disease Development and Progression
Abstract
Alzheimer’s disease is a progressive neurodegenerative disorder that profoundly impacts patients’ memory, cognition, and overall quality of life. Chronic stress is a substantial contributor to Alzheimer's patients' cognitive deterioration. The effects of stress on hippocampus function and dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis can lead to higher cortisol levels and is the link between stress and memory dysregulations. Moreover, acute and chronic stress have been linked to increased production of Amyloid Beta plaques and Tau Tangles, the primary pathological hallmarks of Alzheimer’s disease. As a result, the cellular mechanisms of memory consolidation and storage are disrupted. This paper reviews ongoing research of how cellular, network and endocrine pathways in the brain are impeded by stress and links these findings to Alzheimer’s disease development and progression. Understanding the interplay between stress and the progression of Alzheimer’s disease can play a significant role in further development of research, disease-modifying treatments, and potential cures.
| 3 |
Author(s):
Sakhi Lal.
Page No : 17-24
|
The Role Of Cross-Sector Collaboration In Reducing Racial And Social Disparities In Healthcare
Abstract
Despite the presence of a robust healthcare system, racial disparity and social inequalities
remain prevalent in the United States. These disparities in healthcare are persistent challenges,
disproportionately affecting marginalized communities and contributing to unequal health outcomes.
This study investigates the role of cross-sector collaboration among healthcare providers, public health
agencies, community-based organizations, and policy makers in mitigating these disparities. Using a
mixed-methods approach that includes case studies, stakeholder interviews, and data analysis from
collaborative health initiatives across five urban regions, the research identifies key drivers of success
in cross-sector partnerships. Findings highlight the importance of community engagement, shared data
systems, culturally competent care models, and sustained funding in reducing barriers to access and
improving health equity. The study concludes that cross-sector collaboration is not only essential but also
highly effective in addressing the root causes of health disparities, and it offers policy recommendations
to support the development and scalability of such partnerships nationwide.
| 4 |
Author(s):
Srihari Subramanian.
Page No : 25-33
|
A Neural Network Model in Identifying Non-Small-Cell Lung Cancer through CT Scans
Abstract
Lung cancer is the leading cause of cancer-related deaths worldwide, causing approximately 1.8
million deaths in 2022 alone. Lung cancer is often detected through the use of Low-Dose Computed
Tomography (LDCT) scans, which use small amounts of radiation to construct detailed pictures
of regions in the body. This study aims to explore the ability of Artificial Intelligence,
particularly Convolutional Neural Networks (CNNs), to detect lung cancer from CT scans. Using an
online dataset consisting of 1000 images, a CNN was developed with ResNet50 as the base model
used for feature extraction. The model achieved a validation accuracy of 98.78% and a testing
accuracy of 97.53%. This showcases the proficiency of the model in detecting lung cancer.
However, this was only when a binary classification system was implemented, where the model was
made to simply determine the presence of cancer. The model faced great difficulty in distinguishing
between the types of lung cancer: Adenocarcinoma, Squamous Cell Carcinoma, and Large Cell
Carcinoma. Additionally, the presence of a small number of false negatives while testing shows the
danger of relying on AI and demonstrates the necessity of further fine-tuning before practical use.
| 5 |
Author(s):
Pak Heng Kirklan Pong.
Page No : 34-40
|
Exploring The Neurocognitive Effects Of Magic Intervention On Mild Cognitive Impairment And Alzheimer’s Disease
Abstract
Magic, the art of conjuring, has fascinated people around the world for millennia. Magicians have
mastered manipulating attention (misdirection) and exploiting the human mind to create seemingly
impossible tricks and illusions. In the past few decades, neuroscientists and psychologists have researched
the methods of magic and produced a significant amount of literature relating to how magicians
manipulate people. With this surge of new knowledge, it is worthwhile to investigate whether magic
can be used in treatments for mental disorders and diseases. Mild Cognitive Impairment (MCI) and
Alzheimer’s Disease (AD) are two of the most common neurological conditions among elderly, where
behavioral interventions are crucial for slowing down the progression of neurocognitive impairment.
This paper analyses and proposes how magic intervention can impact neurocognitive function in patients
with MCI or AD, by reviewing current literature in the related areas of magic and the science behind
it. In particular, it is found that magic intervention can positively affect executive functioning, learning,
and memory in individuals with MCI and AD. Furthermore, emerging areas of research in the field
indicate that magic intervention may promote curiosity and engage sensory systems, further improving
neurocognitive function in these individuals. Therefore, the paper shows that magic intervention is
effective in enhancing neurocognitive function in patients with MCI and AD, and in slowing down the
progression from MCI to AD.
| 6 |
Author(s):
Katherine E. Frost .
Page No : 41-50
|
Underlying Similarities Between Psychedelic and Schizophrenia Hallucinations
Abstract
Though distinctly different in their effects, hallucinations occurring from schizophrenia (SCZ)
symptoms and psychedelic drug action can appear similar. To investigate how different mechanisms
underlie these effects, this paper highlights similarities at the molecular and anatomical network level
and identifies potential new therapeutic applications and directions for research. This paper explores
the 1950s-1960s studies involving schizophrenic patients, hallucinogenic drugs, and their historical
significance. Next, the paper dives into overlaps between schizophrenic and psychedelic hallucinations–
from molecular to cellular levels. The paper’s overlaps section starts with Neuroplasticity overlaps
between SCZ and Psychedelics; then is followed by the cortico-striatal-thalamo-cortical (CSTC) theory
in psychedelics and schizophrenia’s hallucinations; serotonin (5-HT) mediated hallucinations and
psychotic effects; triple network disconnectivity in psychopathology and schizophrenia pathology; and
finally, synaptic disconnections role in neuropharmacology of hallucinations seen by computational
modeling. The paper includes a final section of how the drug, nicotine, impacts SCZ patients. This paper
aims to clarify the neuropharmacological overlap between these phenomena to call for further research
in developing targeted treatments.
| 7 |
Author(s):
Maggie Liu.
Page No : 51-59
|
Classifying Classical Music Genres with Neural Networks
Abstract
Current neural network models can process and interpret music for tasks such as melody completion and genre or style classification. However, previous classification tasks do not account specifically for distinct composition styles of different classical music periods, often focusing instead on modern genres. To bridge this gap, this project investigates the use of natural language processing techniques to classify musical excerpts from the Baroque, Classical, and Romantic periods. A curated dataset of samples representative of the three eras, converted to the OctupleMIDI format, was used to train a Sentence Transformers model to complete the classification task with maximum accuracy—62.5% when trained on all three categories and 90.5% when the Classical and Romantic labels were merged. These results indicate that the model was most effective at distinguishing Baroque music, suggesting clearer stylistic separation. These findings demonstrate the feasibility of using sentence-level embeddings for symbolic music classification, offering potential applications in musicological analysis, genre tagging for recommendation systems, and quantitative exploration of musical style beyond human perception.
| 8 |
Author(s):
Saba Brockhagen.
Page No : 60-65
|
Impact of Recreational Substance Use On the Adolescent Brain
Abstract
Adolescence is a critical stage of brain development marked by rapid maturation of the prefrontal
cortex and hippocampus, regions of the brain responsible for memory, decision-making, and emotional
regulation. During this period of heightened neuroplasticity, the brain is especially sensitive to
environmental influences, including the use of substances like alcohol, marijuana, and nicotine. This
literature review examines how each of these substances disrupts brain development and impairs
cognitive function. Alcohol use interferes with synaptic pruning and myelination in the prefrontal cortex,
leading to poor impulse control and decision-making. It also causes hippocampal damage, including
inflammation and volume loss, which impairs memory encoding and learning. Marijuana’s active
compound, THC, disrupts cannabinoid receptor function in the hippocampus, reducing neuroplasticity
and leading to structural shrinkage and long-term memory deficits. Marijuana also thins the prefrontal
cortex, delaying cognitive control development. Nicotine overstimulates acetylcholine receptors,
hindering normal pruning and reducing gray matter volume, especially in the prefrontal cortex and
hippocampus. This contributes to attention problems, increased impulsivity, and impaired working
memory. Neuroimaging studies consistently show functional and structural differences in adolescents
who use these substances compared to non-users. These changes may persist even after substance use
stops, increasing the risk of long-term cognitive challenges and future substance use disorders. Early
prevention and intervention efforts, such as school-based education and promotion of healthy habits, are
essential to reduce adolescent substance use and protect brain development. This review highlights the
urgent need for continued research and public health strategies to address the risks associated with early
exposure to alcohol, marijuana, and nicotine.
| 9 |
Author(s):
Jonathan Yang.
Page No : 66-71
|
Recent Advances In Carbon Nanotube Devices For The Application In Food Allergen Detection
Abstract
Carbon nanotubes are cylindrical shaped structures comprising single or multi layers of graphene
sheets which have distinct characteristics of high conductivity, high flexibility, and high stability across
a range of scenarios. These carbon nanotube properties provide distinct sensitivity and surface area to
manufacture extremely efficient biosensors. Carbon nanotube biosensors detect low concentrations of a
target analyte with the aid of specific antibodies or biomolecules immobilized on the carbon nanotube
surface, allowing for rapid and accurate diagnostic results. Carbon nanotube-based biosensors have
been studied to detect allergens due to the rapid and accurate results provided for identifying allergenic
substances in many contexts, including food safety and prevention of subject exposure to allergenic
substances, which could potentially trigger allergic reactions. This review will focus on the applications
of carbon nanotubes in the development of sensitive biosensors for peanut, wheat, lysozyme, and kidney
bean allergens, and will summarize the performance of each biosensor as well as their limitations and
promising future applications of carbon nanotubes for allergen detection.
| 10 |
Author(s):
Zilu Wang.
Page No : 72-80
|
Factors Affecting Global Video Game Sales Rankings: Analyzing the Impact of Platform, Genre, and Market Regions
Abstract
This study investigates the determinants of global video game sales rankings by examining platform types, game genres, and regional market characteristics. Using a comprehensive dataset of 16,598 entries sourced from VGChartz via Kaggle, this research employs a hybrid methodological framework combining machine learning and traditional statistical approaches. Specifically, correlation analysis, multiple linear regression, binary logit regression, and binary probit modeling are utilized. The study aims to identify the significant predictors of video game sales performance across global markets and to understand the interactions among these predictors. Results show that platform and genre are consistently influential variables, with regional market sales playing a secondary but still impactful role. The findings offer valuable implications for developers, marketers, and stakeholders seeking data-driven strategies in the video game industry.
| 11 |
Author(s):
Rishav Dutt.
Page No : 81-88
|
Exploring Quantum Dot Materials And Synthesis Methods: Current Trends And Future Prospects
Abstract
Quantum dots (QDs) have numerous applications in the fields of optoelectronics and quantum
physics. Their emission wavelengths can be tuned based on size, they have high quantum yields and
excellent photostability. These characteristics offer advantages over previous-generation materials such
as organic dyes. Unfortunately, QD synthesis requires extensive precision and relies on processes that
are difficult to replicate on industrial scales. This review summarizes the different materials and methods
of QD synthesis in order to examine their current limitations and potential areas of improvement. It
also emphasizes potential routes to improve the scalability of existing synthesis processes. As demand
for QDs in optical applications continues to grow, an understanding of their manufacturing will be
necessary to enable their continued development.
